229442	DRR084021	DRP003418	DRS039912	DRX077852	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 paired end sequencing of SAMD00048521			Mili WT RNA-seq replicate 1	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired	101			Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		202	SAMD00048521	mouse ovary small RNA-seq	5911418294	29264447	2017-01-27 00:37:12	3656091426	5911418294	29264447	2	29264447	index:0,count:29264447,average:101,stdev:0|index:1,count:29264447,average:101,stdev:0	DRR084021	KYUSH-MIB			in_mesa	28115634	18.78	2.86	0.04	4423371500	4296430631	4018571872	3926399897	97.13	97.71	27989869	26755267	177.617	523.587	139	263764	68.8	75.97	32541041	19255636	32541041	19255636	73.08	73.01	32541041	20453830	32541041	18506099	908441386	20.54	1.16	0	9.03	0	0.68	0	0.50	0	0.00	0	3.18	0	27989869	0	202	0	200.84	0	1.44	0	0.00	0	1.24	0	0.00	0	104.83	0	0.12	0	338997	0	29264447	0	2643163	0	197717	0	147322	0	0	0	929539	0	4918	0	0	0	57071	0	6897174	0	14764	0	6973927	0	86.61	0	25346706	0	210585	6142258	29.167595032885	29264447.0	27989869.0	338997.0	2643163.0	197717.0	147322.0	0.0	929539.0	25346706.0	95.6	1.2	9.0	0.7	0.5	0.0	3.2	86.6	101	101	101.00	38	2955709147	25.2	22.0	22.9	29.8	0.0	36.7	23.2	bulk
229444	DRR084022	DRP003418	DRS039912	DRX077853	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 paired end sequencing of SAMD00048521			Mili WT RNA-seq replicate 2	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired	101			Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		202	SAMD00048521	mouse ovary small RNA-seq	2576722706	12756053	2017-01-27 00:37:12	2154456087	2576722706	12756053	2	12756053	index:0,count:12756053,average:101,stdev:0|index:1,count:12756053,average:101,stdev:0	DRR084022	KYUSH-MIB			in_mesa	28115634	10.68	2.56	0.09	1899973290	1894822501	1655632349	1664523552	99.73	100.54	11009947	10406590	203.991	586.059	167	82767	75.08	86.47	13386854	8266489	13386854	8266489	78.19	80.78	13386854	8608495	13386854	7722442	226145112	11.90	0.42	0	11.37	0	0.55	0	0.13	0	0.00	0	13.01	0	11009947	0	202	0	199.35	0	2.69	0	0.02	0	1.66	0	0.01	0	124.45	0	1.03	0	53148	0	12756053	0	1450499	0	70044	0	16381	0	0	0	1659681	0	1882	0	0	0	17701	0	2790681	0	7341	0	2817605	0	74.94	0	9559448	0	164634	2697731	16.386232491466	12756053.0	11009947.0	53148.0	1450499.0	70044.0	16381.0	0.0	1659681.0	9559448.0	86.3	0.4	11.4	0.5	0.1	0.0	13.0	74.9	101	101	101.00	38	1288361353	24.0	25.7	26.1	24.1	0.1	31.1	18.6	bulk
229446	DRR084023	DRP003418	DRS039912	DRX077854	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 sequencing of SAMD00048521			Mili WT RNA-seq replicate 2 (single-end)	RNA-Seq	TRANSCRIPTOMIC	RANDOM	single				Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		108	SAMD00048521	mouse ovary small RNA-seq	2465474652	22828469	2017-01-27 00:37:12	1565567475	2465474652	22828469	1	22828469	index:0,count:22828469,average:108,stdev:0	DRR084023	KYUSH-MIB			in_mesa	28115634	6.52	2.25	0.09	1942507256	1945781337	1616934007	1634103676	100.17	101.06	0	0	0	0	0	0	71.95	86.45	23278773	13063789	23278773	13063789	72.61	78.83	23278773	13182647	23278773	11912560	206114550	10.61	0.28	0	13.34	0	0.62	0	0.29	0	0.00	0	19.56	0	18156480	0	108	0	107.00	0	2.61	0	0.04	0	2.19	0	0.04	0	319.78	0	0.42	0	63002	0	22828469	0	3045151	0	140979	0	66096	0	0	0	4464914	0	2102	0	0	0	17540	0	2633991	0	7639	0	2661272	0	66.20	0	15111329	0	165254	2925556	17.703389933073	22828469.0	18156480.0	63002.0	3045151.0	140979.0	66096.0	0.0	4464914.0	15111329.0	79.5	0.3	13.3	0.6	0.3	0.0	19.6	66.2	108	108	108.00	38	2465474652	23.4	27.0	27.1	22.5	0.0	35.8	24.5	bulk
229448	DRR084024	DRP003418	DRS039912	DRX077855	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 paired end sequencing of SAMD00048521			Mili WT RNA-seq replicate 3	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired	101			Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		202	SAMD00048521	mouse ovary small RNA-seq	4917613038	24344619	2017-01-27 00:37:12	4118076530	4917613038	24344619	2	24344619	index:0,count:24344619,average:101,stdev:0|index:1,count:24344619,average:101,stdev:0	DRR084024	KYUSH-MIB			in_mesa	28115634	7.68	2.88	0.06	3484909755	3499306738	3075879136	3112447272	100.41	101.19	20607379	19364239	198.568	616.438	167	159446	80.03	90.96	24739936	16492485	24739936	16492485	82.56	85.23	24739936	17013794	24739936	15452885	282869419	8.12	0.45	0	10.17	0	0.57	0	0.10	0	0.00	0	14.68	0	20607379	0	202	0	199.07	0	2.86	0	0.03	0	1.75	0	0.02	0	77.15	0	1.07	0	109678	0	24344619	0	2476451	0	137661	0	25163	0	0	0	3574416	0	4246	0	0	0	37524	0	6197982	0	14720	0	6254472	0	74.48	0	18130928	0	192086	5881239	30.617738929438	24344619.0	20607379.0	109678.0	2476451.0	137661.0	25163.0	0.0	3574416.0	18130928.0	84.6	0.5	10.2	0.6	0.1	0.0	14.7	74.5	101	101	101.00	38	2458806519	23.7	26.4	26.6	23.2	0.1	30.9	18.3	bulk
229450	DRR084025	DRP003418	DRS039912	DRX077856	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 sequencing of SAMD00048521			Mili WT RNA-seq replicate 3 (single-end)	RNA-Seq	TRANSCRIPTOMIC	RANDOM	single				Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		108	SAMD00048521	mouse ovary small RNA-seq	4503066804	41695063	2017-01-27 00:37:12	2859100597	4503066804	41695063	1	41695063	index:0,count:41695063,average:108,stdev:0	DRR084025	KYUSH-MIB			in_mesa	28115634	4.65	2.47	0.06	3505158976	3531298264	2962895117	3011592001	100.75	101.64	0	0	0	0	0	0	76.73	90.81	41735186	25173384	41735186	25173384	77.59	83.22	41735186	25454787	41735186	23068627	252042894	7.19	0.29	0	12.20	0	0.60	0	0.23	0	0.00	0	20.50	0	32805847	0	108	0	106.89	0	2.72	0	0.04	0	2.23	0	0.04	0	241.71	0	0.44	0	122093	0	41695063	0	5086333	0	248834	0	93963	0	0	0	8546419	0	4269	0	0	0	36223	0	5556992	0	15349	0	5612833	0	66.48	0	27719514	0	190122	6158644	32.393115999201	41695063.0	32805847.0	122093.0	5086333.0	248834.0	93963.0	0.0	8546419.0	27719514.0	78.7	0.3	12.2	0.6	0.2	0.0	20.5	66.5	108	108	108.00	38	4503066804	23.1	27.6	27.5	21.7	0.0	35.7	24.1	bulk
229452	DRR084026	DRP003418	DRS039912	DRX077857	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 paired end sequencing of SAMD00048521			Mili KO RNA-seq replicate 1	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired	101			Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		202	SAMD00048521	mouse ovary small RNA-seq	13805416290	68343645	2017-01-27 00:37:12	8462714426	13805416290	68343645	2	68343645	index:0,count:68343645,average:101,stdev:0|index:1,count:68343645,average:101,stdev:0	DRR084026	KYUSH-MIB			in_mesa	28115634	19.63	2.81	0.05	10159036112	9943200041	9178917212	9034013084	97.88	98.42	65396430	62750405	171.750	506.377	139	651185	68.8	76.43	76195708	44989986	76195708	44989986	73.43	73.52	76195708	48021749	76195708	43278001	2094817137	20.62	1.23	0	9.56	0	0.62	0	0.38	0	0.00	0	3.31	0	65396430	0	202	0	200.80	0	1.48	0	0.01	0	1.27	0	0.00	0	292.90	0	0.11	0	837439	0	68343645	0	6531015	0	425552	0	261686	0	0	0	2259977	0	11011	0	0	0	462063	0	15647723	0	31776	0	16152573	0	86.13	0	58865415	0	255592	13574171	53.108747535134	68343645.0	65396430.0	837439.0	6531015.0	425552.0	261686.0	0.0	2259977.0	58865415.0	95.7	1.2	9.6	0.6	0.4	0.0	3.3	86.1	101	101	101.00	38	6902708145	25.3	22.0	22.8	29.9	0.0	36.8	23.4	bulk
229454	DRR084027	DRP003418	DRS039912	DRX077858	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 paired end sequencing of SAMD00048521			Mili KO RNA-seq replicate 2	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired	101			Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		202	SAMD00048521	mouse ovary small RNA-seq	2022241796	10011098	2017-01-27 00:37:12	1688472114	2022241796	10011098	2	10011098	index:0,count:10011098,average:101,stdev:0|index:1,count:10011098,average:101,stdev:0	DRR084027	KYUSH-MIB			in_mesa	28115634	7.13	2.78	0.1	1505401590	1496297889	1328813964	1332236179	99.4	100.26	8812405	8328084	201.193	599.267	167	65986	73.5	83.55	10592637	6477541	10592637	6477541	75.88	78.02	10592637	6686867	10592637	6048778	215205552	14.30	0.46	0	10.58	0	0.65	0	0.16	0	0.00	0	11.16	0	8812405	0	202	0	199.32	0	2.81	0	0.03	0	1.63	0	0.01	0	79.73	0	1.03	0	45948	0	10011098	0	1059464	0	65484	0	15651	0	0	0	1117558	0	1559	0	0	0	14443	0	2349993	0	5399	0	2371394	0	77.44	0	7752941	0	159267	2241960	14.076739060822	10011098.0	8812405.0	45948.0	1059464.0	65484.0	15651.0	0.0	1117558.0	7752941.0	88.0	0.5	10.6	0.7	0.2	0.0	11.2	77.4	101	101	101.00	38	1011120898	24.5	25.7	25.8	23.9	0.1	31.3	18.9	bulk
229456	DRR084028	DRP003418	DRS039912	DRX077859	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 sequencing of SAMD00048521			Mili KO RNA-seq replicate 2 (single-end)	RNA-Seq	TRANSCRIPTOMIC	RANDOM	single				Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		108	SAMD00048521	mouse ovary small RNA-seq	1795448268	16624521	2017-01-27 00:37:12	1132113096	1795448268	16624521	1	16624521	index:0,count:16624521,average:108,stdev:0	DRR084028	KYUSH-MIB			in_mesa	28115634	4.35	2.42	0.1	1456287389	1457094182	1236267793	1248498892	100.06	100.99	0	0	0	0	0	0	71.44	84.15	17126464	9724708	17126464	9724708	71.47	76.83	17126464	9728720	17126464	8878815	182634338	12.54	0.29	0	12.37	0	0.73	0	0.36	0	0.00	0	17.03	0	13613046	0	108	0	106.98	0	2.65	0	0.04	0	2.09	0	0.04	0	336.23	0	0.41	0	48240	0	16624521	0	2056894	0	120541	0	59306	0	0	0	2831628	0	1513	0	0	0	13635	0	2066178	0	5595	0	2086921	0	69.51	0	11556152	0	157653	2284376	14.489898701579	16624521.0	13613046.0	48240.0	2056894.0	120541.0	59306.0	0.0	2831628.0	11556152.0	81.9	0.3	12.4	0.7	0.4	0.0	17.0	69.5	108	108	108.00	38	1795448268	23.9	26.9	26.8	22.4	0.0	36.0	25.2	bulk
229458	DRR084029	DRP003418	DRS039912	DRX077860	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 paired end sequencing of SAMD00048521			Mili KO RNA-seq replicate 3	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired	101			Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		202	SAMD00048521	mouse ovary small RNA-seq	2626767600	13003800	2017-01-27 00:37:12	2199237657	2626767600	13003800	2	13003800	index:0,count:13003800,average:101,stdev:0|index:1,count:13003800,average:101,stdev:0	DRR084029	KYUSH-MIB			in_mesa	28115634	6.89	2.77	0.06	1921490923	1928756609	1669514405	1689662968	100.38	101.21	11158033	10509099	203.372	599.034	167	84479	77.21	89.18	13594377	8615288	13594377	8615288	80.08	82.91	13594377	8935144	13594377	8009333	179296434	9.33	0.43	0	11.52	0	0.54	0	0.12	0	0.00	0	13.54	0	11158033	0	202	0	199.18	0	2.91	0	0.03	0	1.66	0	0.02	0	142.29	0	1.06	0	56038	0	13003800	0	1497722	0	69713	0	15045	0	0	0	1761009	0	2178	0	0	0	18639	0	3177585	0	6933	0	3205335	0	74.29	0	9660311	0	168076	3081421	18.333497941407	13003800.0	11158033.0	56038.0	1497722.0	69713.0	15045.0	0.0	1761009.0	9660311.0	85.8	0.4	11.5	0.5	0.1	0.0	13.5	74.3	101	101	101.00	38	1313383800	23.9	26.4	26.4	23.2	0.1	31.1	18.6	bulk
229472	DRR084030	DRP003418	DRS039912	DRX077861	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 sequencing of SAMD00048521			Mili KO RNA-seq replicate 3 (single-end)	RNA-Seq	TRANSCRIPTOMIC	RANDOM	single				Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		108	SAMD00048521	mouse ovary small RNA-seq	2448699336	22673142	2017-01-27 00:37:12	1549213663	2448699336	22673142	1	22673142	index:0,count:22673142,average:108,stdev:0	DRR084030	KYUSH-MIB			in_mesa	28115634	4.07	2.37	0.06	1918134281	1933769107	1588418163	1616695497	100.82	101.78	0	0	0	0	0	0	73.85	89.2	23223346	13250088	23223346	13250088	74.5	80.95	23223346	13366825	23223346	12023686	154836723	8.07	0.29	0	13.62	0	0.61	0	0.25	0	0.00	0	20.01	0	17941568	0	108	0	106.94	0	2.70	0	0.04	0	2.13	0	0.04	0	224.24	0	0.45	0	66860	0	22673142	0	3087792	0	138591	0	56823	0	0	0	4536160	0	2246	0	0	0	18084	0	2850955	0	7219	0	2878504	0	65.51	0	14853776	0	165851	3202992	19.312467214548	22673142.0	17941568.0	66860.0	3087792.0	138591.0	56823.0	0.0	4536160.0	14853776.0	79.1	0.3	13.6	0.6	0.3	0.0	20.0	65.5	108	108	108.00	38	2448699336	23.4	27.6	27.3	21.8	0.0	35.8	24.3	bulk
229474	DRR084031	DRP003418	DRS039912	DRX077862	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 paired end sequencing of SAMD00048521			Pld6 WT RNA-seq replicate 1	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired	101			Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		202	SAMD00048521	mouse ovary small RNA-seq	6788896800	33608400	2017-01-27 00:37:12	4241517658	6788896800	33608400	2	33608400	index:0,count:33608400,average:101,stdev:0|index:1,count:33608400,average:101,stdev:0	DRR084031	KYUSH-MIB			in_mesa	28115634	18.31	3.02	0.06	5158900051	4978893023	4739026747	4602718281	96.51	97.12	32199814	30798212	183.317	538.667	139	299842	62.65	68.39	36779807	20173121	36779807	20173121	66.81	66.25	36779807	21513875	36779807	19540414	1423079646	27.58	1.07	0	8.05	0	0.65	0	0.51	0	0.00	0	3.02	0	32199814	0	202	0	200.89	0	1.71	0	0.01	0	1.58	0	0.00	0	203.00	0	0.16	0	358122	0	33608400	0	2704600	0	219422	0	172513	0	0	0	1016651	0	4795	0	0	0	155380	0	6946418	0	17632	0	7124225	0	87.76	0	29495214	0	222827	6348693	28.491578668653	33608400.0	32199814.0	358122.0	2704600.0	219422.0	172513.0	0.0	1016651.0	29495214.0	95.8	1.1	8.0	0.7	0.5	0.0	3.0	87.8	101	101	101.00	38	3394448400	25.7	21.3	22.5	30.5	0.0	36.8	23.3	bulk
229476	DRR084032	DRP003418	DRS039912	DRX077863	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 sequencing of SAMD00048521			Pld6 WT RNA-seq replicate 2	RNA-Seq	TRANSCRIPTOMIC	RANDOM	single				Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		68	SAMD00048521	mouse ovary small RNA-seq	2302870184	33865738	2017-01-27 00:37:12	888725703	2302870184	33865738	1	33865738	index:0,count:33865738,average:68,stdev:0	DRR084032	KYUSH-MIB			in_mesa	28115634	4.82	2.6	0.09	1976374373	1953315564	1644794419	1641984814	98.83	99.83	0	0	0	0	0	0	72.61	87.28	38424906	21285541	38424906	21285541	76.75	81.12	38424906	22498299	38424906	19782670	182027752	9.21	0.28	0	14.55	0	0.92	0	0.56	0	0.00	0	11.95	0	29313897	0	68	0	67.45	0	2.13	0	0.03	0	1.48	0	0.02	0	385.81	0	0.44	0	93561	0	33865738	0	4927418	0	312879	0	191341	0	0	0	4047621	0	1934	0	0	0	44270	0	2502163	0	6764	0	2555131	0	72.01	0	24386479	0	163272	2685529	16.448190749179	33865738.0	29313897.0	93561.0	4927418.0	312879.0	191341.0	0.0	4047621.0	24386479.0	86.6	0.3	14.5	0.9	0.6	0.0	12.0	72.0	68	68	68.00	17	2302870184	22.7	27.3	27.8	22.2	0.0	39.4	36.6	bulk
229478	DRR084033	DRP003418	DRS039912	DRX077864	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 sequencing of SAMD00048521			Pld6 WT RNA-seq replicate 3	RNA-Seq	TRANSCRIPTOMIC	RANDOM	single				Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		68	SAMD00048521	mouse ovary small RNA-seq	2192322584	32240038	2017-01-27 00:37:12	835716226	2192322584	32240038	1	32240038	index:0,count:32240038,average:68,stdev:0	DRR084033	KYUSH-MIB			in_mesa	28115634	8.31	2.43	0.06	1637743046	1572937180	1335101814	1302717819	96.04	97.57	0	0	0	0	0	0	70.57	86.59	33198021	17150387	33198021	17150387	75.98	80.03	33198021	18464307	33198021	15852077	137730513	8.41	0.32	0	13.94	0	1.03	0	0.54	0	0.00	0	23.05	0	24302128	0	68	0	67.41	0	2.49	0	0.04	0	1.58	0	0.02	0	520.47	0	0.73	0	101985	0	32240038	0	4495358	0	331651	0	173771	0	0	0	7432488	0	1336	0	0	0	11780	0	1700153	0	5838	0	1719107	0	61.44	0	19806770	0	147396	1815703	12.318536459605	32240038.0	24302128.0	101985.0	4495358.0	331651.0	173771.0	0.0	7432488.0	19806770.0	75.4	0.3	13.9	1.0	0.5	0.0	23.1	61.4	68	68	68.00	17	2192322584	21.1	28.5	30.2	20.1	0.0	39.4	36.6	bulk
229480	DRR084034	DRP003418	DRS039912	DRX077865	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 paired end sequencing of SAMD00048521			Pld6 KO RNA-seq replicate 1	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired	101			Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		202	SAMD00048521	mouse ovary small RNA-seq	13697305082	67808441	2017-01-27 00:37:12	8392355689	13697305082	67808441	2	67808441	index:0,count:67808441,average:101,stdev:0|index:1,count:67808441,average:101,stdev:0	DRR084034	KYUSH-MIB			in_mesa	28115634	18.57	3.06	0.05	10212801578	9867452329	9327355745	9070867587	96.62	97.25	64486362	61796318	178.425	523.983	139	609780	64.64	70.99	74312001	41684815	74312001	41684815	69.01	68.62	74312001	44503421	74312001	40293698	2562847228	25.09	1.17	0	8.50	0	0.70	0	0.56	0	0.00	0	3.64	0	64486362	0	202	0	200.84	0	1.69	0	0.01	0	1.55	0	0.00	0	239.32	0	0.14	0	794791	0	67808441	0	5766061	0	477718	0	376455	0	0	0	2467906	0	9975	0	0	0	266733	0	14442307	0	34324	0	14753339	0	86.60	0	58720301	0	256537	12843430	50.064630053365	67808441.0	64486362.0	794791.0	5766061.0	477718.0	376455.0	0.0	2467906.0	58720301.0	95.1	1.2	8.5	0.7	0.6	0.0	3.6	86.6	101	101	101.00	38	6848652541	25.7	21.3	22.5	30.4	0.0	36.8	23.3	bulk
229482	DRR084035	DRP003418	DRS039912	DRX077866	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 sequencing of SAMD00048521			Pld6 KO RNA-seq replicate 2	RNA-Seq	TRANSCRIPTOMIC	RANDOM	single				Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		68	SAMD00048521	mouse ovary small RNA-seq	2044675340	30068755	2017-01-27 00:37:12	776885578	2044675340	30068755	1	30068755	index:0,count:30068755,average:68,stdev:0	DRR084035	KYUSH-MIB			in_mesa	28115634	5.28	2.35	0.07	1652640503	1627350712	1325934785	1316783027	98.47	99.31	0	0	0	0	0	0	69.93	87.18	33535087	17148862	33535087	17148862	75.29	80.55	33535087	18465066	33535087	15843666	137948128	8.35	0.28	0	16.14	0	0.95	0	0.51	0	0.00	0	16.98	0	24524126	0	68	0	67.41	0	2.12	0	0.03	0	1.54	0	0.02	0	429.55	0	0.59	0	83898	0	30068755	0	4853984	0	286297	0	154042	0	0	0	5104290	0	1486	0	0	0	49441	0	1915277	0	5785	0	1971989	0	65.42	0	19670142	0	147736	2033722	13.765920290247	30068755.0	24524126.0	83898.0	4853984.0	286297.0	154042.0	0.0	5104290.0	19670142.0	81.6	0.3	16.1	1.0	0.5	0.0	17.0	65.4	68	68	68.00	17	2044675340	22.0	28.2	29.1	20.7	0.0	39.4	36.7	bulk
229484	DRR084036	DRP003418	DRS039912	DRX077867	DRA004523	KYUSH-MIB	Kyushu University	piRNA profiles in mouse oocytes lacking Pld6, Mili, Miwi, or Dicer	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Piwi-interacting RNAs (piRNAs) are approximately 26-30 nucleotide single-stranded RNAs bound to Piwi proteins. In mice, the piRNA pathway is well characterized in male germ cells, but its regulation and function in oocytes are less well understood. We have profiled piRNAs in normal ovaries and mutant ones lacking Pld6, Mili, Miwi, or Dicer using deep sequencing.	Illumina HiSeq 1500 sequencing of SAMD00048521			Pld6 KO RNA-seq replicate 3	RNA-Seq	TRANSCRIPTOMIC	RANDOM	single				Illumina HiSeq 1500	dev_stage;;P20|sample_name;;mouse P20 ovaries|sex;;female|tissue_type;;ovary		68	SAMD00048521	mouse ovary small RNA-seq	2133023116	31367987	2017-01-27 00:37:12	812067693	2133023116	31367987	1	31367987	index:0,count:31367987,average:68,stdev:0	DRR084036	KYUSH-MIB			in_mesa	28115634	5.89	2.45	0.07	1647115303	1599095792	1343013921	1314497421	97.08	97.88	0	0	0	0	0	0	69.6	85.39	33041947	17009130	33041947	17009130	74.72	79.19	33041947	18260702	33041947	15774440	153252569	9.30	0.28	0	14.40	0	1.09	0	0.60	0	0.00	0	20.40	0	24437991	0	68	0	67.42	0	2.16	0	0.03	0	1.54	0	0.02	0	347.46	0	0.68	0	86311	0	31367987	0	4517583	0	342179	0	188180	0	0	0	6399637	0	1477	0	0	0	37998	0	1919761	0	6460	0	1965696	0	63.51	0	19920408	0	152888	2069674	13.537190623201	31367987.0	24437991.0	86311.0	4517583.0	342179.0	188180.0	0.0	6399637.0	19920408.0	77.9	0.3	14.4	1.1	0.6	0.0	20.4	63.5	68	68	68.00	17	2133023116	21.6	28.2	29.9	20.4	0.0	39.4	36.6	bulk
725006	ERR505201	ERP005852	ERS459877	ERX470567	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	Protocols: CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (2 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant murine IL-12 (10 ng/ml, RD Systems) and neutralising anti-IL4 (10 ug/ml, clone 11B11, eBioscience). Cells were cultured for another four days in absence of CD3 and CD28 stimulation to rest them. The original medium was kept and fresh medium containing the same cytokines as before was added to dilute the cultures 1:3. Finally, the cells were labelled with anti-CXCR3-APC (1:200, clone CXCR3-173, BioLegend) and Propidium Iodide and FITC-conjugated antibodies against CD11b, CD11c, Ly6G, CD8a and CD19. The cultures were then FACS-sorted to obtain Propidium Iodide-, FITC-negative and CXCR3-positive cells. RNA was purified using the Qiagen RNEasy Plus Mini Kit automated using a QIAcube Samples were processed using the TruSeq RNA Sample Prep v2 kit (Illumina) according to the manufacturers instructions with an alteration to use KAPA Hifi polymerase for PCR amplification instead of the one supplied with the kit.	Th1_B	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	264	69.5	CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (2 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant murine IL-12 (10 ng/ml, RD Systems) and neutralising anti-IL4 (10 ug/ml, clone 11B11, eBioscience). Cells were cultured for another four days in absence of CD3 and CD28 stimulation to rest them. The original medium was kept and fresh medium containing the same cytokines as before was added to dilute the cultures 1:3. Finally, the cells were labelled with anti-CXCR3-APC (1:200, clone CXCR3-173, BioLegend) and Propidium Iodide and FITC-conjugated antibodies against CD11b, CD11c, Ly6G, CD8a and CD19. The cultures were then FACS-sorted to obtain Propidium Iodide-, FITC-negative and CXCR3-positive cells. RNA was purified using the Qiagen RNEasy Plus Mini Kit automated using a QIAcube Samples were processed using the TruSeq RNA Sample Prep v2 kit (Illumina) according to the manufacturers instructions with an alteration to use KAPA Hifi polymerase for PCR amplification instead of the one supplied with the kit.	Illumina HiSeq 2000	alias;;E-MTAB-2582:Th1 rep2|broker name;;ArrayExpress|cell type;;T-helper 1 cell|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:54Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459877|SRA accession;;ERS459877|title;;Th1 rep2	Experimental Factor: cell type;;T-helper 1 cell	200	SAMEA2536561	E-MTAB-2582:Th1 rep2	8708271600	43541358	2015-04-06 04:39:03	6295814845	8708271600	43541358	2	43541358	index:0,count:43541358,average:100,stdev:0|index:1,count:43541358,average:100,stdev:0	E-MTAB-2582:Teichmann-ThExpress_Th1_B		ArrayExpress	SC	in_mesa	25886751	3.21	3.55	0.07	8264952046	8166826994	7441603601	7405585031	98.81	99.52	42597149	35962616	296.749	1228.695	227	219028	84.66	94.05	49576095	36062481	49576095	36062481	90.51	90.95	49576095	38553520	49576095	34873928	400173254	4.84	0.70	0	9.77	0	0.42	0	0.09	0	0.00	0	1.66	0	42597149	0	200	0	198.35	0	1.49	0	0.01	0	1.22	0	0.01	0	381.38	0	0.30	0	304733	0	43541358	0	4252101	0	182728	0	39818	0	0	0	721663	0	13930	0	0	0	153468	0	20475723	0	34681	0	20677802	0	88.07	0	38345048	0	219639	21949645	99.935098047250	43541358.0	42597149.0	304733.0	4252101.0	182728.0	39818.0	0.0	721663.0	38345048.0	97.8	0.7	9.8	0.4	0.1	0.0	1.7	88.1	100	100	100.00	44	4354135800	24.9	25.2	25.0	24.9	0.0	36.7	25.6	bulk
725014	ERR505202	ERP005852	ERS459876	ERX470566	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina Genome Analyzer IIx paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes		Treg_B	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	185	58.1	MACS was used to isolate splenic CD4+ T cells by depleting CD8a, CD11b, CD11c, CD19 Ly6G(Gr-1) expressing cells followed by positive selection for CD25+ cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Illumina Genome Analyzer IIx	Alias;;E-MTAB-2582:Treg rep2|Broker name;;ArrayExpress|cell type;;regulatory T cell|Description;;Protocols: MACS was used to isolate splenic CD4+ T cells by depleting CD8a, CD11b, CD11c, CD19 Ly6G(Gr-1) expressing cells followed by positive selection for CD25+ cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:51Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459876|SRA accession;;ERS459876|Title;;Treg rep2	Experimental Factor: cell type;;regulatory T cell	72	SAMEA2536560	E-MTAB-2582:Treg rep2	1549789416	21524853	2015-04-06 04:39:03	878239311	1549789416	21524853	2	21524853	index:0,count:21524853,average:36,stdev:0|index:1,count:21524853,average:36,stdev:0	E-MTAB-2582:Teichmann-ThExpress_nTreg_B		ArrayExpress	CRUK	in_mesa	25886751	1.23	2.81	0.16	1043636668	1015631584	942301279	926695664	97.32	98.34	14994791	12949946	219.853	1231.874	203	167830	63.3	70.13	18067009	9491734	18067009	9491734	68.86	67.52	18067009	10324716	18067009	9138663	292388250	28.02	2.50	0	6.78	0	1.61	0	0.56	0	0.00	0	28.17	0	14994791	0	72	0	70.61	0	1.31	0	0.00	0	1.06	0	0.00	0	405.70	0	0.23	0	537518	0	21524853	0	1460207	0	346466	0	120436	0	0	0	6063160	0	723	0	0	0	5653	0	744934	0	10481	0	761791	0	62.88	0	13534584	0	99706	769568	7.718372013720	21524853.0	14994791.0	537518.0	1460207.0	346466.0	120436.0	0.0	6063160.0	13534584.0	69.7	2.5	6.8	1.6	0.6	0.0	28.2	62.9	36	36	36.00	39	774894708	24.4	24.3	28.5	22.7	0.0	38.2	23.2	bulk
725022	ERR505203	ERP005852	ERS459870	ERX470560	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	Protocols: CD4+, CD62L+ cells were purified from DEREG mice with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (1 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant human TGF-beta1 (20ng/ml, Sigma). The cells were gently removed from the activation plate on day 4. The iTreg culture was subjected to FACS sorting for GFP-positive, propidium iodide-negative cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	iTreg_B	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	single			CD4+, CD62L+ cells were purified from DEREG mice with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (1 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant human TGF-beta1 (20ng/ml, Sigma). The cells were gently removed from the activation plate on day 4. The iTreg culture was subjected to FACS sorting for GFP-positive, propidium iodide-negative cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Illumina HiSeq 2000	alias;;E-MTAB-2582:iTreg rep2|broker name;;ArrayExpress|cell type;;induced T-regulatory cell|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:50Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459870|SRA accession;;ERS459870|title;;iTreg rep2	Experimental Factor: cell type;;induced T-regulatory cell		SAMEA2536554	E-MTAB-2582:iTreg rep2	3702448440	102845790	2015-04-06 04:39:03	4327146207	3702448440	102845790	1	102845790	index:0,count:102845790,average:36,stdev:0	E-MTAB-2582:Teichmann-ThExpress_iTreg_B.fq.gz		ArrayExpress	CRUK	in_mesa	25886751	0.99	3.91	0.27	1940385267	1913286378	1475894522	1500172851	98.6	101.64	0	0	0	0	0	0	70.89	93.11	88865787	38544259	88865787	38544259	85.16	87.27	88865787	46301829	88865787	36125183	120779552	6.22	5.70	0	12.62	0	1.27	0	1.33	0	0.00	0	44.53	0	54371378	0	36	0	35.65	0	1.15	0	0.00	0	1.06	0	0.00	0	637.25	0	0.18	0	5864976	0	102845790	0	12975850	0	1306921	0	1365447	0	0	0	45802044	0	1022	0	0	0	11618	0	1604976	0	8767	0	1626383	0	40.25	0	41395528	0	63027	2103244	33.370523743792	102845790.0	54371378.0	5864976.0	12975850.0	1306921.0	1365447.0	0.0	45802044.0	41395528.0	52.9	5.7	12.6	1.3	1.3	0.0	44.5	40.3	36	36	36.00	38	3702448440	22.7	28.0	27.8	21.4	0.0	37.8	25.9	bulk
725030	ERR505204	ERP005852	ERS459874	ERX470564	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	Protocols: CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec) and further purification was performed by FACS using anti-CD62L and anti-CD4 Fab fragments. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Naive 3b	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	121	16.6	CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec) and further purification was performed by FACS using anti-CD62L and anti-CD4 Fab fragments. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Illumina HiSeq 2000	alias;;E-MTAB-2582:Naive rep1|broker name;;ArrayExpress|cell type;;naive thymus-derived CD4-positive, alpha-beta T cell|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:51Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459874|SRA accession;;ERS459874|title;;Naive rep1	Experimental Factor: cell type;;naive thymus-derived CD4-positive, alpha-beta T cell	200	SAMEA2536558	E-MTAB-2582:Naive rep1	25503717000	127518585	2015-04-06 04:39:03	17545194237	25503717000	127518585	2	127518585	index:0,count:127518585,average:100,stdev:0|index:1,count:127518585,average:100,stdev:0	E-MTAB-2582:Teichmann-ThExpress_naive_3b		ArrayExpress	CRUK	in_mesa	25886751	0.21	2.28	0.32	6463217015	6389321671	5997097037	5980948759	98.86	99.73	58665042	55685250	126.623	911.412	101	839776	66.05	71.3	67127657	38746738	67127657	38746738	66.83	66.58	67127657	39203981	67127657	36182131	1745241373	27.00	1.72	0	3.39	0	1.10	0	0.15	0	0.00	0	52.75	0	58665042	0	200	0	185.56	0	1.66	0	0.03	0	1.34	0	0.00	0	127.45	0	0.52	0	2189290	0	127518585	0	4323786	0	1402827	0	188816	0	0	0	67261900	0	9492	0	0	0	125371	0	15499181	0	157176	0	15791220	0	42.61	0	54341256	0	156674	10930135	69.763553620894	127518585.0	58665042.0	2189290.0	4323786.0	1402827.0	188816.0	0.0	67261900.0	54341256.0	46.0	1.7	3.4	1.1	0.1	0.0	52.7	42.6	100	100	100.00	38	12751858500	22.9	26.7	29.9	20.1	0.3	33.6	16.0	bulk
725039	ERR505205	ERP005852	ERS459869	ERX470559	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes		Th2_A	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	258	68	CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (2 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant murine IL-4 (10 ng/ml, RD Systems) and neutralizing anti-IFN-gamma (10 ug/ml, clone XMG1.2, eBioscience). Cells were cultured for another four days in absence of CD3 and CD28 stimulation to rest them. The original medium was kept and fresh medium containing the same cytokines as before was added to dilute the cultures 1:3. Finally, the cells were labelled with Propidium Iodide and FITC-conjugated antibodies against CD11b, CD11c, Ly6G, CD8a and CD19. The cultures were then FACS-sorted to obtain Propidium Iodide-, FITC-negative cells. RNA was purified using the Qiagen RNEasy Plus Mini Kit automated using a QIAcube Samples were processed using the TruSeq RNA Sample Prep v2 kit (Illumina) according to the manufacturers instructions with an alteration to use KAPA Hifi polymerase for PCR amplification instead of the one supplied with the kit.	Illumina HiSeq 2000	Alias;;E-MTAB-2582:Th2 rep1|Broker name;;ArrayExpress|cell type;;T-helper 2 cell|Description;;Protocols: CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (2 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant murine IL-4 (10 ng/ml, RD Systems) and neutralizing anti-IFN-gamma (10 ug/ml, clone XMG1.2, eBioscience). Cells were cultured for another four days in absence of CD3 and CD28 stimulation to rest them. The original medium was kept and fresh medium containing the same cytokines as before was added to dilute the cultures 1:3. Finally, the cells were labelled with Propidium Iodide and FITC-conjugated antibodies against CD11b, CD11c, Ly6G, CD8a and CD19. The cultures were then FACS-sorted to obtain Propidium Iodide-, FITC-negative cells. RNA was purified using the Qiagen RNEasy Plus Mini Kit automated using a QIAcube Samples were processed using the TruSeq RNA Sample Prep v2 kit (Illumina) according to the manufacturers instructions with an alteration to use KAPA Hifi polymerase for PCR amplification instead of the one supplied with the kit.|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:50Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459869|SRA accession;;ERS459869|Title;;Th2 rep1	Experimental Factor: cell type;;T-helper 2 cell	200	SAMEA2536553	E-MTAB-2582:Th2 rep1	10286746400	51433732	2015-04-06 04:39:03	7450242509	10286746400	51433732	2	51433732	index:0,count:51433732,average:100,stdev:0|index:1,count:51433732,average:100,stdev:0	E-MTAB-2582:Teichmann-ThExpress_Th2_A		ArrayExpress	SC	in_mesa	25886751	7.52	3.4	0.09	9712581546	9570261059	8558201888	8494881347	98.53	99.26	50269311	43799692	287.826	1079.599	218	273918	82.13	93.25	59185623	41288559	59185623	41288559	89.72	89.94	59185623	45102447	59185623	39823806	511051187	5.26	0.70	0	11.65	0	0.31	0	0.07	0	0.00	0	1.88	0	50269311	0	200	0	198.37	0	1.59	0	0.01	0	1.24	0	0.01	0	308.09	0	0.31	0	361264	0	51433732	0	5991820	0	161800	0	38115	0	0	0	964506	0	15055	0	0	0	159856	0	21743853	0	39917	0	21958681	0	86.09	0	44277491	0	221245	23363444	105.599873443468	51433732.0	50269311.0	361264.0	5991820.0	161800.0	38115.0	0.0	964506.0	44277491.0	97.7	0.7	11.6	0.3	0.1	0.0	1.9	86.1	100	100	100.00	44	5143373200	24.8	25.2	25.0	24.9	0.0	36.7	25.5	bulk
725046	ERR505206	ERP005852	ERS459872	ERX470562	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina Genome Analyzer IIx paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	Protocols: MACS was used to isolate splenic CD4+ T cells by depleting CD8a, CD11b, CD11c, CD19 Ly6G(Gr-1) expressing cells followed by positive selection for CD25+ cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Treg_A	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	190	67.3	MACS was used to isolate splenic CD4+ T cells by depleting CD8a, CD11b, CD11c, CD19 Ly6G(Gr-1) expressing cells followed by positive selection for CD25+ cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Illumina Genome Analyzer IIx	alias;;E-MTAB-2582:Treg rep1|broker name;;ArrayExpress|cell type;;regulatory T cell|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:50Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459872|SRA accession;;ERS459872|title;;Treg rep1	Experimental Factor: cell type;;regulatory T cell	72	SAMEA2536556	E-MTAB-2582:Treg rep1	1691258688	23489704	2015-04-06 04:39:03	976068089	1691258688	23489704	2	23489704	index:0,count:23489704,average:36,stdev:0|index:1,count:23489704,average:36,stdev:0	E-MTAB-2582:Teichmann-ThExpress_nTreg_A		ArrayExpress	CRUK	in_mesa	25886751	1.22	2.7	0.21	1088201405	1050347740	999924242	973272086	96.52	97.33	15653657	13734867	216.965	1136.254	220	146568	57.35	62.47	18348581	8977534	18348581	8977534	61.53	60.22	18348581	9631441	18348581	8655110	378994763	34.83	3.02	0	5.46	0	1.40	0	0.51	0	0.00	0	31.45	0	15653657	0	72	0	70.79	0	1.27	0	0.00	0	1.06	0	0.00	0	427.09	0	0.23	0	709693	0	23489704	0	1282301	0	329068	0	120238	0	0	0	7386741	0	610	0	0	0	5485	0	705832	0	9568	0	721495	0	61.18	0	14371356	0	99612	727846	7.306810424447	23489704.0	15653657.0	709693.0	1282301.0	329068.0	120238.0	0.0	7386741.0	14371356.0	66.6	3.0	5.5	1.4	0.5	0.0	31.4	61.2	36	36	36.00	39	845629344	24.8	24.3	27.8	23.0	0.0	38.2	23.5	bulk
725052	ERR505207	ERP005852	ERS459878	ERX470568	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	Protocols: CD4+, CD62L+ cells were purified from DEREG mice with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (1 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant human TGF-beta1 (20ng/ml, Sigma). The cells were gently removed from the activation plate on day 4. The iTreg culture was subjected to FACS sorting for GFP-positive, propidium iodide-negative cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	iTreg_A	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	single			CD4+, CD62L+ cells were purified from DEREG mice with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (1 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant human TGF-beta1 (20ng/ml, Sigma). The cells were gently removed from the activation plate on day 4. The iTreg culture was subjected to FACS sorting for GFP-positive, propidium iodide-negative cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Illumina HiSeq 2000	alias;;E-MTAB-2582:iTreg rep1|broker name;;ArrayExpress|cell type;;induced T-regulatory cell|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:54Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459878|SRA accession;;ERS459878|title;;iTreg rep1	Experimental Factor: cell type;;induced T-regulatory cell		SAMEA2536562	E-MTAB-2582:iTreg rep1	3520192356	97783121	2015-04-06 04:39:03	4090385343	3520192356	97783121	1	97783121	index:0,count:97783121,average:36,stdev:0	E-MTAB-2582:Teichmann-ThExpress_iTreg_A.fq.gz		ArrayExpress	CRUK	in_mesa	25886751	1.52	4.21	0.21	529982141	517138134	401569293	402033879	97.58	100.12	0	0	0	0	0	0	68.88	90.81	24461057	10244166	24461057	10244166	84.4	85.94	24461057	12551800	24461057	9695015	37561789	7.09	7.19	0	3.67	0	0.50	0	0.15	0	0.00	0	84.14	0	14871885	0	36	0	35.60	0	1.12	0	0.00	0	1.10	0	0.00	0	423.61	0	0.40	0	7028592	0	97783121	0	3591333	0	490122	0	149254	0	0	0	82271860	0	255	0	0	0	3298	0	445971	0	4409	0	453933	0	11.54	0	11280552	0	34807	550527	15.816559887379	97783121.0	14871885.0	7028592.0	3591333.0	490122.0	149254.0	0.0	82271860.0	11280552.0	15.2	7.2	3.7	0.5	0.2	0.0	84.1	11.5	36	36	36.00	38	3520192356	24.7	28.1	27.2	20.0	0.0	37.5	25.6	bulk
725060	ERR505208	ERP005852	ERS459873	ERX470563	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes		Th17_B	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	213	54.2	CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec) and further purification was performed by FACS using anti-CD62L and anti-CD4 Fab fragments. Cells were seeded into anti-CD3 (1 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant human IL-6 (30ng/ml, Immunotools), recombinant human TGF-beta1 (5ng/ml, Sigma), recombinant murine IL-1beta (10ng/ml, Immunotools), recombinant murine IL-23 (10ng/ ml, R&D systems), neutralizing anti-IL4 (5ug/ml, clone 11B11, eBioscience), neutralizing anti-IFN-gamma (5ug/ml, clone XMG1.2, eBioscience), and neutralizing anti-IL2 (5ug/ml, clone JES6-5H4, eBioscience). Cells were labelled with anti-CCR6-APC (1:200, clone 29-2L17, BioLegend), anti-CD8a-FITC (1:1500, clone 53-6.7, eBioscience), and propidium iodide. FACS sorting was then performed to select FITC-negative, APC-positive, propidium iodide-negative cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Illumina HiSeq 2000	Alias;;E-MTAB-2582:Th17 rep2|Broker name;;ArrayExpress|cell type;;T-helper 17 cell|Description;;Protocols: CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec) and further purification was performed by FACS using anti-CD62L and anti-CD4 Fab fragments. Cells were seeded into anti-CD3 (1 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant human IL-6 (30ng/ml, Immunotools), recombinant human TGF-beta1 (5ng/ml, Sigma), recombinant murine IL-1beta (10ng/ml, Immunotools), recombinant murine IL-23 (10ng/ ml, RD systems), neutralizing anti-IL4 (5ug/ml, clone 11B11, eBioscience), neutralizing anti-IFN-gamma (5ug/ml, clone XMG1.2, eBioscience), and neutralizing anti-IL2 (5ug/ml, clone JES6-5H4, eBioscience). Cells were labelled with anti-CCR6-APC (1:200, clone 29-2L17, BioLegend), anti-CD8a-FITC (1:1500, clone 53-6.7, eBioscience), and propidium iodide. FACS sorting was then performed to select FITC-negative, APC-positive, propidium iodide-negative cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:51Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459873|SRA accession;;ERS459873|Title;;Th17 rep2	Experimental Factor: cell type;;T-helper 17 cell	200	SAMEA2536557	E-MTAB-2582:Th17 rep2	30131552400	150657762	2015-04-06 04:39:03	22329773707	30131552400	150657762	2	150657762	index:0,count:150657762,average:100,stdev:0|index:1,count:150657762,average:100,stdev:0	E-MTAB-2582:Teichmann-ThExpress_Th17_B		ArrayExpress	CRUK	in_mesa	25886751	2.04	3.43	0.2	19755965604	19269750140	18348069835	18068161611	97.54	98.47	111261911	102410470	228.832	757.414	193	665082	70.1	75.57	125545761	77995043	125545761	77995043	72.69	72.52	125545761	80881376	125545761	74851262	4453249173	22.54	0.85	0	5.34	0	0.32	0	0.06	0	0.00	0	25.77	0	111261911	0	200	0	193.22	0	1.89	0	0.01	0	1.35	0	0.00	0	169.28	0	2.16	0	1282508	0	150657762	0	8052439	0	481009	0	83623	0	0	0	38831219	0	21295	0	0	0	176487	0	30790344	0	155934	0	31144060	0	68.51	0	103209472	0	312080	31430187	100.711955267880	150657762.0	111261911.0	1282508.0	8052439.0	481009.0	83623.0	0.0	38831219.0	103209472.0	73.9	0.9	5.3	0.3	0.1	0.0	25.8	68.5	100	100	100.00	38	15065776200	25.6	23.7	24.5	25.8	0.3	29.9	13.0	bulk
725069	ERR505209	ERP005852	ERS459868	ERX470558	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina Genome Analyzer IIx paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	Protocols: CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec) and further purification was performed by FACS using anti-CD62L and anti-CD4 Fab fragments. Cells were seeded into anti-CD3 (1 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant human IL-6 (30ng/ml, Immunotools), recombinant human TGF-beta1 (5ng/ml, Sigma), recombinant murine IL-1beta (10ng/ml, Immunotools), recombinant murine IL-23 (10ng/ ml, RD systems), neutralizing anti-IL4 (5ug/ml, clone 11B11, eBioscience), neutralizing anti-IFN-gamma (5ug/ml, clone XMG1.2, eBioscience), and neutralizing anti-IL2 (5ug/ml, clone JES6-5H4, eBioscience). Cells were labelled with anti-CCR6-APC (1:200, clone 29-2L17, BioLegend), anti-CD8a-FITC (1:1500, clone 53-6.7, eBioscience), and propidium iodide. FACS sorting was then performed to select FITC-negative, APC-positive, propidium iodide-negative cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Th17_A	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	246	90.6	CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec) and further purification was performed by FACS using anti-CD62L and anti-CD4 Fab fragments. Cells were seeded into anti-CD3 (1 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant human IL-6 (30ng/ml, Immunotools), recombinant human TGF-beta1 (5ng/ml, Sigma), recombinant murine IL-1beta (10ng/ml, Immunotools), recombinant murine IL-23 (10ng/ ml, R&D systems), neutralizing anti-IL4 (5ug/ml, clone 11B11, eBioscience), neutralizing anti-IFN-gamma (5ug/ml, clone XMG1.2, eBioscience), and neutralizing anti-IL2 (5ug/ml, clone JES6-5H4, eBioscience). Cells were labelled with anti-CCR6-APC (1:200, clone 29-2L17, BioLegend), anti-CD8a-FITC (1:1500, clone 53-6.7, eBioscience), and propidium iodide. FACS sorting was then performed to select FITC-negative, APC-positive, propidium iodide-negative cells. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Illumina Genome Analyzer IIx	alias;;E-MTAB-2582:Th17 rep1|broker name;;ArrayExpress|cell type;;T-helper 17 cell|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:47:54Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459868|SRA accession;;ERS459868|title;;Th17 rep1	Experimental Factor: cell type;;T-helper 17 cell	72	SAMEA2536552	E-MTAB-2582:Th17 rep1	3138629544	43592077	2015-04-06 04:39:03	2072994000	3138629544	43592077	2	43592077	index:0,count:43592077,average:36,stdev:0|index:1,count:43592077,average:36,stdev:0	E-MTAB-2582:Teichmann-ThExpress_Th17_A		ArrayExpress	CRUK	in_mesa	25886751	2.15	3.67	0.25	2816249949	2733487917	2526754504	2495289527	97.06	98.75	39701298	32047058	270.710	1490.531	234	164555	66.08	73.63	48305624	26235379	48305624	26235379	72.04	71.58	48305624	28601377	48305624	25504180	693383575	24.62	2.47	0	9.34	0	1.07	0	0.60	0	0.00	0	7.26	0	39701298	0	72	0	71.23	0	1.44	0	0.00	0	1.07	0	0.00	0	881.64	0	0.25	0	1077106	0	43592077	0	4071375	0	465362	0	262554	0	0	0	3162863	0	2267	0	0	0	14865	0	2115336	0	13765	0	2146233	0	81.73	0	35629923	0	127647	2200963	17.242575226993	43592077.0	39701298.0	1077106.0	4071375.0	465362.0	262554.0	0.0	3162863.0	35629923.0	91.1	2.5	9.3	1.1	0.6	0.0	7.3	81.7	36	36	36.00	39	1569314772	26.8	22.8	24.1	26.2	0.0	35.8	20.0	bulk
725125	ERR505210	ERP005852	ERS459875	ERX470565	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes		Naive C	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	122	18	CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec) and further purification was performed by FACS using anti-CD62L and anti-CD4 Fab fragments. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497	Illumina HiSeq 2000	Alias;;E-MTAB-2582:Naive rep2|Broker name;;ArrayExpress|cell type;;naive thymus-derived CD4-positive, alpha-beta T cell|Description;;Protocols: CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec) and further purification was performed by FACS using anti-CD62L and anti-CD4 Fab fragments. Poly-(A)+ RNA was purified from ~500,000 cells using the Oligotex kit (Qiagen). The manufacturers protocol was modified slightly to include additional final elution steps resulting in a larger volume. RNA was purified, reverse transcribed and prepared for sequencing described in http://msb.embopress.org/content/7/1/497|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:51Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459875|SRA accession;;ERS459875|Title;;Naive rep2	Experimental Factor: cell type;;naive thymus-derived CD4-positive, alpha-beta T cell	200	SAMEA2536559	E-MTAB-2582:Naive rep2	38097765000	190488825	2015-04-06 04:39:03	27489229064	38097765000	190488825	2	190488825	index:0,count:190488825,average:100,stdev:0|index:1,count:190488825,average:100,stdev:0	E-MTAB-2582:Teichmann-ThExpress_naive_C		ArrayExpress	CRUK	in_mesa	25886751	0.36	2.49	0.31	4173906522	4069592714	3939392529	3881143505	97.5	98.52	41862350	39962731	111.317	1207.140	69	1045629	55.19	58.45	46886083	23103338	46886083	23103338	55.44	55.21	46886083	23210539	46886083	21820862	1617408224	38.75	0.92	0	1.23	0	0.24	0	0.08	0	0.00	0	77.71	0	41862350	0	200	0	175.83	0	1.59	0	0.01	0	1.23	0	0.00	0	111.96	0	0.44	0	1761632	0	190488825	0	2335590	0	459854	0	144131	0	0	0	148022490	0	5037	0	0	0	66067	0	8152736	0	64886	0	8288726	0	20.75	0	39526760	0	156938	5471897	34.866616115918	190488825.0	41862350.0	1761632.0	2335590.0	459854.0	144131.0	0.0	148022490.0	39526760.0	22.0	0.9	1.2	0.2	0.1	0.0	77.7	20.8	100	100	100.00	38	19048882500	25.0	24.8	29.2	20.8	0.3	32.4	14.6	bulk
725133	ERR505211	ERP005852	ERS459871	ERX470561	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	Protocols: CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (2 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant murine IL-12 (10 ng/ml, RD Systems) and neutralising anti-IL4 (10 ug/ml, clone 11B11, eBioscience). Cells were cultured for another four days in absence of CD3 and CD28 stimulation to rest them. The original medium was kept and fresh medium containing the same cytokines as before was added to dilute the cultures 1:3. Finally, the cells were labelled with anti-CXCR3-APC (1:200, clone CXCR3-173, BioLegend) and Propidium Iodide and FITC-conjugated antibodies against CD11b, CD11c, Ly6G, CD8a and CD19. The cultures were then FACS-sorted to obtain Propidium Iodide-, FITC-negative and CXCR3-positive cells. RNA was purified using the Qiagen RNEasy Plus Mini Kit automated using a QIAcube Samples were processed using the TruSeq RNA Sample Prep v2 kit (Illumina) according to the manufacturers instructions with an alteration to use KAPA Hifi polymerase for PCR amplification instead of the one supplied with the kit.	Th1_A	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	262	68.6	CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (2 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant murine IL-12 (10 ng/ml, RD Systems) and neutralising anti-IL4 (10 ug/ml, clone 11B11, eBioscience). Cells were cultured for another four days in absence of CD3 and CD28 stimulation to rest them. The original medium was kept and fresh medium containing the same cytokines as before was added to dilute the cultures 1:3. Finally, the cells were labelled with anti-CXCR3-APC (1:200, clone CXCR3-173, BioLegend) and Propidium Iodide and FITC-conjugated antibodies against CD11b, CD11c, Ly6G, CD8a and CD19. The cultures were then FACS-sorted to obtain Propidium Iodide-, FITC-negative and CXCR3-positive cells. RNA was purified using the Qiagen RNEasy Plus Mini Kit automated using a QIAcube Samples were processed using the TruSeq RNA Sample Prep v2 kit (Illumina) according to the manufacturers instructions with an alteration to use KAPA Hifi polymerase for PCR amplification instead of the one supplied with the kit.	Illumina HiSeq 2000	alias;;E-MTAB-2582:Th1 rep1|broker name;;ArrayExpress|cell type;;T-helper 1 cell|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:48:50Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459871|SRA accession;;ERS459871|title;;Th1 rep1	Experimental Factor: cell type;;T-helper 1 cell	200	SAMEA2536555	E-MTAB-2582:Th1 rep1	10164746600	50823733	2015-04-06 04:39:04	7344222623	10164746600	50823733	2	50823733	index:0,count:50823733,average:100,stdev:0|index:1,count:50823733,average:100,stdev:0	E-MTAB-2582:Teichmann-ThExpress_Th1_A		ArrayExpress	SC	in_mesa	25886751	3.4	3.43	0.08	9636893796	9497730474	8765524603	8702568962	98.56	99.28	49715955	41987734	294.134	1217.331	227	256875	85.29	93.79	57141474	42400872	57141474	42400872	90.35	90.83	57141474	44917769	57141474	41066000	470283174	4.88	0.69	0	8.87	0	0.41	0	0.08	0	0.00	0	1.68	0	49715955	0	200	0	198.38	0	1.49	0	0.01	0	1.23	0	0.00	0	365.93	0	0.29	0	348672	0	50823733	0	4506408	0	210323	0	41500	0	0	0	855955	0	16016	0	0	0	176694	0	23976448	0	42131	0	24211289	0	88.95	0	45209547	0	227383	25424407	111.813139064926	50823733.0	49715955.0	348672.0	4506408.0	210323.0	41500.0	0.0	855955.0	45209547.0	97.8	0.7	8.9	0.4	0.1	0.0	1.7	89.0	100	100	100.00	44	5082373300	25.0	25.0	24.9	25.1	0.0	36.7	25.6	bulk
725142	ERR505212	ERP005852	ERS459879	ERX470569	ERA311846	EBI	ArrayExpress	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	PolyA+ mRNA-seq was performed on naive, Th1, Th2, Th17, splenic Treg, and in vitro-induced Treg (iTreg) cells.	Illumina HiSeq 2000 paired end sequencing; An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	An mRNA-sequencing atlas of mouse CD4+ T cell transcriptomes	Protocols: CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (2 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant murine IL-4 (10 ng/ml, R&D Systems) and neutralizing anti-IFN-gamma (10 ug/ml, clone XMG1.2, eBioscience). Cells were cultured for another four days in absence of CD3 and CD28 stimulation to rest them. The original medium was kept and fresh medium containing the same cytokines as before was added to dilute the cultures 1:3. Finally, the cells were labelled with Propidium Iodide and FITC-conjugated antibodies against CD11b, CD11c, Ly6G, CD8a and CD19. The cultures were then FACS-sorted to obtain Propidium Iodide-, FITC-negative cells. RNA was purified using the Qiagen RNEasy Plus Mini Kit automated using a QIAcube Samples were processed using the TruSeq RNA Sample Prep v2 kit (Illumina) according to the manufacturers instructions with an alteration to use KAPA Hifi polymerase for PCR amplification instead of the one supplied with the kit.	Th2_B	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	260	68.3	CD4+, CD62L+ cells were purified with CD4+CD62L+ T Cell Isolation Kit II (Miltenyi Biotec). Cells were seeded into anti-CD3 (2 ug/ml, clone 145-2C11, eBioscience) and anti-CD28 (5 ug/ml, clone 37.51, eBioscience) coated 96-well plates, at a density of 250,000-500,000 cells/ml and cultured in a total volume of 200 ul in the presence of recombinant murine IL-4 (10 ng/ml, RD Systems) and neutralizing anti-IFN-gamma (10 ug/ml, clone XMG1.2, eBioscience). Cells were cultured for another four days in absence of CD3 and CD28 stimulation to rest them. The original medium was kept and fresh medium containing the same cytokines as before was added to dilute the cultures 1:3. Finally, the cells were labelled with Propidium Iodide and FITC-conjugated antibodies against CD11b, CD11c, Ly6G, CD8a and CD19. The cultures were then FACS-sorted to obtain Propidium Iodide-, FITC-negative cells. RNA was purified using the Qiagen RNEasy Plus Mini Kit automated using a QIAcube Samples were processed using the TruSeq RNA Sample Prep v2 kit (Illumina) according to the manufacturers instructions with an alteration to use KAPA Hifi polymerase for PCR amplification instead of the one supplied with the kit.	Illumina HiSeq 2000	alias;;E-MTAB-2582:Th2 rep2|broker name;;ArrayExpress|cell type;;T-helper 2 cell|ENA checklist;;ERC000011|INSDC center alias;;EBI|INSDC center name;;European Bioinformatics Institute|INSDC first public;;2015-04-05T17:04:12Z|INSDC last update;;2018-03-08T17:50:42Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS459879|SRA accession;;ERS459879|title;;Th2 rep2	Experimental Factor: cell type;;T-helper 2 cell	200	SAMEA2536563	E-MTAB-2582:Th2 rep2	10416061000	52080305	2015-04-06 04:39:04	7515996459	10416061000	52080305	2	52080305	index:0,count:52080305,average:100,stdev:0|index:1,count:52080305,average:100,stdev:0	E-MTAB-2582:Teichmann-ThExpress_Th2_B		ArrayExpress	SC	in_mesa	25886751	7.94	3.39	0.09	9856476660	9743231117	8722054874	8677479789	98.85	99.49	50943008	44815546	288.899	998.324	218	280711	80.31	90.78	59486341	40910556	59486341	40910556	87.65	87.49	59486341	44649506	59486341	39425317	824597356	8.37	0.72	0	11.29	0	0.29	0	0.09	0	0.00	0	1.81	0	50943008	0	200	0	198.41	0	1.54	0	0.01	0	1.20	0	0.01	0	347.20	0	0.30	0	373496	0	52080305	0	5879323	0	148430	0	45527	0	0	0	943340	0	14270	0	0	0	154123	0	20622131	0	39624	0	20830148	0	86.53	0	45063685	0	230716	22178807	96.130337731237	52080305.0	50943008.0	373496.0	5879323.0	148430.0	45527.0	0.0	943340.0	45063685.0	97.8	0.7	11.3	0.3	0.1	0.0	1.8	86.5	100	100	100.00	44	5208030500	25.0	25.0	24.9	25.1	0.0	36.7	25.5	bulk
896076	ERR525589	ERP005997	ERS472808	ERX490829	ERA315790	UCSF	ArrayExpress	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Illumina HiSeq 2500 paired end sequencing; RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Protocols: Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Brown_biolrepli2	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	315	33	Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Illumina HiSeq 2500	alias;;E-MTAB-2624:Brown_biolrepli2|broker name;;ArrayExpress|cell type;;claical brown adipocyte|ENA checklist;;ERC000011|INSDC center alias;;UCSF|INSDC center name;;University of California, San Francisco|INSDC first public;;2015-02-16T17:01:59Z|INSDC last update;;2018-03-08T18:23:10Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS472808|SRA accession;;ERS472808|title;;Brown_biolrepli2	Experimental Factor: cell type;;Classical brown adipocyte	202	SAMEA2579686	E-MTAB-2624:Brown_biolrepli2	9544367084	47249342	2015-02-17 06:11:42	6326450204	9544367084	47249342	2	47249342	index:0,count:47249342,average:101,stdev:0|index:1,count:47249342,average:101,stdev:0	E-MTAB-2624:RNA2_read		ArrayExpress	UCSF Genomics Core	in_mesa	25774848	69.4	0.85	0.1	5352002051	5339289621	5210446100	5215095436	99.76	100.09	35339003	34660696	173.776	356.125	104	263743	91.2	93.96	36782305	32229717	36782305	32229717	91.77	92.23	36782305	32430202	36782305	31635972	274731730	5.13	5.66	0	2.19	0	0.12	0	0.03	0	0.00	0	25.05	0	35339003	0	202	0	195.28	0	1.60	0	0.02	0	1.96	0	0.01	0	255.40	0	0.46	0	2673061	0	47249342	0	1036708	0	58121	0	16426	0	0	0	11835792	0	1701	0	0	0	15296	0	2870864	0	26674	0	2914535	0	72.60	0	34302295	0	104267	2507807	24.051780524998	47249342.0	35339003.0	2673061.0	1036708.0	58121.0	16426.0	0.0	11835792.0	34302295.0	74.8	5.7	2.2	0.1	0.0	0.0	25.0	72.6	101	101	101.00	38	4772183542	31.3	19.2	19.3	30.2	0.0	36.0	20.3	bulk
896132	ERR525590	ERP005997	ERS472804	ERX490825	ERA315790	UCSF	ArrayExpress	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Illumina HiSeq 2500 paired end sequencing; RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes		White_biolrepli1	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	340	38.7	Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Illumina HiSeq 2500	Alias;;E-MTAB-2624:White_biolrepli1|Broker name;;ArrayExpress|cell type;;inguinal white adipocyte|Description;;Protocols: Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2|ENA checklist;;ERC000011|INSDC center alias;;UCSF|INSDC center name;;University of California, San Francisco|INSDC first public;;2015-02-16T17:01:59Z|INSDC last update;;2018-03-08T18:23:10Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS472804|SRA accession;;ERS472804|Title;;White_biolrepli1	Experimental Factor: cell type;;inguinal white adipocyte	202	SAMEA2579682	E-MTAB-2624:White_biolrepli1	9963114296	49322348	2015-02-17 06:11:42	6751759764	9963114296	49322348	2	49322348	index:0,count:49322348,average:101,stdev:0|index:1,count:49322348,average:101,stdev:0	E-MTAB-2624:RNA3_read		ArrayExpress	UCSF Genomics Core	in_mesa	25774848	35.89	1.45	0.12	5243695848	5282325114	4999640189	5069263128	100.74	101.39	35110311	33702023	175.219	563.143	103	255708	83.44	88.13	38316160	29296614	38316160	29296614	80.56	82.11	38316160	28283118	38316160	27293477	482098147	9.19	4.81	0	3.79	0	0.33	0	0.14	0	0.00	0	28.35	0	35110311	0	202	0	193.77	0	2.21	0	0.03	0	2.87	0	0.03	0	183.62	0	0.60	0	2372091	0	49322348	0	1868688	0	160913	0	68914	0	0	0	13982210	0	4688	0	0	0	31633	0	6095842	0	35438	0	6167601	0	67.40	0	33241623	0	144693	5365901	37.084731120372	49322348.0	35110311.0	2372091.0	1868688.0	160913.0	68914.0	0.0	13982210.0	33241623.0	71.2	4.8	3.8	0.3	0.1	0.0	28.3	67.4	101	101	101.00	38	4981557148	27.7	22.5	22.8	27.0	0.0	35.1	18.3	bulk
896140	ERR525591	ERP005997	ERS472807	ERX490828	ERA315790	UCSF	ArrayExpress	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Illumina HiSeq 2500 paired end sequencing; RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Protocols: Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Beige_biolrepli1	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	304	27.3	Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Illumina HiSeq 2500	alias;;E-MTAB-2624:Beige_biolrepli1|broker name;;ArrayExpress|cell type;;rosiglitazone-treated adipocyte (beige cell)|ENA checklist;;ERC000011|INSDC center alias;;UCSF|INSDC center name;;University of California, San Francisco|INSDC first public;;2015-02-16T17:01:59Z|INSDC last update;;2018-03-08T18:23:10Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS472807|SRA accession;;ERS472807|title;;Beige_biolrepli1	Experimental Factor: cell type;;rosiglitazone-treated adipocyte (beige cell)	202	SAMEA2579685	E-MTAB-2624:Beige_biolrepli1	8117348790	40184895	2015-02-17 06:11:42	5454071296	8117348790	40184895	2	40184895	index:0,count:40184895,average:101,stdev:0|index:1,count:40184895,average:101,stdev:0	E-MTAB-2624:RNA5_read		ArrayExpress	UCSF Genomics Core	in_mesa	25774848	56.17	1.01	0.09	4255502154	4283033481	4067915904	4118035621	100.65	101.23	28682372	27926943	170.161	427.931	102	220623	88.42	93.04	30908795	25360623	30908795	25360623	87.47	88.69	30908795	25088593	30908795	24175188	217013552	5.10	5.12	0	3.54	0	0.25	0	0.01	0	0.00	0	28.36	0	28682372	0	202	0	193.90	0	2.07	0	0.03	0	2.49	0	0.02	0	227.10	0	0.56	0	2058860	0	40184895	0	1424249	0	100779	0	5898	0	0	0	11395846	0	2542	0	0	0	16396	0	3346102	0	27173	0	3392213	0	67.83	0	27258123	0	119302	2926754	24.532312953681	40184895.0	28682372.0	2058860.0	1424249.0	100779.0	5898.0	0.0	11395846.0	27258123.0	71.4	5.1	3.5	0.3	0.0	0.0	28.4	67.8	101	101	101.00	38	4058674395	29.4	21.2	21.2	28.1	0.0	35.4	18.8	bulk
896148	ERR525592	ERP005997	ERS472803	ERX490824	ERA315790	UCSF	ArrayExpress	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Illumina HiSeq 2500 paired end sequencing; RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes		Brown_biolrepli1	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	250	17.3	Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Illumina HiSeq 2500	Alias;;E-MTAB-2624:Brown_biolrepli1|Broker name;;ArrayExpress|cell type;;claical brown adipocyte|Description;;Protocols: Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2|ENA checklist;;ERC000011|INSDC center alias;;UCSF|INSDC center name;;University of California, San Francisco|INSDC first public;;2015-02-16T17:01:59Z|INSDC last update;;2018-03-08T18:23:10Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS472803|SRA accession;;ERS472803|Title;;Brown_biolrepli1	Experimental Factor: cell type;;Classical brown adipocyte	202	SAMEA2579681	E-MTAB-2624:Brown_biolrepli1	9444402536	46754468	2015-02-17 06:11:42	6358686090	9444402536	46754468	2	46754468	index:0,count:46754468,average:101,stdev:0|index:1,count:46754468,average:101,stdev:0	E-MTAB-2624:RNA1_read		ArrayExpress	UCSF Genomics Core	in_mesa	25774848	53.15	0.97	0.07	5446652802	5494651048	5223130405	5298162690	100.88	101.44	35398606	34355770	181.015	413.635	113	240058	87.3	91.58	37933435	30903046	37933435	30903046	85.53	86.86	37933435	30276452	37933435	29309961	363466229	6.67	4.96	0	3.54	0	0.16	0	0.02	0	0.00	0	24.11	0	35398606	0	202	0	194.94	0	2.24	0	0.03	0	2.15	0	0.02	0	331.98	0	0.55	0	2319405	0	46754468	0	1653684	0	75898	0	7200	0	0	0	11272764	0	2880	0	0	0	21115	0	4283777	0	28981	0	4336753	0	72.17	0	33744922	0	130938	3800154	29.022545021308	46754468.0	35398606.0	2319405.0	1653684.0	75898.0	7200.0	0.0	11272764.0	33744922.0	75.7	5.0	3.5	0.2	0.0	0.0	24.1	72.2	101	101	101.00	38	4722201268	29.0	21.4	21.5	28.1	0.0	35.4	18.9	bulk
896156	ERR525593	ERP005997	ERS472805	ERX490826	ERA315790	UCSF	ArrayExpress	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Illumina HiSeq 2500 paired end sequencing; RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Protocols: Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Beige_biolrepli2	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	372	33.5	Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Illumina HiSeq 2500	alias;;E-MTAB-2624:Beige_biolrepli2|broker name;;ArrayExpress|cell type;;rosiglitazone-treated adipocyte (beige cell)|ENA checklist;;ERC000011|INSDC center alias;;UCSF|INSDC center name;;University of California, San Francisco|INSDC first public;;2015-02-16T17:01:59Z|INSDC last update;;2018-03-08T18:23:10Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS472805|SRA accession;;ERS472805|title;;Beige_biolrepli2	Experimental Factor: cell type;;rosiglitazone-treated adipocyte (beige cell)	202	SAMEA2579683	E-MTAB-2624:Beige_biolrepli2	14372387062	71150431	2015-02-17 06:11:43	9641746184	14372387062	71150431	2	71150431	index:0,count:71150431,average:101,stdev:0|index:1,count:71150431,average:101,stdev:0	E-MTAB-2624:RNA6_read		ArrayExpress	UCSF Genomics Core	in_mesa	25774848	55.76	1.04	0.07	9179701788	9223579306	8834755920	8919721754	100.48	100.96	57379432	55485007	191.261	452.877	124	341783	88.66	92.51	61071796	50872565	61071796	50872565	87.74	88.73	61071796	50346189	61071796	48789272	550711077	6.00	5.42	0	3.36	0	0.24	0	0.02	0	0.00	0	19.10	0	57379432	0	202	0	195.88	0	2.04	0	0.03	0	2.45	0	0.02	0	256.65	0	0.53	0	3855628	0	71150431	0	2390272	0	172653	0	11088	0	0	0	13587258	0	5661	0	0	0	38674	0	7417026	0	49480	0	7510841	0	77.29	0	54989160	0	152618	6794222	44.517828827530	71150431.0	57379432.0	3855628.0	2390272.0	172653.0	11088.0	0.0	13587258.0	54989160.0	80.6	5.4	3.4	0.2	0.0	0.0	19.1	77.3	101	101	101.00	38	7186193531	29.2	21.0	21.1	28.7	0.0	35.6	19.1	bulk
896164	ERR525594	ERP005997	ERS472806	ERX490827	ERA315790	UCSF	ArrayExpress	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Classical brown adipocytes in interscapular BAT (Myf-5 derived) and "inducible" beige cells in WAT (non-Myf-5 derived) have distinct developmental origins, although both cell types have morphological and biochemical characteristics of brown fat such as the expression of UCP1. This raises an important question as to how similar the two types of brown adipocytes are at molecular and functional levels. To this end, we employed RNA-seq to systematically determine the transcriptional signatures unique to each cell type.	Illumina HiSeq 2500 paired end sequencing; RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	RNA-seq comparison of primary mouse classical brown, beige, and white adipocytes	Protocols: Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	White_biolrepli2	RNA-Seq	TRANSCRIPTOMIC	RANDOM PCR	paired	391	35.5	Primary stromal vascular (SV) cells were isolated from inguinal WAT or from interscapular BAT of the same C57BL/6 mice using Collagenase D (1.5 u/ml) and Dispase II (2.4 u/ml). To clearly define the molecular signatures of PPAR-gamma ligand-induced beige cells, we used C57BL/6 mice that possess less beige cells in the absence of environmental stimuli. SV cells were plated in collagen coated culture dishes in DMEM/F12 medium (D-glucose 17.51 mM) and differentiated as described previously (DOI: 10.1371/journal.pone.0049452). Beige cells were induced by a specific PPAR-gamma agonist rosiglitazone (1uM). RiboZol reagent (AMRESCO) following the manufacturer's protocol Ultralow DR library kit (NuGEN): www.nugeninc.com/nugen/index.cfm/products/cs/ngs/rna-seq-v2	Illumina HiSeq 2500	alias;;E-MTAB-2624:White_biolrepli2|broker name;;ArrayExpress|cell type;;inguinal white adipocyte|ENA checklist;;ERC000011|INSDC center alias;;UCSF|INSDC center name;;University of California, San Francisco|INSDC first public;;2015-02-16T17:01:59Z|INSDC last update;;2018-03-08T18:23:10Z|INSDC status;;public|organism;;Mus musculus|Sample Name;;ERS472806|SRA accession;;ERS472806|title;;White_biolrepli2	Experimental Factor: cell type;;inguinal white adipocyte	202	SAMEA2579684	E-MTAB-2624:White_biolrepli2	7531707158	37285679	2015-02-17 06:11:43	5093935817	7531707158	37285679	2	37285679	index:0,count:37285679,average:101,stdev:0|index:1,count:37285679,average:101,stdev:0	E-MTAB-2624:RNA4_read		ArrayExpress	UCSF Genomics Core	in_mesa	25774848	35.4	1.53	0.09	4755535538	4795339132	4560492548	4624282308	100.84	101.4	29266680	27798805	202.241	608.074	124	157771	83.62	87.67	31559100	24472430	31559100	24472430	81.03	82.27	31559100	23713727	31559100	22965718	491934716	10.34	5.30	0	3.63	0	0.30	0	0.13	0	0.00	0	21.08	0	29266680	0	202	0	195.60	0	2.22	0	0.03	0	2.47	0	0.03	0	200.94	0	0.58	0	1975939	0	37285679	0	1352707	0	112683	0	48128	0	0	0	7858188	0	3657	0	0	0	28169	0	5295806	0	28383	0	5356015	0	74.87	0	27913973	0	143901	4927948	34.245404826930	37285679.0	29266680.0	1975939.0	1352707.0	112683.0	48128.0	0.0	7858188.0	27913973.0	78.5	5.3	3.6	0.3	0.1	0.0	21.1	74.9	101	101	101.00	38	3765853579	27.8	22.2	22.6	27.4	0.0	35.3	18.6	bulk
1671816	ERR789828	ERP009875	ERS685125	ERX780123	ERA419903	Massachusetts Institute of Technology		RNA-seq of Pdx1+ mouse Islet during development	The aim of this experiment was to observe the transcriptional profile of mouse islets during development (at timepoints E18.5, P10, Adult). RNA-seq was performed on the same RNA that was used for an earlier microarray. No MARIS sorting.	The aim of this experiment was to observe the transcriptional profile of mouse islets during development (at timepoints E18.5, P10, Adult). RNA-seq was performed on the same RNA that was used for an earlier microarray. No MARIS sorting.	Illumina HiSeq 2000 paired end sequencing; RNA-seq of Pdx1+ mouse Islet during development	RNA-seq of Pdx1+ mouse Islet during development	Protocols: Isolated islets were GFP sorted using mouse lines that expressed GFP with a minimal Pdx1 promoter. No MARIS sorting. After sorting, cells were pelleted by centrifugation at 3000 g for 5min at 4C. The supernatant was discarded. Total RNA was isolated from the pellet using the RecoverAll Total Nucleic Acid Isolation kit (Ambion), starting at the protease digestion stage of manufacturer-recommended protocol. The following modification to the isolation procedure was made: instead of incubating cells in digestion buffer for 15 minutes at 50C and 15 minutes at 80C, we carried out the incubation for 3 hours at 50C. Cell lysates were frozen at -80C overnight before continuing the RNA isolation by the manufacturer's instructions. NA	Mouse Islet P10 RNA	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	400	200	Isolated islets were GFP sorted using mouse lines that expressed GFP with a minimal Pdx1 promoter. No MARIS sorting. After sorting, cells were pelleted by centrifugation at 3000 g for 5min at 4C. The supernatant was discarded. Total RNA was isolated from the pellet using the RecoverAll Total Nucleic Acid Isolation kit (Ambion), starting at the protease digestion stage of manufacturer-recommended protocol. The following modification to the isolation procedure was made: instead of incubating cells in digestion buffer for 15 minutes at 50C and 15 minutes at 80C, we carried out the incubation for 3 hours at 50C. Cell lysates were frozen at -80C overnight before continuing the RNA isolation by the manufacturer's instructions. NA	Illumina HiSeq 2000	alias;;E-MTAB-3417:P10 pancreas islets|broker name;;ArrayExpress|developmental stage;;P10|ENA checklist;;ERC000011|INSDC center alias;;Massachusetts Institute of Technology|INSDC center name;;Massachusetts Institute of Technology|INSDC first public;;2015-03-17T16:40:38Z|INSDC last update;;2018-03-08T23:43:19Z|INSDC status;;public|organism part;;islet|organism;;Mus musculus|Sample Name;;ERS685125|SRA accession;;ERS685125|strain or line;;Pdx1 minimal promoter-GFP on mixed/outbred background|title;;P10 pancreas islets	Experimental Factor: developmental stage;;P10	200	SAMEA3307738	E-MTAB-3417:P10 pancreas islets	8026981600	40134908	2015-03-18 05:46:06	5409789509	8026981600	40134908	2	40134908	index:0,count:40134908,average:100,stdev:0|index:1,count:40134908,average:100,stdev:0	E-MTAB-3417:RNAseq_Mouse_Islet_P10	Massachusetts Institute of Technology	ArrayExpress	MIT BioMicroCenter			4.66	2.93	0.09	5076545323	5048197037	4790251276	4783428244	99.44	99.86	31273003	29946391	180.144	458.862	157	376766	87.48	92.75	33894365	27356274	33894365	27356274	89.52	89.83	33894365	27995753	33894365	26495989	321955261	6.34	0.40	0	4.43	0	0.24	0	0.06	0	0.00	0	21.78	0	31273003	0	200	0	197.18	0	2.10	0	0.01	0	1.93	0	0.01	0	240.41	0	0.81	0	160250	0	40134908	0	1777885	0	96872	0	22922	0	0	0	8742111	0	7758	0	0	0	71522	0	13085164	0	31705	0	13196149	0	73.49	0	29495118	0	119348	12236404	102.527097228274	40134908.0	31273003.0	160250.0	1777885.0	96872.0	22922.0	0.0	8742111.0	29495118.0	77.9	0.4	4.4	0.2	0.1	0.0	21.8	73.5	100	100	100.00	38	4013490800	24.2	25.7	25.2	24.7	0.2	34.8	18.5	bulk
1671832	ERR789829	ERP009875	ERS685124	ERX780122	ERA419903	Massachusetts Institute of Technology		RNA-seq of Pdx1+ mouse Islet during development	The aim of this experiment was to observe the transcriptional profile of mouse islets during development (at timepoints E18.5, P10, Adult). RNA-seq was performed on the same RNA that was used for an earlier microarray. No MARIS sorting.	The aim of this experiment was to observe the transcriptional profile of mouse islets during development (at timepoints E18.5, P10, Adult). RNA-seq was performed on the same RNA that was used for an earlier microarray. No MARIS sorting.	Illumina HiSeq 2000 paired end sequencing; RNA-seq of Pdx1+ mouse Islet during development	RNA-seq of Pdx1+ mouse Islet during development	Protocols: Isolated islets were GFP sorted using mouse lines that expressed GFP with a minimal Pdx1 promoter. No MARIS sorting. After sorting, cells were pelleted by centrifugation at 3000 g for 5min at 4C. The supernatant was discarded. Total RNA was isolated from the pellet using the RecoverAll Total Nucleic Acid Isolation kit (Ambion), starting at the protease digestion stage of manufacturer-recommended protocol. The following modification to the isolation procedure was made: instead of incubating cells in digestion buffer for 15 minutes at 50C and 15 minutes at 80C, we carried out the incubation for 3 hours at 50C. Cell lysates were frozen at -80C overnight before continuing the RNA isolation by the manufacturer's instructions. NA	Mouse Islet Adult RNA	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	400	200	Isolated islets were GFP sorted using mouse lines that expressed GFP with a minimal Pdx1 promoter. No MARIS sorting. After sorting, cells were pelleted by centrifugation at 3000 g for 5min at 4C. The supernatant was discarded. Total RNA was isolated from the pellet using the RecoverAll Total Nucleic Acid Isolation kit (Ambion), starting at the protease digestion stage of manufacturer-recommended protocol. The following modification to the isolation procedure was made: instead of incubating cells in digestion buffer for 15 minutes at 50C and 15 minutes at 80C, we carried out the incubation for 3 hours at 50C. Cell lysates were frozen at -80C overnight before continuing the RNA isolation by the manufacturer's instructions. NA	Illumina HiSeq 2000	alias;;E-MTAB-3417:Adult pancreas islets|broker name;;ArrayExpress|developmental stage;;adult|ENA checklist;;ERC000011|INSDC center alias;;Massachusetts Institute of Technology|INSDC center name;;Massachusetts Institute of Technology|INSDC first public;;2015-03-17T16:40:38Z|INSDC last update;;2018-03-08T23:43:19Z|INSDC status;;public|organism part;;islet|organism;;Mus musculus|Sample Name;;ERS685124|SRA accession;;ERS685124|strain or line;;Pdx1 minimal promoter-GFP on mixed/outbred background|title;;Adult pancreas islets	Experimental Factor: developmental stage;;adult	200	SAMEA3307737	E-MTAB-3417:Adult pancreas islets	20319963000	101599815	2015-03-18 05:46:07	13658982527	20319963000	101599815	2	101599815	index:0,count:101599815,average:100,stdev:0|index:1,count:101599815,average:100,stdev:0	E-MTAB-3417:RNAseq_Mouse_Islet_Adult	Massachusetts Institute of Technology	ArrayExpress	MIT BioMicroCenter			4.21	2.76	0.07	12753936690	12673804418	12072115149	12039576173	99.37	99.73	79487403	76161793	178.527	458.585	157	1008177	87.91	92.93	86263652	69875913	86263652	69875913	89.88	90.18	86263652	71444066	86263652	67804432	779027418	6.11	0.33	0	4.23	0	0.39	0	0.05	0	0.00	0	21.33	0	79487403	0	200	0	197.32	0	2.05	0	0.01	0	1.87	0	0.01	0	285.53	0	0.79	0	334617	0	101599815	0	4297283	0	396129	0	48858	0	0	0	21667425	0	16780	0	0	0	177566	0	33351001	0	78757	0	33624104	0	74.01	0	75190120	0	158320	31431805	198.533381758464	101599815.0	79487403.0	334617.0	4297283.0	396129.0	48858.0	0.0	21667425.0	75190120.0	78.2	0.3	4.2	0.4	0.0	0.0	21.3	74.0	100	100	100.00	38	10159981500	24.1	25.8	25.4	24.6	0.2	34.7	18.3	bulk
1671944	ERR789830	ERP009875	ERS685123	ERX780121	ERA419903	Massachusetts Institute of Technology		RNA-seq of Pdx1+ mouse Islet during development	The aim of this experiment was to observe the transcriptional profile of mouse islets during development (at timepoints E18.5, P10, Adult). RNA-seq was performed on the same RNA that was used for an earlier microarray. No MARIS sorting.	The aim of this experiment was to observe the transcriptional profile of mouse islets during development (at timepoints E18.5, P10, Adult). RNA-seq was performed on the same RNA that was used for an earlier microarray. No MARIS sorting.	RNA-seq of Pdx1+ mouse Islet during development	RNA-seq of Pdx1+ mouse Islet during development		Mouse Islet E18.5 RNA	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	400	200	Isolated islets were GFP sorted using mouse lines that expressed GFP with a minimal Pdx1 promoter. No MARIS sorting. After sorting, cells were pelleted by centrifugation at 3000 g for 5min at 4C. The supernatant was discarded. Total RNA was isolated from the pellet using the RecoverAll Total Nucleic Acid Isolation kit (Ambion), starting at the protease digestion stage of manufacturer-recommended protocol. The following modification to the isolation procedure was made: instead of incubating cells in digestion buffer for 15 minutes at 50C and 15 minutes at 80C, we carried out the incubation for 3 hours at 50C. Cell lysates were frozen at -80C overnight before continuing the RNA isolation by the manufacturer's instructions. NA	Illumina HiSeq 2000	Alias;;E-MTAB-3417:E18.5 pancreas islets|Broker name;;ArrayExpress|Description;;Protocols: Isolated islets were GFP sorted using mouse lines that expressed GFP with a minimal Pdx1 promoter. No MARIS sorting. After sorting, cells were pelleted by centrifugation at 3000 g for 5min at 4C. The supernatant was discarded. Total RNA was isolated from the pellet using the RecoverAll Total Nucleic Acid Isolation kit (Ambion), starting at the protease digestion stage of manufacturer-recommended protocol. The following modification to the isolation procedure was made: instead of incubating cells in digestion buffer for 15 minutes at 50C and 15 minutes at 80C, we carried out the incubation for 3 hours at 50C. Cell lysates were frozen at -80C overnight before continuing the RNA isolation by the manufacturer's instructions. NA|developmental stage;;E18.5|ENA checklist;;ERC000011|INSDC center alias;;Massachusetts Institute of Technology|INSDC center name;;Massachusetts Institute of Technology|INSDC first public;;2015-03-17T16:40:38Z|INSDC last update;;2018-03-08T23:43:19Z|INSDC status;;public|organism part;;islet|organism;;Mus musculus|Sample Name;;ERS685123|SRA accession;;ERS685123|strain or line;;Pdx1 minimal promoter-GFP on mixed/outbred background|Title;;E18.5 pancreas islets	Experimental Factor: developmental stage;;E18.5	200	SAMEA3308494	E-MTAB-3417:E18.5 pancreas islets	12748842000	63744210	2015-03-18 05:46:07	8556444576	12748842000	63744210	2	63744210	index:0,count:63744210,average:100,stdev:0|index:1,count:63744210,average:100,stdev:0	E-MTAB-3417:RNAseq_Mouse_Islet_E18_5	Massachusetts Institute of Technology	ArrayExpress	MIT BioMicroCenter			2.96	3.41	0.09	8201917178	8205999714	7751274974	7790372221	100.05	100.5	49745350	47225761	185.122	506.502	157	532373	87.32	92.47	54060547	43439787	54060547	43439787	88.42	88.79	54060547	43982872	54060547	41708942	551510621	6.72	0.38	0	4.35	0	0.19	0	0.06	0	0.00	0	21.71	0	49745350	0	200	0	197.22	0	2.12	0	0.01	0	1.84	0	0.01	0	356.89	0	0.80	0	243671	0	63744210	0	2770719	0	121727	0	38302	0	0	0	13838831	0	13410	0	0	0	126540	0	21311774	0	51344	0	21503068	0	73.69	0	46974631	0	164537	20008404	121.604283535010	63744210.0	49745350.0	243671.0	2770719.0	121727.0	38302.0	0.0	13838831.0	46974631.0	78.0	0.4	4.3	0.2	0.1	0.0	21.7	73.7	100	100	100.00	38	6374421000	24.4	25.5	25.1	24.8	0.2	34.8	18.4	bulk
208652	ERR1121786	ERP013145	ERS957184	ERX1201128	ERA532290		European Nucleotide Archive	RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.	Hematopoietic stem cells (HSC) has unique characteristic to self-renew and replenish the entire blood system. During development, HSCs originate in the aorta-gonads-mesonephros (AGM), from where they migrate into the fetal liver at E11. Once resided in fetal liver HSC proliferate extensively to make sufficient stem pool for adult life. Around birth, HSC from FL migrate to bone marrow (BM) which is major site of hematopoiesis for whole adult life. In contrast to FL HSC, BM HSC remain quiescence state and give rise to different blood cell type under normal homeostatic condition. It has shown that FL HSCs display significantly faster expansion kinetics when transplanted into lethally irradiate mice, compared with HSCs from adult BM. However, detail molecular mechanism behind the difference in self-renewal potential is not fully understood. Here, we present the genome-wide transcriptome analysis of more proliferative FL HSC compared to quiescent BM HSC using RNA-Seq platform.	Hematopoietic stem cells (HSC) has unique characteristic to self-renew and replenish the entire blood system. During development, HSCs originate in the aorta-gonads-mesonephros (AGM), from where they migrate into the fetal liver at E11. Once resided in fetal liver HSC proliferate extensively to make sufficient stem pool for adult life. Around birth, HSC from FL migrate to bone marrow (BM) which is major site of hematopoiesis for whole adult life. In contrast to FL HSC, BM HSC remain quiescence state and give rise to different blood cell type under normal homeostatic condition. It has shown that FL HSCs display significantly faster expansion kinetics when transplanted into lethally irradiate mice, compared with HSCs from adult BM. However, detail molecular mechanism behind the difference in self-renewal potential is not fully understood. Here, we present the genome-wide transcriptome analysis of more proliferative FL HSC compared to quiescent BM HSC using RNA-Seq platform.	Illumina HiSeq 2000 paired end sequencing; RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.	RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.		BM_HSC_rep  1	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	170	20	Total adult bone marrow (ABM) cells were flushed from femurs and tibiae of male C57BL/6J mice, pooled, washed twice with phosphatebuffered saline (PBS; Gibco Invitrogen, CA) containing 0.1% bovine serum albumin (BSA; Sigma). Lineage negative cell isolation was performed using lineage cell depletion kit (Miltenyi Biotec, Germany). To isolate LT-HSCs from ABM, resulting Lin cells were stained with FITC conjugated antiSca1, PE conjugated antickit, APC conjugated antilineage antibody cocktail (BD Pharmingen, San Diego, CA), PerCP/Cy5.5 conjugated anti-CD150 and APC conjugated anti-CD48 antibodies. Cells were incubated on ice for 30 minutes. FL tissues were obtained from C57BL/6J embryos dissected at embryonic day (E) 14.5 (14 days after vaginal plug was observed). Ter-119 positive erythrocytes and erythrocyte progenitors were depleted using MACS columns (Miltenyi Biotec, Germany) and stained with Alexa Fluor 488 conjugated anti-lineage antibody cocktail (containing CD4, CD5, CD8a, CD45R, Ter-119, GR-1 antibodies), PE conjugated anti-CD11b, APC conjugated anti-Sca-1, PE-Cy7 conjugated anti-CD150 and Alexa Fluor 488 conjugated anti-CD48. Cells were incubated on ice for 30 minutes. After incubation of cells with antibodies, cells were washed once with PBS. HSCs were sorted by fluorescence-activated cell sorting (FACS), using a FACS ARIAIII (Becton Dickinson). HSCs were directly sorted in QIAzol lysis buffer from miRNeasy Micro Kit (QIAGEN) and stored at -80c until isolation. Fraction of cells were used to checked the purity which was >95 percent. Total RNA isolation was isolated from the indicated populations using miRNeasy Micro Kit (QIAGEN) according to the manufacturer's protocol. DNase treatment was performed using RNAse-free DNase Set (Qiagen). Total RNA from FL and BM HSC was amplified using Ovation RNA-seq V2 system (NuGen technologies, CA) as per manufacturers instructions. Amplified cDNA (1ug) was sheared using the Covaris system (Covaris, MA) and fragments of 200bp (180-220bp) selected to construct a cDNA library. The fragmented DNA is combined with End Repair Mix, incubate at 20C for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit(Qiagen),then add A-Tailing Mix, incubate at 37C for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 20C for 15 min. Adapter-ligated DNA is selected by running a 2% agarose gel to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Several rounds of PCR amplification with PCR Primer Cocktail and PCR Master Mix are performed to enrich the Adapter-ligated DNA fragments. Then the PCR products are purified with Ampure XP Beads (AGENCOURT). The Qualified libraries will amplify on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3cBotHS,Illumina). And the amplified flowcell will be subjected to 2*90 bp paired-end sequencing on the HiSeq 2000 System (TruSeq SBS KIT-HS V3,Illumina).	Illumina HiSeq 2000	age;;8 week|Alias;;E-MTAB-4034:BM_HSC_rep 1|Broker name;;ArrayExpress|cell type;;hematopoietic stem cell|Description;;Protocols: Total adult bone marrow (ABM) cells were flushed from femurs and tibiae of male C57BL/6J mice, pooled, washed twice with phosphatebuffered saline (PBS; Gibco Invitrogen, CA) containing 0.1% bovine serum albumin (BSA; Sigma). Lineage negative cell isolation was performed using lineage cell depletion kit (Miltenyi Biotec, Germany). To isolate LT-HSCs from ABM, resulting Lin cells were stained with FITC conjugated antiSca1, PE conjugated antickit, APC conjugated antilineage antibody cocktail (BD Pharmingen, San Diego, CA), PerCP/Cy5.5 conjugated anti-CD150 and APC conjugated anti-CD48 antibodies. Cells were incubated on ice for 30 minutes. FL tissues were obtained from C57BL/6J embryos dissected at embryonic day (E) 14.5 (14 days after vaginal plug was observed). Ter-119 positive erythrocytes and erythrocyte progenitors were depleted using MACS columns (Miltenyi Biotec, Germany) and stained with Alexa Fluor 488 conjugated anti-lineage antibody cocktail (containing CD4, CD5, CD8a, CD45R, Ter-119, GR-1 antibodies), PE conjugated anti-CD11b, APC conjugated anti-Sca-1, PE-Cy7 conjugated anti-CD150 and Alexa Fluor 488 conjugated anti-CD48. Cells were incubated on ice for 30 minutes. After incubation of cells with antibodies, cells were washed once with PBS. HSCs were sorted by fluorescence-activated cell sorting (FACS), using a FACS ARIAIII (Becton Dickinson). HSCs were directly sorted in QIAzol lysis buffer from miRNeasy Micro Kit (QIAGEN) and stored at -80c until isolation. Fraction of cells were used to checked the purity which was >95 percent. Total RNA isolation was isolated from the indicated populations using miRNeasy Micro Kit (QIAGEN) according to the manufacturer's protocol. DNAse treatment was performed using RNAse-free DNAse Set (Qiagen). Total RNA from FL and BM HSC was amplified using Ovation RNA-seq V2 system (NuGen technologies, CA) as per manufacturers instructions. Amplified cDNA (1ug) was sheared using the Covaris system (Covaris, MA) and fragments of 200bp (180-220bp) selected to construct a cDNA library. The fragmented DNA is combined with End Repair Mix, incubate at 20C for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit(Qiagen),then add A-Tailing Mix, incubate at 37C for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 20C for 15 min. Adapter-ligated DNA is selected by running a 2% agarose gel to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Several rounds of PCR amplification with PCR Primer Cocktail and PCR Master Mix are performed to enrich the Adapter-ligated DNA fragments. Then the PCR products are purified with Ampure XP Beads (AGENCOURT). The Qualified libraries will amplify on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3cBotHS,Illumina). And the amplified flowcell will be subjected to 2*90 bp paired-end sequencing on the HiSeq 2000 System (TruSeq SBS KIT-HS V3,Illumina).|ENA checklist;;ERC000011|genotype;;wild type genotype|INSDC center alias;;Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven|INSDC center name;;Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven|INSDC first public;;2015-11-29T17:01:16Z|INSDC last update;;2018-03-09T09:24:41Z|INSDC status;;public|organism part;;adult bone marrow|organism;;Mus musculus|phenotype;;lin- sca1+ ckit+ cd150+ cd48-|Sample Name;;ERS957184|SRA accession;;ERS957184|strain;;C57BL/6J|Title;;BM_HSC_rep 1	Experimental Factor: adult bone marrow;;organism part	180	SAMEA3650035	E-MTAB-4034:BM_HSC_rep 1	3520743480	19559686	2015-11-30 10:46:22	2543943719	3520743480	19559686	2	19559686	index:0,count:19559686,average:90,stdev:0|index:1,count:19559686,average:90,stdev:0	E-MTAB-4034:BM-LT-HSC_1_L1_	Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven	ArrayExpress	Illumina HiSeq2000 	in_mesa	26599326	7.05	2.47	0.1	3063112999	3030660298	2982158738	2959973179	98.94	99.26	18759829	18591103	167.221	287.135	166	487294	45.33	46.59	19655978	8504078	19655978	8504078	43.11	42.88	19655978	8087975	19655978	7827022	1581789085	51.64	5.38	0	2.59	0	0.18	0	0.20	0	0.00	0	3.71	0	18759829	0	180	0	177.14	0	2.26	0	0.01	0	1.96	0	0.01	0	521.59	0	0.35	0	1052297	0	19559686	0	507091	0	34622	0	38757	0	0	0	726478	0	2313	0	0	0	16173	0	2101902	0	16459	0	2136847	0	93.32	0	18252738	0	124609	2134750	17.131587606032	19559686.0	18759829.0	1052297.0	507091.0	34622.0	38757.0	0.0	726478.0	18252738.0	95.9	5.4	2.6	0.2	0.2	0.0	3.7	93.3	90	90	90.00	38	1760371740	26.9	23.0	23.2	26.9	0.0	35.5	21.0	bulk
208654	ERR1121787	ERP013145	ERS957185	ERX1201129	ERA532290		European Nucleotide Archive	RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.	Hematopoietic stem cells (HSC) has unique characteristic to self-renew and replenish the entire blood system. During development, HSCs originate in the aorta-gonads-mesonephros (AGM), from where they migrate into the fetal liver at E11. Once resided in fetal liver HSC proliferate extensively to make sufficient stem pool for adult life. Around birth, HSC from FL migrate to bone marrow (BM) which is major site of hematopoiesis for whole adult life. In contrast to FL HSC, BM HSC remain quiescence state and give rise to different blood cell type under normal homeostatic condition. It has shown that FL HSCs display significantly faster expansion kinetics when transplanted into lethally irradiate mice, compared with HSCs from adult BM. However, detail molecular mechanism behind the difference in self-renewal potential is not fully understood. Here, we present the genome-wide transcriptome analysis of more proliferative FL HSC compared to quiescent BM HSC using RNA-Seq platform.	Hematopoietic stem cells (HSC) has unique characteristic to self-renew and replenish the entire blood system. During development, HSCs originate in the aorta-gonads-mesonephros (AGM), from where they migrate into the fetal liver at E11. Once resided in fetal liver HSC proliferate extensively to make sufficient stem pool for adult life. Around birth, HSC from FL migrate to bone marrow (BM) which is major site of hematopoiesis for whole adult life. In contrast to FL HSC, BM HSC remain quiescence state and give rise to different blood cell type under normal homeostatic condition. It has shown that FL HSCs display significantly faster expansion kinetics when transplanted into lethally irradiate mice, compared with HSCs from adult BM. However, detail molecular mechanism behind the difference in self-renewal potential is not fully understood. Here, we present the genome-wide transcriptome analysis of more proliferative FL HSC compared to quiescent BM HSC using RNA-Seq platform.	Illumina HiSeq 2000 paired end sequencing; RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.	RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.		BM_HSC_rep  2	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	170	20	Total adult bone marrow (ABM) cells were flushed from femurs and tibiae of male C57BL/6J mice, pooled, washed twice with phosphatebuffered saline (PBS; Gibco Invitrogen, CA) containing 0.1% bovine serum albumin (BSA; Sigma). Lineage negative cell isolation was performed using lineage cell depletion kit (Miltenyi Biotec, Germany). To isolate LT-HSCs from ABM, resulting Lin cells were stained with FITC conjugated antiSca1, PE conjugated antickit, APC conjugated antilineage antibody cocktail (BD Pharmingen, San Diego, CA), PerCP/Cy5.5 conjugated anti-CD150 and APC conjugated anti-CD48 antibodies. Cells were incubated on ice for 30 minutes. FL tissues were obtained from C57BL/6J embryos dissected at embryonic day (E) 14.5 (14 days after vaginal plug was observed). Ter-119 positive erythrocytes and erythrocyte progenitors were depleted using MACS columns (Miltenyi Biotec, Germany) and stained with Alexa Fluor 488 conjugated anti-lineage antibody cocktail (containing CD4, CD5, CD8a, CD45R, Ter-119, GR-1 antibodies), PE conjugated anti-CD11b, APC conjugated anti-Sca-1, PE-Cy7 conjugated anti-CD150 and Alexa Fluor 488 conjugated anti-CD48. Cells were incubated on ice for 30 minutes. After incubation of cells with antibodies, cells were washed once with PBS. HSCs were sorted by fluorescence-activated cell sorting (FACS), using a FACS ARIAIII (Becton Dickinson). HSCs were directly sorted in QIAzol lysis buffer from miRNeasy Micro Kit (QIAGEN) and stored at -80c until isolation. Fraction of cells were used to checked the purity which was >95 percent. Total RNA isolation was isolated from the indicated populations using miRNeasy Micro Kit (QIAGEN) according to the manufacturer's protocol. DNase treatment was performed using RNAse-free DNase Set (Qiagen). Total RNA from FL and BM HSC was amplified using Ovation RNA-seq V2 system (NuGen technologies, CA) as per manufacturers instructions. Amplified cDNA (1ug) was sheared using the Covaris system (Covaris, MA) and fragments of 200bp (180-220bp) selected to construct a cDNA library. The fragmented DNA is combined with End Repair Mix, incubate at 20C for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit(Qiagen),then add A-Tailing Mix, incubate at 37C for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 20C for 15 min. Adapter-ligated DNA is selected by running a 2% agarose gel to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Several rounds of PCR amplification with PCR Primer Cocktail and PCR Master Mix are performed to enrich the Adapter-ligated DNA fragments. Then the PCR products are purified with Ampure XP Beads (AGENCOURT). The Qualified libraries will amplify on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3cBotHS,Illumina). And the amplified flowcell will be subjected to 2*90 bp paired-end sequencing on the HiSeq 2000 System (TruSeq SBS KIT-HS V3,Illumina).	Illumina HiSeq 2000	age;;8 week|Alias;;E-MTAB-4034:BM_HSC_rep 2|Broker name;;ArrayExpress|cell type;;hematopoietic stem cell|Description;;Protocols: Total adult bone marrow (ABM) cells were flushed from femurs and tibiae of male C57BL/6J mice, pooled, washed twice with phosphatebuffered saline (PBS; Gibco Invitrogen, CA) containing 0.1% bovine serum albumin (BSA; Sigma). Lineage negative cell isolation was performed using lineage cell depletion kit (Miltenyi Biotec, Germany). To isolate LT-HSCs from ABM, resulting Lin cells were stained with FITC conjugated antiSca1, PE conjugated antickit, APC conjugated antilineage antibody cocktail (BD Pharmingen, San Diego, CA), PerCP/Cy5.5 conjugated anti-CD150 and APC conjugated anti-CD48 antibodies. Cells were incubated on ice for 30 minutes. FL tissues were obtained from C57BL/6J embryos dissected at embryonic day (E) 14.5 (14 days after vaginal plug was observed). Ter-119 positive erythrocytes and erythrocyte progenitors were depleted using MACS columns (Miltenyi Biotec, Germany) and stained with Alexa Fluor 488 conjugated anti-lineage antibody cocktail (containing CD4, CD5, CD8a, CD45R, Ter-119, GR-1 antibodies), PE conjugated anti-CD11b, APC conjugated anti-Sca-1, PE-Cy7 conjugated anti-CD150 and Alexa Fluor 488 conjugated anti-CD48. Cells were incubated on ice for 30 minutes. After incubation of cells with antibodies, cells were washed once with PBS. HSCs were sorted by fluorescence-activated cell sorting (FACS), using a FACS ARIAIII (Becton Dickinson). HSCs were directly sorted in QIAzol lysis buffer from miRNeasy Micro Kit (QIAGEN) and stored at -80c until isolation. Fraction of cells were used to checked the purity which was >95 percent. Total RNA isolation was isolated from the indicated populations using miRNeasy Micro Kit (QIAGEN) according to the manufacturer's protocol. DNAse treatment was performed using RNAse-free DNAse Set (Qiagen). Total RNA from FL and BM HSC was amplified using Ovation RNA-seq V2 system (NuGen technologies, CA) as per manufacturers instructions. Amplified cDNA (1ug) was sheared using the Covaris system (Covaris, MA) and fragments of 200bp (180-220bp) selected to construct a cDNA library. The fragmented DNA is combined with End Repair Mix, incubate at 20C for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit(Qiagen),then add A-Tailing Mix, incubate at 37C for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 20C for 15 min. Adapter-ligated DNA is selected by running a 2% agarose gel to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Several rounds of PCR amplification with PCR Primer Cocktail and PCR Master Mix are performed to enrich the Adapter-ligated DNA fragments. Then the PCR products are purified with Ampure XP Beads (AGENCOURT). The Qualified libraries will amplify on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3cBotHS,Illumina). And the amplified flowcell will be subjected to 2*90 bp paired-end sequencing on the HiSeq 2000 System (TruSeq SBS KIT-HS V3,Illumina).|ENA checklist;;ERC000011|genotype;;wild type genotype|INSDC center alias;;Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven|INSDC center name;;Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven|INSDC first public;;2015-11-29T17:01:16Z|INSDC last update;;2018-03-09T09:24:45Z|INSDC status;;public|organism part;;adult bone marrow|organism;;Mus musculus|phenotype;;lin- sca1+ ckit+ cd150+ cd48-|Sample Name;;ERS957185|SRA accession;;ERS957185|strain;;C57BL/6J|Title;;BM_HSC_rep 2	Experimental Factor: adult bone marrow;;organism part	180	SAMEA3650036	E-MTAB-4034:BM_HSC_rep 2	3477643560	19320242	2015-11-30 10:46:22	2459057074	3477643560	19320242	2	19320242	index:0,count:19320242,average:90,stdev:0|index:1,count:19320242,average:90,stdev:0	E-MTAB-4034:BM-LT-HSC_2_L1_	Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven	ArrayExpress	Illumina HiSeq2000 	in_mesa	26599326	7.88	2.31	0.09	3036948120	3005523804	2953276902	2932904487	98.97	99.31	18529076	18386513	166.780	280.417	166	597469	47.98	49.37	19440583	8890647	19440583	8890647	45.33	45.22	19440583	8399621	19440583	8144371	1481767768	48.79	5.11	0	2.69	0	0.16	0	0.18	0	0.00	0	3.76	0	18529076	0	180	0	177.03	0	2.56	0	0.01	0	2.22	0	0.01	0	336.00	0	0.39	0	987718	0	19320242	0	520462	0	31793	0	33826	0	0	0	725547	0	1925	0	0	0	15994	0	2094290	0	15309	0	2127518	0	93.21	0	18008614	0	122160	2145607	17.563907989522	19320242.0	18529076.0	987718.0	520462.0	31793.0	33826.0	0.0	725547.0	18008614.0	95.9	5.1	2.7	0.2	0.2	0.0	3.8	93.2	90	90	90.00	38	1738821780	26.9	23.0	23.3	26.8	0.0	35.7	20.7	bulk
208656	ERR1121788	ERP013145	ERS957186	ERX1201130	ERA532290		European Nucleotide Archive	RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.	Hematopoietic stem cells (HSC) has unique characteristic to self-renew and replenish the entire blood system. During development, HSCs originate in the aorta-gonads-mesonephros (AGM), from where they migrate into the fetal liver at E11. Once resided in fetal liver HSC proliferate extensively to make sufficient stem pool for adult life. Around birth, HSC from FL migrate to bone marrow (BM) which is major site of hematopoiesis for whole adult life. In contrast to FL HSC, BM HSC remain quiescence state and give rise to different blood cell type under normal homeostatic condition. It has shown that FL HSCs display significantly faster expansion kinetics when transplanted into lethally irradiate mice, compared with HSCs from adult BM. However, detail molecular mechanism behind the difference in self-renewal potential is not fully understood. Here, we present the genome-wide transcriptome analysis of more proliferative FL HSC compared to quiescent BM HSC using RNA-Seq platform.	Hematopoietic stem cells (HSC) has unique characteristic to self-renew and replenish the entire blood system. During development, HSCs originate in the aorta-gonads-mesonephros (AGM), from where they migrate into the fetal liver at E11. Once resided in fetal liver HSC proliferate extensively to make sufficient stem pool for adult life. Around birth, HSC from FL migrate to bone marrow (BM) which is major site of hematopoiesis for whole adult life. In contrast to FL HSC, BM HSC remain quiescence state and give rise to different blood cell type under normal homeostatic condition. It has shown that FL HSCs display significantly faster expansion kinetics when transplanted into lethally irradiate mice, compared with HSCs from adult BM. However, detail molecular mechanism behind the difference in self-renewal potential is not fully understood. Here, we present the genome-wide transcriptome analysis of more proliferative FL HSC compared to quiescent BM HSC using RNA-Seq platform.	Illumina HiSeq 2000 paired end sequencing; RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.	RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.		FL_HSC_E14.5_rep 1	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	170	20	Total adult bone marrow (ABM) cells were flushed from femurs and tibiae of male C57BL/6J mice, pooled, washed twice with phosphatebuffered saline (PBS; Gibco Invitrogen, CA) containing 0.1% bovine serum albumin (BSA; Sigma). Lineage negative cell isolation was performed using lineage cell depletion kit (Miltenyi Biotec, Germany). To isolate LT-HSCs from ABM, resulting Lin cells were stained with FITC conjugated antiSca1, PE conjugated antickit, APC conjugated antilineage antibody cocktail (BD Pharmingen, San Diego, CA), PerCP/Cy5.5 conjugated anti-CD150 and APC conjugated anti-CD48 antibodies. Cells were incubated on ice for 30 minutes. FL tissues were obtained from C57BL/6J embryos dissected at embryonic day (E) 14.5 (14 days after vaginal plug was observed). Ter-119 positive erythrocytes and erythrocyte progenitors were depleted using MACS columns (Miltenyi Biotec, Germany) and stained with Alexa Fluor 488 conjugated anti-lineage antibody cocktail (containing CD4, CD5, CD8a, CD45R, Ter-119, GR-1 antibodies), PE conjugated anti-CD11b, APC conjugated anti-Sca-1, PE-Cy7 conjugated anti-CD150 and Alexa Fluor 488 conjugated anti-CD48. Cells were incubated on ice for 30 minutes. After incubation of cells with antibodies, cells were washed once with PBS. HSCs were sorted by fluorescence-activated cell sorting (FACS), using a FACS ARIAIII (Becton Dickinson). HSCs were directly sorted in QIAzol lysis buffer from miRNeasy Micro Kit (QIAGEN) and stored at -80c until isolation. Fraction of cells were used to checked the purity which was >95 percent. Total RNA isolation was isolated from the indicated populations using miRNeasy Micro Kit (QIAGEN) according to the manufacturer's protocol. DNase treatment was performed using RNAse-free DNase Set (Qiagen). Total RNA from FL and BM HSC was amplified using Ovation RNA-seq V2 system (NuGen technologies, CA) as per manufacturers instructions. Amplified cDNA (1ug) was sheared using the Covaris system (Covaris, MA) and fragments of 200bp (180-220bp) selected to construct a cDNA library. The fragmented DNA is combined with End Repair Mix, incubate at 20C for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit(Qiagen),then add A-Tailing Mix, incubate at 37C for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 20C for 15 min. Adapter-ligated DNA is selected by running a 2% agarose gel to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Several rounds of PCR amplification with PCR Primer Cocktail and PCR Master Mix are performed to enrich the Adapter-ligated DNA fragments. Then the PCR products are purified with Ampure XP Beads (AGENCOURT). The Qualified libraries will amplify on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3cBotHS,Illumina). And the amplified flowcell will be subjected to 2*90 bp paired-end sequencing on the HiSeq 2000 System (TruSeq SBS KIT-HS V3,Illumina).	Illumina HiSeq 2000	age;;embryonic day 14.5|Alias;;E-MTAB-4034:FL_HSC_E14.5_rep 1|Broker name;;ArrayExpress|cell type;;hematopoietic stem cell|Description;;Protocols: Total adult bone marrow (ABM) cells were flushed from femurs and tibiae of male C57BL/6J mice, pooled, washed twice with phosphatebuffered saline (PBS; Gibco Invitrogen, CA) containing 0.1% bovine serum albumin (BSA; Sigma). Lineage negative cell isolation was performed using lineage cell depletion kit (Miltenyi Biotec, Germany). To isolate LT-HSCs from ABM, resulting Lin cells were stained with FITC conjugated antiSca1, PE conjugated antickit, APC conjugated antilineage antibody cocktail (BD Pharmingen, San Diego, CA), PerCP/Cy5.5 conjugated anti-CD150 and APC conjugated anti-CD48 antibodies. Cells were incubated on ice for 30 minutes. FL tissues were obtained from C57BL/6J embryos dissected at embryonic day (E) 14.5 (14 days after vaginal plug was observed). Ter-119 positive erythrocytes and erythrocyte progenitors were depleted using MACS columns (Miltenyi Biotec, Germany) and stained with Alexa Fluor 488 conjugated anti-lineage antibody cocktail (containing CD4, CD5, CD8a, CD45R, Ter-119, GR-1 antibodies), PE conjugated anti-CD11b, APC conjugated anti-Sca-1, PE-Cy7 conjugated anti-CD150 and Alexa Fluor 488 conjugated anti-CD48. Cells were incubated on ice for 30 minutes. After incubation of cells with antibodies, cells were washed once with PBS. HSCs were sorted by fluorescence-activated cell sorting (FACS), using a FACS ARIAIII (Becton Dickinson). HSCs were directly sorted in QIAzol lysis buffer from miRNeasy Micro Kit (QIAGEN) and stored at -80c until isolation. Fraction of cells were used to checked the purity which was >95 percent. Total RNA isolation was isolated from the indicated populations using miRNeasy Micro Kit (QIAGEN) according to the manufacturer's protocol. DNAse treatment was performed using RNAse-free DNAse Set (Qiagen). Total RNA from FL and BM HSC was amplified using Ovation RNA-seq V2 system (NuGen technologies, CA) as per manufacturers instructions. Amplified cDNA (1ug) was sheared using the Covaris system (Covaris, MA) and fragments of 200bp (180-220bp) selected to construct a cDNA library. The fragmented DNA is combined with End Repair Mix, incubate at 20C for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit(Qiagen),then add A-Tailing Mix, incubate at 37C for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 20C for 15 min. Adapter-ligated DNA is selected by running a 2% agarose gel to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Several rounds of PCR amplification with PCR Primer Cocktail and PCR Master Mix are performed to enrich the Adapter-ligated DNA fragments. Then the PCR products are purified with Ampure XP Beads (AGENCOURT). The Qualified libraries will amplify on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3cBotHS,Illumina). And the amplified flowcell will be subjected to 2*90 bp paired-end sequencing on the HiSeq 2000 System (TruSeq SBS KIT-HS V3,Illumina).|ENA checklist;;ERC000011|genotype;;wild type genotype|INSDC center alias;;Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven|INSDC center name;;Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven|INSDC first public;;2015-11-29T17:01:16Z|INSDC last update;;2018-03-09T09:24:45Z|INSDC status;;public|organism part;;fetus|organism;;Mus musculus|phenotype;;lin- sca1+ cd11b+ cd150+ cd48-|Sample Name;;ERS957186|SRA accession;;ERS957186|strain;;C57BL/6J|Title;;FL_HSC_E14.5_rep 1	Experimental Factor: fetus;;organism part	180	SAMEA3650037	E-MTAB-4034:FL_HSC_E14.5_rep 1	3558704220	19770579	2015-11-30 10:46:22	2456954434	3558704220	19770579	2	19770579	index:0,count:19770579,average:90,stdev:0|index:1,count:19770579,average:90,stdev:0	E-MTAB-4034:FL14.5_1_L1_	Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven	ArrayExpress	Illumina HiSeq2000 	in_mesa	26599326	7.87	2.28	0.1	3116867649	3108185862	3006873003	3013566490	99.72	100.22	18628905	18410422	173.335	311.369	172	518115	51.25	53.17	19803880	9547173	19803880	9547173	47.9	47.84	19803880	8922349	19803880	8590315	1393420214	44.71	6.68	0	3.40	0	0.20	0	0.15	0	0.00	0	5.42	0	18628905	0	180	0	176.21	0	3.08	0	0.02	0	2.64	0	0.02	0	352.35	0	0.38	0	1321442	0	19770579	0	672588	0	40357	0	30295	0	0	0	1071022	0	2251	0	0	0	18770	0	2437388	0	20860	0	2479269	0	90.82	0	17956317	0	132355	2510305	18.966453855162	19770579.0	18628905.0	1321442.0	672588.0	40357.0	30295.0	0.0	1071022.0	17956317.0	94.2	6.7	3.4	0.2	0.2	0.0	5.4	90.8	90	90	90.00	38	1779352110	26.3	23.5	23.8	26.4	0.0	36.1	22.0	bulk
208658	ERR1121789	ERP013145	ERS957187	ERX1201131	ERA532290		European Nucleotide Archive	RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.	Hematopoietic stem cells (HSC) has unique characteristic to self-renew and replenish the entire blood system. During development, HSCs originate in the aorta-gonads-mesonephros (AGM), from where they migrate into the fetal liver at E11. Once resided in fetal liver HSC proliferate extensively to make sufficient stem pool for adult life. Around birth, HSC from FL migrate to bone marrow (BM) which is major site of hematopoiesis for whole adult life. In contrast to FL HSC, BM HSC remain quiescence state and give rise to different blood cell type under normal homeostatic condition. It has shown that FL HSCs display significantly faster expansion kinetics when transplanted into lethally irradiate mice, compared with HSCs from adult BM. However, detail molecular mechanism behind the difference in self-renewal potential is not fully understood. Here, we present the genome-wide transcriptome analysis of more proliferative FL HSC compared to quiescent BM HSC using RNA-Seq platform.	Hematopoietic stem cells (HSC) has unique characteristic to self-renew and replenish the entire blood system. During development, HSCs originate in the aorta-gonads-mesonephros (AGM), from where they migrate into the fetal liver at E11. Once resided in fetal liver HSC proliferate extensively to make sufficient stem pool for adult life. Around birth, HSC from FL migrate to bone marrow (BM) which is major site of hematopoiesis for whole adult life. In contrast to FL HSC, BM HSC remain quiescence state and give rise to different blood cell type under normal homeostatic condition. It has shown that FL HSCs display significantly faster expansion kinetics when transplanted into lethally irradiate mice, compared with HSCs from adult BM. However, detail molecular mechanism behind the difference in self-renewal potential is not fully understood. Here, we present the genome-wide transcriptome analysis of more proliferative FL HSC compared to quiescent BM HSC using RNA-Seq platform.	Illumina HiSeq 2000 paired end sequencing; RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.	RNA-Seq analysis of LT-HSC isolated from fetal liver and adult bone marrow.		FL_HSC_E14.5_rep 2	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	170	20	Total adult bone marrow (ABM) cells were flushed from femurs and tibiae of male C57BL/6J mice, pooled, washed twice with phosphatebuffered saline (PBS; Gibco Invitrogen, CA) containing 0.1% bovine serum albumin (BSA; Sigma). Lineage negative cell isolation was performed using lineage cell depletion kit (Miltenyi Biotec, Germany). To isolate LT-HSCs from ABM, resulting Lin cells were stained with FITC conjugated antiSca1, PE conjugated antickit, APC conjugated antilineage antibody cocktail (BD Pharmingen, San Diego, CA), PerCP/Cy5.5 conjugated anti-CD150 and APC conjugated anti-CD48 antibodies. Cells were incubated on ice for 30 minutes. FL tissues were obtained from C57BL/6J embryos dissected at embryonic day (E) 14.5 (14 days after vaginal plug was observed). Ter-119 positive erythrocytes and erythrocyte progenitors were depleted using MACS columns (Miltenyi Biotec, Germany) and stained with Alexa Fluor 488 conjugated anti-lineage antibody cocktail (containing CD4, CD5, CD8a, CD45R, Ter-119, GR-1 antibodies), PE conjugated anti-CD11b, APC conjugated anti-Sca-1, PE-Cy7 conjugated anti-CD150 and Alexa Fluor 488 conjugated anti-CD48. Cells were incubated on ice for 30 minutes. After incubation of cells with antibodies, cells were washed once with PBS. HSCs were sorted by fluorescence-activated cell sorting (FACS), using a FACS ARIAIII (Becton Dickinson). HSCs were directly sorted in QIAzol lysis buffer from miRNeasy Micro Kit (QIAGEN) and stored at -80c until isolation. Fraction of cells were used to checked the purity which was >95 percent. Total RNA isolation was isolated from the indicated populations using miRNeasy Micro Kit (QIAGEN) according to the manufacturer's protocol. DNase treatment was performed using RNAse-free DNase Set (Qiagen). Total RNA from FL and BM HSC was amplified using Ovation RNA-seq V2 system (NuGen technologies, CA) as per manufacturers instructions. Amplified cDNA (1ug) was sheared using the Covaris system (Covaris, MA) and fragments of 200bp (180-220bp) selected to construct a cDNA library. The fragmented DNA is combined with End Repair Mix, incubate at 20C for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit(Qiagen),then add A-Tailing Mix, incubate at 37C for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 20C for 15 min. Adapter-ligated DNA is selected by running a 2% agarose gel to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Several rounds of PCR amplification with PCR Primer Cocktail and PCR Master Mix are performed to enrich the Adapter-ligated DNA fragments. Then the PCR products are purified with Ampure XP Beads (AGENCOURT). The Qualified libraries will amplify on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3cBotHS,Illumina). And the amplified flowcell will be subjected to 2*90 bp paired-end sequencing on the HiSeq 2000 System (TruSeq SBS KIT-HS V3,Illumina).	Illumina HiSeq 2000	age;;embryonic day 14.5|Alias;;E-MTAB-4034:FL_HSC_E14.5_rep 2|Broker name;;ArrayExpress|cell type;;hematopoietic stem cell|Description;;Protocols: Total adult bone marrow (ABM) cells were flushed from femurs and tibiae of male C57BL/6J mice, pooled, washed twice with phosphatebuffered saline (PBS; Gibco Invitrogen, CA) containing 0.1% bovine serum albumin (BSA; Sigma). Lineage negative cell isolation was performed using lineage cell depletion kit (Miltenyi Biotec, Germany). To isolate LT-HSCs from ABM, resulting Lin cells were stained with FITC conjugated antiSca1, PE conjugated antickit, APC conjugated antilineage antibody cocktail (BD Pharmingen, San Diego, CA), PerCP/Cy5.5 conjugated anti-CD150 and APC conjugated anti-CD48 antibodies. Cells were incubated on ice for 30 minutes. FL tissues were obtained from C57BL/6J embryos dissected at embryonic day (E) 14.5 (14 days after vaginal plug was observed). Ter-119 positive erythrocytes and erythrocyte progenitors were depleted using MACS columns (Miltenyi Biotec, Germany) and stained with Alexa Fluor 488 conjugated anti-lineage antibody cocktail (containing CD4, CD5, CD8a, CD45R, Ter-119, GR-1 antibodies), PE conjugated anti-CD11b, APC conjugated anti-Sca-1, PE-Cy7 conjugated anti-CD150 and Alexa Fluor 488 conjugated anti-CD48. Cells were incubated on ice for 30 minutes. After incubation of cells with antibodies, cells were washed once with PBS. HSCs were sorted by fluorescence-activated cell sorting (FACS), using a FACS ARIAIII (Becton Dickinson). HSCs were directly sorted in QIAzol lysis buffer from miRNeasy Micro Kit (QIAGEN) and stored at -80c until isolation. Fraction of cells were used to checked the purity which was >95 percent. Total RNA isolation was isolated from the indicated populations using miRNeasy Micro Kit (QIAGEN) according to the manufacturer's protocol. DNAse treatment was performed using RNAse-free DNAse Set (Qiagen). Total RNA from FL and BM HSC was amplified using Ovation RNA-seq V2 system (NuGen technologies, CA) as per manufacturers instructions. Amplified cDNA (1ug) was sheared using the Covaris system (Covaris, MA) and fragments of 200bp (180-220bp) selected to construct a cDNA library. The fragmented DNA is combined with End Repair Mix, incubate at 20C for 30 min. Purify the end-repaired DNA with QIAquick PCR Purification Kit(Qiagen),then add A-Tailing Mix, incubate at 37C for 30 min. Combine the purified Adenylate 3'Ends DNA, Adapter and Ligation Mix, incubate the ligation reaction at 20C for 15 min. Adapter-ligated DNA is selected by running a 2% agarose gel to recover the target fragments. Purify the gel with QIAquick Gel Extraction kit (QIAGEN). Several rounds of PCR amplification with PCR Primer Cocktail and PCR Master Mix are performed to enrich the Adapter-ligated DNA fragments. Then the PCR products are purified with Ampure XP Beads (AGENCOURT). The Qualified libraries will amplify on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3cBotHS,Illumina). And the amplified flowcell will be subjected to 2*90 bp paired-end sequencing on the HiSeq 2000 System (TruSeq SBS KIT-HS V3,Illumina).|ENA checklist;;ERC000011|genotype;;wild type genotype|INSDC center alias;;Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven|INSDC center name;;Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven|INSDC first public;;2015-11-29T17:01:16Z|INSDC last update;;2018-03-09T09:24:45Z|INSDC status;;public|organism part;;fetus|organism;;Mus musculus|phenotype;;lin- sca1+ cd11b+ cd150+ cd48-|Sample Name;;ERS957187|SRA accession;;ERS957187|strain;;C57BL/6J|Title;;FL_HSC_E14.5_rep 2	Experimental Factor: fetus;;organism part	180	SAMEA3650038	E-MTAB-4034:FL_HSC_E14.5_rep 2	3450886200	19171590	2015-11-30 10:46:22	2390862852	3450886200	19171590	2	19171590	index:0,count:19171590,average:90,stdev:0|index:1,count:19171590,average:90,stdev:0	E-MTAB-4034:FL14.5_2_L1_	Inter-departmental Stem Cell Institute, KU Leuven, Belgium. Department of Development and Regeneration, Stem Cell Biology and Embryology, KU Leuven	ArrayExpress	Illumina HiSeq2000 	in_mesa	26599326	6.91	2.4	0.09	2997463905	2979111106	2894836106	2889730778	99.39	99.82	18303987	18124503	167.790	281.110	164	552860	51.94	53.82	19418820	9506830	19418820	9506830	49.11	49.04	19418820	8989619	19418820	8662530	1322423307	44.12	5.46	0	3.33	0	0.23	0	0.16	0	0.00	0	4.13	0	18303987	0	180	0	176.74	0	2.99	0	0.02	0	2.58	0	0.02	0	439.60	0	0.35	0	1047137	0	19171590	0	639311	0	44318	0	30966	0	0	0	792319	0	2501	0	0	0	20555	0	2688615	0	17950	0	2729621	0	92.14	0	17664676	0	137175	2753591	20.073562967013	19171590.0	18303987.0	1047137.0	639311.0	44318.0	30966.0	0.0	792319.0	17664676.0	95.5	5.5	3.3	0.2	0.2	0.0	4.1	92.1	90	90	90.00	38	1725443100	26.3	23.6	23.9	26.3	0.0	36.1	22.0	bulk
199979	ERR1197695	ERP013684	ERS1025895	ERX1269954	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A		PC01	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	Alias;;E-MTAB-4157:PC01|Broker name;;ArrayExpress|cell_type;;T cell|Description;;Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol|disease;;T-cell acute lymphoblastic leukemia|ENA checklist;;ERC000011|genotype;;DNMT3A R882H Tet2-/-|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:26Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025895|SRA accession;;ERS1025895|strain;;C57BL/6|Title;;PC01	Experimental Factor: DNMT3A R882H Tet2-/-;;genotype	202	SAMEA3718746	E-MTAB-4157:PC01	17719250726	87719063	2016-02-25 05:20:35	11370814119	17719250726	87719063	2	87719063	index:0,count:87719063,average:101,stdev:0|index:1,count:87719063,average:101,stdev:0	E-MTAB-4157:PC01.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	22.6	2.53	0.1	16403299922	16157249648	15307501022	15131378726	98.5	98.85	83207769	69525989	375.434	1397.200	268	379115	75.95	81.43	91905272	63195602	91905272	63195602	80.03	79.78	91905272	66591222	91905272	61915012	2974432193	18.13	1.10	0	6.39	0	0.32	0	0.06	0	0.00	0	4.77	0	83207769	0	202	0	198.88	0	1.48	0	0.01	0	1.46	0	0.00	0	403.31	0	0.46	0	965277	0	87719063	0	5602142	0	277824	0	48970	0	0	0	4184500	0	19074	0	0	0	174060	0	22865776	0	66156	0	23125066	0	88.47	0	77605627	0	219499	24343533	110.904983621793	87719063.0	83207769.0	965277.0	5602142.0	277824.0	48970.0	0.0	4184500.0	77605627.0	94.9	1.1	6.4	0.3	0.1	0.0	4.8	88.5	101	101	101.00	38	8859625363	28.8	23.3	22.6	25.4	0.0	36.7	22.5	bulk
199981	ERR1197696	ERP013684	ERS1025896	ERX1269955	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A		PC02	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	Alias;;E-MTAB-4157:PC02|Broker name;;ArrayExpress|cell_type;;T cell|Description;;Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol|disease;;T-cell acute lymphoblastic leukemia|ENA checklist;;ERC000011|genotype;;DNMT3A R882H Tet2-/-|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:26Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025896|SRA accession;;ERS1025896|strain;;C57BL/6|Title;;PC02	Experimental Factor: DNMT3A R882H Tet2-/-;;genotype	202	SAMEA3718747	E-MTAB-4157:PC02	8820703498	43666849	2016-02-25 05:20:35	5276743812	8820703498	43666849	2	43666849	index:0,count:43666849,average:101,stdev:0|index:1,count:43666849,average:101,stdev:0	E-MTAB-4157:PC02.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	2.31	3.24	0.37	6338768909	6143199051	5718017083	5566192530	96.91	97.34	34581567	30069924	269.910	1317.977	241	167885	66.62	74.31	40783831	23038429	40783831	23038429	71.95	71.32	40783831	24880297	40783831	22109492	1380914424	21.79	1.29	0	8.20	0	0.55	0	0.15	0	0.00	0	20.11	0	34581567	0	202	0	197.14	0	1.51	0	0.01	0	3.07	0	0.02	0	180.48	0	0.64	0	565147	0	43666849	0	3580047	0	240819	0	63651	0	0	0	8780812	0	9280	0	0	0	76802	0	11666936	0	38106	0	11791124	0	71.00	0	31001520	0	133456	11968701	89.682749370579	43666849.0	34581567.0	565147.0	3580047.0	240819.0	63651.0	0.0	8780812.0	31001520.0	79.2	1.3	8.2	0.6	0.1	0.0	20.1	71.0	101	101	101.00	38	4410351749	27.8	23.0	24.5	24.6	0.1	36.3	18.6	bulk
199983	ERR1197697	ERP013684	ERS1025897	ERX1269956	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A		PC04	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	Alias;;E-MTAB-4157:PC04|Broker name;;ArrayExpress|cell_type;;T cell|Description;;Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol|disease;;T-cell acute lymphoblastic leukemia|ENA checklist;;ERC000011|genotype;;NOTCH1 L1601PdelP Tet2-/-|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:26Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8low) T-cells|Sample Name;;ERS1025897|SRA accession;;ERS1025897|strain;;C57BL/6|Title;;PC04	Experimental Factor: NOTCH1 L1601PdelP Tet2-/-;;genotype	202	SAMEA3718748	E-MTAB-4157:PC04	16461879708	81494454	2016-02-25 05:20:35	10218741566	16461879708	81494454	2	81494454	index:0,count:81494454,average:101,stdev:0|index:1,count:81494454,average:101,stdev:0	E-MTAB-4157:PC04.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	6.08	3.08	0.3	9830356875	9463094889	8618888928	8321157502	96.26	96.55	55797462	50179032	243.096	1201.674	150	495945	62.15	71.17	67214241	34678562	67214241	34678562	69.85	67.86	67214241	38971818	67214241	33067874	2277148765	23.16	0.81	0	8.68	0	0.54	0	0.09	0	0.00	0	30.90	0	55797462	0	202	0	193.26	0	1.97	0	0.01	0	3.41	0	0.02	0	209.41	0	1.34	0	663214	0	81494454	0	7071195	0	443781	0	71997	0	0	0	25181214	0	10600	0	0	0	107291	0	15835641	0	62627	0	16016159	0	59.79	0	48726267	0	149839	16151579	107.792891036379	81494454.0	55797462.0	663214.0	7071195.0	443781.0	71997.0	0.0	25181214.0	48726267.0	68.5	0.8	8.7	0.5	0.1	0.0	30.9	59.8	101	101	101.00	38	8230939854	26.9	23.9	25.3	23.8	0.0	35.3	17.5	bulk
199985	ERR1197698	ERP013684	ERS1025898	ERX1269957	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A		PC05	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	Alias;;E-MTAB-4157:PC05|Broker name;;ArrayExpress|cell_type;;T cell|Description;;Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol|disease;;T-cell acute lymphoblastic leukemia|ENA checklist;;ERC000011|genotype;;NOTCH1 L1601PdelP Tet2-/-|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:26Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025898|SRA accession;;ERS1025898|strain;;C57BL/6|Title;;PC05	Experimental Factor: NOTCH1 L1601PdelP Tet2-/-;;genotype	200	SAMEA3718749	E-MTAB-4157:PC05	12982310800	64911554	2016-02-25 05:20:35	8186296276	12982310800	64911554	2	64911554	index:0,count:64911554,average:100,stdev:0|index:1,count:64911554,average:100,stdev:0	E-MTAB-4157:PC05.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	2.42	3.76	0.08	8067990216	8016716369	7220924466	7227565002	99.36	100.09	56078185	51594658	171.187	852.496	124	492301	83.14	93.21	66977132	46621959	66977132	46621959	88.64	89.2	66977132	49705770	66977132	44616305	458967666	5.69	1.51	0	9.34	0	0.59	0	0.09	0	0.00	0	12.93	0	56078185	0	200	0	195.89	0	1.28	0	0.02	0	1.52	0	0.00	0	234.38	0	0.60	0	980866	0	64911554	0	6062164	0	381984	0	61357	0	0	0	8390028	0	22244	0	0	0	194548	0	27356486	0	66762	0	27640040	0	77.05	0	50016021	0	233856	23170484	99.080134783799	64911554.0	56078185.0	980866.0	6062164.0	381984.0	61357.0	0.0	8390028.0	50016021.0	86.4	1.5	9.3	0.6	0.1	0.0	12.9	77.1	100	100	100.00	38	6491155400	23.3	25.3	25.2	26.1	0.0	35.6	19.6	bulk
199987	ERR1197699	ERP013684	ERS1025899	ERX1269958	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	PC06	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	alias;;E-MTAB-4157:PC06|broker name;;ArrayExpress|cell type;;T cell|disease;;T-cell acute lymphoblastic leukemia|ENA checklist;;ERC000011|genotype;;NOTCH1 L1601PdelP Tet2+/+|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:26Z|INSDC status;;public|organism;;Mus musculus|phenotype;;SP (CD8+) T-cells|Sample Name;;ERS1025899|SRA accession;;ERS1025899|strain;;C57BL/6|title;;PC06	Experimental Factor: NOTCH1 L1601PdelP Tet2+/+;;genotype	200	SAMEA3718750	E-MTAB-4157:PC06	30019200328	148768467	2016-02-25 05:20:35	18480256609	30019200328	148768467				E-MTAB-4157:PC06.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	13.55	3.5	0.08	20153526204	19971964375	18276868756	18182277462	99.1	99.48	109908583	88374557	345.268	1691.131	268	433159	81.05	89.5	127149814	89084656	127149814	89084656	86.74	87.1	127149814	95334401	127149814	86697180	1987365587	9.86	0.71	0	6.97	0	0.20	0	0.02	0	0.00	0	25.90	0	109908583	0	201	0	190.39	0	1.84	0	0.01	0	1.32	0	0.00	0	233.06	0	1.42	0	1060512	0	148768467	0	10375783	0	300933	0	33579	0	0	0	38525372	0	30472	0	0	0	262681	0	35666272	0	93089	0	36052514	0	66.90	0	99532800	0	230058	37403127	162.581292543619	148768467.0	109908583.0	1060512.0	10375783.0	300933.0	33579.0	0.0	38525372.0	99532800.0	73.9	0.7	7.0	0.2	0.0	0.0	25.9	66.9	101	101	101.00	38	15025615167	27.9	23.5	23.5	25.2	0.0	34.7	15.9	bulk
200193	ERR1197700	ERP013684	ERS1025900	ERX1269959	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	PC07	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	alias;;E-MTAB-4157:PC07|broker name;;ArrayExpress|cell type;;T cell|disease;;T-cell acute lymphoblastic leukemia|ENA checklist;;ERC000011|genotype;;TCL1A Tet2+/+|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:26Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4low/CD8+) T-cells|Sample Name;;ERS1025900|SRA accession;;ERS1025900|strain;;C57BL/6|title;;PC07	Experimental Factor: TCL1A Tet2+/+;;genotype	200	SAMEA3718751	E-MTAB-4157:PC07	14410372000	72051860	2016-02-25 05:20:35	8454096918	14410372000	72051860	2	72051860	index:0,count:72051860,average:100,stdev:0|index:1,count:72051860,average:100,stdev:0	E-MTAB-4157:PC07.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	4.85	3.48	0.19	8455963005	8383109739	7340045018	7348244805	99.14	100.11	59498633	54930925	167.910	865.309	124	558919	81.53	94.3	73981795	48507783	73981795	48507783	89.33	90.2	73981795	53149881	73981795	46396631	393691817	4.66	1.51	0	11.19	0	0.95	0	0.08	0	0.00	0	16.39	0	59498633	0	200	0	196.34	0	1.24	0	0.02	0	1.52	0	0.00	0	246.57	0	0.39	0	1089163	0	72051860	0	8059052	0	685531	0	58689	0	0	0	11809007	0	26168	0	0	0	217334	0	29051491	0	75560	0	29370553	0	71.39	0	51439581	0	211165	24386584	115.485918594464	72051860.0	59498633.0	1089163.0	8059052.0	685531.0	58689.0	0.0	11809007.0	51439581.0	82.6	1.5	11.2	1.0	0.1	0.0	16.4	71.4	100	100	100.00	38	7205186000	23.6	25.2	25.2	26.1	0.0	36.5	20.5	bulk
200195	ERR1197701	ERP013684	ERS1025901	ERX1269960	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	PC08	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	alias;;E-MTAB-4157:PC08|broker name;;ArrayExpress|cell type;;T cell|disease;;T-cell acute lymphoblastic leukemia|ENA checklist;;ERC000011|genotype;;TCL1A Tet2+/+|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:26Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025901|SRA accession;;ERS1025901|strain;;C57BL/6|title;;PC08	Experimental Factor: TCL1A Tet2+/+;;genotype	200	SAMEA3718752	E-MTAB-4157:PC08	10531266800	52656334	2016-02-25 05:20:35	6186370840	10531266800	52656334	2	52656334	index:0,count:52656334,average:100,stdev:0|index:1,count:52656334,average:100,stdev:0	E-MTAB-4157:PC08.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	4.32	3.3	0.15	6487556276	6368102427	5741922097	5701758850	98.16	99.3	44679410	41232187	171.727	795.483	124	403181	82.13	93.12	54447935	36694060	54447935	36694060	88.18	89.24	54447935	39397106	54447935	35164970	329808281	5.08	1.44	0	10.01	0	0.87	0	0.10	0	0.00	0	14.18	0	44679410	0	200	0	196.70	0	1.25	0	0.02	0	1.52	0	0.00	0	252.41	0	0.37	0	757345	0	52656334	0	5272297	0	456537	0	52420	0	0	0	7467967	0	20087	0	0	0	159012	0	22281490	0	53487	0	22514076	0	74.84	0	39407113	0	211205	18780695	88.921640112687	52656334.0	44679410.0	757345.0	5272297.0	456537.0	52420.0	0.0	7467967.0	39407113.0	84.9	1.4	10.0	0.9	0.1	0.0	14.2	74.8	100	100	100.00	38	5265633400	23.5	25.2	25.2	26.1	0.0	36.5	20.5	bulk
200197	ERR1197702	ERP013684	ERS1025902	ERX1269961	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	PC09	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	alias;;E-MTAB-4157:PC09|broker name;;ArrayExpress|cell type;;T cell|disease;;normal|ENA checklist;;ERC000011|genotype;;Tet2-/-|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:27Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025902|SRA accession;;ERS1025902|strain;;C57BL/6|title;;PC09	Experimental Factor: Tet2-/-;;genotype	200	SAMEA3718753	E-MTAB-4157:PC09	12380152632	61771090	2016-02-25 05:20:35	7029169033	12380152632	61771090				E-MTAB-4157:PC09.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	7.07	2.69	0.14	8796259529	8662285118	8257904076	8181175116	98.48	99.07	54417439	49669477	220.458	964.922	124	378411	79.32	84.72	60307751	43163675	60307751	43163675	81.39	81.6	60307751	44291056	60307751	41574426	1290690775	14.67	2.25	0	5.61	0	0.29	0	0.03	0	0.00	0	11.58	0	54417439	0	200	0	195.86	0	1.36	0	0.01	0	1.80	0	0.01	0	374.37	0	0.55	0	1392162	0	61771090	0	3466335	0	180178	0	19900	0	0	0	7153573	0	15016	0	0	0	144807	0	20105574	0	54104	0	20319501	0	82.48	0	50951104	0	297004	17868120	60.161209950034	61771090.0	54417439.0	1392162.0	3466335.0	180178.0	19900.0	0.0	7153573.0	50951104.0	88.1	2.3	5.6	0.3	0.0	0.0	11.6	82.5	101	101	101.00	38	6238880090	24.7	24.6	24.5	26.2	0.0	36.9	20.8	bulk
200199	ERR1197703	ERP013684	ERS1025903	ERX1269962	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	PC10	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	alias;;E-MTAB-4157:PC10|broker name;;ArrayExpress|cell type;;T cell|disease;;normal|ENA checklist;;ERC000011|genotype;;Tet2-/-|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:27Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025903|SRA accession;;ERS1025903|strain;;C57BL/6|title;;PC10	Experimental Factor: Tet2-/-;;genotype	200	SAMEA3718754	E-MTAB-4157:PC10	10059078446	50238515	2016-02-25 05:20:35	5978006195	10059078446	50238515				E-MTAB-4157:PC10.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	5.58	3.02	0.09	6846642077	6768911648	6379788066	6347551120	98.86	99.49	43656941	39797186	201.368	974.032	124	350126	82.73	89.01	48905641	36117328	48905641	36117328	85.02	85.42	48905641	37116458	48905641	34662331	699697446	10.22	2.66	0	6.13	0	0.33	0	0.05	0	0.00	0	12.73	0	43656941	0	200	0	196.98	0	1.33	0	0.02	0	1.76	0	0.01	0	319.54	0	0.38	0	1337888	0	50238515	0	3080553	0	163676	0	23101	0	0	0	6394797	0	16839	0	0	0	131085	0	19122534	0	45221	0	19315679	0	80.77	0	40576388	0	223181	16647766	74.593115005310	50238515.0	43656941.0	1337888.0	3080553.0	163676.0	23101.0	0.0	6394797.0	40576388.0	86.9	2.7	6.1	0.3	0.0	0.0	12.7	80.8	101	101	101.00	38	5074090015	24.0	25.0	24.9	26.1	0.0	36.6	21.3	bulk
200201	ERR1197704	ERP013684	ERS1025904	ERX1269963	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A		PC13	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	Alias;;E-MTAB-4157:PC13|Broker name;;ArrayExpress|cell_type;;T cell|Description;;Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol|disease;;T-cell acute lymphoblastic leukemia|ENA checklist;;ERC000011|genotype;;NOTCH1 L1601PdelP Tet2+/+|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:27Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025904|SRA accession;;ERS1025904|strain;;C57BL/6|Title;;PC13	Experimental Factor: NOTCH1 L1601PdelP Tet2+/+;;genotype	202	SAMEA3718755	E-MTAB-4157:PC13	7207506450	35680725	2016-02-25 05:20:35	4462239748	7207506450	35680725	2	35680725	index:0,count:35680725,average:101,stdev:0|index:1,count:35680725,average:101,stdev:0	E-MTAB-4157:PC13.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	23.37	2.82	0.12	5444097528	5398144406	5030725523	5001411563	99.16	99.42	28921811	23587006	405.640	1828.937	384	138524	77.79	84.25	32507381	22499281	32507381	22499281	82.48	82.5	32507381	23855749	32507381	22030960	846916174	15.56	0.60	0	6.22	0	0.23	0	0.04	0	0.00	0	18.68	0	28921811	0	202	0	189.52	0	1.27	0	0.01	0	1.26	0	0.00	0	238.76	0	1.58	0	214567	0	35680725	0	2217680	0	82812	0	12668	0	0	0	6663434	0	5065	0	0	0	47557	0	6440376	0	22543	0	6515541	0	74.84	0	26704131	0	146281	7014052	47.949166330556	35680725.0	28921811.0	214567.0	2217680.0	82812.0	12668.0	0.0	6663434.0	26704131.0	81.1	0.6	6.2	0.2	0.0	0.0	18.7	74.8	101	101	101.00	38	3603753225	29.1	23.1	22.4	25.4	0.0	34.5	15.0	bulk
200203	ERR1197705	ERP013684	ERS1025905	ERX1269964	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A		PC14	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	Alias;;E-MTAB-4157:PC14|Broker name;;ArrayExpress|cell_type;;T cell|Description;;Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol|disease;;normal|ENA checklist;;ERC000011|genotype;;Tet2+/+|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:27Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025905|SRA accession;;ERS1025905|strain;;C57BL/6|Title;;PC14	Experimental Factor: Tet2+/+;;genotype	200	SAMEA3718756	E-MTAB-4157:PC14	17974243302	89764869	2016-02-25 05:20:35	10789768162	17974243302	89764869				E-MTAB-4157:PC14.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	4.31	3.07	0.07	12481213523	12360602819	11678763301	11638237769	99.03	99.65	79034173	72241184	201.972	941.897	124	613375	83.67	89.67	88423485	66129069	88423485	66129069	85.33	85.88	88423485	67443680	88423485	63339016	1205463236	9.66	2.47	0	5.89	0	0.35	0	0.04	0	0.00	0	11.56	0	79034173	0	200	0	196.94	0	1.35	0	0.02	0	1.76	0	0.01	0	358.66	0	0.38	0	2218878	0	89764869	0	5285514	0	310582	0	39137	0	0	0	10380977	0	30429	0	0	0	243207	0	35381093	0	85464	0	35740193	0	82.16	0	73748659	0	291120	31001111	106.489114454520	89764869.0	79034173.0	2218878.0	5285514.0	310582.0	39137.0	0.0	10380977.0	73748659.0	88.0	2.5	5.9	0.3	0.0	0.0	11.6	82.2	101	101	101.00	38	9066251769	23.8	25.2	24.9	26.0	0.0	36.5	21.2	bulk
200205	ERR1197706	ERP013684	ERS1025906	ERX1269965	ERA549726	UMR 1170 INSERM Institut Gustave Roussy	European Nucleotide Archive	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive proliferation of T-lymphocytes usually associated with oncogenic activation of NOTCH1 signaling. Using a bone marrow transplantation approach, we have modeled murine CD4+ CD8+ T-ALL by overexpressing DNMT3A R882H in Tet2-/- multipotent progenitors. T-ALL derived from NOTCH1 L1601PdelP Tet2-/-, NOTCH1 L1601PdelP Tet2+/+ or TCL1A progenitors were used for comparison, as well as normal Tet2+/+  and Tet2-/- CD4+ CD8+ double positive (DP) thymocytes.	Illumina HiSeq 2000 paired end sequencing; RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A	RNA-sequencing of murine T-cell acute lymphoblastic leukemia (T-ALL) cells to investigate expression profiling of lymphocyte deficient for Tet2 and mutated for DNMT3A		PC15	RNA-Seq	TRANSCRIPTOMIC	cDNA	paired	150	37.5	Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol	Illumina HiSeq 2000	Alias;;E-MTAB-4157:PC15|Broker name;;ArrayExpress|cell_type;;T cell|Description;;Protocols: Cells were sorted using flow cytometry based on the expression of GFP and CD4/CD8 markers Allprep Kit (QIAGEN) according to manufacturer's protocol SureSelect Automated Strand Specific RNA library Preparation according to manufacturer's protocol|disease;;normal|ENA checklist;;ERC000011|genotype;;Tet2+/+|INSDC center name;;UMR 1170 INSERM Institut Gustave Roussy|INSDC first public;;2016-02-24T17:02:27Z|INSDC last update;;2015-12-21T18:35:27Z|INSDC status;;public|organism;;Mus musculus|phenotype;;DP (CD4+/CD8+) T-cells|Sample Name;;ERS1025906|SRA accession;;ERS1025906|strain;;C57BL/6|Title;;PC15	Experimental Factor: Tet2+/+;;genotype	202	SAMEA3718757	E-MTAB-4157:PC15	34820335396	172377898	2016-02-25 05:20:35	22169353824	34820335396	172377898	2	172377898	index:0,count:172377898,average:101,stdev:0|index:1,count:172377898,average:101,stdev:0	E-MTAB-4157:PC15.R	UMR 1170 INSERM Institut Gustave Roussy	ArrayExpress	UMR 1170 INSERM, Institut Gustave Roussy, 94805 Villejuif, France	in_mesa	26876596	1.47	3.21	0.06	26951986556	26396030025	24965581589	24489882834	97.94	98.09	143531146	120803594	305.472	1521.755	217	826808	68.74	74.5	162482029	98666837	162482029	98666837	72.19	71.55	162482029	103611887	162482029	94751971	6256594948	23.21	0.88	0	6.44	0	0.21	0	0.07	0	0.00	0	16.46	0	143531146	0	202	0	195.51	0	1.36	0	0.01	0	2.69	0	0.01	0	267.94	0	1.35	0	1511049	0	172377898	0	11101179	0	365242	0	113910	0	0	0	28367600	0	37049	0	0	0	291724	0	42326640	0	121793	0	42777206	0	76.83	0	132429967	0	173144	43944591	253.803718292288	172377898.0	143531146.0	1511049.0	11101179.0	365242.0	113910.0	0.0	28367600.0	132429967.0	83.3	0.9	6.4	0.2	0.1	0.0	16.5	76.8	101	101	101.00	38	17410167698	26.6	23.0	25.0	25.4	0.0	34.7	15.9	bulk
1930040	SRR528733	SRP014599	SRS348125	SRX171237	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_polysome		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	4023603800	20118019	2015-07-22 17:07:41	2523427699	4023603800	20118019	2	20118019	index:0,count:20118019,average:100,stdev:0|index:1,count:20118019,average:100,stdev:0	WT_polysome_2	JAX					2.48	3.55	0.01	2877387621	2860466573	2730104342	2730571757	99.41	100.02	19041008	17975650	174.105	583.251	125	198929	90.74	95.74	20541303	17277373	20541303	17277373	91.31	91.97	20541303	17385604	20541303	16597647	77107593	2.68	1.55	0	4.95	0	0.22	0	0.05	0	0.00	0	5.08	0	19041008	0	200	0	196.91	0	2.19	0	0.02	0	1.64	0	0.02	0	198.97	0	0.66	0	312141	0	20118019	0	995082	0	44633	0	9397	0	0	0	1022981	0	5409	0	0	0	41839	0	6327669	0	36236	0	6411153	0	89.70	0	18045926	0	181878	5434764	29.881371028931	20118019.0	19041008.0	312141.0	995082.0	44633.0	9397.0	0.0	1022981.0	18045926.0	94.6	1.6	4.9	0.2	0.0	0.0	5.1	89.7	100	100	100.00	38	2011801900	25.4	24.7	24.5	25.4	0.0	33.3	14.7	bulk
1930072	SRR528735	SRP014599	SRS348125	SRX171237	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_polysome		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3934413200	19672066	2015-07-22 17:07:41	2480294660	3934413200	19672066	2	19672066	index:0,count:19672066,average:100,stdev:0|index:1,count:19672066,average:100,stdev:0	WT_polysome_7	JAX					2.49	3.56	0.01	2807766774	2790806886	2663906106	2664003961	99.4	100.0	18586085	17548822	173.983	584.173	125	194331	90.72	95.72	20052620	16860738	20052620	16860738	91.3	91.97	20052620	16969032	20052620	16200165	75747999	2.70	1.54	0	4.94	0	0.22	0	0.05	0	0.00	0	5.25	0	18586085	0	200	0	196.80	0	2.19	0	0.02	0	1.63	0	0.02	0	95.83	0	0.70	0	303926	0	19672066	0	971937	0	43280	0	9116	0	0	0	1033585	0	5322	0	0	0	40832	0	6141390	0	34878	0	6222422	0	89.54	0	17614148	0	180455	5283551	29.279050178715	19672066.0	18586085.0	303926.0	971937.0	43280.0	9116.0	0.0	1033585.0	17614148.0	94.5	1.5	4.9	0.2	0.0	0.0	5.3	89.5	100	100	100.00	38	1967206600	25.4	24.6	24.5	25.4	0.1	33.0	14.3	bulk
1930120	SRR528738	SRP014599	SRS348125	SRX171238	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_RNAgranule		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3816785200	19083926	2015-07-22 17:07:41	2397874038	3816785200	19083926	2	19083926	index:0,count:19083926,average:100,stdev:0|index:1,count:19083926,average:100,stdev:0	WT_RNAgranule_2	JAX					3.44	3.57	0.01	2751375965	2742128366	2602906134	2608440748	99.66	100.21	18094512	16997150	176.553	612.042	125	185614	91.12	96.42	19568601	16487602	19568601	16487602	92.22	92.76	19568601	16685884	19568601	15861035	57235413	2.08	1.49	0	5.21	0	0.31	0	0.04	0	0.00	0	4.84	0	18094512	0	200	0	196.90	0	2.19	0	0.02	0	1.66	0	0.02	0	118.04	0	0.67	0	283779	0	19083926	0	995087	0	58350	0	6746	0	0	0	924318	0	5085	0	0	0	46523	0	6560473	0	35176	0	6647257	0	89.60	0	17099425	0	171212	5618735	32.817413499054	19083926.0	18094512.0	283779.0	995087.0	58350.0	6746.0	0.0	924318.0	17099425.0	94.8	1.5	5.2	0.3	0.0	0.0	4.8	89.6	100	100	100.00	38	1908392600	25.1	25.0	24.7	25.1	0.0	33.3	14.7	bulk
1930136	SRR528739	SRP014599	SRS348125	SRX171238	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_RNAgranule		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3784992400	18924962	2015-07-22 17:07:41	2383068274	3784992400	18924962	2	18924962	index:0,count:18924962,average:100,stdev:0|index:1,count:18924962,average:100,stdev:0	WT_RNAgranule_6	JAX					3.45	3.57	0.01	2724402243	2715577581	2577243804	2582929586	99.68	100.22	17926669	16837696	176.419	611.827	125	184702	91.11	96.42	19389164	16333063	19389164	16333063	92.2	92.75	19389164	16529142	19389164	15711193	56911539	2.09	1.48	0	5.22	0	0.31	0	0.03	0	0.00	0	4.94	0	17926669	0	200	0	196.83	0	2.18	0	0.02	0	1.66	0	0.02	0	251.40	0	0.69	0	280424	0	18924962	0	987101	0	57795	0	6539	0	0	0	933959	0	4941	0	0	0	46046	0	6486627	0	35118	0	6572732	0	89.51	0	16939568	0	171221	5560012	32.472722388025	18924962.0	17926669.0	280424.0	987101.0	57795.0	6539.0	0.0	933959.0	16939568.0	94.7	1.5	5.2	0.3	0.0	0.0	4.9	89.5	100	100	100.00	38	1892496200	25.2	24.9	24.8	25.1	0.0	33.0	14.4	bulk
1930248	SRR528740	SRP014599	SRS348125	SRX171238	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_RNAgranule		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3694907800	18474539	2015-07-22 17:07:41	2334481621	3694907800	18474539	2	18474539	index:0,count:18474539,average:100,stdev:0|index:1,count:18474539,average:100,stdev:0	WT_RNAgranule_7	JAX					3.45	3.58	0.01	2657650625	2648699078	2514203467	2519496305	99.66	100.21	17484054	16424237	176.439	611.121	125	180233	91.12	96.42	18908424	15931201	18908424	15931201	92.21	92.75	18908424	16121614	18908424	15325304	55277956	2.08	1.49	0	5.20	0	0.30	0	0.03	0	0.00	0	5.02	0	17484054	0	200	0	196.77	0	2.18	0	0.02	0	1.66	0	0.02	0	118.34	0	0.71	0	274427	0	18474539	0	961527	0	55773	0	6436	0	0	0	928276	0	4699	0	0	0	44713	0	6306217	0	34238	0	6389867	0	89.43	0	16522527	0	170180	5412254	31.803114349512	18474539.0	17484054.0	274427.0	961527.0	55773.0	6436.0	0.0	928276.0	16522527.0	94.6	1.5	5.2	0.3	0.0	0.0	5.0	89.4	100	100	100.00	38	1847453900	25.2	24.9	24.7	25.1	0.1	32.9	14.3	bulk
1930264	SRR528741	SRP014599	SRS348125	SRX171238	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_RNAgranule		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3727535600	18637678	2015-07-22 17:07:41	2348449003	3727535600	18637678	2	18637678	index:0,count:18637678,average:100,stdev:0|index:1,count:18637678,average:100,stdev:0	WT_RNAgranule_8	JAX					3.45	3.57	0.01	2683467999	2674922056	2538916221	2544683126	99.68	100.23	17651724	16580448	176.490	610.125	125	181535	91.13	96.42	19086249	16086197	19086249	16086197	92.22	92.76	19086249	16277589	19086249	15474590	55884072	2.08	1.49	0	5.20	0	0.30	0	0.03	0	0.00	0	4.95	0	17651724	0	200	0	196.82	0	2.19	0	0.02	0	1.66	0	0.02	0	244.87	0	0.69	0	277289	0	18637678	0	969063	0	56768	0	6438	0	0	0	922748	0	4931	0	0	0	45323	0	6384325	0	34647	0	6469226	0	89.51	0	16682661	0	170272	5474044	32.148820710393	18637678.0	17651724.0	277289.0	969063.0	56768.0	6438.0	0.0	922748.0	16682661.0	94.7	1.5	5.2	0.3	0.0	0.0	5.0	89.5	100	100	100.00	38	1863767800	25.2	25.0	24.7	25.1	0.0	33.1	14.5	bulk
1930280	SRR528742	SRP014599	SRS348126	SRX171525	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3107898200	15539491	2015-07-22 17:07:41	1959098122	3107898200	15539491	2	15539491	index:0,count:15539491,average:100,stdev:0|index:1,count:15539491,average:100,stdev:0	KO_RNAgranule_1	JAX					4.9	3.57	0.01	2255682116	2249338306	2116317236	2121593933	99.72	100.25	14768872	13825542	178.466	624.705	126	146825	90.27	96.32	16140967	13331683	16140967	13331683	92.23	92.66	16140967	13621321	16140967	12825436	47854760	2.12	1.45	0	5.97	0	0.42	0	0.03	0	0.00	0	4.51	0	14768872	0	200	0	196.91	0	2.24	0	0.02	0	1.72	0	0.01	0	109.69	0	0.66	0	224740	0	15539491	0	927340	0	65182	0	4819	0	0	0	700618	0	3790	0	0	0	41844	0	5651981	0	22219	0	5719834	0	89.07	0	13841532	0	160684	4858708	30.237659007742	15539491.0	14768872.0	224740.0	927340.0	65182.0	4819.0	0.0	700618.0	13841532.0	95.0	1.4	6.0	0.4	0.0	0.0	4.5	89.1	100	100	100.00	38	1553949100	25.0	25.1	24.8	25.1	0.0	33.5	15.0	bulk
1930296	SRR528743	SRP014599	SRS348126	SRX171525	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3120067600	15600338	2015-07-22 17:07:41	1973675521	3120067600	15600338	2	15600338	index:0,count:15600338,average:100,stdev:0|index:1,count:15600338,average:100,stdev:0	KO_RNAgranule_2	JAX					4.92	3.57	0.01	2263951290	2257373159	2124239278	2129406314	99.71	100.24	14823624	13875520	178.402	626.343	127	147698	90.27	96.31	16196989	13381138	16196989	13381138	92.23	92.66	16196989	13671173	16196989	12873292	48197966	2.13	1.44	0	5.96	0	0.42	0	0.03	0	0.00	0	4.53	0	14823624	0	200	0	196.88	0	2.24	0	0.02	0	1.72	0	0.01	0	216.00	0	0.66	0	224874	0	15600338	0	929841	0	65589	0	5008	0	0	0	706117	0	3845	0	0	0	42198	0	5662783	0	22448	0	5731274	0	89.06	0	13893783	0	160895	4868792	30.260679325026	15600338.0	14823624.0	224874.0	929841.0	65589.0	5008.0	0.0	706117.0	13893783.0	95.0	1.4	6.0	0.4	0.0	0.0	4.5	89.1	100	100	100.00	38	1560033800	25.0	25.1	24.8	25.1	0.0	33.4	14.9	bulk
1930313	SRR528744	SRP014599	SRS348126	SRX171525	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3085239400	15426197	2015-07-22 17:07:41	1953236046	3085239400	15426197	2	15426197	index:0,count:15426197,average:100,stdev:0|index:1,count:15426197,average:100,stdev:0	KO_RNAgranule_6	JAX					4.91	3.57	0.01	2236580574	2230014732	2098600047	2103546491	99.71	100.24	14649822	13713134	178.371	623.991	127	146223	90.27	96.31	16009293	13224794	16009293	13224794	92.24	92.67	16009293	13512814	16009293	12724410	47495316	2.12	1.45	0	5.95	0	0.42	0	0.03	0	0.00	0	4.58	0	14649822	0	200	0	196.85	0	2.23	0	0.02	0	1.72	0	0.01	0	217.78	0	0.68	0	222985	0	15426197	0	918557	0	64637	0	4887	0	0	0	706851	0	3779	0	0	0	41531	0	5592316	0	21923	0	5659549	0	89.01	0	13731265	0	160267	4806694	29.991788702603	15426197.0	14649822.0	222985.0	918557.0	64637.0	4887.0	0.0	706851.0	13731265.0	95.0	1.4	6.0	0.4	0.0	0.0	4.6	89.0	100	100	100.00	38	1542619700	25.0	25.0	24.8	25.1	0.0	33.2	14.7	bulk
1930329	SRR528745	SRP014599	SRS348126	SRX171525	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3034090600	15170453	2015-07-22 17:07:41	1927457291	3034090600	15170453	2	15170453	index:0,count:15170453,average:100,stdev:0|index:1,count:15170453,average:100,stdev:0	KO_RNAgranule_7	JAX					4.91	3.56	0.01	2198375684	2192180097	2062804674	2067844454	99.72	100.24	14396225	13476401	178.415	627.004	125	143370	90.28	96.32	15730582	12997474	15730582	12997474	92.24	92.66	15730582	13278847	15730582	12504146	46472411	2.11	1.43	0	5.95	0	0.42	0	0.03	0	0.00	0	4.65	0	14396225	0	200	0	196.80	0	2.24	0	0.02	0	1.71	0	0.01	0	212.50	0	0.69	0	217547	0	15170453	0	902268	0	63401	0	4840	0	0	0	705987	0	3853	0	0	0	40799	0	5475744	0	21322	0	5541718	0	88.95	0	13493957	0	159528	4716010	29.562271200040	15170453.0	14396225.0	217547.0	902268.0	63401.0	4840.0	0.0	705987.0	13493957.0	94.9	1.4	5.9	0.4	0.0	0.0	4.7	88.9	100	100	100.00	38	1517045300	25.0	25.0	24.8	25.1	0.1	33.1	14.6	bulk
1930344	SRR528746	SRP014599	SRS348126	SRX171525	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3049473400	15247367	2015-07-22 17:07:41	1931140676	3049473400	15247367	2	15247367	index:0,count:15247367,average:100,stdev:0|index:1,count:15247367,average:100,stdev:0	KO_RNAgranule_8	JAX					4.91	3.57	0.01	2210939986	2204917081	2074593302	2079919115	99.73	100.26	14478518	13552424	178.487	627.626	127	144190	90.29	96.33	15820628	13072476	15820628	13072476	92.25	92.68	15820628	13356335	15820628	12576858	46721120	2.11	1.45	0	5.95	0	0.41	0	0.03	0	0.00	0	4.60	0	14478518	0	200	0	196.84	0	2.23	0	0.02	0	1.71	0	0.01	0	200.33	0	0.67	0	221194	0	15247367	0	907593	0	62995	0	4972	0	0	0	700882	0	3827	0	0	0	41069	0	5524952	0	21822	0	5591670	0	89.01	0	13570925	0	159980	4753258	29.711576447056	15247367.0	14478518.0	221194.0	907593.0	62995.0	4972.0	0.0	700882.0	13570925.0	95.0	1.5	6.0	0.4	0.0	0.0	4.6	89.0	100	100	100.00	38	1524736700	25.0	25.1	24.8	25.1	0.0	33.3	14.8	bulk
1930361	SRR528747	SRP014599	SRS348126	SRX171524	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_monosome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	2849387200	14246936	2015-07-22 17:07:41	1740787033	2849387200	14246936	2	14246936	index:0,count:14246936,average:100,stdev:0|index:1,count:14246936,average:100,stdev:0	KO_monosome_1	JAX					5.39	3.4	0.01	1458831389	1432433586	1318779916	1307197590	98.19	99.12	9964522	9522810	166.752	509.273	124	118047	82.4	91.35	11447990	8210367	11447990	8210367	85.25	85.94	11447990	8495069	11447990	7724204	70678950	4.84	1.16	0	6.86	0	0.13	0	0.07	0	0.00	0	29.86	0	9964522	0	200	0	196.39	0	2.45	0	0.03	0	1.84	0	0.03	0	104.03	0	0.74	0	164763	0	14246936	0	977018	0	18464	0	9829	0	0	0	4254121	0	2193	0	0	0	17397	0	2666626	0	21166	0	2707382	0	63.08	0	8987504	0	147891	2303804	15.577716020583	14246936.0	9964522.0	164763.0	977018.0	18464.0	9829.0	0.0	4254121.0	8987504.0	69.9	1.2	6.9	0.1	0.1	0.0	29.9	63.1	100	100	100.00	38	1424693600	25.8	25.5	24.9	23.8	0.0	30.8	11.7	bulk
1930377	SRR528748	SRP014599	SRS348126	SRX171524	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_monosome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	2925062800	14625314	2015-07-22 17:07:41	1793564365	2925062800	14625314	2	14625314	index:0,count:14625314,average:100,stdev:0|index:1,count:14625314,average:100,stdev:0	KO_monosome_2	JAX					5.4	3.39	0.01	1493743337	1466580413	1350296785	1338383917	98.18	99.12	10203986	9752117	166.652	506.183	124	120481	82.39	91.35	11725216	8406914	11725216	8406914	85.24	85.93	11725216	8698249	11725216	7908482	72285592	4.84	1.15	0	6.84	0	0.13	0	0.07	0	0.00	0	30.03	0	10203986	0	200	0	196.35	0	2.45	0	0.03	0	1.84	0	0.03	0	50.67	0	0.75	0	168581	0	14625314	0	1000740	0	18961	0	10026	0	0	0	4392341	0	2303	0	0	0	17700	0	2725365	0	21255	0	2766623	0	62.93	0	9203246	0	148756	2356247	15.839677055043	14625314.0	10203986.0	168581.0	1000740.0	18961.0	10026.0	0.0	4392341.0	9203246.0	69.8	1.2	6.8	0.1	0.1	0.0	30.0	62.9	100	100	100.00	38	1462531400	25.8	25.5	24.9	23.8	0.0	30.7	11.6	bulk
1930392	SRR528749	SRP014599	SRS348126	SRX171524	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_monosome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	2869225200	14346126	2015-07-22 17:07:41	1762894492	2869225200	14346126	2	14346126	index:0,count:14346126,average:100,stdev:0|index:1,count:14346126,average:100,stdev:0	KO_monosome_6	JAX					5.39	3.4	0.01	1464678568	1438117002	1324106639	1312392670	98.19	99.12	10011123	9567938	166.507	506.067	124	118173	82.4	91.36	11501903	8249647	11501903	8249647	85.25	85.94	11501903	8534071	11501903	7760209	70863349	4.84	1.15	0	6.84	0	0.13	0	0.07	0	0.00	0	30.02	0	10011123	0	200	0	196.30	0	2.44	0	0.03	0	1.83	0	0.03	0	54.59	0	0.77	0	164570	0	14346126	0	981043	0	18384	0	9963	0	0	0	4306656	0	2204	0	0	0	17289	0	2670261	0	20882	0	2710636	0	62.94	0	9030080	0	148099	2310310	15.599767722942	14346126.0	10011123.0	164570.0	981043.0	18384.0	9963.0	0.0	4306656.0	9030080.0	69.8	1.1	6.8	0.1	0.1	0.0	30.0	62.9	100	100	100.00	38	1434612600	25.9	25.4	25.0	23.7	0.0	30.5	11.5	bulk
1930504	SRR528750	SRP014599	SRS348126	SRX171524	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_monosome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	2792117000	13960585	2015-07-22 17:07:41	1722230937	2792117000	13960585	2	13960585	index:0,count:13960585,average:100,stdev:0|index:1,count:13960585,average:100,stdev:0	KO_monosome_7	JAX					5.39	3.4	0.01	1424845254	1398914658	1288283264	1276795279	98.18	99.11	9738276	9308288	166.532	503.506	124	115027	82.44	91.38	11185790	8027811	11185790	8027811	85.29	85.99	11185790	8305873	11185790	7553945	68656054	4.82	1.15	0	6.83	0	0.13	0	0.07	0	0.00	0	30.05	0	9738276	0	200	0	196.25	0	2.45	0	0.03	0	1.83	0	0.03	0	97.59	0	0.79	0	159904	0	13960585	0	953368	0	18167	0	9555	0	0	0	4194587	0	2165	0	0	0	16559	0	2589051	0	20235	0	2628010	0	62.93	0	8784908	0	147152	2242159	15.237027019680	13960585.0	9738276.0	159904.0	953368.0	18167.0	9555.0	0.0	4194587.0	8784908.0	69.8	1.1	6.8	0.1	0.1	0.0	30.0	62.9	100	100	100.00	38	1396058500	25.9	25.4	24.9	23.7	0.1	30.4	11.5	bulk
1933852	SRR527821	SRP014599	SRS348125	SRX171211	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_monosome		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_monosome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3190590600	15952953	2015-07-22 17:07:41	2002003755	3190590600	15952953	2	15952953	index:0,count:15952953,average:100,stdev:0|index:1,count:15952953,average:100,stdev:0	WT_monosome_6	JAX					7.28	3.37	0.01	2239958774	2207952591	2029156163	2017878723	98.57	99.44	14674952	14103201	172.353	452.418	134	172771	84.84	93.78	16624434	12450548	16624434	12450548	88.99	89.5	16624434	13059192	16624434	11881262	79239839	3.54	1.03	0	8.77	0	0.16	0	0.07	0	0.00	0	7.79	0	14674952	0	200	0	197.12	0	2.34	0	0.03	0	1.68	0	0.02	0	182.32	0	0.71	0	164938	0	15952953	0	1399179	0	24853	0	11005	0	0	0	1242143	0	3531	0	0	0	25098	0	3741978	0	41457	0	3812064	0	83.22	0	13275773	0	166754	3316382	19.887870755724	15952953.0	14674952.0	164938.0	1399179.0	24853.0	11005.0	0.0	1242143.0	13275773.0	92.0	1.0	8.8	0.2	0.1	0.0	7.8	83.2	100	100	100.00	38	1595295300	25.4	24.6	24.5	25.4	0.0	32.9	14.2	bulk
1934600	SRR527850	SRP014599	SRS348125	SRX171211	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_monosome		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_monosome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3115922000	15579610	2015-07-22 17:07:41	1961638992	3115922000	15579610	2	15579610	index:0,count:15579610,average:100,stdev:0|index:1,count:15579610,average:100,stdev:0	WT_monosome_7	JAX					7.27	3.37	0.01	2186896462	2155678689	1981267451	1970250336	98.57	99.44	14325077	13767232	172.326	450.918	134	168765	84.85	93.78	16223409	12154711	16223409	12154711	88.99	89.5	16223409	12747390	16223409	11599471	77557281	3.55	1.03	0	8.76	0	0.16	0	0.07	0	0.00	0	7.83	0	14325077	0	200	0	197.07	0	2.33	0	0.03	0	1.68	0	0.02	0	165.45	0	0.73	0	160542	0	15579610	0	1364799	0	24684	0	10592	0	0	0	1219257	0	3336	0	0	0	24595	0	3646553	0	40335	0	3714819	0	83.19	0	12960278	0	165804	3235764	19.515596728668	15579610.0	14325077.0	160542.0	1364799.0	24684.0	10592.0	0.0	1219257.0	12960278.0	91.9	1.0	8.8	0.2	0.1	0.0	7.8	83.2	100	100	100.00	38	1557961000	25.4	24.6	24.5	25.4	0.1	32.8	14.1	bulk
1934616	SRR527851	SRP014599	SRS348125	SRX171211	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_monosome		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_monosome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3171127400	15855637	2015-07-22 17:07:41	1990957656	3171127400	15855637	2	15855637	index:0,count:15855637,average:100,stdev:0|index:1,count:15855637,average:100,stdev:0	WT_monosome_8	JAX					7.26	3.37	0.01	2226243424	2194192734	2017117161	2005640345	98.56	99.43	14581511	14013086	172.401	454.098	135	170929	84.83	93.76	16513574	12369756	16513574	12369756	88.95	89.45	16513574	12970054	16513574	11802106	78917678	3.54	1.03	0	8.75	0	0.16	0	0.07	0	0.00	0	7.81	0	14581511	0	200	0	197.11	0	2.32	0	0.03	0	1.68	0	0.02	0	208.32	0	0.71	0	163535	0	15855637	0	1388027	0	25009	0	10871	0	0	0	1238246	0	3319	0	0	0	25029	0	3719321	0	41402	0	3789071	0	83.21	0	13193484	0	166235	3297283	19.835070833459	15855637.0	14581511.0	163535.0	1388027.0	25009.0	10871.0	0.0	1238246.0	13193484.0	92.0	1.0	8.8	0.2	0.1	0.0	7.8	83.2	100	100	100.00	38	1585563700	25.4	24.7	24.5	25.4	0.0	33.0	14.3	bulk
965015	SRR528732	SRP014599	SRS348125	SRX171237	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_polysome		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3934177200	19670886	2015-07-22 17:07:41	2456184167	3934177200	19670886	2	19670886	index:0,count:19670886,average:100,stdev:0|index:1,count:19670886,average:100,stdev:0	WT_polysome_1	JAX					2.48	3.56	0.01	2814726593	2798037611	2670586906	2670936790	99.41	100.01	18626205	17583100	174.087	583.628	125	194756	90.74	95.74	20096507	16900672	20096507	16900672	91.31	91.98	20096507	17007070	20096507	16236215	75430952	2.68	1.56	0	4.95	0	0.22	0	0.05	0	0.00	0	5.04	0	18626205	0	200	0	196.95	0	2.18	0	0.02	0	1.64	0	0.02	0	230.67	0	0.65	0	306723	0	19670886	0	973438	0	43368	0	9156	0	0	0	992157	0	5310	0	0	0	41214	0	6197698	0	35496	0	6279718	0	89.74	0	17652767	0	180721	5323318	29.456001239480	19670886.0	18626205.0	306723.0	973438.0	43368.0	9156.0	0.0	992157.0	17652767.0	94.7	1.6	4.9	0.2	0.0	0.0	5.0	89.7	100	100	100.00	38	1967088600	25.4	24.7	24.5	25.4	0.0	33.4	14.8	bulk
965030	SRR528734	SRP014599	SRS348125	SRX171237	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_polysome		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	4014176200	20070881	2015-07-22 17:07:41	2522269219	4014176200	20070881	2	20070881	index:0,count:20070881,average:100,stdev:0|index:1,count:20070881,average:100,stdev:0	WT_polysome_6	JAX					2.49	3.56	0.01	2865999730	2848878464	2719117028	2719329069	99.4	100.01	18974261	17913834	173.968	583.737	125	199376	90.73	95.74	20470625	17215332	20470625	17215332	91.31	91.98	20470625	17324459	20470625	16539411	76909197	2.68	1.55	0	4.94	0	0.22	0	0.05	0	0.00	0	5.20	0	18974261	0	200	0	196.84	0	2.18	0	0.02	0	1.63	0	0.02	0	104.41	0	0.69	0	311371	0	20070881	0	992364	0	44273	0	9422	0	0	0	1042925	0	5366	0	0	0	41546	0	6283861	0	35580	0	6366353	0	89.59	0	17981897	0	181560	5403420	29.761070720423	20070881.0	18974261.0	311371.0	992364.0	44273.0	9422.0	0.0	1042925.0	17981897.0	94.5	1.6	4.9	0.2	0.0	0.0	5.2	89.6	100	100	100.00	38	2007088100	25.4	24.7	24.5	25.4	0.0	33.1	14.4	bulk
965047	SRR528736	SRP014599	SRS348125	SRX171237	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_polysome		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3979243200	19896216	2015-07-22 17:07:41	2501122770	3979243200	19896216	2	19896216	index:0,count:19896216,average:100,stdev:0|index:1,count:19896216,average:100,stdev:0	WT_polysome_8	JAX					2.49	3.55	0.01	2841872430	2824858253	2696196435	2696385578	99.4	100.01	18808189	17757966	174.073	585.533	125	196840	90.72	95.73	20292976	17062682	20292976	17062682	91.3	91.97	20292976	17171885	20292976	16393313	76489627	2.69	1.55	0	4.94	0	0.22	0	0.05	0	0.00	0	5.20	0	18808189	0	200	0	196.84	0	2.19	0	0.02	0	1.64	0	0.02	0	223.14	0	0.68	0	308434	0	19896216	0	983859	0	43742	0	9315	0	0	0	1034970	0	5470	0	0	0	41923	0	6229340	0	35557	0	6312290	0	89.59	0	17824330	0	181344	5356091	29.535529160049	19896216.0	18808189.0	308434.0	983859.0	43742.0	9315.0	0.0	1034970.0	17824330.0	94.5	1.6	4.9	0.2	0.0	0.0	5.2	89.6	100	100	100.00	38	1989621600	25.4	24.7	24.5	25.4	0.0	33.2	14.5	bulk
965055	SRR528737	SRP014599	SRS348125	SRX171238	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (WT) CELF4_RNAgranule		Paired end RNA sequencing of pooled polysome fractions from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (KO) female adult cerebral cortex   hippocampus combined.  Tissue extracts from 3 biological replicates from each strain were subjected to sucrose gradient fractionation.  Individual fractions from each replicate were pooled into three groups ("monosomes," "polysomes," "RNA granules"), and then split again into 5 technical replicates each for sequencing (R1, R2 forward and reverse paired ends, respectively	WT_RNAgranule	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	genotype;;tm1Frk/tm1Frk (KO)|strain;;129S1		200	CELF4_polysomes	Mus musculus 129S1 CELF4_polysomes	3756832800	18784164	2015-07-22 17:07:41	2350571665	3756832800	18784164	2	18784164	index:0,count:18784164,average:100,stdev:0|index:1,count:18784164,average:100,stdev:0	WT_RNAgranule_1	JAX					3.44	3.57	0.01	2709856589	2701118438	2563523519	2569193065	99.68	100.22	17817957	16733571	176.526	614.412	125	183337	91.12	96.43	19271266	16236378	19271266	16236378	92.21	92.76	19271266	16430670	19271266	15618556	56343639	2.08	1.50	0	5.22	0	0.30	0	0.04	0	0.00	0	4.80	0	17817957	0	200	0	196.93	0	2.19	0	0.02	0	1.66	0	0.02	0	210.66	0	0.66	0	281941	0	18784164	0	980455	0	57089	0	6607	0	0	0	902511	0	4793	0	0	0	45728	0	6472861	0	34917	0	6558299	0	89.64	0	16837502	0	171006	5541450	32.405003333216	18784164.0	17817957.0	281941.0	980455.0	57089.0	6607.0	0.0	902511.0	16837502.0	94.9	1.5	5.2	0.3	0.0	0.0	4.8	89.6	100	100	100.00	38	1878416400	25.1	25.0	24.7	25.1	0.0	33.4	14.8	bulk
965263	SRR528751	SRP014599	SRS348126	SRX171524	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_monosome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	2839090800	14195454	2015-07-22 17:07:41	1746367895	2839090800	14195454	2	14195454	index:0,count:14195454,average:100,stdev:0|index:1,count:14195454,average:100,stdev:0	KO_monosome_8	JAX					5.39	3.4	0.01	1447952207	1421693953	1308873546	1297388264	98.19	99.12	9890968	9453744	166.645	509.908	124	116937	82.39	91.35	11367076	8148842	11367076	8148842	85.24	85.94	11367076	8431399	11367076	7666508	70317014	4.86	1.15	0	6.83	0	0.13	0	0.07	0	0.00	0	30.12	0	9890968	0	200	0	196.29	0	2.44	0	0.03	0	1.84	0	0.03	0	49.66	0	0.77	0	163880	0	14195454	0	970213	0	18503	0	9841	0	0	0	4276142	0	2289	0	0	0	16893	0	2634087	0	21007	0	2674276	0	62.84	0	8920755	0	147904	2277473	15.398319180009	14195454.0	9890968.0	163880.0	970213.0	18503.0	9841.0	0.0	4276142.0	8920755.0	69.7	1.2	6.8	0.1	0.1	0.0	30.1	62.8	100	100	100.00	38	1419545400	25.9	25.4	25.0	23.7	0.0	30.6	11.6	bulk
965271	SRR528752	SRP014599	SRS348126	SRX171523	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3629993000	18149965	2015-07-22 17:07:41	2270815153	3629993000	18149965	2	18149965	index:0,count:18149965,average:100,stdev:0|index:1,count:18149965,average:100,stdev:0	KO_polysome_1	JAX					1.87	3.5	0.01	2589136125	2578183975	2464376313	2468254621	99.58	100.16	17175252	16123228	174.632	636.861	125	176087	91.15	95.88	18484640	15655015	18484640	15655015	91.28	91.97	18484640	15678359	18484640	15015480	66151096	2.55	1.62	0	4.67	0	0.23	0	0.04	0	0.00	0	5.10	0	17175252	0	200	0	196.79	0	2.23	0	0.02	0	1.69	0	0.02	0	231.70	0	0.66	0	294054	0	18149965	0	848325	0	40947	0	7740	0	0	0	926026	0	5537	0	0	0	40964	0	6191170	0	29598	0	6267269	0	89.96	0	16326927	0	172817	5300218	30.669540612324	18149965.0	17175252.0	294054.0	848325.0	40947.0	7740.0	0.0	926026.0	16326927.0	94.6	1.6	4.7	0.2	0.0	0.0	5.1	90.0	100	100	100.00	38	1814996500	25.1	25.0	24.9	25.0	0.0	33.3	14.8	bulk
965279	SRR528753	SRP014599	SRS348126	SRX171523	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3684223800	18421119	2015-07-22 17:07:41	2319160330	3684223800	18421119	2	18421119	index:0,count:18421119,average:100,stdev:0|index:1,count:18421119,average:100,stdev:0	KO_polysome_6	JAX					1.87	3.51	0.01	2622884073	2611874616	2496292667	2500338985	99.58	100.16	17409593	16344567	174.495	632.292	125	178695	91.14	95.88	18740529	15866428	18740529	15866428	91.26	91.95	18740529	15887958	18740529	15215935	67217510	2.56	1.61	0	4.67	0	0.22	0	0.04	0	0.00	0	5.23	0	17409593	0	200	0	196.69	0	2.22	0	0.02	0	1.69	0	0.02	0	193.91	0	0.69	0	295753	0	18421119	0	861002	0	41215	0	7778	0	0	0	962533	0	5330	0	0	0	41192	0	6244095	0	29478	0	6320095	0	89.83	0	16548591	0	173750	5346278	30.769945323741	18421119.0	17409593.0	295753.0	861002.0	41215.0	7778.0	0.0	962533.0	16548591.0	94.5	1.6	4.7	0.2	0.0	0.0	5.2	89.8	100	100	100.00	38	1842111900	25.1	25.0	24.9	25.0	0.0	33.0	14.4	bulk
965287	SRR528754	SRP014599	SRS348126	SRX171523	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3646340000	18231700	2015-07-22 17:07:41	2296019439	3646340000	18231700	2	18231700	index:0,count:18231700,average:100,stdev:0|index:1,count:18231700,average:100,stdev:0	KO_polysome_8	JAX					1.87	3.51	0.01	2596779440	2585914070	2471505548	2475523023	99.58	100.16	17229698	16174789	174.566	635.989	125	176142	91.14	95.88	18543689	15702872	18543689	15702872	91.27	91.95	18543689	15725385	18543689	15059783	66616472	2.57	1.60	0	4.67	0	0.22	0	0.04	0	0.00	0	5.23	0	17229698	0	200	0	196.69	0	2.22	0	0.02	0	1.69	0	0.02	0	236.09	0	0.69	0	292563	0	18231700	0	851438	0	40780	0	7893	0	0	0	953329	0	5509	0	0	0	40599	0	6182351	0	29501	0	6257960	0	89.83	0	16378260	0	173242	5296713	30.574069798317	18231700.0	17229698.0	292563.0	851438.0	40780.0	7893.0	0.0	953329.0	16378260.0	94.5	1.6	4.7	0.2	0.0	0.0	5.2	89.8	100	100	100.00	38	1823170000	25.1	25.0	24.9	25.0	0.0	33.1	14.5	bulk
965294	SRR528755	SRP014599	SRS348126	SRX171523	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3710080800	18550404	2015-07-22 17:07:41	2330597136	3710080800	18550404	2	18550404	index:0,count:18550404,average:100,stdev:0|index:1,count:18550404,average:100,stdev:0	KO_polysome_2	JAX					1.87	3.51	0.01	2644597589	2633639718	2517063611	2521180774	99.59	100.16	17544776	16469961	174.577	634.197	125	180217	91.15	95.89	18881835	15991742	18881835	15991742	91.28	91.96	18881835	16014284	18881835	15336476	67579766	2.56	1.61	0	4.67	0	0.22	0	0.04	0	0.00	0	5.16	0	17544776	0	200	0	196.76	0	2.23	0	0.02	0	1.69	0	0.02	0	235.98	0	0.67	0	298185	0	18550404	0	867175	0	41313	0	7948	0	0	0	956367	0	5469	0	0	0	41397	0	6313715	0	30045	0	6390626	0	89.90	0	16677601	0	174120	5404957	31.041563289685	18550404.0	17544776.0	298185.0	867175.0	41313.0	7948.0	0.0	956367.0	16677601.0	94.6	1.6	4.7	0.2	0.0	0.0	5.2	89.9	100	100	100.00	38	1855040400	25.1	25.0	24.9	25.0	0.0	33.3	14.7	bulk
965303	SRR528756	SRP014599	SRS348126	SRX171523	SRA055349	The Jackson Laboratory		CELF4 wt and knockout transcriptome by polysome fractions	CELF4 wildtype and mutant polysome; 129S1/SvImJ inbred mouse strai.n		Mouse 129S1 (KO) CELF4_polysome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1< / > (WT) and 129S1-Celf4<tm1Frk/tm1Frk> (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively).	KO_polysome	RNA-Seq	TRANSCRIPTOMIC	Hybrid Selection	paired				Illumina HiSeq 2000	dev_stage;;adult|sex;;male|strain;;129S1|tissue;;hippocampus CA1 region		200	CELF4_hippocampal_CA1_dissection	Mus musculus 129S1 (WT) hippocampus CA1 region	3593846600	17969233	2015-07-22 17:07:41	2269452487	3593846600	17969233	2	17969233	index:0,count:17969233,average:100,stdev:0|index:1,count:17969233,average:100,stdev:0	KO_polysome_7	JAX					1.87	3.52	0.01	2557415782	2546605615	2434031474	2437859802	99.58	100.16	16971492	15932408	174.544	633.991	125	173759	91.14	95.88	18267094	15468406	18267094	15468406	91.28	91.97	18267094	15491455	18267094	14836422	65551445	2.56	1.61	0	4.67	0	0.22	0	0.04	0	0.00	0	5.29	0	16971492	0	200	0	196.65	0	2.22	0	0.02	0	1.69	0	0.02	0	199.04	0	0.71	0	288556	0	17969233	0	838859	0	39946	0	7575	0	0	0	950220	0	5399	0	0	0	40237	0	6077052	0	28942	0	6151630	0	89.78	0	16132633	0	172537	5211014	30.202298637394	17969233.0	16971492.0	288556.0	838859.0	39946.0	7575.0	0.0	950220.0	16132633.0	94.4	1.6	4.7	0.2	0.0	0.0	5.3	89.8	100	100	100.00	38	1796923300	25.1	25.0	24.9	25.0	0.1	32.9	14.3	bulk
1844873	SRR540268	SRP014858	SRS356268	SRX176917	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		wt mouse hippocampal cell body transcriptome		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	wt 129S1 cell body A	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;body|strain;;129S1/SvImJ|tissue;;hippocampal CA1		200	129S1_hippocampus_cb	Mus musculus 129S1 hippocampus cell body	6677611000	33388055	2012-08-15 10:32:11	5004929631	6677611000	33388055	2	33388055	index:0,count:33388055,average:100,stdev:0|index:1,count:33388055,average:100,stdev:0	wt_A_cb_GES11_4836_ATCACG_L007	JAX					17.6	2.46	0.05	4934304507	4898591079	4763021987	4747777791	99.28	99.68	30417683	29434966	178.419	572.781	150	290459	66.58	69.11	32195466	20253015	32195466	20253015	64.46	64.72	32195466	19607442	32195466	18966395	1383859312	28.05	4.52	0	3.33	0	0.22	0	0.18	0	0.00	0	8.50	0	30417683	0	200	0	195.49	0	2.40	0	0.02	0	2.46	0	0.02	0	207.95	0	0.77	0	1510615	0	33388055	0	1111861	0	72434	0	59630	0	0	0	2838308	0	5972	0	0	0	42094	0	5661028	0	37127	0	5746221	0	87.77	0	29305822	0	181522	5264491	29.001944667864	33388055.0	30417683.0	1510615.0	1111861.0	72434.0	59630.0	0.0	2838308.0	29305822.0	91.1	4.5	3.3	0.2	0.2	0.0	8.5	87.8	100	100	100.00	38	3338805500	26.9	22.6	22.9	26.7	0.8	33.0	16.1	bulk
1845000	SRR540270	SRP014858	SRS356268	SRX176917	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		wt mouse hippocampal cell body transcriptome		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	wt 129S1 cell body A	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;body|strain;;129S1/SvImJ|tissue;;hippocampal CA1		200	129S1_hippocampus_cb	Mus musculus 129S1 hippocampus cell body	5856469400	29282347	2012-08-15 10:53:10	4388343255	5856469400	29282347	2	29282347	index:0,count:29282347,average:100,stdev:0|index:1,count:29282347,average:100,stdev:0	wt_B_cb_GES11_4838_TTAGGC_L007	JAX					15.76	2.34	0.04	4237274891	4201658669	4066890784	4051025271	99.16	99.61	25722788	24747223	185.230	634.000	158	226769	68.34	71.39	27416298	17579259	27416298	17579259	65.51	66.06	27416298	16851092	27416298	16268289	1085243013	25.61	6.30	0	3.75	0	0.19	0	0.15	0	0.00	0	11.81	0	25722788	0	200	0	194.03	0	2.75	0	0.02	0	2.17	0	0.02	0	306.44	0	0.84	0	1845553	0	29282347	0	1096946	0	55599	0	44604	0	0	0	3459356	0	5378	0	0	0	37067	0	5137439	0	34212	0	5214096	0	84.10	0	24625842	0	168390	4853459	28.822727002791	29282347.0	25722788.0	1845553.0	1096946.0	55599.0	44604.0	0.0	3459356.0	24625842.0	87.8	6.3	3.7	0.2	0.2	0.0	11.8	84.1	100	100	100.00	38	2928234700	25.9	23.6	23.9	25.8	0.8	32.6	15.5	bulk
1845016	SRR540271	SRP014858	SRS356269	SRX176918	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		wt mouse hippocampal neuropil transcriptome		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	wt 129S1 neuropil A	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;neuropil|strain;;129S1/SvImJ|tissue;;hippocampal CA1		200	129S1_hippocampus_np	Mus musculus 129S1 hippocampus neuropil	5838180800	29190904	2012-08-15 11:00:23	4356954667	5838180800	29190904	2	29190904	index:0,count:29190904,average:100,stdev:0|index:1,count:29190904,average:100,stdev:0	wt_B_np_GES11_4839_TTAGGC_L008	JAX					29.81	1.95	0.03	4411162261	4381384775	4251540935	4236958536	99.32	99.66	26493126	25629564	187.591	567.618	155	229235	73.77	76.71	27976092	19544894	27976092	19544894	72.28	72.66	27976092	19149340	27976092	18513794	932185644	21.13	5.60	0	3.47	0	0.17	0	0.12	0	0.00	0	8.96	0	26493126	0	200	0	195.33	0	2.49	0	0.02	0	2.41	0	0.02	0	275.10	0	0.76	0	1635542	0	29190904	0	1012808	0	48665	0	34974	0	0	0	2614139	0	4348	0	0	0	31261	0	4367524	0	27435	0	4430568	0	87.29	0	25480318	0	161991	4132021	25.507719564667	29190904.0	26493126.0	1635542.0	1012808.0	48665.0	34974.0	0.0	2614139.0	25480318.0	90.8	5.6	3.5	0.2	0.1	0.0	9.0	87.3	100	100	100.00	38	2919090400	27.4	22.6	22.8	27.2	0.0	33.6	17.3	bulk
1845048	SRR540273	SRP014858	SRS356269	SRX176918	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		wt mouse hippocampal neuropil transcriptome		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	wt 129S1 neuropil A	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;neuropil|strain;;129S1/SvImJ|tissue;;hippocampal CA1		200	129S1_hippocampus_np	Mus musculus 129S1 hippocampus neuropil	6784252600	33921263	2012-08-15 11:18:18	5052318495	6784252600	33921263	2	33921263	index:0,count:33921263,average:100,stdev:0|index:1,count:33921263,average:100,stdev:0	wt_C_np_GES11_4841_ACTTGA_L008	JAX					25.52	2.12	0.04	5134113451	5078707048	4956481234	4920250159	98.92	99.27	31125844	30089928	184.205	553.230	154	278332	72.25	75.0	32857385	22489868	32857385	22489868	70.99	71.35	32857385	22096164	32857385	21397477	1172233285	22.83	4.62	0	3.35	0	0.18	0	0.14	0	0.00	0	7.92	0	31125844	0	200	0	195.85	0	2.37	0	0.02	0	2.56	0	0.02	0	288.01	0	0.74	0	1566462	0	33921263	0	1137603	0	60617	0	46768	0	0	0	2688034	0	6148	0	0	0	41091	0	5571886	0	32627	0	5651752	0	88.41	0	29988241	0	173705	5223124	30.068932961055	33921263.0	31125844.0	1566462.0	1137603.0	60617.0	46768.0	0.0	2688034.0	29988241.0	91.8	4.6	3.4	0.2	0.1	0.0	7.9	88.4	100	100	100.00	38	3392126300	27.3	22.7	22.9	27.1	0.0	33.7	17.4	bulk
1845064	SRR540274	SRP014858	SRS356275	SRX176920	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		Celf4 knock out mouse hippocampal cell body transcriptome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1( / ) (WT) and 129S1-Celf4 (tm1Frk/tm1Frk) (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively)	129S1 Celf4 cell body	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;cell body|strain;;129S1-Celf4 tm1Frk/tm1Frk (DEL)|tissue;;hippocampal CA1		200	129S1-Celf4_hippocampus_cb	Mus musculus 129S1-Celf4(tm1Frk/tm1Frk) (DEL) cell body	6337074600	31685373	2012-08-15 11:28:11	4748772609	6337074600	31685373	2	31685373	index:0,count:31685373,average:100,stdev:0|index:1,count:31685373,average:100,stdev:0	del_A_cb_GES11_4842_GATCAG_L007	JAX					18.71	2.54	0.05	4733364194	4692111254	4587977139	4564103943	99.13	99.48	28849395	27781805	183.669	625.167	151	259859	70.76	73.11	30311930	20415242	30311930	20415242	69.04	69.21	30311930	19918978	30311930	19326055	1147365994	24.24	4.69	0	2.92	0	0.21	0	0.16	0	0.00	0	8.57	0	28849395	0	200	0	195.52	0	2.23	0	0.02	0	2.82	0	0.02	0	162.95	0	0.77	0	1486886	0	31685373	0	925945	0	67302	0	51976	0	0	0	2716700	0	5130	0	0	0	41477	0	5816221	0	37747	0	5900575	0	88.13	0	27923450	0	176052	5441753	30.909918660396	31685373.0	28849395.0	1486886.0	925945.0	67302.0	51976.0	0.0	2716700.0	27923450.0	91.0	4.7	2.9	0.2	0.2	0.0	8.6	88.1	100	100	100.00	38	3168537300	26.8	22.6	23.0	26.7	0.8	33.0	16.1	bulk
1845083	SRR540275	SRP014858	SRS356275	SRX176920	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		Celf4 knock out mouse hippocampal cell body transcriptome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1( / ) (WT) and 129S1-Celf4 (tm1Frk/tm1Frk) (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively)	129S1 Celf4 cell body	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;cell body|strain;;129S1-Celf4 tm1Frk/tm1Frk (DEL)|tissue;;hippocampal CA1		200	129S1-Celf4_hippocampus_cb	Mus musculus 129S1-Celf4(tm1Frk/tm1Frk) (DEL) cell body	5851692000	29258460	2012-08-15 11:34:10	4381121091	5851692000	29258460	2	29258460	index:0,count:29258460,average:100,stdev:0|index:1,count:29258460,average:100,stdev:0	del_B_cb_GES11_4844_TAGCTT_L007	JAX					19.68	2.48	0.04	4354203039	4334549857	4214063191	4210314795	99.55	99.91	26318418	25322791	186.258	638.920	154	230008	71.58	74.07	27707738	18838382	27707738	18838382	69.67	69.87	27707738	18337051	27707738	17769444	1019923858	23.42	5.21	0	3.03	0	0.22	0	0.15	0	0.00	0	9.68	0	26318418	0	200	0	195.15	0	2.27	0	0.02	0	2.69	0	0.02	0	208.58	0	0.78	0	1523043	0	29258460	0	885513	0	64864	0	44260	0	0	0	2830918	0	4745	0	0	0	37786	0	5274359	0	36800	0	5353690	0	86.92	0	25432905	0	169647	4979063	29.349549358374	29258460.0	26318418.0	1523043.0	885513.0	64864.0	44260.0	0.0	2830918.0	25432905.0	90.0	5.2	3.0	0.2	0.2	0.0	9.7	86.9	100	100	100.00	38	2925846000	26.8	22.7	23.1	26.7	0.8	33.0	16.0	bulk
1845099	SRR540276	SRP014858	SRS356274	SRX176919	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		Celf4 knock out mouse hippocampal neuropil transcriptome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1( / ) (WT) and 129S1-Celf4 (tm1Frk/tm1Frk) (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively)	129S1 Celf4 neuropil	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;neuropil|strain;;129S1-Celf4 tm1Frk/tm1Frk (DEL)|tissue;;hippocampal CA1		200	129S1-Celf4_hippocampus_np	Mus musculus 129S1-Celf4(tm1Frk/tm1Frk) (DEL) hippocampus neuropil	5171659800	25858299	2012-08-15 11:38:13	3851413688	5171659800	25858299	2	25858299	index:0,count:25858299,average:100,stdev:0|index:1,count:25858299,average:100,stdev:0	del_B_np_GES11_4845_GATCAG_L008	JAX					22.82	2.3	0.04	3879677639	3849806274	3746008108	3730641055	99.23	99.59	23379108	22540282	187.331	609.961	153	202516	70.81	73.48	24691658	16555595	24691658	16555595	69.08	69.4	24691658	16150345	24691658	15636770	935672909	24.12	5.92	0	3.28	0	0.20	0	0.15	0	0.00	0	9.24	0	23379108	0	200	0	195.20	0	2.44	0	0.02	0	2.42	0	0.02	0	181.11	0	0.76	0	1532008	0	25858299	0	848719	0	51559	0	38737	0	0	0	2388895	0	4517	0	0	0	31441	0	4270849	0	29211	0	4336018	0	87.13	0	22530389	0	161844	4023795	24.862182101283	25858299.0	23379108.0	1532008.0	848719.0	51559.0	38737.0	0.0	2388895.0	22530389.0	90.4	5.9	3.3	0.2	0.1	0.0	9.2	87.1	100	100	100.00	38	2585829900	27.2	22.8	23.0	27.0	0.0	33.6	17.3	bulk
1845117	SRR540277	SRP014858	SRS356274	SRX176919	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		Celf4 knock out mouse hippocampal neuropil transcriptome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1( / ) (WT) and 129S1-Celf4 (tm1Frk/tm1Frk) (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively)	129S1 Celf4 neuropil	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;neuropil|strain;;129S1-Celf4 tm1Frk/tm1Frk (DEL)|tissue;;hippocampal CA1		200	129S1-Celf4_hippocampus_np	Mus musculus 129S1-Celf4(tm1Frk/tm1Frk) (DEL) hippocampus neuropil	6658322800	33291614	2012-08-15 11:48:14	4955536832	6658322800	33291614	2	33291614	index:0,count:33291614,average:100,stdev:0|index:1,count:33291614,average:100,stdev:0	del_C_np_GES11_4847_TAGCTT_L008	JAX					21.36	2.32	0.04	4996522562	4957371982	4829988551	4809381099	99.22	99.57	30234183	29199050	184.316	602.775	154	269899	69.87	72.41	31878053	21124906	31878053	21124906	67.98	68.21	31878053	20551879	31878053	19899027	1244404239	24.91	5.54	0	3.18	0	0.21	0	0.17	0	0.00	0	8.80	0	30234183	0	200	0	195.43	0	2.37	0	0.02	0	2.53	0	0.02	0	286.72	0	0.75	0	1845003	0	33291614	0	1059826	0	70989	0	58108	0	0	0	2928334	0	5724	0	0	0	41468	0	5576688	0	36425	0	5660305	0	87.63	0	29174357	0	170154	5235853	30.771260152568	33291614.0	30234183.0	1845003.0	1059826.0	70989.0	58108.0	0.0	2928334.0	29174357.0	90.8	5.5	3.2	0.2	0.2	0.0	8.8	87.6	100	100	100.00	38	3329161400	27.2	22.7	23.0	27.1	0.0	33.7	17.3	bulk
1845133	SRR540278	SRP014858	SRS356275	SRX176920	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		Celf4 knock out mouse hippocampal cell body transcriptome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1( / ) (WT) and 129S1-Celf4 (tm1Frk/tm1Frk) (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively)	129S1 Celf4 cell body	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;cell body|strain;;129S1-Celf4 tm1Frk/tm1Frk (DEL)|tissue;;hippocampal CA1		200	129S1-Celf4_hippocampus_cb	Mus musculus 129S1-Celf4(tm1Frk/tm1Frk) (DEL) cell body	5974831000	29874155	2012-08-15 11:55:14	4473698052	5974831000	29874155	2	29874155	index:0,count:29874155,average:100,stdev:0|index:1,count:29874155,average:100,stdev:0	del_D_cb_GES11_4848_GGCTAC_L007	JAX					29.4	2.27	0.03	4455619842	4470351699	4274601293	4304173435	100.33	100.69	27107607	26156195	182.180	557.875	154	252291	80.7	84.29	28837179	21874757	28837179	21874757	78.87	79.5	28837179	21379430	28837179	20630598	622137372	13.96	4.46	0	3.87	0	0.23	0	0.09	0	0.00	0	8.94	0	27107607	0	200	0	195.43	0	2.44	0	0.02	0	2.55	0	0.02	0	259.78	0	0.77	0	1331761	0	29874155	0	1156974	0	67602	0	26905	0	0	0	2672041	0	6000	0	0	0	38861	0	5389510	0	29230	0	5463601	0	86.87	0	25950633	0	170851	5089934	29.791654716683	29874155.0	27107607.0	1331761.0	1156974.0	67602.0	26905.0	0.0	2672041.0	25950633.0	90.7	4.5	3.9	0.2	0.1	0.0	8.9	86.9	100	100	100.00	38	2987415500	26.8	22.7	23.0	26.7	0.8	32.9	15.8	bulk
1845148	SRR540279	SRP014858	SRS356274	SRX176919	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		Celf4 knock out mouse hippocampal neuropil transcriptome		Paired end RNA sequencing of the CA1 region of the hippocampus from mouse strain 129S1( / ) (WT) and 129S1-Celf4 (tm1Frk/tm1Frk) (DEL) male adult, dissected into cell body (cb) and neuropil (np) components. 3 biological replicates (A,B,C or A,B,D) from each strain-genotype were carried through to sequencing (R1, R2 forward and reverse paired ends, respectively)	129S1 Celf4 neuropil	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;neuropil|strain;;129S1-Celf4 tm1Frk/tm1Frk (DEL)|tissue;;hippocampal CA1		200	129S1-Celf4_hippocampus_np	Mus musculus 129S1-Celf4(tm1Frk/tm1Frk) (DEL) hippocampus neuropil	5359184800	26795924	2012-08-15 12:03:01	3996078172	5359184800	26795924	2	26795924	index:0,count:26795924,average:100,stdev:0|index:1,count:26795924,average:100,stdev:0	del_D_np_GES11_4849_GGCTAC_L008	JAX					29.63	2.05	0.03	4038151270	4018058463	3890217925	3883199610	99.5	99.82	24459923	23639516	184.646	560.399	153	219712	76.81	79.88	25859807	18787172	25859807	18787172	75.59	75.96	25859807	18490450	25859807	17864776	730921116	18.10	5.50	0	3.51	0	0.21	0	0.12	0	0.00	0	8.39	0	24459923	0	200	0	195.47	0	2.35	0	0.02	0	2.68	0	0.02	0	259.32	0	0.74	0	1473320	0	26795924	0	941600	0	56032	0	32994	0	0	0	2246975	0	4547	0	0	0	32758	0	4438314	0	27512	0	4503131	0	87.77	0	23518323	0	165519	4182654	25.269932756964	26795924.0	24459923.0	1473320.0	941600.0	56032.0	32994.0	0.0	2246975.0	23518323.0	91.3	5.5	3.5	0.2	0.1	0.0	8.4	87.8	100	100	100.00	38	2679592400	27.3	22.6	22.9	27.2	0.0	33.6	17.3	bulk
922447	SRR540269	SRP014858	SRS356269	SRX176918	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		wt mouse hippocampal neuropil transcriptome		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	wt 129S1 neuropil A	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;neuropil|strain;;129S1/SvImJ|tissue;;hippocampal CA1		200	129S1_hippocampus_np	Mus musculus 129S1 hippocampus neuropil	7351510400	36757552	2012-08-15 10:45:11	5480225485	7351510400	36757552	2	36757552	index:0,count:36757552,average:100,stdev:0|index:1,count:36757552,average:100,stdev:0	wt_A_np_GES11_4837_ATCACG_L008	JAX					20.83	2.29	0.05	5464852520	5409418132	5279531357	5245204941	98.99	99.35	33738402	32663389	178.332	563.706	147	317083	68.11	70.64	35633516	22980793	35633516	22980793	66.53	66.76	35633516	22444700	35633516	21716272	1461885266	26.75	4.98	0	3.29	0	0.21	0	0.17	0	0.00	0	7.84	0	33738402	0	200	0	195.67	0	2.34	0	0.02	0	2.58	0	0.02	0	263.08	0	0.74	0	1830573	0	36757552	0	1208162	0	75435	0	63195	0	0	0	2880520	0	6571	0	0	0	46240	0	6118722	0	39629	0	6211162	0	88.50	0	32530240	0	176680	5650579	31.981995698438	36757552.0	33738402.0	1830573.0	1208162.0	75435.0	63195.0	0.0	2880520.0	32530240.0	91.8	5.0	3.3	0.2	0.2	0.0	7.8	88.5	100	100	100.00	38	3675755200	27.3	22.7	22.9	27.1	0.0	33.7	17.5	bulk
922518	SRR540272	SRP014858	SRS356268	SRX176917	SRA055284	JAX		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	CELF wildtype and mutant transcriptome by subcellular localization; 129S1/SvImJ.C57BL/6J-Celf4 congenic mouse strain.		wt mouse hippocampal cell body transcriptome		CELF4 wt and knockout transcriptome by localization to hippocampal CA1 cell body or neuropil	wt 129S1 cell body A	RNA-Seq	TRANSCRIPTOMIC	RANDOM	paired				Illumina HiSeq 2000	cellular region;;body|strain;;129S1/SvImJ|tissue;;hippocampal CA1		200	129S1_hippocampus_cb	Mus musculus 129S1 hippocampus cell body	6060090400	30300452	2012-08-15 11:13:12	4534213094	6060090400	30300452	2	30300452	index:0,count:30300452,average:100,stdev:0|index:1,count:30300452,average:100,stdev:0	wt_C_cb_GES11_4840_ACTTGA_L007	JAX					15.48	2.39	0.04	4509798129	4459178875	4339842049	4310524390	98.88	99.32	27070194	26001306	188.431	653.455	160	233623	68.29	71.13	28767582	18485232	28767582	18485232	65.89	66.42	28767582	17835706	28767582	17260404	1184123595	26.26	4.74	0	3.57	0	0.20	0	0.17	0	0.00	0	10.28	0	27070194	0	200	0	195.10	0	2.55	0	0.02	0	2.29	0	0.02	0	269.34	0	0.82	0	1437431	0	30300452	0	1083080	0	61446	0	52438	0	0	0	3116374	0	5280	0	0	0	40004	0	5391516	0	34360	0	5471160	0	85.76	0	25987114	0	171902	5110889	29.731410920175	30300452.0	27070194.0	1437431.0	1083080.0	61446.0	52438.0	0.0	3116374.0	25987114.0	89.3	4.7	3.6	0.2	0.2	0.0	10.3	85.8	100	100	100.00	38	3030045200	26.2	23.3	23.6	26.1	0.8	32.8	15.7	bulk
3582135	SRR579545	SRP015997	SRS366858	SRX191149	SRA059267	GEO		The evolutionary landscape of alternative splicing in vertebrate species	How species with similar repertoires of protein coding genes differ so dramatically at the phenotypic level is poorly understood. From comparing the transcriptomes of multiple organs from vertebrate species spanning ~350 million years of evolution, we observe significant differences in alternative splicing complexity between the main vertebrate lineages, with the highest complexity in the primate lineage. Moreover, within as little as six million years, the splicing profiles of physiologically-equivalent organs have diverged to the extent that they are more strongly related to the identity of a species than they are to organ type. Most vertebrate species-specific splicing patterns are governed by the highly variable use of a largely conserved cis-regulatory code. However, a smaller number of pronounced species-dependent splicing changes are predicted to remodel interactions involving factors acting at multiple steps in gene regulation. These events are expected to further contribute to the dramatic diversification of alternative splicing as well as to other gene regulatory changes that contribute to phenotypic differences among vertebrate species. Overall design: mRNA profiles of several organs (brain, liver, kidney, heart, skeletal muscle) in multiple vertebrate species (mouse, chicken, lizard, frog, pufferfish) generated by deep sequencing using Illumina HiSeq		GSM1015150: Mouse brain rep1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;adult|molecule subtype;;poly-A enriched RNA|sex;;mixed|source_name;;Mouse_brain_pooled|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1015150		GSM1015150	Mouse brain rep1	11571398208	80356932	2012-12-24 12:04:54	7398264144	11571398208	80356932	2	80356932	index:0,count:80356932,average:72,stdev:0|index:1,count:80356932,average:72,stdev:0	GSM1015150_r1	GEO			in_mesa	23258890	2.5	2.52	0.05	7723626225	8024131739	7318247139	7671028639	103.89	104.82	67672240	65436959	130.607	422.520	98	729732	86.17	91.17	73468210	58311450	73468210	58311450	80.47	81.69	73468210	54452873	73468210	52244307	486021092	6.29	3.51	0	4.62	0	0.29	0	0.07	0	0.00	0	15.43	0	67672240	0	144	0	140.35	0	3.37	0	0.02	0	1.44	0	0.01	0	298.54	0	0.89	0	2821314	0	80356932	0	3716191	0	230090	0	57547	0	0	0	12397055	0	9155	0	0	0	97713	0	14273694	0	102439	0	14483001	0	79.59	0	63956049	0	146960	12978576	88.313663581927	80356932.0	67672240.0	2821314.0	3716191.0	230090.0	57547.0	0.0	12397055.0	63956049.0	84.2	3.5	4.6	0.3	0.1	0.0	15.4	79.6	72	72	72.00	39	5785699104	23.3	26.6	26.6	23.4	0.0	32.4	12.7	bulk
3582168	SRR579546	SRP015997	SRS366859	SRX191150	SRA059267	GEO		The evolutionary landscape of alternative splicing in vertebrate species	How species with similar repertoires of protein coding genes differ so dramatically at the phenotypic level is poorly understood. From comparing the transcriptomes of multiple organs from vertebrate species spanning ~350 million years of evolution, we observe significant differences in alternative splicing complexity between the main vertebrate lineages, with the highest complexity in the primate lineage. Moreover, within as little as six million years, the splicing profiles of physiologically-equivalent organs have diverged to the extent that they are more strongly related to the identity of a species than they are to organ type. Most vertebrate species-specific splicing patterns are governed by the highly variable use of a largely conserved cis-regulatory code. However, a smaller number of pronounced species-dependent splicing changes are predicted to remodel interactions involving factors acting at multiple steps in gene regulation. These events are expected to further contribute to the dramatic diversification of alternative splicing as well as to other gene regulatory changes that contribute to phenotypic differences among vertebrate species. Overall design: mRNA profiles of several organs (brain, liver, kidney, heart, skeletal muscle) in multiple vertebrate species (mouse, chicken, lizard, frog, pufferfish) generated by deep sequencing using Illumina HiSeq		GSM1015151: Mouse brain rep2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;adult|molecule subtype;;poly-A enriched RNA|sex;;mixed|source_name;;Mouse_brain_pooled|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1015151		GSM1015151	Mouse brain rep2	9234691448	60754549	2012-12-24 12:04:54	5866049594	9234691448	60754549	2	60754549	index:0,count:60754549,average:76,stdev:0|index:1,count:60754549,average:76,stdev:0	GSM1015151_r1	GEO			in_mesa	23258890	2.39	2.52	0.05	5898453848	6133532022	5598817618	5870643160	103.99	104.86	50602164	48960323	131.258	419.078	98	538137	86.33	91.2	54828840	43684457	54828840	43684457	80.41	81.58	54828840	40688139	54828840	39078754	368140339	6.24	3.46	0	4.45	0	0.28	0	0.06	0	0.00	0	16.38	0	50602164	0	152	0	147.52	0	3.47	0	0.02	0	1.50	0	0.01	0	218.72	0	1.03	0	2099213	0	60754549	0	2701056	0	167813	0	35077	0	0	0	9949495	0	7196	0	0	0	77221	0	11426593	0	82454	0	11593464	0	78.84	0	47901108	0	147368	10173318	69.033426524076	60754549.0	50602164.0	2099213.0	2701056.0	167813.0	35077.0	0.0	9949495.0	47901108.0	83.3	3.5	4.4	0.3	0.1	0.0	16.4	78.8	76	76	76.00	39	4617345724	23.1	26.8	26.9	23.2	0.0	32.7	13.1	bulk
3582198	SRR579547	SRP015997	SRS366860	SRX191151	SRA059267	GEO		The evolutionary landscape of alternative splicing in vertebrate species	How species with similar repertoires of protein coding genes differ so dramatically at the phenotypic level is poorly understood. From comparing the transcriptomes of multiple organs from vertebrate species spanning ~350 million years of evolution, we observe significant differences in alternative splicing complexity between the main vertebrate lineages, with the highest complexity in the primate lineage. Moreover, within as little as six million years, the splicing profiles of physiologically-equivalent organs have diverged to the extent that they are more strongly related to the identity of a species than they are to organ type. Most vertebrate species-specific splicing patterns are governed by the highly variable use of a largely conserved cis-regulatory code. However, a smaller number of pronounced species-dependent splicing changes are predicted to remodel interactions involving factors acting at multiple steps in gene regulation. These events are expected to further contribute to the dramatic diversification of alternative splicing as well as to other gene regulatory changes that contribute to phenotypic differences among vertebrate species. Overall design: mRNA profiles of several organs (brain, liver, kidney, heart, skeletal muscle) in multiple vertebrate species (mouse, chicken, lizard, frog, pufferfish) generated by deep sequencing using Illumina HiSeq		GSM1015152: Mouse liver; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;adult|molecule subtype;;poly-A enriched RNA|sex;;mixed|source_name;;Mouse_liver_pooled|strain;;C57BL/6|tissue;;liver	GEO Accession;;GSM1015152		GSM1015152	Mouse liver	10370110168	68224409	2012-12-24 12:04:54	6689629593	10370110168	68224409	2	68224409	index:0,count:68224409,average:76,stdev:0|index:1,count:68224409,average:76,stdev:0	GSM1015152_r1	GEO			in_mesa	23258890	2.83	1.01	0.05	7296342269	7859013360	6683435794	7295701930	107.71	109.16	57317568	54062910	160.276	442.261	98	555409	82.58	90.38	66404839	47334966	66404839	47334966	74.6	75.61	66404839	42761088	66404839	39596186	429113529	5.88	2.94	0	7.25	0	0.71	0	0.62	0	0.00	0	14.66	0	57317568	0	152	0	147.93	0	4.48	0	0.03	0	1.63	0	0.02	0	186.07	0	1.03	0	2006453	0	68224409	0	4945970	0	483967	0	420988	0	0	0	10001886	0	6183	0	0	0	82496	0	15792091	0	96829	0	15977599	0	76.76	0	52371598	0	150710	16288835	108.080651582509	68224409.0	57317568.0	2006453.0	4945970.0	483967.0	420988.0	0.0	10001886.0	52371598.0	84.0	2.9	7.2	0.7	0.6	0.0	14.7	76.8	76	76	76.00	39	5185055084	23.5	26.2	26.4	23.8	0.0	32.4	12.9	bulk
3582232	SRR579548	SRP015997	SRS366861	SRX191152	SRA059267	GEO		The evolutionary landscape of alternative splicing in vertebrate species	How species with similar repertoires of protein coding genes differ so dramatically at the phenotypic level is poorly understood. From comparing the transcriptomes of multiple organs from vertebrate species spanning ~350 million years of evolution, we observe significant differences in alternative splicing complexity between the main vertebrate lineages, with the highest complexity in the primate lineage. Moreover, within as little as six million years, the splicing profiles of physiologically-equivalent organs have diverged to the extent that they are more strongly related to the identity of a species than they are to organ type. Most vertebrate species-specific splicing patterns are governed by the highly variable use of a largely conserved cis-regulatory code. However, a smaller number of pronounced species-dependent splicing changes are predicted to remodel interactions involving factors acting at multiple steps in gene regulation. These events are expected to further contribute to the dramatic diversification of alternative splicing as well as to other gene regulatory changes that contribute to phenotypic differences among vertebrate species. Overall design: mRNA profiles of several organs (brain, liver, kidney, heart, skeletal muscle) in multiple vertebrate species (mouse, chicken, lizard, frog, pufferfish) generated by deep sequencing using Illumina HiSeq		GSM1015153: Mouse kidney; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;adult|molecule subtype;;poly-A enriched RNA|sex;;mixed|source_name;;Mouse_kidney_pooled|strain;;C57BL/6|tissue;;kidney	GEO Accession;;GSM1015153		GSM1015153	Mouse kidney	6327372150	42182481	2012-12-24 12:04:54	4286763614	6327372150	42182481	2	42182481	index:0,count:42182481,average:75,stdev:0|index:1,count:42182481,average:75,stdev:0	GSM1015153_r1	GEO			in_mesa	23258890	3.75	1.49	0.08	2483751357	2532815677	2281074094	2360224608	101.98	103.47	17960738	16925505	173.354	477.572	153	224456	75.21	82.05	20479060	13509020	20479060	13509020	69.94	70.91	20479060	12561256	20479060	11674985	306437609	12.34	0.47	0	3.55	0	0.17	0	0.03	0	0.00	0	57.22	0	17960738	0	150	0	147.70	0	3.78	0	0.02	0	2.02	0	0.02	0	120.62	0	0.77	0	200037	0	42182481	0	1496568	0	71264	0	12843	0	0	0	24137636	0	2801	0	0	0	29961	0	4129114	0	26076	0	4187952	0	39.03	0	16464170	0	107543	4225940	39.295351626791	42182481.0	17960738.0	200037.0	1496568.0	71264.0	12843.0	0.0	24137636.0	16464170.0	42.6	0.5	3.5	0.2	0.0	0.0	57.2	39.0	75	75	75.00	38	3163686075	23.8	25.7	30.5	19.9	0.0	33.9	15.0	bulk
3582262	SRR579549	SRP015997	SRS366862	SRX191153	SRA059267	GEO		The evolutionary landscape of alternative splicing in vertebrate species	How species with similar repertoires of protein coding genes differ so dramatically at the phenotypic level is poorly understood. From comparing the transcriptomes of multiple organs from vertebrate species spanning ~350 million years of evolution, we observe significant differences in alternative splicing complexity between the main vertebrate lineages, with the highest complexity in the primate lineage. Moreover, within as little as six million years, the splicing profiles of physiologically-equivalent organs have diverged to the extent that they are more strongly related to the identity of a species than they are to organ type. Most vertebrate species-specific splicing patterns are governed by the highly variable use of a largely conserved cis-regulatory code. However, a smaller number of pronounced species-dependent splicing changes are predicted to remodel interactions involving factors acting at multiple steps in gene regulation. These events are expected to further contribute to the dramatic diversification of alternative splicing as well as to other gene regulatory changes that contribute to phenotypic differences among vertebrate species. Overall design: mRNA profiles of several organs (brain, liver, kidney, heart, skeletal muscle) in multiple vertebrate species (mouse, chicken, lizard, frog, pufferfish) generated by deep sequencing using Illumina HiSeq		GSM1015154: Mouse heart; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;adult|molecule subtype;;poly-A enriched RNA|sex;;mixed|source_name;;Mouse_heart_pooled|strain;;C57BL/6|tissue;;heart	GEO Accession;;GSM1015154		GSM1015154	Mouse heart	5882596232	38701291	2012-12-24 12:04:54	3686946783	5882596232	38701291	2	38701291	index:0,count:38701291,average:76,stdev:0|index:1,count:38701291,average:76,stdev:0	GSM1015154_r1	GEO			in_mesa	23258890	17.14	1.19	0.04	4263145035	4365695569	3766539876	3903719026	102.41	103.64	33495649	32350955	146.360	337.926	110	411787	79.67	90.29	38527272	26684400	38527272	26684400	81.11	81.16	38527272	27167532	38527272	23985263	251871895	5.91	2.49	0	10.19	0	0.33	0	0.04	0	0.00	0	13.08	0	33495649	0	152	0	148.46	0	3.33	0	0.02	0	1.78	0	0.01	0	258.01	0	0.88	0	963268	0	38701291	0	3942734	0	128315	0	13947	0	0	0	5063380	0	5182	0	0	0	61005	0	7902788	0	52953	0	8021928	0	76.36	0	29552915	0	163873	7720221	47.111000591922	38701291.0	33495649.0	963268.0	3942734.0	128315.0	13947.0	0.0	5063380.0	29552915.0	86.5	2.5	10.2	0.3	0.0	0.0	13.1	76.4	76	76	76.00	39	2941298116	24.4	24.8	25.7	25.1	0.0	33.6	13.9	bulk
3582485	SRR579550	SRP015997	SRS366863	SRX191154	SRA059267	GEO		The evolutionary landscape of alternative splicing in vertebrate species	How species with similar repertoires of protein coding genes differ so dramatically at the phenotypic level is poorly understood. From comparing the transcriptomes of multiple organs from vertebrate species spanning ~350 million years of evolution, we observe significant differences in alternative splicing complexity between the main vertebrate lineages, with the highest complexity in the primate lineage. Moreover, within as little as six million years, the splicing profiles of physiologically-equivalent organs have diverged to the extent that they are more strongly related to the identity of a species than they are to organ type. Most vertebrate species-specific splicing patterns are governed by the highly variable use of a largely conserved cis-regulatory code. However, a smaller number of pronounced species-dependent splicing changes are predicted to remodel interactions involving factors acting at multiple steps in gene regulation. These events are expected to further contribute to the dramatic diversification of alternative splicing as well as to other gene regulatory changes that contribute to phenotypic differences among vertebrate species. Overall design: mRNA profiles of several organs (brain, liver, kidney, heart, skeletal muscle) in multiple vertebrate species (mouse, chicken, lizard, frog, pufferfish) generated by deep sequencing using Illumina HiSeq		GSM1015155: Mouse skeletal muscle; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;adult|molecule subtype;;poly-A enriched RNA|sex;;mixed|source_name;;Mouse_skeletal muscle_pooled|strain;;C57BL/6|tissue;;skeletal muscle	GEO Accession;;GSM1015155		GSM1015155	Mouse skeletal muscle	11853942750	79026285	2012-12-24 12:04:54	8130674059	11853942750	79026285	2	79026285	index:0,count:79026285,average:75,stdev:0|index:1,count:79026285,average:75,stdev:0	GSM1015155_r1	GEO			in_mesa	23258890	3.01	1.06	0.02	6092415926	6381954920	5579388744	5964191577	104.75	106.9	51281206	49461627	145.004	366.565	173	537376	73.7	81.21	58711535	37791736	58711535	37791736	61.8	63.81	58711535	31690258	58711535	29698381	655095415	10.75	1.81	0	6.00	0	0.51	0	0.03	0	0.00	0	34.57	0	51281206	0	150	0	145.96	0	4.76	0	0.04	0	1.93	0	0.02	0	165.79	0	0.84	0	1432807	0	79026285	0	4742833	0	400176	0	26653	0	0	0	27318250	0	4562	0	0	0	62983	0	11533725	0	64650	0	11665920	0	58.89	0	46538373	0	167298	10446018	62.439586845031	79026285.0	51281206.0	1432807.0	4742833.0	400176.0	26653.0	0.0	27318250.0	46538373.0	64.9	1.8	6.0	0.5	0.0	0.0	34.6	58.9	75	75	75.00	38	5926971375	23.4	26.6	28.4	21.6	0.0	34.0	14.9	bulk
2781820	SRR594393	SRP016501	SRS369701	SRX196264	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020640: mouse_a_brain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_brain|strain;;DBA/2J|tissue;;brain	GEO Accession;;GSM1020640		GSM1020640	mouse_a_brain	8726460400	87264604	2015-07-22 17:02:33	5927043102	8726460400	87264604	2	87264604	index:0,count:87264604,average:50,stdev:0|index:1,count:87264604,average:50,stdev:0	GSM1020640_r1	GEO			in_mesa	23258891	7.15	3.39	0.08	8133292805	7992722272	7532272484	7451243629	98.27	98.92	82311911	73929167	174.162	986.028	150	2326458	78.15	84.35	91278187	64323690	91278187	64323690	81.87	81.78	91278187	67389405	91278187	62364078	1067821988	13.13	0.93	0	6.94	0	0.38	0	0.25	0	0.00	0	5.05	0	82311911	0	100	0	98.88	0	1.78	0	0.01	0	1.52	0	0.01	0	423.96	0	0.67	0	810641	0	87264604	0	6055348	0	329177	0	218399	0	0	0	4405117	0	7082	0	0	0	71575	0	9439536	0	23402	0	9541595	0	87.39	0	76256563	0	207864	9652669	46.437425432013	87264604.0	82311911.0	810641.0	6055348.0	329177.0	218399.0	0.0	4405117.0	76256563.0	94.3	0.9	6.9	0.4	0.3	0.0	5.0	87.4	50	50	50.00	37	4363230200	24.6	23.9	24.4	27.1	0.0	31.6	15.5	bulk
2781850	SRR594394	SRP016501	SRS369702	SRX196265	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020641: mouse_a_colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_colon|strain;;DBA/2J|tissue;;colon	GEO Accession;;GSM1020641		GSM1020641	mouse_a_colon	10181649100	101816491	2015-07-22 17:02:33	6835402318	10181649100	101816491	2	101816491	index:0,count:101816491,average:50,stdev:0|index:1,count:101816491,average:50,stdev:0	GSM1020641_r1	GEO			in_mesa	23258891	6.5	2.41	0.18	9391279961	9311298827	8441471055	8451209233	99.15	100.12	95080717	83141477	196.534	1006.665	158	2179347	79.28	88.15	110500766	75376965	110500766	75376965	84.28	84.55	110500766	80130804	110500766	72296092	926062360	9.86	1.39	0	9.40	0	0.53	0	0.16	0	0.00	0	5.92	0	95080717	0	100	0	98.77	0	1.97	0	0.01	0	1.55	0	0.00	0	415.11	0	0.65	0	1418447	0	101816491	0	9569733	0	543265	0	160543	0	0	0	6031966	0	6831	0	0	0	75976	0	13134767	0	26867	0	13244441	0	83.99	0	85510984	0	201333	14216649	70.612611941410	101816491.0	95080717.0	1418447.0	9569733.0	543265.0	160543.0	0.0	6031966.0	85510984.0	93.4	1.4	9.4	0.5	0.2	0.0	5.9	84.0	50	50	50.00	37	5090824550	24.1	24.4	24.8	26.6	0.1	32.0	15.8	bulk
2781881	SRR594395	SRP016501	SRS369703	SRX196266	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020642: mouse_a_heart; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina Genome Analyzer IIx	source_name;;mouse_heart|strain;;DBA/2J|tissue;;heart	GEO Accession;;GSM1020642		GSM1020642	mouse_a_heart	2532670704	35175982	2015-07-22 17:02:33	1502674440	2532670704	35175982	2	35175982	index:0,count:35175982,average:36,stdev:0|index:1,count:35175982,average:36,stdev:0	GSM1020642_r1	GEO			in_mesa	23258891	28.98	1.5	0.04	2363649379	2350059033	1764608883	1781462116	99.43	100.96	33079302	29418736	198.850	751.958	174	786063	65.37	87.42	43594875	21623891	43594875	21623891	86.23	83.93	43594875	28524535	43594875	20760275	216172728	9.15	0.79	0	23.72	0	0.44	0	0.32	0	0.00	0	5.20	0	33079302	0	72	0	71.34	0	1.48	0	0.00	0	1.16	0	0.00	0	462.17	0	0.28	0	276508	0	35175982	0	8343986	0	155353	0	111688	0	0	0	1829639	0	991	0	0	0	7273	0	1405997	0	3207	0	1417468	0	70.32	0	24735316	0	98783	1503624	15.221485478271	35175982.0	33079302.0	276508.0	8343986.0	155353.0	111688.0	0.0	1829639.0	24735316.0	94.0	0.8	23.7	0.4	0.3	0.0	5.2	70.3	36	36	36.00	37	1266335352	26.1	20.9	24.5	28.4	0.0	35.0	20.5	bulk
2781913	SRR594396	SRP016501	SRS369704	SRX196267	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020643: mouse_a_kidney; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_kidney|strain;;DBA/2J|tissue;;kidney	GEO Accession;;GSM1020643		GSM1020643	mouse_a_kidney	11927478600	119274786	2015-07-22 17:02:33	7555854784	11927478600	119274786	2	119274786	index:0,count:119274786,average:50,stdev:0|index:1,count:119274786,average:50,stdev:0	GSM1020643_r1	GEO			in_mesa	23258891	13.2	1.86	0.09	11178101370	11148357043	9928463004	9986854187	99.73	100.59	112915152	98759488	191.292	859.769	160	2785915	78.75	88.6	129755026	88919111	129755026	88919111	85.47	85.14	129755026	96503776	129755026	85443638	1046526892	9.36	1.06	0	10.52	0	0.47	0	0.16	0	0.00	0	4.70	0	112915152	0	100	0	99.00	0	2.34	0	0.01	0	1.46	0	0.00	0	483.55	0	0.46	0	1259766	0	119274786	0	12553610	0	559617	0	195038	0	0	0	5604979	0	8717	0	0	0	95379	0	15880637	0	27954	0	16012687	0	84.14	0	100361542	0	206534	16538657	80.077164050471	119274786.0	112915152.0	1259766.0	12553610.0	559617.0	195038.0	0.0	5604979.0	100361542.0	94.7	1.1	10.5	0.5	0.2	0.0	4.7	84.1	50	50	50.00	37	5963739300	24.8	23.6	24.6	26.9	0.0	33.6	17.3	bulk
2781944	SRR594397	SRP016501	SRS369705	SRX196268	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020644: mouse_a_liver; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_liver|strain;;DBA/2J|tissue;;liver	GEO Accession;;GSM1020644		GSM1020644	mouse_a_liver	11629247800	116292478	2015-07-22 17:02:33	7481554926	11629247800	116292478	2	116292478	index:0,count:116292478,average:50,stdev:0|index:1,count:116292478,average:50,stdev:0	GSM1020644_r1	GEO			in_mesa	23258891	5.86	1.04	0.03	10045213332	10012706389	8226862556	8262799820	99.68	100.44	101641079	86815195	225.062	985.981	160	2147501	73.83	90.07	157640791	75042166	157640791	75042166	87.08	86.42	157640791	88513963	157640791	72001361	747254085	7.44	1.29	0	15.76	0	5.79	0	1.49	0	0.00	0	5.32	0	101641079	0	100	0	98.82	0	2.38	0	0.01	0	1.43	0	0.00	0	109.34	0	0.54	0	1504927	0	116292478	0	18328717	0	6734300	0	1732724	0	0	0	6184375	0	4609	0	0	0	73331	0	15100905	0	16903	0	15195748	0	71.64	0	83312362	0	165980	24081124	145.084492107483	116292478.0	101641079.0	1504927.0	18328717.0	6734300.0	1732724.0	0.0	6184375.0	83312362.0	87.4	1.3	15.8	5.8	1.5	0.0	5.3	71.6	50	50	50.00	37	5814623900	24.6	23.3	24.4	27.7	0.0	33.1	16.9	bulk
2781977	SRR594398	SRP016501	SRS369706	SRX196269	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020645: mouse_a_lung; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina Genome Analyzer IIx	source_name;;mouse_lung|strain;;DBA/2J|tissue;;lung	GEO Accession;;GSM1020645		GSM1020645	mouse_a_lung	2451645072	34050626	2015-07-22 17:02:37	1498159050	2451645072	34050626	2	34050626	index:0,count:34050626,average:36,stdev:0|index:1,count:34050626,average:36,stdev:0	GSM1020645_r1	GEO			in_mesa	23258891	3.01	2.76	0.08	2291185743	2265448494	2083782836	2077438605	98.88	99.7	32146028	27140919	206.341	1089.731	162	760575	76.65	84.24	37581917	24639929	37581917	24639929	81.61	81.55	37581917	26235283	37581917	23852078	318397851	13.90	0.79	0	8.51	0	0.46	0	0.36	0	0.00	0	4.78	0	32146028	0	72	0	71.25	0	1.47	0	0.00	0	1.37	0	0.00	0	580.96	0	0.31	0	268310	0	34050626	0	2898040	0	156365	0	121586	0	0	0	1626647	0	1471	0	0	0	12412	0	2106913	0	4279	0	2125075	0	85.90	0	29247988	0	140115	2254646	16.091396352996	34050626.0	32146028.0	268310.0	2898040.0	156365.0	121586.0	0.0	1626647.0	29247988.0	94.4	0.8	8.5	0.5	0.4	0.0	4.8	85.9	36	36	36.00	37	1225822536	25.1	24.1	24.8	26.0	0.0	34.7	20.1	bulk
2782009	SRR594399	SRP016501	SRS369707	SRX196270	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020646: mouse_a_skm; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_skm|strain;;DBA/2J|tissue;;skeletal muscle	GEO Accession;;GSM1020646		GSM1020646	mouse_a_skm	11311127700	113111277	2015-07-22 17:02:33	7426709775	11311127700	113111277	2	113111277	index:0,count:113111277,average:50,stdev:0|index:1,count:113111277,average:50,stdev:0	GSM1020646_r1	GEO			in_mesa	23258891	10.76	1.4	0.03	10535986613	10754654489	9533070351	9804117912	102.08	102.84	106790070	92777414	225.918	794.272	166	2176109	85.78	94.73	121172624	91604102	121172624	91604102	90.34	90.23	121172624	96478720	121172624	87250798	494659729	4.69	1.07	0	8.92	0	1.00	0	0.09	0	0.00	0	4.50	0	106790070	0	100	0	98.65	0	2.02	0	0.00	0	1.48	0	0.00	0	481.32	0	0.51	0	1212973	0	113111277	0	10094135	0	1126119	0	100754	0	0	0	5094334	0	7518	0	0	0	101057	0	21750990	0	24041	0	21883606	0	85.49	0	96695935	0	171670	22740609	132.466994815635	113111277.0	106790070.0	1212973.0	10094135.0	1126119.0	100754.0	0.0	5094334.0	96695935.0	94.4	1.1	8.9	1.0	0.1	0.0	4.5	85.5	50	50	50.00	37	5655563850	22.4	25.0	25.4	27.1	0.0	32.6	16.4	bulk
2785306	SRR594400	SRP016501	SRS369708	SRX196271	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020647: mouse_a_spleen; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_spleen|strain;;DBA/2J|tissue;;spleen	GEO Accession;;GSM1020647		GSM1020647	mouse_a_spleen	11407225700	114072257	2015-07-22 17:02:37	7431230507	11407225700	114072257	2	114072257	index:0,count:114072257,average:50,stdev:0|index:1,count:114072257,average:50,stdev:0	GSM1020647_r1	GEO			in_mesa	23258891	3.41	3.02	0.23	10422380301	10191102508	9179363102	9081635436	97.78	98.94	105261400	96489646	198.506	768.374	171	2437236	68.15	77.36	128898699	71736242	128898699	71736242	74.19	73.56	128898699	78089378	128898699	68216720	1978022481	18.98	1.67	0	10.98	0	0.62	0	0.26	0	0.00	0	6.84	0	105261400	0	100	0	99.02	0	2.30	0	0.01	0	1.56	0	0.01	0	482.00	0	0.55	0	1909485	0	114072257	0	12529915	0	707534	0	300979	0	0	0	7802344	0	8497	0	0	0	60408	0	9610335	0	33917	0	9713157	0	81.29	0	92731485	0	200642	10809746	53.875788718215	114072257.0	105261400.0	1909485.0	12529915.0	707534.0	300979.0	0.0	7802344.0	92731485.0	92.3	1.7	11.0	0.6	0.3	0.0	6.8	81.3	50	50	50.00	37	5703612850	24.5	24.7	24.5	26.4	0.0	32.8	16.5	bulk
2785338	SRR594401	SRP016501	SRS369709	SRX196272	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020648: mouse_a_testes; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_testes|strain;;DBA/2J|tissue;;testes	GEO Accession;;GSM1020648		GSM1020648	mouse_a_testes	10919993800	109199938	2015-07-22 17:02:37	7132204819	10919993800	109199938	2	109199938	index:0,count:109199938,average:50,stdev:0|index:1,count:109199938,average:50,stdev:0	GSM1020648_r1	GEO			in_mesa	23258891	1.2	1.68	0.19	10256877367	9842576814	9729033424	9386426261	95.96	96.48	103867369	86141357	209.813	1226.785	170	2331666	79.61	83.91	114230867	82687996	114230867	82687996	80.56	80.84	114230867	83680400	114230867	79654914	1212171383	11.82	0.87	0	4.88	0	0.45	0	0.36	0	0.00	0	4.07	0	103867369	0	100	0	98.84	0	1.95	0	0.01	0	1.53	0	0.00	0	527.68	0	0.51	0	947730	0	109199938	0	5328172	0	496150	0	391380	0	0	0	4445039	0	13436	0	0	0	156852	0	17886448	0	46413	0	18103149	0	90.24	0	98539197	0	334271	18797791	56.235183429014	109199938.0	103867369.0	947730.0	5328172.0	496150.0	391380.0	0.0	4445039.0	98539197.0	95.1	0.9	4.9	0.5	0.4	0.0	4.1	90.2	50	50	50.00	37	5459996900	23.3	25.0	24.6	27.2	0.0	33.0	16.8	bulk
2785371	SRR594402	SRP016501	SRS369710	SRX196273	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020649: mouse_b_brain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_brain|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1020649		GSM1020649	mouse_b_brain	19011896480	118824353	2015-07-22 17:02:37	12230336069	19011896480	118824353	2	118824353	index:0,count:118824353,average:80,stdev:0|index:1,count:118824353,average:80,stdev:0	GSM1020649_r1	GEO			in_mesa	23258891	4.15	3.18	0.05	16898096538	16642073327	16084406046	15902975150	98.48	98.87	113905295	107049188	179.777	677.473	182	2648366	78.38	82.4	122471962	89282860	122471962	89282860	79.63	79.6	122471962	90702557	122471962	86246827	2656123811	15.72	0.26	0	4.67	0	0.30	0	0.18	0	0.00	0	3.67	0	113905295	0	160	0	158.01	0	1.75	0	0.00	0	1.36	0	0.00	0	308.19	0	0.81	0	303800	0	118824353	0	5549105	0	354031	0	208569	0	0	0	4356458	0	22325	0	0	0	208443	0	30162987	0	49121	0	30442876	0	91.19	0	108356190	0	291750	29959581	102.689223650386	118824353.0	113905295.0	303800.0	5549105.0	354031.0	208569.0	0.0	4356458.0	108356190.0	95.9	0.3	4.7	0.3	0.2	0.0	3.7	91.2	80	80	80.00	38	9505948240	23.9	25.5	24.5	25.8	0.2	32.3	13.7	bulk
2785402	SRR594403	SRP016501	SRS369711	SRX196274	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020650: mouse_b_colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_colon|strain;;C57BL/6|tissue;;colon	GEO Accession;;GSM1020650		GSM1020650	mouse_b_colon	13991573440	87447334	2015-07-22 17:02:37	8957908853	13991573440	87447334	2	87447334	index:0,count:87447334,average:80,stdev:0|index:1,count:87447334,average:80,stdev:0	GSM1020650_r1	GEO			in_mesa	23258891	3.32	1.64	0.07	12103538075	12134298542	10896102359	11001447319	100.25	100.97	80005487	74986698	192.683	633.676	169	1430437	80.79	89.76	96845792	64632593	96845792	64632593	84.86	84.87	96845792	67891945	96845792	61109805	1017635063	8.41	0.20	0	9.15	0	2.13	0	0.07	0	0.00	0	6.32	0	80005487	0	160	0	155.90	0	2.48	0	0.01	0	1.57	0	0.00	0	226.65	0	1.21	0	177379	0	87447334	0	8002495	0	1859113	0	59998	0	0	0	5522736	0	8144	0	0	0	96910	0	23537100	0	24842	0	23666996	0	82.34	0	72002992	0	207292	28597900	137.959496748548	87447334.0	80005487.0	177379.0	8002495.0	1859113.0	59998.0	0.0	5522736.0	72002992.0	91.5	0.2	9.2	2.1	0.1	0.0	6.3	82.3	80	80	80.00	38	6995786720	23.6	25.6	25.0	25.7	0.1	31.1	12.5	bulk
2785434	SRR594404	SRP016501	SRS369712	SRX196275	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020651: mouse_b_kidney; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_kidney|strain;;C57BL/6|tissue;;kidney	GEO Accession;;GSM1020651		GSM1020651	mouse_b_kidney	18427204450	118885190	2015-07-22 17:02:33	11992642384	18427204450	118885190	2	118885190	index:0,count:118885190,average:80,stdev:0|index:1,count:118885190,average:75,stdev:0	GSM1020651_r1	GEO			in_mesa	23258891	15.25	1.8	0.1	17254551267	17111102641	15282705020	15329443069	99.17	100.31	115788983	109674112	175.717	422.232	166	2235977	78.92	89.11	133146189	91382585	133146189	91382585	85.78	85.73	133146189	99327257	133146189	87915257	1532249658	8.88	0.12	0	11.14	0	0.40	0	0.09	0	0.00	0	2.12	0	115788983	0	155	0	153.69	0	2.04	0	0.00	0	1.19	0	0.00	0	309.46	0	0.51	0	145363	0	118885190	0	13240863	0	470012	0	106177	0	0	0	2520018	0	16156	0	0	0	178335	0	31548071	0	29975	0	31772537	0	86.26	0	102548120	0	248525	32522696	130.862874962277	118885190.0	115788983.0	145363.0	13240863.0	470012.0	106177.0	0.0	2520018.0	102548120.0	97.4	0.1	11.1	0.4	0.1	0.0	2.1	86.3	80	80	80.00	37	9510815200	25.3	23.2	24.3	27.2	0.0	32.5	15.7	bulk
2785468	SRR594405	SRP016501	SRS369713	SRX196276	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020652: mouse_b_liver; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_liver|strain;;C57BL/6|tissue;;liver	GEO Accession;;GSM1020652		GSM1020652	mouse_b_liver	21447315360	134045721	2015-07-22 17:02:37	13711169304	21447315360	134045721	2	134045721	index:0,count:134045721,average:80,stdev:0|index:1,count:134045721,average:80,stdev:0	GSM1020652_r1	GEO			in_mesa	23258891	4.47	1.24	0.04	18452839735	18479012578	16831592649	16900203042	100.14	100.41	124226409	115416386	188.801	495.375	175	2561366	82.68	90.75	146149504	102711298	146149504	102711298	87.25	87.34	146149504	108382633	146149504	98842940	1481057955	8.03	0.19	0	8.24	0	1.55	0	2.49	0	0.00	0	3.28	0	124226409	0	160	0	157.68	0	2.04	0	0.00	0	1.64	0	0.00	0	126.79	0	0.60	0	254953	0	134045721	0	11051061	0	2073721	0	3343986	0	0	0	4401605	0	16524	0	0	0	236430	0	48039121	0	47121	0	48339196	0	84.43	0	113175348	0	231105	54471129	235.698617511521	134045721.0	124226409.0	254953.0	11051061.0	2073721.0	3343986.0	0.0	4401605.0	113175348.0	92.7	0.2	8.2	1.5	2.5	0.0	3.3	84.4	80	80	80.00	38	10723657680	23.4	25.6	25.0	26.0	0.0	34.2	16.7	bulk
2785500	SRR594406	SRP016501	SRS369714	SRX196277	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020653: mouse_b_lung; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_lung|strain;;C57BL/6|tissue;;lung	GEO Accession;;GSM1020653		GSM1020653	mouse_b_lung	9978064160	62362901	2015-07-22 17:02:33	6787372787	9978064160	62362901	2	62362901	index:0,count:62362901,average:80,stdev:0|index:1,count:62362901,average:80,stdev:0	GSM1020653_r1	GEO			in_mesa	23258891	1.55	2.53	0.05	8945814203	8865413191	8344272536	8305479079	99.1	99.54	58551093	55363790	183.158	489.251	169	1995375	77.88	83.51	65766666	45597449	65766666	45597449	79.91	79.91	65766666	46787781	65766666	43629858	1288715713	14.41	0.26	0	6.34	0	0.18	0	0.07	0	0.00	0	5.86	0	58551093	0	160	0	156.56	0	1.86	0	0.01	0	1.27	0	0.00	0	248.35	0	1.38	0	164562	0	62362901	0	3950916	0	112921	0	41659	0	0	0	3657228	0	9371	0	0	0	82564	0	14615399	0	24212	0	14731546	0	87.55	0	54600177	0	213298	16031719	75.161131374884	62362901.0	58551093.0	164562.0	3950916.0	112921.0	41659.0	0.0	3657228.0	54600177.0	93.9	0.3	6.3	0.2	0.1	0.0	5.9	87.6	80	80	80.00	38	4989032080	24.2	26.4	23.8	25.4	0.2	28.7	11.4	bulk
2785531	SRR594407	SRP016501	SRS369715	SRX196278	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020654: mouse_b_skm; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_skm|strain;;C57BL/6|tissue;;skeletal muscle	GEO Accession;;GSM1020654		GSM1020654	mouse_b_skm	18747477920	117171737	2015-07-22 17:02:37	12488535807	18747477920	117171737	2	117171737	index:0,count:117171737,average:80,stdev:0|index:1,count:117171737,average:80,stdev:0	GSM1020654_r1	GEO			in_mesa	23258891	9.61	1.43	0.03	16261428650	16544356311	15013378953	15356032779	101.74	102.28	110920359	104159518	188.215	461.904	180	2243944	85.62	92.82	123523173	94969529	123523173	94969529	87.92	87.75	123523173	97520667	123523173	89779159	976213228	6.00	0.25	0	7.35	0	0.84	0	0.05	0	0.00	0	4.45	0	110920359	0	160	0	157.36	0	2.00	0	0.00	0	1.71	0	0.00	0	274.26	0	0.87	0	295584	0	117171737	0	8609546	0	983158	0	53548	0	0	0	5214672	0	16185	0	0	0	201050	0	45715572	0	46380	0	45979187	0	87.32	0	102310813	0	220554	45496315	206.281976296054	117171737.0	110920359.0	295584.0	8609546.0	983158.0	53548.0	0.0	5214672.0	102310813.0	94.7	0.3	7.3	0.8	0.0	0.0	4.5	87.3	80	80	80.00	38	9373738960	22.2	26.1	24.9	26.6	0.2	31.1	12.9	bulk
2785563	SRR594408	SRP016501	SRS369716	SRX196279	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020655: mouse_b_spleen; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_spleen|strain;;C57BL/6|tissue;;spleen	GEO Accession;;GSM1020655		GSM1020655	mouse_b_spleen	18370262720	114814142	2015-07-22 17:02:33	12172047883	18370262720	114814142	2	114814142	index:0,count:114814142,average:80,stdev:0|index:1,count:114814142,average:80,stdev:0	GSM1020655_r1	GEO			in_mesa	23258891	1.75	2.69	0.2	17045916105	16792751331	15760656258	15599746919	98.51	98.98	110578973	105031309	187.079	536.860	176	4066721	73.98	80.05	126909229	81809298	126909229	81809298	77.07	76.88	126909229	85226206	126909229	78577416	3158008513	18.53	0.22	0	7.30	0	0.38	0	0.15	0	0.00	0	3.16	0	110578973	0	160	0	158.26	0	1.75	0	0.00	0	1.37	0	0.00	0	299.52	0	0.72	0	254948	0	114814142	0	8375741	0	434524	0	173991	0	0	0	3626654	0	22379	0	0	0	188107	0	29911184	0	55677	0	30177347	0	89.02	0	102203232	0	268640	33499874	124.701734663490	114814142.0	110578973.0	254948.0	8375741.0	434524.0	173991.0	0.0	3626654.0	102203232.0	96.3	0.2	7.3	0.4	0.2	0.0	3.2	89.0	80	80	80.00	38	9185131360	23.6	26.0	24.8	25.4	0.1	31.7	13.4	bulk
2785595	SRR594409	SRP016501	SRS369717	SRX196280	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020656: mouse_b_testes; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_testes|strain;;C57BL/6|tissue;;testes	GEO Accession;;GSM1020656		GSM1020656	mouse_b_testes	18644023520	116525147	2015-07-22 17:02:33	12339976490	18644023520	116525147	2	116525147	index:0,count:116525147,average:80,stdev:0|index:1,count:116525147,average:80,stdev:0	GSM1020656_r1	GEO			in_mesa	23258891	0.88	1.25	0.2	17239750808	16627709678	16574736810	16048096479	96.45	96.82	110998275	101165863	198.887	692.456	180	3351126	81.61	84.9	118835160	90588129	118835160	90588129	80.79	81.18	118835160	89678093	118835160	86619840	1928486641	11.19	0.18	0	3.69	0	0.29	0	0.18	0	0.00	0	4.27	0	110998275	0	160	0	157.86	0	2.19	0	0.00	0	1.89	0	0.00	0	270.46	0	0.79	0	213053	0	116525147	0	4295303	0	337795	0	212827	0	0	0	4976250	0	35986	0	0	0	342329	0	40381355	0	81688	0	40841358	0	91.57	0	106702972	0	354790	41788245	117.783040671947	116525147.0	110998275.0	213053.0	4295303.0	337795.0	212827.0	0.0	4976250.0	106702972.0	95.3	0.2	3.7	0.3	0.2	0.0	4.3	91.6	80	80	80.00	38	9322011760	22.2	26.4	25.4	25.9	0.1	31.4	13.0	bulk
2785820	SRR594410	SRP016501	SRS369718	SRX196281	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020657: mouse_c_brain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_brain|strain;;CD1|tissue;;brain	GEO Accession;;GSM1020657		GSM1020657	mouse_c_brain	2600898720	32511234	2015-07-22 17:02:37	1716117689	2600898720	32511234	2	32511234	index:0,count:32511234,average:40,stdev:0|index:1,count:32511234,average:40,stdev:0	GSM1020657_r1	GEO			in_mesa	23258891	4.21	3.23	0.06	2374361471	2333073488	2223332654	2196681430	98.26	98.8	29997218	25261522	214.677	1553.139	184	643727	77.43	82.67	33100295	23228328	33100295	23228328	80.48	80.46	33100295	24143118	33100295	22606836	365726147	15.40	0.78	0	5.85	0	0.31	0	0.40	0	0.00	0	7.02	0	29997218	0	80	0	79.14	0	1.61	0	0.00	0	1.37	0	0.00	0	504.48	0	0.52	0	253257	0	32511234	0	1900449	0	100845	0	130663	0	0	0	2282508	0	1957	0	0	0	16847	0	2262570	0	5648	0	2287022	0	86.42	0	28096769	0	140657	2315069	16.458967559382	32511234.0	29997218.0	253257.0	1900449.0	100845.0	130663.0	0.0	2282508.0	28096769.0	92.3	0.8	5.8	0.3	0.4	0.0	7.0	86.4	40	40	40.00	38	1300449360	24.7	25.1	23.8	26.3	0.1	34.4	18.5	bulk
2785851	SRR594411	SRP016501	SRS369719	SRX196282	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020658: mouse_c_colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_colon|strain;;CD1|tissue;;colon	GEO Accession;;GSM1020658		GSM1020658	mouse_c_colon	2739875520	34248444	2015-07-22 17:02:37	1818624049	2739875520	34248444	2	34248444	index:0,count:34248444,average:40,stdev:0|index:1,count:34248444,average:40,stdev:0	GSM1020658_r1	GEO			in_mesa	23258891	3.48	1.66	0.22	2364591593	2350000623	2030085079	2036984970	99.38	100.34	29972744	24599386	265.104	1309.369	184	537900	76.39	88.96	40939665	22894746	40939665	22894746	85.44	85.39	40939665	25608788	40939665	21974626	218824032	9.25	1.30	0	12.37	0	2.77	0	0.28	0	0.00	0	9.43	0	29972744	0	80	0	78.89	0	1.67	0	0.00	0	1.34	0	0.00	0	435.67	0	0.57	0	446120	0	34248444	0	4237529	0	949995	0	95295	0	0	0	3230410	0	1221	0	0	0	10752	0	2834481	0	8172	0	2854626	0	75.14	0	25735215	0	105689	3777791	35.744410487373	34248444.0	29972744.0	446120.0	4237529.0	949995.0	95295.0	0.0	3230410.0	25735215.0	87.5	1.3	12.4	2.8	0.3	0.0	9.4	75.1	40	40	40.00	38	1369937760	24.0	24.8	24.4	26.7	0.1	34.3	18.2	bulk
2785883	SRR594412	SRP016501	SRS369720	SRX196283	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020659: mouse_c_heart; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_heart|strain;;CD1|tissue;;heart	GEO Accession;;GSM1020659		GSM1020659	mouse_c_heart	1277488400	15968605	2015-07-22 17:02:33	869317272	1277488400	15968605	2	15968605	index:0,count:15968605,average:40,stdev:0|index:1,count:15968605,average:40,stdev:0	GSM1020659_r1	GEO			in_mesa	23258891	20.88	1.8	0.03	1163330591	1162225977	897578737	907738524	99.91	101.13	14715599	12743144	213.739	884.250	174	333351	70.52	91.26	19283955	10378016	19283955	10378016	89.3	87.98	19283955	13141646	19283955	10005077	79376173	6.82	0.88	0	20.94	0	0.41	0	0.18	0	0.00	0	7.26	0	14715599	0	80	0	78.93	0	1.61	0	0.00	0	1.31	0	0.00	0	413.58	0	0.77	0	139945	0	15968605	0	3343462	0	65938	0	28495	0	0	0	1158573	0	640	0	0	0	4667	0	924801	0	2381	0	932489	0	71.22	0	11372137	0	92283	1050721	11.385856549960	15968605.0	14715599.0	139945.0	3343462.0	65938.0	28495.0	0.0	1158573.0	11372137.0	92.2	0.9	20.9	0.4	0.2	0.0	7.3	71.2	40	40	40.00	38	638744200	25.7	21.9	24.7	27.7	0.1	33.7	17.8	bulk
2785915	SRR594413	SRP016501	SRS369721	SRX196284	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020660: mouse_c_kidney; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina Genome Analyzer IIx	source_name;;mouse_kidney|strain;;CD1|tissue;;kidney	GEO Accession;;GSM1020660		GSM1020660	mouse_c_kidney	2147169600	29821800	2015-07-22 17:02:37	1198954344	2147169600	29821800	2	29821800	index:0,count:29821800,average:36,stdev:0|index:1,count:29821800,average:36,stdev:0	GSM1020660_r1	GEO			in_mesa	23258891	12.38	1.84	0.27	1960893291	1941442473	1703881690	1704043786	99.01	100.01	27681032	21354923	260.177	1499.957	211	869920	77.01	88.56	33357549	21316791	33357549	21316791	85.0	85.44	33357549	23528704	33357549	20564462	186841496	9.53	1.47	0	12.11	0	0.66	0	0.37	0	0.00	0	6.15	0	27681032	0	72	0	71.17	0	1.53	0	0.00	0	1.34	0	0.00	0	511.23	0	0.31	0	438907	0	29821800	0	3610798	0	197434	0	110086	0	0	0	1833248	0	1618	0	0	0	13723	0	1976726	0	3505	0	1995572	0	80.71	0	24070234	0	109647	2069562	18.874770855564	29821800.0	27681032.0	438907.0	3610798.0	197434.0	110086.0	0.0	1833248.0	24070234.0	92.8	1.5	12.1	0.7	0.4	0.0	6.1	80.7	36	36	36.00	37	1073584800	24.2	24.5	24.5	26.8	0.0	35.9	23.6	bulk
2785946	SRR594414	SRP016501	SRS369722	SRX196285	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020661: mouse_c_liver; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_liver|strain;;CD1|tissue;;liver	GEO Accession;;GSM1020661		GSM1020661	mouse_c_liver	2785968720	34824609	2015-07-22 17:02:33	1800970171	2785968720	34824609	2	34824609	index:0,count:34824609,average:40,stdev:0|index:1,count:34824609,average:40,stdev:0	GSM1020661_r1	GEO			in_mesa	23258891	4.49	1.22	0.08	2445560774	2439616037	2153515918	2159075406	99.76	100.26	30987506	24144448	250.503	1364.379	175	515678	78.8	89.44	39270030	24418910	39270030	24418910	86.66	86.9	39270030	26853460	39270030	23724989	236396692	9.67	1.09	0	10.58	0	2.60	0	0.40	0	0.00	0	8.02	0	30987506	0	80	0	78.88	0	1.67	0	0.00	0	1.32	0	0.00	0	260.10	0	0.55	0	381219	0	34824609	0	3685741	0	904316	0	139066	0	0	0	2793721	0	1386	0	0	0	15938	0	3421972	0	4681	0	3443977	0	78.40	0	27301765	0	113636	4087390	35.969147101271	34824609.0	30987506.0	381219.0	3685741.0	904316.0	139066.0	0.0	2793721.0	27301765.0	89.0	1.1	10.6	2.6	0.4	0.0	8.0	78.4	40	40	40.00	38	1392984360	24.2	24.9	24.2	26.7	0.0	34.3	17.6	bulk
2785978	SRR594415	SRP016501	SRS369723	SRX196286	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020662: mouse_c_lung; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_lung|strain;;CD1|tissue;;lung	GEO Accession;;GSM1020662		GSM1020662	mouse_c_lung	11187909100	111879091	2015-07-22 17:02:37	6907476502	11187909100	111879091	2	111879091	index:0,count:111879091,average:50,stdev:0|index:1,count:111879091,average:50,stdev:0	GSM1020662_r1	GEO			in_mesa	23258891	1.8	2.51	0.09	10485887757	10444731273	9835916896	9856169063	99.61	100.21	106026117	94187010	187.258	853.377	153	2908504	81.38	86.75	117911396	86286493	117911396	86286493	82.99	83.32	117911396	87987194	117911396	82878329	1240983029	11.83	1.06	0	5.86	0	0.32	0	0.19	0	0.00	0	4.72	0	106026117	0	100	0	98.96	0	2.04	0	0.01	0	1.55	0	0.00	0	499.09	0	0.48	0	1186408	0	111879091	0	6556420	0	355634	0	215086	0	0	0	5282254	0	9829	0	0	0	85762	0	15426709	0	27532	0	15549832	0	88.91	0	99469697	0	221869	16204082	73.034457269830	111879091.0	106026117.0	1186408.0	6556420.0	355634.0	215086.0	0.0	5282254.0	99469697.0	94.8	1.1	5.9	0.3	0.2	0.0	4.7	88.9	50	50	50.00	37	5593954550	23.2	25.6	25.7	25.6	0.0	33.9	17.7	bulk
2786008	SRR594416	SRP016501	SRS369724	SRX196287	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020663: mouse_c_skm; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina Genome Analyzer IIx	source_name;;mouse_skm|strain;;CD1|tissue;;skeletal muscle	GEO Accession;;GSM1020663		GSM1020663	mouse_c_skm	2141198568	29738869	2015-07-22 17:02:33	1193769934	2141198568	29738869	2	29738869	index:0,count:29738869,average:36,stdev:0|index:1,count:29738869,average:36,stdev:0	GSM1020663_r1	GEO			in_mesa	23258891	17.1	1.15	0.04	1876302448	1879239607	1578169069	1600085183	100.16	101.39	26411811	22084807	269.349	1063.304	210	851295	73.35	87.11	32281141	19373786	32281141	19373786	80.95	81.42	32281141	21381150	32281141	18109001	184642268	9.84	2.13	0	14.03	0	0.50	0	0.37	0	0.00	0	10.32	0	26411811	0	72	0	71.03	0	1.44	0	0.00	0	1.31	0	0.00	0	588.24	0	0.35	0	634741	0	29738869	0	4171424	0	148359	0	109625	0	0	0	3069074	0	1062	0	0	0	12018	0	1832471	0	2907	0	1848458	0	74.79	0	22240387	0	72793	1903607	26.150962317805	29738869.0	26411811.0	634741.0	4171424.0	148359.0	109625.0	0.0	3069074.0	22240387.0	88.8	2.1	14.0	0.5	0.4	0.0	10.3	74.8	36	36	36.00	37	1070599284	23.3	25.1	24.5	27.2	0.0	35.8	22.7	bulk
2786040	SRR594417	SRP016501	SRS369725	SRX196288	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020664: mouse_c_spleen; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_spleen|strain;;CD1|tissue;;spleen	GEO Accession;;GSM1020664		GSM1020664	mouse_c_spleen	11332101300	113321013	2015-07-22 17:02:37	7315547147	11332101300	113321013	2	113321013	index:0,count:113321013,average:50,stdev:0|index:1,count:113321013,average:50,stdev:0	GSM1020664_r1	GEO			in_mesa	23258891	1.78	2.68	0.15	10415117066	10290941873	9207801728	9158046338	98.81	99.46	105438260	93692044	209.674	976.050	176	2170345	72.93	82.48	129516554	76893449	129516554	76893449	79.86	79.27	129516554	84204870	129516554	73901827	1608425238	15.44	1.36	0	10.78	0	0.51	0	0.32	0	0.00	0	6.13	0	105438260	0	100	0	98.93	0	2.17	0	0.01	0	1.58	0	0.01	0	533.28	0	0.53	0	1543241	0	113321013	0	12215903	0	582318	0	357617	0	0	0	6942818	0	13262	0	0	0	84956	0	13284754	0	37536	0	13420508	0	82.26	0	93222357	0	220102	15970518	72.559622356907	113321013.0	105438260.0	1543241.0	12215903.0	582318.0	357617.0	0.0	6942818.0	93222357.0	93.0	1.4	10.8	0.5	0.3	0.0	6.1	82.3	50	50	50.00	37	5666050650	23.8	25.3	25.3	25.7	0.0	32.9	16.7	bulk
2786072	SRR594418	SRP016501	SRS369726	SRX196289	SRA059960	GEO		Evolutionary dynamics of gene and isoform regulation in mammalian tissues	Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear.  To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth.  We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific.  Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators.  Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Overall design: Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart)		GSM1020665: mouse_c_testes; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	source_name;;mouse_testes|strain;;CD1|tissue;;testes	GEO Accession;;GSM1020665		GSM1020665	mouse_c_testes	2863186720	35789834	2015-07-22 17:02:37	1884961040	2863186720	35789834	2	35789834	index:0,count:35789834,average:40,stdev:0|index:1,count:35789834,average:40,stdev:0	GSM1020665_r1	GEO			in_mesa	23258891	1.29	1.47	0.16	2551832552	2463842966	2385687222	2317354726	96.55	97.14	32383441	25352926	225.739	1519.691	172	587897	80.94	86.54	36465077	26210093	36465077	26210093	83.17	83.54	36465077	26933335	36465077	25302954	251368237	9.85	0.92	0	5.86	0	0.40	0	0.28	0	0.00	0	8.84	0	32383441	0	80	0	78.79	0	1.65	0	0.00	0	1.44	0	0.00	0	383.46	0	0.78	0	328408	0	35789834	0	2096375	0	141801	0	99884	0	0	0	3164708	0	2928	0	0	0	28260	0	3320707	0	9993	0	3361888	0	84.62	0	30287066	0	179905	3496934	19.437669881326	35789834.0	32383441.0	328408.0	2096375.0	141801.0	99884.0	0.0	3164708.0	30287066.0	90.5	0.9	5.9	0.4	0.3	0.0	8.8	84.6	40	40	40.00	38	1431593360	23.3	25.2	24.0	27.5	0.1	34.1	17.9	bulk
6415395	SRR964790	SRP029464	SRS476313	SRX344333	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223635: RNA-seq ventricle PN90 (adult); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN90 (adult)|genotype/variation;;wild type|source_name;;ventricle|strain;;FVB|tissue;;ventricle	GEO Accession;;GSM1223635		GSM1223635	RNA-seq ventricle PN90 (adult)	30920044400	154600222	2014-04-16 15:55:08	21619271078	30920044400	154600222	2	154600222	index:0,count:154600222,average:100,stdev:0|index:1,count:154600222,average:100,stdev:0	GSM1223635_r1	GEO			in_mesa	24752171	19.59	1.76	0.06	23052849849	23148042897	20140001575	20351093162	100.41	101.05	136506516	119683648	232.882	1101.189	152	899885	81.62	93.9	158535669	111414308	158535669	111414308	90.43	90.31	158535669	123439053	158535669	107147837	1147322805	4.98	1.80	0	11.55	0	0.12	0	0.05	0	0.00	0	11.53	0	136506516	0	200	0	196.09	0	2.02	0	0.01	0	2.06	0	0.01	0	270.57	0	0.63	0	2787762	0	154600222	0	17860280	0	192859	0	74225	0	0	0	17826622	0	24087	0	0	0	364062	0	57067895	0	119150	0	57575194	0	76.74	0	118646236	0	242126	53298753	220.128168804672	154600222.0	136506516.0	2787762.0	17860280.0	192859.0	74225.0	0.0	17826622.0	118646236.0	88.3	1.8	11.6	0.1	0.0	0.0	11.5	76.7	100	100	100.00	38	15460022200	28.4	23.4	23.5	24.6	0.1	34.6	17.7	bulk
6415460	SRR964791	SRP029464	SRS476314	SRX344334	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223636: RNA-seq ventricle PN28; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN28|genotype/variation;;wild type|source_name;;ventricle|strain;;FVB|tissue;;ventricle	GEO Accession;;GSM1223636		GSM1223636	RNA-seq ventricle PN28	31973304400	159866522	2014-04-16 15:55:08	22423109552	31973304400	159866522	2	159866522	index:0,count:159866522,average:100,stdev:0|index:1,count:159866522,average:100,stdev:0	GSM1223636_r1	GEO			in_mesa	24752171	18.58	1.74	0.06	24775032773	24795937571	21897811827	22045346833	100.08	100.67	144459179	127037485	235.946	1050.106	152	1006486	82.21	93.51	166566030	118763961	166566030	118763961	90.11	90.11	166566030	130171686	166566030	114441842	1242245726	5.01	1.56	0	10.92	0	0.14	0	0.06	0	0.00	0	9.44	0	144459179	0	200	0	196.39	0	1.99	0	0.01	0	2.41	0	0.01	0	292.14	0	0.63	0	2489745	0	159866522	0	17451326	0	217849	0	98281	0	0	0	15091213	0	25400	0	0	0	381200	0	60414287	0	117461	0	60938348	0	79.45	0	127007853	0	255176	57389086	224.900014107910	159866522.0	144459179.0	2489745.0	17451326.0	217849.0	98281.0	0.0	15091213.0	127007853.0	90.4	1.6	10.9	0.1	0.1	0.0	9.4	79.4	100	100	100.00	38	15986652200	28.2	23.6	23.7	24.4	0.1	34.6	17.8	bulk
6415525	SRR964792	SRP029464	SRS476315	SRX344335	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223637: RNA-seq ventricle PN10; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN10|genotype/variation;;wild type|source_name;;ventricle|strain;;FVB|tissue;;ventricle	GEO Accession;;GSM1223637		GSM1223637	RNA-seq ventricle PN10	31769192000	158845960	2014-04-16 15:55:08	22208434581	31769192000	158845960	2	158845960	index:0,count:158845960,average:100,stdev:0|index:1,count:158845960,average:100,stdev:0	GSM1223637_r1	GEO			in_mesa	24752171	16.46	2.1	0.05	24457446147	24358269000	21779221270	21832673659	99.59	100.25	143858432	128361885	230.241	993.458	152	1070450	78.83	88.92	164555357	113400897	164555357	113400897	86.23	85.9	164555357	124049349	164555357	109545915	2318031177	9.48	1.62	0	10.28	0	0.13	0	0.08	0	0.00	0	9.23	0	143858432	0	200	0	196.60	0	1.99	0	0.01	0	2.27	0	0.01	0	370.13	0	0.62	0	2565386	0	158845960	0	16328852	0	207176	0	120583	0	0	0	14659769	0	25256	0	0	0	380063	0	55827118	0	121116	0	56353553	0	80.29	0	127529580	0	261604	52643496	201.233528539319	158845960.0	143858432.0	2565386.0	16328852.0	207176.0	120583.0	0.0	14659769.0	127529580.0	90.6	1.6	10.3	0.1	0.1	0.0	9.2	80.3	100	100	100.00	38	15884596000	28.6	23.1	23.2	24.9	0.1	34.7	17.8	bulk
6415591	SRR964793	SRP029464	SRS476316	SRX344336	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223638: RNA-seq ventricle PN1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN1|genotype/variation;;wild type|source_name;;ventricle|strain;;FVB|tissue;;ventricle	GEO Accession;;GSM1223638		GSM1223638	RNA-seq ventricle PN1	33336885600	166684428	2014-04-16 15:55:08	23563265064	33336885600	166684428	2	166684428	index:0,count:166684428,average:100,stdev:0|index:1,count:166684428,average:100,stdev:0	GSM1223638_r1	GEO			in_mesa	24752171	9.38	2.67	0.06	25294990575	25431157305	22774598882	22982189335	100.54	100.91	149788436	130608040	230.800	1128.183	152	1193624	81.43	90.94	172352510	121973537	172352510	121973537	87.38	87.25	172352510	130879670	172352510	117025776	2050250865	8.11	1.68	0	9.40	0	0.15	0	0.06	0	0.00	0	9.94	0	149788436	0	200	0	196.21	0	1.96	0	0.01	0	2.04	0	0.01	0	336.17	0	0.65	0	2797976	0	166684428	0	15660875	0	242630	0	92716	0	0	0	16560646	0	35419	0	0	0	437154	0	67040839	0	139305	0	67652717	0	80.47	0	134127561	0	273997	63397638	231.380774242054	166684428.0	149788436.0	2797976.0	15660875.0	242630.0	92716.0	0.0	16560646.0	134127561.0	89.9	1.7	9.4	0.1	0.1	0.0	9.9	80.5	100	100	100.00	38	16668442800	27.7	23.3	24.8	24.1	0.1	34.3	17.3	bulk
6415657	SRR964794	SRP029464	SRS476317	SRX344337	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223639: RNA-seq ventricle E17; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;E17|genotype/variation;;wild type|source_name;;ventricle|strain;;FVB|tissue;;ventricle	GEO Accession;;GSM1223639		GSM1223639	RNA-seq ventricle E17	33205582800	166027914	2014-04-16 15:55:08	23551488900	33205582800	166027914	2	166027914	index:0,count:166027914,average:100,stdev:0|index:1,count:166027914,average:100,stdev:0	GSM1223639_r1	GEO			in_mesa	24752171	4.97	2.91	0.06	25147476332	25206031993	22152773664	22285033948	100.23	100.6	149640277	131562065	227.118	1110.281	158	1151674	77.02	87.84	179533476	115252031	179533476	115252031	84.34	83.69	179533476	126202628	179533476	109803630	2641191967	10.50	1.53	0	11.10	0	0.19	0	0.07	0	0.00	0	9.60	0	149640277	0	200	0	196.20	0	1.98	0	0.01	0	2.15	0	0.01	0	266.00	0	0.67	0	2541990	0	166027914	0	18434838	0	318021	0	123590	0	0	0	15946026	0	36962	0	0	0	409918	0	63602893	0	143805	0	64193578	0	79.03	0	131205439	0	289605	65687196	226.816512145854	166027914.0	149640277.0	2541990.0	18434838.0	318021.0	123590.0	0.0	15946026.0	131205439.0	90.1	1.5	11.1	0.2	0.1	0.0	9.6	79.0	100	100	100.00	38	16602791400	27.4	23.3	25.2	24.0	0.1	34.2	17.3	bulk
6415719	SRR964795	SRP029464	SRS476318	SRX344338	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223640: RNA-seq cardiac fibroblasts PN60 (adult); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN60 (adult)|genotype/variation;;wild type|source_name;;Cardiac fibroblasts|strain;;FVB|tissue;;Cardiac fibroblasts	GEO Accession;;GSM1223640		GSM1223640	RNA-seq cardiac fibroblasts PN60 (adult)	37343559614	184869107	2014-04-16 15:55:08	25391402007	37343559614	184869107	2	184869107	index:0,count:184869107,average:101,stdev:0|index:1,count:184869107,average:101,stdev:0	GSM1223640_r1	GEO			in_mesa	24752171	3.43	2.77	0.29	27825676809	26782612289	25321280200	24942788757	96.25	98.51	173147606	160827439	189.818	621.911	145	1651012	84.39	92.83	205339748	146124355	205339748	146124355	87.12	89.73	205339748	150846534	205339748	141248592	1454495080	5.23	1.18	0	8.51	0	1.24	0	0.05	0	0.00	0	5.05	0	173147606	0	202	0	199.17	0	2.12	0	0.01	0	1.89	0	0.02	0	310.70	0	0.39	0	2180474	0	184869107	0	15734302	0	2288865	0	100397	0	0	0	9332239	0	33600	0	0	0	548045	0	80367728	0	175615	0	81124988	0	85.15	0	157413304	0	405074	71534450	176.596004680626	184869107.0	173147606.0	2180474.0	15734302.0	2288865.0	100397.0	0.0	9332239.0	157413304.0	93.7	1.2	8.5	1.2	0.1	0.0	5.0	85.1	101	101	101.00	38	18671779807	24.9	25.1	25.0	24.9	0.0	35.2	18.8	bulk
6415782	SRR964796	SRP029464	SRS476319	SRX344339	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223641: RNA-seq cardiac fibroblasts PN28; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN28|genotype/variation;;wild type|source_name;;Cardiac fibroblasts|strain;;FVB|tissue;;Cardiac fibroblasts	GEO Accession;;GSM1223641		GSM1223641	RNA-seq cardiac fibroblasts PN28	39480464892	195447846	2014-04-16 15:55:08	27647865615	39480464892	195447846	2	195447846	index:0,count:195447846,average:101,stdev:0|index:1,count:195447846,average:101,stdev:0	GSM1223641_r1	GEO			in_mesa	24752171	2.18	2.61	0.31	29314587886	28034535425	26842078799	26275783058	95.63	97.89	182120803	169005187	190.235	629.856	145	1727860	83.17	90.93	214770344	151464546	214770344	151464546	85.13	87.84	214770344	155033270	214770344	146323273	1971879101	6.73	1.18	0	7.95	0	1.15	0	0.06	0	0.00	0	5.61	0	182120803	0	202	0	199.12	0	2.17	0	0.01	0	1.93	0	0.02	0	261.57	0	0.50	0	2306476	0	195447846	0	15544648	0	2256751	0	108730	0	0	0	10961562	0	38042	0	0	0	628077	0	83582147	0	199625	0	84447891	0	85.23	0	166576155	0	403126	74663891	185.212293426869	195447846.0	182120803.0	2306476.0	15544648.0	2256751.0	108730.0	0.0	10961562.0	166576155.0	93.2	1.2	8.0	1.2	0.1	0.0	5.6	85.2	101	101	101.00	38	19740232446	24.9	25.1	25.0	24.9	0.0	34.6	17.9	bulk
6415845	SRR964797	SRP029464	SRS476320	SRX344340	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223642: RNA-seq cardiac fibroblasts PN1-3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN1|genotype/variation;;wild type|source_name;;Cardiac fibroblasts neonatal|strain;;FVB|tissue;;Cardiac fibroblasts	GEO Accession;;GSM1223642		GSM1223642	RNA-seq cardiac fibroblasts PN1-3	36486689350	180627175	2014-04-16 15:55:08	24765002861	36486689350	180627175	2	180627175	index:0,count:180627175,average:101,stdev:0|index:1,count:180627175,average:101,stdev:0	GSM1223642_r1	GEO			in_mesa	24752171	1.83	2.96	0.09	27466776816	27157442777	25628066687	25507586499	98.87	99.53	170554302	157061963	192.968	640.626	146	1582649	87.04	93.41	191262093	148442115	191262093	148442115	88.85	89.78	191262093	151529214	191262093	142672400	1462128746	5.32	1.14	0	6.44	0	0.39	0	0.06	0	0.00	0	5.12	0	170554302	0	202	0	199.21	0	2.16	0	0.01	0	1.96	0	0.02	0	293.70	0	0.39	0	2055081	0	180627175	0	11638014	0	713430	0	110180	0	0	0	9249263	0	47677	0	0	0	528847	0	86772222	0	157474	0	87506220	0	87.98	0	158916288	0	398607	77206788	193.691500651017	180627175.0	170554302.0	2055081.0	11638014.0	713430.0	110180.0	0.0	9249263.0	158916288.0	94.4	1.1	6.4	0.4	0.1	0.0	5.1	88.0	101	101	101.00	38	18243344675	24.6	25.4	25.3	24.6	0.0	35.2	18.8	bulk
6415972	SRR964799	SRP029464	SRS476322	SRX344342	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223644: RNA-seq cardiomyocytes PN67 (adult); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN67 (adult)|genotype/variation;;wild type|source_name;;Cardiomyocytes|strain;;FVB|tissue;;Cardiomyocytes	GEO Accession;;GSM1223644		GSM1223644	RNA-seq cardiomyocytes PN67 (adult)	33117300666	163947033	2014-04-16 15:55:08	22016877940	33117300666	163947033	2	163947033	index:0,count:163947033,average:101,stdev:0|index:1,count:163947033,average:101,stdev:0	GSM1223644_r1	GEO			in_mesa	24752171	26.38	1.4	0.02	24834169274	24960471067	20612969107	20910285995	100.51	101.44	156208298	145842099	187.159	541.458	136	1516017	80.61	97.24	186664741	125917783	186664741	125917783	93.54	93.29	186664741	146110944	186664741	120803778	516997137	2.08	1.18	0	16.29	0	0.23	0	0.07	0	0.00	0	4.42	0	156208298	0	202	0	199.40	0	2.01	0	0.01	0	1.57	0	0.01	0	320.59	0	0.30	0	1940620	0	163947033	0	26711607	0	382012	0	117142	0	0	0	7239581	0	38649	0	0	0	456385	0	66994744	0	110169	0	67599947	0	78.99	0	129496691	0	278680	59160597	212.288635711210	163947033.0	156208298.0	1940620.0	26711607.0	382012.0	117142.0	0.0	7239581.0	129496691.0	95.3	1.2	16.3	0.2	0.1	0.0	4.4	79.0	101	101	101.00	38	16558650333	26.3	23.7	23.6	26.3	0.0	35.8	19.7	bulk
6422564	SRR964800	SRP029464	SRS476323	SRX344343	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223645: RNA-seq cardiomyocytes PN30; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN30|genotype/variation;;wild type|source_name;;Cardiomyocytes|strain;;FVB|tissue;;Cardiomyocytes	GEO Accession;;GSM1223645		GSM1223645	RNA-seq cardiomyocytes PN30	34716171874	171862237	2014-04-16 15:55:08	23389877007	34716171874	171862237	2	171862237	index:0,count:171862237,average:101,stdev:0|index:1,count:171862237,average:101,stdev:0	GSM1223645_r1	GEO			in_mesa	24752171	24.26	1.5	0.02	26694896988	26873146123	22524381342	22858283350	100.67	101.48	164093684	152062663	195.461	580.531	145	1490499	81.91	97.19	193638547	134408140	193638547	134408140	93.55	93.32	193638547	153506727	193638547	129055625	585110931	2.19	1.14	0	15.01	0	0.21	0	0.06	0	0.00	0	4.25	0	164093684	0	202	0	199.46	0	2.01	0	0.01	0	1.51	0	0.01	0	314.06	0	0.33	0	1957113	0	171862237	0	25803999	0	365955	0	104003	0	0	0	7298595	0	40590	0	0	0	496501	0	73564311	0	116349	0	74217751	0	80.47	0	138289685	0	281308	66313604	235.733089709500	171862237.0	164093684.0	1957113.0	25803999.0	365955.0	104003.0	0.0	7298595.0	138289685.0	95.5	1.1	15.0	0.2	0.1	0.0	4.2	80.5	101	101	101.00	38	17358085937	26.1	23.9	23.8	26.2	0.0	35.6	19.4	bulk
6422628	SRR964801	SRP029464	SRS476324	SRX344344	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223646: RNA-seq cardiomyocytes PN1-2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN1-2|genotype/variation;;wild type|source_name;;Cardiomyocytes neonatal|strain;;FVB|tissue;;Cardiomyocytes	GEO Accession;;GSM1223646		GSM1223646	RNA-seq cardiomyocytes PN1-2	38456078654	190376627	2014-04-16 15:55:08	26588370513	38456078654	190376627	2	190376627	index:0,count:190376627,average:101,stdev:0|index:1,count:190376627,average:101,stdev:0	GSM1223646_r1	GEO			in_mesa	24752171	26.11	1.7	0.04	29052755018	28980512230	22653801058	22805832417	99.75	100.67	181898191	172174751	185.239	491.130	134	1812432	74.89	96.18	234160897	136215156	234160897	136215156	93.46	92.79	234160897	170005086	234160897	131418881	828996249	2.85	1.05	0	21.15	0	0.28	0	0.05	0	0.00	0	4.13	0	181898191	0	202	0	199.53	0	2.02	0	0.01	0	1.51	0	0.01	0	307.47	0	0.40	0	1996762	0	190376627	0	40269319	0	524128	0	95563	0	0	0	7858745	0	38352	0	0	0	421733	0	62491268	0	125578	0	63076931	0	74.39	0	141628872	0	381541	63011260	165.149381062586	190376627.0	181898191.0	1996762.0	40269319.0	524128.0	95563.0	0.0	7858745.0	141628872.0	95.5	1.0	21.2	0.3	0.1	0.0	4.1	74.4	101	101	101.00	38	19228039327	26.5	23.5	23.5	26.5	0.0	35.2	18.9	bulk
6422691	SRR964802	SRP029464	SRS476325	SRX344345	SRA099825	GEO		Transcriptome modulation of ventricles, cardiomyocytes and cardiac fibroblasts during postnatal mouse development	During development the fetal heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). We performed deep RNA-sequencing for high-resolution analysis of transcriptome changes during postnatal mouse heart development using RNA from ventricles and freshly isolated cardiomyocytes (CM) and cardiac fibroblasts (CF). Extensive changes in gene expression and AS occur primarily between postnatal days 1 and 28. CM and CF showed reciprocal regulation of gene expression during postnatal development reflecting differences in proliferative capacity, cell adhesion functions, and mitochondrial metabolism. We found that AS plays a novel role in vesicular trafficking and membrane organization during postnatal CM development. Interestingly, these AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated change in expression. Vesicular traffic genes affected by AS during normal development where Celf1 is down-regulated, showed a reversion to neonatal AS patterns when Celf1 was over-expressed in adults. Overall design: RNA-seq was performed in RNA samples of ventricles, cardiomyocytes or cardiac fibroblast at different developmental stages; embryonic day 17, postnatal day (PN) 1, 10, 28 and 90 for ventricles, PN1-3, PN28 and PN60 for cardiac fibroblasts, and PN1-2, PN30, and PN67 for cardiomyocytes		GSM1223647: RNA-seq cardiomyocytes PN1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			RNeasy fibrous tissue mini kit was used for ventricles and cardiomyocytes, and micro RNeasy kit for cardiac fibroblasts (all from Qiagen) Illumina TruSeq RNA protocols were used for cardiomyocytes and cardiac fibroblast. For developmental ventricle analysis, RNA was rRNA depleted with the Ribo-Zero Magnetic Gold Kit and libraries were prepared using ScriptSeq v2 RNA-seq library preparation kits (Epicentre).	Illumina HiSeq 2000	age;;PN1|genotype/variation;;wild type|source_name;;Cardiomyocytes neonatal|strain;;FVB|tissue;;Cardiomyocytes	GEO Accession;;GSM1223647		GSM1223647	RNA-seq cardiomyocytes PN1	35946118362	177951081	2014-04-16 15:55:08	24443809144	35946118362	177951081	2	177951081	index:0,count:177951081,average:101,stdev:0|index:1,count:177951081,average:101,stdev:0	GSM1223647_r1	GEO			in_mesa	24752171	20.96	1.82	0.04	27489555280	27460927727	21989159418	22141051425	99.9	100.69	170190764	160284448	189.632	515.587	145	1641045	76.74	96.14	218401918	130612254	218401918	130612254	93.14	92.6	218401918	158512865	218401918	125802175	800826322	2.91	0.99	0	19.29	0	0.30	0	0.06	0	0.00	0	4.01	0	170190764	0	202	0	199.58	0	2.06	0	0.01	0	1.55	0	0.01	0	299.08	0	0.37	0	1768727	0	177951081	0	34329619	0	525635	0	98265	0	0	0	7136417	0	39923	0	0	0	431138	0	62582880	0	125750	0	63179691	0	76.35	0	135861145	0	375786	66248326	176.292693181758	177951081.0	170190764.0	1768727.0	34329619.0	525635.0	98265.0	0.0	7136417.0	135861145.0	95.6	1.0	19.3	0.3	0.1	0.0	4.0	76.3	101	101	101.00	38	17973059181	26.0	24.0	24.0	26.0	0.0	35.3	19.0	bulk
1405290	SRR1035716	SRP030031	SRS483726	SRX355536	SRA098368	UCSD	Yeo	Mus musculus Transcriptome or Gene expression	Whole mouse brain RNA-seq		Rbfox1 KO	Rbfox1 KO (sibling pair of Rbfox1 WT) dUTP RNAseq, whole brain	dUTP RNAseq	Rbfox1 KO	RNA-Seq	TRANSCRIPTOMIC	unspecified	single				Illumina HiSeq 2000	isolate;;Whole Brain|label;;Rbfox1 KO RNAseq|sample type;;hiseq 2000		101	Rbfox1 KO RNAseq	Rbfox1 KO RNAseq	22338480878	221173078	2014-01-02 20:52:07	14270058115	22338480878	221173078	1	221173078	index:0,count:221173078,average:101,stdev:0	Rbfox1KO	UCSD					5.72	3.24	0.06	16998139981	16702344355	15466636080	15392220588	98.26	99.52	0	0	0	0	0	0	81.59	89.67	194467730	138712347	194467730	138712347	83.22	84.46	194467730	141480951	194467730	130651389	1196711902	7.04	0.74	0	6.93	0	0.22	0	0.23	0	0.00	0	22.69	0	170002441	0	101	0	99.99	0	2.36	0	0.02	0	1.35	0	0.04	0	295.44	0	0.98	0	1636683	0	221173078	0	15318289	0	492467	0	502711	0	0	0	50175459	0	16978	0	0	0	194321	0	27939143	0	273012	0	28423454	0	69.94	0	154684152	0	307179	29945309	97.484883406743	221173078.0	170002441.0	1636683.0	15318289.0	492467.0	502711.0	0.0	50175459.0	154684152.0	76.9	0.7	6.9	0.2	0.2	0.0	22.7	69.9	101	101	101.00	38	22338480878	22.3	23.4	24.5	29.5	0.3	30.5	11.1	bulk
1405306	SRR1035717	SRP030031	SRS483727	SRX355537	SRA098368	UCSD	Yeo	Mus musculus Transcriptome or Gene expression	Whole mouse brain RNA-seq		Rbfox2 WT	Rbfox2 WT (sibling pair of Rbfox2 KO) dUTP RNAseq, whole brain	dUTP RNAseq	Rbfox2 WT	RNA-Seq	TRANSCRIPTOMIC	unspecified	single				Illumina HiSeq 2000	isolate;;Whole Brain|label;;Rbfox2 WT RNAseq|sample type;;hiseq 2000		101	Rbfox2 WT RNAseq	Rbfox2 WT RNAseq	21767874409	215523509	2014-01-02 22:00:06	13647939953	21767874409	215523509	1	215523509	index:0,count:215523509,average:101,stdev:0	Rbfox2 WT	UCSD					5.02	3.44	0.06	16340058874	16095622726	14989103707	14877575031	98.5	99.26	0	0	0	0	0	0	81.94	89.33	185834066	134982712	185834066	134982712	84.79	85.33	185834066	139676432	185834066	128935934	1325580364	8.11	0.87	0	6.32	0	0.23	0	0.36	0	0.00	0	22.97	0	164739517	0	101	0	99.19	0	2.16	0	0.02	0	1.10	0	0.08	0	297.73	0	1.01	0	1865450	0	215523509	0	13631561	0	499773	0	782227	0	0	0	49501992	0	17671	0	0	0	203628	0	28315218	0	377940	0	28914457	0	70.11	0	151107956	0	296448	30362613	102.421379128886	215523509.0	164739517.0	1865450.0	13631561.0	499773.0	782227.0	0.0	49501992.0	151107956.0	76.4	0.9	6.3	0.2	0.4	0.0	23.0	70.1	101	101	101.00	38	21767874409	22.6	23.0	24.5	29.6	0.4	29.9	10.6	bulk
1405322	SRR1035718	SRP030031	SRS483728	SRX355538	SRA098368	UCSD	Yeo	Mus musculus Transcriptome or Gene expression	Whole mouse brain RNA-seq		Rbfox2KO	Rbfox2 KO (sibling pair of Rbfox2 WT) dUTP RNAseq, whole brain	dUTP RNAseq	Rbfox2KO	RNA-Seq	TRANSCRIPTOMIC	unspecified	single				Illumina HiSeq 2000	isolate;;Whole Brain|label;;Rbfox2 KO RNAseq|sample type;;hiseq 2000		101	Rbfox2 KO RNAseq	Rbfox2 KO RNAseq	11623376839	115082939	2014-01-02 21:28:07	6880920924	11623376839	115082939	1	115082939	index:0,count:115082939,average:101,stdev:0	Rbfox2 KO	UCSD					4.5	3.36	0.06	8775547397	8668378398	8140470563	8093083494	98.78	99.42	0	0	0	0	0	0	83.78	90.32	98221273	73684643	98221273	73684643	85.68	86.15	98221273	75358540	98221273	70283899	639754756	7.29	0.85	0	5.53	0	0.25	0	0.33	0	0.00	0	23.00	0	87948399	0	101	0	99.79	0	2.19	0	0.02	0	1.28	0	0.05	0	290.94	0	0.75	0	979868	0	115082939	0	6369511	0	287731	0	375141	0	0	0	26471668	0	9990	0	0	0	117631	0	16631649	0	177121	0	16936391	0	70.89	0	81578888	0	228822	17755461	77.595078270446	115082939.0	87948399.0	979868.0	6369511.0	287731.0	375141.0	0.0	26471668.0	81578888.0	76.4	0.9	5.5	0.3	0.3	0.0	23.0	70.9	101	101	101.00	38	11623376839	21.6	23.5	25.0	29.7	0.3	32.8	12.5	bulk
5554353	SRR997302	SRP030031	SRS483725	SRX355535	SRA098368	UCSD	Yeo	Mus musculus Transcriptome or Gene expression	Whole mouse brain RNA-seq		Rbfox1 WT	Rbfox1 WT (sibling pair of Rbfox1 KO) dUTP RNAseq, whole brain	dUTP RNAseq	Rbfox1 WT	RNA-Seq	TRANSCRIPTOMIC	unspecified	single				Illumina HiSeq 2000	isolate;;Whole Brain|label;;Rbfox1 WT RNAseq|sample_type;;hiseq 2000		101	Rbfox1 WT RNAseq	Rbfox1 WT RNAseq	26637785147	263740447	2014-01-02 21:24:11	17280151046	26637785147	263740447	1	263740447	index:0,count:263740447,average:101,stdev:0	Rbfox1WT	UCSD					5.84	3.49	0.05	19226932122	18956929715	17595999133	17485705812	98.6	99.37	0	0	0	0	0	0	83.46	91.18	217885909	160839128	217885909	160839128	86.56	87.14	217885909	166827099	217885909	153705058	1240716829	6.45	0.52	0	6.19	0	0.21	0	0.23	0	0.00	0	26.49	0	192721880	0	101	0	99.76	0	2.15	0	0.01	0	1.26	0	0.04	0	430.21	0	1.34	0	1375173	0	263740447	0	16330825	0	543090	0	604796	0	0	0	69870681	0	19909	0	0	0	214240	0	33616418	0	450884	0	34301451	0	66.88	0	176391055	0	335771	36077060	107.445431559009	263740447.0	192721880.0	1375173.0	16330825.0	543090.0	604796.0	0.0	69870681.0	176391055.0	73.1	0.5	6.2	0.2	0.2	0.0	26.5	66.9	101	101	101.00	38	26637785147	21.4	22.7	24.3	30.7	0.9	27.2	9.5	bulk
1839256	SRR1945109	SRP033468	SRS886940	SRX971927	SRA249131	Beijing Proteome Research Center	Functional proteome	Mus musculus Transcriptome or Gene expression	Normal mouse liver transcriptome landscape		HC1		hepatocyte		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|sample_type;;HC|sex;;male|strain;;C57-BL|tissue;;liver		180	HC1	hepatocyte	3546478980	19702662	2016-03-03 19:57:56	2469142362	3546478980	19702662	2	19702662	index:0,count:19702662,average:90,stdev:0|index:1,count:19702660,average:90,stdev:0	HC1	Beijing Proteome Research Center			in_mesa	27562671	11.83	0.93	0.05	3400618626	3402664336	3003502690	3026132024	100.06	100.75	19142936	17436535	219.182	508.537	187	409951	85.69	96.99	22575357	16403823	22575357	16403823	94.53	94.47	22575357	18096124	22575357	15976658	81311789	2.39	0.43	0.00	11.32	50.00	0.62	0.00	1.58	0.00	0.00	0.00	0.65	0.00	19142936	2	180	90	178.67	90.00	1.60	0.00	0.00	0.00	1.25	0.00	0.00	0.00	155.55	0.01	0.28	0.00	85130	0	19702660	2	2230877	1	121371	0	310353	0	0	0	128000	0	2553	0	0	0	51107	0	8756078	0	7384	0	8817122	0	85.84	50.00	16912059	1	127903	9955897	77.839433007826	19702662.0	19142938.0	85130.0	2230878.0	121371.0	310353.0	0.0	128000.0	16912060.0	97.2	0.4	11.3	0.6	1.6	0.0	0.6	85.8	90	90	90.00	10	180	31.7	17.2	24.4	26.7	0.0	38.4	36.2	bulk
461159	SRR1945259	SRP033468	SRS886942	SRX971928	SRA249131	Beijing Proteome Research Center	Functional proteome	Mus musculus Transcriptome or Gene expression	Normal mouse liver transcriptome landscape		LSEC1		liver sinusoidal endothelial cell		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;9 weeks|BioSampleModel;;Model organism or animal|sample_type;;LSEC|sex;;male|strain;;C57-BL|tissue;;liver		180	LSEC1	liver sinusoidal endothelial cell	3743672220	20798179	2017-01-22 00:00:00	2691849298	3743672220	20798179	2	20798179	index:0,count:20798179,average:90,stdev:0|index:1,count:20798179,average:90,stdev:0	LSEC1	Beijing Proteome Research Center			in_mesa	27562671	6.55	2.61	0.09	3545133370	3513748206	3311315415	3309580138	99.11	99.95	20458360	19154602	204.561	561.527	191	403140	85.8	91.88	22453824	17554087	22453824	17554087	88.25	88.62	22453824	18054222	22453824	16930637	241265062	6.81	1.62	0	6.50	0	0.30	0	0.10	0	0.00	0	1.23	0	20458360	0	180	0	178.43	0	1.54	0	0.00	0	1.24	0	0.00	0	367.03	0	0.27	0	336265	0	20798179	0	1352742	0	62556	0	20733	0	0	0	256530	0	4937	0	0	0	39409	0	7191060	0	12677	0	7248083	0	91.86	0	19105618	0	171961	7240804	42.107245247469	20798179.0	20458360.0	336265.0	1352742.0	62556.0	20733.0	0.0	256530.0	19105618.0	98.4	1.6	6.5	0.3	0.1	0.0	1.2	91.9	90	90	90.00	38	1871836110	25.4	23.8	24.8	26.0	0.0	35.4	21.5	bulk
921750	SRR1042212	SRP033468	SRS510481	SRX386467	SRA115139	Beijing Proteome Research Center	Functional proteome	Mus musculus Transcriptome or Gene expression	Normal mouse liver transcriptome landscape		Normal mouse liver tissue transcriptome				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired		0.0E0		Illumina HiSeq 2000	strain;;C57BL/6J		180	BPRC_mouse_liver_tissue	Normal mouse liver tissue	3371145480	18728586	2015-07-22 17:10:15	1985204879	3371145480	18728586	2	18728586	index:0,count:18728586,average:90,stdev:0|index:1,count:18728586,average:90,stdev:0	mouse liver tissue	Beijing Proteome Research Center			in_mesa	27562671	24.11	0.94	0.02	3150439464	3126306694	2718375884	2720781670	99.23	100.09	17846429	16541474	220.500	540.179	199	664942	82.55	95.66	21088445	14732158	21088445	14732158	93.88	93.45	21088445	16753783	21088445	14392392	106585013	3.38	4.54	0	13.06	0	0.37	0	0.36	0	0.00	0	3.98	0	17846429	0	180	0	176.97	0	1.43	0	0.00	0	1.28	0	0.00	0	140.76	0	0.42	0	849749	0	18728586	0	2445493	0	68391	0	67630	0	0	0	746136	0	1845	0	0	0	29351	0	6286705	0	11392	0	6329293	0	82.23	0	15400936	0	114392	6826417	59.675650395133	18728586.0	17846429.0	849749.0	2445493.0	68391.0	67630.0	0.0	746136.0	15400936.0	95.3	4.5	13.1	0.4	0.4	0.0	4.0	82.2	90	90	90.00	38	1685572740	26.6	22.7	24.1	26.7	0.0	35.0	16.9	bulk
922374	SRR1945260	SRP033468	SRS886943	SRX971929	SRA249131	Beijing Proteome Research Center	Functional proteome	Mus musculus Transcriptome or Gene expression	Normal mouse liver transcriptome landscape		KC1		kupffer		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;10 weeks|BioSampleModel;;Model organism or animal|sample_type;;KC|sex;;male|strain;;C57-BL|tissue;;liver		180	KC1	kupffer	3431500920	19063894	2017-01-22 00:00:00	2403057398	3431500920	19063894	2	19063894	index:0,count:19063894,average:90,stdev:0|index:1,count:19063894,average:90,stdev:0	KC1	Beijing Proteome Research Center			in_mesa	27562671	5.94	2.67	0.13	3327696625	3297811973	3083127740	3077971454	99.1	99.83	18819946	17921119	206.415	453.282	187	422519	85.04	91.78	20942515	16004509	20942515	16004509	88.08	88.32	20942515	16576311	20942515	15401118	219854534	6.61	0.50	0	7.25	0	0.38	0	0.08	0	0.00	0	0.82	0	18819946	0	180	0	178.73	0	1.56	0	0.00	0	1.19	0	0.00	0	313.38	0	0.33	0	94540	0	19063894	0	1382407	0	72329	0	15499	0	0	0	156120	0	6908	0	0	0	32274	0	6377755	0	9749	0	6426686	0	91.47	0	17437539	0	152603	6560202	42.988683053413	19063894.0	18819946.0	94540.0	1382407.0	72329.0	15499.0	0.0	156120.0	17437539.0	98.7	0.5	7.3	0.4	0.1	0.0	0.8	91.5	90	90	90.00	38	1715750460	24.5	24.4	26.6	24.4	0.0	35.2	19.4	bulk
922389	SRR1945262	SRP033468	SRS886980	SRX971930	SRA249131	Beijing Proteome Research Center	Functional proteome	Mus musculus Transcriptome or Gene expression	Normal mouse liver transcriptome landscape		HSC1		Hepatic stellate cell		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;11 weeks|BioSampleModel;;Model organism or animal|sample_type;;HSC|sex;;male|strain;;C57-BL|tissue;;liver		180	HSC1	Hepatic stellate cell	4671310320	25951724	2017-01-22 00:00:00	3221035082	4671310320	25951724	2	25951724	index:0,count:25951724,average:90,stdev:0|index:1,count:25951724,average:90,stdev:0	HSC1	Beijing Proteome Research Center			in_mesa	27562671	4.2	2.81	0.12	4317434643	4273626106	4060702830	4048141754	98.99	99.69	24444918	22082033	241.785	752.472	203	319359	84.85	90.22	26808532	20741437	26808532	20741437	86.79	87.2	26808532	21214582	26808532	20046502	369312339	8.55	4.04	0	5.61	0	0.27	0	0.12	0	0.00	0	5.41	0	24444918	0	180	0	177.65	0	1.50	0	0.00	0	1.19	0	0.00	0	167.73	0	0.23	0	1049541	0	25951724	0	1455848	0	70192	0	32300	0	0	0	1404314	0	7205	0	0	0	51135	0	8402953	0	18012	0	8479305	0	88.58	0	22989070	0	185193	8687364	46.909786007031	25951724.0	24444918.0	1049541.0	1455848.0	70192.0	32300.0	0.0	1404314.0	22989070.0	94.2	4.0	5.6	0.3	0.1	0.0	5.4	88.6	90	90	90.00	38	2335655160	25.8	23.5	25.3	25.4	0.0	35.7	21.3	bulk
327826	SRR1056024	SRP034660	SRS517824	SRX396844	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295651: KO 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295651		GSM1295651	KO 1	5938710312	29399556	2017-01-03 09:54:06	4483716917	5938710312	29399556	2	29399556	index:0,count:29399556,average:101,stdev:0|index:1,count:29399556,average:101,stdev:0	GSM1295651_r2	GEO			in_mesa	26082520	2.39	2.9	0.03	4906151929	4863917878	4689677660	4668435697	99.14	99.55	28480433	26564906	200.058	630.923	158	258659	83.66	87.57	30481122	23826865	30481122	23826865	83.73	84.03	30481122	23845827	30481122	22863329	544439721	11.10	0.98	0	4.32	0	0.16	0	0.07	0	0.00	0	2.89	0	28480433	0	202	0	199.49	0	2.00	0	0.01	0	1.60	0	0.01	0	195.63	0	0.58	0	288992	0	29399556	0	1271321	0	48342	0	20397	0	0	0	850384	0	7215	0	0	0	70290	0	11626950	0	22735	0	11727190	0	92.55	0	27209112	0	220059	10998151	49.978192212089	29399556.0	28480433.0	288992.0	1271321.0	48342.0	20397.0	0.0	850384.0	27209112.0	96.9	1.0	4.3	0.2	0.1	0.0	2.9	92.5	101	101	101.00	38	2969355156	25.4	24.6	24.5	25.5	0.0	32.5	15.3	bulk
327830	SRR1056025	SRP034660	SRS517824	SRX396844	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295651: KO 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295651		GSM1295651	KO 1	5990364540	29655270	2017-01-03 09:54:06	4523862021	5990364540	29655270	2	29655270	index:0,count:29655270,average:101,stdev:0|index:1,count:29655270,average:101,stdev:0	GSM1295651_r3	GEO			in_mesa	26082520	2.39	2.9	0.03	4961182572	4918339893	4742069931	4720372766	99.14	99.54	28765749	26825383	200.359	632.744	157	262225	83.63	87.54	30786843	24056882	30786843	24056882	83.71	84.01	30786843	24079270	30786843	23085139	551567226	11.12	1.01	0	4.34	0	0.16	0	0.07	0	0.00	0	2.77	0	28765749	0	202	0	199.67	0	2.00	0	0.01	0	1.61	0	0.01	0	199.18	0	0.58	0	298371	0	29655270	0	1285699	0	48730	0	20697	0	0	0	820094	0	7288	0	0	0	70462	0	11816260	0	23039	0	11917049	0	92.66	0	27480050	0	220957	11179560	50.596088831764	29655270.0	28765749.0	298371.0	1285699.0	48730.0	20697.0	0.0	820094.0	27480050.0	97.0	1.0	4.3	0.2	0.1	0.0	2.8	92.7	101	101	101.00	38	2995182270	25.4	24.6	24.5	25.5	0.0	32.6	15.5	bulk
327834	SRR1056026	SRP034660	SRS517824	SRX396844	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295651: KO 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295651		GSM1295651	KO 1	6175717114	30572857	2017-01-03 09:54:06	4635573089	6175717114	30572857	2	30572857	index:0,count:30572857,average:101,stdev:0|index:1,count:30572857,average:101,stdev:0	GSM1295651_r4	GEO			in_mesa	26082520	2.36	2.9	0.03	5121970376	5079058189	4897901305	4876473854	99.16	99.56	29673580	27661173	200.766	633.868	166	268816	83.71	87.59	31744014	24840896	31744014	24840896	83.74	84.04	31744014	24849970	31744014	23834589	567298352	11.08	1.04	0	4.30	0	0.16	0	0.07	0	0.00	0	2.70	0	29673580	0	202	0	199.74	0	2.00	0	0.01	0	1.62	0	0.01	0	291.17	0	0.54	0	318222	0	30572857	0	1313862	0	50376	0	22168	0	0	0	826733	0	7780	0	0	0	75115	0	12317763	0	23757	0	12424415	0	92.76	0	28359718	0	223248	11649666	52.182622016771	30572857.0	29673580.0	318222.0	1313862.0	50376.0	22168.0	0.0	826733.0	28359718.0	97.1	1.0	4.3	0.2	0.1	0.0	2.7	92.8	101	101	101.00	38	3087858557	25.4	24.7	24.5	25.5	0.0	32.9	15.9	bulk
327838	SRR1056027	SRP034660	SRS517825	SRX396845	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295652: KO 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295652		GSM1295652	KO 2	4950783660	24508830	2017-01-03 09:54:06	3708750337	4950783660	24508830	2	24508830	index:0,count:24508830,average:101,stdev:0|index:1,count:24508830,average:101,stdev:0	GSM1295652_r1	GEO			in_mesa	26082520	3.28	2.93	0.03	4183236967	4154991765	3991175413	3980906005	99.32	99.74	23854173	21972316	208.538	705.311	167	203100	86.21	90.4	25531906	20564203	25531906	20564203	86.9	87.2	25531906	20729755	25531906	19835758	355579154	8.50	1.07	0	4.52	0	0.16	0	0.06	0	0.00	0	2.44	0	23854173	0	202	0	199.79	0	1.75	0	0.01	0	1.49	0	0.01	0	244.41	0	0.51	0	261075	0	24508830	0	1106959	0	40106	0	15570	0	0	0	598981	0	6628	0	0	0	64091	0	10443261	0	18239	0	10532219	0	92.81	0	22747214	0	211238	9969805	47.197024209659	24508830.0	23854173.0	261075.0	1106959.0	40106.0	15570.0	0.0	598981.0	22747214.0	97.3	1.1	4.5	0.2	0.1	0.0	2.4	92.8	101	101	101.00	38	2475391830	25.5	24.6	24.4	25.6	0.0	32.8	15.6	bulk
327842	SRR1056028	SRP034660	SRS517825	SRX396845	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295652: KO 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295652		GSM1295652	KO 2	4779860754	23662677	2017-01-03 09:54:06	3602113034	4779860754	23662677	2	23662677	index:0,count:23662677,average:101,stdev:0|index:1,count:23662677,average:101,stdev:0	GSM1295652_r2	GEO			in_mesa	26082520	3.32	2.95	0.03	4027198525	3999174302	3840856493	3830278444	99.3	99.72	22995606	21193323	208.030	702.877	166	196569	86.14	90.36	24619907	19807907	24619907	19807907	86.86	87.16	24619907	19974826	24619907	19107093	343840071	8.54	1.04	0	4.54	0	0.16	0	0.06	0	0.00	0	2.59	0	22995606	0	202	0	199.59	0	1.74	0	0.01	0	1.49	0	0.01	0	228.99	0	0.55	0	245605	0	23662677	0	1074887	0	38549	0	14752	0	0	0	613770	0	6241	0	0	0	61065	0	9922179	0	17233	0	10006718	0	92.64	0	21920719	0	208358	9472583	45.463015578955	23662677.0	22995606.0	245605.0	1074887.0	38549.0	14752.0	0.0	613770.0	21920719.0	97.2	1.0	4.5	0.2	0.1	0.0	2.6	92.6	101	101	101.00	38	2389930377	25.5	24.5	24.3	25.7	0.0	32.6	15.5	bulk
327847	SRR1056029	SRP034660	SRS517825	SRX396845	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295652: KO 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295652		GSM1295652	KO 2	4850236746	24011073	2017-01-03 09:54:06	3655981396	4850236746	24011073	2	24011073	index:0,count:24011073,average:101,stdev:0|index:1,count:24011073,average:101,stdev:0	GSM1295652_r3	GEO			in_mesa	26082520	3.33	2.94	0.03	4094464444	4066117443	3904945780	3894327670	99.31	99.73	23358103	21525813	208.270	701.352	166	198799	86.13	90.35	25006549	20118315	25006549	20118315	86.86	87.16	25006549	20288701	25006549	19406254	349787486	8.54	1.06	0	4.55	0	0.16	0	0.06	0	0.00	0	2.50	0	23358103	0	202	0	199.73	0	1.75	0	0.01	0	1.48	0	0.01	0	219.39	0	0.55	0	255010	0	24011073	0	1092043	0	38796	0	14677	0	0	0	599497	0	6166	0	0	0	61864	0	10130683	0	17599	0	10216312	0	92.73	0	22266060	0	209587	9665919	46.118886190460	24011073.0	23358103.0	255010.0	1092043.0	38796.0	14677.0	0.0	599497.0	22266060.0	97.3	1.1	4.5	0.2	0.1	0.0	2.5	92.7	101	101	101.00	38	2425118373	25.5	24.5	24.3	25.7	0.0	32.7	15.6	bulk
327883	SRR1056032	SRP034660	SRS517826	SRX396846	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295653: KO 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295653		GSM1295653	KO 3	5339159768	26431484	2017-01-03 09:54:06	4022785815	5339159768	26431484	2	26431484	index:0,count:26431484,average:101,stdev:0|index:1,count:26431484,average:101,stdev:0	GSM1295653_r2	GEO			in_mesa	26082520	2.12	3.02	0.03	4397249104	4364954594	4224351824	4209626667	99.27	99.65	25725539	23968562	198.953	632.856	157	229895	83.92	87.4	27360970	21588464	27360970	21588464	83.99	84.22	27360970	21606946	27360970	20803447	514209117	11.69	0.97	0	3.88	0	0.17	0	0.09	0	0.00	0	2.41	0	25725539	0	202	0	199.69	0	1.65	0	0.01	0	1.41	0	0.01	0	267.28	0	0.53	0	257342	0	26431484	0	1024950	0	45706	0	23113	0	0	0	637126	0	6748	0	0	0	64935	0	10612722	0	19071	0	10703476	0	93.45	0	24700589	0	214728	9924014	46.216674117954	26431484.0	25725539.0	257342.0	1024950.0	45706.0	23113.0	0.0	637126.0	24700589.0	97.3	1.0	3.9	0.2	0.1	0.0	2.4	93.5	101	101	101.00	38	2669579884	25.4	24.6	24.4	25.5	0.0	32.7	15.5	bulk
327886	SRR1056033	SRP034660	SRS517826	SRX396846	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295653: KO 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295653		GSM1295653	KO 3	5400033680	26732840	2017-01-03 09:54:06	4068974189	5400033680	26732840	2	26732840	index:0,count:26732840,average:101,stdev:0|index:1,count:26732840,average:101,stdev:0	GSM1295653_r3	GEO			in_mesa	26082520	2.12	3.02	0.03	4457520768	4424325158	4281917684	4266546601	99.26	99.64	26048022	24270257	199.282	633.649	157	232319	83.9	87.39	27706554	21853348	27706554	21853348	83.97	84.21	27706554	21873427	27706554	21059100	521880222	11.71	1.00	0	3.89	0	0.17	0	0.09	0	0.00	0	2.30	0	26048022	0	202	0	199.86	0	1.65	0	0.01	0	1.40	0	0.01	0	232.46	0	0.53	0	267319	0	26732840	0	1039932	0	46339	0	23437	0	0	0	615042	0	6816	0	0	0	65946	0	10806555	0	20006	0	10899323	0	93.55	0	25008090	0	215296	10101767	46.920365450357	26732840.0	26048022.0	267319.0	1039932.0	46339.0	23437.0	0.0	615042.0	25008090.0	97.4	1.0	3.9	0.2	0.1	0.0	2.3	93.5	101	101	101.00	38	2700016840	25.4	24.6	24.4	25.6	0.0	32.8	15.7	bulk
327890	SRR1056034	SRP034660	SRS517826	SRX396846	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295653: KO 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295653		GSM1295653	KO 3	5524030168	27346684	2017-01-03 09:54:06	4135850087	5524030168	27346684	2	27346684	index:0,count:27346684,average:101,stdev:0|index:1,count:27346684,average:101,stdev:0	GSM1295653_r4	GEO			in_mesa	26082520	2.1	3.01	0.03	4567613709	4535375082	4389427164	4374965959	99.29	99.67	26660536	24825270	199.809	638.130	157	236579	83.98	87.44	28343291	22390363	28343291	22390363	84.02	84.25	28343291	22401139	28343291	21573632	532774285	11.66	1.03	0	3.85	0	0.17	0	0.09	0	0.00	0	2.24	0	26660536	0	202	0	199.93	0	1.66	0	0.01	0	1.41	0	0.01	0	224.26	0	0.48	0	281384	0	27346684	0	1054127	0	47603	0	25211	0	0	0	613334	0	7376	0	0	0	69085	0	11178569	0	20401	0	11275431	0	93.64	0	25606409	0	217052	10445190	48.122984353980	27346684.0	26660536.0	281384.0	1054127.0	47603.0	25211.0	0.0	613334.0	25606409.0	97.5	1.0	3.9	0.2	0.1	0.0	2.2	93.6	101	101	101.00	38	2762015084	25.4	24.6	24.4	25.5	0.0	33.1	16.2	bulk
655500	SRR1056011	SRP034660	SRS517822	SRX396841	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295648: WT Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295648		GSM1295648	WT Control 1	4468624608	22121904	2017-01-03 09:54:06	3342351692	4468624608	22121904	2	22121904	index:0,count:22121904,average:101,stdev:0|index:1,count:22121904,average:101,stdev:0	GSM1295648_r1	GEO			in_mesa	26082520	2.28	2.95	0.03	3721572644	3696865080	3569541921	3559039820	99.34	99.71	21612543	20126603	200.265	642.917	157	195290	84.13	87.76	23023793	18182833	23023793	18182833	84.41	84.62	23023793	18244041	23023793	17532859	421173250	11.32	1.03	0	4.04	0	0.17	0	0.07	0	0.00	0	2.07	0	21612543	0	202	0	199.94	0	1.80	0	0.01	0	1.44	0	0.01	0	262.83	0	0.49	0	227794	0	22121904	0	893649	0	37128	0	15204	0	0	0	457029	0	5576	0	0	0	54710	0	8954050	0	16682	0	9031018	0	93.66	0	20718894	0	200670	8420969	41.964264713211	22121904.0	21612543.0	227794.0	893649.0	37128.0	15204.0	0.0	457029.0	20718894.0	97.7	1.0	4.0	0.2	0.1	0.0	2.1	93.7	101	101	101.00	38	2234312304	25.6	24.4	24.2	25.8	0.0	33.0	15.9	bulk
655508	SRR1056012	SRP034660	SRS517822	SRX396841	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295648: WT Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295648		GSM1295648	WT Control 1	4322265508	21397354	2017-01-03 09:54:06	3253555937	4322265508	21397354	2	21397354	index:0,count:21397354,average:101,stdev:0|index:1,count:21397354,average:101,stdev:0	GSM1295648_r2	GEO			in_mesa	26082520	2.31	2.98	0.03	3588991320	3563836629	3441593706	3430330596	99.3	99.67	20872717	19447288	199.750	639.554	158	188370	84.03	87.68	22242965	17540379	22242965	17540379	84.35	84.56	22242965	17606161	22242965	16916076	408684241	11.39	1.01	0	4.05	0	0.17	0	0.07	0	0.00	0	2.22	0	20872717	0	202	0	199.71	0	1.81	0	0.01	0	1.44	0	0.01	0	216.38	0	0.52	0	215074	0	21397354	0	867240	0	35469	0	14193	0	0	0	474975	0	5404	0	0	0	52499	0	8513276	0	16007	0	8587186	0	93.50	0	20005477	0	198499	8007183	40.338656617917	21397354.0	20872717.0	215074.0	867240.0	35469.0	14193.0	0.0	474975.0	20005477.0	97.5	1.0	4.1	0.2	0.1	0.0	2.2	93.5	101	101	101.00	38	2161132754	25.7	24.3	24.1	25.9	0.0	32.8	15.8	bulk
655516	SRR1056013	SRP034660	SRS517822	SRX396841	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295648: WT Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295648		GSM1295648	WT Control 1	4344784872	21508836	2017-01-03 09:54:06	3269810243	4344784872	21508836	2	21508836	index:0,count:21508836,average:101,stdev:0|index:1,count:21508836,average:101,stdev:0	GSM1295648_r3	GEO			in_mesa	26082520	2.33	2.97	0.03	3616218727	3591016782	3467344991	3456199301	99.3	99.68	21005464	19569056	200.039	639.258	157	190330	84.02	87.68	22384842	17649808	22384842	17649808	84.35	84.55	22384842	17718137	22384842	17021327	412069140	11.40	1.03	0	4.07	0	0.16	0	0.07	0	0.00	0	2.11	0	21005464	0	202	0	199.88	0	1.80	0	0.01	0	1.45	0	0.01	0	212.72	0	0.52	0	221304	0	21508836	0	874818	0	35342	0	14317	0	0	0	453713	0	5380	0	0	0	52864	0	8614416	0	16373	0	8689033	0	93.59	0	20130646	0	198746	8099185	40.751436506898	21508836.0	21005464.0	221304.0	874818.0	35342.0	14317.0	0.0	453713.0	20130646.0	97.7	1.0	4.1	0.2	0.1	0.0	2.1	93.6	101	101	101.00	38	2172392436	25.7	24.3	24.1	25.9	0.0	32.9	15.9	bulk
655524	SRR1056014	SRP034660	SRS517822	SRX396841	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295648: WT Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295648		GSM1295648	WT Control 1	4489870564	22227082	2017-01-03 09:54:06	3357532911	4489870564	22227082	2	22227082	index:0,count:22227082,average:101,stdev:0|index:1,count:22227082,average:101,stdev:0	GSM1295648_r4	GEO			in_mesa	26082520	2.29	2.96	0.03	3741955939	3716766649	3589009616	3578143762	99.33	99.7	21718475	20220866	200.485	643.390	157	195511	84.11	87.74	23137740	18266519	23137740	18266519	84.4	84.61	23137740	18330826	23137740	17615529	424329281	11.34	1.06	0	4.04	0	0.17	0	0.07	0	0.00	0	2.05	0	21718475	0	202	0	199.94	0	1.81	0	0.01	0	1.45	0	0.01	0	208.92	0	0.48	0	235869	0	22227082	0	898391	0	36892	0	15482	0	0	0	456233	0	5637	0	0	0	56158	0	9005968	0	16863	0	9084626	0	93.67	0	20820084	0	201169	8466820	42.088095084233	22227082.0	21718475.0	235869.0	898391.0	36892.0	15482.0	0.0	456233.0	20820084.0	97.7	1.1	4.0	0.2	0.1	0.0	2.1	93.7	101	101	101.00	38	2244935282	25.6	24.4	24.1	25.9	0.0	33.3	16.4	bulk
655533	SRR1056015	SRP034660	SRS517821	SRX396842	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295649: WT Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295649		GSM1295649	WT Control 2	4320818582	21390191	2017-01-03 09:54:06	3249085576	4320818582	21390191	2	21390191	index:0,count:21390191,average:101,stdev:0|index:1,count:21390191,average:101,stdev:0	GSM1295649_r1	GEO			in_mesa	26082520	2.13	2.9	0.03	3615251796	3596417207	3466694913	3462410463	99.48	99.88	20889032	19417545	202.530	656.241	158	185892	85.27	88.96	22286228	17812111	22286228	17812111	85.49	85.77	22286228	17857081	22286228	17172274	369947895	10.23	1.02	0	4.06	0	0.22	0	0.06	0	0.00	0	2.07	0	20889032	0	202	0	199.86	0	1.76	0	0.01	0	1.44	0	0.01	0	202.64	0	0.52	0	217944	0	21390191	0	867531	0	46307	0	12911	0	0	0	441941	0	5657	0	0	0	53990	0	8781209	0	16002	0	8856858	0	93.60	0	20021501	0	200561	8300266	41.385244389487	21390191.0	20889032.0	217944.0	867531.0	46307.0	12911.0	0.0	441941.0	20021501.0	97.7	1.0	4.1	0.2	0.1	0.0	2.1	93.6	101	101	101.00	38	2160409291	25.4	24.6	24.5	25.5	0.0	32.6	15.4	bulk
655540	SRR1056016	SRP034660	SRS517821	SRX396842	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295649: WT Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295649		GSM1295649	WT Control 2	4190954196	20747298	2017-01-03 09:54:06	3169135397	4190954196	20747298	2	20747298	index:0,count:20747298,average:101,stdev:0|index:1,count:20747298,average:101,stdev:0	GSM1295649_r2	GEO			in_mesa	26082520	2.15	2.91	0.03	3495538221	3476531077	3351315427	3346543171	99.46	99.86	20229593	18814718	201.976	652.558	166	179865	85.21	88.91	21588048	17236860	21588048	17236860	85.45	85.73	21588048	17286335	21588048	16620579	359486279	10.28	0.99	0	4.07	0	0.21	0	0.06	0	0.00	0	2.22	0	20229593	0	202	0	199.64	0	1.75	0	0.01	0	1.43	0	0.01	0	132.66	0	0.56	0	205252	0	20747298	0	843540	0	44266	0	12582	0	0	0	460857	0	5321	0	0	0	51539	0	8387250	0	15436	0	8459546	0	93.44	0	19386053	0	198264	7922537	39.959533752976	20747298.0	20229593.0	205252.0	843540.0	44266.0	12582.0	0.0	460857.0	19386053.0	97.5	1.0	4.1	0.2	0.1	0.0	2.2	93.4	101	101	101.00	38	2095477098	25.4	24.6	24.4	25.5	0.0	32.5	15.3	bulk
655548	SRR1056017	SRP034660	SRS517821	SRX396842	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295649: WT Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295649		GSM1295649	WT Control 2	4253195446	21055423	2017-01-03 09:54:06	3217047971	4253195446	21055423	2	21055423	index:0,count:21055423,average:101,stdev:0|index:1,count:21055423,average:101,stdev:0	GSM1295649_r3	GEO			in_mesa	26082520	2.17	2.91	0.03	3554835538	3535080412	3407779384	3402638999	99.44	99.85	20552623	19113936	202.164	653.841	158	183020	85.19	88.9	21934558	17508038	21934558	17508038	85.44	85.72	21934558	17560298	21934558	16882134	365607377	10.28	1.02	0	4.08	0	0.21	0	0.06	0	0.00	0	2.12	0	20552623	0	202	0	199.80	0	1.76	0	0.01	0	1.44	0	0.01	0	199.47	0	0.56	0	213985	0	21055423	0	859181	0	44401	0	12735	0	0	0	445664	0	5439	0	0	0	52376	0	8560257	0	15344	0	8633416	0	93.53	0	19693442	0	199279	8085140	40.571961922731	21055423.0	20552623.0	213985.0	859181.0	44401.0	12735.0	0.0	445664.0	19693442.0	97.6	1.0	4.1	0.2	0.1	0.0	2.1	93.5	101	101	101.00	38	2126597723	25.4	24.6	24.4	25.6	0.0	32.6	15.5	bulk
655556	SRR1056018	SRP034660	SRS517821	SRX396842	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295649: WT Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295649		GSM1295649	WT Control 2	4369324640	21630320	2017-01-03 09:54:06	3285283667	4369324640	21630320	2	21630320	index:0,count:21630320,average:101,stdev:0|index:1,count:21630320,average:101,stdev:0	GSM1295649_r4	GEO			in_mesa	26082520	2.13	2.89	0.03	3657514295	3637940383	3507166042	3502447613	99.46	99.87	21124509	19636100	202.670	657.064	157	186799	85.27	88.96	22539438	18012245	22539438	18012245	85.49	85.78	22539438	18060230	22539438	17367734	374157846	10.23	1.05	0	4.06	0	0.22	0	0.06	0	0.00	0	2.06	0	21124509	0	202	0	199.86	0	1.76	0	0.01	0	1.44	0	0.01	0	220.59	0	0.51	0	226935	0	21630320	0	877499	0	46743	0	13699	0	0	0	445369	0	5650	0	0	0	54830	0	8895343	0	16177	0	8972000	0	93.60	0	20247010	0	200993	8403004	41.807446030459	21630320.0	21124509.0	226935.0	877499.0	46743.0	13699.0	0.0	445369.0	20247010.0	97.7	1.0	4.1	0.2	0.1	0.0	2.1	93.6	101	101	101.00	38	2184662320	25.4	24.6	24.5	25.5	0.0	32.9	15.9	bulk
655564	SRR1056019	SRP034660	SRS517823	SRX396843	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295650: WT Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295650		GSM1295650	WT Control 3	5351954044	26494822	2017-01-03 09:54:06	4005925828	5351954044	26494822	2	26494822	index:0,count:26494822,average:101,stdev:0|index:1,count:26494822,average:101,stdev:0	GSM1295650_r1	GEO			in_mesa	26082520	2.06	2.9	0.03	4455343508	4437645435	4273420695	4272296397	99.6	99.97	25886786	24096943	200.647	637.452	157	231544	84.95	88.61	27589567	21990564	27589567	21990564	85.14	85.38	27589567	22041164	27589567	21187959	474852781	10.66	1.01	0	4.04	0	0.18	0	0.07	0	0.00	0	2.04	0	25886786	0	202	0	199.93	0	1.70	0	0.01	0	1.39	0	0.01	0	227.10	0	0.49	0	266618	0	26494822	0	1070074	0	46822	0	19528	0	0	0	541686	0	6870	0	0	0	67604	0	10992733	0	18875	0	11086082	0	93.67	0	24816712	0	212149	10337258	48.726404555289	26494822.0	25886786.0	266618.0	1070074.0	46822.0	19528.0	0.0	541686.0	24816712.0	97.7	1.0	4.0	0.2	0.1	0.0	2.0	93.7	101	101	101.00	38	2675977022	25.3	24.7	24.6	25.4	0.0	32.9	15.7	bulk
655620	SRR1056020	SRP034660	SRS517823	SRX396843	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295650: WT Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295650		GSM1295650	WT Control 3	5173724394	25612497	2017-01-03 09:54:06	3896233844	5173724394	25612497	2	25612497	index:0,count:25612497,average:101,stdev:0|index:1,count:25612497,average:101,stdev:0	GSM1295650_r2	GEO			in_mesa	26082520	2.09	2.92	0.03	4295063776	4277159166	4118955569	4117263948	99.58	99.96	24989285	23273238	200.132	634.815	158	224577	84.88	88.56	26640529	21211638	26640529	21211638	85.09	85.32	26640529	21263376	26640529	20436937	460379683	10.72	0.98	0	4.05	0	0.18	0	0.07	0	0.00	0	2.19	0	24989285	0	202	0	199.73	0	1.70	0	0.01	0	1.40	0	0.01	0	229.37	0	0.53	0	252086	0	25612497	0	1036902	0	44831	0	18657	0	0	0	559724	0	6403	0	0	0	63804	0	10463742	0	18155	0	10552104	0	93.52	0	23952383	0	210069	9838247	46.833407118613	25612497.0	24989285.0	252086.0	1036902.0	44831.0	18657.0	0.0	559724.0	23952383.0	97.6	1.0	4.0	0.2	0.1	0.0	2.2	93.5	101	101	101.00	38	2586862197	25.3	24.7	24.5	25.5	0.0	32.7	15.6	bulk
655628	SRR1056021	SRP034660	SRS517823	SRX396843	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295650: WT Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295650		GSM1295650	WT Control 3	5234420950	25912975	2017-01-03 09:54:06	3942048279	5234420950	25912975	2	25912975	index:0,count:25912975,average:101,stdev:0|index:1,count:25912975,average:101,stdev:0	GSM1295650_r3	GEO			in_mesa	26082520	2.1	2.91	0.03	4354135475	4335837609	4175145345	4173253426	99.58	99.95	25307398	23567253	200.401	635.295	157	225854	84.85	88.54	26978808	21474410	26978808	21474410	85.08	85.31	26978808	21530890	26978808	20691676	467034915	10.73	1.01	0	4.06	0	0.18	0	0.07	0	0.00	0	2.09	0	25307398	0	202	0	199.87	0	1.70	0	0.01	0	1.39	0	0.01	0	130.47	0	0.53	0	260439	0	25912975	0	1052918	0	45369	0	18915	0	0	0	541293	0	6793	0	0	0	64512	0	10647867	0	18786	0	10737958	0	93.60	0	24254480	0	210589	10006180	47.515207347012	25912975.0	25307398.0	260439.0	1052918.0	45369.0	18915.0	0.0	541293.0	24254480.0	97.7	1.0	4.1	0.2	0.1	0.0	2.1	93.6	101	101	101.00	38	2617210475	25.4	24.7	24.5	25.5	0.0	32.8	15.7	bulk
655637	SRR1056022	SRP034660	SRS517823	SRX396843	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295650: WT Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;Wildtype|source_name;;Podocytes	GEO Accession;;GSM1295650		GSM1295650	WT Control 3	5380795402	26637601	2017-01-03 09:54:06	4026069816	5380795402	26637601	2	26637601	index:0,count:26637601,average:101,stdev:0|index:1,count:26637601,average:101,stdev:0	GSM1295650_r4	GEO			in_mesa	26082520	2.07	2.9	0.03	4482107151	4463758474	4299268929	4297612724	99.59	99.96	26027030	24225989	200.824	638.129	166	231373	84.94	88.6	27737092	22107523	27737092	22107523	85.14	85.37	27737092	22158542	27737092	21301644	478389248	10.67	1.04	0	4.04	0	0.18	0	0.08	0	0.00	0	2.04	0	26027030	0	202	0	199.93	0	1.70	0	0.01	0	1.40	0	0.01	0	242.77	0	0.48	0	276339	0	26637601	0	1075005	0	47258	0	20000	0	0	0	543313	0	7092	0	0	0	67745	0	11056751	0	19518	0	11151106	0	93.67	0	24952025	0	212824	10396303	48.849298011502	26637601.0	26027030.0	276339.0	1075005.0	47258.0	20000.0	0.0	543313.0	24952025.0	97.7	1.0	4.0	0.2	0.1	0.0	2.0	93.7	101	101	101.00	38	2690397701	25.3	24.7	24.5	25.5	0.0	33.1	16.2	bulk
655645	SRR1056023	SRP034660	SRS517824	SRX396844	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295651: KO 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295651		GSM1295651	KO 1	6168610552	30537676	2017-01-03 09:54:06	4630378399	6168610552	30537676	2	30537676	index:0,count:30537676,average:101,stdev:0|index:1,count:30537676,average:101,stdev:0	GSM1295651_r1	GEO			in_mesa	26082520	2.35	2.9	0.03	5113519835	5070800442	4889057896	4867839467	99.16	99.57	29637217	27628980	200.577	631.985	158	268968	83.73	87.63	31708707	24815849	31708707	24815849	83.77	84.07	31708707	24826511	31708707	23808930	564837940	11.05	1.01	0	4.31	0	0.16	0	0.07	0	0.00	0	2.71	0	29637217	0	202	0	199.74	0	1.99	0	0.01	0	1.62	0	0.01	0	219.87	0	0.54	0	308984	0	30537676	0	1316756	0	50124	0	21330	0	0	0	829005	0	7681	0	0	0	74199	0	12290197	0	23857	0	12395934	0	92.74	0	28320461	0	223285	11627641	52.075334214121	30537676.0	29637217.0	308984.0	1316756.0	50124.0	21330.0	0.0	829005.0	28320461.0	97.1	1.0	4.3	0.2	0.1	0.0	2.7	92.7	101	101	101.00	38	3084305276	25.3	24.7	24.5	25.4	0.0	32.7	15.5	bulk
655748	SRR1056030	SRP034660	SRS517825	SRX396845	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295652: KO 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295652		GSM1295652	KO 2	4999938542	24752171	2017-01-03 09:54:06	3744831663	4999938542	24752171	2	24752171	index:0,count:24752171,average:101,stdev:0|index:1,count:24752171,average:101,stdev:0	GSM1295652_r4	GEO			in_mesa	26082520	3.29	2.93	0.03	4227168630	4198484742	4032776194	4022213570	99.32	99.74	24094441	22191690	208.777	706.117	166	204612	86.19	90.39	25788596	20767683	25788596	20767683	86.9	87.19	25788596	20936975	25788596	20032167	359809040	8.51	1.09	0	4.52	0	0.16	0	0.06	0	0.00	0	2.43	0	24094441	0	202	0	199.80	0	1.75	0	0.01	0	1.49	0	0.01	0	238.89	0	0.50	0	270632	0	24752171	0	1119515	0	40181	0	15905	0	0	0	601644	0	6571	0	0	0	65184	0	10552675	0	18409	0	10642839	0	92.82	0	22974926	0	211270	10069950	47.663889809249	24752171.0	24094441.0	270632.0	1119515.0	40181.0	15905.0	0.0	601644.0	22974926.0	97.3	1.1	4.5	0.2	0.1	0.0	2.4	92.8	101	101	101.00	38	2499969271	25.5	24.6	24.3	25.6	0.0	33.1	16.1	bulk
655756	SRR1056031	SRP034660	SRS517826	SRX396846	SRA122184	GEO		The GYF domain protein CD2BP2 plays a crucial role in alternative splicing, embryonic development and podocyte integrity	The spliceosome is a multimolecular ribonucleoprotein complex, which catalyzes the removal of introns from pre-mRNA and extends the complexity of genetic information by defining alternative transcripts. Here we analyzed the in vivo function of CD2BP2, which is a marker of early spliceosomal complexes.   Using gene targeting in mice, we show that constitutive or mesoderm- specific ablation of the CD2BP2 gene causes embryonic lethality by E10.5 associated with delayed development, growth retardation and pericard effusion.   Transcriptome analysis in CD2BP2 deficient bone-marrow-derived macrophages (BMM) and podocytes revealed dramatic alterations in the alternative splicing pattern of several mRNAs including VEGFA. Consistent with a previously described critical role of specific VEGFA isoforms for podocyte integrity, mice, which specifically lack CD2BP2flox/flox in this cell type, develop progressive albuminuria followed by lethal kidney failure. We further identified the phosphatase PP1 as a GYF domain independent CD2BP2 interaction partner, suggesting that CD2BP2 acts as an important modulator for spliceosome dephosphorylation, thereby affecting alternative splicing of  physiologically highly relevant transcripts. Overall design: 3x KO vs 3x WT mus m.		GSM1295653: KO 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab).  Tissue was mixed with 700 μL Qiazol®. Samples were homogenized with 5 2.8 diameter ceramic beads for 20 sec, 5000 rpm in a homogenizer (SeqLab). After 5 min incubation at RT, samples were mixed with 140 μL chloroform, incubated for 3 min at RT and centrifuged at 12 000 x g, 15min at 4°C. Samples were transferred into fresh tubes, mixed with same volume of 70% Ethanol and transferred on RNeasy Mini columns (Qiagen). Columns were centrifuged for 15 sec at 8 000 x g at RT. Flow through was mixed with 350 μL RWI buffer and centrifuged.   For DNA depletion, samples were treated with 70 μL RDD-Buffer with 10 μL DNase and incubated for 15 min at RT. Columns were one time washed with 350 μL RWI-buffer and centrifuged for 20 sec at 8 600 x g at RT and again washed with 700 μL RPE buffer, centrifugation lasted 2 min at 8 600 x g. RNA was eluted by applying 30 μL RNase free water onto the column, one min incubation and centrifugation for one min with full speed at RT. RNA concentration was determined at the Nano Drop (peqlab). RNA quality was estimated (2100 Bioanalyzer, Agilent) and samples with a RIN > 8 were used as input material for the TruSeq RNA Sample Preparation Kit (Illumina). All cDNA fragments were derived from poly(A)+ RNA, subsequently barcoded and sequenced on a HiSeq 2000 instrument (Illumina) with 2 x 100 bp PE chemistry.	Illumina HiSeq 2000	cell type;;Podocytes|genetic background;;C57BL/6|genotype;;CD2BP2 Knockout|source_name;;Podocytes	GEO Accession;;GSM1295653		GSM1295653	KO 3	5479277876	27125138	2017-01-03 09:54:06	4102550703	5479277876	27125138	2	27125138	index:0,count:27125138,average:101,stdev:0|index:1,count:27125138,average:101,stdev:0	GSM1295653_r1	GEO			in_mesa	26082520	2.09	3.0	0.03	4527890239	4495684996	4351265563	4336883227	99.29	99.67	26443372	24623853	199.593	636.547	157	235678	84.01	87.47	28112417	22214892	28112417	22214892	84.04	84.28	28112417	22224030	28112417	21404559	526709157	11.63	1.00	0	3.86	0	0.17	0	0.09	0	0.00	0	2.25	0	26443372	0	202	0	199.92	0	1.65	0	0.01	0	1.41	0	0.01	0	263.21	0	0.49	0	272290	0	27125138	0	1045726	0	47378	0	24442	0	0	0	609946	0	7016	0	0	0	67842	0	11081065	0	20196	0	11176119	0	93.63	0	25397646	0	217047	10360639	47.734541366616	27125138.0	26443372.0	272290.0	1045726.0	47378.0	24442.0	0.0	609946.0	25397646.0	97.5	1.0	3.9	0.2	0.1	0.0	2.2	93.6	101	101	101.00	38	2739638938	25.4	24.7	24.5	25.5	0.0	32.9	15.7	bulk
1384971	SRR1068220	SRP034891	SRS523969	SRX404375	SRA122965	GEO		Deep sequencing of the murine olfactory receptor neuron transcriptome	The recent development of next-generation sequencing (NGS) techniques encouraged us to assess the transcriptome of the murine OE. We analyzed RNA from OEs of female and male adult mice and from fluorescence-activated cell sorting (FACS)-sorted olfactory receptor neurons (ORNs) obtained from transgenic OMP-GFP mice Overall design: The Illumina RNA-Seq protocol was utilized to generate up to 86 million reads per transcriptome.		GSM1300900: CD1 male OE; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Olfactory Epithelia were prepared and pooled from eight individuals for each condition. ORNs were obtained from OMP-GFP mice and enriched by FACS sorting. Subsequently RNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer´s protocol including the optional on-column DNaseI digestion. Libraries for NGS sequencing were prepared from RNA and subjected to DSN normalization by standard Illumina protocols	Illumina Genome Analyzer IIx	gender;;male|genotype/variation;;wildtype|source_name;;Olfactory Epithelium|strain;;CD1|tissue/cell type;;Olfactory Epithelium (OE)	GEO Accession;;GSM1300900		GSM1300900	CD1 male OE	1342258236	37284951	2015-07-22 17:04:40	825976632	1342258236	37284951	1	37284951	index:0,count:37284951,average:36,stdev:0	GSM1300900_r1	GEO					0.57	3.23	0.02	1129105754	935006115	642446702	604641784	82.81	94.12	0	0	0	0	0	0	30.94	54.15	66067506	9886358	66067506	9886358	26.45	35.23	66067506	8451781	66067506	6431733	321728528	28.49	1.90	0	36.72	0	2.37	0	0.33	0	0.00	0	11.61	0	31949043	0	36	0	35.19	0	1.54	0	0.00	0	1.15	0	0.02	0	422.09	0	1.20	0	706656	0	37284951	0	13691794	0	883456	0	122422	0	0	0	4330030	0	124	0	0	0	2256	0	229696	0	4991	0	237067	0	48.97	0	18257249	0	67392	249112	3.696462488129	37284951.0	31949043.0	706656.0	13691794.0	883456.0	122422.0	0.0	4330030.0	18257249.0	85.7	1.9	36.7	2.4	0.3	0.0	11.6	49.0	36	36	36.00	37	1342258236	22.2	28.2	29.1	20.5	0.0	37.0	21.5	bulk
1384987	SRR1068221	SRP034891	SRS523970	SRX404376	SRA122965	GEO		Deep sequencing of the murine olfactory receptor neuron transcriptome	The recent development of next-generation sequencing (NGS) techniques encouraged us to assess the transcriptome of the murine OE. We analyzed RNA from OEs of female and male adult mice and from fluorescence-activated cell sorting (FACS)-sorted olfactory receptor neurons (ORNs) obtained from transgenic OMP-GFP mice Overall design: The Illumina RNA-Seq protocol was utilized to generate up to 86 million reads per transcriptome.		GSM1300901: CD1 female OE; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Olfactory Epithelia were prepared and pooled from eight individuals for each condition. ORNs were obtained from OMP-GFP mice and enriched by FACS sorting. Subsequently RNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer´s protocol including the optional on-column DNaseI digestion. Libraries for NGS sequencing were prepared from RNA and subjected to DSN normalization by standard Illumina protocols	Illumina Genome Analyzer IIx	gender;;female|genotype/variation;;wildtype|source_name;;Olfactory Epithelium|strain;;CD1|tissue/cell type;;Olfactory Epithelium (OE)	GEO Accession;;GSM1300901		GSM1300901	CD1 female OE	1897784316	52716231	2015-07-22 17:04:40	1131557186	1897784316	52716231	1	52716231	index:0,count:52716231,average:36,stdev:0	GSM1300901_r1	GEO					4.07	3.14	0.06	1497809312	1369789231	1110803625	1083673835	91.45	97.56	0	0	0	0	0	0	45.39	61.22	67983181	19179498	67983181	19179498	46.35	53.63	67983181	19581843	67983181	16800975	443383784	29.60	2.58	0	20.72	0	2.07	0	1.24	0	0.00	0	16.54	0	42251073	0	36	0	35.46	0	1.49	0	0.00	0	1.23	0	0.01	0	735.58	0	0.89	0	1361814	0	52716231	0	10923540	0	1092395	0	654768	0	0	0	8717995	0	407	0	0	0	5193	0	599280	0	18045	0	622925	0	59.43	0	31327533	0	108341	662353	6.113595037890	52716231.0	42251073.0	1361814.0	10923540.0	1092395.0	654768.0	0.0	8717995.0	31327533.0	80.1	2.6	20.7	2.1	1.2	0.0	16.5	59.4	36	36	36.00	37	1897784316	25.2	25.2	26.9	22.2	0.5	29.0	10.3	bulk
1385003	SRR1068222	SRP034891	SRS523971	SRX404377	SRA122965	GEO		Deep sequencing of the murine olfactory receptor neuron transcriptome	The recent development of next-generation sequencing (NGS) techniques encouraged us to assess the transcriptome of the murine OE. We analyzed RNA from OEs of female and male adult mice and from fluorescence-activated cell sorting (FACS)-sorted olfactory receptor neurons (ORNs) obtained from transgenic OMP-GFP mice Overall design: The Illumina RNA-Seq protocol was utilized to generate up to 86 million reads per transcriptome.		GSM1300902: C57BL6/J female OE; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Olfactory Epithelia were prepared and pooled from eight individuals for each condition. ORNs were obtained from OMP-GFP mice and enriched by FACS sorting. Subsequently RNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer´s protocol including the optional on-column DNaseI digestion. Libraries for NGS sequencing were prepared from RNA and subjected to DSN normalization by standard Illumina protocols	Illumina HiSeq 2000	gender;;female|genotype/variation;;wildtype|source_name;;Olfactory Epithelium|strain;;C57BL/6J|tissue/cell type;;Olfactory Epithelium (OE)	GEO Accession;;GSM1300902		GSM1300902	C57BL6/J female OE	8726821776	43202088	2015-01-21 16:03:03	5786300821	8726821776	43202088	2	43202088	index:0,count:43202088,average:101,stdev:0|index:1,count:43202088,average:101,stdev:0	GSM1300902_r1	GEO					3.65	9.09	0.03	6495792246	6389957429	5990475487	5938971824	98.37	99.14	41550810	38439469	189.625	663.362	135	409676	85.13	92.44	46467371	35373973	46467371	35373973	87.42	87.97	46467371	36322920	46467371	33664458	332088199	5.11	1.21	0	7.60	0	0.18	0	0.06	0	0.00	0	3.58	0	41550810	0	202	0	199.67	0	2.10	0	0.01	0	1.77	0	0.01	0	190.13	0	0.28	0	521484	0	43202088	0	3283007	0	79091	0	27672	0	0	0	1544515	0	10367	0	0	0	117211	0	21633670	0	41544	0	21802792	0	88.58	0	38267803	0	262250	20679252	78.853201143947	43202088.0	41550810.0	521484.0	3283007.0	79091.0	27672.0	0.0	1544515.0	38267803.0	96.2	1.2	7.6	0.2	0.1	0.0	3.6	88.6	101	101	101.00	38	4363410888	25.1	24.8	24.7	25.3	0.0	35.6	18.7	bulk
1385020	SRR1068223	SRP034891	SRS523972	SRX404378	SRA122965	GEO		Deep sequencing of the murine olfactory receptor neuron transcriptome	The recent development of next-generation sequencing (NGS) techniques encouraged us to assess the transcriptome of the murine OE. We analyzed RNA from OEs of female and male adult mice and from fluorescence-activated cell sorting (FACS)-sorted olfactory receptor neurons (ORNs) obtained from transgenic OMP-GFP mice Overall design: The Illumina RNA-Seq protocol was utilized to generate up to 86 million reads per transcriptome.		GSM1300903: FACS-sorted ORNs (homozygous); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Olfactory Epithelia were prepared and pooled from eight individuals for each condition. ORNs were obtained from OMP-GFP mice and enriched by FACS sorting. Subsequently RNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer´s protocol including the optional on-column DNaseI digestion. Libraries for NGS sequencing were prepared from RNA and subjected to DSN normalization by standard Illumina protocols	Illumina Genome Analyzer IIx	cell type;;FACS-sorted olfactory receptor neurons (ORNs)|genotype/variation;;transgenic OMP-GFP mice, homozygous|source_name;;Olfactory Receptor Neurons|strain;;C57BL/6J|tissue/cell type;;Olfactory Epithelium (OE)	GEO Accession;;GSM1300903		GSM1300903	FACS-sorted ORNs (homozygous)	526827668	7420108	2015-01-21 16:03:03	320567668	526827668	7420108	1	7420108	index:0,count:7420108,average:71,stdev:0	GSM1300903_r1	GEO					1.56	1.7	0.01	445812249	368484437	332441347	305821763	82.65	91.99	0	0	0	0	0	0	35.25	47.2	10008727	2247271	10008727	2247271	24.58	29.0	10008727	1566879	10008727	1380918	134475119	30.16	1.27	0	21.74	0	0.08	0	0.18	0	0.00	0	13.83	0	6374862	0	71	0	69.82	0	4.39	0	0.06	0	2.39	0	0.08	0	261.89	0	1.46	0	94531	0	7420108	0	1613324	0	6225	0	13031	0	0	0	1025990	0	74	0	0	0	803	0	97829	0	1297	0	100003	0	64.17	0	4761538	0	47424	100049	2.109670209177	7420108.0	6374862.0	94531.0	1613324.0	6225.0	13031.0	0.0	1025990.0	4761538.0	85.9	1.3	21.7	0.1	0.2	0.0	13.8	64.2	71	71	71.00	39	526827668	21.4	28.9	28.3	21.3	0.1	32.3	11.8	bulk
1385035	SRR1068224	SRP034891	SRS523972	SRX404378	SRA122965	GEO		Deep sequencing of the murine olfactory receptor neuron transcriptome	The recent development of next-generation sequencing (NGS) techniques encouraged us to assess the transcriptome of the murine OE. We analyzed RNA from OEs of female and male adult mice and from fluorescence-activated cell sorting (FACS)-sorted olfactory receptor neurons (ORNs) obtained from transgenic OMP-GFP mice Overall design: The Illumina RNA-Seq protocol was utilized to generate up to 86 million reads per transcriptome.		GSM1300903: FACS-sorted ORNs (homozygous); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Olfactory Epithelia were prepared and pooled from eight individuals for each condition. ORNs were obtained from OMP-GFP mice and enriched by FACS sorting. Subsequently RNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer´s protocol including the optional on-column DNaseI digestion. Libraries for NGS sequencing were prepared from RNA and subjected to DSN normalization by standard Illumina protocols	Illumina Genome Analyzer IIx	cell type;;FACS-sorted olfactory receptor neurons (ORNs)|genotype/variation;;transgenic OMP-GFP mice, homozygous|source_name;;Olfactory Receptor Neurons|strain;;C57BL/6J|tissue/cell type;;Olfactory Epithelium (OE)	GEO Accession;;GSM1300903		GSM1300903	FACS-sorted ORNs (homozygous)	461555100	6154068	2015-01-21 16:03:03	305977637	461555100	6154068	1	6154068	index:0,count:6154068,average:75,stdev:0	GSM1300903_r2	GEO					1.43	1.7	0.01	398012795	330085803	302476374	276384429	82.93	91.37	0	0	0	0	0	0	35.61	46.78	8278429	1920317	8278429	1920317	24.39	28.35	8278429	1315343	8278429	1163595	117677350	29.57	1.36	0	20.93	0	0.08	0	0.18	0	0.00	0	12.12	0	5392782	0	75	0	73.69	0	4.59	0	0.07	0	2.39	0	0.09	0	280.44	0	1.40	0	83566	0	6154068	0	1287906	0	4708	0	10919	0	0	0	745659	0	59	0	0	0	710	0	86673	0	1993	0	89435	0	66.70	0	4104876	0	44262	88510	1.999683701595	6154068.0	5392782.0	83566.0	1287906.0	4708.0	10919.0	0.0	745659.0	4104876.0	87.6	1.4	20.9	0.1	0.2	0.0	12.1	66.7	75	75	75.00	38	461555100	21.3	28.9	28.5	21.3	0.0	34.1	14.7	bulk
1385051	SRR1068225	SRP034891	SRS523973	SRX404379	SRA122965	GEO		Deep sequencing of the murine olfactory receptor neuron transcriptome	The recent development of next-generation sequencing (NGS) techniques encouraged us to assess the transcriptome of the murine OE. We analyzed RNA from OEs of female and male adult mice and from fluorescence-activated cell sorting (FACS)-sorted olfactory receptor neurons (ORNs) obtained from transgenic OMP-GFP mice Overall design: The Illumina RNA-Seq protocol was utilized to generate up to 86 million reads per transcriptome.		GSM1300904: FACS-sorted ORNs (heterozygous); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Olfactory Epithelia were prepared and pooled from eight individuals for each condition. ORNs were obtained from OMP-GFP mice and enriched by FACS sorting. Subsequently RNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer´s protocol including the optional on-column DNaseI digestion. Libraries for NGS sequencing were prepared from RNA and subjected to DSN normalization by standard Illumina protocols	Illumina HiSeq 2000	cell type;;FACS-sorted olfactory receptor neurons (ORNs)|genotype/variation;;transgenic OMP-GFP mice, heterozygous|source_name;;Olfactory Receptor Neurons|strain;;C57BL/6J|tissue/cell type;;Olfactory Epithelium (OE)	GEO Accession;;GSM1300904		GSM1300904	FACS-sorted ORNs (heterozygous)	5882157786	29119593	2015-01-21 16:03:03	4281914636	5882157786	29119593	2	29119593	index:0,count:29119593,average:101,stdev:0|index:1,count:29119593,average:101,stdev:0	GSM1300904_r1	GEO					2.31	0.84	0.02	3474583730	3206882499	3124132123	2954506128	92.3	94.57	24573167	24387186	146.624	219.900	124	369746	47.7	53.51	29585754	11720680	29585754	11720680	28.02	29.59	29585754	6884549	29585754	6482381	742598248	21.37	1.14	0	9.16	0	0.17	0	0.09	0	0.00	0	15.35	0	24573167	0	202	0	196.03	0	4.26	0	0.06	0	2.74	0	0.10	0	149.12	0	1.14	0	332908	0	29119593	0	2668316	0	48682	0	26882	0	0	0	4470862	0	740	0	0	0	8352	0	1049322	0	20920	0	1079334	0	75.22	0	21904851	0	120846	873488	7.228108501729	29119593.0	24573167.0	332908.0	2668316.0	48682.0	26882.0	0.0	4470862.0	21904851.0	84.4	1.1	9.2	0.2	0.1	0.0	15.4	75.2	101	101	101.00	38	2941078893	22.7	27.4	27.5	22.5	0.0	33.4	20.1	bulk
328135	SRR1177071	SRP038980	SRS561963	SRX476260	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335263: Splenic dendritic cell -IL10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;spleen-purified dendritic cells|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335263		GSM1335263	Splenic dendritic cell -IL10 -LPS replicate 2	4654989360	25861052	2015-07-22 17:07:11	3274167741	4654989360	25861052	2	25861052	index:0,count:25861052,average:90,stdev:0|index:1,count:25861052,average:90,stdev:0	GSM1335263_r1	GEO			in_mesa	25765318	2.49	3.06	0.13	3928001875	3917994403	3678556735	3686088652	99.75	100.2	25575920	24352304	177.829	436.379	146	321298	83.98	89.77	28282010	21478359	28282010	21478359	85.47	85.87	28282010	21860351	28282010	20545302	374872685	9.54	0.98	0	6.38	0	0.29	0	0.10	0	0.00	0	0.72	0	25575920	0	180	0	178.57	0	1.48	0	0.01	0	1.18	0	0.01	0	381.56	0	0.19	0	254671	0	25861052	0	1650976	0	74299	0	25645	0	0	0	185188	0	5528	0	0	0	63376	0	9233418	0	19808	0	9322130	0	92.51	0	23924944	0	187161	8696370	46.464648083735	25861052.0	25575920.0	254671.0	1650976.0	74299.0	25645.0	0.0	185188.0	23924944.0	98.9	1.0	6.4	0.3	0.1	0.0	0.7	92.5	90	90	90.00	38	2327494680	25.1	24.8	25.0	25.2	0.0	35.7	22.7	bulk
328139	SRR1177072	SRP038980	SRS561964	SRX476261	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335264: Splenic dendritic cell -IL10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;spleen-purified dendritic cells|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335264		GSM1335264	Splenic dendritic cell -IL10 +LPS replicate 1	4780771380	26559841	2015-07-22 17:07:11	3349145747	4780771380	26559841	2	26559841	index:0,count:26559841,average:90,stdev:0|index:1,count:26559841,average:90,stdev:0	GSM1335264_r1	GEO			in_mesa	25765318	2.16	2.93	0.13	4028172809	4014221757	3785957636	3791674278	99.65	100.15	26183611	24853779	180.175	449.496	146	307363	83.13	88.55	28780978	21765926	28780978	21765926	84.11	84.52	28780978	22022288	28780978	20775539	418233902	10.38	1.08	0	6.03	0	0.31	0	0.11	0	0.00	0	1.00	0	26183611	0	180	0	178.52	0	1.60	0	0.01	0	1.28	0	0.01	0	294.20	0	0.17	0	287461	0	26559841	0	1602097	0	82369	0	28870	0	0	0	264991	0	4953	0	0	0	61935	0	9085514	0	19155	0	9171557	0	92.55	0	24581514	0	176642	8563472	48.479251820065	26559841.0	26183611.0	287461.0	1602097.0	82369.0	28870.0	0.0	264991.0	24581514.0	98.6	1.1	6.0	0.3	0.1	0.0	1.0	92.6	90	90	90.00	38	2390385690	25.1	24.8	24.9	25.2	0.0	35.8	22.8	bulk
655892	SRR1177042	SRP038980	SRS561934	SRX476231	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335234: Eosinophils -IL-10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived Eosinophils|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335234		GSM1335234	Eosinophils -IL-10 -LPS replicate 1	8976486060	49869367	2015-07-22 17:07:11	6038218602	8976486060	49869367	2	49869367	index:0,count:49869367,average:90,stdev:0|index:1,count:49869367,average:90,stdev:0	GSM1335234_r1	GEO			in_mesa	25765318	3.22	2.96	0.06	8391688886	8356389260	7766894233	7776487278	99.58	100.12	48815839	46361793	209.893	466.363	198	937617	81.4	88.04	54989309	39736730	54989309	39736730	83.84	84.14	54989309	40927293	54989309	37978473	916031841	10.92	1.32	0	7.38	0	0.40	0	0.11	0	0.00	0	1.61	0	48815839	0	180	0	178.54	0	1.82	0	0.00	0	1.23	0	0.00	0	381.17	0	0.12	0	655860	0	49869367	0	3680414	0	198305	0	54153	0	0	0	801070	0	28505	0	0	0	78878	0	15412380	0	27644	0	15547407	0	90.51	0	45135425	0	167721	15643635	93.271772765486	49869367.0	48815839.0	655860.0	3680414.0	198305.0	54153.0	0.0	801070.0	45135425.0	97.9	1.3	7.4	0.4	0.1	0.0	1.6	90.5	90	90	90.00	38	4488243030	24.9	24.2	26.0	24.9	0.0	36.5	26.0	bulk
655900	SRR1177043	SRP038980	SRS561935	SRX476232	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335235: Eosinophils -IL-10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived Eosinophils|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335235		GSM1335235	Eosinophils -IL-10 -LPS replicate 2	8680590540	48225503	2015-07-22 17:07:11	5926015426	8680590540	48225503	2	48225503	index:0,count:48225503,average:90,stdev:0|index:1,count:48225503,average:90,stdev:0	GSM1335235_r1	GEO			in_mesa	25765318	3.49	2.95	0.07	8133313680	8113094927	7535163115	7552801016	99.75	100.23	47297241	43998240	222.885	567.129	209	909472	82.91	89.58	53208427	39214302	53208427	39214302	85.6	85.93	53208427	40485374	53208427	37616099	811962191	9.98	1.41	0	7.30	0	0.40	0	0.11	0	0.00	0	1.42	0	47297241	0	180	0	178.49	0	1.66	0	0.00	0	1.18	0	0.00	0	398.19	0	0.12	0	680903	0	48225503	0	3519788	0	194286	0	51106	0	0	0	682870	0	32343	0	0	0	94443	0	16356747	0	28854	0	16512387	0	90.78	0	43777453	0	180197	16582335	92.023368868516	48225503.0	47297241.0	680903.0	3519788.0	194286.0	51106.0	0.0	682870.0	43777453.0	98.1	1.4	7.3	0.4	0.1	0.0	1.4	90.8	90	90	90.00	38	4340295270	24.8	24.3	26.0	24.9	0.0	36.3	25.6	bulk
655908	SRR1177044	SRP038980	SRS561937	SRX476233	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335236: Eosinophils -IL-10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived Eosinophils|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335236		GSM1335236	Eosinophils -IL-10 +LPS replicate 1	8216054100	45644745	2015-07-22 17:07:11	5593551578	8216054100	45644745	2	45644745	index:0,count:45644745,average:90,stdev:0|index:1,count:45644745,average:90,stdev:0	GSM1335236_r1	GEO			in_mesa	25765318	3.35	3.03	0.06	7717630441	7693287263	7178143960	7191936007	99.68	100.19	44827777	42529111	206.909	465.277	195	795200	83.06	89.38	50097741	37235268	50097741	37235268	85.27	85.59	50097741	38224926	50097741	35654587	756742012	9.81	1.18	0	6.95	0	0.38	0	0.11	0	0.00	0	1.30	0	44827777	0	180	0	178.62	0	1.61	0	0.00	0	1.19	0	0.00	0	329.30	0	0.12	0	539517	0	45644745	0	3170426	0	173592	0	48600	0	0	0	594776	0	28921	0	0	0	80882	0	15389960	0	25412	0	15525175	0	91.26	0	41657351	0	173159	15616389	90.185257480119	45644745.0	44827777.0	539517.0	3170426.0	173592.0	48600.0	0.0	594776.0	41657351.0	98.2	1.2	6.9	0.4	0.1	0.0	1.3	91.3	90	90	90.00	38	4108027050	24.8	24.4	26.1	24.8	0.0	36.4	25.7	bulk
655917	SRR1177045	SRP038980	SRS561936	SRX476234	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335237: Eosinophils -IL-10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived Eosinophils|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335237		GSM1335237	Eosinophils -IL-10 +LPS replicate 2	6451308720	35840604	2015-07-22 17:07:11	4389529318	6451308720	35840604	2	35840604	index:0,count:35840604,average:90,stdev:0|index:1,count:35840604,average:90,stdev:0	GSM1335237_r1	GEO			in_mesa	25765318	3.44	2.98	0.07	6289459881	6272423439	5824620200	5838792321	99.73	100.24	35313522	32983794	230.819	529.740	205	867653	83.09	89.72	39629801	29343388	39629801	29343388	85.67	86.04	39629801	30252001	39629801	28140515	614106890	9.76	1.33	0	7.28	0	0.38	0	0.11	0	0.00	0	0.98	0	35313522	0	180	0	178.68	0	1.65	0	0.00	0	1.21	0	0.00	0	146.45	0	0.12	0	475159	0	35840604	0	2608246	0	136723	0	38459	0	0	0	351900	0	22634	0	0	0	68026	0	11818501	0	19675	0	11928836	0	91.25	0	32705276	0	162779	12262082	75.329630972054	35840604.0	35313522.0	475159.0	2608246.0	136723.0	38459.0	0.0	351900.0	32705276.0	98.5	1.3	7.3	0.4	0.1	0.0	1.0	91.3	90	90	90.00	38	3225654360	24.8	24.3	25.9	24.9	0.0	36.4	25.7	bulk
655924	SRR1177046	SRP038980	SRS561938	SRX476235	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335238: PEC macrophage -IL10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Peritoneal exudate cells (adherent cells)|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335238		GSM1335238	PEC macrophage -IL10 -LPS replicate 1	2400000120	13333334	2015-07-22 17:07:11	1450873676	2400000120	13333334	2	13333334	index:0,count:13333334,average:90,stdev:0|index:1,count:13333334,average:90,stdev:0	GSM1335238_r1	GEO			in_mesa	25765318	3.26	2.5	0.03	2301617529	2329878819	2151331912	2183757747	101.23	101.51	13082901	12056145	211.832	557.444	190	383579	91.52	97.89	14355101	11973161	14355101	11973161	92.6	93.12	14355101	12114589	14355101	11389711	43526348	1.89	1.05	0	6.38	0	0.28	0	0.02	0	0.00	0	1.58	0	13082901	0	180	0	177.36	0	1.60	0	0.00	0	1.34	0	0.00	0	296.30	0	0.64	0	140134	0	13333334	0	851178	0	37290	0	2894	0	0	0	210249	0	8004	0	0	0	32833	0	6052218	0	6264	0	6099319	0	91.74	0	12231723	0	132401	6212117	46.918958316025	13333334.0	13082901.0	140134.0	851178.0	37290.0	2894.0	0.0	210249.0	12231723.0	98.1	1.1	6.4	0.3	0.0	0.0	1.6	91.7	90	90	90.00	37	1200000060	23.8	25.3	27.0	24.0	0.0	32.8	14.5	bulk
655933	SRR1177047	SRP038980	SRS561940	SRX476236	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335239: PEC macrophage -IL10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Peritoneal exudate cells (adherent cells)|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335239		GSM1335239	PEC macrophage -IL10 -LPS replicate 2	4297953648	23911641	2015-03-25 16:42:21	2964061714	4297953648	23911641	2	23911641	index:0,count:23911641,average:89.87,stdev:2.20|index:1,count:23911641,average:89.87,stdev:2.20	GSM1335239_r1	GEO			in_mesa	25765318	3.97	2.8	0.07	4179649106	4200270886	3913081400	3948757540	100.49	100.91	23663320	22358728	203.636	454.782	190	691244	88.05	94.06	25956820	20836237	25956820	20836237	89.48	89.99	25956820	21174600	25956820	19934962	229494742	5.49	0.51	0	6.32	0	0.23	0	0.05	0	0.00	0	0.77	0	23663374	0	179	0	178.42	0	1.61	0	0.00	0	1.22	0	0.00	0	137.95	0	0.26	0	122113	0	23911641	0	1512078	0	53817	0	11100	0	0	0	183350	0	7990	0	0	0	51578	0	9053777	0	13669	0	9127014	0	92.64	0	22151296	0	159580	9299278	58.273455320216	23911641.0	23663374.0	122113.0	1512078.0	53817.0	11100.0	0.0	183350.0	22151296.0	99.0	0.5	6.3	0.2	0.0	0.0	0.8	92.6	30	90	89.87	38	2148974383	24.6	24.5	25.6	25.2	0.0	35.7	19.8	bulk
655940	SRR1177048	SRP038980	SRS561939	SRX476237	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335240: PEC macrophage -IL10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Peritoneal exudate cells (adherent cells)|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335240		GSM1335240	PEC macrophage -IL10 +LPS replicate 1	1238000040	6877778	2015-07-22 17:07:11	740250251	1238000040	6877778	2	6877778	index:0,count:6877778,average:90,stdev:0|index:1,count:6877778,average:90,stdev:0	GSM1335240_r1	GEO			in_mesa	25765318	2.58	2.82	0.06	1194944045	1195841328	1123561379	1129296137	100.08	100.51	6748039	6161104	221.767	632.117	198	221480	87.74	93.3	7381464	5920573	7381464	5920573	89.03	89.62	7381464	6007791	7381464	5687210	70630201	5.91	1.09	0	5.85	0	0.25	0	0.07	0	0.00	0	1.56	0	6748039	0	180	0	177.79	0	1.79	0	0.00	0	1.30	0	0.00	0	266.24	0	0.49	0	75222	0	6877778	0	402043	0	17336	0	4879	0	0	0	107524	0	2793	0	0	0	17919	0	2763227	0	4231	0	2788170	0	92.27	0	6345996	0	120666	2863717	23.732592445262	6877778.0	6748039.0	75222.0	402043.0	17336.0	4879.0	0.0	107524.0	6345996.0	98.1	1.1	5.8	0.3	0.1	0.0	1.6	92.3	90	90	90.00	38	619000020	24.5	24.7	25.7	25.1	0.0	34.5	16.2	bulk
655948	SRR1177049	SRP038980	SRS561941	SRX476238	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335241: PEC macrophage -IL10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Peritoneal exudate cells (adherent cells)|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335241		GSM1335241	PEC macrophage -IL10 +LPS replicate 2	4320728128	24011045	2015-03-25 16:42:21	2973709119	4320728128	24011045	2	24011045	index:0,count:24011045,average:89.97,stdev:0.96|index:1,count:24011045,average:89.97,stdev:0.96	GSM1335241_r1	GEO			in_mesa	25765318	3.56	2.3	0.1	4172840877	4157496418	3924213884	3930642407	99.63	100.16	23761660	22694246	197.157	407.567	184	637782	87.52	93.07	25931951	20796022	25931951	20796022	89.12	89.79	25931951	21176924	25931951	20063367	256446304	6.15	0.51	0	5.90	0	0.20	0	0.08	0	0.00	0	0.76	0	23761704	0	179	0	178.67	0	1.57	0	0.00	0	1.22	0	0.00	0	338.98	0	0.25	0	121262	0	24011045	0	1416055	0	48556	0	18294	0	0	0	182491	0	6827	0	0	0	45634	0	8556381	0	14458	0	8623300	0	93.06	0	22345649	0	151416	8927304	58.958789031542	24011045.0	23761704.0	121262.0	1416055.0	48556.0	18294.0	0.0	182491.0	22345649.0	99.0	0.5	5.9	0.2	0.1	0.0	0.8	93.1	30	90	89.97	38	2160358910	25.0	24.1	25.5	25.4	0.0	35.7	19.9	bulk
656004	SRR1177050	SRP038980	SRS561942	SRX476239	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335242: PEC macrophage +IL10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Peritoneal exudate cells (adherent cells)|strain;;C57Bl6cJ|treatment;;IL10	GEO Accession;;GSM1335242		GSM1335242	PEC macrophage +IL10 -LPS replicate 1	2400000120	13333334	2015-07-22 17:07:11	1572403190	2400000120	13333334	2	13333334	index:0,count:13333334,average:90,stdev:0|index:1,count:13333334,average:90,stdev:0	GSM1335242_r1	GEO			in_mesa	25765318	2.92	2.51	0.04	2277196669	2300097790	2137687466	2166134788	101.01	101.33	13149589	12235150	202.478	515.122	184	376653	91.67	97.64	14363033	12054253	14363033	12054253	92.5	93.04	14363033	12162757	14363033	11486228	47539022	2.09	0.93	0	6.03	0	0.26	0	0.02	0	0.00	0	1.10	0	13149589	0	180	0	176.96	0	1.59	0	0.00	0	1.27	0	0.00	0	266.67	0	0.85	0	123997	0	13333334	0	803709	0	34787	0	2469	0	0	0	146489	0	7108	0	0	0	32202	0	5935213	0	6398	0	5980921	0	92.59	0	12345880	0	131906	6074222	46.049626248995	13333334.0	13149589.0	123997.0	803709.0	34787.0	2469.0	0.0	146489.0	12345880.0	98.6	0.9	6.0	0.3	0.0	0.0	1.1	92.6	90	90	90.00	37	1200000060	23.8	25.4	26.8	24.0	0.0	31.0	13.3	bulk
656012	SRR1177051	SRP038980	SRS561943	SRX476240	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335243: PEC macrophage +IL10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Peritoneal exudate cells (adherent cells)|strain;;C57Bl6cJ|treatment;;IL10	GEO Accession;;GSM1335243		GSM1335243	PEC macrophage +IL10 -LPS replicate 2	4289942009	23862473	2015-03-25 16:42:21	2954123668	4289942009	23862473	2	23862473	index:0,count:23862473,average:89.89,stdev:2.05|index:1,count:23862473,average:89.89,stdev:2.05	GSM1335243_r1	GEO			in_mesa	25765318	3.59	2.7	0.07	4167506824	4188355745	3909754620	3944324197	100.5	100.88	23624263	22173765	206.647	479.776	184	547659	88.51	94.35	25846359	20909413	25846359	20909413	89.87	90.38	25846359	21230068	25846359	20028569	219697034	5.27	0.50	0	6.13	0	0.22	0	0.05	0	0.00	0	0.73	0	23624317	0	179	0	178.41	0	1.63	0	0.00	0	1.23	0	0.00	0	284.45	0	0.27	0	119761	0	23862473	0	1463251	0	52764	0	10786	0	0	0	174606	0	9355	0	0	0	55050	0	9485277	0	13964	0	9563646	0	92.87	0	22161066	0	160335	9768858	60.927794929367	23862473.0	23624317.0	119761.0	1463251.0	52764.0	10786.0	0.0	174606.0	22161066.0	99.0	0.5	6.1	0.2	0.0	0.0	0.7	92.9	30	90	89.89	38	2144967993	24.5	24.6	25.7	25.2	0.0	35.7	19.7	bulk
656020	SRR1177052	SRP038980	SRS561944	SRX476241	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335244: PEC macrophage +IL10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Peritoneal exudate cells (adherent cells)|strain;;C57Bl6cJ|treatment;;IL10, LPS	GEO Accession;;GSM1335244		GSM1335244	PEC macrophage +IL10 +LPS replicate 1	1238000040	6877778	2015-07-22 17:07:11	776528235	1238000040	6877778	2	6877778	index:0,count:6877778,average:90,stdev:0|index:1,count:6877778,average:90,stdev:0	GSM1335244_r1	GEO			in_mesa	25765318	2.18	2.88	0.07	1197347441	1194539570	1127974864	1130444154	99.77	100.22	6746485	5966910	240.678	757.833	211	204068	88.73	94.16	7372699	5985990	7372699	5985990	90.22	90.87	7372699	6086547	7372699	5776867	62797961	5.24	0.70	0	5.66	0	0.26	0	0.07	0	0.00	0	1.58	0	6746485	0	180	0	177.57	0	1.55	0	0.00	0	1.23	0	0.00	0	330.13	0	0.62	0	48232	0	6877778	0	388986	0	17800	0	5143	0	0	0	108350	0	3612	0	0	0	17912	0	2886655	0	3610	0	2911789	0	92.44	0	6357499	0	120742	2998554	24.834390684269	6877778.0	6746485.0	48232.0	388986.0	17800.0	5143.0	0.0	108350.0	6357499.0	98.1	0.7	5.7	0.3	0.1	0.0	1.6	92.4	90	90	90.00	38	619000020	24.4	24.7	25.8	25.1	0.0	34.9	17.1	bulk
656028	SRR1177053	SRP038980	SRS561945	SRX476242	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335245: PEC macrophage +IL10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Peritoneal exudate cells (adherent cells)|strain;;C57Bl6cJ|treatment;;IL10, LPS	GEO Accession;;GSM1335245		GSM1335245	PEC macrophage +IL10 +LPS replicate 2	4583825100	25465695	2015-07-22 17:07:11	3088984894	4583825100	25465695	2	25465695	index:0,count:25465695,average:90,stdev:0|index:1,count:25465695,average:90,stdev:0	GSM1335245_r1	GEO			in_mesa	25765318	2.89	2.53	0.09	4504828451	4485949727	4231279888	4238397325	99.58	100.17	25247953	23546808	215.924	509.422	198	849073	87.9	93.57	27659191	22192089	27659191	22192089	89.48	90.21	27659191	22592964	27659191	21394502	255371700	5.67	0.48	0	6.01	0	0.22	0	0.08	0	0.00	0	0.55	0	25247953	0	180	0	178.92	0	1.69	0	0.00	0	1.20	0	0.00	0	295.73	0	0.16	0	122920	0	25465695	0	1530979	0	57142	0	20734	0	0	0	139866	0	9309	0	0	0	50552	0	10028431	0	16021	0	10104313	0	93.13	0	23716974	0	155714	10453732	67.134181897581	25465695.0	25247953.0	122920.0	1530979.0	57142.0	20734.0	0.0	139866.0	23716974.0	99.1	0.5	6.0	0.2	0.1	0.0	0.5	93.1	90	90	90.00	38	2291912550	24.9	24.2	25.3	25.6	0.0	36.4	23.4	bulk
656036	SRR1177054	SRP038980	SRS561946	SRX476243	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335246: Mast cell -IL10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived mast cell|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335246		GSM1335246	Mast cell -IL10 -LPS replicate 1	5259898980	29221661	2015-07-22 17:07:11	3546906412	5259898980	29221661	2	29221661	index:0,count:29221661,average:90,stdev:0|index:1,count:29221661,average:90,stdev:0	GSM1335246_r1	GEO			in_mesa	25765318	1.89	2.66	0.09	4947823308	4847823328	4760863489	4688804042	97.98	98.49	28625563	26241964	225.957	699.380	212	525378	79.04	82.22	30659299	22625601	30659299	22625601	78.8	79.15	30659299	22557263	30659299	21781926	809364446	16.36	1.46	0	3.78	0	0.34	0	0.20	0	0.00	0	1.50	0	28625563	0	180	0	178.59	0	1.47	0	0.00	0	1.16	0	0.00	0	339.35	0	0.12	0	426291	0	29221661	0	1106036	0	100746	0	58147	0	0	0	437205	0	8502	0	0	0	74053	0	9777712	0	18660	0	9878927	0	94.18	0	27519527	0	187999	9776107	52.000845749180	29221661.0	28625563.0	426291.0	1106036.0	100746.0	58147.0	0.0	437205.0	27519527.0	98.0	1.5	3.8	0.3	0.2	0.0	1.5	94.2	90	90	90.00	38	2629949490	25.0	24.2	25.7	25.0	0.0	36.5	25.8	bulk
656044	SRR1177055	SRP038980	SRS561947	SRX476244	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335247: Mast cell -IL10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived mast cell|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335247		GSM1335247	Mast cell -IL10 -LPS replicate 2	6011596440	33397758	2015-07-22 17:07:11	4273371204	6011596440	33397758	2	33397758	index:0,count:33397758,average:90,stdev:0|index:1,count:33397758,average:90,stdev:0	GSM1335247_r1	GEO			in_mesa	25765318	3.4	2.76	0.11	5000115066	4977141077	4665181394	4668266228	99.54	100.07	32990864	31204570	176.535	458.007	136	357779	82.56	88.59	36740181	27236895	36740181	27236895	84.38	84.81	36740181	27836652	36740181	26073650	543041569	10.86	0.78	0	6.72	0	0.46	0	0.13	0	0.00	0	0.63	0	32990864	0	180	0	178.77	0	1.40	0	0.00	0	1.14	0	0.01	0	440.41	0	0.18	0	259393	0	33397758	0	2245573	0	153405	0	42246	0	0	0	211243	0	7894	0	0	0	90258	0	12228905	0	22925	0	12349982	0	92.06	0	30745291	0	188012	11369917	60.474421845414	33397758.0	32990864.0	259393.0	2245573.0	153405.0	42246.0	0.0	211243.0	30745291.0	98.8	0.8	6.7	0.5	0.1	0.0	0.6	92.1	90	90	90.00	38	3005798220	25.4	24.5	24.5	25.6	0.0	35.8	23.2	bulk
656053	SRR1177056	SRP038980	SRS561948	SRX476245	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335248: Mast cell -IL10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived mast cell|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335248		GSM1335248	Mast cell -IL10 +LPS replicate 1	6024723660	33470687	2015-07-22 17:07:11	4144975185	6024723660	33470687	2	33470687	index:0,count:33470687,average:90,stdev:0|index:1,count:33470687,average:90,stdev:0	GSM1335248_r1	GEO			in_mesa	25765318	4.7	2.45	0.17	5640931390	5519156413	5281999823	5204104884	97.84	98.53	32808613	30345729	217.242	630.937	205	625115	79.42	84.88	36257756	26058014	36257756	26058014	81.25	81.65	36257756	26657908	36257756	25066524	748241112	13.26	1.24	0	6.30	0	0.37	0	0.17	0	0.00	0	1.44	0	32808613	0	180	0	178.56	0	1.58	0	0.00	0	1.18	0	0.00	0	352.32	0	0.12	0	414742	0	33470687	0	2107912	0	124264	0	55605	0	0	0	482205	0	11981	0	0	0	90968	0	10976858	0	19775	0	11099582	0	91.72	0	30700701	0	178717	10965378	61.356099307844	33470687.0	32808613.0	414742.0	2107912.0	124264.0	55605.0	0.0	482205.0	30700701.0	98.0	1.2	6.3	0.4	0.2	0.0	1.4	91.7	90	90	90.00	38	3012361830	25.2	23.9	25.4	25.3	0.2	36.2	24.3	bulk
656061	SRR1177057	SRP038980	SRS561949	SRX476246	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335249: Mast cell -IL10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived mast cell|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335249		GSM1335249	Mast cell -IL10 +LPS replicate 2	5752032840	31955738	2015-07-22 17:07:11	4119476623	5752032840	31955738	2	31955738	index:0,count:31955738,average:90,stdev:0|index:1,count:31955738,average:90,stdev:0	GSM1335249_r1	GEO			in_mesa	25765318	3.31	2.9	0.12	4804143568	4788018812	4481563595	4488670440	99.66	100.16	31574484	29846993	176.854	451.333	136	346198	83.95	90.09	35206377	26506625	35206377	26506625	85.85	86.32	35206377	27105166	35206377	25397939	449524182	9.36	0.88	0	6.74	0	0.46	0	0.10	0	0.00	0	0.64	0	31574484	0	180	0	178.68	0	1.42	0	0.00	0	1.15	0	0.01	0	310.08	0	0.19	0	281178	0	31955738	0	2152504	0	145557	0	31484	0	0	0	204213	0	7402	0	0	0	90179	0	12137807	0	21758	0	12257146	0	92.07	0	29421980	0	178823	11322717	63.318012783590	31955738.0	31574484.0	281178.0	2152504.0	145557.0	31484.0	0.0	204213.0	29421980.0	98.8	0.9	6.7	0.5	0.1	0.0	0.6	92.1	90	90	90.00	38	2876016420	25.4	24.6	24.6	25.5	0.0	35.6	22.9	bulk
656069	SRR1177058	SRP038980	SRS561950	SRX476247	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335250: Mast cell +IL10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived mast cell|strain;;C57Bl6cJ|treatment;;IL10	GEO Accession;;GSM1335250		GSM1335250	Mast cell +IL10 -LPS replicate 1	4672570680	25958726	2015-07-22 17:07:11	3149073259	4672570680	25958726	2	25958726	index:0,count:25958726,average:90,stdev:0|index:1,count:25958726,average:90,stdev:0	GSM1335250_r1	GEO			in_mesa	25765318	1.95	2.61	0.12	4370149262	4291500114	4193810523	4140074891	98.2	98.72	25412840	23545498	215.929	635.109	205	490418	79.77	83.21	27326362	20271456	27326362	20271456	79.54	79.93	27326362	20212980	27326362	19472809	679183900	15.54	1.51	0	4.05	0	0.35	0	0.18	0	0.00	0	1.58	0	25412840	0	180	0	178.49	0	1.53	0	0.00	0	1.18	0	0.00	0	150.73	0	0.13	0	392226	0	25958726	0	1050143	0	90221	0	46460	0	0	0	409205	0	7667	0	0	0	64899	0	8746941	0	17953	0	8837460	0	93.85	0	24362697	0	181079	8747169	48.305816798193	25958726.0	25412840.0	392226.0	1050143.0	90221.0	46460.0	0.0	409205.0	24362697.0	97.9	1.5	4.0	0.3	0.2	0.0	1.6	93.9	90	90	90.00	38	2336285340	25.0	24.2	25.8	24.9	0.0	36.5	25.8	bulk
656077	SRR1177059	SRP038980	SRS561951	SRX476248	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335251: Mast cell +IL10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived mast cell|strain;;C57Bl6cJ|treatment;;IL10	GEO Accession;;GSM1335251		GSM1335251	Mast cell +IL10 -LPS replicate 2	5774024880	32077916	2015-07-22 17:07:11	4109478328	5774024880	32077916	2	32077916	index:0,count:32077916,average:90,stdev:0|index:1,count:32077916,average:90,stdev:0	GSM1335251_r1	GEO			in_mesa	25765318	3.14	2.81	0.13	4865910212	4826019468	4524622453	4515763076	99.18	99.8	31694362	29928145	180.189	457.571	145	333740	82.42	88.74	35541062	26121885	35541062	26121885	84.24	84.81	35541062	26698431	35541062	24966928	515486423	10.59	0.77	0	7.04	0	0.48	0	0.11	0	0.00	0	0.61	0	31694362	0	180	0	178.76	0	1.40	0	0.00	0	1.15	0	0.01	0	315.52	0	0.19	0	245556	0	32077916	0	2257394	0	153190	0	35844	0	0	0	194520	0	7628	0	0	0	84701	0	11864619	0	22372	0	11979320	0	91.77	0	29436968	0	184303	11205904	60.801527918699	32077916.0	31694362.0	245556.0	2257394.0	153190.0	35844.0	0.0	194520.0	29436968.0	98.8	0.8	7.0	0.5	0.1	0.0	0.6	91.8	90	90	90.00	38	2887012440	25.4	24.5	24.5	25.6	0.0	35.8	23.2	bulk
656133	SRR1177060	SRP038980	SRS561952	SRX476249	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335252: Mast cell +IL10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived mast cell|strain;;C57Bl6cJ|treatment;;IL10, LPS	GEO Accession;;GSM1335252		GSM1335252	Mast cell +IL10 +LPS replicate 1	7960440960	44224672	2015-07-22 17:07:11	5334137691	7960440960	44224672	2	44224672	index:0,count:44224672,average:90,stdev:0|index:1,count:44224672,average:90,stdev:0	GSM1335252_r1	GEO			in_mesa	25765318	4.57	2.38	0.31	7441988890	7239726362	6906615446	6786810537	97.28	98.27	43363882	40678351	206.204	537.920	194	810788	79.74	85.99	48778793	34576483	48778793	34576483	81.76	82.51	48778793	35453342	48778793	33178934	877385378	11.79	1.20	0	7.13	0	0.42	0	0.13	0	0.00	0	1.39	0	43363882	0	180	0	178.62	0	1.59	0	0.00	0	1.18	0	0.00	0	340.92	0	0.10	0	529985	0	44224672	0	3152367	0	185402	0	59411	0	0	0	615977	0	14094	0	0	0	117781	0	14855053	0	25151	0	15012079	0	90.93	0	40211515	0	188858	14930607	79.057318196740	44224672.0	43363882.0	529985.0	3152367.0	185402.0	59411.0	0.0	615977.0	40211515.0	98.1	1.2	7.1	0.4	0.1	0.0	1.4	90.9	90	90	90.00	38	3980220480	25.1	24.1	25.6	25.2	0.0	36.6	26.2	bulk
656142	SRR1177061	SRP038980	SRS561953	SRX476250	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335253: Mast cell +IL10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow-derived mast cell|strain;;C57Bl6cJ|treatment;;IL10, LPS	GEO Accession;;GSM1335253		GSM1335253	Mast cell +IL10 +LPS replicate 2	6158355480	34213086	2015-07-22 17:07:11	4411937865	6158355480	34213086	2	34213086	index:0,count:34213086,average:90,stdev:0|index:1,count:34213086,average:90,stdev:0	GSM1335253_r1	GEO			in_mesa	25765318	3.0	2.81	0.22	5181583340	5133817444	4809238766	4798789945	99.08	99.78	33825059	31950824	178.870	446.932	145	376820	82.66	89.17	38204744	27960899	38204744	27960899	84.65	85.36	38204744	28631627	38204744	26766134	529814299	10.22	0.77	0	7.21	0	0.51	0	0.10	0	0.00	0	0.52	0	33825059	0	180	0	178.74	0	1.41	0	0.00	0	1.14	0	0.01	0	399.89	0	0.19	0	263328	0	34213086	0	2468142	0	175988	0	32778	0	0	0	179261	0	7872	0	0	0	93366	0	12980565	0	23711	0	13105514	0	91.65	0	31356917	0	182491	12235418	67.046692713613	34213086.0	33825059.0	263328.0	2468142.0	175988.0	32778.0	0.0	179261.0	31356917.0	98.9	0.8	7.2	0.5	0.1	0.0	0.5	91.7	90	90	90.00	38	3079177740	25.4	24.6	24.5	25.5	0.0	35.6	22.9	bulk
656149	SRR1177062	SRP038980	SRS561954	SRX476251	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335254: Neutrophil -IL10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow neutrophil|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335254		GSM1335254	Neutrophil -IL10 -LPS replicate 1	4668852240	25938068	2015-07-22 17:07:11	3007793001	4668852240	25938068	2	25938068	index:0,count:25938068,average:90,stdev:0|index:1,count:25938068,average:90,stdev:0	GSM1335254_r1	GEO			in_mesa	25765318	2.12	2.77	0.1	4574242901	4509140912	4334553327	4294429904	98.58	99.07	25647506	24042155	217.053	520.942	195	789685	83.3	87.9	27946011	21364092	27946011	21364092	84.1	84.49	27946011	21569904	27946011	20535164	487944137	10.67	0.63	0	5.18	0	0.40	0	0.11	0	0.00	0	0.62	0	25647506	0	180	0	178.80	0	1.60	0	0.00	0	1.25	0	0.00	0	253.74	0	0.23	0	164590	0	25938068	0	1342818	0	102999	0	27739	0	0	0	159824	0	15941	0	0	0	50297	0	10594405	0	16664	0	10677307	0	93.70	0	24304688	0	175621	10906167	62.100585920818	25938068.0	25647506.0	164590.0	1342818.0	102999.0	27739.0	0.0	159824.0	24304688.0	98.9	0.6	5.2	0.4	0.1	0.0	0.6	93.7	90	90	90.00	38	2334426120	24.8	24.3	25.8	25.2	0.0	36.9	25.1	bulk
656157	SRR1177063	SRP038980	SRS561955	SRX476252	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335255: Neutrophil -IL10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow neutrophil|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335255		GSM1335255	Neutrophil -IL10 -LPS replicate 2	7192346040	39957478	2015-07-22 17:07:11	4906053847	7192346040	39957478	2	39957478	index:0,count:39957478,average:90,stdev:0|index:1,count:39957478,average:90,stdev:0	GSM1335255_r1	GEO			in_mesa	25765318	2.61	2.9	0.1	6899698824	6832168790	6459059828	6434726724	99.02	99.62	39369828	36553022	222.765	555.851	195	823194	84.86	90.66	43721985	33407797	43721985	33407797	86.7	87.28	43721985	34133516	43721985	32159865	575225748	8.34	1.06	0	6.31	0	0.42	0	0.09	0	0.00	0	0.96	0	39369828	0	180	0	178.68	0	1.59	0	0.00	0	1.22	0	0.00	0	326.92	0	0.11	0	423327	0	39957478	0	2521338	0	167433	0	37674	0	0	0	382543	0	27650	0	0	0	80223	0	16353001	0	22839	0	16483713	0	92.22	0	36848490	0	197755	16691100	84.402922808526	39957478.0	39369828.0	423327.0	2521338.0	167433.0	37674.0	0.0	382543.0	36848490.0	98.5	1.1	6.3	0.4	0.1	0.0	1.0	92.2	90	90	90.00	38	3596173020	24.7	24.6	25.8	24.9	0.0	36.4	25.8	bulk
656165	SRR1177064	SRP038980	SRS561956	SRX476253	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335256: Neutrophil -IL10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow neutrophil|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335256		GSM1335256	Neutrophil -IL10 +LPS replicate 1	4946737680	27481876	2015-07-22 17:07:11	3167289920	4946737680	27481876	2	27481876	index:0,count:27481876,average:90,stdev:0|index:1,count:27481876,average:90,stdev:0	GSM1335256_r1	GEO			in_mesa	25765318	2.7	2.4	0.13	4813624491	4694895112	4524671518	4455618541	97.53	98.47	27131644	25933661	205.200	431.854	195	1103010	81.07	86.25	29825119	21996013	29825119	21996013	82.07	82.87	29825119	22266562	29825119	21135096	548804211	11.40	0.66	0	5.93	0	0.45	0	0.15	0	0.00	0	0.68	0	27131644	0	180	0	178.83	0	1.55	0	0.00	0	1.21	0	0.00	0	321.22	0	0.20	0	180051	0	27481876	0	1628915	0	122575	0	41386	0	0	0	186271	0	12393	0	0	0	51163	0	10118427	0	17402	0	10199385	0	92.80	0	25502729	0	156960	10462492	66.657059123344	27481876.0	27131644.0	180051.0	1628915.0	122575.0	41386.0	0.0	186271.0	25502729.0	98.7	0.7	5.9	0.4	0.2	0.0	0.7	92.8	90	90	90.00	38	2473368840	25.4	23.6	24.8	26.2	0.0	37.0	25.1	bulk
656173	SRR1177065	SRP038980	SRS561957	SRX476254	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335257: Neutrophil -IL10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow neutrophil|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335257		GSM1335257	Neutrophil -IL10 +LPS replicate 2	7491432420	41619069	2015-07-22 17:07:11	5156625887	7491432420	41619069	2	41619069	index:0,count:41619069,average:90,stdev:0|index:1,count:41619069,average:90,stdev:0	GSM1335257_r1	GEO			in_mesa	25765318	2.49	2.65	0.14	7005668097	6938529819	6550669316	6535380349	99.04	99.77	40728579	38327948	212.372	484.622	195	685054	84.99	90.95	45457478	34615244	45457478	34615244	86.46	87.31	45457478	35213324	45457478	33228351	554998414	7.92	1.13	0	6.41	0	0.55	0	0.11	0	0.00	0	1.49	0	40728579	0	180	0	178.54	0	1.75	0	0.00	0	1.36	0	0.00	0	226.33	0	0.13	0	469972	0	41619069	0	2669549	0	228483	0	43742	0	0	0	618265	0	16945	0	0	0	98757	0	16063779	0	28947	0	16208428	0	91.45	0	38059030	0	194134	16241326	83.660389215696	41619069.0	40728579.0	469972.0	2669549.0	228483.0	43742.0	0.0	618265.0	38059030.0	97.9	1.1	6.4	0.5	0.1	0.0	1.5	91.4	90	90	90.00	38	3745716210	24.4	24.8	26.1	24.5	0.2	36.1	24.3	bulk
656181	SRR1177066	SRP038980	SRS561958	SRX476255	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335258: Neutrophil +IL10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow neutrophil|strain;;C57Bl6cJ|treatment;;IL10	GEO Accession;;GSM1335258		GSM1335258	Neutrophil +IL10 -LPS replicate 1	4926256740	27368093	2015-07-22 17:07:11	3040808483	4926256740	27368093	2	27368093	index:0,count:27368093,average:90,stdev:0|index:1,count:27368093,average:90,stdev:0	GSM1335258_r1	GEO			in_mesa	25765318	2.2	2.69	0.11	4799502193	4719795157	4548691395	4498692430	98.34	98.9	27047951	25599797	207.554	480.301	195	900666	82.86	87.43	29460210	22411389	29460210	22411389	83.58	84.03	29460210	22606793	29460210	21539340	527523993	10.99	0.61	0	5.17	0	0.39	0	0.12	0	0.00	0	0.66	0	27047951	0	180	0	178.83	0	1.58	0	0.00	0	1.26	0	0.00	0	155.89	0	0.13	0	166995	0	27368093	0	1414636	0	107096	0	31784	0	0	0	181262	0	16929	0	0	0	53671	0	11248005	0	18968	0	11337573	0	93.66	0	25633315	0	176793	11565319	65.417290277330	27368093.0	27047951.0	166995.0	1414636.0	107096.0	31784.0	0.0	181262.0	25633315.0	98.8	0.6	5.2	0.4	0.1	0.0	0.7	93.7	90	90	90.00	38	2463128370	24.7	24.2	25.6	25.5	0.0	37.2	26.0	bulk
656189	SRR1177067	SRP038980	SRS561959	SRX476256	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335259: Neutrophil +IL10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow neutrophil|strain;;C57Bl6cJ|treatment;;IL10	GEO Accession;;GSM1335259		GSM1335259	Neutrophil +IL10 -LPS replicate 2	8793547200	48853040	2015-07-22 17:07:11	6055258393	8793547200	48853040	2	48853040	index:0,count:48853040,average:90,stdev:0|index:1,count:48853040,average:90,stdev:0	GSM1335259_r1	GEO			in_mesa	25765318	2.36	2.82	0.11	8314338411	8233196544	7801798936	7772079978	99.02	99.62	48013899	44674274	217.757	549.460	195	982574	85.11	90.73	53253805	40862571	53253805	40862571	86.7	87.34	53253805	41627948	53253805	39333346	691920866	8.32	1.05	0	6.10	0	0.47	0	0.09	0	0.00	0	1.16	0	48013899	0	180	0	178.57	0	1.58	0	0.00	0	1.22	0	0.00	0	311.83	0	0.12	0	511880	0	48853040	0	2977707	0	229075	0	44767	0	0	0	565299	0	30321	0	0	0	100444	0	20181108	0	28511	0	20340384	0	92.19	0	45036192	0	209906	20436690	97.361152134765	48853040.0	48013899.0	511880.0	2977707.0	229075.0	44767.0	0.0	565299.0	45036192.0	98.3	1.0	6.1	0.5	0.1	0.0	1.2	92.2	90	90	90.00	38	4396773600	24.5	24.7	26.0	24.7	0.2	36.2	24.3	bulk
656197	SRR1177068	SRP038980	SRS561960	SRX476257	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335260: Neutrophil +IL10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow neutrophil|strain;;C57Bl6cJ|treatment;;IL10, LPS	GEO Accession;;GSM1335260		GSM1335260	Neutrophil +IL10 +LPS replicate 1	4946737680	27481876	2015-07-22 17:07:11	3191861740	4946737680	27481876	2	27481876	index:0,count:27481876,average:90,stdev:0|index:1,count:27481876,average:90,stdev:0	GSM1335260_r1	GEO			in_mesa	25765318	2.44	2.48	0.14	4802069607	4692615039	4535447594	4467564007	97.72	98.5	27172442	25898206	204.692	437.427	195	1004432	82.52	87.37	29748756	22421829	29748756	22421829	83.52	84.2	29748756	22693337	29748756	21607000	506575521	10.55	0.61	0	5.50	0	0.44	0	0.12	0	0.00	0	0.56	0	27172442	0	180	0	178.83	0	1.58	0	0.00	0	1.21	0	0.00	0	309.17	0	0.20	0	166549	0	27481876	0	1510716	0	121535	0	32652	0	0	0	155247	0	13325	0	0	0	55496	0	10807264	0	18408	0	10894493	0	93.38	0	25661726	0	172553	11117410	64.428958059263	27481876.0	27172442.0	166549.0	1510716.0	121535.0	32652.0	0.0	155247.0	25661726.0	98.9	0.6	5.5	0.4	0.1	0.0	0.6	93.4	90	90	90.00	38	2473368840	24.9	24.1	25.6	25.3	0.0	36.8	25.1	bulk
656205	SRR1177069	SRP038980	SRS561961	SRX476258	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335261: Neutrophil +IL10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;Bone marrow neutrophil|strain;;C57Bl6cJ|treatment;;IL10, LPS	GEO Accession;;GSM1335261		GSM1335261	Neutrophil +IL10 +LPS replicate 2	8018563320	44547574	2015-07-22 17:07:11	5530962877	8018563320	44547574	2	44547574	index:0,count:44547574,average:90,stdev:0|index:1,count:44547574,average:90,stdev:0	GSM1335261_r1	GEO			in_mesa	25765318	2.73	2.69	0.14	7485691467	7396209746	6979968050	6945109325	98.8	99.5	43621163	40303093	224.932	583.027	198	709312	84.98	91.19	48839392	37067450	48839392	37067450	87.1	87.93	48839392	37995129	48839392	35742713	576531341	7.70	1.21	0	6.67	0	0.51	0	0.10	0	0.00	0	1.47	0	43621163	0	180	0	178.44	0	1.60	0	0.00	0	1.22	0	0.00	0	432.27	0	0.13	0	536949	0	44547574	0	2972586	0	227028	0	44093	0	0	0	655290	0	27850	0	0	0	94832	0	17953187	0	25957	0	18101826	0	91.25	0	40648577	0	199858	18088822	90.508370943370	44547574.0	43621163.0	536949.0	2972586.0	227028.0	44093.0	0.0	655290.0	40648577.0	97.9	1.2	6.7	0.5	0.1	0.0	1.5	91.2	90	90	90.00	38	4009281660	24.6	24.7	25.9	24.7	0.2	36.2	24.2	bulk
656260	SRR1177070	SRP038980	SRS561962	SRX476259	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335262: Splenic dendritic cell -IL10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;spleen-purified dendritic cells|strain;;C57Bl6cJ|treatment;;None	GEO Accession;;GSM1335262		GSM1335262	Splenic dendritic cell -IL10 -LPS replicate 1	4883906160	27132812	2015-07-22 17:07:11	3358362660	4883906160	27132812	2	27132812	index:0,count:27132812,average:90,stdev:0|index:1,count:27132812,average:90,stdev:0	GSM1335262_r1	GEO			in_mesa	25765318	2.7	3.11	0.13	4106989340	4095741507	3828824583	3836406273	99.73	100.2	26782286	25508277	178.501	433.144	146	326707	84.36	90.6	29779999	22592666	29779999	22592666	86.09	86.53	29779999	23057957	29779999	21577681	351747968	8.56	1.09	0	6.80	0	0.30	0	0.09	0	0.00	0	0.90	0	26782286	0	180	0	178.49	0	1.51	0	0.01	0	1.21	0	0.01	0	309.11	0	0.18	0	295261	0	27132812	0	1845628	0	81057	0	25128	0	0	0	244341	0	5838	0	0	0	65290	0	9519080	0	21868	0	9612076	0	91.91	0	24936658	0	183539	8955070	48.791101618730	27132812.0	26782286.0	295261.0	1845628.0	81057.0	25128.0	0.0	244341.0	24936658.0	98.7	1.1	6.8	0.3	0.1	0.0	0.9	91.9	90	90	90.00	38	2441953080	25.0	24.9	25.0	25.1	0.0	36.0	23.3	bulk
656284	SRR1177073	SRP038980	SRS561965	SRX476262	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335265: Splenic dendritic cell -IL10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;spleen-purified dendritic cells|strain;;C57Bl6cJ|treatment;;LPS	GEO Accession;;GSM1335265		GSM1335265	Splenic dendritic cell -IL10 +LPS replicate 2	4814626860	26747927	2015-07-22 17:07:14	3382232269	4814626860	26747927	2	26747927	index:0,count:26747927,average:90,stdev:0|index:1,count:26747927,average:90,stdev:0	GSM1335265_r1	GEO			in_mesa	25765318	2.31	2.9	0.1	4069106609	4070660651	3805365385	3827332569	100.04	100.58	26449422	25217307	178.140	418.061	146	327880	85.26	91.27	29245676	22549848	29245676	22549848	86.85	87.36	29245676	22971798	29245676	21582288	333991317	8.21	1.02	0	6.52	0	0.31	0	0.08	0	0.00	0	0.72	0	26449422	0	180	0	178.57	0	1.45	0	0.01	0	1.17	0	0.01	0	413.27	0	0.17	0	273762	0	26747927	0	1743068	0	83796	0	21572	0	0	0	193137	0	5125	0	0	0	61819	0	9053725	0	19612	0	9140281	0	92.37	0	24706354	0	174764	8583559	49.115143851136	26747927.0	26449422.0	273762.0	1743068.0	83796.0	21572.0	0.0	193137.0	24706354.0	98.9	1.0	6.5	0.3	0.1	0.0	0.7	92.4	90	90	90.00	38	2407313430	25.2	24.7	24.8	25.3	0.0	35.7	22.7	bulk
656293	SRR1177074	SRP038980	SRS561966	SRX476263	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335266: Splenic dendritic cell +IL10 -LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;spleen-purified dendritic cells|strain;;C57Bl6cJ|treatment;;IL10	GEO Accession;;GSM1335266		GSM1335266	Splenic dendritic cell +IL10 -LPS replicate 1	4927055400	27372530	2015-07-22 17:07:14	3460579241	4927055400	27372530	2	27372530	index:0,count:27372530,average:90,stdev:0|index:1,count:27372530,average:90,stdev:0	GSM1335266_r1	GEO			in_mesa	25765318	2.85	3.18	0.14	4161069179	4140871484	3875571718	3876529777	99.51	100.02	27089023	25749277	179.140	434.458	146	329228	84.14	90.45	30149150	22793033	30149150	22793033	86.1	86.55	30149150	23324742	30149150	21811872	358830660	8.62	0.84	0	6.90	0	0.30	0	0.09	0	0.00	0	0.64	0	27089023	0	180	0	178.61	0	1.45	0	0.01	0	1.18	0	0.01	0	363.62	0	0.19	0	229348	0	27372530	0	1888682	0	83252	0	24586	0	0	0	175669	0	5850	0	0	0	66424	0	9822972	0	19861	0	9915107	0	92.06	0	25200341	0	185821	9243080	49.741848337917	27372530.0	27089023.0	229348.0	1888682.0	83252.0	24586.0	0.0	175669.0	25200341.0	99.0	0.8	6.9	0.3	0.1	0.0	0.6	92.1	90	90	90.00	38	2463527700	25.4	24.5	24.6	25.4	0.0	35.8	22.8	bulk
656300	SRR1177075	SRP038980	SRS561968	SRX476264	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335267: Splenic dendritic cell +IL10 -LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;spleen-purified dendritic cells|strain;;C57Bl6cJ|treatment;;IL10	GEO Accession;;GSM1335267		GSM1335267	Splenic dendritic cell +IL10 -LPS replicate 2	4940506800	27447260	2015-07-22 17:07:14	3472045748	4940506800	27447260	2	27447260	index:0,count:27447260,average:90,stdev:0|index:1,count:27447260,average:90,stdev:0	GSM1335267_r1	GEO			in_mesa	25765318	2.73	3.01	0.12	4164856133	4157250771	3872164376	3885481687	99.82	100.34	27100920	25850709	178.812	423.451	145	332465	85.14	91.69	30238900	23073080	30238900	23073080	86.98	87.52	30238900	23571698	30238900	22025281	314604093	7.55	1.04	0	7.05	0	0.30	0	0.08	0	0.00	0	0.88	0	27100920	0	180	0	178.52	0	1.47	0	0.01	0	1.22	0	0.01	0	297.62	0	0.19	0	286820	0	27447260	0	1936011	0	81883	0	22346	0	0	0	242111	0	5842	0	0	0	63685	0	9534701	0	21478	0	9625706	0	91.68	0	25164909	0	183679	9000167	48.999433794827	27447260.0	27100920.0	286820.0	1936011.0	81883.0	22346.0	0.0	242111.0	25164909.0	98.7	1.0	7.1	0.3	0.1	0.0	0.9	91.7	90	90	90.00	38	2470253400	25.0	24.8	25.0	25.1	0.0	35.7	22.7	bulk
656308	SRR1177076	SRP038980	SRS561967	SRX476265	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335268: Splenic dendritic cell +IL10 +LPS replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;spleen-purified dendritic cells|strain;;C57Bl6cJ|treatment;;IL10, LPS	GEO Accession;;GSM1335268		GSM1335268	Splenic dendritic cell +IL10 +LPS replicate 1	4682787840	26015488	2015-07-22 17:07:14	3111682395	4682787840	26015488	2	26015488	index:0,count:26015488,average:90,stdev:0|index:1,count:26015488,average:90,stdev:0	GSM1335268_r1	GEO			in_mesa	25765318	2.32	2.95	0.12	3951002859	3947936582	3701766005	3717702716	99.92	100.43	25660954	24440094	178.844	424.988	146	316592	84.54	90.34	28325453	21694633	28325453	21694633	85.87	86.32	28325453	22034948	28325453	20731431	352285833	8.92	1.04	0	6.32	0	0.31	0	0.09	0	0.00	0	0.95	0	25660954	0	180	0	178.54	0	1.50	0	0.01	0	1.22	0	0.01	0	379.17	0	0.15	0	270317	0	26015488	0	1645263	0	81839	0	24419	0	0	0	248276	0	5327	0	0	0	61891	0	9095080	0	19065	0	9181363	0	92.31	0	24015691	0	176460	8595365	48.709990932789	26015488.0	25660954.0	270317.0	1645263.0	81839.0	24419.0	0.0	248276.0	24015691.0	98.6	1.0	6.3	0.3	0.1	0.0	1.0	92.3	90	90	90.00	38	2341393920	25.0	24.9	25.1	25.1	0.0	36.4	24.1	bulk
656316	SRR1177077	SRP038980	SRS561970	SRX476266	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335269: Splenic dendritic cell +IL10 +LPS replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;spleen-purified dendritic cells|strain;;C57Bl6cJ|treatment;;IL10, LPS	GEO Accession;;GSM1335269		GSM1335269	Splenic dendritic cell +IL10 +LPS replicate 2	4610776680	25615426	2015-07-22 17:07:11	2973708387	4610776680	25615426	2	25615426	index:0,count:25615426,average:90,stdev:0|index:1,count:25615426,average:90,stdev:0	GSM1335269_r1	GEO			in_mesa	25765318	2.14	2.88	0.1	3877607521	3883722933	3632100244	3657271490	100.16	100.69	25289811	24090872	178.014	422.873	146	308215	85.59	91.49	27943713	21645954	27943713	21645954	86.96	87.47	27943713	21991025	27943713	20695953	311380017	8.03	1.18	0	6.36	0	0.33	0	0.08	0	0.00	0	0.86	0	25289811	0	180	0	178.49	0	1.46	0	0.01	0	1.19	0	0.01	0	363.05	0	0.14	0	301988	0	25615426	0	1629440	0	83975	0	21625	0	0	0	220015	0	5370	0	0	0	61719	0	8992675	0	19309	0	9079073	0	92.37	0	23660371	0	175839	8477797	48.213405444753	25615426.0	25289811.0	301988.0	1629440.0	83975.0	21625.0	0.0	220015.0	23660371.0	98.7	1.2	6.4	0.3	0.1	0.0	0.9	92.4	90	90	90.00	38	2305388340	24.8	25.1	25.2	24.9	0.0	36.7	25.0	bulk
656324	SRR1177078	SRP038980	SRS561969	SRX476267	SRA142452	GEO		Systematic analysis of the pro and anti-inflammatory activation of mouse myeloid cells	Inflammation is a fundamental physiological process and a key line of defense against pathogen invasion. Inflammation is exquisitely controlled: Too high and inflammation can be dangerous to the organism, but too low and the invading pathogen can escape suppression. Multiple opposing molecules initiate either a pro or anti inflammatory program, of particular interest is the pro-inflammatory bacterial endotoxins and an opposing anti-inflammatory pathway involving IL-10 and STAT3. Much work has been expended in understanding these two pathways in macrophages, key cells in the myeloid system. But other cells of the myeloid system also show a response to endotoxin and IL-10. These myeloid cell types have been less well explored. With the aim to understand similarities and differences amongst myeloid cells we performed RNA-seq analysis on 5 cells from the myeloid system: Macrophages, Neutrophils, splenic dendritic cells, mast cells and eosinophils. We treated the cells with IL-10 or LPS (endotoxin), either separately or in combination. Although the 5 cell types show much similarity in the outcome of the pro inflammatory response, the broad outline of their pro and anti-inflammatory response is highly divergent between the 5 myeloid cell types. Overall design: RNA-seq data from 5 myeloid cell types, treated with IL-10, LPS or both in combination. Samples are in biological duplicate.		GSM1335270: naïve CD4+ T cells anti-CD3/28 treated 24 hours; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			TRIzol RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	source_name;;CD4+ naïve T cells|strain;;C57Bl6cJ|treatment;;anti-CD3, anti-CD28	GEO Accession;;GSM1335270		GSM1335270	naïve CD4+ T cells anti-CD3/28 treated 24 hours	4979924640	27666248	2015-07-22 17:07:11	3205636951	4979924640	27666248	2	27666248	index:0,count:27666248,average:90,stdev:0|index:1,count:27666248,average:90,stdev:0	GSM1335270_r1	GEO			in_mesa	25765318	5.79	3.38	0.25	4814830383	4765407937	4284406569	4281329058	98.97	99.93	27320369	26069889	199.144	479.100	184	782706	81.78	91.89	32357043	22341727	32357043	22341727	87.98	88.31	32357043	24036459	32357043	21471877	330104064	6.86	0.59	0	10.87	0	0.39	0	0.12	0	0.00	0	0.74	0	27320369	0	180	0	178.75	0	1.61	0	0.00	0	1.38	0	0.00	0	309.31	0	0.18	0	164580	0	27666248	0	3006127	0	108638	0	33569	0	0	0	203672	0	12659	0	0	0	63607	0	10236397	0	20090	0	10332753	0	87.88	0	24314242	0	160911	10533744	65.463169081045	27666248.0	27320369.0	164580.0	3006127.0	108638.0	33569.0	0.0	203672.0	24314242.0	98.7	0.6	10.9	0.4	0.1	0.0	0.7	87.9	90	90	90.00	38	2489962320	24.8	24.1	25.5	25.5	0.0	36.8	25.2	bulk
1336664	SRR1181655	SRP039090	SRS564492	SRX478903	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E13.0 Embryo Brain (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;13 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E13.0 Embryo Brain (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Brain		200	E13.0 Embryo Brain (Strain 129S1/SvImJ)		3183994000	15919970	2017-01-20 00:00:00	2012303169	3183994000	15919970	2	15919970	index:0,count:15919970,average:100,stdev:0|index:1,count:15919970,average:100,stdev:0	E13.0 Embryo Brain (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.06	2.87	0.1	3036461751	3057016290	2851670422	2875337179	100.68	100.83	15712599	14195509	251.625	879.220	208	173056	86.33	91.93	17398146	13563984	17398146	13563984	87.53	87.76	17398146	13754013	17398146	12949024	230122692	7.58	0.63	0	6.01	0	0.31	0	0.07	0	0.00	0	0.92	0	15712599	0	200	0	198.41	0	2.65	0	0.01	0	1.98	0	0.01	0	265.33	0	0.29	0	100797	0	15919970	0	957406	0	49181	0	11698	0	0	0	146492	0	6322	0	0	0	54799	0	7606229	0	20648	0	7687998	0	92.68	0	14755193	0	190471	8020654	42.109580986082	15919970.0	15712599.0	100797.0	957406.0	49181.0	11698.0	0.0	146492.0	14755193.0	98.7	0.6	6.0	0.3	0.1	0.0	0.9	92.7	100	100	100.00	38	1591997000	21.5	27.7	26.8	24.0	0.0	36.2	22.1	bulk
1336680	SRR1181656	SRP039090	SRS564493	SRX478904	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E13.0 Embryo Heart (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;13 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E13.0 Embryo Heart (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Heart		200	E13.0 Embryo Heart (Strain 129S1/SvImJ)		4025430200	20127151	2017-01-20 00:00:00	2550905630	4025430200	20127151	2	20127151	index:0,count:20127151,average:100,stdev:0|index:1,count:20127151,average:100,stdev:0	E13.0 Embryo Heart (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.08	1.93	0.06	3886090173	3935290974	3385373525	3431676805	101.27	101.37	19845326	17548748	282.799	881.642	202	173174	82.06	94.22	25503836	16284118	25503836	16284118	90.29	89.76	25503836	17918826	25503836	15513389	202606079	5.21	0.58	0	12.73	0	0.40	0	0.04	0	0.00	0	0.96	0	19845326	0	200	0	198.27	0	2.42	0	0.01	0	2.14	0	0.01	0	227.85	0	0.35	0	115828	0	20127151	0	2561709	0	80786	0	8322	0	0	0	192717	0	6421	0	0	0	62640	0	9992167	0	22427	0	10083655	0	85.87	0	17283617	0	189404	13705244	72.359844565057	20127151.0	19845326.0	115828.0	2561709.0	80786.0	8322.0	0.0	192717.0	17283617.0	98.6	0.6	12.7	0.4	0.0	0.0	1.0	85.9	100	100	100.00	38	2012715100	21.6	27.4	27.7	23.3	0.0	36.1	22.0	bulk
1340426	SRR1181740	SRP039090	SRS564566	SRX478988	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Brain Stem (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Brain Stem (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Brain Stem		202	6 Months Old Adult 2 Brain Stem (Strain 129S1/SvImJ)		2430089492	12030146	2017-01-20 00:00:00	1588700698	2430089492	12030146	2	12030146	index:0,count:12030146,average:101,stdev:0|index:1,count:12030146,average:101,stdev:0	6 Months Old Adult 2 Brain Stem (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.27	2.99	0.02	2258862950	2261021050	2179761827	2186172828	100.1	100.29	11434888	9157012	316.764	1785.851	238	83659	88.41	91.62	12161375	10109947	12161375	10109947	88.34	88.52	12161375	10101170	12161375	9767388	171868121	7.61	0.67	0	3.33	0	0.32	0	0.06	0	0.00	0	4.57	0	11434888	0	202	0	197.82	0	2.43	0	0.01	0	2.43	0	0.01	0	175.34	0	1.29	0	80514	0	12030146	0	400311	0	38394	0	7581	0	0	0	549283	0	2805	0	0	0	39682	0	5448653	0	11658	0	5502798	0	91.72	0	11034577	0	181869	5637840	30.999455652145	12030146.0	11434888.0	80514.0	400311.0	38394.0	7581.0	0.0	549283.0	11034577.0	95.1	0.7	3.3	0.3	0.1	0.0	4.6	91.7	101	101	101.00	38	1215044746	22.3	26.9	26.1	24.8	0.0	31.3	12.7	bulk
1340505	SRR1181745	SRP039090	SRS564567	SRX478993	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Cerebellum (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Cerebellum (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Cerebellum		202	6 Months Old Adult 2 Cerebellum (Strain 129S1/SvImJ)		2608339948	12912574	2017-01-20 00:00:00	1705324746	2608339948	12912574	2	12912574	index:0,count:12912574,average:101,stdev:0|index:1,count:12912574,average:101,stdev:0	6 Months Old Adult 2 Cerebellum (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.18	2.59	0.03	2431188526	2434612622	2356132940	2364313445	100.14	100.35	12305122	10045032	303.190	1727.023	235	102095	87.75	90.54	13006607	10797266	13006607	10797266	87.12	87.3	13006607	10720195	13006607	10410574	217165006	8.93	0.64	0	2.94	0	0.27	0	0.06	0	0.00	0	4.37	0	12305122	0	202	0	197.80	0	2.45	0	0.01	0	2.33	0	0.01	0	90.61	0	1.32	0	82644	0	12912574	0	379829	0	35010	0	7655	0	0	0	564787	0	3217	0	0	0	40529	0	5840635	0	12807	0	5897188	0	92.35	0	11925293	0	187237	6028403	32.196643825740	12912574.0	12305122.0	82644.0	379829.0	35010.0	7655.0	0.0	564787.0	11925293.0	95.3	0.6	2.9	0.3	0.1	0.0	4.4	92.4	101	101	101.00	38	1304169974	22.1	27.0	26.4	24.5	0.0	31.1	12.5	bulk
1340682	SRR1181750	SRP039090	SRS564568	SRX478998	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Colon (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Colon (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Colon		202	6 Months Old Adult 2 Colon (Strain 129S1/SvImJ)		2935339366	14531383	2017-01-20 00:00:00	1883310024	2935339366	14531383	2	14531383	index:0,count:14531383,average:101,stdev:0|index:1,count:14531383,average:101,stdev:0	6 Months Old Adult 2 Colon (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.18	2.06	0.03	2669247454	2681199727	2507417410	2522694306	100.45	100.61	13491107	11197848	307.346	1282.526	232	115587	88.87	94.59	14952308	11989579	14952308	11989579	91.44	91.62	14952308	12336557	14952308	11613190	140854491	5.28	0.52	0	5.61	0	0.26	0	0.05	0	0.00	0	6.86	0	13491107	0	202	0	198.03	0	2.31	0	0.01	0	2.20	0	0.01	0	133.79	0	1.20	0	75525	0	14531383	0	815632	0	37506	0	6598	0	0	0	996172	0	3397	0	0	0	46859	0	7195658	0	13071	0	7258985	0	87.23	0	12675475	0	181889	7813844	42.959409310074	14531383.0	13491107.0	75525.0	815632.0	37506.0	6598.0	0.0	996172.0	12675475.0	92.8	0.5	5.6	0.3	0.0	0.0	6.9	87.2	101	101	101.00	38	1467669683	22.3	26.0	26.8	24.9	0.0	31.4	12.6	bulk
1340712	SRR1181752	SRP039090	SRS564569	SRX479000	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Duodenum (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Duodenum (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Duodenum		202	6 Months Old Adult 2 Duodenum (Strain 129S1/SvImJ)		2862632294	14171447	2017-01-20 00:00:00	1838260136	2862632294	14171447	2	14171447	index:0,count:14171447,average:101,stdev:0|index:1,count:14171447,average:101,stdev:0	6 Months Old Adult 2 Duodenum (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.17	2.09	0.02	2673666015	2729454354	2524795321	2582544382	102.09	102.29	13505030	10848651	321.798	1415.104	232	106970	89.82	95.1	14939906	12129693	14939906	12129693	90.39	90.51	14939906	12206648	14939906	11544222	118323963	4.43	0.55	0	5.30	0	0.38	0	0.07	0	0.00	0	4.25	0	13505030	0	202	0	198.10	0	3.08	0	0.01	0	2.22	0	0.01	0	132.51	0	1.20	0	78516	0	14171447	0	750513	0	54203	0	10261	0	0	0	601953	0	3029	0	0	0	41469	0	7438832	0	12985	0	7496315	0	90.00	0	12754517	0	164060	8106638	49.412641716445	14171447.0	13505030.0	78516.0	750513.0	54203.0	10261.0	0.0	601953.0	12754517.0	95.3	0.6	5.3	0.4	0.1	0.0	4.2	90.0	101	101	101.00	38	1431316147	22.2	26.7	26.2	25.0	0.0	31.8	13.0	bulk
1340728	SRR1181753	SRP039090	SRS564570	SRX479001	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Frontal Lobe (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Frontal Lobe (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Frontal Lobe		202	6 Months Old Adult 2 Frontal Lobe (Strain 129S1/SvImJ)		2659775410	13167205	2017-01-20 00:00:00	1741409328	2659775410	13167205	2	13167205	index:0,count:13167205,average:101,stdev:0|index:1,count:13167205,average:101,stdev:0	6 Months Old Adult 2 Frontal Lobe (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.2	2.66	0.02	2472021621	2478512406	2397397727	2408053163	100.26	100.44	12512474	10270244	303.166	1757.918	234	99932	89.07	91.84	13185628	11144901	13185628	11144901	88.4	88.58	13185628	11061157	13185628	10749496	187626094	7.59	0.62	0	2.87	0	0.23	0	0.05	0	0.00	0	4.69	0	12512474	0	202	0	197.76	0	2.48	0	0.01	0	2.32	0	0.01	0	174.27	0	1.34	0	81539	0	13167205	0	377419	0	30942	0	6227	0	0	0	617562	0	3242	0	0	0	40210	0	5838781	0	13100	0	5895333	0	92.16	0	12135055	0	181677	6011284	33.087754641479	13167205.0	12512474.0	81539.0	377419.0	30942.0	6227.0	0.0	617562.0	12135055.0	95.0	0.6	2.9	0.2	0.0	0.0	4.7	92.2	101	101	101.00	38	1329887705	22.0	27.1	26.6	24.3	0.0	30.9	12.4	bulk
1340776	SRR1181756	SRP039090	SRS564571	SRX479004	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Heart (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Heart (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Heart		202	6 Months Old Adult 2 Heart (Strain 129S1/SvImJ)		2235887904	11068752	2017-01-20 00:00:00	1460574631	2235887904	11068752	2	11068752	index:0,count:11068752,average:101,stdev:0|index:1,count:11068752,average:101,stdev:0	6 Months Old Adult 2 Heart (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	1.71	1.72	0.02	2042870444	2072673701	1915279969	1947806216	101.46	101.7	10372785	8270673	321.026	1309.566	222	63049	89.12	95.05	11511359	9244337	11511359	9244337	89.75	90.18	11511359	9310087	11511359	8771243	66670384	3.26	0.63	0	5.84	0	0.32	0	0.02	0	0.00	0	5.95	0	10372785	0	202	0	197.29	0	2.79	0	0.02	0	2.94	0	0.02	0	144.38	0	1.30	0	70039	0	11068752	0	646535	0	35810	0	1845	0	0	0	658312	0	2647	0	0	0	42169	0	5888477	0	9972	0	5943265	0	87.87	0	9726250	0	153326	6412833	41.824824230724	11068752.0	10372785.0	70039.0	646535.0	35810.0	1845.0	0.0	658312.0	9726250.0	93.7	0.6	5.8	0.3	0.0	0.0	5.9	87.9	101	101	101.00	38	1117943952	21.7	27.3	25.6	25.4	0.0	31.4	12.8	bulk
668351	SRR1181657	SRP039090	SRS564494	SRX478905	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E13.0 Embryo Intestine (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;13 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E13.0 Embryo Intestine (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Intestine		200	E13.0 Embryo Intestine (Strain 129S1/SvImJ)		6567483200	32837416	2017-01-20 00:00:00	4166818077	6567483200	32837416	2	32837416	index:0,count:32837416,average:100,stdev:0|index:1,count:32837416,average:100,stdev:0	E13.0 Embryo Intestine (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.07	3.08	0.11	6363539378	6404110927	5943218822	5991793837	100.64	100.82	32424585	28349129	279.104	1043.420	204	236364	84.66	90.64	36206989	27451503	36206989	27451503	86.5	86.54	36206989	28048702	36206989	26209088	596804168	9.38	0.55	0	6.52	0	0.25	0	0.07	0	0.00	0	0.93	0	32424585	0	200	0	198.43	0	2.55	0	0.01	0	2.07	0	0.01	0	223.05	0	0.31	0	181113	0	32837416	0	2139914	0	82781	0	24369	0	0	0	305681	0	13084	0	0	0	118518	0	16183691	0	41100	0	16356393	0	92.23	0	30284671	0	232420	17226804	74.119284054729	32837416.0	32424585.0	181113.0	2139914.0	82781.0	24369.0	0.0	305681.0	30284671.0	98.7	0.6	6.5	0.3	0.1	0.0	0.9	92.2	100	100	100.00	38	3283741600	21.5	27.6	26.3	24.6	0.0	36.2	22.1	bulk
668358	SRR1181658	SRP039090	SRS564495	SRX478906	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E13.0 Embryo Kidney (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;13 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E13.0 Embryo Kidney (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Kidney		200	E13.0 Embryo Kidney (Strain 129S1/SvImJ)		3639561000	18197805	2017-01-20 00:00:00	2310953724	3639561000	18197805	2	18197805	index:0,count:18197805,average:100,stdev:0|index:1,count:18197805,average:100,stdev:0	E13.0 Embryo Kidney (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.06	2.98	0.13	3510984707	3533723076	3278014927	3306414558	100.65	100.87	17954624	15590333	280.930	1055.898	204	112365	85.54	91.62	20087951	15359020	20087951	15359020	87.64	87.72	20087951	15736116	20087951	14705270	302303536	8.61	0.49	0	6.55	0	0.29	0	0.06	0	0.00	0	0.98	0	17954624	0	200	0	198.51	0	2.45	0	0.01	0	1.94	0	0.01	0	233.14	0	0.30	0	88396	0	18197805	0	1191274	0	53357	0	11276	0	0	0	178548	0	7817	0	0	0	66078	0	9175524	0	23091	0	9272510	0	92.12	0	16763350	0	186340	9776421	52.465498551036	18197805.0	17954624.0	88396.0	1191274.0	53357.0	11276.0	0.0	178548.0	16763350.0	98.7	0.5	6.5	0.3	0.1	0.0	1.0	92.1	100	100	100.00	38	1819780500	21.5	27.4	26.3	24.7	0.0	36.2	22.1	bulk
668366	SRR1181659	SRP039090	SRS564496	SRX478907	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E13.0 Embryo Liver (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;13 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E13.0 Embryo Liver (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Liver		200	E13.0 Embryo Liver (Strain 129S1/SvImJ)		4225364000	21126820	2017-01-20 00:00:00	2686899089	4225364000	21126820	2	21126820	index:0,count:21126820,average:100,stdev:0|index:1,count:21126820,average:100,stdev:0	E13.0 Embryo Liver (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.05	1.71	0.07	4118764900	4162988155	3331816642	3372180857	101.07	101.21	20836849	18350606	314.422	833.074	222	173522	75.83	93.77	29396848	15799705	29396848	15799705	90.66	89.61	29396848	18891240	29396848	15098167	218077031	5.29	0.51	0	18.88	0	0.23	0	0.03	0	0.00	0	1.11	0	20836849	0	200	0	198.28	0	2.27	0	0.03	0	2.25	0	0.01	0	214.24	0	0.37	0	107949	0	21126820	0	3988204	0	48258	0	6247	0	0	0	235466	0	8322	0	0	0	61065	0	9178881	0	19255	0	9267523	0	79.75	0	16848645	0	181408	14962064	82.477421061916	21126820.0	20836849.0	107949.0	3988204.0	48258.0	6247.0	0.0	235466.0	16848645.0	98.6	0.5	18.9	0.2	0.0	0.0	1.1	79.8	100	100	100.00	38	2112682000	22.1	27.1	27.3	23.5	0.0	36.1	22.0	bulk
668422	SRR1181660	SRP039090	SRS564497	SRX478908	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E13.0 Embryo Lung (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;13 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E13.0 Embryo Lung (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Lung		200	E13.0 Embryo Lung (Strain 129S1/SvImJ)		6434531600	32172658	2017-01-20 00:00:00	4104878638	6434531600	32172658	2	32172658	index:0,count:32172658,average:100,stdev:0|index:1,count:32172658,average:100,stdev:0	E13.0 Embryo Lung (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.07	2.94	0.11	6275831141	6320345450	5798189656	5849658646	100.71	100.89	31770728	27069805	297.792	1150.618	212	216564	84.76	91.74	36257304	26929102	36257304	26929102	87.93	87.92	36257304	27936952	36257304	25808413	526002501	8.38	0.54	0	7.51	0	0.26	0	0.06	0	0.00	0	0.93	0	31770728	0	200	0	198.43	0	2.52	0	0.01	0	2.07	0	0.01	0	258.53	0	0.31	0	172163	0	32172658	0	2415863	0	82563	0	19280	0	0	0	300087	0	13242	0	0	0	108936	0	15950653	0	38314	0	16111145	0	91.24	0	29354865	0	224290	17516792	78.098854162022	32172658.0	31770728.0	172163.0	2415863.0	82563.0	19280.0	0.0	300087.0	29354865.0	98.8	0.5	7.5	0.3	0.1	0.0	0.9	91.2	100	100	100.00	38	3217265800	21.7	27.4	26.3	24.6	0.0	36.2	22.0	bulk
668430	SRR1181661	SRP039090	SRS564498	SRX478909	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E13.0 Embryo Stomach (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;13 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E13.0 Embryo Stomach (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Stomach		200	E13.0 Embryo Stomach (Strain 129S1/SvImJ)		5417908600	27089543	2017-01-20 00:00:00	3444996562	5417908600	27089543	2	27089543	index:0,count:27089543,average:100,stdev:0|index:1,count:27089543,average:100,stdev:0	E13.0 Embryo Stomach (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.07	3.07	0.12	5282062924	5319901175	4938910517	4983275715	100.72	100.9	26729730	22803578	297.922	1182.800	213	180694	85.36	91.28	29799941	22816627	29799941	22816627	87.16	87.2	29799941	23298076	29799941	21794945	464539885	8.79	0.54	0	6.40	0	0.24	0	0.07	0	0.00	0	1.02	0	26729730	0	200	0	198.43	0	2.62	0	0.01	0	2.09	0	0.01	0	130.90	0	0.31	0	145261	0	27089543	0	1734769	0	66015	0	18693	0	0	0	275105	0	10788	0	0	0	94619	0	13356846	0	32076	0	13494329	0	92.27	0	24994961	0	218923	14237911	65.036158832101	27089543.0	26729730.0	145261.0	1734769.0	66015.0	18693.0	0.0	275105.0	24994961.0	98.7	0.5	6.4	0.2	0.1	0.0	1.0	92.3	100	100	100.00	38	2708954300	21.7	27.5	26.2	24.6	0.0	36.2	22.1	bulk
668550	SRR1181670	SRP039090	SRS564503	SRX478918	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E19.0 Embryo Brain (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;19 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E19.0 Embryo Brain (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Brain		200	E19.0 Embryo Brain (Strain 129S1/SvImJ)		2708945600	13544728	2017-01-20 00:00:00	1695691125	2708945600	13544728	2	13544728	index:0,count:13544728,average:100,stdev:0|index:1,count:13544728,average:100,stdev:0	E19.0 Embryo Brain (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.08	2.68	0.05	2618529356	2636923922	2496350207	2518584476	100.7	100.89	13259828	11062966	308.931	1647.733	241	126770	85.92	90.13	14286137	11393204	14286137	11393204	85.68	85.9	14286137	11361313	14286137	10858701	237643063	9.08	0.75	0	4.57	0	0.23	0	0.09	0	0.00	0	1.78	0	13259828	0	200	0	198.28	0	3.11	0	0.02	0	2.70	0	0.02	0	275.49	0	0.30	0	102040	0	13544728	0	619467	0	31236	0	12560	0	0	0	241104	0	4758	0	0	0	44266	0	6115736	0	16460	0	6181220	0	93.32	0	12640361	0	190603	6395945	33.556371095943	13544728.0	13259828.0	102040.0	619467.0	31236.0	12560.0	0.0	241104.0	12640361.0	97.9	0.8	4.6	0.2	0.1	0.0	1.8	93.3	100	100	100.00	38	1354472800	22.0	27.3	26.6	24.1	0.0	36.4	22.8	bulk
668557	SRR1181671	SRP039090	SRS564504	SRX478919	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E19.0 Embryo Heart (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;19 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E19.0 Embryo Heart (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Heart		200	E19.0 Embryo Heart (Strain 129S1/SvImJ)		3575871600	17879358	2017-01-20 00:00:00	2229123497	3575871600	17879358	2	17879358	index:0,count:17879358,average:100,stdev:0|index:1,count:17879358,average:100,stdev:0	E19.0 Embryo Heart (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.39	2.13	0.04	3431425132	3495541112	3241097354	3303968354	101.87	101.94	17393423	14289957	320.391	1233.009	231	147905	85.35	90.36	19185090	14845604	19185090	14845604	84.92	85.07	19185090	14771088	19185090	13975732	298414330	8.70	0.78	0	5.40	0	0.42	0	0.05	0	0.00	0	2.25	0	17393423	0	200	0	197.86	0	3.27	0	0.02	0	2.95	0	0.02	0	218.93	0	0.34	0	140330	0	17879358	0	964682	0	74461	0	9480	0	0	0	401994	0	5295	0	0	0	64312	0	9722163	0	21593	0	9813363	0	91.89	0	16428741	0	184602	10462078	56.673698009772	17879358.0	17393423.0	140330.0	964682.0	74461.0	9480.0	0.0	401994.0	16428741.0	97.3	0.8	5.4	0.4	0.1	0.0	2.2	91.9	100	100	100.00	38	1787935800	21.5	27.7	26.0	24.7	0.0	36.5	23.2	bulk
668565	SRR1181672	SRP039090	SRS564505	SRX478920	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E19.0 Embryo Intestine (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;19 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E19.0 Embryo Intestine (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Intestine		200	E19.0 Embryo Intestine (Strain 129S1/SvImJ)		3732589600	18662948	2017-01-20 00:00:00	2336030074	3732589600	18662948	2	18662948	index:0,count:18662948,average:100,stdev:0|index:1,count:18662948,average:100,stdev:0	E19.0 Embryo Intestine (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.18	1.89	0.03	3543343479	3732516023	3373660744	3561870306	105.34	105.58	17937213	15434166	305.261	976.917	222	133031	83.49	87.69	19387184	14976470	19387184	14976470	77.68	77.8	19387184	13932893	19387184	13287045	354724751	10.01	0.79	0	4.60	0	0.17	0	0.04	0	0.00	0	3.68	0	17937213	0	200	0	197.79	0	4.40	0	0.05	0	3.05	0	0.04	0	235.74	0	0.39	0	146670	0	18662948	0	859022	0	30833	0	8112	0	0	0	686790	0	4057	0	0	0	50328	0	7883492	0	16543	0	7954420	0	91.51	0	17078191	0	186190	8321757	44.694972877168	18662948.0	17937213.0	146670.0	859022.0	30833.0	8112.0	0.0	686790.0	17078191.0	96.1	0.8	4.6	0.2	0.0	0.0	3.7	91.5	100	100	100.00	38	1866294800	21.9	27.6	26.2	24.4	0.0	36.4	22.9	bulk
668573	SRR1181673	SRP039090	SRS564506	SRX478921	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E19.0 Embryo Kidney (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;19 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E19.0 Embryo Kidney (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Kidney		200	E19.0 Embryo Kidney (Strain 129S1/SvImJ)		3693547000	18467735	2017-01-20 00:00:00	2314866356	3693547000	18467735	2	18467735	index:0,count:18467735,average:100,stdev:0|index:1,count:18467735,average:100,stdev:0	E19.0 Embryo Kidney (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.14	2.68	0.06	3569423185	3607414704	3351961370	3395360152	101.06	101.29	18030795	15249204	312.291	1174.314	232	144036	82.0	87.31	19963428	14784706	19963428	14784706	82.42	82.33	19963428	14861697	19963428	13942228	425834825	11.93	0.67	0	5.94	0	0.28	0	0.07	0	0.00	0	2.01	0	18030795	0	200	0	198.19	0	3.39	0	0.03	0	2.73	0	0.02	0	251.83	0	0.33	0	124349	0	18467735	0	1096904	0	51394	0	13489	0	0	0	372057	0	6053	0	0	0	59028	0	8272866	0	19929	0	8357876	0	91.69	0	16933891	0	204034	8792760	43.094582275503	18467735.0	18030795.0	124349.0	1096904.0	51394.0	13489.0	0.0	372057.0	16933891.0	97.6	0.7	5.9	0.3	0.1	0.0	2.0	91.7	100	100	100.00	38	1846773500	22.1	27.3	25.9	24.7	0.0	36.4	22.9	bulk
668581	SRR1181674	SRP039090	SRS564507	SRX478922	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E19.0 Embryo Liver (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;19 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E19.0 Embryo Liver (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Liver		200	E19.0 Embryo Liver (Strain 129S1/SvImJ)		3269555000	16347775	2017-01-20 00:00:00	2028323411	3269555000	16347775	2	16347775	index:0,count:16347775,average:100,stdev:0|index:1,count:16347775,average:100,stdev:0	E19.0 Embryo Liver (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.23	1.35	0.02	3168575227	3202005262	2955535735	2988304206	101.06	101.11	16025366	12884332	308.766	993.195	218	136499	86.94	93.2	18301379	13932208	18301379	13932208	88.81	88.91	18301379	14231850	18301379	13290092	182055609	5.75	0.61	0	6.59	0	0.31	0	0.03	0	0.00	0	1.62	0	16025366	0	200	0	198.12	0	2.93	0	0.02	0	3.09	0	0.02	0	234.47	0	0.32	0	99677	0	16347775	0	1076886	0	51428	0	5625	0	0	0	265356	0	3022	0	0	0	50428	0	9844624	0	13055	0	9911129	0	91.44	0	14948480	0	164705	11028928	66.961707294861	16347775.0	16025366.0	99677.0	1076886.0	51428.0	5625.0	0.0	265356.0	14948480.0	98.0	0.6	6.6	0.3	0.0	0.0	1.6	91.4	100	100	100.00	38	1634777500	22.1	27.1	26.1	24.7	0.0	36.5	23.3	bulk
668589	SRR1181675	SRP039090	SRS564508	SRX478923	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E19.0 Embryo Lung (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;19 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E19.0 Embryo Lung (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Lung		200	E19.0 Embryo Lung (Strain 129S1/SvImJ)		3257000200	16285001	2017-01-20 00:00:00	2037382211	3257000200	16285001	2	16285001	index:0,count:16285001,average:100,stdev:0|index:1,count:16285001,average:100,stdev:0	E19.0 Embryo Lung (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.05	2.3	0.04	3174374919	3187196419	2955931965	2973383286	100.4	100.59	16047371	13527926	315.413	1196.756	225	120591	82.77	88.89	18208884	13281965	18208884	13281965	85.74	85.47	18208884	13759633	18208884	12771305	339750161	10.70	0.65	0	6.79	0	0.16	0	0.06	0	0.00	0	1.24	0	16047371	0	200	0	198.31	0	2.54	0	0.02	0	2.63	0	0.01	0	222.91	0	0.31	0	105639	0	16285001	0	1105250	0	26319	0	9396	0	0	0	201915	0	4408	0	0	0	53291	0	7873590	0	17741	0	7949030	0	91.75	0	14942121	0	198286	9060410	45.693644533653	16285001.0	16047371.0	105639.0	1105250.0	26319.0	9396.0	0.0	201915.0	14942121.0	98.5	0.6	6.8	0.2	0.1	0.0	1.2	91.8	100	100	100.00	38	1628500100	22.3	27.1	26.4	24.3	0.0	36.4	22.9	bulk
668596	SRR1181676	SRP039090	SRS564509	SRX478924	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E19.0 Embryo Spleen (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;19 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E19.0 Embryo Spleen (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Spleen		200	E19.0 Embryo Spleen (Strain 129S1/SvImJ)		3236557800	16182789	2017-01-20 00:00:00	2018162572	3236557800	16182789	2	16182789	index:0,count:16182789,average:100,stdev:0|index:1,count:16182789,average:100,stdev:0	E19.0 Embryo Spleen (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.05	2.1	0.06	3150935383	3189075250	2676125382	2714674686	101.21	101.44	15908339	13800571	324.189	910.589	222	120094	77.09	90.76	20753864	12263432	20753864	12263432	87.23	86.29	20753864	13877581	20753864	11659179	258714341	8.21	0.50	0	14.81	0	0.18	0	0.04	0	0.00	0	1.48	0	15908339	0	200	0	198.28	0	2.47	0	0.04	0	2.74	0	0.02	0	242.74	0	0.35	0	80835	0	16182789	0	2396411	0	28476	0	5868	0	0	0	240106	0	6390	0	0	0	45280	0	6719061	0	15283	0	6786014	0	83.50	0	13511928	0	175833	9537003	54.238982443569	16182789.0	15908339.0	80835.0	2396411.0	28476.0	5868.0	0.0	240106.0	13511928.0	98.3	0.5	14.8	0.2	0.0	0.0	1.5	83.5	100	100	100.00	38	1618278900	22.5	26.9	26.3	24.3	0.0	36.5	22.9	bulk
668604	SRR1181677	SRP039090	SRS564510	SRX478925	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		E19.0 Embryo Stomach (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;19 days embryo|biomaterial_provider;;Jackson Laboratory|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;E19.0 Embryo Stomach (Strain 129S1/SvImJ)|sex;;unknown|strain;;129S1/SvImJ|tissue;;Stomach		200	E19.0 Embryo Stomach (Strain 129S1/SvImJ)		2722515800	13612579	2017-01-20 00:00:00	1705429589	2722515800	13612579	2	13612579	index:0,count:13612579,average:100,stdev:0|index:1,count:13612579,average:100,stdev:0	E19.0 Embryo Stomach (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.1	2.26	0.04	2605916383	2658203638	2461854482	2517014890	102.01	102.24	13178761	10965091	315.248	1099.106	231	97929	84.4	89.33	14470398	11122321	14470398	11122321	83.33	83.4	14470398	10982269	14470398	10384670	243528252	9.35	0.72	0	5.34	0	0.47	0	0.10	0	0.00	0	2.62	0	13178761	0	200	0	198.01	0	3.80	0	0.03	0	2.93	0	0.02	0	226.88	0	0.34	0	98593	0	13612579	0	727407	0	63365	0	14160	0	0	0	356293	0	3381	0	0	0	44139	0	6843840	0	14765	0	6906125	0	91.47	0	12451354	0	184974	7206514	38.959605133694	13612579.0	13178761.0	98593.0	727407.0	63365.0	14160.0	0.0	356293.0	12451354.0	96.8	0.7	5.3	0.5	0.1	0.0	2.6	91.5	100	100	100.00	38	1361257900	21.9	27.5	26.3	24.3	0.0	36.4	22.9	bulk
669957	SRR1181720	SRP039090	SRS564551	SRX478968	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		1 Month Old Adult (Strain C57BL/6J) Kidney - RNA-seq	"The general Illumina mRNA-seq library preparation workflow was followed with some modifications. In particular, these libraries do not follow the standard 6bp Illumina barcodes. Instead, custom 3bp barcodes were inserted at the ligated end of the adapters. Hence, during the library amplication step, common forward and reverse primers were used for all libraries, since the barcodes had already been added during ligation."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;1 month|biomaterial_provider;;Gary Peltz (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;1 Month Old Adult (Strain C57BL/6J) Kidney|sex;;male|strain;;C57BL/6J|tissue;;Kidney		194	1 Month Old Adult (Strain C57BL/6J) Kidney		2369846382	12215703	2017-01-20 00:00:00	1490243065	2369846382	12215703	2	12215703	index:0,count:12215703,average:97,stdev:0|index:1,count:12215703,average:97,stdev:0	1 Month Old Adult (Strain C57BL/6J) Kidney - RNA-seq	Stanford University			in_mesa	29022589	1.62	1.98	0.04	1896984562	1918212384	1775497264	1804552172	101.12	101.64	10169940	7981155	300.506	1370.548	208	64495	90.27	96.43	11316849	9180367	11316849	9180367	91.59	92.26	11316849	9314670	11316849	8783367	53459271	2.82	0.39	0	5.32	0	0.38	0	0.05	0	0.00	0	16.32	0	10169940	0	194	0	188.36	0	2.54	0	0.01	0	1.93	0	0.01	0	142.32	0	1.65	0	47300	0	12215703	0	649379	0	45963	0	6011	0	0	0	1993789	0	2681	0	0	0	27048	0	4800427	0	7260	0	4837416	0	77.94	0	9520561	0	151605	5042973	33.263896309488	12215703.0	10169940.0	47300.0	649379.0	45963.0	6011.0	0.0	1993789.0	9520561.0	83.3	0.4	5.3	0.4	0.0	0.0	16.3	77.9	97	97	97.00	38	1184923191	22.7	26.2	26.3	24.8	0.0	23.8	8.6	bulk
669965	SRR1181721	SRP039090	SRS564552	SRX478969	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		1 Month Old Adult (Strain C57BL/6J) Liver - RNA-seq	"The general Illumina mRNA-seq library preparation workflow was followed with some modifications. In particular, these libraries do not follow the standard 6bp Illumina barcodes. Instead, custom 3bp barcodes were inserted at the ligated end of the adapters. Hence, during the library amplication step, common forward and reverse primers were used for all libraries, since the barcodes had already been added during ligation."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;1 month|biomaterial_provider;;Gary Peltz (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;1 Month Old Adult (Strain C57BL/6J) Liver|sex;;male|strain;;C57BL/6J|tissue;;Liver		194	1 Month Old Adult (Strain C57BL/6J) Liver		2989569294	15410151	2017-01-20 00:00:00	1881453001	2989569294	15410151	2	15410151	index:0,count:15410151,average:97,stdev:0|index:1,count:15410151,average:97,stdev:0	1 Month Old Adult (Strain C57BL/6J) Liver - RNA-seq	Stanford University			in_mesa	29022589	1.33	1.21	0.02	2608874068	2647611082	2429892261	2466874344	101.48	101.52	13945722	11055180	288.014	1063.468	192	97657	90.15	96.77	15927201	12572499	15927201	12572499	92.71	93.19	15927201	12928976	15927201	12108001	71491673	2.74	0.45	0	6.19	0	0.74	0	0.75	0	0.00	0	8.01	0	13945722	0	194	0	189.93	0	2.64	0	0.00	0	1.78	0	0.00	0	151.58	0	1.17	0	69058	0	15410151	0	953420	0	114496	0	115034	0	0	0	1234899	0	2609	0	0	0	36049	0	7830750	0	8691	0	7878099	0	84.31	0	12992302	0	138225	8590627	62.149589437511	15410151.0	13945722.0	69058.0	953420.0	114496.0	115034.0	0.0	1234899.0	12992302.0	90.5	0.4	6.2	0.7	0.7	0.0	8.0	84.3	97	97	97.00	38	1494784647	22.4	25.8	26.1	25.7	0.0	31.9	13.2	bulk
669973	SRR1181722	SRP039090	SRS564553	SRX478970	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		1 Month Old Adult 1 (Strain 129S1/SvImJ) Kidney - RNA-seq	"The general Illumina mRNA-seq library preparation workflow was followed with some modifications. In particular, these libraries do not follow the standard 6bp Illumina barcodes. Instead, custom 3bp barcodes were inserted at the ligated end of the adapters. Hence, during the library amplication step, common forward and reverse primers were used for all libraries, since the barcodes had already been added during ligation."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;1 month|biomaterial_provider;;Gary Peltz (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;1 Month Old Adult 1 (Strain 129S1/SvImJ) Kidney|sex;;male|strain;;129S1/SvImJ|tissue;;Kidney		194	1 Month Old Adult 1 (Strain 129S1/SvImJ) Kidney		2169676406	11183899	2017-01-20 00:00:00	1373146403	2169676406	11183899	2	11183899	index:0,count:11183899,average:97,stdev:0|index:1,count:11183899,average:97,stdev:0	1 Month Old Adult 1 (Strain 129S1/SvImJ) Kidney - RNA-seq	Stanford University			in_mesa	29022589	1.57	2.06	0.02	1758468815	1783371807	1644533554	1673397006	101.42	101.76	9404950	7248338	308.046	1453.540	212	56682	90.61	96.85	10440568	8521783	10440568	8521783	92.24	92.7	10440568	8674857	10440568	8156563	45219895	2.57	0.38	0	5.42	0	0.32	0	0.05	0	0.00	0	15.54	0	9404950	0	194	0	188.20	0	2.53	0	0.01	0	1.98	0	0.01	0	146.41	0	1.70	0	42358	0	11183899	0	606212	0	35322	0	5602	0	0	0	1738025	0	2493	0	0	0	25475	0	4519683	0	6986	0	4554637	0	78.67	0	8798738	0	147282	4745242	32.218750424356	11183899.0	9404950.0	42358.0	606212.0	35322.0	5602.0	0.0	1738025.0	8798738.0	84.1	0.4	5.4	0.3	0.1	0.0	15.5	78.7	97	97	97.00	38	1084838203	22.5	26.3	26.0	25.1	0.0	24.0	8.7	bulk
669982	SRR1181723	SRP039090	SRS564554	SRX478971	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		1 Month Old Adult 1 (Strain 129S1/SvImJ) Liver - RNA-seq	"The general Illumina mRNA-seq library preparation workflow was followed with some modifications. In particular, these libraries do not follow the standard 6bp Illumina barcodes. Instead, custom 3bp barcodes were inserted at the ligated end of the adapters. Hence, during the library amplication step, common forward and reverse primers were used for all libraries, since the barcodes had already been added during ligation."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;1 month|biomaterial_provider;;Gary Peltz (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;1 Month Old Adult 1 (Strain 129S1/SvImJ) Liver|sex;;male|strain;;129S1/SvImJ|tissue;;Liver		194	1 Month Old Adult 1 (Strain 129S1/SvImJ) Liver		2854543936	14714144	2017-01-20 00:00:00	1805875547	2854543936	14714144	2	14714144	index:0,count:14714144,average:97,stdev:0|index:1,count:14714144,average:97,stdev:0	1 Month Old Adult 1 (Strain 129S1/SvImJ) Liver - RNA-seq	Stanford University			in_mesa	29022589	0.84	1.26	0.01	2452501147	2495677397	2258758927	2295633580	101.76	101.63	13277091	10538051	279.211	1434.686	185	86881	90.24	97.95	15838799	11980745	15838799	11980745	93.59	94.37	15838799	12426500	15838799	11543052	43859419	1.79	0.46	0	7.10	0	1.17	0	1.49	0	0.00	0	7.11	0	13277091	0	194	0	189.45	0	2.63	0	0.01	0	1.83	0	0.01	0	110.82	0	1.33	0	67367	0	14714144	0	1045231	0	172218	0	218839	0	0	0	1045996	0	2789	0	0	0	37732	0	7455581	0	9336	0	7505438	0	83.13	0	12231860	0	138723	8492253	61.217339590407	14714144.0	13277091.0	67367.0	1045231.0	172218.0	218839.0	0.0	1045996.0	12231860.0	90.2	0.5	7.1	1.2	1.5	0.0	7.1	83.1	97	97	97.00	38	1427271968	21.9	26.3	26.4	25.4	0.0	31.0	12.5	bulk
669990	SRR1181724	SRP039090	SRS564555	SRX478972	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		1 Month Old Adult 1 (Strain 129S1/SvImJ) Lung - RNA-seq	"The general Illumina mRNA-seq library preparation workflow was followed with some modifications. In particular, these libraries do not follow the standard 6bp Illumina barcodes. Instead, custom 3bp barcodes were inserted at the ligated end of the adapters. Hence, during the library amplication step, common forward and reverse primers were used for all libraries, since the barcodes had already been added during ligation."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;1 month|biomaterial_provider;;Gary Peltz (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;1 Month Old Adult 1 (Strain 129S1/SvImJ) Lung|sex;;male|strain;;129S1/SvImJ|tissue;;Lung		194	1 Month Old Adult 1 (Strain 129S1/SvImJ) Lung		2721817284	14029986	2017-01-20 00:00:00	1727046627	2721817284	14029986	2	14029986	index:0,count:14029986,average:97,stdev:0|index:1,count:14029986,average:97,stdev:0	1 Month Old Adult 1 (Strain 129S1/SvImJ) Lung - RNA-seq	Stanford University			in_mesa	29022589	0.3	2.23	0.03	2421386051	2434392669	2300878660	2319860918	100.54	100.83	12875743	10386372	294.869	1245.979	205	84329	90.42	95.16	14040765	11641995	14040765	11641995	91.36	91.74	14040765	11763209	14040765	11223354	98340654	4.06	0.44	0	4.57	0	0.18	0	0.02	0	0.00	0	8.03	0	12875743	0	194	0	189.78	0	2.43	0	0.01	0	1.97	0	0.01	0	95.66	0	1.29	0	62026	0	14029986	0	641308	0	25484	0	2189	0	0	0	1126570	0	3162	0	0	0	34344	0	5830318	0	10827	0	5878651	0	87.20	0	12234435	0	172743	6150291	35.603706083604	14029986.0	12875743.0	62026.0	641308.0	25484.0	2189.0	0.0	1126570.0	12234435.0	91.8	0.4	4.6	0.2	0.0	0.0	8.0	87.2	97	97	97.00	38	1360908642	22.5	26.0	26.3	25.1	0.0	31.5	12.9	bulk
669998	SRR1181725	SRP039090	SRS564556	SRX478973	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		1 Month Old Adult 2 (Strain 129S1/SvImJ) Kidney - RNA-seq	"The general Illumina mRNA-seq library preparation workflow was followed with some modifications. In particular, these libraries do not follow the standard 6bp Illumina barcodes. Instead, custom 3bp barcodes were inserted at the ligated end of the adapters. Hence, during the library amplication step, common forward and reverse primers were used for all libraries, since the barcodes had already been added during ligation."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;1 month|biomaterial_provider;;Gary Peltz (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;1 Month Old Adult 2 (Strain 129S1/SvImJ) Kidney|sex;;male|strain;;129S1/SvImJ|tissue;;Kidney		194	1 Month Old Adult 2 (Strain 129S1/SvImJ) Kidney		2178810896	11230984	2017-01-20 00:00:00	1376814199	2178810896	11230984	2	11230984	index:0,count:11230984,average:97,stdev:0|index:1,count:11230984,average:97,stdev:0	1 Month Old Adult 2 (Strain 129S1/SvImJ) Kidney - RNA-seq	Stanford University			in_mesa	29022589	1.17	1.85	0.02	1805134471	1830520058	1699335264	1725713739	101.41	101.55	9682785	7432371	303.690	1538.444	205	53464	90.92	96.56	10804711	8803717	10804711	8803717	92.48	92.86	10804711	8954601	10804711	8466423	54125401	3.00	0.39	0	5.04	0	0.59	0	0.45	0	0.00	0	12.75	0	9682785	0	194	0	188.32	0	2.42	0	0.01	0	1.92	0	0.01	0	78.05	0	1.65	0	43770	0	11230984	0	565680	0	66464	0	50282	0	0	0	1431453	0	2492	0	0	0	27763	0	4844726	0	7991	0	4882972	0	81.18	0	9117105	0	151096	5170591	34.220568380367	11230984.0	9682785.0	43770.0	565680.0	66464.0	50282.0	0.0	1431453.0	9117105.0	86.2	0.4	5.0	0.6	0.4	0.0	12.7	81.2	97	97	97.00	38	1089405448	22.2	26.5	26.3	25.0	0.0	24.5	8.8	bulk
670006	SRR1181726	SRP039090	SRS564557	SRX478974	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		1 Month Old Adult 2 (Strain 129S1/SvImJ) Liver - RNA-seq	"The general Illumina mRNA-seq library preparation workflow was followed with some modifications. In particular, these libraries do not follow the standard 6bp Illumina barcodes. Instead, custom 3bp barcodes were inserted at the ligated end of the adapters. Hence, during the library amplication step, common forward and reverse primers were used for all libraries, since the barcodes had already been added during ligation."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;1 month|biomaterial_provider;;Gary Peltz (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;1 Month Old Adult 2 (Strain 129S1/SvImJ) Liver|sex;;male|strain;;129S1/SvImJ|tissue;;Liver		194	1 Month Old Adult 2 (Strain 129S1/SvImJ) Liver		2421154338	12480177	2017-01-20 00:00:00	1523905024	2421154338	12480177	2	12480177	index:0,count:12480177,average:97,stdev:0|index:1,count:12480177,average:97,stdev:0	1 Month Old Adult 2 (Strain 129S1/SvImJ) Liver - RNA-seq	Stanford University			in_mesa	29022589	0.75	1.35	0.01	1931493032	1963548137	1779841464	1807692035	101.66	101.56	10349820	7598211	314.290	1757.678	218	57945	89.98	97.61	12375289	9313077	12375289	9313077	93.58	94.29	12375289	9685793	12375289	8996056	41336959	2.14	0.36	0	6.48	0	1.37	0	1.64	0	0.00	0	14.06	0	10349820	0	194	0	188.31	0	2.53	0	0.01	0	1.85	0	0.01	0	119.17	0	1.64	0	45252	0	12480177	0	808803	0	170695	0	205163	0	0	0	1754499	0	2048	0	0	0	27119	0	5514465	0	7895	0	5551527	0	76.45	0	9541017	0	141050	6309097	44.729507266927	12480177.0	10349820.0	45252.0	808803.0	170695.0	205163.0	0.0	1754499.0	9541017.0	82.9	0.4	6.5	1.4	1.6	0.0	14.1	76.4	97	97	97.00	38	1210577169	22.3	26.1	26.4	25.2	0.0	24.5	8.8	bulk
670015	SRR1181727	SRP039090	SRS564558	SRX478975	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		1 Month Old Adult 2 (Strain 129S1/SvImJ) Lung - RNA-seq	"The general Illumina mRNA-seq library preparation workflow was followed with some modifications. In particular, these libraries do not follow the standard 6bp Illumina barcodes. Instead, custom 3bp barcodes were inserted at the ligated end of the adapters. Hence, during the library amplication step, common forward and reverse primers were used for all libraries, since the barcodes had already been added during ligation."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;1 month|biomaterial_provider;;Gary Peltz (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;1 Month Old Adult 2 (Strain 129S1/SvImJ) Lung|sex;;male|strain;;129S1/SvImJ|tissue;;Lung		194	1 Month Old Adult 2 (Strain 129S1/SvImJ) Lung		2428200612	12516498	2017-01-20 00:00:00	1548192601	2428200612	12516498	2	12516498	index:0,count:12516498,average:97,stdev:0|index:1,count:12516498,average:97,stdev:0	1 Month Old Adult 2 (Strain 129S1/SvImJ) Lung - RNA-seq	Stanford University			in_mesa	29022589	0.38	2.22	0.02	2178938064	2198940699	2061165447	2084776949	100.92	101.15	11583074	9279492	300.918	1313.237	213	78844	90.93	96.12	12770099	10532455	12770099	10532455	92.34	92.68	12770099	10695673	12770099	10154969	73872425	3.39	0.44	0	5.00	0	0.27	0	0.08	0	0.00	0	7.11	0	11583074	0	194	0	189.61	0	2.35	0	0.01	0	1.88	0	0.01	0	165.05	0	1.31	0	54498	0	12516498	0	625937	0	33314	0	10466	0	0	0	889644	0	2947	0	0	0	32411	0	5512127	0	9812	0	5557297	0	87.54	0	10957137	0	177154	5873232	33.153256488705	12516498.0	11583074.0	54498.0	625937.0	33314.0	10466.0	0.0	889644.0	10957137.0	92.5	0.4	5.0	0.3	0.1	0.0	7.1	87.5	97	97	97.00	38	1214100306	22.1	26.4	26.5	25.0	0.0	30.7	12.2	bulk
670479	SRR1181761	SRP039090	SRS564572	SRX479009	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Jejunum (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Jejunum (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Jejunum		202	6 Months Old Adult 2 Jejunum (Strain 129S1/SvImJ)		2927027672	14490236	2017-01-20 00:00:00	1877251230	2927027672	14490236	2	14490236	index:0,count:14490236,average:101,stdev:0|index:1,count:14490236,average:101,stdev:0	6 Months Old Adult 2 Jejunum (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.13	1.81	0.02	2731126516	2806992551	2558813564	2636832494	102.78	103.05	13793821	11315852	319.470	1508.900	232	113087	89.47	95.48	15411750	12341739	15411750	12341739	90.32	90.48	15411750	12459037	15411750	11694933	117625757	4.31	0.54	0	5.99	0	0.32	0	0.22	0	0.00	0	4.26	0	13793821	0	202	0	198.14	0	3.24	0	0.02	0	2.23	0	0.01	0	107.56	0	1.21	0	77854	0	14490236	0	868078	0	46415	0	32329	0	0	0	617671	0	2871	0	0	0	40632	0	7258024	0	12666	0	7314193	0	89.20	0	12925743	0	162102	8053539	49.681922493245	14490236.0	13793821.0	77854.0	868078.0	46415.0	32329.0	0.0	617671.0	12925743.0	95.2	0.5	6.0	0.3	0.2	0.0	4.3	89.2	101	101	101.00	38	1463513836	22.1	26.8	26.2	24.9	0.0	31.8	13.0	bulk
670487	SRR1181762	SRP039090	SRS564573	SRX479010	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Kidney (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Kidney (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Kidney		202	6 Months Old Adult 2 Kidney (Strain 129S1/SvImJ)		2361897322	11692561	2017-01-20 00:00:00	1535985164	2361897322	11692561	2	11692561	index:0,count:11692561,average:101,stdev:0|index:1,count:11692561,average:101,stdev:0	6 Months Old Adult 2 Kidney (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.92	1.98	0.07	2192421091	2203269165	2080072882	2095191481	100.49	100.73	11092631	9369280	290.169	1072.584	220	88468	87.45	92.16	12076484	9700505	12076484	9700505	88.23	88.42	12076484	9787470	12076484	9306589	154147698	7.03	0.63	0	4.85	0	0.33	0	0.05	0	0.00	0	4.76	0	11092631	0	202	0	198.06	0	2.40	0	0.01	0	2.36	0	0.01	0	183.81	0	1.23	0	74132	0	11692561	0	567125	0	38338	0	5320	0	0	0	556272	0	2684	0	0	0	30992	0	5387189	0	9890	0	5430755	0	90.02	0	10525506	0	158588	5708519	35.995907634878	11692561.0	11092631.0	74132.0	567125.0	38338.0	5320.0	0.0	556272.0	10525506.0	94.9	0.6	4.9	0.3	0.0	0.0	4.8	90.0	101	101	101.00	38	1180948661	23.3	26.2	25.7	24.9	0.0	31.6	12.9	bulk
670502	SRR1181764	SRP039090	SRS564574	SRX479012	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Liver (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Liver (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Liver		202	6 Months Old Adult 2 Liver (Strain 129S1/SvImJ)		2258810864	11182232	2017-01-20 00:00:00	1470967672	2258810864	11182232	2	11182232	index:0,count:11182232,average:101,stdev:0|index:1,count:11182232,average:101,stdev:0	6 Months Old Adult 2 Liver (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.29	1.13	0.02	2053824000	2078000319	1915898780	1934302045	101.18	100.96	10381441	7847358	330.595	1500.812	232	63672	88.22	94.55	12065585	9158103	12065585	9158103	90.82	91.49	12065585	9428194	12065585	8860872	106068794	5.16	0.55	0	6.22	0	0.86	0	2.12	0	0.00	0	4.18	0	10381441	0	202	0	197.96	0	2.76	0	0.01	0	2.39	0	0.01	0	75.39	0	1.24	0	60944	0	11182232	0	695927	0	96018	0	236918	0	0	0	467855	0	1695	0	0	0	26432	0	5948406	0	7414	0	5983947	0	86.62	0	9685514	0	126664	6721419	53.064951367397	11182232.0	10381441.0	60944.0	695927.0	96018.0	236918.0	0.0	467855.0	9685514.0	92.8	0.5	6.2	0.9	2.1	0.0	4.2	86.6	101	101	101.00	38	1129405432	22.8	25.8	25.9	25.4	0.0	31.6	13.0	bulk
670540	SRR1181769	SRP039090	SRS564575	SRX479017	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Lung (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Lung (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Lung		202	6 Months Old Adult 2 Lung (Strain 129S1/SvImJ)		2194072086	10861743	2017-01-20 00:00:00	1428624659	2194072086	10861743	2	10861743	index:0,count:10861743,average:101,stdev:0|index:1,count:10861743,average:101,stdev:0	6 Months Old Adult 2 Lung (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.12	2.19	0.05	2055638046	2050603217	1958982419	1960440087	99.76	100.07	10386564	8753660	293.962	1049.634	235	82401	86.75	91.03	11280757	9010432	11280757	9010432	87.73	88.04	11280757	9111992	11280757	8714330	171220961	8.33	0.59	0	4.49	0	0.17	0	0.03	0	0.00	0	4.17	0	10386564	0	202	0	198.24	0	2.32	0	0.01	0	2.24	0	0.01	0	222.17	0	1.21	0	64458	0	10861743	0	488183	0	18941	0	3690	0	0	0	452548	0	2008	0	0	0	25950	0	4786918	0	9401	0	4824277	0	91.13	0	9898381	0	171637	5088518	29.646975885153	10861743.0	10386564.0	64458.0	488183.0	18941.0	3690.0	0.0	452548.0	9898381.0	95.6	0.6	4.5	0.2	0.0	0.0	4.2	91.1	101	101	101.00	38	1097036043	23.0	26.0	25.9	25.2	0.0	31.7	13.1	bulk
670606	SRR1181771	SRP039090	SRS564576	SRX479019	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Pancreas (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Pancreas (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Pancreas		202	6 Months Old Adult 2 Pancreas (Strain 129S1/SvImJ)		2799775752	13860276	2017-01-20 00:00:00	1802352940	2799775752	13860276	2	13860276	index:0,count:13860276,average:101,stdev:0|index:1,count:13860276,average:101,stdev:0	6 Months Old Adult 2 Pancreas (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.02	0.32	0.0	2454979719	2473316541	2238686544	2257276712	100.75	100.83	12405842	9132049	381.477	1093.506	227	86610	89.5	98.11	16345627	11103706	16345627	11103706	94.73	94.5	16345627	11752193	16345627	10694601	46797687	1.91	0.45	0	7.86	0	6.48	0	0.00	0	0.00	0	4.01	0	12405842	0	202	0	197.93	0	2.39	0	0.00	0	2.55	0	0.00	0	114.18	0	1.08	0	62286	0	13860276	0	1088761	0	898227	0	584	0	0	0	555623	0	422	0	0	0	7050	0	9845484	0	6390	0	9859346	0	81.65	0	11317081	0	84352	12089082	143.317076062215	13860276.0	12405842.0	62286.0	1088761.0	898227.0	584.0	0.0	555623.0	11317081.0	89.5	0.4	7.9	6.5	0.0	0.0	4.0	81.7	101	101	101.00	38	1399887876	23.0	25.3	26.8	24.8	0.0	32.3	13.8	bulk
670621	SRR1181773	SRP039090	SRS564577	SRX479021	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Skeletal Muscle (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Skeletal Muscle (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Skeletal Muscle		202	6 Months Old Adult 2 Skeletal Muscle (Strain 129S1/SvImJ)		2046280806	10130103	2017-01-20 00:00:00	1350794770	2046280806	10130103	2	10130103	index:0,count:10130103,average:101,stdev:0|index:1,count:10130103,average:101,stdev:0	6 Months Old Adult 2 Skeletal Muscle (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.3	1.33	0.01	1888152396	1962703601	1820315239	1895774838	103.95	104.15	9587861	7500300	365.285	1296.604	244	61501	94.49	98.01	10458294	9059580	10458294	9059580	92.45	92.58	10458294	8864094	10458294	8557412	31650234	1.68	0.61	0	3.40	0	0.67	0	0.01	0	0.00	0	4.67	0	9587861	0	202	0	197.26	0	2.79	0	0.01	0	2.72	0	0.01	0	92.56	0	1.28	0	61849	0	10130103	0	344376	0	68087	0	1220	0	0	0	472935	0	2089	0	0	0	29810	0	6657106	0	8143	0	6697148	0	91.25	0	9243485	0	132176	6991779	52.897492736957	10130103.0	9587861.0	61849.0	344376.0	68087.0	1220.0	0.0	472935.0	9243485.0	94.6	0.6	3.4	0.7	0.0	0.0	4.7	91.2	101	101	101.00	38	1023140403	20.6	27.9	25.9	25.5	0.0	31.0	12.6	bulk
670644	SRR1181776	SRP039090	SRS564579	SRX479024	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Spleen (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Spleen (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Spleen		202	6 Months Old Adult 2 Spleen (Strain 129S1/SvImJ)		2950360086	14605743	2017-01-20 00:00:00	1883475483	2950360086	14605743	2	14605743	index:0,count:14605743,average:101,stdev:0|index:1,count:14605743,average:101,stdev:0	6 Months Old Adult 2 Spleen (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.07	2.35	0.21	2732773097	2682723284	2465354739	2423744287	98.17	98.31	13809968	12261245	302.620	1393.591	234	122697	78.21	86.71	16428856	10801102	16428856	10801102	83.63	83.19	16428856	11549782	16428856	10363250	298805768	10.93	0.71	0	9.26	0	0.40	0	0.12	0	0.00	0	4.93	0	13809968	0	202	0	198.17	0	2.34	0	0.02	0	2.22	0	0.01	0	132.78	0	1.22	0	104338	0	14605743	0	1353056	0	58337	0	17409	0	0	0	720029	0	3324	0	0	0	29648	0	5276158	0	20389	0	5329519	0	85.29	0	12456912	0	171676	6477908	37.733334886647	14605743.0	13809968.0	104338.0	1353056.0	58337.0	17409.0	0.0	720029.0	12456912.0	94.6	0.7	9.3	0.4	0.1	0.0	4.9	85.3	101	101	101.00	38	1475180043	23.1	26.2	26.0	24.7	0.0	31.8	13.0	bulk
670661	SRR1181778	SRP039090	SRS564580	SRX479026	SRA143022	Stanford University	Li Lab	A Quantitative Mammalian Atlas of A-to-I RNA Editing	Human RNA-seq/exome-seq and mouse RNA-seq libraries were generated to identify A-to-I RNA editing events. RNA editing levels at >10,000 exonic sites in >400 human and mouse samples were profiled by mmPCR-seq.		6 Months Old Adult 2 Stomach (Strain 129S1/SvImJ) - RNA-seq	"The Illumina mRNA-seq library preparation workflow was followed with some modifications, as described previously by Tan et al. (2013). The library amplification step was performed with SYBR Green I on a real-time PCR machine to prevent over-amplification. The standard 6bp Illumina barcodes were added to each library in the final PCR step. All libraries were quantified using the Qubit dsDNA High Sensitivity Assay Kit (Invitrogen) and sequenced on HiSeq 2000 (Illumina)."			RNA-Seq	TRANSCRIPTOMIC	cDNA	paired				Illumina HiSeq 2000	age;;6 months|biomaterial_provider;;Laura Attardi (Stanford)|BioSampleModel;;Model organism or animal|genotype;;Wildtype|label;;6 Months Old Adult 2 Stomach (Strain 129S1/SvImJ)|sex;;male|strain;;129S1/SvImJ|tissue;;Stomach		202	6 Months Old Adult 2 Stomach (Strain 129S1/SvImJ)		3076235174	15228887	2017-01-20 00:00:00	1969693215	3076235174	15228887	2	15228887	index:0,count:15228887,average:101,stdev:0|index:1,count:15228887,average:101,stdev:0	6 Months Old Adult 2 Stomach (Strain 129S1/SvImJ) - RNA-seq	Stanford University			in_mesa	29022589	0.13	2.07	0.01	2816784325	2878452359	2577631420	2641284132	102.19	102.47	14213320	10922581	334.261	1107.095	234	91791	89.42	97.66	16374922	12709530	16374922	12709530	92.98	93.09	16374922	13214844	16374922	12114301	60042745	2.13	0.42	0	7.88	0	0.59	0	0.03	0	0.00	0	6.05	0	14213320	0	202	0	198.18	0	2.29	0	0.01	0	2.72	0	0.01	0	172.95	0	1.16	0	63737	0	15228887	0	1199511	0	89300	0	4808	0	0	0	921459	0	2516	0	0	0	33439	0	7832720	0	10587	0	7879262	0	85.45	0	13013809	0	139344	8717969	62.564365885865	15228887.0	14213320.0	63737.0	1199511.0	89300.0	4808.0	0.0	921459.0	13013809.0	93.3	0.4	7.9	0.6	0.0	0.0	6.1	85.5	101	101	101.00	38	1538117587	23.2	25.6	25.9	25.3	0.0	32.0	13.3	bulk
1520763	SRR1258347	SRP041343	SRS595523	SRX523362	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372454: LPS_0min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;0 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372454		GSM1372454	LPS_0min_RNA_total	9508169088	47070144	2014-12-16 07:10:52	6121893709	9508169088	47070144	2	47070144	index:0,count:47070144,average:101,stdev:0|index:1,count:47070144,average:101,stdev:0	GSM1372454_r1	GEO					13.18	2.05	0.08	7571801420	7250456981	6613463281	6314027062	95.76	95.47	38824461	34875436	305.944	938.095	282	335641	58.85	67.29	44610801	22850075	44610801	22850075	66.8	64.61	44610801	25935918	44610801	21939395	1918337941	25.34	0.47	0	10.34	0	0.11	0	0.10	0	0.00	0	17.31	0	38824461	0	202	0	198.74	0	4.13	0	0.05	0	3.40	0	0.06	0	165.16	0	0.52	0	222798	0	47070144	0	4866997	0	51110	0	49084	0	0	0	8145489	0	5438	0	0	0	48230	0	7704200	0	19377	0	7777245	0	72.14	0	33957464	0	181089	8039958	44.397826483111	47070144.0	38824461.0	222798.0	4866997.0	51110.0	49084.0	0.0	8145489.0	33957464.0	82.5	0.5	10.3	0.1	0.1	0.0	17.3	72.1	101	101	101.00	38	4754084544	23.3	26.0	25.1	25.6	0.0	35.3	17.6	bulk
1520780	SRR1258348	SRP041343	SRS595539	SRX523363	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372455: LPS_15min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;15 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372455		GSM1372455	LPS_15min_RNA_total	10468538294	51824447	2014-12-16 07:10:52	6760048472	10468538294	51824447	2	51824447	index:0,count:51824447,average:101,stdev:0|index:1,count:51824447,average:101,stdev:0	GSM1372455_r1	GEO					12.26	1.65	0.07	7651792932	7407848988	6779152463	6558146483	96.81	96.74	39506489	36607757	306.333	770.562	270	356255	55.07	62.1	44803851	21755207	44803851	21755207	58.19	55.62	44803851	22990003	44803851	19484330	2193075516	28.66	0.98	0	8.63	0	0.10	0	0.10	0	0.00	0	23.58	0	39506489	0	202	0	197.57	0	4.62	0	0.08	0	3.20	0	0.07	0	164.81	0	0.65	0	506459	0	51824447	0	4474481	0	50155	0	49905	0	0	0	12217898	0	3705	0	0	0	35871	0	5682309	0	24743	0	5746628	0	67.60	0	35032008	0	172279	5924070	34.386489357380	51824447.0	39506489.0	506459.0	4474481.0	50155.0	49905.0	0.0	12217898.0	35032008.0	76.2	1.0	8.6	0.1	0.1	0.0	23.6	67.6	101	101	101.00	38	5234269147	22.5	27.4	25.7	24.5	0.0	35.2	17.7	bulk
1520796	SRR1258349	SRP041343	SRS595540	SRX523364	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372456: LPS_30min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;30 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372456		GSM1372456	LPS_30min_RNA_total	8694457336	43041868	2014-12-16 07:10:52	5582420467	8694457336	43041868	2	43041868	index:0,count:43041868,average:101,stdev:0|index:1,count:43041868,average:101,stdev:0	GSM1372456_r1	GEO					14.08	1.7	0.08	6572875372	6215673208	5748989940	5414098842	94.57	94.17	33885252	30997939	306.615	838.427	286	307806	56.38	64.37	38846622	19103428	38846622	19103428	63.18	60.74	38846622	21409244	38846622	18026252	1720319774	26.17	0.72	0	9.78	0	0.11	0	0.09	0	0.00	0	21.07	0	33885252	0	202	0	197.86	0	4.46	0	0.07	0	3.40	0	0.08	0	181.23	0	0.61	0	310096	0	43041868	0	4209223	0	46415	0	40727	0	0	0	9069474	0	3615	0	0	0	34234	0	5594564	0	21966	0	5654379	0	68.95	0	29676029	0	169980	5830880	34.303329803506	43041868.0	33885252.0	310096.0	4209223.0	46415.0	40727.0	0.0	9069474.0	29676029.0	78.7	0.7	9.8	0.1	0.1	0.0	21.1	68.9	101	101	101.00	38	4347228668	23.2	26.5	25.0	25.3	0.0	35.1	17.2	bulk
1520908	SRR1258350	SRP041343	SRS595524	SRX523365	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372457: LPS_45min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;45 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372457		GSM1372457	LPS_45min_RNA_total	10608057876	52515138	2014-12-16 07:10:52	6858493448	10608057876	52515138	2	52515138	index:0,count:52515138,average:101,stdev:0|index:1,count:52515138,average:101,stdev:0	GSM1372457_r1	GEO					12.79	1.59	0.1	7977850336	7586476231	7076141891	6715454120	95.09	94.9	41447753	38814009	293.092	692.998	270	370305	53.21	59.91	46986611	22054365	46986611	22054365	56.77	54.25	46986611	23530719	46986611	19968826	2328182596	29.18	0.89	0	8.83	0	0.11	0	0.10	0	0.00	0	20.87	0	41447753	0	202	0	197.42	0	4.58	0	0.08	0	3.44	0	0.09	0	156.89	0	0.69	0	468535	0	52515138	0	4635595	0	56801	0	53132	0	0	0	10957452	0	3516	0	0	0	34624	0	5572166	0	29568	0	5639874	0	70.10	0	36812158	0	176867	5788696	32.729090220335	52515138.0	41447753.0	468535.0	4635595.0	56801.0	53132.0	0.0	10957452.0	36812158.0	78.9	0.9	8.8	0.1	0.1	0.0	20.9	70.1	101	101	101.00	38	5304028938	22.6	27.1	25.4	24.9	0.0	35.2	17.8	bulk
1520924	SRR1258351	SRP041343	SRS596838	SRX523366	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372458: LPS_60min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;60 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372458		GSM1372458	LPS_60min_RNA_total	9788382882	48457341	2014-12-16 07:10:52	6360023245	9788382882	48457341	2	48457341	index:0,count:48457341,average:101,stdev:0|index:1,count:48457341,average:101,stdev:0	GSM1372458_r1	GEO					9.7	1.5	0.1	7062286431	7000841690	6341764272	6304410542	99.13	99.41	36618779	34274689	312.551	722.695	270	355919	53.35	59.39	41019974	19537856	41019974	19537856	51.65	48.92	41019974	18914745	41019974	16094862	2146902915	30.40	1.18	0	7.68	0	0.09	0	0.09	0	0.00	0	24.25	0	36618779	0	202	0	196.83	0	4.73	0	0.09	0	3.23	0	0.09	0	175.15	0	0.73	0	573357	0	48457341	0	3720611	0	42667	0	44503	0	0	0	11751392	0	2495	0	0	0	26634	0	4426352	0	29323	0	4484804	0	67.89	0	32898168	0	165611	4604032	27.800278966977	48457341.0	36618779.0	573357.0	3720611.0	42667.0	44503.0	0.0	11751392.0	32898168.0	75.6	1.2	7.7	0.1	0.1	0.0	24.3	67.9	101	101	101.00	38	4894191441	21.9	28.2	26.1	23.8	0.0	35.2	18.2	bulk
1520940	SRR1258352	SRP041343	SRS595541	SRX523367	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372459: LPS_75min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;75 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372459		GSM1372459	LPS_75min_RNA_total	9676676478	47904339	2014-12-16 07:10:52	6291734166	9676676478	47904339	2	47904339	index:0,count:47904339,average:101,stdev:0|index:1,count:47904339,average:101,stdev:0	GSM1372459_r1	GEO					7.1	1.28	0.1	6622440272	6668362263	5891562621	5960152432	100.69	101.16	34561482	32513334	300.958	663.281	270	316320	54.39	61.12	39062203	18799358	39062203	18799358	50.13	47.38	39062203	17325982	39062203	14572765	1827635451	27.60	1.36	0	7.93	0	0.07	0	0.06	0	0.00	0	27.72	0	34561482	0	202	0	196.28	0	4.87	0	0.11	0	3.24	0	0.11	0	146.90	0	0.82	0	651631	0	47904339	0	3801042	0	35231	0	30339	0	0	0	13277287	0	2330	0	0	0	24560	0	4206498	0	34728	0	4268116	0	64.21	0	30760440	0	157566	4361113	27.678007945877	47904339.0	34561482.0	651631.0	3801042.0	35231.0	30339.0	0.0	13277287.0	30760440.0	72.1	1.4	7.9	0.1	0.1	0.0	27.7	64.2	101	101	101.00	38	4838338239	21.0	29.4	26.7	22.8	0.0	35.0	18.1	bulk
1520956	SRR1258353	SRP041343	SRS596837	SRX523368	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372460: LPS_90min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;90 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372460		GSM1372460	LPS_90min_RNA_total	8997571870	44542435	2014-12-16 07:10:52	5814917001	8997571870	44542435	2	44542435	index:0,count:44542435,average:101,stdev:0|index:1,count:44542435,average:101,stdev:0	GSM1372460_r1	GEO					9.78	1.44	0.09	6238173066	6168588262	5505395459	5455448946	98.88	99.09	32415939	30024984	305.448	752.526	270	308254	56.21	63.63	36873883	18220122	36873883	18220122	55.85	53.25	36873883	18105794	36873883	15247046	1609398467	25.80	1.14	0	8.49	0	0.09	0	0.06	0	0.00	0	27.07	0	32415939	0	202	0	196.65	0	4.62	0	0.09	0	3.17	0	0.09	0	139.07	0	0.76	0	506335	0	44542435	0	3781006	0	39433	0	28638	0	0	0	12058425	0	2570	0	0	0	27745	0	4680485	0	26387	0	4737187	0	64.29	0	28634933	0	158983	4866448	30.609863947718	44542435.0	32415939.0	506335.0	3781006.0	39433.0	28638.0	0.0	12058425.0	28634933.0	72.8	1.1	8.5	0.1	0.1	0.0	27.1	64.3	101	101	101.00	38	4498785935	21.7	28.4	26.2	23.7	0.0	35.0	17.7	bulk
1520971	SRR1258354	SRP041343	SRS596839	SRX523369	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372461: LPS_105min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;105 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372461		GSM1372461	LPS_105min_RNA_total	11243121636	55659018	2014-12-16 07:10:52	7310995586	11243121636	55659018	2	55659018	index:0,count:55659018,average:101,stdev:0|index:1,count:55659018,average:101,stdev:0	GSM1372461_r1	GEO					10.14	1.3	0.09	8492292097	8425810009	7588269096	7551103231	99.22	99.51	44062102	41265240	307.902	699.523	270	467311	55.37	61.87	49539098	24395027	49539098	24395027	52.61	50.1	49539098	23181880	49539098	19755579	2147709105	25.29	1.26	0	8.32	0	0.08	0	0.07	0	0.00	0	20.69	0	44062102	0	202	0	196.38	0	4.74	0	0.11	0	3.34	0	0.10	0	178.74	0	0.82	0	699300	0	55659018	0	4632992	0	42678	0	37952	0	0	0	11516286	0	3036	0	0	0	32537	0	5391063	0	38405	0	5465041	0	70.84	0	39429110	0	170848	5625678	32.927971061997	55659018.0	44062102.0	699300.0	4632992.0	42678.0	37952.0	0.0	11516286.0	39429110.0	79.2	1.3	8.3	0.1	0.1	0.0	20.7	70.8	101	101	101.00	38	5621560818	21.9	27.9	25.6	24.7	0.0	35.4	18.7	bulk
1520986	SRR1258355	SRP041343	SRS596840	SRX523370	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372462: LPS_120min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;120 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372462		GSM1372462	LPS_120min_RNA_total	10321013856	51094128	2014-12-16 07:10:52	6669596409	10321013856	51094128	2	51094128	index:0,count:51094128,average:101,stdev:0|index:1,count:51094128,average:101,stdev:0	GSM1372462_r1	GEO					10.76	1.49	0.09	7779624324	7515164541	6779266415	6540041800	96.6	96.47	40207739	37168596	306.818	766.005	270	434018	54.34	62.24	46137857	21847916	46137857	21847916	57.74	54.7	46137857	23217494	46137857	19201072	2039137074	26.21	0.98	0	9.99	0	0.09	0	0.08	0	0.00	0	21.14	0	40207739	0	202	0	196.92	0	4.54	0	0.08	0	3.36	0	0.08	0	165.26	0	0.73	0	502492	0	51094128	0	5103001	0	46560	0	40662	0	0	0	10799167	0	3322	0	0	0	35667	0	5903010	0	29126	0	5971125	0	68.71	0	35104738	0	173390	6157378	35.511725012977	51094128.0	40207739.0	502492.0	5103001.0	46560.0	40662.0	0.0	10799167.0	35104738.0	78.7	1.0	10.0	0.1	0.1	0.0	21.1	68.7	101	101	101.00	38	5160506928	22.2	27.4	25.5	25.0	0.0	35.4	18.6	bulk
1521002	SRR1258356	SRP041343	SRS595525	SRX523371	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372463: LPS_135min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;135 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372463		GSM1372463	LPS_135min_RNA_total	8353248228	41352714	2014-12-16 07:10:52	5421466387	8353248228	41352714	2	41352714	index:0,count:41352714,average:101,stdev:0|index:1,count:41352714,average:101,stdev:0	GSM1372463_r1	GEO					11.24	1.8	0.08	6196249528	5857207165	5435837612	5117614712	94.53	94.15	31962421	28786964	310.300	927.814	270	333093	56.91	64.77	36557507	18190089	36557507	18190089	63.49	61.25	36557507	20291450	36557507	17202098	1600651975	25.83	0.75	0	9.38	0	0.09	0	0.08	0	0.00	0	22.53	0	31962421	0	202	0	197.57	0	4.33	0	0.06	0	3.32	0	0.07	0	156.21	0	0.65	0	311957	0	41352714	0	3879040	0	38919	0	33987	0	0	0	9317387	0	3424	0	0	0	36886	0	5995326	0	19222	0	6054858	0	67.91	0	28083381	0	165160	6249292	37.837805764108	41352714.0	31962421.0	311957.0	3879040.0	38919.0	33987.0	0.0	9317387.0	28083381.0	77.3	0.8	9.4	0.1	0.1	0.0	22.5	67.9	101	101	101.00	38	4176624114	22.0	27.3	26.0	24.7	0.0	35.4	18.5	bulk
1521018	SRR1258357	SRP041343	SRS595526	SRX523372	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372464: LPS_150min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;150 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372464		GSM1372464	LPS_150min_RNA_total	9571925944	47385772	2014-12-16 07:10:52	6154086596	9571925944	47385772	2	47385772	index:0,count:47385772,average:101,stdev:0|index:1,count:47385772,average:101,stdev:0	GSM1372464_r1	GEO					12.55	1.87	0.08	7411169274	7090797625	6322883268	6025062162	95.68	95.29	37995014	34000281	308.127	950.026	287	370665	59.1	69.15	44407480	22456381	44407480	22456381	68.84	66.45	44407480	26154474	44407480	21579062	1702159832	22.97	0.46	0	11.65	0	0.11	0	0.09	0	0.00	0	19.62	0	37995014	0	202	0	198.55	0	3.90	0	0.04	0	3.33	0	0.06	0	185.02	0	0.54	0	219522	0	47385772	0	5520061	0	50515	0	42291	0	0	0	9297952	0	4362	0	0	0	47498	0	7676958	0	18641	0	7747459	0	68.53	0	32474953	0	176981	8012659	45.274119820772	47385772.0	37995014.0	219522.0	5520061.0	50515.0	42291.0	0.0	9297952.0	32474953.0	80.2	0.5	11.6	0.1	0.1	0.0	19.6	68.5	101	101	101.00	38	4785962972	22.8	26.2	25.4	25.5	0.0	35.3	17.8	bulk
1521033	SRR1258358	SRP041343	SRS595527	SRX523373	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372465: LPS_165min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;165 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372465		GSM1372465	LPS_165min_RNA_total	9353033492	46302146	2014-12-16 07:10:52	6056671726	9353033492	46302146	2	46302146	index:0,count:46302146,average:101,stdev:0|index:1,count:46302146,average:101,stdev:0	GSM1372465_r1	GEO					11.62	1.81	0.08	7071221179	6727310997	6017486944	5695748490	95.14	94.65	36329636	32521413	305.716	952.894	287	338656	57.92	67.92	42539419	21040480	42539419	21040480	67.63	65.08	42539419	24571322	42539419	20160533	1651511666	23.36	0.48	0	11.56	0	0.10	0	0.09	0	0.00	0	21.35	0	36329636	0	202	0	198.25	0	4.01	0	0.05	0	3.56	0	0.06	0	144.32	0	0.57	0	221789	0	46302146	0	5350531	0	47660	0	41306	0	0	0	9883544	0	4210	0	0	0	45209	0	7321506	0	17364	0	7388289	0	66.91	0	30979105	0	176350	7643588	43.343283243550	46302146.0	36329636.0	221789.0	5350531.0	47660.0	41306.0	0.0	9883544.0	30979105.0	78.5	0.5	11.6	0.1	0.1	0.0	21.3	66.9	101	101	101.00	38	4676516746	22.1	27.1	26.0	24.8	0.0	35.3	18.2	bulk
1521049	SRR1258359	SRP041343	SRS595528	SRX523374	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372466: LPS_180min_RNA_total; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;180 min|treatment;;ribosomal delpetion	GEO Accession;;GSM1372466		GSM1372466	LPS_180min_RNA_total	10161614444	50305022	2014-12-16 07:10:52	6561928499	10161614444	50305022	2	50305022	index:0,count:50305022,average:101,stdev:0|index:1,count:50305022,average:101,stdev:0	GSM1372466_r1	GEO					11.54	1.81	0.07	7823955712	7422035486	6679923679	6306363220	94.86	94.41	40711630	36899755	291.157	866.777	281	325657	56.98	66.59	47616177	23196030	47616177	23196030	66.04	63.85	47616177	26885105	47616177	22239672	1905836184	24.36	0.51	0	11.69	0	0.11	0	0.10	0	0.00	0	18.86	0	40711630	0	202	0	198.35	0	4.08	0	0.05	0	3.62	0	0.07	0	175.65	0	0.57	0	257098	0	50305022	0	5878952	0	56636	0	50335	0	0	0	9486421	0	4555	0	0	0	50014	0	7928180	0	21617	0	8004366	0	69.24	0	34832678	0	178099	8225775	46.186531086643	50305022.0	40711630.0	257098.0	5878952.0	56636.0	50335.0	0.0	9486421.0	34832678.0	80.9	0.5	11.7	0.1	0.1	0.0	18.9	69.2	101	101	101.00	38	5080807222	22.4	26.7	25.8	25.1	0.0	35.5	18.5	bulk
1521161	SRR1258360	SRP041343	SRS595529	SRX523375	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372467: LPS_0min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;0 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372467		GSM1372467	LPS_0min_RNA_4sU	9699774976	48018688	2014-12-16 07:10:52	6274341179	9699774976	48018688	2	48018688	index:0,count:48018688,average:101,stdev:0|index:1,count:48018688,average:101,stdev:0	GSM1372467_r1	GEO					12.85	2.4	0.1	8076362931	7818987992	7496206585	7264766582	96.81	96.91	41156259	36652766	315.222	983.121	270	243551	61.23	65.95	44983789	25198132	44983789	25198132	65.08	63.95	44983789	26785896	44983789	24433808	2462803396	30.49	0.38	0	6.14	0	0.12	0	0.13	0	0.00	0	14.04	0	41156259	0	202	0	199.65	0	3.10	0	0.03	0	2.94	0	0.03	0	186.68	0	0.41	0	181885	0	48018688	0	2948690	0	56340	0	64341	0	0	0	6741748	0	5788	0	0	0	57600	0	8934241	0	18326	0	9015955	0	79.57	0	38207569	0	190091	9328410	49.073391165284	48018688.0	41156259.0	181885.0	2948690.0	56340.0	64341.0	0.0	6741748.0	38207569.0	85.7	0.4	6.1	0.1	0.1	0.0	14.0	79.6	101	101	101.00	38	4849887488	24.4	25.1	24.6	25.9	0.0	35.6	18.4	bulk
1521177	SRR1258361	SRP041343	SRS595542	SRX523376	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372468: LPS_15min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;15 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372468		GSM1372468	LPS_15min_RNA_4sU	8777702950	43453975	2014-12-16 07:10:52	5577473201	8777702950	43453975	2	43453975	index:0,count:43453975,average:101,stdev:0|index:1,count:43453975,average:101,stdev:0	GSM1372468_r1	GEO					5.5	2.45	0.14	6744444878	6404658964	6425311792	6112934711	94.96	95.14	34334393	32731705	313.490	603.864	270	196271	44.49	46.72	36642195	15274919	36642195	15274919	45.84	44.61	36642195	15737956	36642195	14586393	3423133995	50.75	0.40	0	3.77	0	0.11	0	0.16	0	0.00	0	20.72	0	34334393	0	202	0	199.85	0	2.82	0	0.03	0	2.54	0	0.03	0	151.29	0	0.44	0	173092	0	43453975	0	1637838	0	46181	0	68510	0	0	0	9004891	0	1681	0	0	0	18508	0	3135368	0	13818	0	3169375	0	75.24	0	32696555	0	148742	3356742	22.567546489895	43453975.0	34334393.0	173092.0	1637838.0	46181.0	68510.0	0.0	9004891.0	32696555.0	79.0	0.4	3.8	0.1	0.2	0.0	20.7	75.2	101	101	101.00	38	4388851475	26.8	24.6	23.3	25.3	0.0	34.8	15.8	bulk
1521193	SRR1258362	SRP041343	SRS595530	SRX523377	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372469: LPS_30min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;30 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372469		GSM1372469	LPS_30min_RNA_4sU	12414066348	61455774	2014-12-16 07:10:52	7747052382	12414066348	61455774	2	61455774	index:0,count:61455774,average:101,stdev:0|index:1,count:61455774,average:101,stdev:0	GSM1372469_r1	GEO					4.99	2.77	0.2	9015313188	8472717364	8727762941	8222907398	93.98	94.22	45902021	44544863	306.146	521.652	270	222068	38.15	39.42	48115621	17512887	48115621	17512887	38.9	38.16	48115621	17856536	48115621	16950723	5252609180	58.26	0.22	0	2.40	0	0.10	0	0.15	0	0.00	0	25.06	0	45902021	0	202	0	200.41	0	2.23	0	0.02	0	2.03	0	0.02	0	134.74	0	0.40	0	132269	0	61455774	0	1477194	0	59520	0	91828	0	0	0	15402405	0	1513	0	0	0	17105	0	2805409	0	17538	0	2841565	0	72.29	0	44424827	0	142367	2989120	20.995876853484	61455774.0	45902021.0	132269.0	1477194.0	59520.0	91828.0	0.0	15402405.0	44424827.0	74.7	0.2	2.4	0.1	0.1	0.0	25.1	72.3	101	101	101.00	38	6207033174	27.8	23.8	22.4	26.0	0.0	34.4	14.8	bulk
1521211	SRR1258363	SRP041343	SRS595531	SRX523378	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372470: LPS_45min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;45 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372470		GSM1372470	LPS_45min_RNA_4sU	5155848	25524	2014-12-16 07:10:52	3390877	5155848	25524	2	25524	index:0,count:25524,average:101,stdev:0|index:1,count:25524,average:101,stdev:0	GSM1372470_r1	GEO					10.69	2.09	0.08	3908624	3804690	3626056	3536127	97.34	97.52	19985	18392	325.935	843.035	270	157	55.3	59.61	21746	11052	21746	11052	55.35	53.9	21746	11061	21746	9995	1307645	33.46	0.78	0	5.65	0	0.07	0	0.09	0	0.00	0	21.54	0	19985	0	202	0	198.55	0	4.12	0	0.06	0	3.10	0	0.06	0	11.49	0	0.59	0	198	0	25524	0	1443	0	18	0	24	0	0	0	5497	0	3	0	0	0	16	0	2882	0	5	0	2906	0	72.65	0	18542	0	2332	2949	1.264579759863	25524.0	19985.0	198.0	1443.0	18.0	24.0	0.0	5497.0	18542.0	78.3	0.8	5.7	0.1	0.1	0.0	21.5	72.6	101	101	101.00	38	2577924	24.7	25.5	24.0	25.8	0.0	35.1	16.8	bulk
1521226	SRR1258364	SRP041343	SRS595532	SRX523379	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372471: LPS_60min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;60 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372471		GSM1372471	LPS_60min_RNA_4sU	12723764466	62988933	2014-12-16 07:10:52	8089353247	12723764466	62988933	2	62988933	index:0,count:62988933,average:101,stdev:0|index:1,count:62988933,average:101,stdev:0	GSM1372471_r1	GEO					5.93	2.51	0.2	9364643824	8800310830	9035818501	8509559999	93.97	94.18	47466263	45988601	331.604	568.836	270	261355	36.99	38.35	49848147	17556365	49848147	17556365	36.46	35.64	49848147	17308502	49848147	16313565	5418287169	57.86	0.46	0	2.69	0	0.09	0	0.15	0	0.00	0	24.41	0	47466263	0	202	0	199.79	0	2.87	0	0.03	0	2.63	0	0.03	0	132.22	0	0.48	0	292394	0	62988933	0	1691502	0	53641	0	93269	0	0	0	15375760	0	1321	0	0	0	16060	0	2606557	0	20161	0	2644099	0	72.67	0	45774761	0	145584	2758395	18.947102703594	62988933.0	47466263.0	292394.0	1691502.0	53641.0	93269.0	0.0	15375760.0	45774761.0	75.4	0.5	2.7	0.1	0.1	0.0	24.4	72.7	101	101	101.00	38	6361882233	26.8	24.7	22.8	25.7	0.0	34.9	16.0	bulk
1521241	SRR1258365	SRP041343	SRS595533	SRX523380	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372472: LPS_75min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;75 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372472		GSM1372472	LPS_75min_RNA_4sU	8344933706	41311553	2014-12-16 07:10:52	5292908793	8344933706	41311553	2	41311553	index:0,count:41311553,average:101,stdev:0|index:1,count:41311553,average:101,stdev:0	GSM1372472_r1	GEO					4.16	2.47	0.25	6163271838	5858011929	5954780739	5672671401	95.05	95.26	31322517	30532542	313.754	511.903	270	176072	35.49	36.76	32846131	11117647	32846131	11117647	34.84	34.1	32846131	10912489	32846131	10313797	3757712784	60.97	0.41	0	2.60	0	0.08	0	0.14	0	0.00	0	23.96	0	31322517	0	202	0	199.87	0	2.73	0	0.03	0	2.61	0	0.03	0	134.96	0	0.49	0	171146	0	41311553	0	1075423	0	33178	0	58199	0	0	0	9897659	0	765	0	0	0	9606	0	1535992	0	13733	0	1560096	0	73.22	0	30247094	0	124815	1618919	12.970548411649	41311553.0	31322517.0	171146.0	1075423.0	33178.0	58199.0	0.0	9897659.0	30247094.0	75.8	0.4	2.6	0.1	0.1	0.0	24.0	73.2	101	101	101.00	38	4172466853	26.7	24.8	23.0	25.4	0.0	34.9	15.9	bulk
1521257	SRR1258366	SRP041343	SRS595534	SRX523381	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372473: LPS_90min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;90 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372473		GSM1372473	LPS_90min_RNA_4sU	8825576950	43690975	2014-12-16 07:10:52	5605332713	8825576950	43690975	2	43690975	index:0,count:43690975,average:101,stdev:0|index:1,count:43690975,average:101,stdev:0	GSM1372473_r1	GEO					12.09	2.82	0.18	6866563162	6626268489	6598477607	6384105101	96.5	96.75	34683014	31389424	340.450	949.314	270	160559	56.1	58.39	36627507	19457228	36627507	19457228	57.27	56.76	36627507	19864559	36627507	18912447	2745195364	39.98	0.28	0	3.11	0	0.09	0	0.12	0	0.00	0	20.40	0	34683014	0	202	0	200.26	0	2.30	0	0.02	0	2.21	0	0.02	0	150.23	0	0.38	0	122441	0	43690975	0	1360502	0	40238	0	54363	0	0	0	8913360	0	3088	0	0	0	35270	0	5674016	0	14938	0	5727312	0	76.27	0	33322512	0	165896	5929739	35.743712928582	43690975.0	34683014.0	122441.0	1360502.0	40238.0	54363.0	0.0	8913360.0	33322512.0	79.4	0.3	3.1	0.1	0.1	0.0	20.4	76.3	101	101	101.00	38	4412788475	27.0	23.6	22.7	26.7	0.0	35.1	16.0	bulk
1521273	SRR1258367	SRP041343	SRS595535	SRX523382	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372474: LPS_105min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;105 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372474		GSM1372474	LPS_105min_RNA_4sU	8941715840	44265920	2014-12-16 07:10:52	5605645283	8941715840	44265920	2	44265920	index:0,count:44265920,average:101,stdev:0|index:1,count:44265920,average:101,stdev:0	GSM1372474_r1	GEO					6.06	2.25	0.16	6229922559	5952795919	5977871260	5725403972	95.55	95.78	31757816	30676351	318.421	572.613	270	194518	39.2	40.88	33539920	12449534	33539920	12449534	38.67	37.81	33539920	12279241	33539920	11514677	3523905184	56.56	0.53	0	2.94	0	0.07	0	0.12	0	0.00	0	28.06	0	31757816	0	202	0	199.46	0	2.86	0	0.04	0	2.78	0	0.03	0	136.90	0	0.54	0	235421	0	44265920	0	1302060	0	32757	0	53404	0	0	0	12421943	0	1047	0	0	0	12498	0	1987793	0	14938	0	2016276	0	68.80	0	30455756	0	134985	2094603	15.517301922436	44265920.0	31757816.0	235421.0	1302060.0	32757.0	53404.0	0.0	12421943.0	30455756.0	71.7	0.5	2.9	0.1	0.1	0.0	28.1	68.8	101	101	101.00	38	4470857920	26.9	24.8	23.2	25.1	0.0	34.6	15.2	bulk
1521289	SRR1258368	SRP041343	SRS596861	SRX523383	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372475: LPS_120min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;120 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372475		GSM1372475	LPS_120min_RNA_4sU	8668245816	42912108	2014-12-16 07:10:52	5563572854	8668245816	42912108	2	42912108	index:0,count:42912108,average:101,stdev:0|index:1,count:42912108,average:101,stdev:0	GSM1372475_r1	GEO					7.29	2.61	0.14	7259079641	6902356026	6997868295	6671042433	95.09	95.33	36628198	34750389	337.743	678.891	270	182554	42.26	43.84	38529436	15478835	38529436	15478835	43.2	42.52	38529436	15823949	38529436	15012141	3989731660	54.96	0.29	0	3.09	0	0.09	0	0.16	0	0.00	0	14.39	0	36628198	0	202	0	200.37	0	2.24	0	0.02	0	2.09	0	0.02	0	173.77	0	0.42	0	125466	0	42912108	0	1324202	0	40077	0	67175	0	0	0	6176658	0	1598	0	0	0	18890	0	3164985	0	13323	0	3198796	0	82.27	0	35303996	0	148531	3355612	22.591997630124	42912108.0	36628198.0	125466.0	1324202.0	40077.0	67175.0	0.0	6176658.0	35303996.0	85.4	0.3	3.1	0.1	0.2	0.0	14.4	82.3	101	101	101.00	38	4334122908	27.5	23.2	22.3	27.0	0.0	35.8	17.7	bulk
1521306	SRR1258369	SRP041343	SRS596862	SRX523384	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372476: LPS_135min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;135 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372476		GSM1372476	LPS_135min_RNA_4sU	14117372162	69887981	2014-12-16 07:10:52	8778495549	14117372162	69887981	2	69887981	index:0,count:69887981,average:101,stdev:0|index:1,count:69887981,average:101,stdev:0	GSM1372476_r1	GEO					4.07	2.57	0.12	9887118860	9403807972	9595784601	9151770858	95.11	95.37	49958561	48610727	328.092	547.257	270	232985	35.28	36.36	52158359	17624952	52158359	17624952	35.78	35.28	52158359	17872872	52158359	17104531	6302278091	63.74	0.20	0	2.12	0	0.07	0	0.14	0	0.00	0	28.31	0	49958561	0	202	0	200.55	0	2.05	0	0.02	0	1.85	0	0.01	0	120.15	0	0.44	0	137573	0	69887981	0	1482060	0	50459	0	94725	0	0	0	19784236	0	1132	0	0	0	15138	0	2363962	0	17825	0	2398057	0	69.36	0	48476501	0	129168	2518751	19.499806453611	69887981.0	49958561.0	137573.0	1482060.0	50459.0	94725.0	0.0	19784236.0	48476501.0	71.5	0.2	2.1	0.1	0.1	0.0	28.3	69.4	101	101	101.00	38	7058686081	28.3	24.1	21.7	25.9	0.0	34.4	14.7	bulk
1521419	SRR1258370	SRP041343	SRS595536	SRX523385	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372477: LPS_150min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;150 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372477		GSM1372477	LPS_150min_RNA_4sU	17554322675	101013839	2014-12-16 07:10:52	10708869669	17554322675	101013839	2	101013839	index:0,count:101013839,average:101,stdev:0|index:1,count:72791336,average:101,stdev:0	GSM1372477_r1	GEO					4.12	2.42	0.12	14060798542	13389292708	13601882248	13001264264	95.22	95.58	60120794	58293389	319.825	553.147	270	276861	47.77	49.24	86403790	28718885	86403790	28718885	48.6	47.78	86403790	29219307	86403790	27867553	8805068292	62.62	0.18	0.16	2.47	3.72	0.08	0.29	0.14	0.36	0.00	0.00	17.18	22.35	60120794	21732228	202	101	200.69	100.38	1.90	1.80	0.02	0.02	1.67	1.75	0.01	0.01	157.86	267.37	0.42	0.45	133365	46277	72791336	28222503	1800634	1050692	58628	81084	104389	100568	0	0	12507525	6308623	1540	290	0	0	21102	3303	3299698	527051	21216	5790	3343556	536434	80.12	73.28	58320160	20681536	157324	4101092	26.067809107320	101013839.0	81853022.0	179642.0	2851326.0	139712.0	204957.0	0.0	18816148.0	79001696.0	81.0	0.2	2.8	0.1	0.2	0.0	18.6	78.2	101	101	101.00	38	2850472803	28.1	23.7	22.1	26.1	0.0	34.7	15.3	bulk
1521436	SRR1258371	SRP041343	SRS595537	SRX523386	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372478: LPS_165min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;165 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372478		GSM1372478	LPS_165min_RNA_4sU	8238103784	40782692	2014-12-16 07:10:52	5241952520	8238103784	40782692	2	40782692	index:0,count:40782692,average:101,stdev:0|index:1,count:40782692,average:101,stdev:0	GSM1372478_r1	GEO					4.38	2.52	0.13	6611932710	6303257876	6398891356	6116842510	95.33	95.59	33455104	32356576	320.627	571.753	270	161618	37.04	38.28	35053133	12391066	35053133	12391066	37.8	37.21	35053133	12645708	35053133	12045506	4080300836	61.71	0.24	0	2.66	0	0.09	0	0.17	0	0.00	0	17.71	0	33455104	0	202	0	200.62	0	2.09	0	0.02	0	1.81	0	0.01	0	162.59	0	0.43	0	97441	0	40782692	0	1083107	0	36123	0	69931	0	0	0	7221534	0	898	0	0	0	12420	0	1940263	0	12029	0	1965610	0	79.38	0	32371997	0	128915	2061044	15.987619749447	40782692.0	33455104.0	97441.0	1083107.0	36123.0	69931.0	0.0	7221534.0	32371997.0	82.0	0.2	2.7	0.1	0.2	0.0	17.7	79.4	101	101	101.00	38	4119051892	27.7	23.7	22.2	26.4	0.0	35.4	16.8	bulk
1521452	SRR1258372	SRP041343	SRS595538	SRX523387	SRA159047	GEO		A high resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies	To monitor the relative regulatory contributions of RNA production, processing and degradation, we sampled RNA from mouse DCs every 15 minutes, for the first 3 hours of their response to LPS (13 samples in total), following a short (10 minute) metabolic labeling pulse with 4sU preceding the sampled time point. We isolated RNA from each of these samples in two ways. First, to comprehensively measure total RNA regardless of its transcription time, we isolated RNA depleted of rRNA. Second, to measure only newly made RNA, we isolated 4sU-labeled RNA, which could only have been transcribed during the 10 minute labeling pulse and is thus enriched for short-lived transcripts, including mRNA precursors and processing intermediates. We deeply sequenced each isolated RNA population to provide the necessary depth to study exons, introns, and splicing junctions across the transcriptome. We showed our approach general utility by also applying it to lincRNAs and early zebrafish development data Overall design: Time-course mRNA profiles of mouse DCs that were stimulated with LPS, and labeled with a short (10 minute) 4sU pulse (0-3 hours, 15 min. intervals, 13 time points).		GSM1372479: LPS_180min_RNA_4sU; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted with the miRNeasy kit's procedure (Qiagen). For preparation of RNA-Sequencing samples, we used 10 μg total RNA and removed rRNA with the RiboZero kit (Epicenter). After taking an aliquot of 100 ng ribosomal depleted total RNA, we followed with 4sU purification for the remainder of the sample as desceibed in Rabani et. al., Nat. Biotech., 2011 We prepared the RNA-Seq libraries using the dUTP second strand (strand specific) protocol as described in Levin et. al, Nat. Methods, 2010.	Illumina HiSeq 2000	cell type;;dendritic cell|source_name;;Mouse dendritic cells|stimulation;;LPS|strain;;C57BL/6|time post stimulation;;180 min|treatment;;ribosomal delpetion, 4sU selection	GEO Accession;;GSM1372479		GSM1372479	LPS_180min_RNA_4sU	8645628179	43948402	2014-12-16 07:10:52	5291304022	8645628179	43948402	2	43948402	index:0,count:43948402,average:101,stdev:0|index:1,count:41651877,average:101,stdev:0	GSM1372479_r1	GEO					4.04	2.43	0.1	7121222776	6783520220	6896534812	6589662985	95.26	95.55	35241648	34171342	317.007	553.006	270	169244	37.36	38.56	38676747	13168021	38676747	13168021	38.05	37.5	38676747	13407765	38676747	12803703	4472118437	62.80	0.23	0.21	2.63	4.13	0.09	0.47	0.17	0.68	0.00	0.00	15.13	29.10	35241648	1601792	202	101	200.64	100.26	2.00	2.14	0.02	0.03	1.73	1.88	0.01	0.02	163.70	155.99	0.41	0.54	94196	4862	41651877	2296525	1096023	94928	37142	10721	71684	15660	0	0	6301403	668352	869	21	0	0	12666	270	1950045	38736	11626	483	1975206	39510	81.98	65.61	34145625	1506864	130584	2119393	16.230112418060	43948402.0	36843440.0	99058.0	1190951.0	47863.0	87344.0	0.0	6969755.0	35652489.0	83.8	0.2	2.7	0.1	0.2	0.0	15.9	81.1	101	101	101.00	38	231949025	28.0	24.4	22.7	24.9	0.0	33.8	13.9	bulk
461091	SRR1291248	SRP042078	SRS613250	SRX546213	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388406: SMC Jejunum; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Sorted primary cells|cell type;;SMC|source_name;;SMC in jejunum|strain;;smMHCCre-eGFP/+|tissue;;Jejunum	GEO Accession;;GSM1388406		GSM1388406	SMC Jejunum	15070238800	75351194	2015-07-31 20:26:22	9646329703	15070238800	75351194	2	75351194	index:0,count:75351194,average:100,stdev:0|index:1,count:75351194,average:100,stdev:0	GSM1388406_r1	GEO			in_mesa	26241044	8.04	3.81	0.05	11995402975	12042734834	11076075619	11180998986	100.39	100.95	72637219	68052359	192.195	536.219	146	707004	86.22	93.46	80374864	62625064	80374864	62625064	89.54	89.6	80374864	65039412	80374864	60033513	675505891	5.63	1.13	0	7.48	0	0.25	0	0.05	0	0.00	0	3.30	0	72637219	0	200	0	198.19	0	1.76	0	0.01	0	1.48	0	0.01	0	221.26	0	0.21	0	854127	0	75351194	0	5632824	0	191842	0	38846	0	0	0	2483287	0	16460	0	0	0	181539	0	34324374	0	51843	0	34574216	0	88.92	0	67004395	0	221518	31237711	141.016581045333	75351194.0	72637219.0	854127.0	5632824.0	191842.0	38846.0	0.0	2483287.0	67004395.0	96.4	1.1	7.5	0.3	0.1	0.0	3.3	88.9	100	100	100.00	38	7535119400	25.0	25.1	24.8	25.1	0.0	36.3	21.1	bulk
461095	SRR1291249	SRP042078	SRS613251	SRX546214	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388407: SMC Colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Sorted primary cells|cell type;;SMC|source_name;;SMC in colon|strain;;smMHCCre-eGFP/+|tissue;;Colon	GEO Accession;;GSM1388407		GSM1388407	SMC Colon	15144592600	75722963	2015-07-31 20:26:22	9728489419	15144592600	75722963	2	75722963	index:0,count:75722963,average:100,stdev:0|index:1,count:75722963,average:100,stdev:0	GSM1388407_r1	GEO			in_mesa	26241044	6.12	3.73	0.05	11861301320	11975396276	11128291828	11292069245	100.96	101.47	72928407	68054676	190.180	542.591	146	720567	87.37	93.21	79374592	63720059	79374592	63720059	88.64	88.8	79374592	64645841	79374592	60701173	701339597	5.91	1.10	0	6.03	0	0.23	0	0.05	0	0.00	0	3.41	0	72928407	0	200	0	198.12	0	1.68	0	0.01	0	1.57	0	0.01	0	284.26	0	0.21	0	834361	0	75722963	0	4568982	0	177738	0	35652	0	0	0	2581166	0	15351	0	0	0	166420	0	36713268	0	46649	0	36941688	0	90.28	0	68359425	0	235562	32788441	139.192403698389	75722963.0	72928407.0	834361.0	4568982.0	177738.0	35652.0	0.0	2581166.0	68359425.0	96.3	1.1	6.0	0.2	0.0	0.0	3.4	90.3	100	100	100.00	38	7572296300	24.7	25.5	25.1	24.7	0.0	36.2	20.9	bulk
461123	SRR1291250	SRP042078	SRS613252	SRX546215	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388408: ICC Jejunum; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Sorted primary cells|cell type;;ICC|source_name;;ICC in jejunum|strain;;KitcopGFP/+|tissue;;Jejunum	GEO Accession;;GSM1388408		GSM1388408	ICC Jejunum	20877832008	103355604	2015-07-31 20:26:22	14397995701	20877832008	103355604	2	103355604	index:0,count:103355604,average:101,stdev:0|index:1,count:103355604,average:101,stdev:0	GSM1388408_r1	GEO			in_mesa	26241044	12.06	2.69	0.13	15791620723	14918123538	14296670148	13566581826	94.47	94.89	98691117	94073252	186.682	524.906	134	904877	72.28	79.98	111009438	71338062	111009438	71338062	77.8	76.85	111009438	76781784	111009438	68549914	2257841614	14.30	1.42	0	9.19	0	0.27	0	0.20	0	0.00	0	4.03	0	98691117	0	202	0	200.11	0	1.93	0	0.01	0	1.53	0	0.01	0	258.03	0	0.29	0	1470029	0	103355604	0	9497173	0	283580	0	211731	0	0	0	4169176	0	18114	0	0	0	205676	0	29306946	0	82840	0	29613576	0	86.30	0	89193944	0	287201	25492764	88.762796786919	103355604.0	98691117.0	1470029.0	9497173.0	283580.0	211731.0	0.0	4169176.0	89193944.0	95.5	1.4	9.2	0.3	0.2	0.0	4.0	86.3	101	101	101.00	38	10438916004	26.0	23.9	24.1	26.0	0.0	34.9	18.0	bulk
461127	SRR1291251	SRP042078	SRS613253	SRX546216	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388409: ICC Colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Sorted primary cells|cell type;;ICC|source_name;;ICC in colon|strain;;KitcopGFP/+|tissue;;Colon	GEO Accession;;GSM1388409		GSM1388409	ICC Colon	19508745092	96577946	2015-07-31 20:26:22	13483461201	19508745092	96577946	2	96577946	index:0,count:96577946,average:101,stdev:0|index:1,count:96577946,average:101,stdev:0	GSM1388409_r1	GEO			in_mesa	26241044	4.28	3.13	0.1	14776563829	14468759516	14013098396	13786724824	97.92	98.38	93057787	87629280	184.611	579.040	136	867827	80.1	84.55	100329058	74543509	100329058	74543509	81.24	81.27	100329058	75602754	100329058	71650112	1987891649	13.45	1.34	0	5.07	0	0.25	0	0.16	0	0.00	0	3.23	0	93057787	0	202	0	200.15	0	1.90	0	0.01	0	1.41	0	0.01	0	239.28	0	0.27	0	1290781	0	96577946	0	4892622	0	244870	0	152076	0	0	0	3123213	0	20355	0	0	0	233137	0	35489959	0	77133	0	35820584	0	91.29	0	88165165	0	282172	30632405	108.559336149583	96577946.0	93057787.0	1290781.0	4892622.0	244870.0	152076.0	0.0	3123213.0	88165165.0	96.4	1.3	5.1	0.3	0.2	0.0	3.2	91.3	101	101	101.00	38	9754372546	25.6	24.4	24.5	25.5	0.0	34.9	18.1	bulk
922262	SRR1291252	SRP042078	SRS613254	SRX546217	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388410: PDGFRαC Jejunum; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Sorted primary cells|cell type;;PDGFRalpha|source_name;;PDGFRa cells in jejunum|strain;;PdgfraeGFP/+|tissue;;Jejunum	GEO Accession;;GSM1388410		GSM1388410	PDGFRaC Jejunum	14941935200	74709676	2015-07-31 20:26:22	9573373980	14941935200	74709676	2	74709676	index:0,count:74709676,average:100,stdev:0|index:1,count:74709676,average:100,stdev:0	GSM1388410_r1	GEO			in_mesa	26241044	17.03	2.4	0.03	11591079236	11473603134	9950450322	9939482170	98.99	99.89	71488011	68101969	184.238	442.709	146	802721	80.23	93.67	84254447	57353881	84254447	57353881	89.41	89.32	84254447	63917248	84254447	54695113	445679553	3.85	1.21	0	13.73	0	0.25	0	0.03	0	0.00	0	4.04	0	71488011	0	200	0	197.84	0	2.13	0	0.01	0	2.09	0	0.02	0	268.95	0	0.27	0	901384	0	74709676	0	10255753	0	187346	0	18850	0	0	0	3015469	0	13265	0	0	0	147935	0	25434086	0	43897	0	25639183	0	81.96	0	61232258	0	219593	23229313	105.783485812389	74709676.0	71488011.0	901384.0	10255753.0	187346.0	18850.0	0.0	3015469.0	61232258.0	95.7	1.2	13.7	0.3	0.0	0.0	4.0	82.0	100	100	100.00	38	7470967600	25.4	24.7	24.5	25.5	0.0	36.3	20.7	bulk
922271	SRR1291253	SRP042078	SRS613255	SRX546218	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388411: PDGFRαC Colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Sorted primary cells|cell type;;PDGFRalpha|source_name;;PDGFRa cell in colon|strain;;PdgfraeGFP/+|tissue;;Colon	GEO Accession;;GSM1388411		GSM1388411	PDGFRaC Colon	13656309000	68281545	2015-07-31 20:26:22	8847055941	13656309000	68281545	2	68281545	index:0,count:68281545,average:100,stdev:0|index:1,count:68281545,average:100,stdev:0	GSM1388411_r1	GEO			in_mesa	26241044	4.08	2.7	0.07	10442688935	10373795400	9871312711	9854102617	99.34	99.83	65119615	60866359	190.113	556.068	146	596733	84.83	89.85	70604305	55238717	70604305	55238717	86.02	86.34	70604305	56015525	70604305	53079583	935389582	8.96	1.38	0	5.33	0	0.19	0	0.06	0	0.00	0	4.38	0	65119615	0	200	0	197.88	0	1.80	0	0.01	0	1.59	0	0.01	0	238.89	0	0.25	0	942341	0	68281545	0	3640361	0	129173	0	42876	0	0	0	2989881	0	15309	0	0	0	153843	0	29753086	0	46451	0	29968689	0	90.04	0	61479254	0	224450	26356325	117.426264201381	68281545.0	65119615.0	942341.0	3640361.0	129173.0	42876.0	0.0	2989881.0	61479254.0	95.4	1.4	5.3	0.2	0.1	0.0	4.4	90.0	100	100	100.00	38	6828154500	24.7	25.5	25.2	24.6	0.0	36.0	19.9	bulk
922278	SRR1291254	SRP042078	SRS613256	SRX546219	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388412: SM Jejunum; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Unsorted mixed cells|cell type;;SM|source_name;;Jejunum SM|strain;;KitcopGFP/+|tissue;;Jejunum	GEO Accession;;GSM1388412		GSM1388412	SM Jejunum	24062944980	119123490	2015-07-31 20:26:22	17351090389	24062944980	119123490	2	119123490	index:0,count:119123490,average:101,stdev:0|index:1,count:119123490,average:101,stdev:0	GSM1388412_r1	GEO			in_mesa	26241044	8.03	3.78	0.04	17574093885	17598243856	16329181836	16452376110	100.14	100.75	110391488	101755031	187.883	688.518	136	951305	88.63	95.51	121389062	97837423	121389062	97837423	91.71	92.02	121389062	101242873	121389062	94256685	643743730	3.66	1.25	0	6.68	0	0.29	0	0.04	0	0.00	0	7.01	0	110391488	0	202	0	198.82	0	1.84	0	0.01	0	1.37	0	0.01	0	199.00	0	0.55	0	1488544	0	119123490	0	7958410	0	342257	0	44153	0	0	0	8345592	0	25263	0	0	0	308752	0	51856354	0	76430	0	52266799	0	85.99	0	102433078	0	287601	45362502	157.727205399147	119123490.0	110391488.0	1488544.0	7958410.0	342257.0	44153.0	0.0	8345592.0	102433078.0	92.7	1.2	6.7	0.3	0.0	0.0	7.0	86.0	101	101	101.00	38	12031472490	25.4	24.7	24.6	25.3	0.0	33.9	17.2	bulk
922285	SRR1291255	SRP042078	SRS613257	SRX546220	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388413: SM Colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Unsorted mixed cells|cell type;;SM|source_name;;Colon SM|strain;;KitcopGFP/+|tissue;;Colon	GEO Accession;;GSM1388413		GSM1388413	SM Colon	21487145616	106372008	2015-07-31 20:26:22	15521089638	21487145616	106372008	2	106372008	index:0,count:106372008,average:101,stdev:0|index:1,count:106372008,average:101,stdev:0	GSM1388413_r1	GEO			in_mesa	26241044	6.39	3.67	0.04	15767535496	15814774705	14773904448	14903061692	100.3	100.87	98569943	90963008	188.933	678.117	137	835273	87.79	93.8	107604292	86530777	107604292	86530777	89.88	90.11	107604292	88592344	107604292	83128793	850664128	5.40	1.27	0	5.94	0	0.27	0	0.05	0	0.00	0	7.01	0	98569943	0	202	0	198.84	0	1.86	0	0.01	0	1.36	0	0.01	0	231.94	0	0.55	0	1354514	0	106372008	0	6316185	0	286125	0	56911	0	0	0	7459029	0	22846	0	0	0	264572	0	46431042	0	72489	0	46790949	0	86.73	0	92253758	0	290428	40842986	140.630331786191	106372008.0	98569943.0	1354514.0	6316185.0	286125.0	56911.0	0.0	7459029.0	92253758.0	92.7	1.3	5.9	0.3	0.1	0.0	7.0	86.7	101	101	101.00	38	10743572808	25.3	24.8	24.7	25.2	0.0	33.8	17.0	bulk
922292	SRR1291256	SRP042078	SRS613258	SRX546221	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388414: Mu Colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Unsorted mixed cells|cell type;;mucosal|source_name;;Colon mucosa|strain;;PdgfraeGFP/+|tissue;;Colon mucosa	GEO Accession;;GSM1388414		GSM1388414	Mu Colon	16883523600	84417618	2015-07-31 20:26:22	10955988923	16883523600	84417618	2	84417618	index:0,count:84417618,average:100,stdev:0|index:1,count:84417618,average:100,stdev:0	GSM1388414_r1	GEO			in_mesa	26241044	6.74	2.32	0.1	13185308818	13069734809	11953529823	11930659983	99.12	99.81	80180620	74877487	191.220	628.462	146	787243	82.96	91.6	91254684	66515386	91254684	66515386	88.38	88.54	91254684	70867598	91254684	64291353	974471208	7.39	1.04	0	8.96	0	0.28	0	0.08	0	0.00	0	4.66	0	80180620	0	200	0	198.20	0	1.55	0	0.00	0	1.27	0	0.00	0	242.35	0	0.23	0	878002	0	84417618	0	7566047	0	235916	0	71295	0	0	0	3929787	0	20035	0	0	0	242493	0	37339280	0	102215	0	37704023	0	86.02	0	72614573	0	285925	35008939	122.440986272624	84417618.0	80180620.0	878002.0	7566047.0	235916.0	71295.0	0.0	3929787.0	72614573.0	95.0	1.0	9.0	0.3	0.1	0.0	4.7	86.0	100	100	100.00	38	8441761800	25.2	24.8	24.6	25.4	0.0	36.2	20.9	bulk
922300	SRR1291257	SRP042078	SRS613259	SRX546222	SRA165378	GEO		Transcriptome of Smooth Muscle Cells, Interstitial Cells of Cajal and PDGFRa+ Cells	Genome scale expression data on absolute numbers of gene isoforms offer essential clues for cellular functions and biological processes. Gastrointestinal (GI) motility is regulated by smooth muscle cells (SMC) closely contacted with interstitial cells of Cajal (ICC) and fibroblast-like PDGFRa+ cells (PaC), forming an electrical syncytium. To uncover genetic identifies and cellular functions of the cells, we isolated these three cell populations from mouse small intestine and colon, obtained the transcriptome for each type of cells, and built each cell type transcriptome browser. To our knowledge, this is the first genetic resource providing a comprehensive reference for all mRNA transcripts expressed in these unique GI cell populations. Integration of these data with the UCSC genome browser revealed novel cell-specific markers, ion channel and transporter isoforms, and unique cellular and biological functions of these cells in GI physiology. Our transcriptome browsers bring new insight into the alternative expression of genes in different types of the cells and provides references for future functional studies. Overall design: mRNA profiles of SMC, ICC and PDGFRa cells isolated from mouse jejunum and colon were generated by deep sequencing using Illumina Hiseq2000..		GSM1388415: PDGFRαC Mu Colon; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			mirVana miRNA Isolation Kit TruSeq RNA Sample Preparation	Illumina HiSeq 2000	age;;4 weeks|background strain;;C57BL/6|cell population;;Sorted primary cells|cell type;;PDGFRalpha|source_name;;PDGFRa cells in colon mucosa|strain;;PdgfraeGFP/+|tissue;;Colon mucosa	GEO Accession;;GSM1388415		GSM1388415	PDGFRaC Mu Colon	15415150800	77075754	2015-07-31 20:26:22	9978650913	15415150800	77075754	2	77075754	index:0,count:77075754,average:100,stdev:0|index:1,count:77075754,average:100,stdev:0	GSM1388415_r1	GEO			in_mesa	26241044	2.64	2.82	0.06	11985573127	11903819133	11344174764	11315423811	99.32	99.75	74352724	69410587	190.230	566.617	146	719380	84.05	88.9	80948659	62491566	80948659	62491566	85.37	85.62	80948659	63474866	80948659	60183551	1208958388	10.09	1.26	0	5.26	0	0.21	0	0.07	0	0.00	0	3.25	0	74352724	0	200	0	198.03	0	1.68	0	0.01	0	1.54	0	0.01	0	209.89	0	0.23	0	974085	0	77075754	0	4057457	0	163388	0	56349	0	0	0	2503293	0	15851	0	0	0	218286	0	35746535	0	61453	0	36042125	0	91.20	0	70295267	0	260335	32158754	123.528353851768	77075754.0	74352724.0	974085.0	4057457.0	163388.0	56349.0	0.0	2503293.0	70295267.0	96.5	1.3	5.3	0.2	0.1	0.0	3.2	91.2	100	100	100.00	38	7707575400	24.7	25.4	25.2	24.8	0.0	36.1	20.7	bulk
1509257	SRR1382078	SRP043153	SRS634994	SRX591752	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410654: KH2 control, No Dox (E13.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E13.5|source_name;;NSCs|time point;;72 hours|treatment;;No Dox	GEO Accession;;GSM1410654		GSM1410654	KH2 control, No Dox (E13.5)	4379737200	54746715	2015-07-22 17:06:27	3002728111	4379737200	54746715	2	54746715	index:0,count:54746715,average:40,stdev:0|index:1,count:54746715,average:40,stdev:0	GSM1410654_r1	GEO					2.14	3.41	0.06	4129321159	4117962888	3767548257	3785386334	99.72	100.47	52097840	43654809	210.187	1228.370	160	1204379	80.45	88.12	60798875	41911292	60798875	41911292	84.65	84.92	60798875	44099824	60798875	40387617	441839654	10.70	1.17	0	8.29	0	0.62	0	0.20	0	0.00	0	4.02	0	52097840	0	80	0	79.23	0	1.52	0	0.00	0	1.15	0	0.00	0	507.96	0	0.20	0	639762	0	54746715	0	4538373	0	339322	0	108115	0	0	0	2201438	0	4754	0	0	0	36245	0	5117474	0	9407	0	5167880	0	86.87	0	47559467	0	159478	5256623	32.961430416735	54746715.0	52097840.0	639762.0	4538373.0	339322.0	108115.0	0.0	2201438.0	47559467.0	95.2	1.2	8.3	0.6	0.2	0.0	4.0	86.9	40	40	40.00	36	2189868600	23.3	26.7	24.1	25.9	0.0	36.9	24.7	bulk
1509274	SRR1382079	SRP043153	SRS634995	SRX591753	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410655: MSI1, No Dox (E13.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E13.5|source_name;;NSCs|time point;;72 hours|treatment;;No Dox	GEO Accession;;GSM1410655		GSM1410655	MSI1, No Dox (E13.5)	3302467920	41280849	2015-07-22 17:06:27	2266734358	3302467920	41280849	2	41280849	index:0,count:41280849,average:40,stdev:0|index:1,count:41280849,average:40,stdev:0	GSM1410655_r1	GEO					2.86	3.48	0.09	3116624343	3093402927	2861741952	2860727999	99.25	99.96	39294813	33367735	206.070	1159.811	173	691894	76.44	83.21	45283350	30037039	45283350	30037039	80.46	80.39	45283350	31617786	45283350	29017699	478639617	15.36	1.02	0	7.75	0	0.58	0	0.26	0	0.00	0	3.97	0	39294813	0	80	0	79.30	0	1.43	0	0.00	0	1.15	0	0.00	0	493.72	0	0.19	0	419196	0	41280849	0	3198118	0	239405	0	108358	0	0	0	1638273	0	3131	0	0	0	24058	0	3470670	0	6185	0	3504044	0	87.44	0	36096695	0	149133	3566562	23.915310494659	41280849.0	39294813.0	419196.0	3198118.0	239405.0	108358.0	0.0	1638273.0	36096695.0	95.2	1.0	7.7	0.6	0.3	0.0	4.0	87.4	40	40	40.00	36	1651233960	24.1	25.8	23.4	26.7	0.0	36.9	24.9	bulk
1509389	SRR1382080	SRP043153	SRS634996	SRX591754	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410656: MSI1, No Dox, technical replicate (E13.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E13.5|source_name;;NSCs|time point;;72 hours|treatment;;No Dox	GEO Accession;;GSM1410656		GSM1410656	MSI1, No Dox, technical replicate (E13.5)	7273375760	99166757	2014-06-15 12:59:04	4823423729	7273375760	99166757	2	99166757	index:0,count:99166757,average:40,stdev:0|index:1,count:82667637,average:40,stdev:0	GSM1410656_r1	GEO					2.85	3.51	0.09	6909245148	6849467826	6310886428	6306878199	99.13	99.94	79100560	67125241	206.860	1162.434	172	1423311	90.72	98.76	112039897	71759567	112039897	71759567	96.11	95.3	112039897	76025288	112039897	69241390	1065009515	15.41	1.02	0.51	7.79	12.92	0.58	1.20	0.27	0.66	0.00	0.00	3.46	1.14	79100560	16004178	80	40	79.30	39.68	1.43	1.37	0.00	0.00	1.16	1.13	0.00	0.00	528.60	771.39	0.16	0.19	843772	83990	82667637	16499120	6442135	2131836	482888	198019	221868	109190	0	0	2862321	187733	6463	608	0	0	49413	4571	6999124	656696	12272	1056	7067272	662931	87.89	84.08	72658425	13872342	175660	7917172	45.071000796994	99166757.0	95104738.0	927762.0	8573971.0	680907.0	331058.0	0.0	3050054.0	86530767.0	95.9	0.9	8.6	0.7	0.3	0.0	3.1	87.3	40	40	40.00	38	659964800	24.2	25.7	23.3	26.8	0.0	36.8	24.8	bulk
1509405	SRR1382081	SRP043153	SRS634997	SRX591755	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410657: MSI1, DOX (E13.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E13.5|source_name;;NSCs|time point;;72 hours|treatment;;DOX 1ug/ml	GEO Accession;;GSM1410657		GSM1410657	MSI1, DOX (E13.5)	1358203400	19024314	2014-07-20 17:48:08	886830388	1358203400	19024314	2	19024314	index:0,count:19024314,average:40,stdev:0|index:1,count:14930771,average:40,stdev:0	GSM1410657_r1	GEO					2.64	3.25	0.08	1291095459	1280597154	1182270487	1181508276	99.19	99.94	14293259	12091708	209.688	1175.239	170	353004	98.44	106.73	21490715	14070915	21490715	14070915	103.82	102.86	21490715	14839557	21490715	13560884	178759517	13.85	1.00	0.22	7.43	12.53	0.65	1.14	0.24	0.57	0.00	0.00	3.37	1.21	14293259	3974191	80	40	79.29	39.65	1.46	1.37	0.00	0.00	1.13	1.12	0.00	0.00	484.24	491.23	0.13	0.28	149693	8935	14930771	4093543	1109687	512811	97529	46496	36262	23365	0	0	503721	49491	1287	147	0	0	9378	1200	1327785	165741	2338	267	1340788	167355	88.30	84.56	13183572	3461380	126858	1539892	12.138706270003	19024314.0	18267450.0	158628.0	1622498.0	144025.0	59627.0	0.0	553212.0	16644952.0	96.0	0.8	8.5	0.8	0.3	0.0	2.9	87.5	40	40	40.00	38	163741720	23.4	26.2	24.1	26.3	0.0	36.4	23.6	bulk
1509422	SRR1382082	SRP043153	SRS634998	SRX591756	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410658: KH2 control, No Dox (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;No Dox	GEO Accession;;GSM1410658		GSM1410658	KH2 control, No Dox (E12.5)	6260562600	52171355	2015-07-22 17:06:27	4398486372	6260562600	52171355	2	52171355	index:0,count:52171355,average:60,stdev:0|index:1,count:52171355,average:60,stdev:0	GSM1410658_r1	GEO					3.45	4.03	0.03	6027353090	6023071766	5439834646	5475426750	99.93	100.65	50803418	43802863	221.423	1065.175	184	1446500	84.56	93.66	58999102	42959768	58999102	42959768	90.44	90.82	58999102	45947501	58999102	41656324	352144885	5.84	0.94	0	9.46	0	0.67	0	0.07	0	0.00	0	1.89	0	50803418	0	120	0	118.77	0	1.67	0	0.01	0	1.36	0	0.00	0	278.25	0	0.37	0	490937	0	52171355	0	4934950	0	347240	0	35219	0	0	0	985478	0	8261	0	0	0	67999	0	10353310	0	22159	0	10451729	0	87.92	0	45868468	0	195445	10771328	55.111811507074	52171355.0	50803418.0	490937.0	4934950.0	347240.0	35219.0	0.0	985478.0	45868468.0	97.4	0.9	9.5	0.7	0.1	0.0	1.9	87.9	60	60	60.00	38	3130281300	25.4	24.6	24.4	25.6	0.0	36.1	21.0	bulk
1509439	SRR1382083	SRP043153	SRS634999	SRX591757	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410659: KH2 control, Dox (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;DOX 1ug/ml	GEO Accession;;GSM1410659		GSM1410659	KH2 control, Dox (E12.5)	11164592880	93038274	2015-07-22 17:06:27	7807642423	11164592880	93038274	2	93038274	index:0,count:93038274,average:60,stdev:0|index:1,count:93038274,average:60,stdev:0	GSM1410659_r1	GEO					4.4	3.99	0.03	10610925872	10582621196	9545979827	9593249287	99.73	100.5	89432160	78517707	208.289	954.445	175	2942655	83.63	92.92	103798903	74789711	103798903	74789711	89.82	90.1	103798903	80329567	103798903	72522724	677382377	6.38	0.89	0	9.61	0	0.62	0	0.07	0	0.00	0	3.18	0	89432160	0	120	0	118.74	0	1.66	0	0.01	0	1.36	0	0.00	0	326.45	0	0.40	0	825178	0	93038274	0	8942557	0	576495	0	67040	0	0	0	2962579	0	13863	0	0	0	118194	0	17573978	0	38309	0	17744344	0	86.51	0	80489603	0	221556	18253949	82.389775045587	93038274.0	89432160.0	825178.0	8942557.0	576495.0	67040.0	0.0	2962579.0	80489603.0	96.1	0.9	9.6	0.6	0.1	0.0	3.2	86.5	60	60	60.00	38	5582296440	25.6	24.3	24.1	25.9	0.0	36.1	21.3	bulk
1509471	SRR1382085	SRP043153	SRS635001	SRX591759	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410661: MSI1, DOX (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;DOX 1ug/ml	GEO Accession;;GSM1410661		GSM1410661	MSI1, DOX (E12.5)	4041860160	33682168	2015-07-22 17:06:27	2819844121	4041860160	33682168	2	33682168	index:0,count:33682168,average:60,stdev:0|index:1,count:33682168,average:60,stdev:0	GSM1410661_r1	GEO					4.46	3.61	0.07	3850739398	3825259795	3483620148	3485407447	99.34	100.05	32439200	28240989	216.475	1004.338	182	1059634	82.83	91.52	37350095	26868931	37350095	26868931	88.64	88.81	37350095	28753740	37350095	26073068	287105116	7.46	0.78	0	9.15	0	0.57	0	0.10	0	0.00	0	3.03	0	32439200	0	120	0	118.79	0	1.70	0	0.01	0	1.41	0	0.01	0	341.57	0	0.40	0	261653	0	33682168	0	3081412	0	190829	0	32507	0	0	0	1019632	0	4881	0	0	0	41891	0	6196746	0	13790	0	6257308	0	87.16	0	29357788	0	180359	6431776	35.660965075211	33682168.0	32439200.0	261653.0	3081412.0	190829.0	32507.0	0.0	1019632.0	29357788.0	96.3	0.8	9.1	0.6	0.1	0.0	3.0	87.2	60	60	60.00	38	2020930080	25.7	24.2	24.0	26.1	0.0	36.2	21.4	bulk
1509487	SRR1382086	SRP043153	SRS635002	SRX591760	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410662: MSI2, No Dox (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;No Dox	GEO Accession;;GSM1410662		GSM1410662	MSI2, No Dox (E12.5)	6772374480	56436454	2015-07-22 17:06:27	4729401363	6772374480	56436454	2	56436454	index:0,count:56436454,average:60,stdev:0|index:1,count:56436454,average:60,stdev:0	GSM1410662_r1	GEO					3.69	3.8	0.07	6537192854	6513872576	5880536475	5904162309	99.64	100.4	55042062	47723347	218.060	1018.527	182	1753553	83.29	92.55	64213050	45842693	64213050	45842693	89.52	89.82	64213050	49273887	64213050	44487907	445068363	6.81	0.79	0	9.76	0	0.74	0	0.09	0	0.00	0	1.64	0	55042062	0	120	0	118.85	0	1.58	0	0.01	0	1.31	0	0.00	0	366.74	0	0.34	0	443580	0	56436454	0	5509621	0	417817	0	50887	0	0	0	925688	0	8629	0	0	0	75000	0	11019873	0	23240	0	11126742	0	87.77	0	49532441	0	196589	11471234	58.351352313710	56436454.0	55042062.0	443580.0	5509621.0	417817.0	50887.0	0.0	925688.0	49532441.0	97.5	0.8	9.8	0.7	0.1	0.0	1.6	87.8	60	60	60.00	38	3386187240	25.6	24.3	24.2	25.9	0.0	36.1	21.2	bulk
1509502	SRR1382087	SRP043153	SRS635003	SRX591761	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410663: MSI2, DOX (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;DOX 1ug/ml	GEO Accession;;GSM1410663		GSM1410663	MSI2, DOX (E12.5)	8152982280	67941519	2015-07-22 17:06:27	5714896514	8152982280	67941519	2	67941519	index:0,count:67941519,average:60,stdev:0|index:1,count:67941519,average:60,stdev:0	GSM1410663_r1	GEO					4.44	3.63	0.06	7877604474	7848384788	7041275974	7070826349	99.63	100.42	66317653	59366207	192.510	817.221	163	1933705	83.01	92.83	77848467	55052050	77848467	55052050	89.68	89.95	77848467	59471369	77848467	53343856	504167027	6.40	0.73	0	10.33	0	0.70	0	0.09	0	0.00	0	1.60	0	66317653	0	120	0	118.85	0	1.61	0	0.01	0	1.33	0	0.00	0	375.71	0	0.34	0	499068	0	67941519	0	7015477	0	478227	0	59731	0	0	0	1085908	0	10165	0	0	0	93267	0	13376329	0	27377	0	13507138	0	87.28	0	59302176	0	206788	13903989	67.237890980134	67941519.0	66317653.0	499068.0	7015477.0	478227.0	59731.0	0.0	1085908.0	59302176.0	97.6	0.7	10.3	0.7	0.1	0.0	1.6	87.3	60	60	60.00	38	4076491140	25.5	24.4	24.2	25.9	0.0	36.1	21.1	bulk
1509518	SRR1382088	SRP043153	SRS635004	SRX591762	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410664: Cre-less Msi1/Msi2 floxed control line C1, No Tam (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;48 hours|treatment;;No 4-OHT	GEO Accession;;GSM1410664		GSM1410664	Cre-less Msi1/Msi2 floxed control line C1, No Tam (E12.5)	12919499040	107662492	2015-07-22 17:06:27	9117771894	12919499040	107662492	2	107662492	index:0,count:107662492,average:60,stdev:0|index:1,count:107662492,average:60,stdev:0	GSM1410664_r1	GEO					4.77	3.49	0.05	12543176436	12563938806	11443919300	11532304321	100.17	100.77	105395092	93194643	197.927	884.878	163	3523300	86.75	95.04	119501355	91425720	119501355	91425720	91.65	92.08	119501355	96594275	119501355	88585995	565817122	4.51	0.13	0	8.54	0	0.29	0	0.08	0	0.00	0	1.74	0	105395092	0	120	0	118.97	0	1.58	0	0.01	0	1.31	0	0.00	0	329.58	0	0.41	0	134601	0	107662492	0	9193277	0	313424	0	81040	0	0	0	1872936	0	17868	0	0	0	145418	0	22232083	0	40199	0	22435568	0	89.35	0	96201815	0	238295	22963454	96.365656014604	107662492.0	105395092.0	134601.0	9193277.0	313424.0	81040.0	0.0	1872936.0	96201815.0	97.9	0.1	8.5	0.3	0.1	0.0	1.7	89.4	60	60	60.00	38	6459749520	25.0	24.1	24.0	26.9	0.0	35.9	20.9	bulk
1509533	SRR1382089	SRP043153	SRS635005	SRX591763	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410665: Cre-less Msi1/Msi2 floxed control line C1, TAM (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;48 hours|treatment;;4-OHT	GEO Accession;;GSM1410665		GSM1410665	Cre-less Msi1/Msi2 floxed control line C1, TAM (E12.5)	11463141960	95526183	2015-07-22 17:06:27	8108899501	11463141960	95526183	2	95526183	index:0,count:95526183,average:60,stdev:0|index:1,count:95526183,average:60,stdev:0	GSM1410665_r1	GEO					4.66	3.53	0.06	11113335260	11125253529	10145442879	10218973537	100.11	100.72	93397742	83260986	191.494	838.858	160	3127428	86.42	94.63	105943581	80718363	105943581	80718363	91.25	91.67	105943581	85230029	105943581	78193601	543785765	4.89	0.14	0	8.48	0	0.30	0	0.07	0	0.00	0	1.85	0	93397742	0	120	0	118.95	0	1.56	0	0.01	0	1.31	0	0.00	0	338.81	0	0.42	0	134685	0	95526183	0	8096552	0	286450	0	71139	0	0	0	1770852	0	15707	0	0	0	129039	0	19674555	0	37070	0	19856371	0	89.30	0	85301190	0	232100	20329027	87.587363205515	95526183.0	93397742.0	134685.0	8096552.0	286450.0	71139.0	0.0	1770852.0	85301190.0	97.8	0.1	8.5	0.3	0.1	0.0	1.9	89.3	60	60	60.00	38	5731570980	24.9	24.1	24.1	26.9	0.0	35.9	20.8	bulk
1509644	SRR1382090	SRP043153	SRS635006	SRX591764	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410666: Cre-carrying Msi1/Msi2 floxed line C4, No Tam (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;48 hours|treatment;;No 4-OHT	GEO Accession;;GSM1410666		GSM1410666	Cre-carrying Msi1/Msi2 floxed line C4, No Tam (E12.5)	10527444600	87728705	2015-07-22 17:06:27	7411350377	10527444600	87728705	2	87728705	index:0,count:87728705,average:60,stdev:0|index:1,count:87728705,average:60,stdev:0	GSM1410666_r1	GEO					4.8	3.58	0.05	10257389970	10266838068	9356453505	9422850943	100.09	100.71	86267029	78060914	180.898	743.906	152	2666942	86.11	94.37	98031381	74287379	98031381	74287379	90.98	91.39	98031381	78489705	98031381	71949104	527112525	5.14	0.12	0	8.60	0	0.30	0	0.07	0	0.00	0	1.29	0	86267029	0	120	0	118.86	0	1.56	0	0.01	0	1.31	0	0.00	0	327.96	0	0.38	0	105372	0	87728705	0	7543745	0	265441	0	65749	0	0	0	1130486	0	13892	0	0	0	118076	0	17986012	0	33661	0	18151641	0	89.73	0	78723284	0	226403	18574533	82.041903154994	87728705.0	86267029.0	105372.0	7543745.0	265441.0	65749.0	0.0	1130486.0	78723284.0	98.3	0.1	8.6	0.3	0.1	0.0	1.3	89.7	60	60	60.00	38	5263722300	25.1	23.9	23.7	27.0	0.2	35.9	20.7	bulk
1509662	SRR1382091	SRP043153	SRS635007	SRX591765	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410667: Cre-carrying Msi1/Msi2 floxed line C4, TAM (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;48 hours|treatment;;4-OHT	GEO Accession;;GSM1410667		GSM1410667	Cre-carrying Msi1/Msi2 floxed line C4, TAM (E12.5)	12793216560	106610138	2015-07-22 17:06:27	9005458277	12793216560	106610138	2	106610138	index:0,count:106610138,average:60,stdev:0|index:1,count:106610138,average:60,stdev:0	GSM1410667_r1	GEO					5.0	3.57	0.06	12415044541	12438813891	11282299214	11376904926	100.19	100.84	104431171	93705110	183.652	797.693	154	4087491	86.62	95.27	119466961	90456836	119466961	90456836	91.81	92.24	119466961	95873283	119466961	87579239	534426177	4.30	0.12	0	8.90	0	0.34	0	0.07	0	0.00	0	1.63	0	104431171	0	120	0	118.83	0	1.58	0	0.01	0	1.31	0	0.00	0	329.16	0	0.38	0	130455	0	106610138	0	9484202	0	366710	0	72806	0	0	0	1739451	0	17907	0	0	0	151785	0	22950317	0	40391	0	23160400	0	89.06	0	94946969	0	228238	23713391	103.897646316564	106610138.0	104431171.0	130455.0	9484202.0	366710.0	72806.0	0.0	1739451.0	94946969.0	98.0	0.1	8.9	0.3	0.1	0.0	1.6	89.1	60	60	60.00	38	6396608280	24.5	24.1	24.3	26.8	0.2	35.9	20.6	bulk
1509677	SRR1382092	SRP043153	SRS635008	SRX591766	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410668: Ribo-Seq KH2 control, No Dox (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Ribosome profiling library	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;No Dox	GEO Accession;;GSM1410668		GSM1410668	Ribo-Seq KH2 control, No Dox (E12.5)	1871743252	40972587	2015-07-22 17:06:27	1270988105	1871743252	40972587	1	40972587	index:0,count:40972587,average:45.68,stdev:5.50	GSM1410668_r1	GEO					0.52	4.95	0.17	644688250	387307110	292511873	208762126	60.08	71.37	0	0	0	0	0	0	19.51	44.78	48582478	3586207	48582478	3586207	25.83	38.3	48582478	4747621	48582478	3067316	183579780	28.48	9.52	0	25.32	0	1.99	0	0.54	0	0.00	0	52.60	0	18383317	0	45	0	36.52	0	1.60	0	0.00	0	1.00	0	0.00	0	335.99	0	3.71	0	3902630	0	40972587	0	10374506	0	813515	0	222681	0	0	0	21553074	0	2532	0	0	0	33220	0	136918	0	428631	0	601301	0	19.55	0	8008811	0	9806	227905	23.241382826841	40972587.0	18383317.0	3902630.0	10374506.0	813515.0	222681.0	0.0	21553074.0	8008811.0	44.9	9.5	25.3	2.0	0.5	0.0	52.6	19.5	40	51	45.68	36	1871743252	43.7	19.5	22.5	14.1	0.2	34.7	18.0	bulk
1509693	SRR1382093	SRP043153	SRS635009	SRX591767	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410669: Ribo-Seq KH2 control, DOX (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Ribosome profiling library	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;DOX 1ug/ml	GEO Accession;;GSM1410669		GSM1410669	Ribo-Seq KH2 control, DOX (E12.5)	2283334195	50509297	2015-07-22 17:06:27	1544919544	2283334195	50509297	1	50509297	index:0,count:50509297,average:45.21,stdev:5.49	GSM1410669_r1	GEO					0.57	6.06	0.12	836075758	523081519	421744187	316367226	62.56	75.01	0	0	0	0	0	0	22.77	46.45	59174169	5497464	59174169	5497464	25.13	41.41	59174169	6067007	59174169	4900646	268478992	32.11	9.05	0	24.37	0	2.00	0	0.41	0	0.00	0	49.79	0	24143496	0	45	0	35.63	0	1.53	0	0.00	0	1.00	0	0.00	0	342.44	0	3.79	0	4570570	0	50509297	0	12308308	0	1011125	0	206568	0	0	0	25148108	0	3445	0	0	0	15949	0	140670	0	435482	0	595546	0	23.43	0	11835188	0	9496	232078	24.439553496209	50509297.0	24143496.0	4570570.0	12308308.0	1011125.0	206568.0	0.0	25148108.0	11835188.0	47.8	9.0	24.4	2.0	0.4	0.0	49.8	23.4	40	51	45.21	36	2283334195	42.1	20.0	23.1	14.6	0.2	34.8	18.8	bulk
1509710	SRR1382094	SRP043153	SRS635010	SRX591768	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410670: Ribo-Seq MSI1, No Dox (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Ribosome profiling library	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;No Dox	GEO Accession;;GSM1410670		GSM1410670	Ribo-Seq MSI1, No Dox (E12.5)	6210768232	134834145	2015-07-22 17:06:27	4218971196	6210768232	134834145	1	134834145	index:0,count:134834145,average:46.06,stdev:5.47	GSM1410670_r1	GEO					0.4	5.84	0.16	2113872623	1396295948	1089523533	812186772	66.05	74.55	0	0	0	0	0	0	22.39	44.99	137398454	13474656	137398454	13474656	24.86	39.41	137398454	14965810	137398454	11804318	740166955	35.01	10.45	0	22.43	0	1.77	0	0.33	0	0.00	0	53.26	0	60190896	0	46	0	36.38	0	1.17	0	0.00	0	1.00	0	0.00	0	375.41	0	3.91	0	14088943	0	134834145	0	30238584	0	2383675	0	440954	0	0	0	71818620	0	11284	0	0	0	50407	0	423239	0	1306482	0	1791412	0	22.21	0	29952312	0	19842	710044	35.784900715654	134834145.0	60190896.0	14088943.0	30238584.0	2383675.0	440954.0	0.0	71818620.0	29952312.0	44.6	10.4	22.4	1.8	0.3	0.0	53.3	22.2	40	51	46.06	36	6210768232	42.5	20.0	23.1	14.3	0.2	34.5	18.3	bulk
1509725	SRR1382095	SRP043153	SRS635011	SRX591769	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410671: Ribo-Seq MSI1, DOX (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Ribosome profiling library	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;DOX 1ug/ml	GEO Accession;;GSM1410671		GSM1410671	Ribo-Seq MSI1, DOX (E12.5)	1670313461	36926595	2015-07-22 17:06:27	1133896826	1670313461	36926595	1	36926595	index:0,count:36926595,average:45.23,stdev:5.49	GSM1410671_r1	GEO					0.53	5.1	0.17	585204279	374630429	286640517	216567819	64.02	75.55	0	0	0	0	0	0	23.28	49.04	41692999	3954201	41692999	3954201	26.59	41.69	41692999	4516749	41692999	3361538	178454482	30.49	9.53	0	24.17	0	1.81	0	0.43	0	0.00	0	51.76	0	16988331	0	45	0	35.55	0	1.25	0	0.00	0	1.00	0	0.00	0	404.06	0	3.70	0	3518289	0	36926595	0	8925005	0	668361	0	158205	0	0	0	19111698	0	2848	0	0	0	21644	0	119608	0	399930	0	544030	0	21.84	0	8063326	0	9730	248533	25.542959917780	36926595.0	16988331.0	3518289.0	8925005.0	668361.0	158205.0	0.0	19111698.0	8063326.0	46.0	9.5	24.2	1.8	0.4	0.0	51.8	21.8	40	51	45.23	36	1670313461	43.3	19.3	22.7	14.5	0.2	34.8	18.2	bulk
1509742	SRR1382096	SRP043153	SRS635012	SRX591770	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410672: Ribo-Seq Cre-less Msi1/Msi2 floxed control line C1, No Tam (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Ribosome profiling library	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;48 hours|treatment;;No 4-OHT	GEO Accession;;GSM1410672		GSM1410672	Ribo-Seq Cre-less Msi1/Msi2 floxed control line C1, No Tam (E12.5)	3196175320	79904383	2015-07-22 17:06:27	2246289630	3196175320	79904383	1	79904383	index:0,count:79904383,average:40,stdev:0	GSM1410672_r1	GEO					1.73	4.75	0.05	1558160607	1205582962	939317991	834378341	77.37	88.83	0	0	0	0	0	0	38.77	65.14	111126987	19060204	111126987	19060204	42.71	61.17	111126987	21000051	111126987	17899938	425541747	27.31	3.74	0	24.91	0	2.53	0	0.57	0	0.00	0	35.37	0	49166687	0	40	0	32.10	0	1.77	0	0.00	0	1.00	0	0.00	0	385.08	0	3.57	0	2985229	0	79904383	0	19905684	0	2023074	0	453205	0	0	0	28261417	0	464	0	0	0	6903	0	108795	0	165477	0	281639	0	36.62	0	29261003	0	12671	133103	10.504537921237	79904383.0	49166687.0	2985229.0	19905684.0	2023074.0	453205.0	0.0	28261417.0	29261003.0	61.5	3.7	24.9	2.5	0.6	0.0	35.4	36.6	40	40	40.00	36	3196175320	37.3	21.4	23.4	17.1	0.8	35.6	21.2	bulk
1509757	SRR1382097	SRP043153	SRS635013	SRX591771	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410673: Ribo-Seq Cre-less Msi1/Msi2 floxed control line C1, TAM (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Ribosome profiling library	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;48 hours|treatment;;4-OHT	GEO Accession;;GSM1410673		GSM1410673	Ribo-Seq Cre-less Msi1/Msi2 floxed control line C1, TAM (E12.5)	4961770600	124044265	2015-07-22 17:06:27	3345824492	4961770600	124044265	1	124044265	index:0,count:124044265,average:40,stdev:0	GSM1410673_r1	GEO					0.68	6.4	0.22	1740236195	905193498	787786553	489667274	52.02	62.16	0	0	0	0	0	0	19.71	44.92	158002672	10688107	158002672	10688107	22.7	40.67	158002672	12309250	158002672	9677688	421456117	24.22	5.73	0	24.54	0	2.68	0	0.79	0	0.00	0	52.81	0	54229491	0	40	0	33.11	0	1.75	0	0.00	0	1.00	0	0.00	0	290.73	0	3.93	0	7112461	0	124044265	0	30436637	0	3328390	0	981001	0	0	0	65505383	0	1144	0	0	0	40286	0	311055	0	456274	0	808759	0	19.18	0	23792854	0	20259	759855	37.507033910854	124044265.0	54229491.0	7112461.0	30436637.0	3328390.0	981001.0	0.0	65505383.0	23792854.0	43.7	5.7	24.5	2.7	0.8	0.0	52.8	19.2	40	40	40.00	36	4961770600	34.7	25.0	23.3	16.4	0.6	35.6	18.3	bulk
1509772	SRR1382098	SRP043153	SRS635014	SRX591772	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410674: Ribo-Seq Cre-carrying Msi1/Msi2 floxed line C4, No Tam (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Ribosome profiling library	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;48 hours|treatment;;No 4-OHT	GEO Accession;;GSM1410674		GSM1410674	Ribo-Seq Cre-carrying Msi1/Msi2 floxed line C4, No Tam (E12.5)	6083985600	152099640	2015-07-22 17:06:27	4133265752	6083985600	152099640	1	152099640	index:0,count:152099640,average:40,stdev:0	GSM1410674_r1	GEO					0.46	6.83	0.15	2149676072	1241443482	1027672957	690503614	57.75	67.19	0	0	0	0	0	0	23.23	50.12	181075644	15517445	181075644	15517445	25.37	39.76	181075644	16944150	181075644	12309984	487338414	22.67	5.64	0	23.56	0	2.53	0	0.75	0	0.00	0	52.81	0	66790096	0	40	0	33.19	0	1.65	0	0.00	0	1.00	0	0.00	0	324.38	0	4.23	0	8579530	0	152099640	0	35828415	0	3851874	0	1141294	0	0	0	80316376	0	1227	0	0	0	47285	0	424836	0	543526	0	1016874	0	20.36	0	30961681	0	19819	797918	40.260255310561	152099640.0	66790096.0	8579530.0	35828415.0	3851874.0	1141294.0	0.0	80316376.0	30961681.0	43.9	5.6	23.6	2.5	0.8	0.0	52.8	20.4	40	40	40.00	36	6083985600	35.4	24.8	22.7	16.4	0.6	36.0	20.0	bulk
1509789	SRR1382099	SRP043153	SRS635015	SRX591773	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410675: Ribo-Seq Cre-carrying Msi1/Msi2 floxed line C4, TAM (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Ribosome profiling library	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;48 hours|treatment;;4-OHT	GEO Accession;;GSM1410675		GSM1410675	Ribo-Seq Cre-carrying Msi1/Msi2 floxed line C4, TAM (E12.5)	5734376720	143359418	2015-07-22 17:06:27	3890089371	5734376720	143359418	1	143359418	index:0,count:143359418,average:40,stdev:0	GSM1410675_r1	GEO					0.48	7.19	0.19	1953271737	1021275660	888051532	514131886	52.29	57.89	0	0	0	0	0	0	20.84	47.4	165330318	12606306	165330318	12606306	25.54	41.77	165330318	15447654	165330318	11109840	414974804	21.25	5.85	0	23.64	0	1.88	0	0.87	0	0.00	0	55.05	0	60491925	0	40	0	33.39	0	1.69	0	0.00	0	1.00	0	0.00	0	367.33	0	4.26	0	8381290	0	143359418	0	33896158	0	2701087	0	1246262	0	0	0	78920144	0	1162	0	0	0	40337	0	308389	0	526257	0	876145	0	18.55	0	26595767	0	17272	566426	32.794465030107	143359418.0	60491925.0	8381290.0	33896158.0	2701087.0	1246262.0	0.0	78920144.0	26595767.0	42.2	5.8	23.6	1.9	0.9	0.0	55.1	18.6	40	40	40.00	36	5734376720	34.2	25.7	23.0	16.4	0.7	36.1	20.3	bulk
3018896	SRR1382084	SRP043153	SRS635000	SRX591758	SRA170153	GEO		Musashi proteins are post-transcriptional regulators of the epithelial-luminal cell state	mRNA-seq and ribosome profiling of neural stem cells overexpressing or knocked out for Musashi RNA-binding proteins Overall design: Study of the global effects of Musashi (Msi) proteins on the transcriptome of embryonic neural stem cells. Neural stem cells were derived from brains of E12.5 or E13.5 embryos engineered to have inducible Msi1 or Msi2 genes, or from embryos with double floxed alleles of Msi1 and Msi2 carrying a Tamoxifen-induclble Cre (CreER). The overexpression mice were made using the Flp-in system (OpenBioSystems), where a cDNA of interest (in this case Msi1 or Msi2) is knocked into the Collagen (Col1A1) locus. The expression of the cDNA of interest is driven by m2rTTA that is knocked into the Rosa26 locus (R26). KH2 describes a strain containing the R26-m2rTTA but lacking Msi1 or Msi2 cDNA. MSI1 describes a strain containing R26-m2rTTA and Msi1 cDNA in Col1A1. MSI2 describes a strain containing R26-m2rTTA and Msi2 cDNA in Col1A1. C1 describes a strain lacking the CreER allele but containing double floxed alleles of Msi1/Msi2 (used as Tamoxifen control). C4 describes a strain carrying the CreER allele and double floxed alleles of Msi1/Msi2.		GSM1410660: MSI1, No Dox (E12.5); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Poly(A)+ RNA was selected by oligo-dT magnetic beads, and prepared for paired end RNA sequencing using Illumina paired end sequencing primers.	Illumina HiSeq 2000	developmental stage;;E12.5|source_name;;NSCs|time point;;72 hours|treatment;;No Dox	GEO Accession;;GSM1410660		GSM1410660	MSI1, No Dox (E12.5)	10483283760	87360698	2015-07-22 17:06:27	7328975616	10483283760	87360698	2	87360698	index:0,count:87360698,average:60,stdev:0|index:1,count:87360698,average:60,stdev:0	GSM1410660_r1	GEO					3.5	3.79	0.07	9967571404	9937833507	9039956175	9075767128	99.7	100.4	84014344	73218966	214.563	1011.889	179	1884941	83.56	92.1	96960716	70201395	96960716	70201395	89.07	89.33	96960716	74831924	96960716	68088521	720269194	7.23	0.81	0	8.92	0	0.60	0	0.08	0	0.00	0	3.15	0	84014344	0	120	0	118.75	0	1.69	0	0.01	0	1.40	0	0.00	0	294.47	0	0.41	0	703267	0	87360698	0	7790664	0	523868	0	72244	0	0	0	2750242	0	12668	0	0	0	109564	0	16352364	0	35970	0	16510566	0	87.25	0	76223680	0	222747	16994854	76.296668417532	87360698.0	84014344.0	703267.0	7790664.0	523868.0	72244.0	0.0	2750242.0	76223680.0	96.2	0.8	8.9	0.6	0.1	0.0	3.1	87.3	60	60	60.00	38	5241641880	25.5	24.4	24.2	25.8	0.0	36.1	21.2	bulk
1913498	SRR1574329	SRP047079	SRS700492	SRX700307	SRA184282	GEO		MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancers (RNA-Seq)	Organismal development requires the precise coordination of genetic programs to regulate cell fate and function. MEF2 transcription factors play essential roles in this process but how these broadly expressed factors contribute to the generation of specific cell types during development is poorly understood.  Here we show that despite being expressed in virtually all mammalian tissues, in the retina MEF2D binds to retina-specific enhancers and controls photoreceptor cell development. MEF2D achieves specificity by cooperating with a retina-specific factor CRX, which recruits MEF2D away from canonical MEF2 binding sites, and redirects it to retina-specific enhancers that lack the consensus MEF2 sequence.  Once bound to retina-specific enhancers, MEF2D and CRX co-activate the expression of photoreceptor-specific genes that are critical for retinal function. These findings demonstrate that broadly expressed TFs acquire specific functions through competitive recruitment to enhancers by tissue-specific TFs, and through cooperative activation of these enhancers to regulate tissue-specific genes. Overall design: Total RNA-seq data from WT, Mef2d KO and Crx KO P11 mouse retinae		GSM1503669: P11_WT_Retina_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Retinae were dissected from p11 knockout or wild-type littermate controls. Both retinae from each animal were pooled for each sample.  RNA was extracted using trizol and Qiagen Rneasy purification with on-column DNase digestion. Illumina library construction and sequencing was carried out as follows: total RNA was depleted of ribosomal RNA using the Ribozero rRNA removal kit (Epicentre), heat-fragmented to 200-700 bp in length and cloned using Uricil-N-Glycosylase-based strand-specific cloning. cDNA fragments were sequenced using an Illumina HiSeq 2000 Strand-specific, rRNA depleted total RNA, Paired (WT vs. Mef2d KO) or single-end (WT vs. Crx KO) 49 bp sequencing	Illumina HiSeq 2000	age;;postnatal day 11|gender;;male|genotype;;wild type|source_name;;Retina, postnatal day 11, male|tissue;;retina	GEO Accession;;GSM1503669		GSM1503669	P11_WT_Retina_1	19460430000	108113500	2015-07-22 17:06:50	13328237530	19460430000	108113500	2	108113500	index:0,count:108113500,average:90,stdev:0|index:1,count:108113500,average:90,stdev:0	GSM1503669_r1	GEO					1.04	2.6	0.07	14126775077	13810195869	12657745022	12392071876	97.76	97.9	102091087	97672186	152.855	482.607	119	1399092	61.92	69.05	120030668	63210953	120030668	63210953	66.36	65.45	120030668	67749906	120030668	59916488	3711814761	26.28	0.99	0	9.76	0	3.59	0	0.27	0	0.00	0	1.72	0	102091087	0	180	0	178.87	0	1.74	0	0.01	0	1.29	0	0.00	0	149.47	0	0.19	0	1067537	0	108113500	0	10550810	0	3876483	0	287344	0	0	0	1858586	0	20259	0	0	0	206366	0	24903993	0	76588	0	25207206	0	84.67	0	91540277	0	279089	20960200	75.102207539530	108113500.0	102091087.0	1067537.0	10550810.0	3876483.0	287344.0	0.0	1858586.0	91540277.0	94.4	1.0	9.8	3.6	0.3	0.0	1.7	84.7	90	90	90.00	38	9730215000	24.3	24.1	23.7	27.9	0.0	36.0	22.6	bulk
1913612	SRR1574330	SRP047079	SRS700494	SRX700308	SRA184282	GEO		MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancers (RNA-Seq)	Organismal development requires the precise coordination of genetic programs to regulate cell fate and function. MEF2 transcription factors play essential roles in this process but how these broadly expressed factors contribute to the generation of specific cell types during development is poorly understood.  Here we show that despite being expressed in virtually all mammalian tissues, in the retina MEF2D binds to retina-specific enhancers and controls photoreceptor cell development. MEF2D achieves specificity by cooperating with a retina-specific factor CRX, which recruits MEF2D away from canonical MEF2 binding sites, and redirects it to retina-specific enhancers that lack the consensus MEF2 sequence.  Once bound to retina-specific enhancers, MEF2D and CRX co-activate the expression of photoreceptor-specific genes that are critical for retinal function. These findings demonstrate that broadly expressed TFs acquire specific functions through competitive recruitment to enhancers by tissue-specific TFs, and through cooperative activation of these enhancers to regulate tissue-specific genes. Overall design: Total RNA-seq data from WT, Mef2d KO and Crx KO P11 mouse retinae		GSM1503670: P11_WT_Retina_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Retinae were dissected from p11 knockout or wild-type littermate controls. Both retinae from each animal were pooled for each sample.  RNA was extracted using trizol and Qiagen Rneasy purification with on-column DNase digestion. Illumina library construction and sequencing was carried out as follows: total RNA was depleted of ribosomal RNA using the Ribozero rRNA removal kit (Epicentre), heat-fragmented to 200-700 bp in length and cloned using Uricil-N-Glycosylase-based strand-specific cloning. cDNA fragments were sequenced using an Illumina HiSeq 2000 Strand-specific, rRNA depleted total RNA, Paired (WT vs. Mef2d KO) or single-end (WT vs. Crx KO) 49 bp sequencing	Illumina HiSeq 2000	age;;postnatal day 11|gender;;female|genotype;;wild type|source_name;;Retina, postnatal day 11, female|tissue;;retina	GEO Accession;;GSM1503670		GSM1503670	P11_WT_Retina_2	19080685620	106003809	2015-07-22 17:06:50	12862013484	19080685620	106003809	2	106003809	index:0,count:106003809,average:90,stdev:0|index:1,count:106003809,average:90,stdev:0	GSM1503670_r1	GEO					0.91	2.57	0.03	14027229596	13712337198	12400089246	12131545503	97.76	97.83	99155103	95177701	155.512	464.665	127	1289506	59.73	67.49	118582608	59228416	118582608	59228416	65.37	63.94	118582608	64821291	118582608	56109564	3838242843	27.36	0.82	0	10.75	0	4.60	0	0.30	0	0.00	0	1.56	0	99155103	0	180	0	178.93	0	1.58	0	0.01	0	1.26	0	0.00	0	317.22	0	0.15	0	865612	0	106003809	0	11399864	0	4880539	0	313532	0	0	0	1654635	0	19314	0	0	0	194442	0	23226454	0	71552	0	23511762	0	82.78	0	87755239	0	277434	20020106	72.161688906190	106003809.0	99155103.0	865612.0	11399864.0	4880539.0	313532.0	0.0	1654635.0	87755239.0	93.5	0.8	10.8	4.6	0.3	0.0	1.6	82.8	90	90	90.00	38	9540342810	24.3	24.2	24.0	27.5	0.0	36.2	23.2	bulk
1913629	SRR1574331	SRP047079	SRS700493	SRX700309	SRA184282	GEO		MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancers (RNA-Seq)	Organismal development requires the precise coordination of genetic programs to regulate cell fate and function. MEF2 transcription factors play essential roles in this process but how these broadly expressed factors contribute to the generation of specific cell types during development is poorly understood.  Here we show that despite being expressed in virtually all mammalian tissues, in the retina MEF2D binds to retina-specific enhancers and controls photoreceptor cell development. MEF2D achieves specificity by cooperating with a retina-specific factor CRX, which recruits MEF2D away from canonical MEF2 binding sites, and redirects it to retina-specific enhancers that lack the consensus MEF2 sequence.  Once bound to retina-specific enhancers, MEF2D and CRX co-activate the expression of photoreceptor-specific genes that are critical for retinal function. These findings demonstrate that broadly expressed TFs acquire specific functions through competitive recruitment to enhancers by tissue-specific TFs, and through cooperative activation of these enhancers to regulate tissue-specific genes. Overall design: Total RNA-seq data from WT, Mef2d KO and Crx KO P11 mouse retinae		GSM1503671: P11_Mef2d_KO_Retina_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Retinae were dissected from p11 knockout or wild-type littermate controls. Both retinae from each animal were pooled for each sample.  RNA was extracted using trizol and Qiagen Rneasy purification with on-column DNase digestion. Illumina library construction and sequencing was carried out as follows: total RNA was depleted of ribosomal RNA using the Ribozero rRNA removal kit (Epicentre), heat-fragmented to 200-700 bp in length and cloned using Uricil-N-Glycosylase-based strand-specific cloning. cDNA fragments were sequenced using an Illumina HiSeq 2000 Strand-specific, rRNA depleted total RNA, Paired (WT vs. Mef2d KO) or single-end (WT vs. Crx KO) 49 bp sequencing	Illumina HiSeq 2000	age;;postnatal day 11|gender;;male|genotype;;Mef2d KO|source_name;;Retina, postnatal day 11, male|tissue;;retina	GEO Accession;;GSM1503671		GSM1503671	P11_Mef2d_KO_Retina_1	18814480560	104524892	2015-07-22 17:06:50	12877542151	18814480560	104524892	2	104524892	index:0,count:104524892,average:90,stdev:0|index:1,count:104524892,average:90,stdev:0	GSM1503671_r1	GEO					0.82	2.52	0.07	13841179290	13538533490	12365499570	12109343785	97.81	97.93	99381708	95146150	153.982	480.945	118	1314061	61.4	68.7	116994288	61018616	116994288	61018616	66.04	65.22	116994288	65630569	116994288	57923633	3682699713	26.61	0.96	0	10.11	0	2.89	0	0.27	0	0.00	0	1.76	0	99381708	0	180	0	178.87	0	1.59	0	0.01	0	1.28	0	0.00	0	383.19	0	0.17	0	1004089	0	104524892	0	10563533	0	3020487	0	279606	0	0	0	1843091	0	20367	0	0	0	204254	0	24477148	0	80271	0	24782040	0	84.97	0	88818175	0	280990	20750887	73.849201039183	104524892.0	99381708.0	1004089.0	10563533.0	3020487.0	279606.0	0.0	1843091.0	88818175.0	95.1	1.0	10.1	2.9	0.3	0.0	1.8	85.0	90	90	90.00	38	9407240280	24.2	24.3	24.0	27.6	0.0	36.1	22.7	bulk
1913644	SRR1574332	SRP047079	SRS700495	SRX700310	SRA184282	GEO		MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancers (RNA-Seq)	Organismal development requires the precise coordination of genetic programs to regulate cell fate and function. MEF2 transcription factors play essential roles in this process but how these broadly expressed factors contribute to the generation of specific cell types during development is poorly understood.  Here we show that despite being expressed in virtually all mammalian tissues, in the retina MEF2D binds to retina-specific enhancers and controls photoreceptor cell development. MEF2D achieves specificity by cooperating with a retina-specific factor CRX, which recruits MEF2D away from canonical MEF2 binding sites, and redirects it to retina-specific enhancers that lack the consensus MEF2 sequence.  Once bound to retina-specific enhancers, MEF2D and CRX co-activate the expression of photoreceptor-specific genes that are critical for retinal function. These findings demonstrate that broadly expressed TFs acquire specific functions through competitive recruitment to enhancers by tissue-specific TFs, and through cooperative activation of these enhancers to regulate tissue-specific genes. Overall design: Total RNA-seq data from WT, Mef2d KO and Crx KO P11 mouse retinae		GSM1503672: P11_Mef2d_KO_Retina_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Retinae were dissected from p11 knockout or wild-type littermate controls. Both retinae from each animal were pooled for each sample.  RNA was extracted using trizol and Qiagen Rneasy purification with on-column DNase digestion. Illumina library construction and sequencing was carried out as follows: total RNA was depleted of ribosomal RNA using the Ribozero rRNA removal kit (Epicentre), heat-fragmented to 200-700 bp in length and cloned using Uricil-N-Glycosylase-based strand-specific cloning. cDNA fragments were sequenced using an Illumina HiSeq 2000 Strand-specific, rRNA depleted total RNA, Paired (WT vs. Mef2d KO) or single-end (WT vs. Crx KO) 49 bp sequencing	Illumina HiSeq 2000	age;;postnatal day 11|gender;;female|genotype;;Mef2d KO|source_name;;Retina, postnatal day 11, female|tissue;;retina	GEO Accession;;GSM1503672		GSM1503672	P11_Mef2d_KO_Retina_2	19204853760	106693632	2015-07-22 17:06:50	13096221534	19204853760	106693632	2	106693632	index:0,count:106693632,average:90,stdev:0|index:1,count:106693632,average:90,stdev:0	GSM1503672_r1	GEO					1.02	2.55	0.03	13934420189	13648423723	12273210315	12033347922	97.95	98.05	98768157	94721782	155.294	464.595	127	1362988	61.29	69.51	119050278	60534017	119050278	60534017	67.34	65.9	119050278	66513993	119050278	57390517	3572082020	25.63	0.71	0	10.95	0	5.83	0	0.26	0	0.00	0	1.35	0	98768157	0	180	0	178.91	0	1.64	0	0.01	0	1.26	0	0.00	0	313.04	0	0.18	0	755701	0	106693632	0	11679920	0	6215193	0	272264	0	0	0	1438018	0	19195	0	0	0	200375	0	23616174	0	74697	0	23910441	0	81.62	0	87088237	0	280465	20308808	72.411202823882	106693632.0	98768157.0	755701.0	11679920.0	6215193.0	272264.0	0.0	1438018.0	87088237.0	92.6	0.7	10.9	5.8	0.3	0.0	1.3	81.6	90	90	90.00	38	9602426880	24.2	24.3	24.1	27.4	0.0	36.1	22.9	bulk
1913661	SRR1574333	SRP047079	SRS700496	SRX700311	SRA184282	GEO		MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancers (RNA-Seq)	Organismal development requires the precise coordination of genetic programs to regulate cell fate and function. MEF2 transcription factors play essential roles in this process but how these broadly expressed factors contribute to the generation of specific cell types during development is poorly understood.  Here we show that despite being expressed in virtually all mammalian tissues, in the retina MEF2D binds to retina-specific enhancers and controls photoreceptor cell development. MEF2D achieves specificity by cooperating with a retina-specific factor CRX, which recruits MEF2D away from canonical MEF2 binding sites, and redirects it to retina-specific enhancers that lack the consensus MEF2 sequence.  Once bound to retina-specific enhancers, MEF2D and CRX co-activate the expression of photoreceptor-specific genes that are critical for retinal function. These findings demonstrate that broadly expressed TFs acquire specific functions through competitive recruitment to enhancers by tissue-specific TFs, and through cooperative activation of these enhancers to regulate tissue-specific genes. Overall design: Total RNA-seq data from WT, Mef2d KO and Crx KO P11 mouse retinae		GSM1503673: P11_WT_Retina_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Retinae were dissected from p11 knockout or wild-type littermate controls. Both retinae from each animal were pooled for each sample.  RNA was extracted using trizol and Qiagen Rneasy purification with on-column DNase digestion. Illumina library construction and sequencing was carried out as follows: total RNA was depleted of ribosomal RNA using the Ribozero rRNA removal kit (Epicentre), heat-fragmented to 200-700 bp in length and cloned using Uricil-N-Glycosylase-based strand-specific cloning. cDNA fragments were sequenced using an Illumina HiSeq 2000 Strand-specific, rRNA depleted total RNA, Paired (WT vs. Mef2d KO) or single-end (WT vs. Crx KO) 49 bp sequencing	Illumina HiSeq 2000	age;;postnatal day 11|gender;;male|genotype;;wild type|source_name;;Retina, postnatal day 11, male|tissue;;retina	GEO Accession;;GSM1503673		GSM1503673	P11_WT_Retina_3	8631943880	176162120	2015-07-22 17:06:50	8666179162	8631943880	176162120	1	176162120	index:0,count:176162120,average:49,stdev:0	GSM1503673_r1	GEO					7.9	3.3	0.09	8288093233	8024755369	7424644765	7240471640	96.82	97.52	0	0	0	0	0	0	59.62	66.53	209329647	102377839	209329647	102377839	63.37	64.26	209329647	108831875	209329647	98877204	2329918609	28.11	0.41	0	10.14	0	0.63	0	0.47	0	0.00	0	1.42	0	171730206	0	49	0	48.25	0	1.41	0	0.01	0	1.28	0	0.00	0	561.22	0	0.71	0	728186	0	176162120	0	17858407	0	1104703	0	828799	0	0	0	2498412	0	3782	0	0	0	43366	0	5654046	0	31157	0	5732351	0	87.35	0	153871799	0	191348	6093797	31.846672032109	176162120.0	171730206.0	728186.0	17858407.0	1104703.0	828799.0	0.0	2498412.0	153871799.0	97.5	0.4	10.1	0.6	0.5	0.0	1.4	87.3	49	49	49.00	36	8631943880	23.8	23.2	25.4	27.6	0.0	36.1	23.5	bulk
1913677	SRR1574334	SRP047079	SRS700497	SRX700312	SRA184282	GEO		MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancers (RNA-Seq)	Organismal development requires the precise coordination of genetic programs to regulate cell fate and function. MEF2 transcription factors play essential roles in this process but how these broadly expressed factors contribute to the generation of specific cell types during development is poorly understood.  Here we show that despite being expressed in virtually all mammalian tissues, in the retina MEF2D binds to retina-specific enhancers and controls photoreceptor cell development. MEF2D achieves specificity by cooperating with a retina-specific factor CRX, which recruits MEF2D away from canonical MEF2 binding sites, and redirects it to retina-specific enhancers that lack the consensus MEF2 sequence.  Once bound to retina-specific enhancers, MEF2D and CRX co-activate the expression of photoreceptor-specific genes that are critical for retinal function. These findings demonstrate that broadly expressed TFs acquire specific functions through competitive recruitment to enhancers by tissue-specific TFs, and through cooperative activation of these enhancers to regulate tissue-specific genes. Overall design: Total RNA-seq data from WT, Mef2d KO and Crx KO P11 mouse retinae		GSM1503674: P11_WT_Retina_4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Retinae were dissected from p11 knockout or wild-type littermate controls. Both retinae from each animal were pooled for each sample.  RNA was extracted using trizol and Qiagen Rneasy purification with on-column DNase digestion. Illumina library construction and sequencing was carried out as follows: total RNA was depleted of ribosomal RNA using the Ribozero rRNA removal kit (Epicentre), heat-fragmented to 200-700 bp in length and cloned using Uricil-N-Glycosylase-based strand-specific cloning. cDNA fragments were sequenced using an Illumina HiSeq 2000 Strand-specific, rRNA depleted total RNA, Paired (WT vs. Mef2d KO) or single-end (WT vs. Crx KO) 49 bp sequencing	Illumina HiSeq 2000	age;;postnatal day 11|gender;;female|genotype;;wild type|source_name;;Retina, postnatal day 11, female|tissue;;retina	GEO Accession;;GSM1503674		GSM1503674	P11_WT_Retina_4	8634123890	176206610	2015-07-22 17:06:50	8628949011	8634123890	176206610	1	176206610	index:0,count:176206610,average:49,stdev:0	GSM1503674_r1	GEO					7.33	3.47	0.05	8286843488	8034596601	7390176144	7214908126	96.96	97.63	0	0	0	0	0	0	60.99	68.37	210970183	104837440	210970183	104837440	64.84	65.93	210970183	111461736	210970183	101093250	2185895363	26.38	0.43	0	10.53	0	0.59	0	0.42	0	0.00	0	1.44	0	171892454	0	49	0	48.20	0	1.38	0	0.01	0	1.26	0	0.00	0	593.40	0	0.74	0	751777	0	176206610	0	18554409	0	1045888	0	738026	0	0	0	2530242	0	3868	0	0	0	43440	0	5836204	0	31399	0	5914911	0	87.02	0	153338045	0	190514	6206621	32.578293458748	176206610.0	171892454.0	751777.0	18554409.0	1045888.0	738026.0	0.0	2530242.0	153338045.0	97.6	0.4	10.5	0.6	0.4	0.0	1.4	87.0	49	49	49.00	36	8634123890	23.6	23.4	25.6	27.4	0.0	36.2	23.8	bulk
1913693	SRR1574335	SRP047079	SRS700498	SRX700313	SRA184282	GEO		MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancers (RNA-Seq)	Organismal development requires the precise coordination of genetic programs to regulate cell fate and function. MEF2 transcription factors play essential roles in this process but how these broadly expressed factors contribute to the generation of specific cell types during development is poorly understood.  Here we show that despite being expressed in virtually all mammalian tissues, in the retina MEF2D binds to retina-specific enhancers and controls photoreceptor cell development. MEF2D achieves specificity by cooperating with a retina-specific factor CRX, which recruits MEF2D away from canonical MEF2 binding sites, and redirects it to retina-specific enhancers that lack the consensus MEF2 sequence.  Once bound to retina-specific enhancers, MEF2D and CRX co-activate the expression of photoreceptor-specific genes that are critical for retinal function. These findings demonstrate that broadly expressed TFs acquire specific functions through competitive recruitment to enhancers by tissue-specific TFs, and through cooperative activation of these enhancers to regulate tissue-specific genes. Overall design: Total RNA-seq data from WT, Mef2d KO and Crx KO P11 mouse retinae		GSM1503675: P11_Crx_KO_Retina_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Retinae were dissected from p11 knockout or wild-type littermate controls. Both retinae from each animal were pooled for each sample.  RNA was extracted using trizol and Qiagen Rneasy purification with on-column DNase digestion. Illumina library construction and sequencing was carried out as follows: total RNA was depleted of ribosomal RNA using the Ribozero rRNA removal kit (Epicentre), heat-fragmented to 200-700 bp in length and cloned using Uricil-N-Glycosylase-based strand-specific cloning. cDNA fragments were sequenced using an Illumina HiSeq 2000 Strand-specific, rRNA depleted total RNA, Paired (WT vs. Mef2d KO) or single-end (WT vs. Crx KO) 49 bp sequencing	Illumina HiSeq 2000	age;;postnatal day 11|gender;;male|genotype;;Crx KO|source_name;;Retina, postnatal day 11, male|tissue;;retina	GEO Accession;;GSM1503675		GSM1503675	P11_Crx_KO_Retina_1	8598255841	175474609	2015-07-22 17:06:50	8480003448	8598255841	175474609	1	175474609	index:0,count:175474609,average:49,stdev:0	GSM1503675_r1	GEO					9.0	3.18	0.1	8251787360	7975003497	7429121557	7235438392	96.65	97.39	0	0	0	0	0	0	58.96	65.48	206446563	100898986	206446563	100898986	62.79	63.34	206446563	107439462	206446563	97603764	2401105742	29.10	0.39	0	9.71	0	0.64	0	0.46	0	0.00	0	1.38	0	171122591	0	49	0	48.21	0	1.40	0	0.01	0	1.26	0	0.00	0	568.59	0	0.78	0	691945	0	175474609	0	17031707	0	1124262	0	808490	0	0	0	2419266	0	3456	0	0	0	40572	0	5235569	0	28619	0	5308216	0	87.81	0	154090884	0	182970	5558328	30.378357107723	175474609.0	171122591.0	691945.0	17031707.0	1124262.0	808490.0	0.0	2419266.0	154090884.0	97.5	0.4	9.7	0.6	0.5	0.0	1.4	87.8	49	49	49.00	36	8598255841	24.0	22.7	25.3	27.9	0.0	36.5	24.4	bulk
1913709	SRR1574336	SRP047079	SRS700499	SRX700314	SRA184282	GEO		MEF2D drives photoreceptor development through a genome-wide competition for tissue-specific enhancers (RNA-Seq)	Organismal development requires the precise coordination of genetic programs to regulate cell fate and function. MEF2 transcription factors play essential roles in this process but how these broadly expressed factors contribute to the generation of specific cell types during development is poorly understood.  Here we show that despite being expressed in virtually all mammalian tissues, in the retina MEF2D binds to retina-specific enhancers and controls photoreceptor cell development. MEF2D achieves specificity by cooperating with a retina-specific factor CRX, which recruits MEF2D away from canonical MEF2 binding sites, and redirects it to retina-specific enhancers that lack the consensus MEF2 sequence.  Once bound to retina-specific enhancers, MEF2D and CRX co-activate the expression of photoreceptor-specific genes that are critical for retinal function. These findings demonstrate that broadly expressed TFs acquire specific functions through competitive recruitment to enhancers by tissue-specific TFs, and through cooperative activation of these enhancers to regulate tissue-specific genes. Overall design: Total RNA-seq data from WT, Mef2d KO and Crx KO P11 mouse retinae		GSM1503676: P11_Crx_KO_Retina_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Retinae were dissected from p11 knockout or wild-type littermate controls. Both retinae from each animal were pooled for each sample.  RNA was extracted using trizol and Qiagen Rneasy purification with on-column DNase digestion. Illumina library construction and sequencing was carried out as follows: total RNA was depleted of ribosomal RNA using the Ribozero rRNA removal kit (Epicentre), heat-fragmented to 200-700 bp in length and cloned using Uricil-N-Glycosylase-based strand-specific cloning. cDNA fragments were sequenced using an Illumina HiSeq 2000 Strand-specific, rRNA depleted total RNA, Paired (WT vs. Mef2d KO) or single-end (WT vs. Crx KO) 49 bp sequencing	Illumina HiSeq 2000	age;;postnatal day 11|gender;;female|genotype;;Crx KO|source_name;;Retina, postnatal day 11, female|tissue;;retina	GEO Accession;;GSM1503676		GSM1503676	P11_Crx_KO_Retina_2	8633249436	176188764	2015-07-22 17:06:50	8664000900	8633249436	176188764	1	176188764	index:0,count:176188764,average:49,stdev:0	GSM1503676_r1	GEO					8.57	3.43	0.09	8287825999	8028286182	7374235241	7194219063	96.87	97.56	0	0	0	0	0	0	58.99	66.28	211685229	101361205	211685229	101361205	63.19	63.96	211685229	108583916	211685229	97805174	2334423279	28.17	0.42	0	10.73	0	0.62	0	0.42	0	0.00	0	1.43	0	171829764	0	49	0	48.22	0	1.41	0	0.01	0	1.26	0	0.00	0	318.89	0	0.77	0	732211	0	176188764	0	18903621	0	1092767	0	743953	0	0	0	2522280	0	3542	0	0	0	41954	0	5387254	0	28998	0	5461748	0	86.80	0	152926143	0	187481	5816202	31.022887652615	176188764.0	171829764.0	732211.0	18903621.0	1092767.0	743953.0	0.0	2522280.0	152926143.0	97.5	0.4	10.7	0.6	0.4	0.0	1.4	86.8	49	49	49.00	36	8633249436	23.7	23.2	25.4	27.7	0.0	36.1	23.8	bulk
1704585	SRR1576028	SRP047176	SRS701617	SRX701736	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505542: Primitive Streak 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.0 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505542		GSM1505542	Primitive Streak 1	3615684500	14462738	2015-02-09 22:39:05	1758398867	3615684500	14462738	2	14462738	index:0,count:14462738,average:125,stdev:0|index:1,count:14462738,average:125,stdev:0	GSM1505542_r1	GEO					6.52	3.36	0.08	1762473373	1868690257	1492845242	1636163301	106.03	109.6	9663280	8884202	228.305	1757.218	106	57540	70.9	85.44	12836857	6851476	12836857	6851476	68.33	70.44	12836857	6602762	12836857	5648181	186049051	10.56	2.30	0	11.37	0	1.27	0	0.05	0	0.00	0	31.86	0	9663280	0	250	0	238.92	0	4.08	0	0.07	0	1.29	0	0.03	0	97.68	0	0.42	0	332520	0	14462738	0	1644502	0	183679	0	7514	0	0	0	4608265	0	2300	0	0	0	16034	0	2950747	0	30403	0	2999484	0	55.44	0	8018778	0	106757	2754127	25.798092865105	14462738.0	9663280.0	332520.0	1644502.0	183679.0	7514.0	0.0	4608265.0	8018778.0	66.8	2.3	11.4	1.3	0.1	0.0	31.9	55.4	125	125	125.00	24	1807842250	24.8	25.0	22.9	27.3	0.0	35.2	18.2	smartseq
1704600	SRR1576029	SRP047176	SRS701618	SRX701737	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505543: Primitive Streak 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.0 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505543		GSM1505543	Primitive Streak 2	7254186500	29016746	2015-02-09 22:39:05	3533307356	7254186500	29016746	2	29016746	index:0,count:29016746,average:125,stdev:0|index:1,count:29016746,average:125,stdev:0	GSM1505543_r1	GEO					6.78	3.31	0.1	3608845236	3872387563	3126895943	3445707045	107.3	110.2	19760644	18191523	227.365	1360.623	125	110658	74.07	86.78	25070846	14636190	25070846	14636190	70.71	71.84	25070846	13972366	25070846	12115970	365937254	10.14	2.17	0	9.98	0	0.90	0	0.05	0	0.00	0	30.95	0	19760644	0	250	0	239.39	0	4.10	0	0.07	0	1.29	0	0.03	0	94.96	0	0.39	0	628925	0	29016746	0	2894612	0	259744	0	14923	0	0	0	8981435	0	5125	0	0	0	36901	0	6409929	0	57314	0	6509269	0	58.13	0	16866032	0	131410	5819377	44.284126017807	29016746.0	19760644.0	628925.0	2894612.0	259744.0	14923.0	0.0	8981435.0	16866032.0	68.1	2.2	10.0	0.9	0.1	0.0	31.0	58.1	125	125	125.00	24	3627093250	24.9	25.1	22.7	27.3	0.0	35.4	18.7	smartseq
1704712	SRR1576030	SRP047176	SRS701619	SRX701738	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505544: Primitive Streak 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.0 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505544		GSM1505544	Primitive Streak 3	7754523000	31018092	2015-02-09 22:39:05	3741738328	7754523000	31018092	2	31018092	index:0,count:31018092,average:125,stdev:0|index:1,count:31018092,average:125,stdev:0	GSM1505544_r1	GEO					7.64	3.47	0.11	3799763112	4019725117	3235748970	3525203974	105.79	108.95	20979957	19380929	223.431	1403.389	126	119843	72.94	86.96	27204336	15301962	27204336	15301962	71.85	73.06	27204336	15074871	27204336	12857184	376104925	9.90	2.23	0	10.91	0	0.99	0	0.06	0	0.00	0	31.32	0	20979957	0	250	0	239.08	0	3.87	0	0.06	0	1.32	0	0.03	0	131.06	0	0.37	0	691687	0	31018092	0	3382931	0	305740	0	17442	0	0	0	9714953	0	5029	0	0	0	35973	0	6514951	0	56168	0	6612121	0	56.73	0	17597026	0	123580	5983586	48.418724712737	31018092.0	20979957.0	691687.0	3382931.0	305740.0	17442.0	0.0	9714953.0	17597026.0	67.6	2.2	10.9	1.0	0.1	0.0	31.3	56.7	125	125	125.00	24	3877261500	25.5	24.6	22.5	27.4	0.0	35.4	18.5	smartseq
1704728	SRR1576031	SRP047176	SRS701620	SRX701739	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505545: Primitive Streak 4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.0 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505545		GSM1505545	Primitive Streak 4	9150216500	36600866	2015-02-09 22:39:05	4399525769	9150216500	36600866	2	36600866	index:0,count:36600866,average:125,stdev:0|index:1,count:36600866,average:125,stdev:0	GSM1505545_r1	GEO					7.86	3.3	0.09	4240289628	4521426417	3644940222	4000363943	106.63	109.75	23809497	22146142	216.312	1323.134	126	144900	73.35	86.55	30391662	17465228	30391662	17465228	70.96	72.04	30391662	16895043	30391662	14537121	427977144	10.09	2.08	0	9.92	0	0.87	0	0.05	0	0.00	0	34.03	0	23809497	0	250	0	238.58	0	4.06	0	0.06	0	1.31	0	0.03	0	119.13	0	0.37	0	760832	0	36600866	0	3630348	0	317905	0	18544	0	0	0	12454920	0	5339	0	0	0	39133	0	6991917	0	60722	0	7097111	0	55.13	0	20179149	0	129487	6293691	48.604809749241	36600866.0	23809497.0	760832.0	3630348.0	317905.0	18544.0	0.0	12454920.0	20179149.0	65.1	2.1	9.9	0.9	0.1	0.0	34.0	55.1	125	125	125.00	24	4575108250	25.1	25.0	22.0	27.9	0.0	35.3	18.3	smartseq
1704744	SRR1576032	SRP047176	SRS701621	SRX701740	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505546: Primitive Streak 5; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.0 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505546		GSM1505546	Primitive Streak 5	12522749500	50090998	2015-02-09 22:39:05	5993675763	12522749500	50090998	2	50090998	index:0,count:50090998,average:125,stdev:0|index:1,count:50090998,average:125,stdev:0	GSM1505546_r1	GEO					9.02	3.43	0.07	6254968636	6664859875	5416441294	5918943509	106.55	109.28	34474142	31855100	222.359	1174.565	126	198587	73.77	86.16	43002664	25432535	43002664	25432535	72.19	72.48	43002664	24887434	43002664	21394178	683479839	10.93	1.87	0	9.89	0	0.65	0	0.06	0	0.00	0	30.48	0	34474142	0	250	0	239.59	0	3.96	0	0.06	0	1.36	0	0.03	0	122.26	0	0.35	0	937628	0	50090998	0	4955305	0	323311	0	27859	0	0	0	15265686	0	8558	0	0	0	62853	0	10928477	0	92793	0	11092681	0	58.93	0	29518837	0	146579	9783428	66.745086267474	50090998.0	34474142.0	937628.0	4955305.0	323311.0	27859.0	0.0	15265686.0	29518837.0	68.8	1.9	9.9	0.6	0.1	0.0	30.5	58.9	125	125	125.00	24	6261374750	25.5	24.8	22.2	27.5	0.0	35.6	19.6	smartseq
1704760	SRR1576033	SRP047176	SRS701622	SRX701741	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505547: Neural Plate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.5 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505547		GSM1505547	Neural Plate 1	4918105500	19672422	2015-02-09 22:39:05	2436905688	4918105500	19672422	2	19672422	index:0,count:19672422,average:125,stdev:0|index:1,count:19672422,average:125,stdev:0	GSM1505547_r1	GEO					5.67	3.41	0.09	2288708807	2401066415	1951064596	2111500945	104.91	108.22	12761391	11706995	222.462	1762.897	106	78021	71.25	85.29	16805275	9092607	16805275	9092607	69.13	71.4	16805275	8821891	16805275	7611879	232518876	10.16	2.03	0	10.68	0	1.23	0	0.05	0	0.00	0	33.85	0	12761391	0	250	0	238.52	0	4.12	0	0.07	0	1.30	0	0.03	0	86.37	0	0.42	0	399609	0	19672422	0	2100298	0	242150	0	9678	0	0	0	6659203	0	3411	0	0	0	23663	0	4223940	0	37910	0	4288924	0	54.19	0	10661093	0	121523	3858319	31.749701702558	19672422.0	12761391.0	399609.0	2100298.0	242150.0	9678.0	0.0	6659203.0	10661093.0	64.9	2.0	10.7	1.2	0.0	0.0	33.9	54.2	125	125	125.00	24	2459052750	24.8	25.0	22.8	27.5	0.0	35.0	17.9	smartseq
1704777	SRR1576034	SRP047176	SRS701623	SRX701742	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505548: Neural Plate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.5 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505548		GSM1505548	Neural Plate 2	4520556500	18082226	2015-02-09 22:39:05	2243705746	4520556500	18082226	2	18082226	index:0,count:18082226,average:125,stdev:0|index:1,count:18082226,average:125,stdev:0	GSM1505548_r1	GEO					5.87	3.42	0.12	2106080581	2188375789	1787588450	1920866430	103.91	107.46	11665746	10684864	225.962	1957.729	109	74842	68.28	82.29	15581568	7964908	15581568	7964908	66.14	68.6	15581568	7715653	15581568	6639713	253900509	12.06	2.08	0	10.98	0	1.37	0	0.07	0	0.00	0	34.05	0	11665746	0	250	0	238.44	0	4.09	0	0.06	0	1.32	0	0.03	0	74.23	0	0.46	0	376748	0	18082226	0	1986231	0	248081	0	12083	0	0	0	6156316	0	2765	0	0	0	20902	0	3651246	0	34959	0	3709872	0	53.53	0	9679515	0	120650	3388906	28.088736013261	18082226.0	11665746.0	376748.0	1986231.0	248081.0	12083.0	0.0	6156316.0	9679515.0	64.5	2.1	11.0	1.4	0.1	0.0	34.0	53.5	125	125	125.00	24	2260278250	24.6	25.2	22.5	27.7	0.0	35.1	18.0	smartseq
852399	SRR1576035	SRP047176	SRS701624	SRX701743	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505549: Neural Plate 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.5 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505549		GSM1505549	Neural Plate 3	6488059250	25952237	2015-02-09 22:39:05	3202235400	6488059250	25952237	2	25952237	index:0,count:25952237,average:125,stdev:0|index:1,count:25952237,average:125,stdev:0	GSM1505549_r1	GEO					6.43	3.39	0.11	3140556962	3301289362	2702701875	2925519461	105.12	108.24	17280735	15808287	227.178	1702.085	109	101001	71.7	84.92	22396160	12390533	22396160	12390533	69.31	71.19	22396160	11976648	22396160	10386551	337007509	10.73	1.93	0	10.37	0	1.09	0	0.06	0	0.00	0	32.26	0	17280735	0	250	0	239.09	0	4.16	0	0.06	0	1.31	0	0.03	0	86.35	0	0.43	0	499709	0	25952237	0	2690413	0	284126	0	14903	0	0	0	8372473	0	4727	0	0	0	33495	0	5825561	0	50573	0	5914356	0	56.22	0	14590322	0	137366	5318362	38.716727574509	25952237.0	17280735.0	499709.0	2690413.0	284126.0	14903.0	0.0	8372473.0	14590322.0	66.6	1.9	10.4	1.1	0.1	0.0	32.3	56.2	125	125	125.00	24	3244029625	25.2	25.0	22.9	26.9	0.0	35.4	18.8	smartseq
852407	SRR1576036	SRP047176	SRS701625	SRX701744	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505550: Neural Plate 4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.5 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505550		GSM1505550	Neural Plate 4	6695655750	26782623	2015-02-09 22:39:05	3324485363	6695655750	26782623	2	26782623	index:0,count:26782623,average:125,stdev:0|index:1,count:26782623,average:125,stdev:0	GSM1505550_r1	GEO					6.64	3.33	0.11	3144794961	3309108700	2720806492	2940226035	105.22	108.06	17540641	16064674	221.737	1539.338	125	102242	72.66	85.36	22388802	12745102	22388802	12745102	70.44	71.87	22388802	12355157	22388802	10731651	328188309	10.44	1.90	0	9.74	0	0.96	0	0.05	0	0.00	0	33.50	0	17540641	0	250	0	238.76	0	4.14	0	0.06	0	1.31	0	0.03	0	98.99	0	0.38	0	508979	0	26782623	0	2608979	0	256814	0	14310	0	0	0	8970858	0	4811	0	0	0	35320	0	6151010	0	50274	0	6241415	0	55.75	0	14931662	0	135791	5496659	40.478816710975	26782623.0	17540641.0	508979.0	2608979.0	256814.0	14310.0	0.0	8970858.0	14931662.0	65.5	1.9	9.7	1.0	0.1	0.0	33.5	55.8	125	125	125.00	24	3347827875	24.6	25.4	22.6	27.4	0.0	35.0	18.3	smartseq
852414	SRR1576037	SRP047176	SRS701626	SRX701745	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505551: Neural Plate 5; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.5 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505551		GSM1505551	Neural Plate 5	8328812000	33315248	2015-02-09 22:39:05	4077402783	8328812000	33315248	2	33315248	index:0,count:33315248,average:125,stdev:0|index:1,count:33315248,average:125,stdev:0	GSM1505551_r1	GEO					6.8	3.35	0.09	3934050968	4166068968	3395211667	3695485420	105.9	108.84	21865031	20014088	222.759	1571.735	125	127103	72.71	85.65	27995214	15898717	27995214	15898717	70.09	71.53	27995214	15324938	27995214	13277921	402681687	10.24	1.87	0	9.91	0	0.92	0	0.05	0	0.00	0	33.40	0	21865031	0	250	0	238.86	0	4.17	0	0.06	0	1.31	0	0.03	0	111.88	0	0.40	0	624610	0	33315248	0	3302863	0	307281	0	16330	0	0	0	11126606	0	6154	0	0	0	43899	0	7581592	0	63799	0	7695444	0	55.72	0	18562168	0	143403	6821408	47.568098296409	33315248.0	21865031.0	624610.0	3302863.0	307281.0	16330.0	0.0	11126606.0	18562168.0	65.6	1.9	9.9	0.9	0.0	0.0	33.4	55.7	125	125	125.00	24	4164406000	24.6	25.5	22.7	27.2	0.0	35.3	18.7	smartseq
852423	SRR1576038	SRP047176	SRS701627	SRX701746	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505552: Head fold 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.75 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505552		GSM1505552	Head fold 1	8367307250	33469229	2015-02-09 22:39:05	4037233627	8367307250	33469229	2	33469229	index:0,count:33469229,average:125,stdev:0|index:1,count:33469229,average:125,stdev:0	GSM1505552_r1	GEO					7.92	3.41	0.13	4277829116	4501282522	3674174373	3971869947	105.22	108.1	23394470	21465715	226.698	1314.370	126	130977	72.58	85.58	29522962	16979185	29522962	16979185	72.11	72.82	29522962	16869130	29522962	14448179	468419672	10.95	2.07	0	10.62	0	0.82	0	0.06	0	0.00	0	29.22	0	23394470	0	250	0	239.59	0	3.51	0	0.05	0	1.35	0	0.02	0	131.68	0	0.36	0	694053	0	33469229	0	3554190	0	274271	0	20769	0	0	0	9779719	0	6295	0	0	0	44135	0	7627537	0	63443	0	7741410	0	59.28	0	19840280	0	139689	6936469	49.656515545247	33469229.0	23394470.0	694053.0	3554190.0	274271.0	20769.0	0.0	9779719.0	19840280.0	69.9	2.1	10.6	0.8	0.1	0.0	29.2	59.3	125	125	125.00	24	4183653625	25.8	24.1	22.2	27.9	0.0	35.6	19.4	smartseq
852431	SRR1576039	SRP047176	SRS701628	SRX701747	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505553: Head fold 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.75 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505553		GSM1505553	Head fold 2	17384535000	69538140	2015-02-09 22:39:05	8249925565	17384535000	69538140	2	69538140	index:0,count:69538140,average:125,stdev:0|index:1,count:69538140,average:125,stdev:0	GSM1505553_r1	GEO					14.92	3.6	0.12	7847127592	8055537393	6603342045	6969681620	102.66	105.55	45707769	43016205	199.775	998.071	126	326794	70.92	84.88	57547029	32417946	57547029	32417946	75.33	75.39	57547029	34432771	57547029	28796311	928440634	11.83	1.69	0	10.80	0	0.49	0	0.07	0	0.00	0	33.71	0	45707769	0	250	0	238.01	0	3.03	0	0.04	0	1.32	0	0.03	0	160.06	0	0.30	0	1173809	0	69538140	0	7513143	0	341799	0	47928	0	0	0	23440644	0	8217	0	0	0	61293	0	10989218	0	103198	0	11161926	0	54.93	0	38194626	0	146959	9653910	65.691179172422	69538140.0	45707769.0	1173809.0	7513143.0	341799.0	47928.0	0.0	23440644.0	38194626.0	65.7	1.7	10.8	0.5	0.1	0.0	33.7	54.9	125	125	125.00	24	8692267500	27.8	22.9	19.2	30.1	0.0	35.5	19.4	smartseq
852487	SRR1576040	SRP047176	SRS701629	SRX701748	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505554: Head fold 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.75 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505554		GSM1505554	Head fold 3	9518296750	38073187	2015-02-09 22:39:05	4688310766	9518296750	38073187	2	38073187	index:0,count:38073187,average:125,stdev:0|index:1,count:38073187,average:125,stdev:0	GSM1505554_r1	GEO					5.71	3.41	0.09	4841731186	5186069362	4207192481	4617535488	107.11	109.75	26471992	24333573	227.902	1210.075	126	145889	75.12	87.53	33120234	19886933	33120234	19886933	72.64	73.21	33120234	19229571	33120234	16632464	474808566	9.81	2.03	0	9.85	0	0.76	0	0.05	0	0.00	0	29.66	0	26471992	0	250	0	239.63	0	3.97	0	0.06	0	1.29	0	0.03	0	133.98	0	0.38	0	771274	0	38073187	0	3751888	0	288067	0	19262	0	0	0	11293866	0	7362	0	0	0	50828	0	8962715	0	75356	0	9096261	0	59.67	0	22720104	0	142249	8093568	56.897187326449	38073187.0	26471992.0	771274.0	3751888.0	288067.0	19262.0	0.0	11293866.0	22720104.0	69.5	2.0	9.9	0.8	0.1	0.0	29.7	59.7	125	125	125.00	24	4759148375	25.2	24.8	22.9	27.1	0.0	35.5	19.6	smartseq
852494	SRR1576041	SRP047176	SRS701630	SRX701749	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505555: Head fold 4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.75 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505555		GSM1505555	Head fold 4	8907430000	35629720	2015-02-09 22:39:05	4416073036	8907430000	35629720	2	35629720	index:0,count:35629720,average:125,stdev:0|index:1,count:35629720,average:125,stdev:0	GSM1505555_r1	GEO					6.47	3.37	0.1	4301466509	4582309074	3693376416	4041694495	106.53	109.43	23835557	21863371	223.595	1331.430	125	137309	74.76	88.32	30399805	17819957	30399805	17819957	73.27	74.26	30399805	17463294	30399805	14983604	382216971	8.89	1.85	0	10.27	0	0.82	0	0.05	0	0.00	0	32.23	0	23835557	0	250	0	239.14	0	4.03	0	0.06	0	1.28	0	0.02	0	146.59	0	0.38	0	660673	0	35629720	0	3659669	0	293438	0	17171	0	0	0	11483554	0	7017	0	0	0	46458	0	8244460	0	66932	0	8364867	0	56.63	0	20175888	0	141789	7416371	52.305686618849	35629720.0	23835557.0	660673.0	3659669.0	293438.0	17171.0	0.0	11483554.0	20175888.0	66.9	1.9	10.3	0.8	0.0	0.0	32.2	56.6	125	125	125.00	24	4453715000	25.0	25.4	22.1	27.6	0.0	35.2	18.9	smartseq
852503	SRR1576042	SRP047176	SRS701631	SRX701750	SRA184672	GEO		Decoding the regulatory network of early blood development from single-cell gene expression measurements.	Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis. Overall design: Transcriptome analysis in populations of 50 cells from each of 5 mouse embryos at primitive streak, neural plate and head fold stages of development		GSM1505556: Head fold 5; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Timed matings were set up and embryos were staged according to morphologic criteria. Suspensions of embryo cells were prepared as described previously (Tanaka et al 2012 PNAS) and single cell suspensions were stained with Flk-1-APC (AVAS12; BD Bioscience). Cells were sorted into 2 μl of lysis buffer (0.2 % (v/v) Triton X-100 and 2 U/μl RNase inhibitor (Clontech)) and stored at -80 °C. RNAseq was carried out using the Smart-seq2 protocol according to Picelli et al 2014 Nature Protocols and sequenced on an Illumina HiSeq 2500.	Illumina HiSeq 2500	age;;E7.75 embryo|source_name;;Flk1+ mesoderm|strain;;CD1(ICR)	GEO Accession;;GSM1505556		GSM1505556	Head fold 5	8903163750	35612655	2015-02-09 22:39:05	4434201855	8903163750	35612655	2	35612655	index:0,count:35612655,average:125,stdev:0|index:1,count:35612655,average:125,stdev:0	GSM1505556_r1	GEO					5.9	3.31	0.09	4473541377	4794817567	3886618128	4266559143	107.18	109.78	24500437	22414109	227.686	1234.316	125	134341	75.58	88.14	30711167	18518439	30711167	18518439	73.19	73.88	30711167	17930994	30711167	15521842	410661554	9.18	1.94	0	9.80	0	0.75	0	0.05	0	0.00	0	30.40	0	24500437	0	250	0	239.54	0	4.10	0	0.06	0	1.27	0	0.02	0	116.13	0	0.40	0	691546	0	35612655	0	3489908	0	267568	0	16691	0	0	0	10827959	0	7806	0	0	0	51016	0	8817035	0	71965	0	8947822	0	59.00	0	21010529	0	145139	7923304	54.591143662282	35612655.0	24500437.0	691546.0	3489908.0	267568.0	16691.0	0.0	10827959.0	21010529.0	68.8	1.9	9.8	0.8	0.0	0.0	30.4	59.0	125	125	125.00	24	4451581875	25.2	25.0	23.2	26.6	0.0	35.4	19.2	smartseq
862983	SRR1706560	SRP051076	SRS788248	SRX806615	SRA214041	GEO		Transcriptional profiling of cutaneous Mrgprd free nerve endings and C-LTMRs	Cutaneous C-unmyelinated free nerve endings and hair follicles-innervating C-LTMRs convey two opposite aspects of touch sensation: a sensation of pain and a sensation of pleasant touch. The molecular mechanisms underlying these diametrically opposite functions are unknown. Here we used a mouse model that genetically marks C-LTMRs and the free nerve endings MRGPRD+ neurons in combination with fluorescent cell surface labeling, flow cytometry and RNA deep-sequencing technology. Cluster analysis of the RNA-Seq profiles of the purified neuronal subsets revealed 156 and 184 genes differentially expressed in MRGPRD-expressing neurons and C-LTMRs, respectively. 48 MRGPD- and 67 C-LTMRs-enriched genes were validated using a triple staining experiment approach and the Cav3.3 channel, found to be exclusively expressed in C-LTMRs, was validated using electrophysiology. Furthermore, our study greatly expands the molecular characterization of C-LTMRs and suggests that this particular population of neurons shares common transcriptional signatures with A and A low threshold mechanoreceptors. Overall design: RNA profiles of FACS-sorted subsets of sensory neurons, namely Mrgprd+ neurons (DP, double-positive=IB4+GINIP+), C-LTMRs (IB4-GINIP+) and remaining cells (DN, double-negative=IB4-GINIP-) were generated by deep sequencing in duplicate using Illumina HiSeq 2000.		GSM1564174: DP-1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Neurons were sorted directly in RLT-lysis buffer from RNeasy Micro Kit (Qiagen), snap-frozen at -80°C and processed for RNA extraction following manufacturer's recommendations. 50 nanograms of high-quality total RNAs were amplified with the Amino Allyl Message Amp II Amplification kit (Life Technologies, Carlsbad, CA). RNA-Seq libraries were constructed with the TruSeq RNA sample preparation (Low-throughput protocol) kit from Illumina.	Illumina HiSeq 2000	genotype/variation;;GINIP+/mcherry|sensory neuron subset;;Mrgprd+ (DP, double-positive=IB4+GINIP+)|source_name;;Mrgprd+ sensory neurons|tissue;;dorsal root ganglia (DRG)	GEO Accession;;GSM1564174		GSM1564174	DP-1	11172041200	55860206	2015-02-02 16:00:02	7728756873	11172041200	55860206	2	55860206	index:0,count:55860206,average:100,stdev:0|index:1,count:55860206,average:100,stdev:0	GSM1564174_r1	GEO					2.88	3.32	0.07	8638924765	8602793448	7903206840	7936333392	99.58	100.42	52253397	49492728	191.311	557.023	147	479059	87.64	95.97	59483294	45796207	59483294	45796207	91.04	91.99	59483294	47569188	59483294	43897329	231255172	2.68	1.14	0	8.11	0	0.40	0	0.06	0	0.00	0	6.00	0	52253397	0	200	0	197.86	0	1.56	0	0.01	0	1.43	0	0.01	0	278.53	0	0.41	0	638094	0	55860206	0	4532539	0	221583	0	32039	0	0	0	3353187	0	12274	0	0	0	101302	0	17211505	0	74252	0	17399333	0	85.43	0	47720858	0	184300	16311129	88.503141616929	55860206.0	52253397.0	638094.0	4532539.0	221583.0	32039.0	0.0	3353187.0	47720858.0	93.5	1.1	8.1	0.4	0.1	0.0	6.0	85.4	100	100	100.00	38	5586020600	26.0	24.0	23.9	26.1	0.0	33.2	14.2	bulk
862991	SRR1706561	SRP051076	SRS788250	SRX806616	SRA214041	GEO		Transcriptional profiling of cutaneous Mrgprd free nerve endings and C-LTMRs	Cutaneous C-unmyelinated free nerve endings and hair follicles-innervating C-LTMRs convey two opposite aspects of touch sensation: a sensation of pain and a sensation of pleasant touch. The molecular mechanisms underlying these diametrically opposite functions are unknown. Here we used a mouse model that genetically marks C-LTMRs and the free nerve endings MRGPRD+ neurons in combination with fluorescent cell surface labeling, flow cytometry and RNA deep-sequencing technology. Cluster analysis of the RNA-Seq profiles of the purified neuronal subsets revealed 156 and 184 genes differentially expressed in MRGPRD-expressing neurons and C-LTMRs, respectively. 48 MRGPD- and 67 C-LTMRs-enriched genes were validated using a triple staining experiment approach and the Cav3.3 channel, found to be exclusively expressed in C-LTMRs, was validated using electrophysiology. Furthermore, our study greatly expands the molecular characterization of C-LTMRs and suggests that this particular population of neurons shares common transcriptional signatures with A and A low threshold mechanoreceptors. Overall design: RNA profiles of FACS-sorted subsets of sensory neurons, namely Mrgprd+ neurons (DP, double-positive=IB4+GINIP+), C-LTMRs (IB4-GINIP+) and remaining cells (DN, double-negative=IB4-GINIP-) were generated by deep sequencing in duplicate using Illumina HiSeq 2000.		GSM1564175: DP-2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Neurons were sorted directly in RLT-lysis buffer from RNeasy Micro Kit (Qiagen), snap-frozen at -80°C and processed for RNA extraction following manufacturer's recommendations. 50 nanograms of high-quality total RNAs were amplified with the Amino Allyl Message Amp II Amplification kit (Life Technologies, Carlsbad, CA). RNA-Seq libraries were constructed with the TruSeq RNA sample preparation (Low-throughput protocol) kit from Illumina.	Illumina HiSeq 2000	genotype/variation;;GINIP+/mcherry|sensory neuron subset;;Mrgprd+ (DP, double-positive=IB4+GINIP+)|source_name;;Mrgprd+ sensory neurons|tissue;;dorsal root ganglia (DRG)	GEO Accession;;GSM1564175		GSM1564175	DP-2	10052702000	50263510	2015-02-02 16:00:02	6969297939	10052702000	50263510	2	50263510	index:0,count:50263510,average:100,stdev:0|index:1,count:50263510,average:100,stdev:0	GSM1564175_r1	GEO					2.88	3.32	0.05	7821239705	7801311574	7155182618	7195504898	99.75	100.56	47542160	45171095	188.410	518.418	147	454047	88.34	96.71	54081079	41998952	54081079	41998952	91.72	92.7	54081079	43606810	54081079	40255983	162522118	2.08	1.00	0	8.19	0	0.38	0	0.06	0	0.00	0	4.98	0	47542160	0	200	0	197.95	0	1.59	0	0.01	0	1.43	0	0.01	0	265.71	0	0.40	0	502461	0	50263510	0	4116671	0	192730	0	27755	0	0	0	2500865	0	11652	0	0	0	92843	0	15752013	0	93051	0	15949559	0	86.40	0	43425489	0	180956	14887288	82.270209332655	50263510.0	47542160.0	502461.0	4116671.0	192730.0	27755.0	0.0	2500865.0	43425489.0	94.6	1.0	8.2	0.4	0.1	0.0	5.0	86.4	100	100	100.00	38	5026351000	26.0	24.0	23.9	26.1	0.0	33.4	14.5	bulk
862999	SRR1706562	SRP051076	SRS788249	SRX806617	SRA214041	GEO		Transcriptional profiling of cutaneous Mrgprd free nerve endings and C-LTMRs	Cutaneous C-unmyelinated free nerve endings and hair follicles-innervating C-LTMRs convey two opposite aspects of touch sensation: a sensation of pain and a sensation of pleasant touch. The molecular mechanisms underlying these diametrically opposite functions are unknown. Here we used a mouse model that genetically marks C-LTMRs and the free nerve endings MRGPRD+ neurons in combination with fluorescent cell surface labeling, flow cytometry and RNA deep-sequencing technology. Cluster analysis of the RNA-Seq profiles of the purified neuronal subsets revealed 156 and 184 genes differentially expressed in MRGPRD-expressing neurons and C-LTMRs, respectively. 48 MRGPD- and 67 C-LTMRs-enriched genes were validated using a triple staining experiment approach and the Cav3.3 channel, found to be exclusively expressed in C-LTMRs, was validated using electrophysiology. Furthermore, our study greatly expands the molecular characterization of C-LTMRs and suggests that this particular population of neurons shares common transcriptional signatures with A and A low threshold mechanoreceptors. Overall design: RNA profiles of FACS-sorted subsets of sensory neurons, namely Mrgprd+ neurons (DP, double-positive=IB4+GINIP+), C-LTMRs (IB4-GINIP+) and remaining cells (DN, double-negative=IB4-GINIP-) were generated by deep sequencing in duplicate using Illumina HiSeq 2000.		GSM1564176: C-LTMRs-1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Neurons were sorted directly in RLT-lysis buffer from RNeasy Micro Kit (Qiagen), snap-frozen at -80°C and processed for RNA extraction following manufacturer's recommendations. 50 nanograms of high-quality total RNAs were amplified with the Amino Allyl Message Amp II Amplification kit (Life Technologies, Carlsbad, CA). RNA-Seq libraries were constructed with the TruSeq RNA sample preparation (Low-throughput protocol) kit from Illumina.	Illumina HiSeq 2000	genotype/variation;;GINIP+/mcherry|sensory neuron subset;;C-LTMR (IB4-GINIP+)|source_name;;C-LTMR sensory neurons|tissue;;dorsal root ganglia (DRG)	GEO Accession;;GSM1564176		GSM1564176	C-LTMRs-1	9124042800	45620214	2015-02-02 16:00:02	6315467489	9124042800	45620214	2	45620214	index:0,count:45620214,average:100,stdev:0|index:1,count:45620214,average:100,stdev:0	GSM1564176_r1	GEO					3.94	3.15	0.06	7066951328	7034722722	6423289478	6446331551	99.54	100.36	42812455	40634672	190.230	540.041	148	401519	87.03	95.91	49045789	37259674	49045789	37259674	91.28	92.09	49045789	39077946	49045789	35774471	194812361	2.76	1.22	0	8.69	0	0.39	0	0.06	0	0.00	0	5.71	0	42812455	0	200	0	197.86	0	1.58	0	0.01	0	1.43	0	0.01	0	212.74	0	0.40	0	556245	0	45620214	0	3963944	0	177165	0	25658	0	0	0	2604936	0	9661	0	0	0	85216	0	14125527	0	66453	0	14286857	0	85.16	0	38848511	0	174870	13595106	77.744072739750	45620214.0	42812455.0	556245.0	3963944.0	177165.0	25658.0	0.0	2604936.0	38848511.0	93.8	1.2	8.7	0.4	0.1	0.0	5.7	85.2	100	100	100.00	38	4562021400	26.0	24.0	23.9	26.2	0.0	33.4	14.4	bulk
863007	SRR1706563	SRP051076	SRS788251	SRX806618	SRA214041	GEO		Transcriptional profiling of cutaneous Mrgprd free nerve endings and C-LTMRs	Cutaneous C-unmyelinated free nerve endings and hair follicles-innervating C-LTMRs convey two opposite aspects of touch sensation: a sensation of pain and a sensation of pleasant touch. The molecular mechanisms underlying these diametrically opposite functions are unknown. Here we used a mouse model that genetically marks C-LTMRs and the free nerve endings MRGPRD+ neurons in combination with fluorescent cell surface labeling, flow cytometry and RNA deep-sequencing technology. Cluster analysis of the RNA-Seq profiles of the purified neuronal subsets revealed 156 and 184 genes differentially expressed in MRGPRD-expressing neurons and C-LTMRs, respectively. 48 MRGPD- and 67 C-LTMRs-enriched genes were validated using a triple staining experiment approach and the Cav3.3 channel, found to be exclusively expressed in C-LTMRs, was validated using electrophysiology. Furthermore, our study greatly expands the molecular characterization of C-LTMRs and suggests that this particular population of neurons shares common transcriptional signatures with A and A low threshold mechanoreceptors. Overall design: RNA profiles of FACS-sorted subsets of sensory neurons, namely Mrgprd+ neurons (DP, double-positive=IB4+GINIP+), C-LTMRs (IB4-GINIP+) and remaining cells (DN, double-negative=IB4-GINIP-) were generated by deep sequencing in duplicate using Illumina HiSeq 2000.		GSM1564177: C-LTMRs-2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Neurons were sorted directly in RLT-lysis buffer from RNeasy Micro Kit (Qiagen), snap-frozen at -80°C and processed for RNA extraction following manufacturer's recommendations. 50 nanograms of high-quality total RNAs were amplified with the Amino Allyl Message Amp II Amplification kit (Life Technologies, Carlsbad, CA). RNA-Seq libraries were constructed with the TruSeq RNA sample preparation (Low-throughput protocol) kit from Illumina.	Illumina HiSeq 2000	genotype/variation;;GINIP+/mcherry|sensory neuron subset;;C-LTMR (IB4-GINIP+)|source_name;;C-LTMR sensory neurons|tissue;;dorsal root ganglia (DRG)	GEO Accession;;GSM1564177		GSM1564177	C-LTMRs-2	8727791600	43638958	2015-02-02 16:00:02	6027426007	8727791600	43638958	2	43638958	index:0,count:43638958,average:100,stdev:0|index:1,count:43638958,average:100,stdev:0	GSM1564177_r1	GEO					4.42	3.17	0.05	6741863212	6714237889	6082565980	6106970965	99.59	100.4	41009498	39021062	188.432	517.666	148	391778	86.83	96.4	47433583	35608393	47433583	35608393	91.75	92.55	47433583	37627958	47433583	34185344	155024685	2.30	1.10	0	9.33	0	0.37	0	0.06	0	0.00	0	5.60	0	41009498	0	200	0	197.90	0	1.67	0	0.01	0	1.44	0	0.01	0	286.68	0	0.40	0	478118	0	43638958	0	4071859	0	162302	0	24956	0	0	0	2442202	0	9195	0	0	0	82170	0	13174641	0	109925	0	13375931	0	84.64	0	36937639	0	180611	12890527	71.371771376051	43638958.0	41009498.0	478118.0	4071859.0	162302.0	24956.0	0.0	2442202.0	36937639.0	94.0	1.1	9.3	0.4	0.1	0.0	5.6	84.6	100	100	100.00	38	4363895800	26.0	24.0	23.9	26.1	0.0	33.4	14.3	bulk
863015	SRR1706564	SRP051076	SRS788253	SRX806619	SRA214041	GEO		Transcriptional profiling of cutaneous Mrgprd free nerve endings and C-LTMRs	Cutaneous C-unmyelinated free nerve endings and hair follicles-innervating C-LTMRs convey two opposite aspects of touch sensation: a sensation of pain and a sensation of pleasant touch. The molecular mechanisms underlying these diametrically opposite functions are unknown. Here we used a mouse model that genetically marks C-LTMRs and the free nerve endings MRGPRD+ neurons in combination with fluorescent cell surface labeling, flow cytometry and RNA deep-sequencing technology. Cluster analysis of the RNA-Seq profiles of the purified neuronal subsets revealed 156 and 184 genes differentially expressed in MRGPRD-expressing neurons and C-LTMRs, respectively. 48 MRGPD- and 67 C-LTMRs-enriched genes were validated using a triple staining experiment approach and the Cav3.3 channel, found to be exclusively expressed in C-LTMRs, was validated using electrophysiology. Furthermore, our study greatly expands the molecular characterization of C-LTMRs and suggests that this particular population of neurons shares common transcriptional signatures with A and A low threshold mechanoreceptors. Overall design: RNA profiles of FACS-sorted subsets of sensory neurons, namely Mrgprd+ neurons (DP, double-positive=IB4+GINIP+), C-LTMRs (IB4-GINIP+) and remaining cells (DN, double-negative=IB4-GINIP-) were generated by deep sequencing in duplicate using Illumina HiSeq 2000.		GSM1564178: DN-1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Neurons were sorted directly in RLT-lysis buffer from RNeasy Micro Kit (Qiagen), snap-frozen at -80°C and processed for RNA extraction following manufacturer's recommendations. 50 nanograms of high-quality total RNAs were amplified with the Amino Allyl Message Amp II Amplification kit (Life Technologies, Carlsbad, CA). RNA-Seq libraries were constructed with the TruSeq RNA sample preparation (Low-throughput protocol) kit from Illumina.	Illumina HiSeq 2000	genotype/variation;;GINIP+/mcherry|sensory neuron subset;;remaining cells (DN, double-negative=IB4-GINIP-)|source_name;;Remaining sensory neurons|tissue;;dorsal root ganglia (DRG)	GEO Accession;;GSM1564178		GSM1564178	DN-1	10360350000	51801750	2015-02-02 16:00:02	7222802465	10360350000	51801750	2	51801750	index:0,count:51801750,average:100,stdev:0|index:1,count:51801750,average:100,stdev:0	GSM1564178_r1	GEO					4.35	3.34	0.05	8007358064	8015932770	7257286101	7322816840	100.11	100.9	48902471	46510484	188.441	498.359	148	469921	87.13	96.31	56188906	42608728	56188906	42608728	91.44	92.24	56188906	44717276	56188906	40808712	225895586	2.82	1.14	0	8.99	0	0.44	0	0.04	0	0.00	0	5.12	0	48902471	0	200	0	197.85	0	1.56	0	0.01	0	1.42	0	0.01	0	250.32	0	0.41	0	588683	0	51801750	0	4659189	0	228162	0	19936	0	0	0	2651181	0	11144	0	0	0	91475	0	16405186	0	59307	0	16567112	0	85.41	0	44243282	0	200249	15470015	77.253893902092	51801750.0	48902471.0	588683.0	4659189.0	228162.0	19936.0	0.0	2651181.0	44243282.0	94.4	1.1	9.0	0.4	0.0	0.0	5.1	85.4	100	100	100.00	38	5180175000	25.9	24.1	24.0	26.0	0.0	33.6	14.7	bulk
863023	SRR1706565	SRP051076	SRS788252	SRX806620	SRA214041	GEO		Transcriptional profiling of cutaneous Mrgprd free nerve endings and C-LTMRs	Cutaneous C-unmyelinated free nerve endings and hair follicles-innervating C-LTMRs convey two opposite aspects of touch sensation: a sensation of pain and a sensation of pleasant touch. The molecular mechanisms underlying these diametrically opposite functions are unknown. Here we used a mouse model that genetically marks C-LTMRs and the free nerve endings MRGPRD+ neurons in combination with fluorescent cell surface labeling, flow cytometry and RNA deep-sequencing technology. Cluster analysis of the RNA-Seq profiles of the purified neuronal subsets revealed 156 and 184 genes differentially expressed in MRGPRD-expressing neurons and C-LTMRs, respectively. 48 MRGPD- and 67 C-LTMRs-enriched genes were validated using a triple staining experiment approach and the Cav3.3 channel, found to be exclusively expressed in C-LTMRs, was validated using electrophysiology. Furthermore, our study greatly expands the molecular characterization of C-LTMRs and suggests that this particular population of neurons shares common transcriptional signatures with A and A low threshold mechanoreceptors. Overall design: RNA profiles of FACS-sorted subsets of sensory neurons, namely Mrgprd+ neurons (DP, double-positive=IB4+GINIP+), C-LTMRs (IB4-GINIP+) and remaining cells (DN, double-negative=IB4-GINIP-) were generated by deep sequencing in duplicate using Illumina HiSeq 2000.		GSM1564179: DN-2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Neurons were sorted directly in RLT-lysis buffer from RNeasy Micro Kit (Qiagen), snap-frozen at -80°C and processed for RNA extraction following manufacturer's recommendations. 50 nanograms of high-quality total RNAs were amplified with the Amino Allyl Message Amp II Amplification kit (Life Technologies, Carlsbad, CA). RNA-Seq libraries were constructed with the TruSeq RNA sample preparation (Low-throughput protocol) kit from Illumina.	Illumina HiSeq 2000	genotype/variation;;GINIP+/mcherry|sensory neuron subset;;remaining cells (DN, double-negative=IB4-GINIP-)|source_name;;Remaining sensory neurons|tissue;;dorsal root ganglia (DRG)	GEO Accession;;GSM1564179		GSM1564179	DN-2	8609015800	43045079	2015-02-02 16:00:02	5997039778	8609015800	43045079	2	43045079	index:0,count:43045079,average:100,stdev:0|index:1,count:43045079,average:100,stdev:0	GSM1564179_r1	GEO					4.39	3.4	0.07	6688108707	6697269789	6063801911	6122800718	100.14	100.97	40568030	38675887	190.089	485.012	147	384411	87.27	96.42	46582005	35403332	46582005	35403332	91.54	92.41	46582005	37136783	46582005	33932220	186395208	2.79	1.04	0	8.94	0	0.39	0	0.03	0	0.00	0	5.33	0	40568030	0	200	0	197.91	0	1.57	0	0.01	0	1.43	0	0.02	0	264.89	0	0.43	0	445852	0	43045079	0	3849920	0	166833	0	14786	0	0	0	2295430	0	8709	0	0	0	67606	0	12807401	0	49408	0	12933124	0	85.30	0	36718110	0	186949	12239247	65.468373727594	43045079.0	40568030.0	445852.0	3849920.0	166833.0	14786.0	0.0	2295430.0	36718110.0	94.2	1.0	8.9	0.4	0.0	0.0	5.3	85.3	100	100	100.00	38	4304507900	26.1	23.9	23.8	26.2	0.0	33.4	14.5	bulk
465159	SRR1782641	SRP053008	SRS832981	SRX861698	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598390: S166_RFPminus_1 single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598390		GSM1598390	S166_RFPminus_1 single	2121458072	27913922	2015-04-23 16:23:12	1414307462	2121458072	27913922	1	27913922	index:0,count:27913922,average:76,stdev:0	GSM1598390_r1	GEO					1.22	3.43	0.13	1953796106	1940331744	1761633380	1762767652	99.31	100.06	0	0	0	0	0	0	78.1	86.62	30712121	20261358	30712121	20261358	82.88	82.86	30712121	21498966	30712121	19382058	229859081	11.76	0.63	0	9.14	0	0.63	0	0.18	0	0.00	0	6.26	0	25941341	0	76	0	75.31	0	1.53	0	0.00	0	1.17	0	0.00	0	425.81	0	0.39	0	175651	0	27913922	0	2550573	0	175888	0	49436	0	0	0	1747257	0	3089	0	0	0	23971	0	3636276	0	11002	0	3674338	0	83.80	0	23390768	0	164000	4285008	26.128097560976	27913922.0	25941341.0	175651.0	2550573.0	175888.0	49436.0	0.0	1747257.0	23390768.0	92.9	0.6	9.1	0.6	0.2	0.0	6.3	83.8	76	76	76.00	38	2121458072	24.3	25.4	25.2	25.1	0.0	34.7	14.8	bulk
465162	SRR1782642	SRP053008	SRS832978	SRX861699	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598391: S166_RFPminus_1 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598391		GSM1598391	S166_RFPminus_1 paired-end	3712246600	18561233	2015-04-23 16:23:12	2666592844	3712246600	18561233	2	18561233	index:0,count:18561233,average:100,stdev:0|index:1,count:18561233,average:100,stdev:0	GSM1598391_r1	GEO					1.27	3.34	0.13	3144814419	3133232008	2942654337	2944915592	99.63	100.08	17631903	15824124	231.612	905.031	175	128239	82.59	88.28	19886554	14562131	19886554	14562131	85.11	85.01	19886554	15005853	19886554	14023304	360059658	11.45	0.90	0	6.12	0	0.29	0	0.06	0	0.00	0	4.66	0	17631903	0	200	0	194.84	0	1.01	0	0.45	0	1.26	0	0.00	0	206.24	0	0.31	0	166511	0	18561233	0	1136068	0	53372	0	10254	0	0	0	865704	0	5201	0	0	0	43567	0	6059875	0	218213	0	6326856	0	88.87	0	16495835	0	203594	6784509	33.323717791291	18561233.0	17631903.0	166511.0	1136068.0	53372.0	10254.0	0.0	865704.0	16495835.0	95.0	0.9	6.1	0.3	0.1	0.0	4.7	88.9	100	100	100.00	38	1856123300	24.2	25.5	25.2	25.1	0.0	34.1	17.3	bulk
465166	SRR1782643	SRP053008	SRS832978	SRX861699	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598391: S166_RFPminus_1 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598391		GSM1598391	S166_RFPminus_1 paired-end	3722293000	18611465	2015-04-23 16:23:12	2683593036	3722293000	18611465	2	18611465	index:0,count:18611465,average:100,stdev:0|index:1,count:18611465,average:100,stdev:0	GSM1598391_r2	GEO					1.28	3.34	0.12	3153373778	3141665827	2950545224	2952728531	99.63	100.07	17682383	15865987	231.637	907.579	173	128662	82.59	88.28	19941980	14603306	19941980	14603306	85.12	85.02	19941980	15050423	19941980	14064458	360849547	11.44	0.89	0	6.12	0	0.28	0	0.05	0	0.00	0	4.65	0	17682383	0	200	0	194.82	0	1.01	0	0.45	0	1.26	0	0.00	0	116.93	0	0.32	0	166188	0	18611465	0	1139820	0	52934	0	10029	0	0	0	866119	0	5149	0	0	0	43459	0	6074202	0	218399	0	6341209	0	88.88	0	16542563	0	203884	6799936	33.351984461753	18611465.0	17682383.0	166188.0	1139820.0	52934.0	10029.0	0.0	866119.0	16542563.0	95.0	0.9	6.1	0.3	0.1	0.0	4.7	88.9	100	100	100.00	38	1861146500	24.2	25.5	25.2	25.1	0.0	34.0	17.1	bulk
465170	SRR1782644	SRP053008	SRS832979	SRX861700	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598392: S167_RFPplus_1  single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598392		GSM1598392	S167_RFPplus_1 single	2432100928	32001328	2015-04-23 16:23:12	1631441974	2432100928	32001328	1	32001328	index:0,count:32001328,average:76,stdev:0	GSM1598392_r1	GEO					1.33	3.52	0.13	2212466841	2200198955	2041256968	2044711696	99.45	100.17	0	0	0	0	0	0	80.1	86.8	33898918	23530445	33898918	23530445	82.77	83.06	33898918	24316288	33898918	22516063	264680103	11.96	0.64	0	7.09	0	0.57	0	0.17	0	0.00	0	7.46	0	29376776	0	76	0	75.30	0	1.50	0	0.00	0	1.17	0	0.00	0	698.21	0	0.38	0	205210	0	32001328	0	2268187	0	182205	0	54831	0	0	0	2387516	0	3526	0	0	0	27687	0	4248646	0	12009	0	4291868	0	84.71	0	27108589	0	170232	4432987	26.040856008271	32001328.0	29376776.0	205210.0	2268187.0	182205.0	54831.0	0.0	2387516.0	27108589.0	91.8	0.6	7.1	0.6	0.2	0.0	7.5	84.7	76	76	76.00	38	2432100928	24.2	25.7	25.1	25.0	0.0	34.6	14.9	bulk
465174	SRR1782645	SRP053008	SRS832980	SRX861701	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598393: S167_RFPplus_1 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598393		GSM1598393	S167_RFPplus_1 paired-end	4314695400	21573477	2015-04-23 16:23:12	3090308196	4314695400	21573477	2	21573477	index:0,count:21573477,average:100,stdev:0|index:1,count:21573477,average:100,stdev:0	GSM1598393_r1	GEO					1.4	3.49	0.13	3536280158	3527424321	3378970795	3385079064	99.75	100.18	20257147	18388467	218.187	832.996	164	163344	84.44	88.4	21832760	17104568	21832760	17104568	84.94	85.12	21832760	17206645	21832760	16469774	411436113	11.63	0.95	0	4.21	0	0.27	0	0.05	0	0.00	0	5.78	0	20257147	0	200	0	194.85	0	1.00	0	0.45	0	1.25	0	0.00	0	181.46	0	0.31	0	204862	0	21573477	0	908368	0	59246	0	10675	0	0	0	1246409	0	5836	0	0	0	50634	0	7137317	0	242300	0	7436087	0	89.69	0	19348779	0	212206	7146816	33.678670725616	21573477.0	20257147.0	204862.0	908368.0	59246.0	10675.0	0.0	1246409.0	19348779.0	93.9	0.9	4.2	0.3	0.0	0.0	5.8	89.7	100	100	100.00	38	2157347700	24.1	25.7	25.2	25.0	0.0	33.9	16.8	bulk
465178	SRR1782646	SRP053008	SRS832980	SRX861701	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598393: S167_RFPplus_1 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598393		GSM1598393	S167_RFPplus_1 paired-end	4328662600	21643313	2015-04-23 16:23:12	3111300096	4328662600	21643313	2	21643313	index:0,count:21643313,average:100,stdev:0|index:1,count:21643313,average:100,stdev:0	GSM1598393_r2	GEO					1.41	3.48	0.13	3548272325	3539382389	3390154851	3396184612	99.75	100.18	20325207	18446670	218.248	834.008	164	163978	84.45	88.42	21903004	17164639	21903004	17164639	84.97	85.15	21903004	17269946	21903004	16528723	412153620	11.62	0.94	0	4.22	0	0.27	0	0.05	0	0.00	0	5.77	0	20325207	0	200	0	194.84	0	1.00	0	0.45	0	1.25	0	0.00	0	184.63	0	0.31	0	204348	0	21643313	0	913059	0	59350	0	10907	0	0	0	1247849	0	5664	0	0	0	50673	0	7156358	0	242755	0	7455450	0	89.69	0	19412148	0	212265	7166659	33.762791793277	21643313.0	20325207.0	204348.0	913059.0	59350.0	10907.0	0.0	1247849.0	19412148.0	93.9	0.9	4.2	0.3	0.1	0.0	5.8	89.7	100	100	100.00	38	2164331300	24.1	25.7	25.2	25.0	0.0	33.8	16.6	bulk
465182	SRR1782647	SRP053008	SRS832982	SRX861702	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598394: S168_GFPplus_1 single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598394		GSM1598394	S168_GFPplus_1 single	2732014484	35947559	2015-04-23 16:23:12	1827853133	2732014484	35947559	1	35947559	index:0,count:35947559,average:76,stdev:0	GSM1598394_r1	GEO					1.68	3.39	0.08	2469040992	2448239038	2294027909	2287679990	99.16	99.72	0	0	0	0	0	0	79.74	85.8	37374157	26117801	37374157	26117801	82.11	82.29	37374157	26896398	37374157	25048037	311751290	12.63	0.52	0	6.44	0	0.35	0	0.19	0	0.00	0	8.35	0	32755736	0	76	0	75.36	0	1.46	0	0.00	0	1.17	0	0.00	0	613.32	0	0.37	0	187634	0	35947559	0	2316608	0	124534	0	67183	0	0	0	3000106	0	3226	0	0	0	29660	0	4445673	0	11847	0	4490406	0	84.68	0	30439128	0	168951	4608970	27.279921397328	35947559.0	32755736.0	187634.0	2316608.0	124534.0	67183.0	0.0	3000106.0	30439128.0	91.1	0.5	6.4	0.3	0.2	0.0	8.3	84.7	76	76	76.00	38	2732014484	24.1	25.5	25.1	25.2	0.0	34.6	14.8	bulk
465186	SRR1782648	SRP053008	SRS832983	SRX861703	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598395: S168_GFPplus_1 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598395		GSM1598395	S168_GFPplus_1 paired-end	4761948400	23809742	2015-04-23 16:23:12	3397156964	4761948400	23809742	2	23809742	index:0,count:23809742,average:100,stdev:0|index:1,count:23809742,average:100,stdev:0	GSM1598395_r1	GEO					1.78	3.38	0.08	3866057435	3841189093	3703329104	3692863303	99.36	99.72	22242005	20316447	214.221	884.943	160	185798	83.68	87.39	23768464	18611153	23768464	18611153	84.2	84.3	23768464	18728462	23768464	17953647	475316784	12.29	0.80	0	3.97	0	0.17	0	0.07	0	0.00	0	6.35	0	22242005	0	200	0	195.22	0	1.00	0	0.46	0	1.24	0	0.00	0	185.13	0	0.29	0	189408	0	23809742	0	944544	0	39562	0	16070	0	0	0	1512105	0	5407	0	0	0	52412	0	7426231	0	246614	0	7730664	0	89.45	0	21297461	0	211506	7398485	34.980024207351	23809742.0	22242005.0	189408.0	944544.0	39562.0	16070.0	0.0	1512105.0	21297461.0	93.4	0.8	4.0	0.2	0.1	0.0	6.4	89.4	100	100	100.00	38	2380974200	24.0	25.6	25.3	25.1	0.0	33.9	16.8	bulk
465191	SRR1782649	SRP053008	SRS832983	SRX861703	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598395: S168_GFPplus_1 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598395		GSM1598395	S168_GFPplus_1 paired-end	4774813200	23874066	2015-04-23 16:23:12	3418475508	4774813200	23874066	2	23874066	index:0,count:23874066,average:100,stdev:0|index:1,count:23874066,average:100,stdev:0	GSM1598395_r2	GEO					1.79	3.39	0.08	3876723706	3851568910	3713582390	3702834359	99.35	99.71	22305044	20370264	214.261	886.323	161	187388	83.67	87.38	23832798	18663364	23832798	18663364	84.21	84.3	23832798	18782817	23832798	18005571	476798561	12.30	0.79	0	3.97	0	0.17	0	0.07	0	0.00	0	6.34	0	22305044	0	200	0	195.21	0	1.00	0	0.46	0	1.24	0	0.00	0	172.93	0	0.29	0	188680	0	23874066	0	946814	0	39682	0	16002	0	0	0	1513338	0	5454	0	0	0	53252	0	7437557	0	245507	0	7741770	0	89.46	0	21358230	0	211744	7408588	34.988419978842	23874066.0	22305044.0	188680.0	946814.0	39682.0	16002.0	0.0	1513338.0	21358230.0	93.4	0.8	4.0	0.2	0.1	0.0	6.3	89.5	100	100	100.00	38	2387406600	24.0	25.6	25.3	25.1	0.0	33.8	16.6	bulk
465219	SRR1782650	SRP053008	SRS832984	SRX861704	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598396: S334_RFPminus_2 single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598396		GSM1598396	S334_RFPminus_2 single	2502839220	32932095	2015-04-23 16:23:12	1722693541	2502839220	32932095	1	32932095	index:0,count:32932095,average:76,stdev:0	GSM1598396_r1	GEO					1.38	3.42	0.11	2290005574	2271800678	2085479967	2084816442	99.21	99.97	0	0	0	0	0	0	77.86	85.49	35589231	23682137	35589231	23682137	81.78	81.86	35589231	24875393	35589231	22678345	296553995	12.95	0.69	0	8.24	0	0.68	0	0.17	0	0.00	0	6.79	0	30415787	0	76	0	75.28	0	1.47	0	0.00	0	1.20	0	0.00	0	338.73	0	0.56	0	227485	0	32932095	0	2713541	0	223731	0	55374	0	0	0	2237203	0	3560	0	0	0	27033	0	4126146	0	13769	0	4170508	0	84.12	0	27702246	0	170730	4578429	26.816780882095	32932095.0	30415787.0	227485.0	2713541.0	223731.0	55374.0	0.0	2237203.0	27702246.0	92.4	0.7	8.2	0.7	0.2	0.0	6.8	84.1	76	76	76.00	38	2502839220	24.3	25.4	25.1	25.2	0.0	33.2	13.3	bulk
465223	SRR1782651	SRP053008	SRS832985	SRX861705	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598397: S334_RFPminus_2 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598397		GSM1598397	S334_RFPminus_2 paired-end	4602887200	23014436	2015-04-23 16:23:12	3310183087	4602887200	23014436	2	23014436	index:0,count:23014436,average:100,stdev:0|index:1,count:23014436,average:100,stdev:0	GSM1598397_r1	GEO					1.38	3.33	0.1	3806596135	3791444241	3592006141	3593596128	99.6	100.04	21739760	19738413	221.450	838.837	164	169173	82.52	87.47	24085695	17940539	24085695	17940539	84.25	84.25	24085695	18316158	24085695	17278236	470267788	12.35	0.96	0	5.35	0	0.32	0	0.06	0	0.00	0	5.16	0	21739760	0	200	0	194.96	0	1.00	0	0.45	0	1.28	0	0.00	0	172.61	0	0.31	0	221601	0	23014436	0	1230356	0	73835	0	13695	0	0	0	1187146	0	6382	0	0	0	52631	0	7360548	0	254968	0	7674529	0	89.12	0	20509404	0	216706	7819186	36.082000498371	23014436.0	21739760.0	221601.0	1230356.0	73835.0	13695.0	0.0	1187146.0	20509404.0	94.5	1.0	5.3	0.3	0.1	0.0	5.2	89.1	100	100	100.00	38	2301443600	24.2	25.7	25.1	25.1	0.0	34.0	17.0	bulk
465226	SRR1782652	SRP053008	SRS832985	SRX861705	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598397: S334_RFPminus_2 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598397		GSM1598397	S334_RFPminus_2 paired-end	4618824000	23094120	2015-04-23 16:23:12	3333733388	4618824000	23094120	2	23094120	index:0,count:23094120,average:100,stdev:0|index:1,count:23094120,average:100,stdev:0	GSM1598397_r2	GEO					1.39	3.32	0.1	3820264712	3805275846	3605323688	3606946528	99.61	100.05	21817754	19805870	221.502	837.676	163	169774	82.54	87.48	24166558	18008271	24166558	18008271	84.26	84.25	24166558	18383485	24166558	17343245	471737742	12.35	0.96	0	5.34	0	0.32	0	0.06	0	0.00	0	5.15	0	21817754	0	200	0	194.93	0	1.00	0	0.45	0	1.28	0	0.00	0	183.94	0	0.32	0	220906	0	23094120	0	1232240	0	74205	0	13548	0	0	0	1188613	0	6546	0	0	0	53030	0	7379206	0	256354	0	7695136	0	89.14	0	20585514	0	216738	7843854	36.190488054702	23094120.0	21817754.0	220906.0	1232240.0	74205.0	13548.0	0.0	1188613.0	20585514.0	94.5	1.0	5.3	0.3	0.1	0.0	5.1	89.1	100	100	100.00	38	2309412000	24.2	25.6	25.1	25.1	0.0	33.9	16.8	bulk
465230	SRR1782653	SRP053008	SRS832986	SRX861706	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598398: S335_RFPplus_2 single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598398		GSM1598398	S335_RFPplus_2 single	2764599484	36376309	2015-04-23 16:23:12	1896320205	2764599484	36376309	1	36376309	index:0,count:36376309,average:76,stdev:0	GSM1598398_r1	GEO					1.52	3.5	0.09	2528090181	2509635754	2330920276	2330917270	99.27	100.0	0	0	0	0	0	0	78.69	85.33	38698480	26409575	38698480	26409575	81.54	81.74	38698480	27363576	38698480	25296897	335488770	13.27	0.58	0	7.18	0	0.57	0	0.18	0	0.00	0	6.99	0	33559908	0	76	0	75.32	0	1.45	0	0.00	0	1.19	0	0.00	0	274.54	0	0.56	0	210685	0	36376309	0	2611318	0	206137	0	66025	0	0	0	2544239	0	3529	0	0	0	29825	0	4536347	0	13465	0	4583166	0	85.08	0	30948590	0	173555	4731094	27.259911843508	36376309.0	33559908.0	210685.0	2611318.0	206137.0	66025.0	0.0	2544239.0	30948590.0	92.3	0.6	7.2	0.6	0.2	0.0	7.0	85.1	76	76	76.00	38	2764599484	24.1	25.5	25.0	25.5	0.0	33.4	13.5	bulk
465234	SRR1782654	SRP053008	SRS832987	SRX861707	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598399: S335_RFPplus_2 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598399		GSM1598399	S335_RFPplus_2 paired-end	5083234800	25416174	2015-04-23 16:23:12	3640824969	5083234800	25416174	2	25416174	index:0,count:25416174,average:100,stdev:0|index:1,count:25416174,average:100,stdev:0	GSM1598399_r1	GEO					1.54	3.42	0.1	4168740352	4153051337	3981123810	3982997302	99.62	100.05	24118369	22033880	214.343	800.594	157	200260	83.29	87.26	25982211	20089358	25982211	20089358	83.91	84.04	25982211	20236606	25982211	19350021	530297659	12.72	0.75	0	4.31	0	0.27	0	0.05	0	0.00	0	4.78	0	24118369	0	200	0	195.20	0	1.00	0	0.45	0	1.28	0	0.00	0	170.71	0	0.29	0	190967	0	25416174	0	1094728	0	68259	0	13407	0	0	0	1216139	0	6369	0	0	0	58241	0	8143655	0	267829	0	8476094	0	90.59	0	23023641	0	222183	8110600	36.504142981236	25416174.0	24118369.0	190967.0	1094728.0	68259.0	13407.0	0.0	1216139.0	23023641.0	94.9	0.8	4.3	0.3	0.1	0.0	4.8	90.6	100	100	100.00	38	2541617400	24.0	25.7	25.0	25.3	0.0	34.1	17.3	bulk
465238	SRR1782655	SRP053008	SRS832987	SRX861707	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598399: S335_RFPplus_2 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598399		GSM1598399	S335_RFPplus_2 paired-end	5095594400	25477972	2015-04-23 16:23:12	3663347248	5095594400	25477972	2	25477972	index:0,count:25477972,average:100,stdev:0|index:1,count:25477972,average:100,stdev:0	GSM1598399_r2	GEO					1.54	3.41	0.1	4179074966	4163405129	3990676920	3992687725	99.63	100.05	24180613	22084964	214.420	798.192	157	200311	83.28	87.25	26054326	20137608	26054326	20137608	83.9	84.04	26054326	20287097	26054326	19396978	532067640	12.73	0.75	0	4.32	0	0.27	0	0.05	0	0.00	0	4.77	0	24180613	0	200	0	195.18	0	1.00	0	0.45	0	1.27	0	0.00	0	197.25	0	0.30	0	190068	0	25477972	0	1099464	0	68456	0	13404	0	0	0	1215499	0	6575	0	0	0	58239	0	8161074	0	269421	0	8495309	0	90.59	0	23081149	0	222173	8130076	36.593447448610	25477972.0	24180613.0	190068.0	1099464.0	68456.0	13404.0	0.0	1215499.0	23081149.0	94.9	0.7	4.3	0.3	0.1	0.0	4.8	90.6	100	100	100.00	38	2547797200	24.0	25.7	25.0	25.3	0.0	34.0	17.1	bulk
465243	SRR1782656	SRP053008	SRS832989	SRX861708	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598400: S336_GFPplus_2 single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598400		GSM1598400	S336_GFPplus_2 single	3238390096	42610396	2015-04-23 16:23:12	2222326167	3238390096	42610396	1	42610396	index:0,count:42610396,average:76,stdev:0	GSM1598400_r1	GEO					1.78	3.34	0.06	2925341759	2898878604	2717494262	2708523273	99.1	99.67	0	0	0	0	0	0	78.79	84.8	44235420	30584477	44235420	30584477	81.2	81.33	44235420	31519995	44235420	29335085	396716584	13.56	0.54	0	6.46	0	0.35	0	0.18	0	0.00	0	8.37	0	38819517	0	76	0	75.34	0	1.45	0	0.00	0	1.20	0	0.00	0	463.44	0	0.57	0	229725	0	42610396	0	2751869	0	148023	0	77643	0	0	0	3565213	0	3661	0	0	0	32946	0	5003459	0	14374	0	5054440	0	84.65	0	36067648	0	176073	5193876	29.498423949157	42610396.0	38819517.0	229725.0	2751869.0	148023.0	77643.0	0.0	3565213.0	36067648.0	91.1	0.5	6.5	0.3	0.2	0.0	8.4	84.6	76	76	76.00	38	3238390096	24.2	25.5	25.1	25.2	0.0	33.1	13.2	bulk
465247	SRR1782657	SRP053008	SRS832988	SRX861709	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598401: S336_GFPplus_2 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598401		GSM1598401	S336_GFPplus_2 paired-end	5342437200	26712186	2015-04-23 16:23:12	3818313469	5342437200	26712186	2	26712186	index:0,count:26712186,average:100,stdev:0|index:1,count:26712186,average:100,stdev:0	GSM1598401_r1	GEO					1.8	3.29	0.06	4348327805	4320190111	4166289663	4154187571	99.35	99.71	25060330	22924211	214.334	884.889	157	207818	83.03	86.68	26755662	20806528	26755662	20806528	83.51	83.57	26755662	20927674	26755662	20061157	565784100	13.01	0.73	0	3.95	0	0.16	0	0.08	0	0.00	0	5.94	0	25060330	0	200	0	195.38	0	1.00	0	0.46	0	1.26	0	0.00	0	144.61	0	0.29	0	194532	0	26712186	0	1056107	0	42178	0	21850	0	0	0	1587828	0	5890	0	0	0	57879	0	8112909	0	268049	0	8444727	0	89.86	0	24004223	0	219218	8073264	36.827559780675	26712186.0	25060330.0	194532.0	1056107.0	42178.0	21850.0	0.0	1587828.0	24004223.0	93.8	0.7	4.0	0.2	0.1	0.0	5.9	89.9	100	100	100.00	38	2671218600	24.1	25.7	25.2	25.0	0.0	33.9	16.8	bulk
465251	SRR1782658	SRP053008	SRS832988	SRX861709	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598401: S336_GFPplus_2 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598401		GSM1598401	S336_GFPplus_2 paired-end	5356187400	26780937	2015-04-23 16:23:12	3842165904	5356187400	26780937	2	26780937	index:0,count:26780937,average:100,stdev:0|index:1,count:26780937,average:100,stdev:0	GSM1598401_r2	GEO					1.8	3.29	0.06	4359620980	4331603557	4177218154	4165307736	99.36	99.71	25127609	22980344	214.352	886.310	157	207731	83.03	86.68	26828792	20862702	26828792	20862702	83.5	83.57	26828792	20982517	26828792	20115512	567251868	13.01	0.72	0	3.95	0	0.16	0	0.08	0	0.00	0	5.93	0	25127609	0	200	0	195.36	0	1.00	0	0.46	0	1.25	0	0.00	0	151.12	0	0.30	0	194040	0	26780937	0	1058506	0	42015	0	22274	0	0	0	1589039	0	5875	0	0	0	58241	0	8130152	0	269191	0	8463459	0	89.87	0	24069103	0	219489	8092361	36.869095945583	26780937.0	25127609.0	194040.0	1058506.0	42015.0	22274.0	0.0	1589039.0	24069103.0	93.8	0.7	4.0	0.2	0.1	0.0	5.9	89.9	100	100	100.00	38	2678093700	24.0	25.7	25.2	25.0	0.0	33.8	16.6	bulk
465254	SRR1782659	SRP053008	SRS832990	SRX861710	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598402: S353_RFPminus_3 single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598402		GSM1598402	S353_RFPminus_3 single	2837150452	37330927	2015-04-23 16:23:12	1917026102	2837150452	37330927	1	37330927	index:0,count:37330927,average:76,stdev:0	GSM1598402_r1	GEO					1.31	3.42	0.13	2641316571	2618272670	2424188658	2421733712	99.13	99.9	0	0	0	0	0	0	77.09	83.99	40548394	27052522	40548394	27052522	80.32	80.36	40548394	28183603	40548394	25881927	381066359	14.43	0.73	0	7.72	0	0.69	0	0.19	0	0.00	0	5.13	0	35090094	0	76	0	75.27	0	1.48	0	0.00	0	1.19	0	0.00	0	646.11	0	0.52	0	270848	0	37330927	0	2882319	0	255905	0	70224	0	0	0	1914704	0	3905	0	0	0	30631	0	4623818	0	15649	0	4674003	0	86.28	0	32207775	0	180661	5141033	28.456794770316	37330927.0	35090094.0	270848.0	2882319.0	255905.0	70224.0	0.0	1914704.0	32207775.0	94.0	0.7	7.7	0.7	0.2	0.0	5.1	86.3	76	76	76.00	38	2837150452	24.4	25.3	25.2	25.0	0.0	34.0	14.0	bulk
465282	SRR1782660	SRP053008	SRS832992	SRX861711	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598403: S353_RFPminus_3 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598403		GSM1598403	S353_RFPminus_3 paired-end	4728663800	23643319	2015-04-23 16:23:12	3418372907	4728663800	23643319	2	23643319	index:0,count:23643319,average:100,stdev:0|index:1,count:23643319,average:100,stdev:0	GSM1598403_r1	GEO					1.35	3.34	0.13	4020874238	3999489997	3808976887	3806450727	99.47	99.93	22734844	20600886	226.931	844.902	166	167925	81.4	85.95	25050360	18505830	25050360	18505830	82.79	82.76	25050360	18821140	25050360	17819593	563155470	14.01	0.98	0	5.09	0	0.32	0	0.07	0	0.00	0	3.45	0	22734844	0	200	0	194.96	0	1.00	0	0.45	0	1.26	0	0.00	0	211.73	0	0.32	0	231256	0	23643319	0	1202801	0	76281	0	16416	0	0	0	815778	0	6238	0	0	0	51949	0	7396906	0	263580	0	7718673	0	91.07	0	21532043	0	224577	7924260	35.285269640257	23643319.0	22734844.0	231256.0	1202801.0	76281.0	16416.0	0.0	815778.0	21532043.0	96.2	1.0	5.1	0.3	0.1	0.0	3.5	91.1	100	100	100.00	38	2364331900	24.4	25.5	25.1	25.0	0.0	34.2	17.7	bulk
465286	SRR1782661	SRP053008	SRS832992	SRX861711	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598403: S353_RFPminus_3 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Proliferating Progenitors Btg2 negative|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598403		GSM1598403	S353_RFPminus_3 paired-end	4738956600	23694783	2015-04-23 16:23:12	3439092101	4738956600	23694783	2	23694783	index:0,count:23694783,average:100,stdev:0|index:1,count:23694783,average:100,stdev:0	GSM1598403_r2	GEO					1.35	3.34	0.13	4029833458	4008604998	3817244988	3814953075	99.47	99.94	22786012	20642095	226.957	846.152	166	169002	81.41	85.96	25109346	18550394	25109346	18550394	82.79	82.77	25109346	18864515	25109346	17860622	563453031	13.98	0.97	0	5.09	0	0.32	0	0.07	0	0.00	0	3.44	0	22786012	0	200	0	194.93	0	1.00	0	0.45	0	1.26	0	0.00	0	159.44	0	0.32	0	230584	0	23694783	0	1206250	0	76081	0	16411	0	0	0	816279	0	6121	0	0	0	52482	0	7413475	0	262967	0	7735045	0	91.07	0	21579762	0	224641	7940451	35.347291901300	23694783.0	22786012.0	230584.0	1206250.0	76081.0	16411.0	0.0	816279.0	21579762.0	96.2	1.0	5.1	0.3	0.1	0.0	3.4	91.1	100	100	100.00	38	2369478300	24.4	25.4	25.1	25.0	0.0	34.1	17.5	bulk
465307	SRR1782666	SRP053008	SRS832996	SRX861715	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598407: S355_GFPplus_3 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598407		GSM1598407	S355_GFPplus_3 paired-end	3970763800	19853819	2015-04-23 16:23:12	2858546902	3970763800	19853819	2	19853819	index:0,count:19853819,average:100,stdev:0|index:1,count:19853819,average:100,stdev:0	GSM1598407_r1	GEO					1.94	3.37	0.07	3366866181	3338092436	3227820482	3212841285	99.15	99.54	19049852	17308423	222.684	926.914	166	145832	82.58	86.16	20312639	15731229	20312639	15731229	83.06	83.16	20312639	15823702	20312639	15182320	452762984	13.45	0.64	0	3.99	0	0.16	0	0.08	0	0.00	0	3.80	0	19049852	0	200	0	195.44	0	1.00	0	0.46	0	1.24	0	0.00	0	199.65	0	0.29	0	126809	0	19853819	0	792158	0	32432	0	16410	0	0	0	755125	0	4350	0	0	0	42265	0	5995610	0	205908	0	6248133	0	91.96	0	18257694	0	204911	6001770	29.289642820542	19853819.0	19049852.0	126809.0	792158.0	32432.0	16410.0	0.0	755125.0	18257694.0	96.0	0.6	4.0	0.2	0.1	0.0	3.8	92.0	100	100	100.00	38	1985381900	24.2	25.4	25.1	25.3	0.0	34.2	17.6	bulk
465310	SRR1782667	SRP053008	SRS832996	SRX861715	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598407: S355_GFPplus_3 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598407		GSM1598407	S355_GFPplus_3 paired-end	3981876200	19909381	2015-04-23 16:23:12	2876837898	3981876200	19909381	2	19909381	index:0,count:19909381,average:100,stdev:0|index:1,count:19909381,average:100,stdev:0	GSM1598407_r2	GEO					1.94	3.37	0.07	3376636511	3347708069	3237064549	3221894823	99.14	99.53	19106682	17357807	222.675	929.260	164	146311	82.59	86.17	20373972	15779264	20373972	15779264	83.08	83.17	20373972	15872931	20373972	15228979	453728795	13.44	0.64	0	3.99	0	0.16	0	0.08	0	0.00	0	3.79	0	19106682	0	200	0	195.42	0	1.00	0	0.46	0	1.25	0	0.00	0	252.37	0	0.30	0	126476	0	19909381	0	795182	0	32732	0	16130	0	0	0	753837	0	4367	0	0	0	42476	0	6011967	0	206174	0	6264984	0	91.97	0	18311500	0	205241	6023602	29.348921511784	19909381.0	19106682.0	126476.0	795182.0	32732.0	16130.0	0.0	753837.0	18311500.0	96.0	0.6	4.0	0.2	0.1	0.0	3.8	92.0	100	100	100.00	38	1990938100	24.2	25.4	25.1	25.3	0.0	34.1	17.4	bulk
930580	SRR1782662	SRP053008	SRS832991	SRX861712	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598404: S354_RFPplus_3 single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598404		GSM1598404	S354_RFPplus_3 single	2292484596	30164271	2015-04-23 16:23:12	1549660432	2292484596	30164271	1	30164271	index:0,count:30164271,average:76,stdev:0	GSM1598404_r1	GEO					1.58	3.52	0.12	2142642920	2122667726	1990050212	1986747922	99.07	99.83	0	0	0	0	0	0	77.25	83.16	32384166	21971226	32384166	21971226	79.39	79.57	32384166	22581121	32384166	21023909	328928944	15.35	0.62	0	6.70	0	0.61	0	0.21	0	0.00	0	4.89	0	28442029	0	76	0	75.32	0	1.45	0	0.00	0	1.19	0	0.00	0	486.96	0	0.50	0	188214	0	30164271	0	2021733	0	183748	0	64564	0	0	0	1473930	0	2788	0	0	0	24222	0	3631837	0	10607	0	3669454	0	87.59	0	26420296	0	168860	3782649	22.401095582139	30164271.0	28442029.0	188214.0	2021733.0	183748.0	64564.0	0.0	1473930.0	26420296.0	94.3	0.6	6.7	0.6	0.2	0.0	4.9	87.6	76	76	76.00	38	2292484596	24.4	25.3	24.9	25.4	0.0	34.2	14.3	bulk
930588	SRR1782663	SRP053008	SRS832993	SRX861713	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598405: S354_RFPplus_3 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598405		GSM1598405	S354_RFPplus_3 paired-end	4090281200	20451406	2015-04-23 16:23:12	2956345621	4090281200	20451406	2	20451406	index:0,count:20451406,average:100,stdev:0|index:1,count:20451406,average:100,stdev:0	GSM1598405_r1	GEO					1.66	3.46	0.12	3506226600	3484401499	3360422036	3354890776	99.38	99.84	19706122	17851383	228.004	848.066	167	143294	81.59	85.16	21112867	16078920	21112867	16078920	81.94	82.06	21112867	16146255	21112867	15493142	524284596	14.95	0.79	0	4.03	0	0.27	0	0.06	0	0.00	0	3.31	0	19706122	0	200	0	195.23	0	1.00	0	0.46	0	1.25	0	0.00	0	196.33	0	0.31	0	160616	0	20451406	0	825125	0	55207	0	12802	0	0	0	677275	0	4864	0	0	0	44589	0	6246497	0	220533	0	6516483	0	92.32	0	18880997	0	213413	6280949	29.430957814191	20451406.0	19706122.0	160616.0	825125.0	55207.0	12802.0	0.0	677275.0	18880997.0	96.4	0.8	4.0	0.3	0.1	0.0	3.3	92.3	100	100	100.00	38	2045140600	24.4	25.4	24.8	25.4	0.0	34.2	17.7	bulk
930597	SRR1782664	SRP053008	SRS832993	SRX861713	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598405: S354_RFPplus_3 paired-end; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Differentiating Progenitors Btg2 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598405		GSM1598405	S354_RFPplus_3 paired-end	4097388200	20486941	2015-04-23 16:23:12	2972541937	4097388200	20486941	2	20486941	index:0,count:20486941,average:100,stdev:0|index:1,count:20486941,average:100,stdev:0	GSM1598405_r2	GEO					1.66	3.45	0.12	3511829205	3490000543	3365655853	3360211811	99.38	99.84	19740790	17882008	228.028	852.055	166	143830	81.59	85.16	21152313	16106640	21152313	16106640	81.93	82.06	21152313	16174544	21152313	15519575	525078159	14.95	0.78	0	4.04	0	0.27	0	0.06	0	0.00	0	3.31	0	19740790	0	200	0	195.21	0	1.00	0	0.46	0	1.25	0	0.00	0	232.66	0	0.31	0	159371	0	20486941	0	827346	0	54842	0	12721	0	0	0	678588	0	4822	0	0	0	44487	0	6250826	0	220814	0	6520949	0	92.32	0	18913444	0	213221	6286244	29.482293019918	20486941.0	19740790.0	159371.0	827346.0	54842.0	12721.0	0.0	678588.0	18913444.0	96.4	0.8	4.0	0.3	0.1	0.0	3.3	92.3	100	100	100.00	38	2048694100	24.4	25.4	24.8	25.3	0.0	34.1	17.5	bulk
930604	SRR1782665	SRP053008	SRS832994	SRX861714	SRA235889	GEO		Identification and Expression Patterns of Novel Long Non-Coding RNAs in Neural Progenitors of the Developing Mammalian Cortex	Long non-coding (lnc)RNAs play key roles in many biological processes. Elucidating the function of lncRNAs in cell type specification during organ development requires knowledge about their expression in individual progenitor types rather than in whole tissues. To achieve this during cortical development, we used a dual-reporter mouse line to isolate coexisting proliferating neural stem cells, differentiating neurogenic progenitors and newborn neurons and assessed the expression of lncRNAs by paired-end, high-throughput sequencing. We identified 379 genomic loci encoding novel lncRNAs and performed a comprehensive assessment of cell-specific expression patterns for all, annotated and novel, lncRNAs described to date. Our study provides a powerful new resource for studying these elusive transcripts during stem cell commitment and neurogenesis. Overall design: mRNA profiles of Proliferating Progenitors, Differentiating Progenitors and Neurons from lateral cortex of E14.5 mouse embryos. Each cell type in three biological replicates.		GSM1598406: S355_GFPplus_3 single; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			E14.5 Btg2GFP/Tubb3GFP cortices were dissociated using the papain-based neural dissociation kit (Miltenyi Biotec) after removal of meninges and ganglionic eminences. FACS was performed at 4˚C in the 4-way purity mode with a flow rate of 20 μl/min using side and forward scatter light to eliminate debris and aggregates and gating established for green (488 nm) and red (561 nm) fluorescence. About 1x106 sorted cells from >3 embryos from different litters were immediately lysed in μMACS™ mRNA Isolation Kit and lysates cleaned on LysateClear Colums (Miltenyi) resulting in ca. 1 µg of poly-A RNAs with a integrity number >9.2 Library preparation and enrichment was performed using 15 µl Sera-Mag Oligo(dT) beads (Thermo Scientific) in 50 µl 10 mM Tris-HCl. Samples were treated with 1U Turbo DNase (Ambion) and purified with Agencourt RNAclean XP beads. Eluted mRNA (18 µl) was chemically fragmented with NEBNext-Mg RNA Fragmentation Module (New England Biolabs), re-purified with RNAclean XP beads and eluted in 13,5 µl nuclease-free water. First strand cDNA synthesis was performed using 0.15 µg/µl Random Primers (New England Biolabs), 1x First Strand Synthesis Reaction Buffer (New England Biolabs), 10 U/uL Superscript II (Invitrogen) with an initial hybridization for 5 min at 65°C with mRNA and primers followed by incubation at 25°C for 10 min, 42°C for 50 min, and 70°C for 15 min. After purification with Agencourt Ampure XP-beads (Beckman Coulter), second strand synthesis was performed using the Second Strand Synthesis module (New England Biolabs) replacing the 2nd strand synthesis buffer with a NTP-free buffer and adding equimolar 2.5 mM of d-nucleotides. Incubation for 2.5 h at 16°C was followed by Ampure XP beads purification as described above. End-Repair was done with the NEBnext End Repair Module (New England Biolabs) followed by XP beads purification and A-Tailing using the NEBnext dA-Tailing Module. Adaptors were ligated  (Adaptor-Oligo 1: 5'-ACA-CTC-TTT-CCC-TAC-ACG-ACG-CTC-TTC-CGA-TCT-3', Adaptor-Oligo 2: 5'-P-GAT-CGG-AAG-AGC-ACA-CGT-CTG-AAC-TCC-AGT-CAC-3') using 1x NEBnext Quick Ligation Buffer (New England Biolabs), 0.3 uM DNA Adaptors, 1 uL Quick T4 DNA Ligase (New England Biolabs) in 50 µl. XP beads purification was followed by dUTP cleavage with 1 U USER enzyme mix (New England Biolabs) per sample and direct enrichment using the PCR Enrich Adaptor Ligated cDNA Library module (New England Biolabs) with indexed primers.	Illumina HiSeq 2000	cell type;;Neurons Tubb3 positive|developmental stage;;Embryonic day 14.5|genotype;;Btg2GFP/Tubb3GFP|source_name;;Lateral cortex of the brain|strain;;C57BL/6	GEO Accession;;GSM1598406		GSM1598406	S355_GFPplus_3 single	2416985896	31802446	2015-04-23 16:23:12	1639352263	2416985896	31802446	1	31802446	index:0,count:31802446,average:76,stdev:0	GSM1598406_r1	GEO					1.85	3.4	0.07	2254533801	2229957480	2097568145	2087894999	98.91	99.54	0	0	0	0	0	0	78.58	84.45	33979153	23504835	33979153	23504835	80.81	81.0	33979153	24172412	33979153	22543797	311258422	13.81	0.52	0	6.53	0	0.37	0	0.21	0	0.00	0	5.36	0	29911311	0	76	0	75.36	0	1.44	0	0.00	0	1.19	0	0.00	0	268.75	0	0.49	0	165048	0	31802446	0	2078193	0	119254	0	67545	0	0	0	1704336	0	2741	0	0	0	25557	0	3782130	0	10210	0	3820638	0	87.52	0	27833118	0	166426	3923401	23.574447502193	31802446.0	29911311.0	165048.0	2078193.0	119254.0	67545.0	0.0	1704336.0	27833118.0	94.1	0.5	6.5	0.4	0.2	0.0	5.4	87.5	76	76	76.00	38	2416985896	24.2	25.3	25.1	25.4	0.0	34.2	14.3	bulk
466971	SRR1783806	SRP053038	SRS833778	SRX862820	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598863: Sertoli repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598863		GSM1598863	Sertoli repC	3118141892	15436346	2015-05-21 16:54:12	1871727505	3118141892	15436346	2	15436346	index:0,count:15436346,average:101,stdev:0|index:1,count:15436346,average:101,stdev:0	GSM1598863_r1	GEO			in_mesa	25855264	12.32	3.34	0.18	2542891185	2496949455	2392191275	2361915729	98.19	98.73	14859807	14476035	181.371	368.463	139	169290	65.32	69.46	16349484	9705880	16349484	9705880	67.02	66.97	16349484	9959338	16349484	9357870	720955597	28.35	0.17	0	5.75	0	0.21	0	0.22	0	0.00	0	3.31	0	14859807	0	202	0	200.94	0	2.12	0	0.01	0	2.00	0	0.01	0	219.65	0	0.20	0	26517	0	15436346	0	886983	0	32361	0	33701	0	0	0	510477	0	2477	0	0	0	32041	0	3673707	0	13002	0	3721227	0	90.52	0	13972824	0	173105	3531909	20.403275468646	15436346.0	14859807.0	26517.0	886983.0	32361.0	33701.0	0.0	510477.0	13972824.0	96.3	0.2	5.7	0.2	0.2	0.0	3.3	90.5	101	101	101.00	38	1559070946	25.9	23.6	22.8	27.7	0.0	37.3	29.0	bulk
466975	SRR1783807	SRP053038	SRS833778	SRX862820	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598863: Sertoli repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598863		GSM1598863	Sertoli repC	3117720116	15434258	2015-05-21 16:54:12	1876798734	3117720116	15434258	2	15434258	index:0,count:15434258,average:101,stdev:0|index:1,count:15434258,average:101,stdev:0	GSM1598863_r2	GEO			in_mesa	25855264	12.29	3.34	0.18	2542880209	2497024640	2392659396	2362379628	98.2	98.73	14855878	14473243	181.382	369.877	139	169216	65.34	69.47	16338214	9707003	16338214	9707003	67.05	67.0	16338214	9961060	16338214	9361280	721214873	28.36	0.17	0	5.73	0	0.21	0	0.22	0	0.00	0	3.32	0	14855878	0	202	0	200.95	0	2.12	0	0.01	0	2.00	0	0.01	0	306.98	0	0.20	0	25998	0	15434258	0	883710	0	32552	0	33346	0	0	0	512482	0	2578	0	0	0	31511	0	3668741	0	12842	0	3715672	0	90.53	0	13972168	0	172225	3530625	20.500072579475	15434258.0	14855878.0	25998.0	883710.0	32552.0	33346.0	0.0	512482.0	13972168.0	96.3	0.2	5.7	0.2	0.2	0.0	3.3	90.5	101	101	101.00	38	1558860058	25.9	23.6	22.8	27.7	0.0	37.3	29.1	bulk
466979	SRR1783808	SRP053038	SRS833778	SRX862820	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598863: Sertoli repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598863		GSM1598863	Sertoli repC	3076746234	15231417	2015-05-21 16:54:12	1835780129	3076746234	15231417	2	15231417	index:0,count:15231417,average:101,stdev:0|index:1,count:15231417,average:101,stdev:0	GSM1598863_r3	GEO			in_mesa	25855264	12.29	3.34	0.18	2519078791	2473260176	2370199449	2339859485	98.18	98.72	14713759	14334903	181.417	368.412	139	167396	65.3	69.43	16179985	9608201	16179985	9608201	67.01	66.95	16179985	9859345	16179985	9265000	714760056	28.37	0.17	0	5.75	0	0.21	0	0.22	0	0.00	0	2.97	0	14713759	0	202	0	201.00	0	2.11	0	0.01	0	1.99	0	0.01	0	293.23	0	0.20	0	26196	0	15231417	0	875614	0	31884	0	33413	0	0	0	452361	0	2611	0	0	0	31423	0	3635656	0	13065	0	3682755	0	90.85	0	13838145	0	172144	3490643	20.277459568733	15231417.0	14713759.0	26196.0	875614.0	31884.0	33413.0	0.0	452361.0	13838145.0	96.6	0.2	5.7	0.2	0.2	0.0	3.0	90.9	101	101	101.00	38	1538373117	25.9	23.6	22.8	27.7	0.0	37.3	29.4	bulk
466982	SRR1783809	SRP053038	SRS833778	SRX862820	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598863: Sertoli repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598863		GSM1598863	Sertoli repC	3057815400	15137700	2015-05-21 16:54:12	1814202601	3057815400	15137700	2	15137700	index:0,count:15137700,average:101,stdev:0|index:1,count:15137700,average:101,stdev:0	GSM1598863_r4	GEO			in_mesa	25855264	12.28	3.34	0.18	2503765589	2458491755	2355750098	2325788571	98.19	98.73	14623255	14247924	181.404	371.058	139	167167	65.32	69.45	16082398	9551487	16082398	9551487	67.02	66.98	16082398	9800689	16082398	9211266	710401961	28.37	0.17	0	5.75	0	0.21	0	0.22	0	0.00	0	2.96	0	14623255	0	202	0	201.01	0	2.10	0	0.01	0	1.98	0	0.01	0	122.19	0	0.20	0	25996	0	15137700	0	870465	0	32077	0	33542	0	0	0	448826	0	2577	0	0	0	31045	0	3612626	0	12904	0	3659152	0	90.85	0	13752790	0	171873	3468480	20.180482100155	15137700.0	14623255.0	25996.0	870465.0	32077.0	33542.0	0.0	448826.0	13752790.0	96.6	0.2	5.8	0.2	0.2	0.0	3.0	90.9	101	101	101.00	38	1528907700	25.9	23.6	22.8	27.7	0.0	37.4	29.6	bulk
467011	SRR1783810	SRP053038	SRS833777	SRX862821	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598864: Leydig repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598864		GSM1598864	Leydig repA	2716970094	13450347	2015-05-21 16:54:12	1653758467	2716970094	13450347	2	13450347	index:0,count:13450347,average:101,stdev:0|index:1,count:13450347,average:101,stdev:0	GSM1598864_r1	GEO			in_mesa	25855264	10.76	3.26	0.13	2127188532	2085229792	1986570994	1958298684	98.03	98.58	12505341	12179679	180.360	381.045	139	146453	64.87	69.51	13908324	8111634	13908324	8111634	66.42	66.6	13908324	8306513	13908324	7772189	590552403	27.76	0.22	0	6.21	0	0.22	0	0.22	0	0.00	0	6.59	0	12505341	0	202	0	200.67	0	2.18	0	0.01	0	2.40	0	0.02	0	156.20	0	0.25	0	29423	0	13450347	0	835101	0	29188	0	29015	0	0	0	886803	0	2426	0	0	0	27132	0	3141719	0	10899	0	3182176	0	86.77	0	11670240	0	167889	3009383	17.924837243655	13450347.0	12505341.0	29423.0	835101.0	29188.0	29015.0	0.0	886803.0	11670240.0	93.0	0.2	6.2	0.2	0.2	0.0	6.6	86.8	101	101	101.00	38	1358485047	25.4	24.0	23.5	27.1	0.0	37.2	28.7	bulk
467015	SRR1783811	SRP053038	SRS833777	SRX862821	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598864: Leydig repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598864		GSM1598864	Leydig repA	2706295606	13397503	2015-05-21 16:54:12	1651037438	2706295606	13397503	2	13397503	index:0,count:13397503,average:101,stdev:0|index:1,count:13397503,average:101,stdev:0	GSM1598864_r2	GEO			in_mesa	25855264	10.77	3.27	0.12	2119493100	2077922932	1979778792	1951758936	98.04	98.58	12456778	12130633	180.445	378.961	139	145451	64.87	69.5	13847486	8080880	13847486	8080880	66.41	66.59	13847486	8272816	13847486	7742141	588786744	27.78	0.22	0	6.19	0	0.22	0	0.22	0	0.00	0	6.59	0	12456778	0	202	0	200.68	0	2.17	0	0.01	0	2.41	0	0.02	0	241.16	0	0.25	0	29072	0	13397503	0	829400	0	29204	0	28835	0	0	0	882686	0	2269	0	0	0	27064	0	3134931	0	10627	0	3174891	0	86.79	0	11627378	0	168077	3000474	17.851782218864	13397503.0	12456778.0	29072.0	829400.0	29204.0	28835.0	0.0	882686.0	11627378.0	93.0	0.2	6.2	0.2	0.2	0.0	6.6	86.8	101	101	101.00	38	1353147803	25.4	24.0	23.5	27.1	0.0	37.2	28.8	bulk
467047	SRR1783819	SRP053038	SRS833781	SRX862823	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598866: Leydig repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598866		GSM1598866	Leydig repC	3027388140	14987070	2015-05-21 16:54:12	1831914999	3027388140	14987070	2	14987070	index:0,count:14987070,average:101,stdev:0|index:1,count:14987070,average:101,stdev:0	GSM1598866_r2	GEO			in_mesa	25855264	10.85	3.31	0.13	2457559999	2410517643	2305833901	2274237295	98.09	98.63	14282927	13920672	182.535	375.404	151	155507	64.25	68.51	15784368	9176413	15784368	9176413	65.76	65.75	15784368	9392838	15784368	8806741	712225856	28.98	0.17	0	5.93	0	0.22	0	0.23	0	0.00	0	4.25	0	14282927	0	202	0	200.81	0	2.19	0	0.01	0	2.21	0	0.02	0	233.56	0	0.22	0	26183	0	14987070	0	889341	0	32654	0	34543	0	0	0	636946	0	2686	0	0	0	30768	0	3514063	0	12296	0	3559813	0	89.37	0	13393586	0	174215	3401271	19.523410728123	14987070.0	14282927.0	26183.0	889341.0	32654.0	34543.0	0.0	636946.0	13393586.0	95.3	0.2	5.9	0.2	0.2	0.0	4.2	89.4	101	101	101.00	38	1513694070	25.7	23.8	23.0	27.4	0.0	37.2	28.9	bulk
467075	SRR1783820	SRP053038	SRS833781	SRX862823	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598866: Leydig repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598866		GSM1598866	Leydig repC	2952950736	14618568	2015-05-21 16:54:12	1772070402	2952950736	14618568	2	14618568	index:0,count:14618568,average:101,stdev:0|index:1,count:14618568,average:101,stdev:0	GSM1598866_r3	GEO			in_mesa	25855264	10.87	3.33	0.13	2405496738	2359482256	2257351183	2226359602	98.09	98.63	13978543	13625675	182.501	373.223	151	153004	64.22	68.47	15445273	8977199	15445273	8977199	65.73	65.72	15445273	9188343	15445273	8616524	698434601	29.03	0.18	0	5.94	0	0.22	0	0.23	0	0.00	0	3.93	0	13978543	0	202	0	200.88	0	2.20	0	0.01	0	2.19	0	0.02	0	234.94	0	0.22	0	26014	0	14618568	0	868248	0	31808	0	33797	0	0	0	574420	0	2559	0	0	0	29790	0	3430471	0	12241	0	3475061	0	89.68	0	13110295	0	173527	3318768	19.125369539034	14618568.0	13978543.0	26014.0	868248.0	31808.0	33797.0	0.0	574420.0	13110295.0	95.6	0.2	5.9	0.2	0.2	0.0	3.9	89.7	101	101	101.00	38	1476475368	25.8	23.8	23.0	27.4	0.0	37.3	29.3	bulk
467079	SRR1783821	SRP053038	SRS833781	SRX862823	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598866: Leydig repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598866		GSM1598866	Leydig repC	2943491480	14571740	2015-05-21 16:54:12	1756445730	2943491480	14571740	2	14571740	index:0,count:14571740,average:101,stdev:0|index:1,count:14571740,average:101,stdev:0	GSM1598866_r4	GEO			in_mesa	25855264	10.87	3.32	0.13	2398496299	2352328630	2250799139	2219593924	98.08	98.61	13937140	13585150	182.494	375.155	151	152225	64.23	68.48	15399770	8951893	15399770	8951893	65.74	65.73	15399770	9162744	15399770	8591775	695804748	29.01	0.18	0	5.94	0	0.22	0	0.23	0	0.00	0	3.91	0	13937140	0	202	0	200.88	0	2.19	0	0.01	0	2.20	0	0.02	0	214.99	0	0.22	0	25949	0	14571740	0	865559	0	31606	0	33781	0	0	0	569213	0	2527	0	0	0	30098	0	3421883	0	12359	0	3466867	0	89.71	0	13071581	0	173413	3312167	19.099877171838	14571740.0	13937140.0	25949.0	865559.0	31606.0	33781.0	0.0	569213.0	13071581.0	95.6	0.2	5.9	0.2	0.2	0.0	3.9	89.7	101	101	101.00	38	1471745740	25.8	23.8	23.0	27.4	0.0	37.3	29.4	bulk
467082	SRR1783822	SRP053038	SRS833780	SRX862824	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598867: Interstitial repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598867		GSM1598867	Interstitial repA	3232000000	16000000	2015-05-21 16:54:12	1964246536	3232000000	16000000	2	16000000	index:0,count:16000000,average:101,stdev:0|index:1,count:16000000,average:101,stdev:0	GSM1598867_r1	GEO			in_mesa	25855264	8.81	2.99	0.14	2559437634	2498711556	2367573665	2323240666	97.63	98.13	14971828	14584825	181.697	378.970	151	170077	62.71	67.85	16937892	9389073	16937892	9389073	64.65	64.57	16937892	9679320	16937892	8934799	728538362	28.46	0.25	0	7.09	0	0.27	0	0.23	0	0.00	0	5.92	0	14971828	0	202	0	200.39	0	2.27	0	0.01	0	2.90	0	0.02	0	186.41	0	0.30	0	39779	0	16000000	0	1134516	0	43218	0	37543	0	0	0	947411	0	2784	0	0	0	35097	0	3806998	0	13027	0	3857906	0	86.48	0	13837312	0	182772	3830613	20.958423609743	16000000.0	14971828.0	39779.0	1134516.0	43218.0	37543.0	0.0	947411.0	13837312.0	93.6	0.2	7.1	0.3	0.2	0.0	5.9	86.5	101	101	101.00	38	1616000000	25.1	24.3	24.0	26.6	0.0	37.1	28.6	bulk
467087	SRR1783823	SRP053038	SRS833780	SRX862824	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598867: Interstitial repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598867		GSM1598867	Interstitial repA	3232000000	16000000	2015-05-21 16:54:12	1969571309	3232000000	16000000	2	16000000	index:0,count:16000000,average:101,stdev:0|index:1,count:16000000,average:101,stdev:0	GSM1598867_r2	GEO			in_mesa	25855264	8.81	2.99	0.13	2559561173	2498690845	2367781249	2323385161	97.62	98.12	14968385	14582014	181.773	374.510	151	169907	62.73	67.87	16938224	9389331	16938224	9389331	64.67	64.58	16938224	9679772	16938224	8934713	727924726	28.44	0.25	0	7.09	0	0.27	0	0.24	0	0.00	0	5.94	0	14968385	0	202	0	200.40	0	2.28	0	0.01	0	2.90	0	0.02	0	184.62	0	0.30	0	39804	0	16000000	0	1133932	0	43313	0	37700	0	0	0	950602	0	2928	0	0	0	35401	0	3805771	0	12723	0	3856823	0	86.47	0	13834453	0	182961	3824443	20.903050376856	16000000.0	14968385.0	39804.0	1133932.0	43313.0	37700.0	0.0	950602.0	13834453.0	93.6	0.2	7.1	0.3	0.2	0.0	5.9	86.5	101	101	101.00	38	1616000000	25.2	24.3	24.0	26.6	0.0	37.1	28.6	bulk
467091	SRR1783824	SRP053038	SRS833780	SRX862824	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598867: Interstitial repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598867		GSM1598867	Interstitial repA	3244764986	16063193	2015-05-21 16:54:12	1964009005	3244764986	16063193	2	16063193	index:0,count:16063193,average:101,stdev:0|index:1,count:16063193,average:101,stdev:0	GSM1598867_r3	GEO			in_mesa	25855264	8.81	2.99	0.13	2581664130	2520374713	2388363467	2343571657	97.63	98.12	15096550	14708100	181.701	376.787	151	171459	62.7	67.83	17080957	9465310	17080957	9465310	64.64	64.56	17080957	9758324	17080957	9007911	735328039	28.48	0.25	0	7.12	0	0.27	0	0.23	0	0.00	0	5.52	0	15096550	0	202	0	200.46	0	2.28	0	0.01	0	2.88	0	0.02	0	259.32	0	0.30	0	40162	0	16063193	0	1142976	0	42882	0	37739	0	0	0	886022	0	2988	0	0	0	35633	0	3836199	0	12976	0	3887796	0	86.87	0	13953574	0	182998	3853581	21.058049814752	16063193.0	15096550.0	40162.0	1142976.0	42882.0	37739.0	0.0	886022.0	13953574.0	94.0	0.3	7.1	0.3	0.2	0.0	5.5	86.9	101	101	101.00	38	1622382493	25.2	24.3	24.0	26.6	0.0	37.1	29.0	bulk
467095	SRR1783825	SRP053038	SRS833780	SRX862824	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598867: Interstitial repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598867		GSM1598867	Interstitial repA	3224476308	15962754	2015-05-21 16:54:12	1940109206	3224476308	15962754	2	15962754	index:0,count:15962754,average:101,stdev:0|index:1,count:15962754,average:101,stdev:0	GSM1598867_r4	GEO			in_mesa	25855264	8.79	2.98	0.13	2566003356	2505016886	2374244936	2329625534	97.62	98.12	15003077	14616351	181.767	377.174	151	169836	62.71	67.84	16970303	9408665	16970303	9408665	64.63	64.55	16970303	9697210	16970303	8953275	730696984	28.48	0.25	0	7.10	0	0.27	0	0.24	0	0.00	0	5.51	0	15003077	0	202	0	200.46	0	2.26	0	0.01	0	2.87	0	0.02	0	280.32	0	0.29	0	40071	0	15962754	0	1133649	0	42854	0	38035	0	0	0	878788	0	2890	0	0	0	35500	0	3814979	0	12752	0	3866121	0	86.89	0	13869428	0	183217	3839379	20.955364403958	15962754.0	15003077.0	40071.0	1133649.0	42854.0	38035.0	0.0	878788.0	13869428.0	94.0	0.3	7.1	0.3	0.2	0.0	5.5	86.9	101	101	101.00	38	1612238154	25.2	24.3	24.0	26.6	0.0	37.2	29.1	bulk
467099	SRR1783826	SRP053038	SRS833783	SRX862825	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598868: Interstitial repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598868		GSM1598868	Interstitial repB	2889579498	14304849	2015-05-21 16:54:12	1762485717	2889579498	14304849	2	14304849	index:0,count:14304849,average:101,stdev:0|index:1,count:14304849,average:101,stdev:0	GSM1598868_r1	GEO			in_mesa	25855264	9.99	2.94	0.14	2169801533	2113567080	2027784656	1985622375	97.41	97.92	12891718	12544134	178.673	376.070	139	156260	64.75	69.35	14437942	8346896	14437942	8346896	66.5	66.33	14437942	8573602	14437942	7982917	591499573	27.26	0.27	0	5.99	0	0.27	0	0.23	0	0.00	0	9.38	0	12891718	0	202	0	200.41	0	2.41	0	0.02	0	2.99	0	0.02	0	156.53	0	0.29	0	39112	0	14304849	0	856472	0	38694	0	32224	0	0	0	1342213	0	2561	0	0	0	29477	0	3360797	0	11851	0	3404686	0	84.13	0	12035246	0	177925	3309391	18.599921315161	14304849.0	12891718.0	39112.0	856472.0	38694.0	32224.0	0.0	1342213.0	12035246.0	90.1	0.3	6.0	0.3	0.2	0.0	9.4	84.1	101	101	101.00	38	1444789749	24.3	25.0	24.7	26.0	0.0	37.0	28.1	bulk
467151	SRR1783833	SRP053038	SRS833782	SRX862826	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598869: Interstitial repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598869		GSM1598869	Interstitial repC	3079999848	15247524	2015-05-21 16:54:12	1825290679	3079999848	15247524	2	15247524	index:0,count:15247524,average:101,stdev:0|index:1,count:15247524,average:101,stdev:0	GSM1598869_r4	GEO			in_mesa	25855264	10.25	3.14	0.14	2495433477	2453284090	2321267380	2294602396	98.31	98.85	14690902	14306216	180.129	376.541	139	167668	64.39	69.26	16499086	9459821	16499086	9459821	66.71	66.46	16499086	9799826	16499086	9076795	706211255	28.30	0.19	0	6.77	0	0.29	0	0.26	0	0.00	0	3.10	0	14690902	0	202	0	200.92	0	2.25	0	0.01	0	1.95	0	0.01	0	250.64	0	0.20	0	29015	0	15247524	0	1032974	0	44816	0	38962	0	0	0	472844	0	2882	0	0	0	34014	0	3744502	0	13031	0	3794429	0	89.57	0	13657928	0	181633	3719814	20.479835712673	15247524.0	14690902.0	29015.0	1032974.0	44816.0	38962.0	0.0	472844.0	13657928.0	96.3	0.2	6.8	0.3	0.3	0.0	3.1	89.6	101	101	101.00	38	1539999924	25.9	23.7	22.8	27.5	0.0	37.4	29.4	bulk
933062	SRR1783798	SRP053038	SRS833776	SRX862818	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598861: Sertoli repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598861		GSM1598861	Sertoli repA	3138327550	15536275	2015-05-21 16:54:12	1911675606	3138327550	15536275	2	15536275	index:0,count:15536275,average:101,stdev:0|index:1,count:15536275,average:101,stdev:0	GSM1598861_r1	GEO			in_mesa	25855264	10.84	3.11	0.15	2443146392	2378848666	2271229688	2223799126	97.37	97.91	14390059	14018360	179.984	368.300	151	167935	64.43	69.38	16093473	9270823	16093473	9270823	65.63	66.07	16093473	9444330	16093473	8829208	653437028	26.75	0.30	0	6.61	0	0.21	0	0.19	0	0.00	0	6.98	0	14390059	0	202	0	200.26	0	2.13	0	0.01	0	3.08	0	0.03	0	159.80	0	0.31	0	46290	0	15536275	0	1027376	0	32542	0	29432	0	0	0	1084242	0	2492	0	0	0	31564	0	3568946	0	12076	0	3615078	0	86.01	0	13362683	0	171204	3418015	19.964574425831	15536275.0	14390059.0	46290.0	1027376.0	32542.0	29432.0	0.0	1084242.0	13362683.0	92.6	0.3	6.6	0.2	0.2	0.0	7.0	86.0	101	101	101.00	38	1569163775	25.0	24.2	24.3	26.5	0.0	37.0	28.4	bulk
933069	SRR1783799	SRP053038	SRS833776	SRX862818	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598861: Sertoli repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598861		GSM1598861	Sertoli repA	3127175736	15481068	2015-05-21 16:54:12	1910046415	3127175736	15481068	2	15481068	index:0,count:15481068,average:101,stdev:0|index:1,count:15481068,average:101,stdev:0	GSM1598861_r2	GEO			in_mesa	25855264	10.83	3.11	0.15	2435559328	2371372798	2264164768	2216807432	97.36	97.91	14339847	13970102	180.081	368.665	151	166240	64.42	69.38	16039831	9238426	16039831	9238426	65.63	66.07	16039831	9411607	16039831	8798327	651224691	26.74	0.29	0	6.61	0	0.22	0	0.19	0	0.00	0	6.97	0	14339847	0	202	0	200.27	0	2.12	0	0.01	0	3.08	0	0.03	0	195.55	0	0.31	0	45598	0	15481068	0	1023634	0	33387	0	29302	0	0	0	1078532	0	2550	0	0	0	31244	0	3556874	0	11888	0	3602556	0	86.02	0	13316213	0	171468	3414189	19.911522849745	15481068.0	14339847.0	45598.0	1023634.0	33387.0	29302.0	0.0	1078532.0	13316213.0	92.6	0.3	6.6	0.2	0.2	0.0	7.0	86.0	101	101	101.00	38	1563587868	25.0	24.2	24.3	26.6	0.0	37.0	28.5	bulk
933893	SRR1783800	SRP053038	SRS833776	SRX862818	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598861: Sertoli repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598861		GSM1598861	Sertoli repA	3076663212	15231006	2015-05-21 16:54:12	1860712071	3076663212	15231006	2	15231006	index:0,count:15231006,average:101,stdev:0|index:1,count:15231006,average:101,stdev:0	GSM1598861_r3	GEO			in_mesa	25855264	10.84	3.1	0.16	2408128952	2344415919	2239423579	2192342769	97.35	97.9	14177560	13812238	180.039	366.856	150	164455	64.41	69.34	15853310	9131437	15853310	9131437	65.61	66.03	15853310	9302587	15853310	8696506	644801938	26.78	0.30	0	6.62	0	0.21	0	0.19	0	0.00	0	6.52	0	14177560	0	202	0	200.32	0	2.13	0	0.01	0	3.06	0	0.03	0	197.24	0	0.31	0	45402	0	15231006	0	1007818	0	32087	0	28738	0	0	0	992621	0	2446	0	0	0	30784	0	3516035	0	12207	0	3561472	0	86.47	0	13169742	0	170516	3372709	19.779428323442	15231006.0	14177560.0	45402.0	1007818.0	32087.0	28738.0	0.0	992621.0	13169742.0	93.1	0.3	6.6	0.2	0.2	0.0	6.5	86.5	101	101	101.00	38	1538331606	25.0	24.2	24.3	26.5	0.0	37.1	28.9	bulk
933901	SRR1783801	SRP053038	SRS833776	SRX862818	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598861: Sertoli repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598861		GSM1598861	Sertoli repA	3058975284	15143442	2015-05-21 16:54:12	1839457729	3058975284	15143442	2	15143442	index:0,count:15143442,average:101,stdev:0|index:1,count:15143442,average:101,stdev:0	GSM1598861_r4	GEO			in_mesa	25855264	10.83	3.11	0.15	2394733135	2331437901	2226998645	2180261618	97.36	97.9	14097306	13735342	180.069	366.424	151	164023	64.41	69.34	15763366	9080136	15763366	9080136	65.61	66.04	15763366	9249333	15763366	8647835	641114729	26.77	0.30	0	6.62	0	0.21	0	0.19	0	0.00	0	6.51	0	14097306	0	202	0	200.33	0	2.13	0	0.01	0	3.06	0	0.03	0	194.70	0	0.30	0	45162	0	15143442	0	1002398	0	32076	0	28967	0	0	0	985093	0	2394	0	0	0	30956	0	3495495	0	11940	0	3540785	0	86.47	0	13094908	0	170438	3353504	19.675799997653	15143442.0	14097306.0	45162.0	1002398.0	32076.0	28967.0	0.0	985093.0	13094908.0	93.1	0.3	6.6	0.2	0.2	0.0	6.5	86.5	101	101	101.00	38	1529487642	25.0	24.2	24.3	26.5	0.0	37.1	29.0	bulk
933909	SRR1783802	SRP053038	SRS833775	SRX862819	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598862: Sertoli repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598862		GSM1598862	Sertoli repB	3020413686	14952543	2015-05-21 16:54:12	1817659054	3020413686	14952543	2	14952543	index:0,count:14952543,average:101,stdev:0|index:1,count:14952543,average:101,stdev:0	GSM1598862_r1	GEO			in_mesa	25855264	9.95	3.24	0.18	2415676034	2349361104	2278992972	2228874473	97.25	97.8	14209575	13850578	180.199	367.881	139	169883	62.6	66.41	15624732	8895094	15624732	8895094	63.47	63.5	15624732	9019453	15624732	8504617	728196315	30.14	0.27	0	5.46	0	0.21	0	0.22	0	0.00	0	4.54	0	14209575	0	202	0	200.45	0	2.18	0	0.01	0	2.80	0	0.02	0	171.43	0	0.28	0	39939	0	14952543	0	816202	0	30751	0	33245	0	0	0	678972	0	2417	0	0	0	28713	0	3413264	0	12973	0	3457367	0	89.57	0	13393373	0	170302	3271429	19.209574755434	14952543.0	14209575.0	39939.0	816202.0	30751.0	33245.0	0.0	678972.0	13393373.0	95.0	0.3	5.5	0.2	0.2	0.0	4.5	89.6	101	101	101.00	38	1510206843	25.7	23.9	23.6	26.8	0.0	37.2	28.7	bulk
933917	SRR1783803	SRP053038	SRS833775	SRX862819	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598862: Sertoli repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598862		GSM1598862	Sertoli repB	3010589416	14903908	2015-05-21 16:54:12	1816240079	3010589416	14903908	2	14903908	index:0,count:14903908,average:101,stdev:0|index:1,count:14903908,average:101,stdev:0	GSM1598862_r2	GEO			in_mesa	25855264	9.94	3.23	0.18	2408435092	2342063670	2271829859	2221624329	97.24	97.79	14162304	13805057	180.276	366.578	139	167806	62.58	66.41	15579142	8862991	15579142	8862991	63.47	63.5	15579142	8988328	15579142	8474594	726155504	30.15	0.26	0	5.47	0	0.21	0	0.22	0	0.00	0	4.55	0	14162304	0	202	0	200.47	0	2.18	0	0.01	0	2.83	0	0.02	0	291.60	0	0.28	0	39285	0	14903908	0	815694	0	30914	0	32809	0	0	0	677881	0	2405	0	0	0	28860	0	3403114	0	12960	0	3447339	0	89.55	0	13346610	0	170297	3256807	19.124276998420	14903908.0	14162304.0	39285.0	815694.0	30914.0	32809.0	0.0	677881.0	13346610.0	95.0	0.3	5.5	0.2	0.2	0.0	4.5	89.6	101	101	101.00	38	1505294708	25.7	23.9	23.6	26.8	0.0	37.2	28.8	bulk
933926	SRR1783804	SRP053038	SRS833775	SRX862819	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598862: Sertoli repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598862		GSM1598862	Sertoli repB	2948965478	14598839	2015-05-21 16:54:12	1761802716	2948965478	14598839	2	14598839	index:0,count:14598839,average:101,stdev:0|index:1,count:14598839,average:101,stdev:0	GSM1598862_r3	GEO			in_mesa	25855264	9.94	3.25	0.18	2369400479	2304395930	2235261882	2186149558	97.26	97.8	13929474	13578461	180.250	367.513	139	165520	62.58	66.4	15322389	8717180	15322389	8717180	63.46	63.49	15322389	8839077	15322389	8335176	714758255	30.17	0.27	0	5.49	0	0.21	0	0.22	0	0.00	0	4.16	0	13929474	0	202	0	200.53	0	2.17	0	0.01	0	2.81	0	0.02	0	255.13	0	0.28	0	38983	0	14598839	0	800872	0	30303	0	32417	0	0	0	606645	0	2459	0	0	0	27807	0	3342490	0	12829	0	3385585	0	89.93	0	13128602	0	169154	3202459	18.932209702401	14598839.0	13929474.0	38983.0	800872.0	30303.0	32417.0	0.0	606645.0	13128602.0	95.4	0.3	5.5	0.2	0.2	0.0	4.2	89.9	101	101	101.00	38	1474482739	25.7	23.9	23.6	26.8	0.0	37.2	29.2	bulk
933932	SRR1783805	SRP053038	SRS833775	SRX862819	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598862: Sertoli repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Sertoli cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598862		GSM1598862	Sertoli repB	2942700246	14567823	2015-05-21 16:54:12	1748300623	2942700246	14567823	2	14567823	index:0,count:14567823,average:101,stdev:0|index:1,count:14567823,average:101,stdev:0	GSM1598862_r4	GEO			in_mesa	25855264	9.93	3.23	0.18	2364685084	2299990236	2231138913	2182345312	97.26	97.81	13900501	13551026	180.292	366.077	139	164645	62.61	66.42	15288886	8703265	15288886	8703265	63.47	63.51	15288886	8823178	15288886	8321371	713091439	30.16	0.26	0	5.47	0	0.21	0	0.22	0	0.00	0	4.15	0	13900501	0	202	0	200.53	0	2.17	0	0.01	0	2.80	0	0.02	0	213.19	0	0.27	0	38530	0	14567823	0	797355	0	29951	0	32736	0	0	0	604635	0	2342	0	0	0	27948	0	3344127	0	12732	0	3387149	0	89.95	0	13103146	0	169801	3197712	18.832115240782	14567823.0	13900501.0	38530.0	797355.0	29951.0	32736.0	0.0	604635.0	13103146.0	95.4	0.3	5.5	0.2	0.2	0.0	4.2	89.9	101	101	101.00	38	1471350123	25.7	23.9	23.6	26.8	0.0	37.3	29.3	bulk
934036	SRR1783812	SRP053038	SRS833777	SRX862821	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598864: Leydig repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598864		GSM1598864	Leydig repA	2662475544	13180572	2015-05-21 16:54:12	1611333653	2662475544	13180572	2	13180572	index:0,count:13180572,average:101,stdev:0|index:1,count:13180572,average:101,stdev:0	GSM1598864_r3	GEO			in_mesa	25855264	10.78	3.26	0.13	2098370919	2056845227	1959800565	1931756372	98.02	98.57	12329288	12007811	180.448	377.618	139	143560	64.82	69.45	13709004	7992033	13709004	7992033	66.38	66.55	13709004	8184081	13709004	7658064	583613759	27.81	0.22	0	6.24	0	0.22	0	0.22	0	0.00	0	6.02	0	12329288	0	202	0	200.74	0	2.16	0	0.01	0	2.39	0	0.02	0	172.55	0	0.25	0	28978	0	13180572	0	822349	0	28997	0	28789	0	0	0	793498	0	2170	0	0	0	26631	0	3095932	0	10643	0	3135376	0	87.30	0	11506939	0	168008	2965018	17.648076282082	13180572.0	12329288.0	28978.0	822349.0	28997.0	28789.0	0.0	793498.0	11506939.0	93.5	0.2	6.2	0.2	0.2	0.0	6.0	87.3	101	101	101.00	38	1331237772	25.4	24.0	23.5	27.1	0.0	37.2	29.1	bulk
934044	SRR1783813	SRP053038	SRS833777	SRX862821	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598864: Leydig repA; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598864		GSM1598864	Leydig repA	2660217790	13169395	2015-05-21 16:54:12	1601843399	2660217790	13169395	2	13169395	index:0,count:13169395,average:101,stdev:0|index:1,count:13169395,average:101,stdev:0	GSM1598864_r4	GEO			in_mesa	25855264	10.77	3.26	0.12	2096603608	2055410994	1958500202	1930767756	98.04	98.58	12318457	11997387	180.417	378.738	139	142970	64.86	69.49	13694739	7990114	13694739	7990114	66.4	66.57	13694739	8178868	13694739	7655140	582574715	27.79	0.22	0	6.23	0	0.22	0	0.22	0	0.00	0	6.03	0	12318457	0	202	0	200.74	0	2.16	0	0.01	0	2.40	0	0.02	0	207.03	0	0.24	0	28711	0	13169395	0	819861	0	28826	0	28538	0	0	0	793574	0	2195	0	0	0	27055	0	3098608	0	10622	0	3138480	0	87.31	0	11498596	0	167843	2972078	17.707488545843	13169395.0	12318457.0	28711.0	819861.0	28826.0	28538.0	0.0	793574.0	11498596.0	93.5	0.2	6.2	0.2	0.2	0.0	6.0	87.3	101	101	101.00	38	1330108895	25.4	24.0	23.5	27.1	0.0	37.3	29.3	bulk
934052	SRR1783814	SRP053038	SRS833779	SRX862822	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598865: Leydig repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598865		GSM1598865	Leydig repB	3108535782	15388791	2015-05-21 16:54:12	1878033201	3108535782	15388791	2	15388791	index:0,count:15388791,average:101,stdev:0|index:1,count:15388791,average:101,stdev:0	GSM1598865_r1	GEO			in_mesa	25855264	10.02	3.17	0.14	2451089156	2379782475	2306899053	2253098745	97.09	97.67	14521480	14181694	178.235	358.260	139	175489	60.46	64.31	16058229	8779505	16058229	8779505	61.1	61.1	16058229	8872110	16058229	8340440	779681103	31.81	0.29	0	5.65	0	0.22	0	0.25	0	0.00	0	5.17	0	14521480	0	202	0	200.33	0	2.24	0	0.01	0	2.95	0	0.03	0	215.56	0	0.30	0	43963	0	15388791	0	870176	0	33471	0	37724	0	0	0	796116	0	2398	0	0	0	28404	0	3229302	0	12471	0	3272575	0	88.71	0	13651304	0	172358	3089331	17.923919980506	15388791.0	14521480.0	43963.0	870176.0	33471.0	37724.0	0.0	796116.0	13651304.0	94.4	0.3	5.7	0.2	0.2	0.0	5.2	88.7	101	101	101.00	38	1554267891	25.7	23.9	23.5	26.9	0.0	37.1	28.5	bulk
934060	SRR1783815	SRP053038	SRS833779	SRX862822	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598865: Leydig repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598865		GSM1598865	Leydig repB	3098220450	15337725	2015-05-21 16:54:12	1877012294	3098220450	15337725	2	15337725	index:0,count:15337725,average:101,stdev:0|index:1,count:15337725,average:101,stdev:0	GSM1598865_r2	GEO			in_mesa	25855264	10.02	3.18	0.14	2443257234	2372361449	2299605062	2246082886	97.1	97.67	14470380	14131270	178.298	358.841	139	173678	60.48	64.33	15997019	8751524	15997019	8751524	61.12	61.12	15997019	8844149	15997019	8314285	777038527	31.80	0.29	0	5.65	0	0.22	0	0.25	0	0.00	0	5.19	0	14470380	0	202	0	200.33	0	2.25	0	0.01	0	2.94	0	0.03	0	231.03	0	0.30	0	43749	0	15337725	0	866156	0	33002	0	37629	0	0	0	796714	0	2388	0	0	0	28093	0	3222939	0	12473	0	3265893	0	88.70	0	13604224	0	172178	3074956	17.859168999524	15337725.0	14470380.0	43749.0	866156.0	33002.0	37629.0	0.0	796714.0	13604224.0	94.3	0.3	5.6	0.2	0.2	0.0	5.2	88.7	101	101	101.00	38	1549110225	25.8	23.9	23.5	26.9	0.0	37.1	28.6	bulk
934068	SRR1783816	SRP053038	SRS833779	SRX862822	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598865: Leydig repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598865		GSM1598865	Leydig repB	3041584700	15057350	2015-05-21 16:54:12	1825111583	3041584700	15057350	2	15057350	index:0,count:15057350,average:101,stdev:0|index:1,count:15057350,average:101,stdev:0	GSM1598865_r3	GEO			in_mesa	25855264	10.01	3.17	0.14	2408938359	2338713790	2267603074	2214524480	97.08	97.66	14265652	13932970	178.319	356.541	139	172071	60.48	64.33	15774784	8628071	15774784	8628071	61.12	61.11	15774784	8718608	15774784	8196968	765726028	31.79	0.29	0	5.66	0	0.22	0	0.25	0	0.00	0	4.80	0	14265652	0	202	0	200.39	0	2.25	0	0.01	0	2.92	0	0.03	0	194.99	0	0.30	0	43279	0	15057350	0	852669	0	32542	0	36998	0	0	0	722158	0	2309	0	0	0	27476	0	3174926	0	12188	0	3216899	0	89.08	0	13412983	0	171890	3034782	17.655372622026	15057350.0	14265652.0	43279.0	852669.0	32542.0	36998.0	0.0	722158.0	13412983.0	94.7	0.3	5.7	0.2	0.2	0.0	4.8	89.1	101	101	101.00	38	1520792350	25.8	23.8	23.5	26.9	0.0	37.2	29.0	bulk
934076	SRR1783817	SRP053038	SRS833779	SRX862822	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598865: Leydig repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598865		GSM1598865	Leydig repB	3027809714	14989157	2015-05-21 16:54:12	1806750136	3027809714	14989157	2	14989157	index:0,count:14989157,average:101,stdev:0|index:1,count:14989157,average:101,stdev:0	GSM1598865_r4	GEO			in_mesa	25855264	10.01	3.17	0.14	2398163107	2327946390	2257590955	2204381082	97.07	97.64	14201518	13869154	178.284	355.918	139	171209	60.45	64.29	15702831	8584675	15702831	8584675	61.1	61.09	15702831	8676531	15702831	8157543	763213956	31.82	0.29	0	5.66	0	0.22	0	0.25	0	0.00	0	4.79	0	14201518	0	202	0	200.39	0	2.24	0	0.01	0	2.93	0	0.03	0	201.35	0	0.29	0	43157	0	14989157	0	848274	0	32411	0	37216	0	0	0	718012	0	2357	0	0	0	27575	0	3160871	0	12136	0	3202939	0	89.09	0	13353244	0	171904	3014317	17.534885750186	14989157.0	14201518.0	43157.0	848274.0	32411.0	37216.0	0.0	718012.0	13353244.0	94.7	0.3	5.7	0.2	0.2	0.0	4.8	89.1	101	101	101.00	38	1513904857	25.8	23.8	23.5	26.9	0.0	37.2	29.1	bulk
934084	SRR1783818	SRP053038	SRS833781	SRX862823	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598866: Leydig repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Leydig cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598866		GSM1598866	Leydig repC	3049356650	15095825	2015-05-21 16:54:12	1840124215	3049356650	15095825	2	15095825	index:0,count:15095825,average:101,stdev:0|index:1,count:15095825,average:101,stdev:0	GSM1598866_r1	GEO			in_mesa	25855264	10.88	3.32	0.13	2475039530	2427895432	2322442307	2290848203	98.1	98.64	14388992	14024687	182.432	374.579	151	157641	64.26	68.52	15899996	9246366	15899996	9246366	65.77	65.76	15899996	9463796	15899996	8873526	717470168	28.99	0.17	0	5.93	0	0.22	0	0.23	0	0.00	0	4.23	0	14388992	0	202	0	200.81	0	2.20	0	0.01	0	2.20	0	0.02	0	215.65	0	0.22	0	26164	0	15095825	0	894659	0	32695	0	35007	0	0	0	639131	0	2663	0	0	0	30393	0	3538755	0	12525	0	3584336	0	89.39	0	13494333	0	173943	3416656	19.642388598564	15095825.0	14388992.0	26164.0	894659.0	32695.0	35007.0	0.0	639131.0	13494333.0	95.3	0.2	5.9	0.2	0.2	0.0	4.2	89.4	101	101	101.00	38	1524678325	25.7	23.8	23.0	27.4	0.0	37.2	28.8	bulk
934204	SRR1783827	SRP053038	SRS833783	SRX862825	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598868: Interstitial repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598868		GSM1598868	Interstitial repB	2874173160	14228580	2015-05-21 16:54:12	1758285122	2874173160	14228580	2	14228580	index:0,count:14228580,average:101,stdev:0|index:1,count:14228580,average:101,stdev:0	GSM1598868_r2	GEO			in_mesa	25855264	10.01	2.94	0.14	2160256708	2104428047	2018907659	1977054917	97.42	97.93	12829873	12484486	178.761	375.196	139	154615	64.77	69.37	14367411	8309523	14367411	8309523	66.52	66.35	14367411	8535072	14367411	7947594	588680338	27.25	0.27	0	5.99	0	0.27	0	0.22	0	0.00	0	9.34	0	12829873	0	202	0	200.42	0	2.39	0	0.01	0	2.99	0	0.02	0	107.16	0	0.29	0	38782	0	14228580	0	851954	0	38427	0	31894	0	0	0	1328386	0	2569	0	0	0	29427	0	3342221	0	11938	0	3386155	0	84.18	0	11977919	0	177653	3292609	18.533934130018	14228580.0	12829873.0	38782.0	851954.0	38427.0	31894.0	0.0	1328386.0	11977919.0	90.2	0.3	6.0	0.3	0.2	0.0	9.3	84.2	101	101	101.00	38	1437086580	24.3	25.0	24.7	26.0	0.0	36.9	28.2	bulk
934212	SRR1783828	SRP053038	SRS833783	SRX862825	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598868: Interstitial repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598868		GSM1598868	Interstitial repB	2809688498	13909349	2015-05-21 16:54:12	1704322043	2809688498	13909349	2	13909349	index:0,count:13909349,average:101,stdev:0|index:1,count:13909349,average:101,stdev:0	GSM1598868_r3	GEO			in_mesa	25855264	9.98	2.94	0.14	2119052910	2064031620	1980315853	1939041725	97.4	97.92	12584662	12246336	178.686	377.443	139	152229	64.72	69.32	14095589	8144372	14095589	8144372	66.49	66.31	14095589	8367587	14095589	7790126	578328799	27.29	0.27	0	6.01	0	0.27	0	0.22	0	0.00	0	9.03	0	12584662	0	202	0	200.48	0	2.39	0	0.02	0	2.97	0	0.02	0	175.08	0	0.29	0	38038	0	13909349	0	836498	0	37449	0	30667	0	0	0	1256571	0	2410	0	0	0	29045	0	3275242	0	11597	0	3318294	0	84.46	0	11748164	0	176957	3232835	18.269042761801	13909349.0	12584662.0	38038.0	836498.0	37449.0	30667.0	0.0	1256571.0	11748164.0	90.5	0.3	6.0	0.3	0.2	0.0	9.0	84.5	101	101	101.00	38	1404844249	24.3	25.0	24.7	26.0	0.0	37.0	28.6	bulk
934220	SRR1783829	SRP053038	SRS833783	SRX862825	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598868: Interstitial repB; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598868		GSM1598868	Interstitial repB	2802649202	13874501	2015-05-21 16:54:12	1690349186	2802649202	13874501	2	13874501	index:0,count:13874501,average:101,stdev:0|index:1,count:13874501,average:101,stdev:0	GSM1598868_r4	GEO			in_mesa	25855264	9.98	2.93	0.14	2114642920	2059721663	1976596067	1935320543	97.4	97.91	12556646	12219193	178.759	373.529	139	151036	64.75	69.34	14060744	8130117	14060744	8130117	66.5	66.32	14060744	8349817	14060744	7775772	576748595	27.27	0.27	0	6.00	0	0.27	0	0.22	0	0.00	0	9.00	0	12556646	0	202	0	200.48	0	2.40	0	0.02	0	2.98	0	0.02	0	174.64	0	0.28	0	37787	0	13874501	0	832248	0	37740	0	31217	0	0	0	1248898	0	2464	0	0	0	28672	0	3273730	0	11963	0	3316829	0	84.50	0	11724398	0	176776	3229666	18.269821695253	13874501.0	12556646.0	37787.0	832248.0	37740.0	31217.0	0.0	1248898.0	11724398.0	90.5	0.3	6.0	0.3	0.2	0.0	9.0	84.5	101	101	101.00	38	1401324601	24.3	25.0	24.7	26.0	0.0	37.1	28.8	bulk
934277	SRR1783830	SRP053038	SRS833782	SRX862826	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598869: Interstitial repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598869		GSM1598869	Interstitial repC	3143031322	15559561	2015-05-21 16:54:12	1883869300	3143031322	15559561	2	15559561	index:0,count:15559561,average:101,stdev:0|index:1,count:15559561,average:101,stdev:0	GSM1598869_r1	GEO			in_mesa	25855264	10.3	3.15	0.14	2535037340	2492422355	2358170548	2331191378	98.32	98.86	14933556	14542005	180.036	377.687	139	170863	64.45	69.32	16768338	9624329	16768338	9624329	66.76	66.51	16768338	9969207	16768338	9234229	715801781	28.24	0.19	0	6.75	0	0.29	0	0.25	0	0.00	0	3.48	0	14933556	0	202	0	200.85	0	2.26	0	0.01	0	1.95	0	0.01	0	231.46	0	0.21	0	29612	0	15559561	0	1049653	0	45875	0	39403	0	0	0	540727	0	2938	0	0	0	34955	0	3804656	0	13317	0	3855866	0	89.23	0	13883903	0	182644	3782311	20.708651803508	15559561.0	14933556.0	29612.0	1049653.0	45875.0	39403.0	0.0	540727.0	13883903.0	96.0	0.2	6.7	0.3	0.3	0.0	3.5	89.2	101	101	101.00	38	1571515661	25.9	23.7	22.8	27.5	0.0	37.3	28.9	bulk
934285	SRR1783831	SRP053038	SRS833782	SRX862826	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598869: Interstitial repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598869		GSM1598869	Interstitial repC	3129879910	15494455	2015-05-21 16:54:12	1881033768	3129879910	15494455	2	15494455	index:0,count:15494455,average:101,stdev:0|index:1,count:15494455,average:101,stdev:0	GSM1598869_r2	GEO			in_mesa	25855264	10.26	3.15	0.14	2524803279	2482531522	2348674105	2321986626	98.33	98.86	14868468	14478630	180.136	376.943	139	170683	64.43	69.3	16696696	9579019	16696696	9579019	66.73	66.48	16696696	9922144	16696696	9189536	713714045	28.27	0.19	0	6.74	0	0.29	0	0.25	0	0.00	0	3.50	0	14868468	0	202	0	200.86	0	2.26	0	0.01	0	1.96	0	0.01	0	193.01	0	0.21	0	29472	0	15494455	0	1045097	0	45372	0	38800	0	0	0	541815	0	2840	0	0	0	34413	0	3787492	0	13231	0	3837976	0	89.21	0	13823371	0	182379	3771720	20.680670471929	15494455.0	14868468.0	29472.0	1045097.0	45372.0	38800.0	0.0	541815.0	13823371.0	96.0	0.2	6.7	0.3	0.3	0.0	3.5	89.2	101	101	101.00	38	1564939955	25.9	23.7	22.8	27.5	0.0	37.3	29.0	bulk
934292	SRR1783832	SRP053038	SRS833782	SRX862826	SRA236037	GEO		Purification and transcriptomic analysis of mouse fetal Leydig cells reveals candidate genes for disorders of sex development	To examine the transcriptome of early testicular somatic cells during gonadogenesis at 12.5dpc RNA sequencing (RNA-Seq) was performed on murine primary testicular cell lineages isolated from the Sf1-eGFP line by FACS. The three main somatic cell lineages of the testis were isolated: the Sertoli cells which direct male development; the fetal Leydig cells (FLCs) that produce steroid hormones and virilise the XY individual and a heterogenous population of interstitial cells, some of which give rise to the adult Leydig cells (ALCs). This dataset provides a platform for exploring the biology of FLCs and understanding the role of these cells in testicular development and masculinization of the embryo, and a basis for targeted studies designed to identify causes of idiopathic XY DSD. Overall design: RNA-Seq of 3 enriched cell populations from 12.5dpc mouse gonad (Sertoli cells, Leydig cells and Interstitial cells isolated by FACS-sorting) on an Illumina HiSeq 1500, in triplicate.		GSM1598869: Interstitial repC; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted (Micro RNeasy kit without carrier RNA, Qiagen) from CD31-treated FACS-sorted cells. Each sample represented approximately 10 sorting experiments conducted on different days with 4-10 litters of Sf1-eGFP embryos in each experiment. We prepared sample A, sample B and Sample A+B (a mix of samples A and B), with 100ng of total RNA in each sample. Libraries were prepared using TruSeq Stranded Total RNA Libraries  (Illumina protocol 15031048 Rev C, Sep 2012), with multiplexing, Ribosomal depletion,with all sample run over the 4 rapid lanes	Illumina HiSeq 1500	age;;12.5 dpc|source_name;;Enriched Interstitial cells|strain;;Sf1-eGFP|tissue;;gonad	GEO Accession;;GSM1598869		GSM1598869	Interstitial repC	3081962682	15257241	2015-05-21 16:54:12	1836704695	3081962682	15257241	2	15257241	index:0,count:15257241,average:101,stdev:0|index:1,count:15257241,average:101,stdev:0	GSM1598869_r3	GEO			in_mesa	25855264	10.25	3.14	0.15	2496558770	2454421031	2322253613	2295567578	98.31	98.85	14698833	14312934	180.139	376.699	139	167910	64.38	69.25	16507869	9463075	16507869	9463075	66.7	66.45	16507869	9804256	16507869	9079944	706793414	28.31	0.19	0	6.78	0	0.29	0	0.25	0	0.00	0	3.11	0	14698833	0	202	0	200.92	0	2.24	0	0.01	0	1.95	0	0.01	0	203.43	0	0.21	0	29409	0	15257241	0	1034035	0	44949	0	38305	0	0	0	475154	0	2822	0	0	0	33504	0	3746729	0	13261	0	3796316	0	89.56	0	13664798	0	181843	3730202	20.513310933058	15257241.0	14698833.0	29409.0	1034035.0	44949.0	38305.0	0.0	475154.0	13664798.0	96.3	0.2	6.8	0.3	0.3	0.0	3.1	89.6	101	101	101.00	38	1540981341	25.9	23.7	22.8	27.5	0.0	37.3	29.3	bulk
1909594	SRR1787235	SRP053189	SRS836616	SRX865245	SRA236340	GEO		RNA-seq analysis of neonatal mouse cochlear hair cells	This study examined transcripts that are enriched in neonatal mouse cochlear hair cells. Hair cells were purified by FACS sorting for GFP fluorescence from the cochleas of transgenic mice in which the endogenous Atoh1 gene was fused with GFP Overall design: Two replicates of GFP+ hair cells were compared with all other cochlear cell types that were GFP-		GSM1602228: Purified Atoh1-GFP+ cells from mouse cochlea_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted from FACS-purified cells using an RNeasy Plus Micro kit (Qiagen). RNA-seq libraries of FACS purified cells were generated as previously described: Lott SE, Villalta JE, Schroth GP, Luo S, Tonkin LA, Eisen MB (2011) Noncanonical compensation of zygotic X transcription in early Drosophila melanogaster development revealed through single-embryo RNA-seq. PLoS Biol 9:e1000590.	Illumina HiSeq 2000	background strain;;outbred (ICR)|genotype;;Atoh1-GFP Knock-in Mouse (Atoh1tm4.1Hzo)|source_name;;Cochlea GFP+ rep 1|tissue;;P0 Mouse cochlea	GEO Accession;;GSM1602228		GSM1602228	Purified Atoh1-GFP+ cells from mouse cochlea_1	20498923640	101479820	2015-03-05 17:37:14	13623798942	20498923640	101479820	2	101479820	index:0,count:101479820,average:101,stdev:0|index:1,count:101479820,average:101,stdev:0	GSM1602228_r1	GEO			in_mesa	25855195	2.61	3.17	0.14	13805623756	13779849239	12827715081	12857258550	99.81	100.23	95558040	90156103	165.129	553.645	128	1222439	82.1	88.48	107295993	78457445	107295993	78457445	84.68	84.68	107295993	80921068	107295993	75088889	1483398482	10.74	1.00	0	6.79	0	0.25	0	0.10	0	0.00	0	5.48	0	95558040	0	202	0	199.82	0	1.95	0	0.01	0	1.61	0	0.01	0	129.00	0	0.43	0	1018977	0	101479820	0	6885956	0	251636	0	105788	0	0	0	5564356	0	26950	0	0	0	247249	0	40199243	0	74580	0	40548022	0	87.38	0	88672084	0	295411	33277072	112.646692235563	101479820.0	95558040.0	1018977.0	6885956.0	251636.0	105788.0	0.0	5564356.0	88672084.0	94.2	1.0	6.8	0.2	0.1	0.0	5.5	87.4	101	101	101.00	37	10249461820	24.5	25.7	25.1	24.6	0.1	35.0	18.0	bulk
1909610	SRR1787236	SRP053189	SRS836615	SRX865246	SRA236340	GEO		RNA-seq analysis of neonatal mouse cochlear hair cells	This study examined transcripts that are enriched in neonatal mouse cochlear hair cells. Hair cells were purified by FACS sorting for GFP fluorescence from the cochleas of transgenic mice in which the endogenous Atoh1 gene was fused with GFP Overall design: Two replicates of GFP+ hair cells were compared with all other cochlear cell types that were GFP-		GSM1602229: Purified Atoh1-GFP+ cells from mouse cochlea_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted from FACS-purified cells using an RNeasy Plus Micro kit (Qiagen). RNA-seq libraries of FACS purified cells were generated as previously described: Lott SE, Villalta JE, Schroth GP, Luo S, Tonkin LA, Eisen MB (2011) Noncanonical compensation of zygotic X transcription in early Drosophila melanogaster development revealed through single-embryo RNA-seq. PLoS Biol 9:e1000590.	Illumina HiSeq 2000	background strain;;outbred (ICR)|genotype;;Atoh1-GFP Knock-in Mouse (Atoh1tm4.1Hzo)|source_name;;Cochlea GFP+ rep 2|tissue;;P0 Mouse cochlea	GEO Accession;;GSM1602229		GSM1602229	Purified Atoh1-GFP+ cells from mouse cochlea_2	37936648178	187805189	2015-03-05 17:37:14	26764489627	37936648178	187805189	2	187805189	index:0,count:187805189,average:101,stdev:0|index:1,count:187805189,average:101,stdev:0	GSM1602229_r1	GEO			in_mesa	25855195	2.44	3.3	0.13	24865235379	24948247880	22416041150	22589458769	100.33	100.77	175866366	166268704	162.086	566.885	124	2463539	84.25	93.62	206667410	148172578	206667410	148172578	89.04	89.26	206667410	156593307	206667410	141277142	1419076911	5.71	1.65	0	9.37	0	0.29	0	0.06	0	0.00	0	6.01	0	175866366	0	202	0	199.60	0	1.95	0	0.01	0	1.61	0	0.00	0	223.36	0	0.45	0	3102490	0	187805189	0	17594280	0	544778	0	112381	0	0	0	11281664	0	55765	0	0	0	443651	0	75622328	0	123690	0	76245434	0	84.27	0	158272086	0	310228	63163809	203.604474773392	187805189.0	175866366.0	3102490.0	17594280.0	544778.0	112381.0	0.0	11281664.0	158272086.0	93.6	1.7	9.4	0.3	0.1	0.0	6.0	84.3	101	101	101.00	37	18968324089	24.0	25.9	25.6	24.3	0.2	34.4	18.7	bulk
1909627	SRR1787237	SRP053189	SRS836617	SRX865247	SRA236340	GEO		RNA-seq analysis of neonatal mouse cochlear hair cells	This study examined transcripts that are enriched in neonatal mouse cochlear hair cells. Hair cells were purified by FACS sorting for GFP fluorescence from the cochleas of transgenic mice in which the endogenous Atoh1 gene was fused with GFP Overall design: Two replicates of GFP+ hair cells were compared with all other cochlear cell types that were GFP-		GSM1602230: Purified Atoh1-GFP- cells from mouse cochlea_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted from FACS-purified cells using an RNeasy Plus Micro kit (Qiagen). RNA-seq libraries of FACS purified cells were generated as previously described: Lott SE, Villalta JE, Schroth GP, Luo S, Tonkin LA, Eisen MB (2011) Noncanonical compensation of zygotic X transcription in early Drosophila melanogaster development revealed through single-embryo RNA-seq. PLoS Biol 9:e1000590.	Illumina HiSeq 2000	background strain;;outbred (ICR)|genotype;;Atoh1-GFP Knock-in Mouse (Atoh1tm4.1Hzo)|source_name;;Cochlea GFP- rep 1|tissue;;P0 Mouse cochlea	GEO Accession;;GSM1602230		GSM1602230	Purified Atoh1-GFP- cells from mouse cochlea_1	23177072970	114737985	2015-03-05 17:37:14	15837678652	23177072970	114737985	2	114737985	index:0,count:114737985,average:101,stdev:0|index:1,count:114737985,average:101,stdev:0	GSM1602230_r1	GEO			in_mesa	25855195	4.18	2.56	0.04	15782641235	15700579179	14594342489	14582096125	99.48	99.92	107954133	100934088	166.997	585.254	128	1290753	87.24	94.45	120678809	94183666	120678809	94183666	90.31	90.63	120678809	97496025	120678809	90371068	642244592	4.07	0.97	0	7.18	0	0.25	0	0.07	0	0.00	0	5.59	0	107954133	0	202	0	199.69	0	1.95	0	0.01	0	1.65	0	0.01	0	141.12	0	0.48	0	1107367	0	114737985	0	8234766	0	291763	0	79488	0	0	0	6412601	0	39136	0	0	0	321461	0	48990469	0	87247	0	49438313	0	86.91	0	99719367	0	295573	40251358	136.180767526127	114737985.0	107954133.0	1107367.0	8234766.0	291763.0	79488.0	0.0	6412601.0	99719367.0	94.1	1.0	7.2	0.3	0.1	0.0	5.6	86.9	101	101	101.00	37	11588536485	24.5	25.7	25.1	24.7	0.1	34.5	17.4	bulk
1909642	SRR1787238	SRP053189	SRS836614	SRX865248	SRA236340	GEO		RNA-seq analysis of neonatal mouse cochlear hair cells	This study examined transcripts that are enriched in neonatal mouse cochlear hair cells. Hair cells were purified by FACS sorting for GFP fluorescence from the cochleas of transgenic mice in which the endogenous Atoh1 gene was fused with GFP Overall design: Two replicates of GFP+ hair cells were compared with all other cochlear cell types that were GFP-		GSM1602231: Purified Atoh1-GFP- cells from mouse cochlea_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted from FACS-purified cells using an RNeasy Plus Micro kit (Qiagen). RNA-seq libraries of FACS purified cells were generated as previously described: Lott SE, Villalta JE, Schroth GP, Luo S, Tonkin LA, Eisen MB (2011) Noncanonical compensation of zygotic X transcription in early Drosophila melanogaster development revealed through single-embryo RNA-seq. PLoS Biol 9:e1000590.	Illumina HiSeq 2000	background strain;;outbred (ICR)|genotype;;Atoh1-GFP Knock-in Mouse (Atoh1tm4.1Hzo)|source_name;;Cochlea GFP- rep 2|tissue;;P0 Mouse cochlea	GEO Accession;;GSM1602231		GSM1602231	Purified Atoh1-GFP- cells from mouse cochlea_2	19979331362	98907581	2015-03-05 17:37:14	13306184980	19979331362	98907581	2	98907581	index:0,count:98907581,average:101,stdev:0|index:1,count:98907581,average:101,stdev:0	GSM1602231_r1	GEO			in_mesa	25855195	3.14	2.54	0.03	13025785928	12997204235	12075222843	12092915287	99.78	100.15	93785822	86671708	161.617	679.705	122	1224333	88.04	95.08	104962626	82570918	104962626	82570918	90.79	91.14	104962626	85151194	104962626	79155131	473814893	3.64	1.29	0	7.02	0	0.28	0	0.07	0	0.00	0	4.83	0	93785822	0	202	0	199.52	0	1.92	0	0.01	0	1.68	0	0.00	0	121.52	0	0.42	0	1279502	0	98907581	0	6938895	0	281547	0	67507	0	0	0	4772705	0	36001	0	0	0	304514	0	46491548	0	76227	0	46908290	0	87.81	0	86846927	0	276067	36330151	131.599035741324	98907581.0	93785822.0	1279502.0	6938895.0	281547.0	67507.0	0.0	4772705.0	86846927.0	94.8	1.3	7.0	0.3	0.1	0.0	4.8	87.8	101	101	101.00	37	9989665681	23.9	26.1	25.7	24.2	0.1	35.0	17.9	bulk
1639294	SRR1810037	SRP055125	SRS849135	SRX882877	SRA243151	GEO		Functional characterization of DNA methylation in the oligodendrocyte lineage [RNASeq_development]	Myelination in the CNS is modulated by interplay between transcription factors and recruitment of chromatin modifying enzymes. Using a network built from genome-wide DNA methylation and transcriptomic profiling of sorted oligodendrocyte lineage cells that integrates oligodendrocyte-specific ChIP-Seq data, we defined a crucial role of DNA methylation in coordinating the transition between progenitor cell cycle arrest and oligodendrocyte differentiation. We further identified DNA methyltransferase 1 (DNMT1) as key regulator of oligodendrocyte survival at this transition point, as we detected severe and extensive developmental hypomyelination only in Olig1cre/+;Dnmt1flox/flox but not in Olig1cre/+;Dnmt3aflox/flox mice  or in Cnpcre/+;Dnmt1flox/flox. This phenotype was characterized by decreased expression of genes regulating myelination and lipid metabolism – despite the hypomethylation observed at these genetic loci  – and upregulation of cell cycle and DNA-damage pathways. Therefore DNMT1 is a nodal point regulating proliferation, survival, and differentiation in the oligodendrocyte lineage, and is critical for cell number regulation in the developing brain. Overall design: mRNA profiles of FAC-sorted P2 Pdgfra::GFP and P18 Plp1-GFP purified cell samples from mouse brains were generated by RNA-sequencing, in triplicate, using Illumina HiSeq 2000.		GSM1613116: P2 brain oligodendrocyte progenitor cells_RNASeq_n1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNAs were obtained from FAC-sorted P2 oligodendrocyte progenitor cells or P18 oligodendrocytes, isolated from mouse brains. We used AllPrep DNA/RNA Mini Kit (Qiagen), with on-column DNase treatment during the RNA isolation, in accordance with the manufacturer’s protocol, to isolate DNA and RNA simultaneously from the same cell pellet. RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop, and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	cell type;;Primary FAC-sorted Pdgfra::GFP+ cells|development stage;;Post-natal day 2|source_name;;Brain|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1613116		GSM1613116	P2 brain oligodendrocyte progenitor cells_RNASeq_n1	7282074576	71392888	2016-04-14 16:08:06	4724891521	7282074576	71392888	2	71392888	index:0,count:71392888,average:51,stdev:0|index:1,count:71392888,average:51,stdev:0	GSM1613116_r1	GEO					4.55	3.66	0.04	6926036151	6897621373	6166153006	6202323658	99.59	100.59	68641621	59720800	204.250	1055.275	136	642441	85.08	95.52	81465882	58403605	81465882	58403605	91.2	92.08	81465882	62597856	81465882	56295485	241975120	3.49	0.85	0	10.51	0	0.33	0	0.08	0	0.00	0	3.44	0	68641621	0	102	0	100.96	0	1.92	0	0.00	0	1.23	0	0.01	0	353.04	0	0.27	0	609719	0	71392888	0	7501690	0	236512	0	58551	0	0	0	2456204	0	9115	0	0	0	58598	0	10040859	0	19684	0	10128256	0	85.64	0	61139931	0	157037	10457766	66.594280328840	71392888.0	68641621.0	609719.0	7501690.0	236512.0	58551.0	0.0	2456204.0	61139931.0	96.1	0.9	10.5	0.3	0.1	0.0	3.4	85.6	51	51	51.00	38	3641037288	24.8	25.1	25.2	24.8	0.0	36.7	18.1	bulk
1639309	SRR1810038	SRP055125	SRS849134	SRX882878	SRA243151	GEO		Functional characterization of DNA methylation in the oligodendrocyte lineage [RNASeq_development]	Myelination in the CNS is modulated by interplay between transcription factors and recruitment of chromatin modifying enzymes. Using a network built from genome-wide DNA methylation and transcriptomic profiling of sorted oligodendrocyte lineage cells that integrates oligodendrocyte-specific ChIP-Seq data, we defined a crucial role of DNA methylation in coordinating the transition between progenitor cell cycle arrest and oligodendrocyte differentiation. We further identified DNA methyltransferase 1 (DNMT1) as key regulator of oligodendrocyte survival at this transition point, as we detected severe and extensive developmental hypomyelination only in Olig1cre/+;Dnmt1flox/flox but not in Olig1cre/+;Dnmt3aflox/flox mice  or in Cnpcre/+;Dnmt1flox/flox. This phenotype was characterized by decreased expression of genes regulating myelination and lipid metabolism – despite the hypomethylation observed at these genetic loci  – and upregulation of cell cycle and DNA-damage pathways. Therefore DNMT1 is a nodal point regulating proliferation, survival, and differentiation in the oligodendrocyte lineage, and is critical for cell number regulation in the developing brain. Overall design: mRNA profiles of FAC-sorted P2 Pdgfra::GFP and P18 Plp1-GFP purified cell samples from mouse brains were generated by RNA-sequencing, in triplicate, using Illumina HiSeq 2000.		GSM1613117: P2 brain oligodendrocyte progenitor cells_RNASeq_n2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNAs were obtained from FAC-sorted P2 oligodendrocyte progenitor cells or P18 oligodendrocytes, isolated from mouse brains. We used AllPrep DNA/RNA Mini Kit (Qiagen), with on-column DNase treatment during the RNA isolation, in accordance with the manufacturer’s protocol, to isolate DNA and RNA simultaneously from the same cell pellet. RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop, and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	cell type;;Primary FAC-sorted Pdgfra::GFP+ cells|development stage;;Post-natal day 2|source_name;;Brain|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1613117		GSM1613117	P2 brain oligodendrocyte progenitor cells_RNASeq_n2	7472452170	73259335	2016-04-14 16:08:06	4845113130	7472452170	73259335	2	73259335	index:0,count:73259335,average:51,stdev:0|index:1,count:73259335,average:51,stdev:0	GSM1613117_r1	GEO					2.98	3.73	0.05	7108010133	7098230024	6447335095	6494485571	99.86	100.73	70473154	59700549	212.073	1296.120	136	605372	87.17	96.07	81983984	61432997	81983984	61432997	91.77	92.68	81983984	64676578	81983984	59265428	216558892	3.05	0.91	0	8.91	0	0.32	0	0.09	0	0.00	0	3.40	0	70473154	0	102	0	100.93	0	1.98	0	0.00	0	1.21	0	0.01	0	364.78	0	0.26	0	665318	0	73259335	0	6524571	0	233461	0	63894	0	0	0	2488826	0	9755	0	0	0	68519	0	11197476	0	21117	0	11296867	0	87.29	0	63948583	0	181599	11610044	63.932312402601	73259335.0	70473154.0	665318.0	6524571.0	233461.0	63894.0	0.0	2488826.0	63948583.0	96.2	0.9	8.9	0.3	0.1	0.0	3.4	87.3	51	51	51.00	38	3736226085	24.7	25.3	25.3	24.8	0.0	36.7	18.3	bulk
1639326	SRR1810039	SRP055125	SRS849133	SRX882879	SRA243151	GEO		Functional characterization of DNA methylation in the oligodendrocyte lineage [RNASeq_development]	Myelination in the CNS is modulated by interplay between transcription factors and recruitment of chromatin modifying enzymes. Using a network built from genome-wide DNA methylation and transcriptomic profiling of sorted oligodendrocyte lineage cells that integrates oligodendrocyte-specific ChIP-Seq data, we defined a crucial role of DNA methylation in coordinating the transition between progenitor cell cycle arrest and oligodendrocyte differentiation. We further identified DNA methyltransferase 1 (DNMT1) as key regulator of oligodendrocyte survival at this transition point, as we detected severe and extensive developmental hypomyelination only in Olig1cre/+;Dnmt1flox/flox but not in Olig1cre/+;Dnmt3aflox/flox mice  or in Cnpcre/+;Dnmt1flox/flox. This phenotype was characterized by decreased expression of genes regulating myelination and lipid metabolism – despite the hypomethylation observed at these genetic loci  – and upregulation of cell cycle and DNA-damage pathways. Therefore DNMT1 is a nodal point regulating proliferation, survival, and differentiation in the oligodendrocyte lineage, and is critical for cell number regulation in the developing brain. Overall design: mRNA profiles of FAC-sorted P2 Pdgfra::GFP and P18 Plp1-GFP purified cell samples from mouse brains were generated by RNA-sequencing, in triplicate, using Illumina HiSeq 2000.		GSM1613118: P2 brain oligodendrocyte progenitor cells_RNASeq_n3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNAs were obtained from FAC-sorted P2 oligodendrocyte progenitor cells or P18 oligodendrocytes, isolated from mouse brains. We used AllPrep DNA/RNA Mini Kit (Qiagen), with on-column DNase treatment during the RNA isolation, in accordance with the manufacturer’s protocol, to isolate DNA and RNA simultaneously from the same cell pellet. RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop, and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	cell type;;Primary FAC-sorted Pdgfra::GFP+ cells|development stage;;Post-natal day 2|source_name;;Brain|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1613118		GSM1613118	P2 brain oligodendrocyte progenitor cells_RNASeq_n3	7508823024	73615912	2016-04-14 16:08:06	4880756641	7508823024	73615912	2	73615912	index:0,count:73615912,average:51,stdev:0|index:1,count:73615912,average:51,stdev:0	GSM1613118_r1	GEO					3.75	3.76	0.04	7180387520	7161578703	6510427508	6549196421	99.74	100.6	71176169	60468673	209.186	1249.210	146	625400	85.93	94.73	82533318	61158462	82533318	61158462	90.63	91.39	82533318	64509864	82533318	59002751	314438985	4.38	0.73	0	8.99	0	0.30	0	0.09	0	0.00	0	2.92	0	71176169	0	102	0	100.94	0	1.96	0	0.00	0	1.21	0	0.01	0	473.25	0	0.27	0	538219	0	73615912	0	6614426	0	220641	0	67948	0	0	0	2151154	0	9382	0	0	0	68902	0	11374122	0	20659	0	11473065	0	87.70	0	64561743	0	179600	11794900	65.673162583519	73615912.0	71176169.0	538219.0	6614426.0	220641.0	67948.0	0.0	2151154.0	64561743.0	96.7	0.7	9.0	0.3	0.1	0.0	2.9	87.7	51	51	51.00	38	3754411512	25.0	25.0	25.0	25.0	0.0	36.7	18.4	bulk
1639437	SRR1810040	SRP055125	SRS849132	SRX882880	SRA243151	GEO		Functional characterization of DNA methylation in the oligodendrocyte lineage [RNASeq_development]	Myelination in the CNS is modulated by interplay between transcription factors and recruitment of chromatin modifying enzymes. Using a network built from genome-wide DNA methylation and transcriptomic profiling of sorted oligodendrocyte lineage cells that integrates oligodendrocyte-specific ChIP-Seq data, we defined a crucial role of DNA methylation in coordinating the transition between progenitor cell cycle arrest and oligodendrocyte differentiation. We further identified DNA methyltransferase 1 (DNMT1) as key regulator of oligodendrocyte survival at this transition point, as we detected severe and extensive developmental hypomyelination only in Olig1cre/+;Dnmt1flox/flox but not in Olig1cre/+;Dnmt3aflox/flox mice  or in Cnpcre/+;Dnmt1flox/flox. This phenotype was characterized by decreased expression of genes regulating myelination and lipid metabolism – despite the hypomethylation observed at these genetic loci  – and upregulation of cell cycle and DNA-damage pathways. Therefore DNMT1 is a nodal point regulating proliferation, survival, and differentiation in the oligodendrocyte lineage, and is critical for cell number regulation in the developing brain. Overall design: mRNA profiles of FAC-sorted P2 Pdgfra::GFP and P18 Plp1-GFP purified cell samples from mouse brains were generated by RNA-sequencing, in triplicate, using Illumina HiSeq 2000.		GSM1613119: P18 brain oligodendrocytes_RNASeq_n1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNAs were obtained from FAC-sorted P2 oligodendrocyte progenitor cells or P18 oligodendrocytes, isolated from mouse brains. We used AllPrep DNA/RNA Mini Kit (Qiagen), with on-column DNase treatment during the RNA isolation, in accordance with the manufacturer’s protocol, to isolate DNA and RNA simultaneously from the same cell pellet. RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop, and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	cell type;;Primary FAC-sorted Plp1-GFP+ cells|development stage;;Post-natal day 18|source_name;;Brain|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1613119		GSM1613119	P18 brain oligodendrocytes_RNASeq_n1	9326751276	91438738	2016-04-14 16:08:06	6040493701	9326751276	91438738	2	91438738	index:0,count:91438738,average:51,stdev:0|index:1,count:91438738,average:51,stdev:0	GSM1613119_r1	GEO					2.64	11.97	0.02	8806852135	8778774318	8320888320	8351973967	99.68	100.37	87363743	72903257	211.000	1291.696	136	742690	90.45	95.71	95158364	79017614	95158364	79017614	92.28	93.15	95158364	80621158	95158364	76903030	297650948	3.38	0.94	0	5.26	0	0.25	0	0.17	0	0.00	0	4.04	0	87363743	0	102	0	100.93	0	1.92	0	0.00	0	1.38	0	0.01	0	552.31	0	0.29	0	860704	0	91438738	0	4805794	0	227236	0	152625	0	0	0	3695134	0	8915	0	0	0	78402	0	14285809	0	24315	0	14397441	0	90.29	0	82557949	0	171284	14640655	85.475905513650	91438738.0	87363743.0	860704.0	4805794.0	227236.0	152625.0	0.0	3695134.0	82557949.0	95.5	0.9	5.3	0.2	0.2	0.0	4.0	90.3	51	51	51.00	38	4663375638	24.9	25.0	25.0	25.0	0.0	36.7	18.3	bulk
1639452	SRR1810041	SRP055125	SRS849144	SRX882881	SRA243151	GEO		Functional characterization of DNA methylation in the oligodendrocyte lineage [RNASeq_development]	Myelination in the CNS is modulated by interplay between transcription factors and recruitment of chromatin modifying enzymes. Using a network built from genome-wide DNA methylation and transcriptomic profiling of sorted oligodendrocyte lineage cells that integrates oligodendrocyte-specific ChIP-Seq data, we defined a crucial role of DNA methylation in coordinating the transition between progenitor cell cycle arrest and oligodendrocyte differentiation. We further identified DNA methyltransferase 1 (DNMT1) as key regulator of oligodendrocyte survival at this transition point, as we detected severe and extensive developmental hypomyelination only in Olig1cre/+;Dnmt1flox/flox but not in Olig1cre/+;Dnmt3aflox/flox mice  or in Cnpcre/+;Dnmt1flox/flox. This phenotype was characterized by decreased expression of genes regulating myelination and lipid metabolism – despite the hypomethylation observed at these genetic loci  – and upregulation of cell cycle and DNA-damage pathways. Therefore DNMT1 is a nodal point regulating proliferation, survival, and differentiation in the oligodendrocyte lineage, and is critical for cell number regulation in the developing brain. Overall design: mRNA profiles of FAC-sorted P2 Pdgfra::GFP and P18 Plp1-GFP purified cell samples from mouse brains were generated by RNA-sequencing, in triplicate, using Illumina HiSeq 2000.		GSM1613120: P18 brain oligodendrocytes_RNASeq_n2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNAs were obtained from FAC-sorted P2 oligodendrocyte progenitor cells or P18 oligodendrocytes, isolated from mouse brains. We used AllPrep DNA/RNA Mini Kit (Qiagen), with on-column DNase treatment during the RNA isolation, in accordance with the manufacturer’s protocol, to isolate DNA and RNA simultaneously from the same cell pellet. RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop, and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	cell type;;Primary FAC-sorted Plp1-GFP+ cells|development stage;;Post-natal day 18|source_name;;Brain|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1613120		GSM1613120	P18 brain oligodendrocytes_RNASeq_n2	7276211106	71335403	2016-04-14 16:08:06	4710155288	7276211106	71335403	2	71335403	index:0,count:71335403,average:51,stdev:0|index:1,count:71335403,average:51,stdev:0	GSM1613120_r1	GEO					9.56	6.03	0.01	6823663787	6713026185	5889251066	5871658017	98.38	99.7	67689975	58212573	204.964	1017.705	136	619371	82.97	96.06	81281892	56162035	81281892	56162035	91.96	93.3	81281892	62249676	81281892	54544545	177722303	2.60	0.98	0	12.93	0	0.22	0	0.13	0	0.00	0	4.76	0	67689975	0	102	0	100.84	0	1.83	0	0.00	0	1.62	0	0.01	0	393.27	0	0.34	0	697344	0	71335403	0	9225737	0	158543	0	91361	0	0	0	3395524	0	7586	0	0	0	44255	0	9836978	0	17689	0	9906508	0	81.96	0	58464238	0	120076	10242299	85.298469302775	71335403.0	67689975.0	697344.0	9225737.0	158543.0	91361.0	0.0	3395524.0	58464238.0	94.9	1.0	12.9	0.2	0.1	0.0	4.8	82.0	51	51	51.00	38	3638105553	25.0	24.8	25.0	25.2	0.0	36.8	18.3	bulk
1639468	SRR1810042	SRP055125	SRS849145	SRX882882	SRA243151	GEO		Functional characterization of DNA methylation in the oligodendrocyte lineage [RNASeq_development]	Myelination in the CNS is modulated by interplay between transcription factors and recruitment of chromatin modifying enzymes. Using a network built from genome-wide DNA methylation and transcriptomic profiling of sorted oligodendrocyte lineage cells that integrates oligodendrocyte-specific ChIP-Seq data, we defined a crucial role of DNA methylation in coordinating the transition between progenitor cell cycle arrest and oligodendrocyte differentiation. We further identified DNA methyltransferase 1 (DNMT1) as key regulator of oligodendrocyte survival at this transition point, as we detected severe and extensive developmental hypomyelination only in Olig1cre/+;Dnmt1flox/flox but not in Olig1cre/+;Dnmt3aflox/flox mice  or in Cnpcre/+;Dnmt1flox/flox. This phenotype was characterized by decreased expression of genes regulating myelination and lipid metabolism – despite the hypomethylation observed at these genetic loci  – and upregulation of cell cycle and DNA-damage pathways. Therefore DNMT1 is a nodal point regulating proliferation, survival, and differentiation in the oligodendrocyte lineage, and is critical for cell number regulation in the developing brain. Overall design: mRNA profiles of FAC-sorted P2 Pdgfra::GFP and P18 Plp1-GFP purified cell samples from mouse brains were generated by RNA-sequencing, in triplicate, using Illumina HiSeq 2000.		GSM1613121: P18 brain oligodendrocytes_RNASeq_n3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNAs were obtained from FAC-sorted P2 oligodendrocyte progenitor cells or P18 oligodendrocytes, isolated from mouse brains. We used AllPrep DNA/RNA Mini Kit (Qiagen), with on-column DNase treatment during the RNA isolation, in accordance with the manufacturer’s protocol, to isolate DNA and RNA simultaneously from the same cell pellet. RNA purity was assessed by measuring the A260/A280 ratio using a NanoDrop, and RNA quality checked using an Agilent 2100 Bioanalyzer (Agilent Technologies). RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2000	cell type;;Primary FAC-sorted Plp1-GFP+ cells|development stage;;Post-natal day 18|source_name;;Brain|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM1613121		GSM1613121	P18 brain oligodendrocytes_RNASeq_n3	8128395504	79690152	2016-04-14 16:08:06	5280354308	8128395504	79690152	2	79690152	index:0,count:79690152,average:51,stdev:0|index:1,count:79690152,average:51,stdev:0	GSM1613121_r1	GEO					9.34	6.76	0.01	7641352544	7569640616	6695860806	6712149476	99.06	100.24	75788309	63963094	211.558	1149.072	145	652501	84.87	96.79	89249239	64322413	89249239	64322413	93.0	94.05	89249239	70486463	89249239	62502498	166569161	2.18	0.92	0	11.71	0	0.27	0	0.13	0	0.00	0	4.50	0	75788309	0	102	0	100.85	0	1.93	0	0.00	0	1.54	0	0.01	0	387.16	0	0.33	0	733940	0	79690152	0	9331196	0	213386	0	105634	0	0	0	3582823	0	8291	0	0	0	55817	0	11762024	0	19841	0	11845973	0	83.39	0	66457113	0	133380	12199448	91.463847653321	79690152.0	75788309.0	733940.0	9331196.0	213386.0	105634.0	0.0	3582823.0	66457113.0	95.1	0.9	11.7	0.3	0.1	0.0	4.5	83.4	51	51	51.00	38	4064197752	25.0	24.9	25.1	25.1	0.0	36.7	18.2	bulk
1399167	SRR1811597	SRP055201	SRS851170	SRX884159	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614845: 24h [347]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;24 hrs	GEO Accession;;GSM1614845		GSM1614845	24h [347]	5492145096	34760412	2016-09-18 20:49:05	3895751526	5492145096	34760412	2	34760412	index:0,count:34760412,average:79,stdev:0|index:1,count:34760412,average:79,stdev:0	GSM1614845_r1	GEO			in_mesa	27720483	4.27	3.54	0.04	4186336197	4099284442	3916851836	3861427668	97.92	98.58	31745180	30198825	152.904	499.184	115	417614	82.8	88.57	35003291	26286223	35003291	26286223	85.17	85.6	35003291	27036206	35003291	25404737	375407114	8.97	0.79	0	5.95	0	0.28	0	0.20	0	0.00	0	8.19	0	31745180	0	158	0	156.30	0	1.54	0	0.00	0	1.21	0	0.01	0	199.90	0	0.74	0	276055	0	34760412	0	2068304	0	98523	0	69435	0	0	0	2847274	0	6681	0	0	0	65187	0	9130954	0	16735	0	9219557	0	85.38	0	29676876	0	216465	8512404	39.324620608412	34760412.0	31745180.0	276055.0	2068304.0	98523.0	69435.0	0.0	2847274.0	29676876.0	91.3	0.8	6.0	0.3	0.2	0.0	8.2	85.4	79	79	79.00	38	2746072548	26.8	23.1	22.9	27.0	0.2	30.6	11.6	bulk
1399183	SRR1811598	SRP055201	SRS851168	SRX884160	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614846: 36h [348]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;36 hrs	GEO Accession;;GSM1614846		GSM1614846	36h [348]	3926217366	24849477	2016-09-18 20:49:05	2821188933	3926217366	24849477	2	24849477	index:0,count:24849477,average:79,stdev:0|index:1,count:24849477,average:79,stdev:0	GSM1614846_r1	GEO			in_mesa	27720483	4.7	3.43	0.04	3152147706	3106396384	2940098879	2914744275	98.55	99.14	23172643	21580339	172.352	614.475	115	243926	83.09	89.18	25643557	19255155	25643557	19255155	85.96	86.24	25643557	19918943	25643557	18621522	283576984	9.00	0.92	0	6.36	0	0.29	0	0.18	0	0.00	0	6.28	0	23172643	0	158	0	156.37	0	1.46	0	0.00	0	1.19	0	0.01	0	229.97	0	0.68	0	227975	0	24849477	0	1580191	0	71711	0	44311	0	0	0	1560812	0	4797	0	0	0	46501	0	6792449	0	12250	0	6855997	0	86.89	0	21592452	0	193508	6454270	33.354021539161	24849477.0	23172643.0	227975.0	1580191.0	71711.0	44311.0	0.0	1560812.0	21592452.0	93.3	0.9	6.4	0.3	0.2	0.0	6.3	86.9	79	79	79.00	38	1963108683	26.3	23.7	23.5	26.3	0.2	31.7	12.6	bulk
1400847	SRR1811600	SRP055201	SRS851166	SRX884162	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614848: 36h [350]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;36 hrs	GEO Accession;;GSM1614848		GSM1614848	36h [350]	4729573738	29934011	2016-09-18 20:49:05	3373915292	4729573738	29934011	2	29934011	index:0,count:29934011,average:79,stdev:0|index:1,count:29934011,average:79,stdev:0	GSM1614848_r1	GEO			in_mesa	27720483	3.39	3.31	0.05	3635044735	3587749775	3414513445	3388948690	98.7	99.25	27075767	25054604	171.986	688.291	116	276827	84.01	89.54	29796303	22745390	29796303	22745390	85.92	86.31	29796303	23264561	29796303	21925972	308321267	8.48	1.39	0	5.59	0	0.32	0	0.16	0	0.00	0	9.07	0	27075767	0	158	0	156.17	0	1.58	0	0.00	0	1.30	0	0.01	0	226.87	0	0.74	0	414984	0	29934011	0	1673374	0	94772	0	49329	0	0	0	2714143	0	5537	0	0	0	56590	0	8308451	0	15187	0	8385765	0	84.86	0	25402393	0	190753	7806640	40.925385183981	29934011.0	27075767.0	414984.0	1673374.0	94772.0	49329.0	0.0	2714143.0	25402393.0	90.5	1.4	5.6	0.3	0.2	0.0	9.1	84.9	79	79	79.00	38	2364786869	25.6	24.4	24.2	25.6	0.2	30.6	11.6	bulk
1400863	SRR1811601	SRP055201	SRS851165	SRX884163	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614849: Peripheral lesion [74]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614849		GSM1614849	Peripheral lesion [74]	7622633400	38113167	2016-09-18 20:49:05	5043477437	7622633400	38113167	2	38113167	index:0,count:38113167,average:100,stdev:0|index:1,count:38113167,average:100,stdev:0	GSM1614849_r1	GEO			in_mesa	27720483	3.15	3.29	0.02	5912526156	5884560520	5580099613	5579660402	99.53	99.99	35722735	32754656	200.112	774.503	145	301342	88.11	93.44	38853744	31474642	38853744	31474642	89.74	90.09	38853744	32056484	38853744	30348075	315071197	5.33	0.91	0	5.35	0	0.26	0	0.08	0	0.00	0	5.93	0	35722735	0	200	0	196.31	0	1.56	0	0.00	0	1.29	0	0.01	0	191.63	0	0.78	0	345685	0	38113167	0	2038159	0	97708	0	31622	0	0	0	2261102	0	11440	0	0	0	111951	0	15469934	0	23957	0	15617282	0	88.38	0	33684576	0	235192	14334784	60.949283989251	38113167.0	35722735.0	345685.0	2038159.0	97708.0	31622.0	0.0	2261102.0	33684576.0	93.7	0.9	5.3	0.3	0.1	0.0	5.9	88.4	100	100	100.00	38	3811316700	25.1	24.8	24.8	25.0	0.3	30.7	11.5	bulk
1400879	SRR1811602	SRP055201	SRS851164	SRX884164	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614850: Peripheral lesion [75]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614850		GSM1614850	Peripheral lesion [75]	7707899200	38539496	2016-09-18 20:49:05	5088634919	7707899200	38539496	2	38539496	index:0,count:38539496,average:100,stdev:0|index:1,count:38539496,average:100,stdev:0	GSM1614850_r1	GEO			in_mesa	27720483	2.94	3.33	0.02	5900902117	5863343400	5586511388	5576935532	99.36	99.83	35497691	32605297	200.513	779.008	155	272076	87.98	93.01	38452917	31231820	38452917	31231820	89.43	89.79	38452917	31747258	38452917	30147540	334555039	5.67	1.59	0	4.98	0	0.24	0	0.09	0	0.00	0	7.56	0	35497691	0	200	0	196.09	0	1.55	0	0.00	0	1.29	0	0.01	0	187.74	0	0.78	0	611967	0	38539496	0	1920355	0	93420	0	33577	0	0	0	2914808	0	11695	0	0	0	110310	0	15146639	0	26483	0	15295127	0	87.12	0	33577336	0	236599	14074789	59.487947962586	38539496.0	35497691.0	611967.0	1920355.0	93420.0	33577.0	0.0	2914808.0	33577336.0	92.1	1.6	5.0	0.2	0.1	0.0	7.6	87.1	100	100	100.00	38	3853949600	25.3	24.7	24.7	25.1	0.3	30.6	11.4	bulk
1400895	SRR1811603	SRP055201	SRS851163	SRX884165	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614851: Peripheral lesion [124]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614851		GSM1614851	Peripheral lesion [124]	9847717200	49238586	2016-09-18 20:49:05	6488089468	9847717200	49238586	2	49238586	index:0,count:49238586,average:100,stdev:0|index:1,count:49238586,average:100,stdev:0	GSM1614851_r1	GEO			in_mesa	27720483	2.71	3.31	0.02	6899176450	6865807184	6518081222	6517051253	99.52	99.98	44763676	41381168	180.280	734.356	136	408578	88.27	93.54	48786986	39511275	48786986	39511275	89.7	90.11	48786986	40150946	48786986	38060575	361911767	5.25	1.31	0	5.13	0	0.27	0	0.09	0	0.00	0	8.73	0	44763676	0	200	0	195.84	0	1.45	0	0.00	0	1.24	0	0.01	0	189.99	0	0.77	0	643739	0	49238586	0	2523675	0	134419	0	42122	0	0	0	4298369	0	14257	0	0	0	142915	0	19791019	0	32295	0	19980486	0	85.79	0	42240001	0	231655	17340317	74.854058837495	49238586.0	44763676.0	643739.0	2523675.0	134419.0	42122.0	0.0	4298369.0	42240001.0	90.9	1.3	5.1	0.3	0.1	0.0	8.7	85.8	100	100	100.00	38	4923858600	25.1	25.0	24.8	24.8	0.3	30.4	11.2	bulk
1400943	SRR1811606	SRP055201	SRS851169	SRX884168	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614854: Sham operated [123]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614854		GSM1614854	Sham operated [123]	10222090200	51110451	2016-09-18 20:49:05	6751215777	10222090200	51110451	2	51110451	index:0,count:51110451,average:100,stdev:0|index:1,count:51110451,average:100,stdev:0	GSM1614854_r1	GEO			in_mesa	27720483	3.86	3.4	0.02	7512155947	7476690532	7077988640	7078784252	99.53	100.01	47100604	43458899	187.478	765.019	146	389964	88.71	94.24	51291292	41780608	51291292	41780608	90.53	90.89	51291292	42638661	51291292	40295396	335490267	4.47	1.32	0	5.42	0	0.26	0	0.09	0	0.00	0	7.50	0	47100604	0	200	0	195.93	0	1.46	0	0.00	0	1.23	0	0.01	0	188.33	0	0.76	0	674841	0	51110451	0	2767742	0	131036	0	44487	0	0	0	3834324	0	16261	0	0	0	149087	0	20545794	0	35612	0	20746754	0	86.74	0	44332862	0	242362	18492847	76.302584563587	51110451.0	47100604.0	674841.0	2767742.0	131036.0	44487.0	0.0	3834324.0	44332862.0	92.2	1.3	5.4	0.3	0.1	0.0	7.5	86.7	100	100	100.00	38	5111045100	25.4	24.6	24.6	25.2	0.3	30.7	11.4	bulk
2797873	SRR1811589	SRP055201	SRS851178	SRX884151	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614837: 06h [339]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;6 hrs	GEO Accession;;GSM1614837		GSM1614837	06h [339]	8048056548	41061513	2016-09-18 20:49:05	5039823527	8048056548	41061513	2	41061513	index:0,count:41061513,average:98,stdev:0|index:1,count:41061513,average:98,stdev:0	GSM1614837_r1	GEO			in_mesa	27720483	4.11	3.42	0.02	6218305382	6090353331	5857078241	5770467373	97.94	98.52	39817660	36917528	183.633	675.176	135	379649	86.01	91.41	43407217	34247183	43407217	34247183	87.74	88.23	43407217	34935324	43407217	33055501	373357083	6.00	1.03	0	5.73	0	0.27	0	0.13	0	0.00	0	2.63	0	39817660	0	196	0	194.25	0	1.62	0	0.01	0	1.25	0	0.01	0	282.10	0	0.26	0	422986	0	41061513	0	2353174	0	110084	0	55402	0	0	0	1078367	0	14317	0	0	0	127060	0	17019255	0	31468	0	17192100	0	91.24	0	37464486	0	233329	14648407	62.780053058128	41061513.0	39817660.0	422986.0	2353174.0	110084.0	55402.0	0.0	1078367.0	37464486.0	97.0	1.0	5.7	0.3	0.1	0.0	2.6	91.2	98	98	98.00	38	4024028274	26.5	23.5	23.2	26.7	0.0	36.0	18.0	bulk
2798096	SRR1811590	SRP055201	SRS851177	SRX884152	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614838: 06h [340]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;6 hrs	GEO Accession;;GSM1614838		GSM1614838	06h [340]	8289319110	52464045	2016-09-18 20:49:05	5888163701	8289319110	52464045	2	52464045	index:0,count:52464045,average:79,stdev:0|index:1,count:52464045,average:79,stdev:0	GSM1614838_r1	GEO			in_mesa	27720483	3.71	3.32	0.03	6405867861	6267243016	6018326912	5924430711	97.84	98.44	47762539	44562007	164.999	655.690	115	540502	85.44	91.02	52362497	40806868	52362497	40806868	87.52	88.04	52362497	41801518	52362497	39472217	402785550	6.29	0.98	0	5.58	0	0.29	0	0.14	0	0.00	0	8.53	0	47762539	0	158	0	156.22	0	1.57	0	0.00	0	1.21	0	0.01	0	261.23	0	0.76	0	514458	0	52464045	0	2929191	0	150597	0	74649	0	0	0	4476260	0	11585	0	0	0	102978	0	14588625	0	27950	0	14731138	0	85.46	0	44833348	0	237562	13704991	57.690165093744	52464045.0	47762539.0	514458.0	2929191.0	150597.0	74649.0	0.0	4476260.0	44833348.0	91.0	1.0	5.6	0.3	0.1	0.0	8.5	85.5	79	79	79.00	38	4144659555	26.3	23.7	23.5	26.3	0.2	30.5	11.5	bulk
2798128	SRR1811591	SRP055201	SRS851176	SRX884153	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614839: 06h [341]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;6 hrs	GEO Accession;;GSM1614839		GSM1614839	06h [341]	1267792000	8024000	2016-09-18 20:49:05	914685685	1267792000	8024000	2	8024000	index:0,count:8024000,average:79,stdev:0|index:1,count:8024000,average:79,stdev:0	GSM1614839_r1	GEO			in_mesa	27720483	4.42	3.6	0.03	973320440	949392015	909110271	893049478	97.54	98.23	7498402	7133535	148.665	525.210	116	95826	85.17	91.25	8268743	6386086	8268743	6386086	87.86	88.43	8268743	6588303	8268743	6188939	58412697	6.00	1.10	0	6.23	0	0.28	0	0.16	0	0.00	0	6.11	0	7498402	0	158	0	156.33	0	1.47	0	0.00	0	1.18	0	0.01	0	209.32	0	0.68	0	88645	0	8024000	0	499969	0	22426	0	12580	0	0	0	490592	0	1938	0	0	0	15530	0	2186508	0	4553	0	2208529	0	87.22	0	6998433	0	147503	2008587	13.617262021789	8024000.0	7498402.0	88645.0	499969.0	22426.0	12580.0	0.0	490592.0	6998433.0	93.4	1.1	6.2	0.3	0.2	0.0	6.1	87.2	79	79	79.00	38	633896000	27.1	22.7	22.6	27.4	0.2	31.6	12.5	bulk
2798160	SRR1811592	SRP055201	SRS851175	SRX884154	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614840: 12h [342]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;12 hrs	GEO Accession;;GSM1614840		GSM1614840	12h [342]	1142785244	7232818	2016-09-18 20:49:05	824877598	1142785244	7232818	2	7232818	index:0,count:7232818,average:79,stdev:0|index:1,count:7232818,average:79,stdev:0	GSM1614840_r1	GEO			in_mesa	27720483	5.25	3.54	0.03	862373014	835896804	798985405	781088999	96.93	97.76	6802960	6550886	140.104	426.359	115	107305	81.26	87.77	7580367	5528137	7580367	5528137	84.13	84.69	7580367	5723093	7580367	5334055	76133098	8.83	0.95	0	6.98	0	0.26	0	0.20	0	0.00	0	5.48	0	6802960	0	158	0	156.41	0	1.58	0	0.01	0	1.28	0	0.01	0	205.02	0	0.67	0	68826	0	7232818	0	504667	0	19072	0	14355	0	0	0	396431	0	1535	0	0	0	13161	0	1815160	0	3682	0	1833538	0	87.08	0	6298293	0	140694	1641758	11.668997967220	7232818.0	6802960.0	68826.0	504667.0	19072.0	14355.0	0.0	396431.0	6298293.0	94.1	1.0	7.0	0.3	0.2	0.0	5.5	87.1	79	79	79.00	38	571392622	27.4	22.4	22.3	27.7	0.2	31.8	12.8	bulk
2798193	SRR1811593	SRP055201	SRS851174	SRX884155	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614841: 12h [343]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;12 hrs	GEO Accession;;GSM1614841		GSM1614841	12h [343]	9230580884	58421398	2016-09-18 20:49:05	6533922472	9230580884	58421398	2	58421398	index:0,count:58421398,average:79,stdev:0|index:1,count:58421398,average:79,stdev:0	GSM1614841_r1	GEO			in_mesa	27720483	3.26	3.25	0.04	7044976640	6919914385	6630963096	6551570704	98.22	98.8	52217925	48084697	173.638	758.102	115	526038	85.03	90.44	57242039	44401870	57242039	44401870	86.64	87.14	57242039	45243678	57242039	42781823	494959386	7.03	1.18	0	5.34	0	0.32	0	0.16	0	0.00	0	10.14	0	52217925	0	158	0	156.10	0	1.67	0	0.00	0	1.31	0	0.01	0	189.82	0	0.78	0	687116	0	58421398	0	3121190	0	185884	0	92742	0	0	0	5924847	0	11587	0	0	0	116111	0	16227964	0	30829	0	16386491	0	84.04	0	49096735	0	263701	15277888	57.936405246852	58421398.0	52217925.0	687116.0	3121190.0	185884.0	92742.0	0.0	5924847.0	49096735.0	89.4	1.2	5.3	0.3	0.2	0.0	10.1	84.0	79	79	79.00	38	4615290442	25.6	24.3	24.2	25.6	0.2	30.1	11.2	bulk
2798225	SRR1811594	SRP055201	SRS851172	SRX884156	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614842: 12h [344]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;12 hrs	GEO Accession;;GSM1614842		GSM1614842	12h [344]	8943803988	45631653	2016-09-18 20:49:05	5635774673	8943803988	45631653	2	45631653	index:0,count:45631653,average:98,stdev:0|index:1,count:45631653,average:98,stdev:0	GSM1614842_r1	GEO			in_mesa	27720483	3.18	3.28	0.03	7116093800	6967076293	6769976835	6660053083	97.91	98.38	43849915	40089120	199.198	782.759	136	359675	85.81	90.29	47279161	37626329	47279161	37626329	86.87	87.25	47279161	38091157	47279161	36357001	509015386	7.15	1.44	0	4.78	0	0.29	0	0.16	0	0.00	0	3.45	0	43849915	0	196	0	194.21	0	1.57	0	0.01	0	1.27	0	0.01	0	275.63	0	0.27	0	659062	0	45631653	0	2179256	0	131753	0	74222	0	0	0	1575763	0	14939	0	0	0	149376	0	19327772	0	35086	0	19527173	0	91.32	0	41670659	0	281431	17268246	61.358720254698	45631653.0	43849915.0	659062.0	2179256.0	131753.0	74222.0	0.0	1575763.0	41670659.0	96.1	1.4	4.8	0.3	0.2	0.0	3.5	91.3	98	98	98.00	38	4471901994	25.7	24.2	24.0	26.0	0.0	35.7	17.4	bulk
2798257	SRR1811595	SRP055201	SRS851173	SRX884157	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614843: 24h [345]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;24 hrs	GEO Accession;;GSM1614843		GSM1614843	24h [345]	1816038412	11493914	2016-09-18 20:49:05	1305700325	1816038412	11493914	2	11493914	index:0,count:11493914,average:79,stdev:0|index:1,count:11493914,average:79,stdev:0	GSM1614843_r1	GEO			in_mesa	27720483	4.14	3.3	0.04	1450683148	1418978395	1354164716	1334460949	97.81	98.54	10665721	9972901	170.205	606.600	125	110940	80.68	86.54	11820317	8605348	11820317	8605348	82.41	82.94	11820317	8789380	11820317	8247304	150314257	10.36	0.94	0	6.28	0	0.28	0	0.19	0	0.00	0	6.73	0	10665721	0	158	0	156.26	0	1.92	0	0.01	0	1.49	0	0.01	0	220.10	0	0.71	0	107558	0	11493914	0	721820	0	32517	0	21904	0	0	0	773772	0	2158	0	0	0	21105	0	2987066	0	5636	0	3015965	0	86.51	0	9943901	0	165069	2841131	17.211778104914	11493914.0	10665721.0	107558.0	721820.0	32517.0	21904.0	0.0	773772.0	9943901.0	92.8	0.9	6.3	0.3	0.2	0.0	6.7	86.5	79	79	79.00	38	908019206	26.2	23.7	23.6	26.3	0.2	31.6	12.5	bulk
2798288	SRR1811596	SRP055201	SRS851171	SRX884158	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614844: 24h [346]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;24 hrs	GEO Accession;;GSM1614844		GSM1614844	24h [346]	10344455288	65471236	2016-09-18 20:49:05	7314822917	10344455288	65471236	2	65471236	index:0,count:65471236,average:79,stdev:0|index:1,count:65471236,average:79,stdev:0	GSM1614844_r1	GEO			in_mesa	27720483	3.98	3.3	0.05	8120496854	7966046817	7611751518	7515294396	98.1	98.73	58982543	54485716	178.067	696.851	125	577411	82.56	88.16	64945050	48693406	64945050	48693406	84.4	84.86	64945050	49782740	64945050	46871055	750302304	9.24	0.91	0	5.73	0	0.28	0	0.19	0	0.00	0	9.44	0	58982543	0	158	0	156.14	0	1.75	0	0.01	0	1.42	0	0.01	0	200.25	0	0.78	0	592910	0	65471236	0	3752247	0	185788	0	124462	0	0	0	6178443	0	12294	0	0	0	123161	0	17249614	0	33034	0	17418103	0	84.36	0	55230296	0	254513	16530968	64.951369871087	65471236.0	58982543.0	592910.0	3752247.0	185788.0	124462.0	0.0	6178443.0	55230296.0	90.1	0.9	5.7	0.3	0.2	0.0	9.4	84.4	79	79	79.00	38	5172227644	26.0	24.0	23.8	26.0	0.2	30.3	11.3	bulk
2798384	SRR1811599	SRP055201	SRS851167	SRX884161	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614847: 36h [349]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;36 hrs	GEO Accession;;GSM1614847		GSM1614847	36h [349]	2834443844	17939518	2016-09-18 20:49:05	2010233767	2834443844	17939518	2	17939518	index:0,count:17939518,average:79,stdev:0|index:1,count:17939518,average:79,stdev:0	GSM1614847_r1	GEO			in_mesa	27720483	3.92	3.24	0.05	2154823213	2124877091	2017117791	2000428786	98.61	99.17	15990050	14865479	170.859	657.916	115	177450	83.26	89.05	17666830	13313581	17666830	13313581	85.35	85.73	17666830	13647339	17666830	12816590	190859201	8.86	1.08	0	5.79	0	0.31	0	0.18	0	0.00	0	10.38	0	15990050	0	158	0	156.15	0	1.63	0	0.00	0	1.36	0	0.01	0	179.40	0	0.77	0	194004	0	17939518	0	1039493	0	56226	0	31639	0	0	0	1861603	0	3125	0	0	0	33077	0	4816220	0	8557	0	4860979	0	83.34	0	14950557	0	143061	4552920	31.825025688343	17939518.0	15990050.0	194004.0	1039493.0	56226.0	31639.0	0.0	1861603.0	14950557.0	89.1	1.1	5.8	0.3	0.2	0.0	10.4	83.3	79	79	79.00	38	1417221922	25.5	24.5	24.4	25.4	0.2	30.0	11.2	bulk
2801809	SRR1811604	SRP055201	SRS851161	SRX884166	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614852: Sham operated [69]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614852		GSM1614852	Sham operated [69]	6359348600	31796743	2016-09-18 20:49:05	4212910100	6359348600	31796743	2	31796743	index:0,count:31796743,average:100,stdev:0|index:1,count:31796743,average:100,stdev:0	GSM1614852_r1	GEO			in_mesa	27720483	4.43	3.22	0.02	4575644617	4566999509	4266063680	4283748525	99.81	100.41	29250277	27303700	178.624	665.029	145	303674	86.66	93.07	32302203	25347092	32302203	25347092	87.74	88.26	32302203	25665301	32302203	24037346	212201038	4.64	1.53	0	6.34	0	0.26	0	0.08	0	0.00	0	7.67	0	29250277	0	200	0	195.83	0	2.29	0	0.01	0	1.57	0	0.01	0	219.29	0	0.81	0	484936	0	31796743	0	2015588	0	81749	0	25363	0	0	0	2439354	0	9373	0	0	0	86532	0	12258342	0	23048	0	12377295	0	85.65	0	27234689	0	213758	10956666	51.257337737067	31796743.0	29250277.0	484936.0	2015588.0	81749.0	25363.0	0.0	2439354.0	27234689.0	92.0	1.5	6.3	0.3	0.1	0.0	7.7	85.7	100	100	100.00	38	3179674300	25.1	24.8	25.0	24.8	0.3	30.6	11.4	bulk
2801840	SRR1811605	SRP055201	SRS851160	SRX884167	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614853: Sham operated [70]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;adult|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614853		GSM1614853	Sham operated [70]	8068413400	40342067	2016-09-18 20:49:05	5361169862	8068413400	40342067	2	40342067	index:0,count:40342067,average:100,stdev:0|index:1,count:40342067,average:100,stdev:0	GSM1614853_r1	GEO			in_mesa	27720483	4.28	3.36	0.02	5989242191	5968595300	5606748462	5616929591	99.66	100.18	37775830	34500351	190.539	829.615	136	330206	88.02	94.16	41530490	33250983	41530490	33250983	90.06	90.46	41530490	34022432	41530490	31945713	263486627	4.40	0.86	0	6.10	0	0.27	0	0.10	0	0.00	0	5.99	0	37775830	0	200	0	196.30	0	1.66	0	0.00	0	1.27	0	0.01	0	189.60	0	0.78	0	348060	0	40342067	0	2461829	0	109208	0	39221	0	0	0	2417808	0	12399	0	0	0	119378	0	16636239	0	23503	0	16791519	0	87.54	0	35314001	0	232133	14888667	64.138519727915	40342067.0	37775830.0	348060.0	2461829.0	109208.0	39221.0	0.0	2417808.0	35314001.0	93.6	0.9	6.1	0.3	0.1	0.0	6.0	87.5	100	100	100.00	38	4034206700	25.1	24.8	24.9	24.9	0.3	30.8	11.5	bulk
2801904	SRR1811607	SRP055201	SRS851162	SRX884169	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614855: E12.5 [84]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;embryonic 12.5|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614855		GSM1614855	E12.5 [84]	9825233600	49126168	2016-09-18 20:49:05	6497522492	9825233600	49126168	2	49126168	index:0,count:49126168,average:100,stdev:0|index:1,count:49126168,average:100,stdev:0	GSM1614855_r1	GEO			in_mesa	27720483	2.91	3.7	0.06	6998162455	6974851334	6466607968	6481332723	99.67	100.23	44674049	41660949	182.964	598.729	136	450639	83.85	90.89	50522803	37460083	50522803	37460083	86.82	87.1	50522803	38783999	50522803	35897101	569997942	8.14	0.68	0	7.04	0	0.27	0	0.08	0	0.00	0	8.71	0	44674049	0	200	0	196.31	0	1.58	0	0.00	0	1.29	0	0.01	0	158.76	0	0.80	0	336034	0	49126168	0	3458698	0	130989	0	40322	0	0	0	4280808	0	14939	0	0	0	125368	0	18620271	0	31614	0	18792192	0	83.90	0	41215351	0	238429	16843336	70.642983865218	49126168.0	44674049.0	336034.0	3458698.0	130989.0	40322.0	0.0	4280808.0	41215351.0	90.9	0.7	7.0	0.3	0.1	0.0	8.7	83.9	100	100	100.00	38	4912616800	25.3	24.8	24.7	24.9	0.3	30.3	11.1	bulk
2801937	SRR1811608	SRP055201	SRS851159	SRX884170	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614856: E12.5 [86]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;embryonic 12.5|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614856		GSM1614856	E12.5 [86]	8390834200	41954171	2016-09-18 20:49:05	5549052519	8390834200	41954171	2	41954171	index:0,count:41954171,average:100,stdev:0|index:1,count:41954171,average:100,stdev:0	GSM1614856_r1	GEO			in_mesa	27720483	2.78	3.7	0.05	6025797251	5998689387	5584168076	5590705318	99.55	100.12	38455604	35654345	186.762	670.386	134	319818	83.2	89.95	43357977	31995956	43357977	31995956	86.01	86.25	43357977	33074961	43357977	30678685	544745011	9.04	1.43	0	6.88	0	0.27	0	0.10	0	0.00	0	7.97	0	38455604	0	200	0	195.88	0	1.61	0	0.01	0	1.27	0	0.01	0	191.18	0	0.79	0	598437	0	41954171	0	2885348	0	112835	0	40047	0	0	0	3345685	0	12613	0	0	0	107378	0	15763182	0	30208	0	15913381	0	84.78	0	35570256	0	234591	14227062	60.646239625561	41954171.0	38455604.0	598437.0	2885348.0	112835.0	40047.0	0.0	3345685.0	35570256.0	91.7	1.4	6.9	0.3	0.1	0.0	8.0	84.8	100	100	100.00	38	4195417100	25.4	24.5	24.8	25.0	0.3	30.7	11.5	bulk
2801970	SRR1811609	SRP055201	SRS851158	SRX884171	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614857: E12.5 [87]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;embryonic 12.5|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614857		GSM1614857	E12.5 [87]	7307078400	36535392	2016-09-18 20:49:05	4815337757	7307078400	36535392	2	36535392	index:0,count:36535392,average:100,stdev:0|index:1,count:36535392,average:100,stdev:0	GSM1614857_r1	GEO			in_mesa	27720483	3.21	3.85	0.05	5255044379	5237088724	4851460818	4863916233	99.66	100.26	33430382	31148447	184.652	627.277	134	295691	83.98	91.12	37804444	28074349	37804444	28074349	87.01	87.27	37804444	29087030	37804444	26890075	422830553	8.05	1.27	0	7.17	0	0.27	0	0.09	0	0.00	0	8.14	0	33430382	0	200	0	195.88	0	1.51	0	0.00	0	1.24	0	0.01	0	204.55	0	0.78	0	465662	0	36535392	0	2618688	0	98954	0	32061	0	0	0	2973995	0	11369	0	0	0	92367	0	13952383	0	27062	0	14083181	0	84.33	0	30811694	0	226431	12638085	55.814287796282	36535392.0	33430382.0	465662.0	2618688.0	98954.0	32061.0	0.0	2973995.0	30811694.0	91.5	1.3	7.2	0.3	0.1	0.0	8.1	84.3	100	100	100.00	38	3653539200	25.5	24.5	24.5	25.2	0.3	30.6	11.3	bulk
2802193	SRR1811610	SRP055201	SRS851157	SRX884172	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614858: E17.5 [336]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;embryonic 17.5|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614858		GSM1614858	E17.5 [336]	9104614752	57624144	2016-09-18 20:49:05	6456852056	9104614752	57624144	2	57624144	index:0,count:57624144,average:79,stdev:0|index:1,count:57624144,average:79,stdev:0	GSM1614858_r1	GEO			in_mesa	27720483	4.46	3.63	0.04	6675059546	6618726939	6162331073	6145578177	99.16	99.73	51821058	48949273	152.141	573.943	114	610901	85.42	92.66	58433851	44267791	58433851	44267791	88.94	89.34	58433851	46091553	58433851	42683462	394542588	5.91	1.53	0	7.02	0	0.26	0	0.10	0	0.00	0	9.71	0	51821058	0	158	0	156.06	0	1.42	0	0.00	0	1.20	0	0.00	0	200.63	0	0.76	0	884418	0	57624144	0	4047062	0	149969	0	56262	0	0	0	5596855	0	14396	0	0	0	102573	0	16000989	0	29260	0	16147218	0	82.91	0	47773996	0	231375	14845646	64.162705564560	57624144.0	51821058.0	884418.0	4047062.0	149969.0	56262.0	0.0	5596855.0	47773996.0	89.9	1.5	7.0	0.3	0.1	0.0	9.7	82.9	79	79	79.00	38	4552307376	26.1	23.8	23.8	26.1	0.2	30.2	11.3	bulk
2802226	SRR1811611	SRP055201	SRS851156	SRX884173	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614859: E17.5 [337]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;embryonic 17.5|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614859		GSM1614859	E17.5 [337]	1110819790	7030505	2016-09-18 20:49:05	801271785	1110819790	7030505	2	7030505	index:0,count:7030505,average:79,stdev:0|index:1,count:7030505,average:79,stdev:0	GSM1614859_r1	GEO			in_mesa	27720483	4.93	3.94	0.04	880398197	869137356	812937867	807985191	98.72	99.39	6584107	6216664	160.857	558.284	115	74359	84.01	91.08	7398460	5531568	7398460	5531568	87.75	88.08	7398460	5777430	7398460	5348860	64559713	7.33	1.03	0	7.27	0	0.22	0	0.12	0	0.00	0	6.02	0	6584107	0	158	0	156.37	0	1.36	0	0.00	0	1.16	0	0.01	0	207.46	0	0.69	0	72299	0	7030505	0	511133	0	15117	0	8346	0	0	0	422935	0	1821	0	0	0	11634	0	1825841	0	3365	0	1842661	0	86.38	0	6072974	0	144953	1761173	12.149958952212	7030505.0	6584107.0	72299.0	511133.0	15117.0	8346.0	0.0	422935.0	6072974.0	93.7	1.0	7.3	0.2	0.1	0.0	6.0	86.4	79	79	79.00	38	555409895	27.0	23.0	22.7	27.0	0.2	31.6	12.5	bulk
2802258	SRR1811612	SRP055201	SRS851155	SRX884174	SRA243458	GEO		The Calcium Channel Subunit Alpha2delta2 Suppresses Axon Regeneration in the Adult CNS	Purpose: Injuries to the adult central nervous system (CNS) often result in permanent disabilities because neurons lose the ability to regenerate their axon during development. Although the developmental transition from a growing to a transmitting phase may represent one of the first steps in the gradual loss of axon growth and regeneration ability, the molecular mechanisms regulating this process has yet to be identified. The main goal of this study was to dissect the molecular mechanisms mediating the decline in axon growth ability and its relationship with regeneration failure in the adult CNS. To this end, we sequenced the whole transcriptome of dorsal root ganglia (DRG) neurons in both growth competent and incompetent states at different developmental stages, in diverse culture and in vivo experimental conditions. Overall design: mRNA profiles of mouse embryonic E12.5 and E17.5 lumbar DRGs, conditioned and sham operated adult L4-5DRGs, and cultured adult lumbar DRG (6, 12, 24 and 36 hr after plating) neurons were generated by deep sequencing, in triplicate, using the Illumina TruSeq RNA Sample Prep Kits V2.		GSM1614860: E17.5 [338]; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Cells were isolated by cell sorting, lyzed in Qiazol and RNA isolated. Illumina TruSeq RNA Sample Prep Kits V2 was used with 10 ng of total RNA for the construction of sequencing libraries. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 1500	developmental stage;;embryonic 17.5|source_name;;DRG neuron|time after plating;;none	GEO Accession;;GSM1614860		GSM1614860	E17.5 [338]	1719016300	10879850	2016-09-18 20:49:05	1224258792	1719016300	10879850	2	10879850	index:0,count:10879850,average:79,stdev:0|index:1,count:10879850,average:79,stdev:0	GSM1614860_r1	GEO			in_mesa	27720483	3.99	3.57	0.04	1377414670	1371183656	1281219602	1282374658	99.55	100.09	9847232	8995705	187.025	822.584	126	86407	86.21	92.76	10948602	8488989	10948602	8488989	89.07	89.39	10948602	8771413	10948602	8180544	84055507	6.10	1.14	0	6.40	0	0.21	0	0.09	0	0.00	0	9.19	0	9847232	0	158	0	156.12	0	1.41	0	0.00	0	1.19	0	0.01	0	186.51	0	0.78	0	123570	0	10879850	0	696025	0	23298	0	9650	0	0	0	999670	0	2616	0	0	0	18690	0	2945555	0	5465	0	2972326	0	84.11	0	9151207	0	158815	2900889	18.265837609798	10879850.0	9847232.0	123570.0	696025.0	23298.0	9650.0	0.0	999670.0	9151207.0	90.5	1.1	6.4	0.2	0.1	0.0	9.2	84.1	79	79	79.00	38	859508150	25.6	24.4	24.2	25.6	0.2	30.3	11.4	bulk
1386831	SRR1947294	SRP056191	SRS874594	SRX973877	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Thymus GFP+ Tregs replicate 2	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Treg recently generated from thymus		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;ThymusGFPplusTreg|sex;;male|tissue;;Regulatory T cells		200	ThymusGFPplusTreg	ThymusGFPplusTreg	2908430528	14958091	2015-04-15 00:00:00	1394272750	2908430528	14958091	2	14958091	index:0,count:14716667,average:99.30,stdev:3.96|index:1,count:14638057,average:98.86,stdev:5.35	ThymusGFPplusTreg_replicate2	INSERM			in_mesa	25939024	5.63	3.52	0.03	2351656175	2336753423	2087595384	2089742506	99.37	100.1	14265098	13449625	202.017	487.905	130	111776	85.69	96.88	17689560	12223494	17689560	12223494	92.82	93.47	17689560	13240315	17689560	11793598	135147123	5.75	0.41	0.08	11.45	13.86	0.34	0.75	0.11	0.10	0.00	0.00	0.46	0.06	14265098	556340	198	96	197.77	95.10	1.16	1.19	0.00	0.00	1.11	1.12	0.00	0.01	442.97	202.12	0.12	0.26	58707	473	14396633	561458	1647871	77791	48611	4213	16500	547	0	0	66424	358	2273	63	0	0	22944	537	3984979	111722	984	78	4011180	112400	87.64	85.23	12617227	478549	85339	3896734	45.661819332310	14958091.0	14821438.0	59180.0	1725662.0	52824.0	17047.0	0.0	66782.0	13095776.0	99.1	0.4	11.5	0.4	0.1	0.0	0.4	87.5	50	100	96.07	38	53940360	26.5	23.2	22.6	27.7	0.0	35.1	25.3	bulk
1389135	SRR1947324	SRP056191	SRS874613	SRX973874	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Spleen GFP- Tregs replicate 1	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Treg from spleen		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;SpleenGFPminusTreg|sex;;male|tissue;;Regulatory T cells		200	SpleenGFPminusTreg	SpleenGFPminusTreg	2545422427	13309105	2015-04-15 00:00:00	1218093206	2545422427	13309105	2	13309105	index:0,count:12881467,average:99.21,stdev:4.32|index:1,count:12842146,average:98.69,stdev:5.85	SpleenGFPminusTreg	INSERM			in_mesa	25939024	6.03	3.62	0.03	1839963927	1783443415	1613110156	1577624272	96.93	97.8	12235528	11629316	163.505	429.579	109	160246	82.91	94.98	15982527	10144621	15982527	10144621	89.42	91.21	15982527	10941538	15982527	9742365	153397416	8.34	0.73	0.08	12.52	22.45	0.37	0.43	0.16	0.06	0.00	0.00	0.92	0.07	12235528	889542	198	94	197.46	94.17	1.14	1.17	0.00	0.01	1.10	1.14	0.00	0.01	343.79	357.84	0.17	0.57	90685	688	12414508	894597	1554325	200828	46123	3865	19259	553	0	0	113598	637	2399	99	0	0	28020	691	3990892	128161	1484	137	4022795	129088	86.04	76.99	10681203	688714	100454	3542780	35.267684711410	13309105.0	13125070.0	91373.0	1755153.0	49988.0	19812.0	0.0	114235.0	11369917.0	98.6	0.7	13.2	0.4	0.1	0.0	0.9	85.4	50	100	94.83	38	84834267	25.0	24.1	23.9	27.0	0.0	35.1	25.4	bulk
1389150	SRR1947325	SRP056191	SRS874613	SRX973887	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Spleen GFP- Tregs replicate 2	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Treg from spleen		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;SpleenGFPminusTreg|sex;;male|tissue;;Regulatory T cells		200	SpleenGFPminusTreg	SpleenGFPminusTreg	2389746870	12364654	2015-04-15 00:00:00	1147292279	2389746870	12364654	2	12364654	index:0,count:12097406,average:99.20,stdev:4.33|index:1,count:12033895,average:98.86,stdev:5.37	SpleenGFPminusTreg_replicate2	INSERM			in_mesa	25939024	6.43	4.0	0.03	1822601530	1806174783	1603683446	1602659173	99.1	99.94	11617451	11054038	182.944	466.530	108	122209	83.65	95.43	14843188	9718481	14843188	9718481	91.14	91.66	14843188	10587830	14843188	9334235	143951167	7.90	0.64	0.09	12.19	14.80	0.37	0.70	0.16	0.11	0.00	0.00	0.74	0.07	11617451	592737	198	95	197.72	94.01	1.14	1.18	0.00	0.01	1.09	1.14	0.00	0.01	385.09	269.10	0.12	0.28	75842	544	11766647	598007	1434062	88517	43709	4168	18449	656	0	0	87038	446	1865	67	0	0	17875	576	3131249	105921	843	99	3151832	106663	86.54	84.32	10183389	504220	75733	2961397	39.103125453897	12364654.0	12210188.0	76386.0	1522579.0	47877.0	19105.0	0.0	87484.0	10687609.0	98.8	0.6	12.3	0.4	0.2	0.0	0.7	86.4	50	100	95.19	38	56922584	26.6	23.0	22.4	28.0	0.0	35.2	25.4	bulk
1389183	SRR1947327	SRP056191	SRS874613	SRX973888	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Spleen GFP- Tregs replicate 3	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Treg from spleen		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;SpleenGFPminusTreg|sex;;male|tissue;;Regulatory T cells		200	SpleenGFPminusTreg	SpleenGFPminusTreg	2824557087	14571725	2015-04-15 00:00:00	1363076340	2824557087	14571725	2	14571725	index:0,count:14296526,average:99.23,stdev:4.21|index:1,count:14215354,average:98.90,stdev:5.26	SpleenGFPminusTreg_replicate3	INSERM			in_mesa	25939024	8.32	3.87	0.03	2212690101	2193036835	1933721812	1931267151	99.11	99.87	13776604	13150195	189.314	446.971	119	126372	81.52	93.71	17585118	11231057	17585118	11231057	89.77	89.98	17585118	12367483	17585118	10784541	196275345	8.87	0.53	0.08	12.85	15.27	0.36	0.68	0.20	0.13	0.00	0.00	0.61	0.08	13776604	625934	198	95	197.80	94.79	1.16	1.19	0.00	0.01	1.10	1.12	0.00	0.01	332.35	252.63	0.12	0.27	73994	492	13940155	631570	1791338	96468	50359	4299	27573	847	0	0	85619	490	1892	81	0	0	19533	600	3437680	108224	813	91	3459918	108996	85.98	83.83	11985266	529466	83997	3359961	40.000964320154	14571725.0	14402538.0	74486.0	1887806.0	54658.0	28420.0	0.0	86109.0	12514732.0	98.8	0.5	13.0	0.4	0.2	0.0	0.6	85.9	50	100	95.71	38	60447550	26.6	23.0	22.5	27.8	0.0	35.3	25.4	bulk
1389199	SRR1947328	SRP056191	SRS874663	SRX973884	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Thymus GFP- Tregs replicate 2	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Recirculating Treg		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;ThymusGFPminusTreg|sex;;male|tissue;;Regulatory T cells		200	ThymusGFPminusTreg	ThymusGFPminusTreg	2435734382	12580149	2015-04-15 00:00:00	1165234321	2435734382	12580149	2	12580149	index:0,count:12312790,average:99.25,stdev:4.17|index:1,count:12280500,average:98.83,stdev:5.45	ThymusGFPminusTreg_replicate2	INSERM			in_mesa	25939024	5.24	3.84	0.04	1837526371	1827418324	1616854427	1623036871	99.45	100.38	11866366	11275262	179.406	426.306	118	129215	85.11	97.12	15164260	10099972	15164260	10099972	92.56	93.3	15164260	10983194	15164260	9702703	114156009	6.21	0.62	0.10	12.21	15.10	0.38	0.75	0.13	0.09	0.00	0.00	0.72	0.09	11866366	561722	198	95	197.70	93.92	1.15	1.18	0.00	0.01	1.10	1.13	0.00	0.01	327.63	204.12	0.12	0.28	75052	584	12013141	567008	1467266	85614	45072	4266	15266	538	0	0	86437	482	1904	60	0	0	21599	569	3503056	106700	783	118	3527342	107447	86.56	83.97	10399100	476108	76536	3238301	42.310821051531	12580149.0	12428088.0	75636.0	1552880.0	49338.0	15804.0	0.0	86919.0	10875208.0	98.8	0.6	12.3	0.4	0.1	0.0	0.7	86.4	50	100	95.06	38	53899979	26.3	23.2	22.6	27.8	0.0	35.1	25.2	bulk
1389214	SRR1947329	SRP056191	SRS874663	SRX973886	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Thymus GFP- Tregs replicate 3	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Recirculating Treg		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;ThymusGFPminusTreg|sex;;male|tissue;;Regulatory T cells		200	ThymusGFPminusTreg	ThymusGFPminusTreg	2389901684	12370071	2015-04-15 00:00:00	1134321252	2389901684	12370071	2	12370071	index:0,count:12089382,average:99.24,stdev:4.24|index:1,count:12045605,average:98.81,stdev:5.55	ThymusGFPminusTreg_replicate3	INSERM			in_mesa	25939024	6.23	3.54	0.03	1795201879	1780328120	1576149811	1575812248	99.17	99.98	11605708	11089981	179.182	399.067	108	135968	85.04	97.21	14822432	9869573	14822432	9869573	92.8	93.5	14822432	10770508	14822432	9492261	111880892	6.23	0.74	0.09	12.35	15.25	0.37	0.69	0.14	0.11	0.00	0.00	0.85	0.08	11605708	599817	198	94	197.77	93.12	1.14	1.18	0.00	0.01	1.10	1.13	0.00	0.01	325.80	217.86	0.12	0.28	87208	516	11764916	605155	1453337	92301	43347	4184	16348	659	0	0	99513	495	1302	34	0	0	13841	482	2850295	99280	581	55	2866019	99851	86.29	83.87	10152371	507516	63159	2662200	42.150762361659	12370071.0	12205525.0	87724.0	1545638.0	47531.0	17007.0	0.0	100008.0	10659887.0	98.7	0.7	12.5	0.4	0.1	0.0	0.8	86.2	50	100	94.40	38	57126530	26.5	23.0	22.4	28.2	0.0	35.2	25.1	bulk
2772050	SRR1916262	SRP056191	SRS874663	SRX957257	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Thymus GFP- Tregs replicate 1	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Recirculating Treg		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;ThymusGFPminusTreg|sex;;male|tissue;;Regulatory T cells		200	ThymusGFPminusTreg	ThymusGFPminusTreg	2857286094	14832509	2015-04-15 00:00:00	1356531005	2857286094	14832509	2	14832509	index:0,count:14438505,average:99.22,stdev:4.29|index:1,count:14404086,average:98.91,stdev:5.24	RNA-seq regulatory T cells	INSERM			in_mesa	25939024	6.27	3.19	0.03	2142300615	2086961710	1925368676	1891910089	97.42	98.26	13842854	13154952	169.656	411.321	120	148973	83.63	93.43	17204763	11576964	17204763	11576964	88.86	90.11	17204763	12300726	17204763	11164893	193548077	9.03	0.57	0.08	10.37	18.38	0.33	0.50	0.15	0.07	0.00	0.00	0.71	0.06	13842854	817275	198	95	197.66	94.76	1.14	1.17	0.00	0.01	1.09	1.13	0.00	0.01	382.09	370.09	0.15	0.53	80545	654	14010082	822427	1452154	151161	46395	4121	21245	547	0	0	99588	484	2753	69	0	0	28719	640	4427776	125298	1415	120	4460663	126127	88.44	80.99	12390700	666114	101580	3980229	39.183195510927	14832509.0	14660129.0	81199.0	1603315.0	50516.0	21792.0	0.0	100072.0	13056814.0	98.8	0.5	10.8	0.3	0.1	0.0	0.7	88.0	50	100	95.55	38	78582974	25.6	23.5	23.4	27.6	0.0	35.2	25.6	bulk
2777809	SRR1947316	SRP056191	SRS874594	SRX973879	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Thymus GFP+ Tregs replicate 3	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Treg recently generated from thymus		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;ThymusGFPplusTreg|sex;;male|tissue;;Regulatory T cells		200	ThymusGFPplusTreg	ThymusGFPplusTreg	2757560751	14225664	2015-04-15 00:00:00	1329632426	2757560751	14225664	2	14225664	index:0,count:13956006,average:99.27,stdev:4.08|index:1,count:13879018,average:98.87,stdev:5.35	ThymusGFPplusTreg	INSERM			in_mesa	25939024	7.6	3.97	0.03	2109887427	2085076730	1819891081	1815935620	98.82	99.78	13452013	12995639	176.182	343.285	120	142585	79.28	92.38	17499175	10664882	17499175	10664882	88.41	88.6	17499175	11892865	17499175	10228344	202728566	9.61	0.56	0.07	14.02	16.47	0.35	0.70	0.17	0.12	0.00	0.00	0.64	0.07	13452013	610807	198	95	197.86	94.71	1.15	1.18	0.00	0.01	1.11	1.15	0.00	0.01	357.62	246.52	0.12	0.26	76226	413	13609360	616304	1907506	101484	47254	4317	22649	751	0	0	87444	429	1255	58	0	0	12211	414	2894937	93452	670	57	2909073	93981	84.83	82.64	11544507	509323	67054	2836009	42.294404509798	14225664.0	14062820.0	76639.0	2008990.0	51571.0	23400.0	0.0	87873.0	12053830.0	98.9	0.5	14.1	0.4	0.2	0.0	0.6	84.7	50	100	95.59	38	58913314	27.1	22.6	21.9	28.4	0.0	35.2	25.4	bulk
2778192	SRR1947322	SRP056191	SRS874599	SRX973881	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Spleen GFP+ Tregs replicate 2	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Treg recently generated from spleen		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;SpleenGFPplusTreg|sex;;male|tissue;;Regulatory T cells		200	SpleenGFPplusTreg	SpleenGFPplusTreg	3008180604	15578134	2015-04-15 00:00:00	1452423014	3008180604	15578134	2	15578134	index:0,count:15226555,average:99.22,stdev:4.29|index:1,count:15163035,average:98.76,stdev:5.66	SpleenGFPplusTreg_Replicate2	INSERM			in_mesa	25939024	5.76	4.28	0.04	2237710373	2216101918	1937377436	1936918353	99.03	99.98	14602955	13969644	173.360	420.035	108	168754	82.72	96.01	19189578	12080093	19189578	12080093	91.34	91.98	19189578	13337825	19189578	11573290	161808576	7.23	0.69	0.09	13.64	16.82	0.42	0.72	0.18	0.12	0.00	0.00	0.81	0.09	14602955	759596	198	94	197.64	93.48	1.14	1.18	0.00	0.01	1.10	1.14	0.00	0.01	370.29	250.91	0.12	0.29	102374	722	14811456	766678	2020675	128943	62130	5482	27116	903	0	0	119255	697	2176	79	0	0	22531	791	4013225	135512	933	85	4038865	136467	84.95	82.26	12582280	630653	80671	3777520	46.826244871143	15578134.0	15362551.0	103096.0	2149618.0	67612.0	28019.0	0.0	119952.0	13212933.0	98.6	0.7	13.8	0.4	0.2	0.0	0.8	84.8	50	100	94.59	38	72521128	26.1	23.4	22.8	27.7	0.0	35.0	25.1	bulk
2778224	SRR1947323	SRP056191	SRS874599	SRX973882	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Spleen GFP+ Tregs replicate 3	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Treg recently generated from spleen		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;SpleenGFPplusTreg|sex;;male|tissue;;Regulatory T cells		200	SpleenGFPplusTreg	SpleenGFPplusTreg	2791724460	14374137	2015-04-15 00:00:00	1355183900	2791724460	14374137	2	14374137	index:0,count:14105654,average:99.04,stdev:4.76|index:1,count:14057282,average:99.21,stdev:4.34	SpleenGFPplusTreg_replicate3	INSERM			in_mesa	25939024	7.28	3.77	0.04	2143216624	2120184577	1897622028	1892064201	98.93	99.71	13610701	12977185	181.035	439.196	120	130257	81.97	92.95	17078413	11156666	17078413	11156666	89.09	89.32	17078413	12125418	17078413	10720576	195096376	9.10	0.56	0.09	11.66	14.03	0.41	0.64	0.24	0.13	0.00	0.00	0.64	0.11	13610701	580188	198	95	197.87	94.38	1.15	1.19	0.00	0.01	1.10	1.13	0.00	0.01	280.45	191.57	0.12	0.28	76575	538	13788799	585338	1608311	82140	56373	3738	32807	765	0	0	88918	647	2415	64	0	0	27019	645	3925445	114018	994	87	3955873	114814	87.04	85.09	12002390	498048	98651	3696179	37.467222836058	14374137.0	14190889.0	77113.0	1690451.0	60111.0	33572.0	0.0	89565.0	12500438.0	98.7	0.5	11.8	0.4	0.2	0.0	0.6	87.0	50	100	95.54	38	55921437	26.1	23.4	23.0	27.5	0.0	35.2	25.4	bulk
2780401	SRR1916367	SRP056191	SRS874594	SRX957164	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Thymus GFP+ Tregs replicate 1	Totalscript RNA-seq kit (Illumina)	Treg recently generated from thymus		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;ThymusGFPplusTreg|sex;;male|tissue;;Regulatory T cells		200	ThymusGFPplusTreg	ThymusGFPplusTreg	2850250956	14901367	2015-04-15 00:00:00	1374247898	2850250956	14901367	2	14901367	index:0,count:14426439,average:99.19,stdev:4.41|index:1,count:14374421,average:98.74,stdev:5.72	RNA-seq regulatory T cells_2	INSERM			in_mesa	25939024	5.45	3.43	0.04	2054593078	1994519294	1796266137	1761549077	97.08	98.07	13690478	13025359	163.116	404.981	109	179474	81.93	94.13	18003055	11216237	18003055	11216237	88.67	90.42	18003055	12138739	18003055	10774019	187532857	9.13	0.75	0.09	12.77	22.10	0.40	0.51	0.17	0.07	0.00	0.00	0.93	0.07	13690478	995295	198	94	197.49	94.25	1.14	1.15	0.00	0.01	1.10	1.15	0.00	0.01	352.38	327.89	0.17	0.56	103906	868	13899493	1001874	1774657	221453	55442	5153	24044	675	0	0	129529	751	2679	62	0	0	30159	848	4317671	137338	1441	176	4351950	138424	85.73	77.24	11915821	773842	100803	3835180	38.046288304912	14901367.0	14685773.0	104774.0	1996110.0	60595.0	24719.0	0.0	130280.0	12689663.0	98.6	0.7	13.4	0.4	0.2	0.0	0.9	85.2	50	100	94.95	38	95127415	25.0	24.0	23.8	27.2	0.0	35.1	25.4	bulk
2780434	SRR1916368	SRP056191	SRS874599	SRX957169	SRA246770	INSERM	U1043 CPTP	Mouse regulatory T cells Transcriptome	Regulatory T-cells (Tregs) differentiate in the thymus. After selection, they migrate to the periphery where they exert their effector functions. In the thymus and in the spleen of Rag2-GFP transgenic mice, two populations of Treg are found: I. a GFP+ population (respectively, developing cells and recent thymic emigrants) II. a GFP- population (mature cells).		Spleen GFP+ Tregs replicate 1	RNA sequencing analysis Rag2-GFP+ and Rag2-GFP- CD4+CD8-Foxp3-Thy1.1+ Tregs from mouse thymus and spleen were sorted by FACS and total RNA was immediately extracted by using the RNeasy® Micro Kit (QIAGEN) (including a DNase I treatment step) and the quality of the RNA was assessed by using an Agilent 2100 BioAnalyzer (Agilent Technologies). Three biological replicates were performed per cell population. Libraries for RNA-sequencing (RNAseq) were prepared according to the TotalScript RNA-seq protocol (Epicentre), starting from 5 ng of high-quality total RNA (i.e. RIN>7) and using the Oligo(dT) primer synthesis strategy. The quality of each library was assessed by using an Agilent 2100 BioAnalyzer. Samples were indexed and sequenced on Illumina HiSeq 2000 (paired-end 2x100bp). Reads were trimmed by using Cutadapt (v1.3), removing low-quality bases (-q < 10) and clipping adapter sequences. High-quality RNAseq reads were aligned to the mouse reference genome mm10 by using TopHat (v2.0.5) (11). Mice Rag2-Gfp transgenic mice (Rag-GFP) (W. Yu et al., Nature 400, 682 (1999)) on a C57BL/6 (B6) genetic background were provided by Dr. Pamela Fink (T. E. Boursalian, J. Golob, D. M. Soper, C. J. Cooper, P. J. Fink, Nature Immunol 5, 418 (2004)), B6 Foxp3-Thy1.1 knock-in mice by Dr. Alexander Rudensky (A. Liston et al., Proc Natl Acad Sci U S A 105, 11903 (2008)), and B6 GK mice by Dr. Andrew Lew (Y. Zhan, A. J. Corbett, J. L. Brady, R. M. Sutherland, A. M. Lew, Xenotransplantation 7, 267 (2000)). 	Treg recently generated from spleen		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 2000	age;;8 weeks|BioSampleModel;;Model organism or animal|breed;;C57Bl6 Rag2GFP Foxp3 Thy1 1|sample_type;;SpleenGFPplusTreg|sex;;male|tissue;;Regulatory T cells		200	SpleenGFPplusTreg	SpleenGFPplusTreg	2987887645	15598599	2015-04-15 00:00:00	1437655460	2987887645	15598599	2	15598599	index:0,count:15120640,average:99.19,stdev:4.37|index:1,count:15060546,average:98.80,stdev:5.54	RNA-seq regulatory T cells_3	INSERM			in_mesa	25939024	5.29	3.74	0.04	2169257850	2096842039	1899657253	1853614181	96.66	97.58	14363461	13650108	165.394	433.144	109	176136	81.12	92.89	18751160	11651339	18751160	11651339	87.93	89.28	18751160	12629785	18751160	11198074	210166315	9.69	0.70	0.09	12.49	21.77	0.40	0.47	0.22	0.08	0.00	0.00	0.89	0.09	14363461	1009423	198	95	197.51	94.34	1.15	1.16	0.00	0.01	1.11	1.15	0.00	0.01	372.32	365.76	0.16	0.55	102185	879	14582587	1016012	1820843	221193	57691	4824	31665	837	0	0	129770	928	2929	106	0	0	33061	810	4596635	145915	1879	191	4634504	147022	86.01	77.58	12542618	788230	108370	4095531	37.792110362646	15598599.0	15372884.0	103064.0	2042036.0	62515.0	32502.0	0.0	130698.0	13330848.0	98.6	0.7	13.1	0.4	0.2	0.0	0.8	85.5	50	100	95.28	38	96804425	25.0	24.0	23.8	27.1	0.0	35.1	25.6	bulk
1741464	SRR2229929	SRP056666	SRS1052839	SRX1178474	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867257: deep_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Deep CA1 pyramidal cells|location;;CA1|source_name;;Deep CA1 pyramidal cells	GEO Accession;;GSM1867257		GSM1867257	deep_0	3292421000	32924210	2016-01-06 15:50:16	1551694082	3292421000	32924210	1	32924210	index:0,count:32924210,average:100,stdev:0	GSM1867257_r1				in_mesa	26777276	5.13	2.96	0.06	2985565661	2960316422	2811797715	2812938216	99.15	100.04	0	0	0	0	0	0	68.29	72.56	33816927	20910515	33816927	20910515	64.61	66.17	33816927	19782420	33816927	19068656	699730890	23.44	3.16	0	5.48	0	0.28	0	0.35	0	0.00	0	6.36	0	30620195	0	100	0	97.57	0	2.60	0	0.01	0	2.35	0	0.02	0	464.81	0	0.32	0	1039332	0	32924210	0	1803049	0	93658	0	114895	0	0	0	2095462	0	4345	0	0	0	30048	0	3333032	0	23475	0	3390900	0	87.53	0	28817146	0	110583	3509682	31.737988660101	32924210.0	30620195.0	1039332.0	1803049.0	93658.0	114895.0	0.0	2095462.0	28817146.0	93.0	3.2	5.5	0.3	0.3	0.0	6.4	87.5	100	100	100.00	8	3292421000	27.0	23.1	23.3	26.5	0.0	35.6	20.0	bulk
1741672	SRR2229936	SRP056666	SRS1052832	SRX1178481	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867264: ca3v_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA3 pyramidal cells|location;;CA3|source_name;;Ventral CA3 pyramidal cells	GEO Accession;;GSM1867264		GSM1867264	ca3v_1	4371547305	47005885	2016-01-06 15:50:16	2234710388	4371547305	47005885	1	47005885	index:0,count:47005885,average:93,stdev:0	GSM1867264_r1				in_mesa	26777276	9.32	3.12	0.06	3989176293	3979265414	3690790824	3725259250	99.75	100.93	0	0	0	0	0	0	77.42	83.74	49805029	34106653	49805029	34106653	73.83	76.62	49805029	32525473	49805029	31204143	514725363	12.90	3.34	0	7.08	0	0.31	0	0.26	0	0.00	0	5.71	0	44055016	0	93	0	90.62	0	2.77	0	0.01	0	1.31	0	0.01	0	441.83	0	0.44	0	1570128	0	47005885	0	3328166	0	147080	0	122066	0	0	0	2681723	0	6205	0	0	0	44145	0	4748351	0	29873	0	4828574	0	86.64	0	40726850	0	137726	4906629	35.626018326242	47005885.0	44055016.0	1570128.0	3328166.0	147080.0	122066.0	0.0	2681723.0	40726850.0	93.7	3.3	7.1	0.3	0.3	0.0	5.7	86.6	93	93	93.00	8	4371547305	27.2	23.1	23.3	26.4	0.0	34.0	17.7	bulk
1741688	SRR2229937	SRP056666	SRS1052831	SRX1178482	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867265: ca3v_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA3 pyramidal cells|location;;CA3|source_name;;Ventral CA3 pyramidal cells	GEO Accession;;GSM1867265		GSM1867265	ca3v_2	5067517455	54489435	2016-01-06 15:50:16	2592842981	5067517455	54489435	1	54489435	index:0,count:54489435,average:93,stdev:0	GSM1867265_r1				in_mesa	26777276	11.69	3.05	0.06	4645513348	4617303168	4327737118	4345174537	99.39	100.4	0	0	0	0	0	0	78.26	84.07	57146269	40035729	57146269	40035729	75.47	77.81	57146269	38604532	57146269	37054082	579455360	12.47	3.18	0	6.49	0	0.29	0	0.24	0	0.00	0	5.58	0	51155319	0	93	0	90.88	0	2.45	0	0.01	0	1.31	0	0.01	0	514.86	0	0.43	0	1731922	0	54489435	0	3533736	0	160375	0	132498	0	0	0	3041243	0	7469	0	0	0	47778	0	5399334	0	32047	0	5486628	0	87.40	0	47621583	0	142269	5587257	39.272483815870	54489435.0	51155319.0	1731922.0	3533736.0	160375.0	132498.0	0.0	3041243.0	47621583.0	93.9	3.2	6.5	0.3	0.2	0.0	5.6	87.4	93	93	93.00	8	5067517455	27.6	22.7	22.8	26.9	0.0	33.9	17.5	bulk
1741720	SRR2229939	SRP056666	SRS1052829	SRX1178484	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867267: sst_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;SST interneuron|location;;CA1|source_name;;SST interneurons	GEO Accession;;GSM1867267		GSM1867267	sst_1	3662609480	38553784	2016-01-06 15:50:16	2300346509	3662609480	38553784	1	38553784	index:0,count:38553784,average:95,stdev:0	GSM1867267_r1				in_mesa	26777276	8.4	2.79	0.06	3160910954	3200128676	2823027896	2920693198	101.24	103.46	0	0	0	0	0	0	78.79	88.31	40873800	26942575	40873800	26942575	73.17	77.36	40873800	25022832	40873800	23600795	258981361	8.19	3.59	0	9.57	0	0.33	0	0.28	0	0.00	0	10.69	0	34197247	0	95	0	92.53	0	3.67	0	0.03	0	1.26	0	0.02	0	673.76	0	0.45	0	1383562	0	38553784	0	3689435	0	126304	0	109334	0	0	0	4120899	0	4285	0	0	0	29200	0	3410513	0	25743	0	3469741	0	79.13	0	30507812	0	128795	3554510	27.598198687837	38553784.0	34197247.0	1383562.0	3689435.0	126304.0	109334.0	0.0	4120899.0	30507812.0	88.7	3.6	9.6	0.3	0.3	0.0	10.7	79.1	95	95	95.00	38	3662609480	25.8	24.2	24.2	25.8	0.0	36.3	20.1	bulk
1741848	SRR2229941	SRP056666	SRS1052827	SRX1178486	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867270: pv_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;PV interneuron|location;;CA1|source_name;;PV interneurons	GEO Accession;;GSM1867270		GSM1867270	pv_0	5264918145	55420191	2016-01-06 15:50:16	2472287127	5264918145	55420191	1	55420191	index:0,count:55420191,average:95,stdev:0	GSM1867270_r1				in_mesa	26777276	13.9	2.36	0.08	4558462608	4567163642	4150894506	4236720551	100.19	102.07	0	0	0	0	0	0	73.27	80.54	56967310	36136845	56967310	36136845	68.71	71.38	56967310	33890158	56967310	32024669	698344504	15.32	3.91	0	8.04	0	0.31	0	0.41	0	0.00	0	10.28	0	49322550	0	95	0	92.52	0	3.76	0	0.04	0	1.26	0	0.02	0	475.03	0	0.39	0	2165608	0	55420191	0	4455822	0	174228	0	226133	0	0	0	5697280	0	5560	0	0	0	32499	0	3725337	0	41790	0	3805186	0	80.96	0	44866728	0	107579	3899129	36.244332072245	55420191.0	49322550.0	2165608.0	4455822.0	174228.0	226133.0	0.0	5697280.0	44866728.0	89.0	3.9	8.0	0.3	0.4	0.0	10.3	81.0	95	95	95.00	8	5264918145	27.0	23.0	23.1	26.9	0.0	35.4	19.2	bulk
1741882	SRR2229943	SRP056666	SRS1052825	SRX1178488	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867273: pv_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;PV interneuron|location;;CA1|source_name;;PV interneurons	GEO Accession;;GSM1867273		GSM1867273	pv_2	4841535730	50963534	2016-01-06 15:50:16	2280130312	4841535730	50963534	1	50963534	index:0,count:50963534,average:95,stdev:0	GSM1867273_r1				in_mesa	26777276	12.51	2.66	0.08	4309677143	4303183834	3957875258	4006849121	99.85	101.24	0	0	0	0	0	0	71.75	78.19	53059681	33344436	53059681	33344436	67.9	70.44	53059681	31555189	53059681	30037059	772727609	17.93	3.39	0	7.52	0	0.32	0	0.37	0	0.00	0	8.12	0	46474012	0	95	0	92.81	0	2.89	0	0.02	0	1.41	0	0.01	0	528.73	0	0.39	0	1725492	0	50963534	0	3830369	0	162683	0	187792	0	0	0	4139047	0	4864	0	0	0	34946	0	3704960	0	34580	0	3779350	0	83.67	0	42643643	0	116930	3864648	33.050953561960	50963534.0	46474012.0	1725492.0	3830369.0	162683.0	187792.0	0.0	4139047.0	42643643.0	91.2	3.4	7.5	0.3	0.4	0.0	8.1	83.7	95	95	95.00	8	4841535730	27.2	22.9	22.9	27.0	0.0	35.4	19.4	bulk
1741897	SRR2229944	SRP056666	SRS1052824	SRX1178489	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867274: amyg_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 amygdala-projecting pyramidal cells|location;;CA1|source_name;;Ventral CA1 amygdala-projecting pyramidal cells	GEO Accession;;GSM1867274		GSM1867274	amyg_0	4254760020	40521524	2016-01-06 15:50:16	1949022752	4254760020	40521524	1	40521524	index:0,count:40521524,average:105,stdev:0	GSM1867274_r1				in_mesa	26777276	14.23	3.47	0.1	3689388725	3640210190	3486730624	3469739602	98.67	99.51	0	0	0	0	0	0	78.83	83.48	39621768	28679846	39621768	28679846	77.56	78.74	39621768	28219501	39621768	27053797	494689835	13.41	6.42	0	5.00	0	0.31	0	0.92	0	0.00	0	8.98	0	36382760	0	105	0	101.48	0	2.34	0	0.01	0	1.50	0	0.01	0	626.08	0	0.29	0	2599688	0	40521524	0	2025384	0	126481	0	374258	0	0	0	3638025	0	7918	0	0	0	38071	0	4074424	0	36130	0	4156543	0	84.79	0	34357376	0	103903	4331149	41.684542313504	40521524.0	36382760.0	2599688.0	2025384.0	126481.0	374258.0	0.0	3638025.0	34357376.0	89.8	6.4	5.0	0.3	0.9	0.0	9.0	84.8	105	105	105.00	7	4254760020	27.9	22.2	22.5	27.3	0.0	36.9	20.7	bulk
1741914	SRR2229945	SRP056666	SRS1052823	SRX1178490	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867276: amyg_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 amygdala-projecting pyramidal cells|location;;CA1|source_name;;Ventral CA1 amygdala-projecting pyramidal cells	GEO Accession;;GSM1867276		GSM1867276	amyg_1	3623131575	34506015	2016-01-06 15:50:16	1675949705	3623131575	34506015	1	34506015	index:0,count:34506015,average:105,stdev:0	GSM1867276_r1				in_mesa	26777276	9.35	2.84	0.12	3094075346	3089084572	2873881561	2897446203	99.84	100.82	0	0	0	0	0	0	69.59	75.01	34209772	21284721	34209772	21284721	65.12	66.98	34209772	19916699	34209772	19005961	636438151	20.57	6.03	0	6.41	0	0.30	0	0.86	0	0.00	0	10.20	0	30586716	0	105	0	101.28	0	3.37	0	0.03	0	2.43	0	0.03	0	528.60	0	0.37	0	2081405	0	34506015	0	2210617	0	104844	0	296274	0	0	0	3518181	0	5598	0	0	0	25355	0	3037971	0	33397	0	3102321	0	82.24	0	28376099	0	91518	3227246	35.263511003300	34506015.0	30586716.0	2081405.0	2210617.0	104844.0	296274.0	0.0	3518181.0	28376099.0	88.6	6.0	6.4	0.3	0.9	0.0	10.2	82.2	105	105	105.00	7	3623131575	26.7	23.5	23.8	26.0	0.0	36.7	20.4	bulk
1741931	SRR2229946	SRP056666	SRS1052822	SRX1178491	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867278: amyg_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 amygdala-projecting pyramidal cells|location;;CA1|source_name;;Ventral CA1 amygdala-projecting pyramidal cells	GEO Accession;;GSM1867278		GSM1867278	amyg_2	4980277680	47431216	2016-01-06 15:50:16	2287747916	4980277680	47431216	1	47431216	index:0,count:47431216,average:105,stdev:0	GSM1867278_r1				in_mesa	26777276	10.57	3.06	0.09	4292376709	4281651552	4028053439	4061539049	99.75	100.83	0	0	0	0	0	0	70.38	75.07	46745793	29839068	46745793	29839068	66.77	68.09	46745793	28308799	46745793	27065614	906931187	21.13	6.54	0	5.59	0	0.31	0	0.75	0	0.00	0	9.55	0	42399322	0	105	0	101.34	0	3.00	0	0.02	0	1.65	0	0.02	0	448.17	0	0.32	0	3104232	0	47431216	0	2650690	0	147049	0	357387	0	0	0	4527458	0	7126	0	0	0	37819	0	4165760	0	44300	0	4255005	0	83.80	0	39748632	0	101690	4427951	43.543622775101	47431216.0	42399322.0	3104232.0	2650690.0	147049.0	357387.0	0.0	4527458.0	39748632.0	89.4	6.5	5.6	0.3	0.8	0.0	9.5	83.8	105	105	105.00	7	4980277680	27.2	22.9	23.1	26.7	0.0	36.8	20.5	bulk
1741945	SRR2229947	SRP056666	SRS1052821	SRX1178492	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867279: nac_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 nucleus accumbens-projecting pyramidal cells|location;;CA1|source_name;;Ventral CA1 nucleus accumbens-projecting pyramidal cells	GEO Accession;;GSM1867279		GSM1867279	nac_0	4249636860	40472732	2016-01-06 15:50:16	1951081264	4249636860	40472732	1	40472732	index:0,count:40472732,average:105,stdev:0	GSM1867279_r1				in_mesa	26777276	9.06	3.18	0.1	3622690484	3630964300	3381388900	3426687400	100.23	101.34	0	0	0	0	0	0	72.35	77.6	39854587	25910797	39854587	25910797	67.74	69.53	39854587	24257423	39854587	23215682	669787581	18.49	6.54	0	5.98	0	0.33	0	1.02	0	0.00	0	10.16	0	35812105	0	105	0	101.26	0	3.37	0	0.03	0	2.07	0	0.02	0	488.93	0	0.35	0	2645100	0	40472732	0	2420504	0	132835	0	414770	0	0	0	4113022	0	7892	0	0	0	33498	0	3735467	0	40019	0	3816876	0	82.50	0	33391601	0	104891	3966835	37.818640302791	40472732.0	35812105.0	2645100.0	2420504.0	132835.0	414770.0	0.0	4113022.0	33391601.0	88.5	6.5	6.0	0.3	1.0	0.0	10.2	82.5	105	105	105.00	7	4249636860	26.9	23.3	23.5	26.3	0.0	36.8	20.5	bulk
1741963	SRR2229948	SRP056666	SRS1052820	SRX1178493	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867281: nac_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 nucleus accumbens-projecting pyramidal cells|location;;CA1|source_name;;Ventral CA1 nucleus accumbens-projecting pyramidal cells	GEO Accession;;GSM1867281		GSM1867281	nac_1	3711764805	35350141	2016-01-06 15:50:16	1701318633	3711764805	35350141	1	35350141	index:0,count:35350141,average:105,stdev:0	GSM1867281_r1				in_mesa	26777276	8.94	3.34	0.15	3189351226	3095066657	3054937307	2986720496	97.04	97.77	0	0	0	0	0	0	62.28	65.07	33800112	19621101	33800112	19621101	61.35	61.72	33800112	19326648	33800112	18612120	981561514	30.78	6.81	0	3.82	0	0.30	0	1.50	0	0.00	0	9.08	0	31503023	0	105	0	101.31	0	1.84	0	0.01	0	1.33	0	0.01	0	400.19	0	0.30	0	2408911	0	35350141	0	1349296	0	107199	0	530091	0	0	0	3209828	0	3298	0	0	0	24563	0	2760637	0	36273	0	2824771	0	85.30	0	30153727	0	87315	2934413	33.607203802325	35350141.0	31503023.0	2408911.0	1349296.0	107199.0	530091.0	0.0	3209828.0	30153727.0	89.1	6.8	3.8	0.3	1.5	0.0	9.1	85.3	105	105	105.00	7	3711764805	28.5	21.6	22.0	27.9	0.0	36.9	20.6	bulk
1741979	SRR2229949	SRP056666	SRS1052819	SRX1178494	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867282: nac_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 nucleus accumbens-projecting pyramidal cells|location;;CA1|source_name;;Ventral CA1 nucleus accumbens-projecting pyramidal cells	GEO Accession;;GSM1867282		GSM1867282	nac_2	4703212920	44792504	2016-01-06 15:50:16	2159799115	4703212920	44792504	1	44792504	index:0,count:44792504,average:105,stdev:0	GSM1867282_r1				in_mesa	26777276	8.92	2.95	0.09	4035637075	3995348080	3782169022	3778847587	99.0	99.91	0	0	0	0	0	0	63.81	68.16	44110310	25437540	44110310	25437540	59.98	61.22	44110310	23910399	44110310	22849439	1088039070	26.96	6.32	0	5.68	0	0.33	0	1.01	0	0.00	0	9.66	0	39866984	0	105	0	101.34	0	2.95	0	0.02	0	2.38	0	0.02	0	411.36	0	0.35	0	2830119	0	44792504	0	2545501	0	146919	0	451788	0	0	0	4326813	0	6240	0	0	0	30496	0	3586834	0	46442	0	3670012	0	83.32	0	37321483	0	91533	3817141	41.702347787137	44792504.0	39866984.0	2830119.0	2545501.0	146919.0	451788.0	0.0	4326813.0	37321483.0	89.0	6.3	5.7	0.3	1.0	0.0	9.7	83.3	105	105	105.00	7	4703212920	27.0	23.1	23.3	26.5	0.0	36.8	20.5	bulk
1742089	SRR2229950	SRP056666	SRS1052818	SRX1178495	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867284: post_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA1 postsubiculum-projecting pyramidal cells|location;;CA1|source_name;;Dorsal CA1 postsubiculum-projecting pyramidal cells	GEO Accession;;GSM1867284		GSM1867284	post_0	4508965125	42942525	2016-01-06 15:50:16	2042226401	4508965125	42942525	1	42942525	index:0,count:42942525,average:105,stdev:0	GSM1867284_r1				in_mesa	26777276	7.42	3.48	0.14	3969088122	3832224894	3840671228	3729361200	96.55	97.1	0	0	0	0	0	0	58.77	60.77	41247271	22972427	41247271	22972427	58.38	58.45	41247271	22820630	41247271	22096363	1396622328	35.19	6.53	0	2.99	0	0.27	0	0.80	0	0.00	0	7.92	0	39086687	0	105	0	101.60	0	1.38	0	0.01	0	1.24	0	0.01	0	503.56	0	0.29	0	2805779	0	42942525	0	1283717	0	114004	0	342148	0	0	0	3399686	0	3299	0	0	0	29816	0	3106633	0	41519	0	3181267	0	88.03	0	37802970	0	98529	3280111	33.290817931776	42942525.0	39086687.0	2805779.0	1283717.0	114004.0	342148.0	0.0	3399686.0	37802970.0	91.0	6.5	3.0	0.3	0.8	0.0	7.9	88.0	105	105	105.00	7	4508965125	28.7	21.4	21.8	28.1	0.0	37.1	21.0	bulk
1742105	SRR2229951	SRP056666	SRS1052817	SRX1178496	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867286: post_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA1 postsubiculum-projecting pyramidal cells|location;;CA1|source_name;;Dorsal CA1 postsubiculum-projecting pyramidal cells	GEO Accession;;GSM1867286		GSM1867286	post_1	3534090105	33658001	2016-01-06 15:50:16	1601840863	3534090105	33658001	1	33658001	index:0,count:33658001,average:105,stdev:0	GSM1867286_r1				in_mesa	26777276	7.43	3.44	0.12	3103111323	2996612623	3002148988	2915480230	96.57	97.11	0	0	0	0	0	0	59.34	61.36	32313532	18159547	32313532	18159547	58.98	59.05	32313532	18049467	32313532	17476059	1074168137	34.62	6.60	0	3.01	0	0.27	0	0.72	0	0.00	0	8.08	0	30604408	0	105	0	101.45	0	1.38	0	0.01	0	1.24	0	0.01	0	419.27	0	0.29	0	2221884	0	33658001	0	1011473	0	91334	0	242733	0	0	0	2719526	0	3007	0	0	0	23806	0	2462785	0	32137	0	2521735	0	87.92	0	29592935	0	97068	2597099	26.755460089834	33658001.0	30604408.0	2221884.0	1011473.0	91334.0	242733.0	0.0	2719526.0	29592935.0	90.9	6.6	3.0	0.3	0.7	0.0	8.1	87.9	105	105	105.00	7	3534090105	28.7	21.4	21.7	28.1	0.0	37.1	21.1	bulk
1742121	SRR2229952	SRP056666	SRS1052816	SRX1178497	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867287: post_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA1 postsubiculum-projecting pyramidal cells|location;;CA1|source_name;;Dorsal CA1 postsubiculum-projecting pyramidal cells	GEO Accession;;GSM1867287		GSM1867287	post_2	3983612745	37939169	2016-01-06 15:50:16	1803300271	3983612745	37939169	1	37939169	index:0,count:37939169,average:105,stdev:0	GSM1867287_r1				in_mesa	26777276	6.35	3.39	0.13	3505586483	3387044415	3393708298	3297505626	96.62	97.17	0	0	0	0	0	0	59.52	61.52	36464275	20575403	36464275	20575403	59.05	59.15	36464275	20411566	36464275	19783369	1209009327	34.49	6.42	0	2.95	0	0.27	0	0.72	0	0.00	0	7.89	0	34567331	0	105	0	101.46	0	1.39	0	0.01	0	1.25	0	0.01	0	588.71	0	0.28	0	2436227	0	37939169	0	1120071	0	102648	0	273981	0	0	0	2995209	0	3401	0	0	0	26952	0	2892686	0	35942	0	2958981	0	88.16	0	33447260	0	104823	3047800	29.075679955735	37939169.0	34567331.0	2436227.0	1120071.0	102648.0	273981.0	0.0	2995209.0	33447260.0	91.1	6.4	3.0	0.3	0.7	0.0	7.9	88.2	105	105	105.00	7	3983612745	28.6	21.5	21.8	28.0	0.0	37.1	21.1	bulk
1742137	SRR2229953	SRP056666	SRS1052815	SRX1178498	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867289: dgd_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal DG granule cells|location;;DG|source_name;;Dorsal DG granule cells	GEO Accession;;GSM1867289		GSM1867289	dgd_0	3286556216	34963364	2016-01-06 15:50:16	1601660456	3286556216	34963364	1	34963364	index:0,count:34963364,average:94,stdev:0	GSM1867289_r1				in_mesa	26777276	10.67	2.93	0.09	2982697179	2937671753	2844524193	2823844873	98.49	99.27	0	0	0	0	0	0	57.17	59.98	35150360	18574229	35150360	18574229	54.77	55.32	35150360	17794683	35150360	17131685	1072796279	35.97	3.91	0	4.35	0	0.27	0	0.43	0	0.00	0	6.38	0	32488264	0	94	0	91.86	0	2.45	0	0.01	0	1.27	0	0.01	0	673.09	0	0.35	0	1365469	0	34963364	0	1522400	0	95066	0	150663	0	0	0	2229371	0	3467	0	0	0	17986	0	2032292	0	23188	0	2076933	0	88.57	0	30965864	0	111993	2107193	18.815399176734	34963364.0	32488264.0	1365469.0	1522400.0	95066.0	150663.0	0.0	2229371.0	30965864.0	92.9	3.9	4.4	0.3	0.4	0.0	6.4	88.6	94	94	94.00	8	3286556216	28.4	21.8	21.9	27.8	0.0	35.2	19.1	bulk
1742168	SRR2229955	SRP056666	SRS1052813	SRX1178500	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867293: dgd_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal DG granule cells|location;;DG|source_name;;Dorsal DG granule cells	GEO Accession;;GSM1867293		GSM1867293	dgd_2	3253505534	34611761	2016-01-06 15:50:16	1589194956	3253505534	34611761	1	34611761	index:0,count:34611761,average:94,stdev:0	GSM1867293_r1				in_mesa	26777276	10.94	2.98	0.09	2951209954	2919599267	2792179211	2785188912	98.93	99.75	0	0	0	0	0	0	62.03	65.61	35081176	19926546	35081176	19926546	59.33	60.33	35081176	19058022	35081176	18323256	900259659	30.50	3.64	0	5.06	0	0.27	0	0.36	0	0.00	0	6.56	0	32121490	0	94	0	91.93	0	2.66	0	0.02	0	1.32	0	0.01	0	471.98	0	0.36	0	1258670	0	34611761	0	1749803	0	94653	0	124776	0	0	0	2270842	0	3793	0	0	0	19517	0	2281858	0	21667	0	2326835	0	87.75	0	30371687	0	116552	2369016	20.325828814606	34611761.0	32121490.0	1258670.0	1749803.0	94653.0	124776.0	0.0	2270842.0	30371687.0	92.8	3.6	5.1	0.3	0.4	0.0	6.6	87.7	94	94	94.00	8	3253505534	28.1	22.2	22.3	27.5	0.0	35.0	18.7	bulk
1742184	SRR2229956	SRP056666	SRS1052812	SRX1178501	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867296: dgv_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral DG granule cells|location;;DG|source_name;;Ventral DG granule cells	GEO Accession;;GSM1867296		GSM1867296	dgv_0	2016456400	20164564	2016-01-06 15:50:16	939134131	2016456400	20164564	1	20164564	index:0,count:20164564,average:100,stdev:0	GSM1867296_r1				in_mesa	26777276	9.1	2.6	0.1	1740596681	1731463562	1636129238	1635908412	99.48	99.99	0	0	0	0	0	0	64.63	68.82	19860075	11592877	19860075	11592877	60.57	61.95	19860075	10865706	19860075	10435355	454360870	26.10	5.03	0	5.41	0	0.29	0	0.40	0	0.00	0	10.35	0	17937768	0	100	0	97.12	0	2.72	0	0.02	0	1.90	0	0.01	0	392.39	0	0.49	0	1014865	0	20164564	0	1091876	0	57753	0	81287	0	0	0	2087756	0	2518	0	0	0	13668	0	1555581	0	17695	0	1589462	0	83.54	0	16845892	0	80050	1652193	20.639512804497	20164564.0	17937768.0	1014865.0	1091876.0	57753.0	81287.0	0.0	2087756.0	16845892.0	89.0	5.0	5.4	0.3	0.4	0.0	10.4	83.5	100	100	100.00	8	2016456400	27.0	23.3	23.3	26.4	0.0	35.2	18.1	bulk
1742200	SRR2229957	SRP056666	SRS1052811	SRX1178502	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867298: dgv_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral DG granule cells|location;;DG|source_name;;Ventral DG granule cells	GEO Accession;;GSM1867298		GSM1867298	dgv_1	1926723700	19267237	2016-01-06 15:50:16	898284223	1926723700	19267237	1	19267237	index:0,count:19267237,average:100,stdev:0	GSM1867298_r1				in_mesa	26777276	7.55	2.7	0.07	1657186602	1645330246	1562780215	1565755189	99.28	100.19	0	0	0	0	0	0	60.99	64.72	18888924	10424575	18888924	10424575	56.76	57.8	18888924	9702638	18888924	9310438	503720726	30.40	5.55	0	5.12	0	0.28	0	0.46	0	0.00	0	10.55	0	17093505	0	100	0	97.03	0	2.95	0	0.02	0	1.55	0	0.01	0	394.10	0	0.48	0	1068673	0	19267237	0	986560	0	53127	0	87740	0	0	0	2032865	0	1890	0	0	0	11981	0	1307354	0	18037	0	1339262	0	83.60	0	16106945	0	79055	1395830	17.656441717791	19267237.0	17093505.0	1068673.0	986560.0	53127.0	87740.0	0.0	2032865.0	16106945.0	88.7	5.5	5.1	0.3	0.5	0.0	10.6	83.6	100	100	100.00	8	1926723700	27.1	23.2	23.2	26.6	0.0	35.3	18.4	bulk
1742216	SRR2229958	SRP056666	SRS1052810	SRX1178503	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867300: dgv_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral DG granule cells|location;;DG|source_name;;Ventral DG granule cells	GEO Accession;;GSM1867300		GSM1867300	dgv_2	1966512000	19665120	2016-01-06 15:50:16	914683542	1966512000	19665120	1	19665120	index:0,count:19665120,average:100,stdev:0	GSM1867300_r1				in_mesa	26777276	7.35	2.7	0.07	1687291635	1672291745	1590623695	1589868708	99.11	99.95	0	0	0	0	0	0	61.09	64.86	19266839	10641172	19266839	10641172	57.18	58.21	19266839	9960159	19266839	9549914	510706343	30.27	5.55	0	5.14	0	0.27	0	0.43	0	0.00	0	10.72	0	17418904	0	100	0	96.95	0	2.87	0	0.02	0	1.59	0	0.01	0	498.55	0	0.49	0	1090871	0	19665120	0	1011737	0	52649	0	84750	0	0	0	2108817	0	2338	0	0	0	12091	0	1367341	0	19328	0	1401098	0	83.43	0	16407167	0	75431	1458040	19.329453407750	19665120.0	17418904.0	1090871.0	1011737.0	52649.0	84750.0	0.0	2108817.0	16407167.0	88.6	5.5	5.1	0.3	0.4	0.0	10.7	83.4	100	100	100.00	8	1966512000	27.0	23.2	23.3	26.5	0.0	35.3	18.4	bulk
870542	SRR2229911	SRP056666	SRS1052857	SRX1178456	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867239: dorsal_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA1 pyramidal cells|location;;CA1|source_name;;Dorsal CA1 pyramidal cells	GEO Accession;;GSM1867239		GSM1867239	dorsal_0	4639956465	49892005	2016-01-06 15:50:16	2377398879	4639956465	49892005	1	49892005	index:0,count:49892005,average:93,stdev:0	GSM1867239_r1				in_mesa	26777276	5.86	3.03	0.07	4252979800	4238679847	3961566835	3989572957	99.66	100.71	0	0	0	0	0	0	73.29	78.74	52329117	34307446	52329117	34307446	69.37	71.75	52329117	32473275	52329117	31263087	746771291	17.56	3.28	0	6.49	0	0.29	0	0.27	0	0.00	0	5.61	0	46811554	0	93	0	90.92	0	2.72	0	0.01	0	1.28	0	0.01	0	594.74	0	0.45	0	1636490	0	49892005	0	3238603	0	144990	0	134191	0	0	0	2801270	0	5484	0	0	0	43592	0	4965554	0	32710	0	5047340	0	87.33	0	43572951	0	132872	5127972	38.593322897224	49892005.0	46811554.0	1636490.0	3238603.0	144990.0	134191.0	0.0	2801270.0	43572951.0	93.8	3.3	6.5	0.3	0.3	0.0	5.6	87.3	93	93	93.00	8	4639956465	27.2	23.1	23.2	26.5	0.0	33.8	17.4	bulk
870550	SRR2229912	SRP056666	SRS1052856	SRX1178457	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867240: dorsal_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA1 pyramidal cells|location;;CA1|source_name;;Dorsal CA1 pyramidal cells	GEO Accession;;GSM1867240		GSM1867240	dorsal_1	5247843432	56428424	2016-01-06 15:50:16	2692916528	5247843432	56428424	1	56428424	index:0,count:56428424,average:93,stdev:0	GSM1867240_r1				in_mesa	26777276	6.14	3.08	0.07	4823397778	4798685298	4487363225	4505326195	99.49	100.4	0	0	0	0	0	0	74.46	80.1	59350713	39500474	59350713	39500474	71.0	73.45	59350713	37662784	59350713	36222432	783429658	16.24	2.98	0	6.61	0	0.29	0	0.26	0	0.00	0	5.44	0	53047694	0	93	0	90.99	0	2.63	0	0.01	0	1.28	0	0.01	0	610.04	0	0.46	0	1683398	0	56428424	0	3732563	0	164122	0	145717	0	0	0	3070891	0	5948	0	0	0	50344	0	5831808	0	34959	0	5923059	0	87.39	0	49315131	0	134126	6021509	44.894420172077	56428424.0	53047694.0	1683398.0	3732563.0	164122.0	145717.0	0.0	3070891.0	49315131.0	94.0	3.0	6.6	0.3	0.3	0.0	5.4	87.4	93	93	93.00	8	5247843432	27.1	23.2	23.3	26.4	0.0	33.7	17.2	bulk
870557	SRR2229913	SRP056666	SRS1052855	SRX1178458	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867241: dorsal_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA1 pyramidal cells|location;;CA1|source_name;;Dorsal CA1 pyramidal cells	GEO Accession;;GSM1867241		GSM1867241	dorsal_2	4227877092	45461044	2016-01-06 15:50:16	2169524415	4227877092	45461044	1	45461044	index:0,count:45461044,average:93,stdev:0	GSM1867241_r1				in_mesa	26777276	5.55	2.98	0.08	3880168955	3855190886	3638284463	3648210280	99.36	100.27	0	0	0	0	0	0	69.58	74.26	47340118	29732151	47340118	29732151	66.14	68.0	47340118	28263070	47340118	27224284	846158281	21.81	3.23	0	5.92	0	0.29	0	0.33	0	0.00	0	5.39	0	42729323	0	93	0	90.87	0	2.47	0	0.01	0	1.26	0	0.01	0	531.36	0	0.44	0	1470193	0	45461044	0	2691605	0	132071	0	150327	0	0	0	2449323	0	4883	0	0	0	37620	0	4265253	0	29118	0	4336874	0	88.07	0	40037718	0	120873	4414350	36.520562904867	45461044.0	42729323.0	1470193.0	2691605.0	132071.0	150327.0	0.0	2449323.0	40037718.0	94.0	3.2	5.9	0.3	0.3	0.0	5.4	88.1	93	93	93.00	8	4227877092	27.5	22.9	23.0	26.7	0.0	33.9	17.5	bulk
870564	SRR2229914	SRP056666	SRS1052854	SRX1178459	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867242: intermediate_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Intermediate CA1 pyramidal cells|location;;CA1|source_name;;Intermediate CA1 pyramidal cells	GEO Accession;;GSM1867242		GSM1867242	intermediate_0	1248571400	12485714	2016-01-06 15:50:16	559220773	1248571400	12485714	1	12485714	index:0,count:12485714,average:100,stdev:0	GSM1867242_r1				in_mesa	26777276	6.36	3.18	0.04	1110705175	1109050826	1038570023	1046191998	99.85	100.73	0	0	0	0	0	0	80.48	86.16	12695087	9190104	12695087	9190104	76.91	79.37	12695087	8782382	12695087	8465787	117282120	10.56	3.52	0	6.02	0	0.24	0	0.28	0	0.00	0	8.03	0	11418427	0	100	0	97.37	0	2.54	0	0.02	0	2.56	0	0.02	0	548.15	0	0.36	0	439500	0	12485714	0	751823	0	29867	0	35079	0	0	0	1002341	0	1808	0	0	0	13706	0	1498205	0	9121	0	1522840	0	85.43	0	10666604	0	100923	1568573	15.542274803563	12485714.0	11418427.0	439500.0	751823.0	29867.0	35079.0	0.0	1002341.0	10666604.0	91.5	3.5	6.0	0.2	0.3	0.0	8.0	85.4	100	100	100.00	8	1248571400	26.9	23.4	23.4	26.3	0.0	36.1	20.6	bulk
870573	SRR2229915	SRP056666	SRS1052853	SRX1178460	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867243: intermediate_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Intermediate CA1 pyramidal cells|location;;CA1|source_name;;Intermediate CA1 pyramidal cells	GEO Accession;;GSM1867243		GSM1867243	intermediate_1	1918987400	19189874	2016-01-06 15:50:16	857397334	1918987400	19189874	1	19189874	index:0,count:19189874,average:100,stdev:0	GSM1867243_r1				in_mesa	26777276	6.22	3.34	0.06	1723844906	1715148728	1619957723	1625433293	99.5	100.34	0	0	0	0	0	0	80.28	85.5	19562248	14213562	19562248	14213562	77.39	79.54	19562248	13701619	19562248	13222516	195966720	11.37	3.58	0	5.63	0	0.23	0	0.31	0	0.00	0	7.19	0	17705392	0	100	0	97.45	0	2.30	0	0.01	0	2.42	0	0.02	0	727.20	0	0.34	0	686216	0	19189874	0	1081190	0	44771	0	59982	0	0	0	1379729	0	2777	0	0	0	20427	0	2259645	0	13862	0	2296711	0	86.63	0	16624202	0	106007	2374383	22.398360485628	19189874.0	17705392.0	686216.0	1081190.0	44771.0	59982.0	0.0	1379729.0	16624202.0	92.3	3.6	5.6	0.2	0.3	0.0	7.2	86.6	100	100	100.00	8	1918987400	27.2	23.0	23.0	26.7	0.0	36.2	21.0	bulk
870581	SRR2229916	SRP056666	SRS1052852	SRX1178461	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867244: intermediate_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Intermediate CA1 pyramidal cells|location;;CA1|source_name;;Intermediate CA1 pyramidal cells	GEO Accession;;GSM1867244		GSM1867244	intermediate_2	1554326600	15543266	2016-01-06 15:50:16	683740608	1554326600	15543266	1	15543266	index:0,count:15543266,average:100,stdev:0	GSM1867244_r1				in_mesa	26777276	7.25	3.36	0.07	1404477096	1393489935	1327359660	1326309368	99.22	99.92	0	0	0	0	0	0	79.3	83.98	15820050	11437926	15820050	11437926	76.76	78.57	15820050	11071815	15820050	10700778	178299046	12.70	3.69	0	5.17	0	0.27	0	0.32	0	0.00	0	6.61	0	14424046	0	100	0	97.46	0	1.92	0	0.01	0	2.46	0	0.01	0	513.36	0	0.31	0	573532	0	15543266	0	804221	0	42659	0	49701	0	0	0	1026860	0	2177	0	0	0	17634	0	1879699	0	11878	0	1911388	0	87.63	0	13619825	0	104553	1970123	18.843294788289	15543266.0	14424046.0	573532.0	804221.0	42659.0	49701.0	0.0	1026860.0	13619825.0	92.8	3.7	5.2	0.3	0.3	0.0	6.6	87.6	100	100	100.00	8	1554326600	27.4	22.7	22.9	27.0	0.0	36.5	21.7	bulk
870590	SRR2229917	SRP056666	SRS1052851	SRX1178462	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867245: ventral_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 pyramidal cells|location;;CA1|source_name;;Ventral CA1 pyramidal cells	GEO Accession;;GSM1867245		GSM1867245	ventral_0	1659119600	16591196	2016-01-06 15:50:16	741854678	1659119600	16591196	1	16591196	index:0,count:16591196,average:100,stdev:0	GSM1867245_r1				in_mesa	26777276	6.44	3.0	0.06	1493442794	1484797524	1412540493	1415265503	99.42	100.19	0	0	0	0	0	0	71.26	75.4	16854872	10929357	16854872	10929357	68.13	69.69	16854872	10449221	16854872	10102225	315927078	21.15	3.77	0	5.08	0	0.27	0	0.31	0	0.00	0	6.98	0	15337597	0	100	0	97.45	0	2.17	0	0.01	0	2.43	0	0.02	0	519.38	0	0.34	0	625705	0	16591196	0	842489	0	44179	0	51183	0	0	0	1158237	0	2089	0	0	0	15157	0	1636015	0	12156	0	1665417	0	87.37	0	14495108	0	98238	1725449	17.563967100307	16591196.0	15337597.0	625705.0	842489.0	44179.0	51183.0	0.0	1158237.0	14495108.0	92.4	3.8	5.1	0.3	0.3	0.0	7.0	87.4	100	100	100.00	8	1659119600	27.3	22.9	23.0	26.8	0.0	36.2	21.1	bulk
870597	SRR2229918	SRP056666	SRS1052850	SRX1178463	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867246: ventral_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 pyramidal cells|location;;CA1|source_name;;Ventral CA1 pyramidal cells	GEO Accession;;GSM1867246		GSM1867246	ventral_1	1017452900	10174529	2016-01-06 15:50:16	442654960	1017452900	10174529	1	10174529	index:0,count:10174529,average:100,stdev:0	GSM1867246_r1				in_mesa	26777276	7.22	3.07	0.07	916291726	913828266	860329109	865563350	99.73	100.61	0	0	0	0	0	0	74.77	79.71	10435390	7039124	10435390	7039124	71.3	73.28	10435390	6712568	10435390	6471080	154387817	16.85	3.65	0	5.73	0	0.26	0	0.33	0	0.00	0	6.88	0	9414170	0	100	0	97.42	0	2.37	0	0.01	0	2.52	0	0.02	0	732.57	0	0.33	0	370869	0	10174529	0	583205	0	26581	0	33444	0	0	0	700334	0	1539	0	0	0	10381	0	1121161	0	7716	0	1140797	0	86.79	0	8830965	0	96996	1177209	12.136675739206	10174529.0	9414170.0	370869.0	583205.0	26581.0	33444.0	0.0	700334.0	8830965.0	92.5	3.6	5.7	0.3	0.3	0.0	6.9	86.8	100	100	100.00	8	1017452900	27.1	23.1	23.2	26.7	0.0	36.6	21.6	bulk
870607	SRR2229919	SRP056666	SRS1052849	SRX1178464	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867247: ventral_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA1 pyramidal cells|location;;CA1|source_name;;Ventral CA1 pyramidal cells	GEO Accession;;GSM1867247		GSM1867247	ventral_2	1542929300	15429293	2016-01-06 15:50:16	690282479	1542929300	15429293	1	15429293	index:0,count:15429293,average:100,stdev:0	GSM1867247_r1				in_mesa	26777276	8.61	3.16	0.06	1384125946	1383328762	1289432293	1301299306	99.94	100.92	0	0	0	0	0	0	79.68	85.61	15889628	11329324	15889628	11329324	76.2	78.72	15889628	10834769	15889628	10417054	156511920	11.31	3.52	0	6.39	0	0.27	0	0.30	0	0.00	0	7.28	0	14218627	0	100	0	97.44	0	2.54	0	0.01	0	2.54	0	0.02	0	375.31	0	0.36	0	542981	0	15429293	0	985227	0	41952	0	45949	0	0	0	1122765	0	2393	0	0	0	16012	0	1772340	0	10349	0	1801094	0	85.77	0	13233400	0	110012	1861475	16.920654110461	15429293.0	14218627.0	542981.0	985227.0	41952.0	45949.0	0.0	1122765.0	13233400.0	92.2	3.5	6.4	0.3	0.3	0.0	7.3	85.8	100	100	100.00	8	1542929300	27.0	23.3	23.3	26.4	0.0	36.1	20.7	bulk
870662	SRR2229920	SRP056666	SRS1052848	SRX1178465	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867248: proximal_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Proximal CA1 pyramidal cells|location;;CA1|source_name;;Proximal CA1 pyramidal cells	GEO Accession;;GSM1867248		GSM1867248	proximal_0	4295715415	45218057	2016-01-06 15:50:16	2025395057	4295715415	45218057	1	45218057	index:0,count:45218057,average:95,stdev:0	GSM1867248_r1				in_mesa	26777276	4.99	2.83	0.08	3803901981	3827250912	3524087954	3593476664	100.61	101.97	0	0	0	0	0	0	71.7	77.46	46563897	29518441	46563897	29518441	66.82	69.15	46563897	27507866	46563897	26352322	715654094	18.81	4.55	0	6.77	0	0.33	0	0.34	0	0.00	0	8.28	0	41168982	0	95	0	92.48	0	3.28	0	0.03	0	1.28	0	0.01	0	410.04	0	0.41	0	2056187	0	45218057	0	3062248	0	151344	0	153435	0	0	0	3744296	0	5069	0	0	0	30066	0	3675879	0	35359	0	3746373	0	84.27	0	38106734	0	109859	3824672	34.814371148472	45218057.0	41168982.0	2056187.0	3062248.0	151344.0	153435.0	0.0	3744296.0	38106734.0	91.0	4.5	6.8	0.3	0.3	0.0	8.3	84.3	95	95	95.00	8	4295715415	26.4	23.6	23.7	26.2	0.0	35.4	19.2	bulk
870671	SRR2229921	SRP056666	SRS1052847	SRX1178466	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867249: proximal_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Proximal CA1 pyramidal cells|location;;CA1|source_name;;Proximal CA1 pyramidal cells	GEO Accession;;GSM1867249		GSM1867249	proximal_1	3783038795	39821461	2016-01-06 15:50:16	1788858079	3783038795	39821461	1	39821461	index:0,count:39821461,average:95,stdev:0	GSM1867249_r1				in_mesa	26777276	5.1	2.94	0.06	3367570527	3378992792	3105752308	3158592767	100.34	101.7	0	0	0	0	0	0	73.84	80.13	41384530	26879175	41384530	26879175	69.33	72.0	41384530	25237142	41384530	24151304	546218017	16.22	4.16	0	7.18	0	0.31	0	0.29	0	0.00	0	8.00	0	36400854	0	95	0	92.59	0	3.38	0	0.03	0	1.26	0	0.01	0	459.48	0	0.40	0	1658108	0	39821461	0	2857366	0	121494	0	114521	0	0	0	3184592	0	4794	0	0	0	26895	0	3392123	0	29583	0	3453395	0	84.23	0	33543488	0	110477	3520378	31.865257021824	39821461.0	36400854.0	1658108.0	2857366.0	121494.0	114521.0	0.0	3184592.0	33543488.0	91.4	4.2	7.2	0.3	0.3	0.0	8.0	84.2	95	95	95.00	8	3783038795	26.4	23.6	23.7	26.2	0.0	35.3	19.1	bulk
870677	SRR2229922	SRP056666	SRS1052846	SRX1178467	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867250: proximal_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Proximal CA1 pyramidal cells|location;;CA1|source_name;;Proximal CA1 pyramidal cells	GEO Accession;;GSM1867250		GSM1867250	proximal_2	5646596225	59437855	2016-01-06 15:50:16	2652995071	5646596225	59437855	1	59437855	index:0,count:59437855,average:95,stdev:0	GSM1867250_r1				in_mesa	26777276	5.24	3.13	0.06	5080146275	5099854794	4693997174	4768297592	100.39	101.58	0	0	0	0	0	0	78.1	84.6	62180099	42848564	62180099	42848564	74.04	76.79	62180099	40616485	62180099	38889091	607925538	11.97	3.77	0	7.09	0	0.32	0	0.25	0	0.00	0	7.13	0	54860522	0	95	0	92.68	0	3.12	0	0.02	0	1.27	0	0.01	0	606.17	0	0.37	0	2243552	0	59437855	0	4213873	0	188140	0	151459	0	0	0	4237734	0	7454	0	0	0	47232	0	5756850	0	40559	0	5852095	0	85.21	0	50646649	0	133098	5966654	44.829028234834	59437855.0	54860522.0	2243552.0	4213873.0	188140.0	151459.0	0.0	4237734.0	50646649.0	92.3	3.8	7.1	0.3	0.3	0.0	7.1	85.2	95	95	95.00	8	5646596225	26.5	23.6	23.7	26.2	0.0	35.5	19.5	bulk
870686	SRR2229923	SRP056666	SRS1052845	SRX1178468	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867251: distal_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Distal CA1 pyramidal cells|location;;CA1|source_name;;Distal CA1 pyramidal cells	GEO Accession;;GSM1867251		GSM1867251	distal_0	4755264995	50055421	2016-01-06 15:50:16	2218445454	4755264995	50055421	1	50055421	index:0,count:50055421,average:95,stdev:0	GSM1867251_r1				in_mesa	26777276	4.89	3.08	0.08	4225348025	4257255030	3903595491	3990563225	100.76	102.23	0	0	0	0	0	0	73.67	79.81	51673318	33546041	51673318	33546041	69.17	71.56	51673318	31498590	51673318	30078183	707159766	16.74	3.61	0	7.00	0	0.32	0	0.35	0	0.00	0	8.35	0	45538279	0	95	0	92.87	0	3.19	0	0.02	0	1.22	0	0.01	0	563.12	0	0.41	0	1807964	0	50055421	0	3503837	0	162248	0	175417	0	0	0	4179477	0	4842	0	0	0	35440	0	4305769	0	35617	0	4381668	0	83.98	0	42034442	0	119697	4478971	37.419241919179	50055421.0	45538279.0	1807964.0	3503837.0	162248.0	175417.0	0.0	4179477.0	42034442.0	91.0	3.6	7.0	0.3	0.4	0.0	8.3	84.0	95	95	95.00	8	4755264995	26.9	23.1	23.2	26.9	0.0	35.5	19.4	bulk
870693	SRR2229924	SRP056666	SRS1052844	SRX1178469	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867252: distal_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Distal CA1 pyramidal cells|location;;CA1|source_name;;Distal CA1 pyramidal cells	GEO Accession;;GSM1867252		GSM1867252	distal_1	4538355675	47772165	2016-01-06 15:50:16	2117953389	4538355675	47772165	1	47772165	index:0,count:47772165,average:95,stdev:0	GSM1867252_r1				in_mesa	26777276	4.59	3.01	0.09	4114993216	4108102635	3836035501	3878533285	99.83	101.11	0	0	0	0	0	0	68.12	73.13	49703931	30180769	49703931	30180769	64.51	66.27	49703931	28583174	49703931	27350881	952998395	23.16	3.64	0	6.35	0	0.32	0	0.44	0	0.00	0	6.49	0	44307300	0	95	0	92.95	0	2.96	0	0.02	0	1.24	0	0.01	0	534.10	0	0.39	0	1739413	0	47772165	0	3035733	0	155241	0	210670	0	0	0	3098954	0	4350	0	0	0	30433	0	3831906	0	34430	0	3901119	0	86.39	0	41271567	0	122810	3985801	32.455019949516	47772165.0	44307300.0	1739413.0	3035733.0	155241.0	210670.0	0.0	3098954.0	41271567.0	92.7	3.6	6.4	0.3	0.4	0.0	6.5	86.4	95	95	95.00	8	4538355675	27.2	22.7	22.8	27.2	0.0	35.6	19.6	bulk
870703	SRR2229925	SRP056666	SRS1052843	SRX1178470	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867253: distal_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Distal CA1 pyramidal cells|location;;CA1|source_name;;Distal CA1 pyramidal cells	GEO Accession;;GSM1867253		GSM1867253	distal_2	3935061405	41421699	2016-01-06 15:50:16	1849867503	3935061405	41421699	1	41421699	index:0,count:41421699,average:95,stdev:0	GSM1867253_r1				in_mesa	26777276	5.22	3.06	0.07	3521431593	3561018130	3228771830	3318008564	101.12	102.76	0	0	0	0	0	0	76.56	83.57	43700397	29132157	43700397	29132157	71.54	74.44	43700397	27220903	43700397	25949160	459766161	13.06	3.94	0	7.71	0	0.33	0	0.37	0	0.00	0	7.43	0	38050891	0	95	0	92.63	0	3.30	0	0.02	0	1.26	0	0.01	0	540.28	0	0.43	0	1631021	0	41421699	0	3192861	0	137360	0	154215	0	0	0	3079233	0	5798	0	0	0	30015	0	3642416	0	29207	0	3707436	0	84.15	0	34858030	0	104401	3788750	36.290361203437	41421699.0	38050891.0	1631021.0	3192861.0	137360.0	154215.0	0.0	3079233.0	34858030.0	91.9	3.9	7.7	0.3	0.4	0.0	7.4	84.2	95	95	95.00	8	3935061405	26.7	23.3	23.4	26.6	0.0	35.4	19.2	bulk
870711	SRR2229926	SRP056666	SRS1052842	SRX1178471	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867254: superficial_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Superficial CA1 pyramidal cells|location;;CA1|source_name;;Superficial CA1 pyramidal cells	GEO Accession;;GSM1867254		GSM1867254	superficial_0	4858651400	48586514	2016-01-06 15:50:16	2275661278	4858651400	48586514	1	48586514	index:0,count:48586514,average:100,stdev:0	GSM1867254_r1				in_mesa	26777276	5.43	3.0	0.05	4382550826	4407622727	4082238661	4152712327	100.57	101.73	0	0	0	0	0	0	75.54	81.16	50375744	34027800	50375744	34027800	70.6	72.96	50375744	31799739	50375744	30587149	669159224	15.27	3.69	0	6.42	0	0.27	0	0.24	0	0.00	0	6.78	0	45045135	0	100	0	97.37	0	3.14	0	0.02	0	2.16	0	0.02	0	450.80	0	0.34	0	1792776	0	48586514	0	3119966	0	130107	0	116247	0	0	0	3295025	0	6887	0	0	0	46782	0	5420397	0	36667	0	5510733	0	86.29	0	41925169	0	128825	5687943	44.152478168057	48586514.0	45045135.0	1792776.0	3119966.0	130107.0	116247.0	0.0	3295025.0	41925169.0	92.7	3.7	6.4	0.3	0.2	0.0	6.8	86.3	100	100	100.00	8	4858651400	26.6	23.4	23.6	26.4	0.0	35.4	19.5	bulk
870719	SRR2229927	SRP056666	SRS1052841	SRX1178472	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867255: superficial_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Superficial CA1 pyramidal cells|location;;CA1|source_name;;Superficial CA1 pyramidal cells	GEO Accession;;GSM1867255		GSM1867255	superficial_1	4976518800	49765188	2016-01-06 15:50:16	2333113735	4976518800	49765188	1	49765188	index:0,count:49765188,average:100,stdev:0	GSM1867255_r1				in_mesa	26777276	5.35	2.89	0.06	4501941130	4500877235	4213899753	4257727205	99.98	101.04	0	0	0	0	0	0	71.65	76.62	51314867	33124998	51314867	33124998	67.14	69.11	51314867	31040929	51314867	29881594	872949900	19.39	3.66	0	6.02	0	0.25	0	0.26	0	0.00	0	6.59	0	46230456	0	100	0	97.46	0	2.98	0	0.02	0	2.17	0	0.02	0	464.13	0	0.33	0	1820656	0	49765188	0	2995020	0	126535	0	130868	0	0	0	3277329	0	6899	0	0	0	45022	0	5231787	0	37153	0	5320861	0	86.88	0	43235436	0	128521	5479065	42.631671088771	49765188.0	46230456.0	1820656.0	2995020.0	126535.0	130868.0	0.0	3277329.0	43235436.0	92.9	3.7	6.0	0.3	0.3	0.0	6.6	86.9	100	100	100.00	8	4976518800	26.8	23.2	23.4	26.6	0.0	35.4	19.5	bulk
870727	SRR2229928	SRP056666	SRS1052840	SRX1178473	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867256: superficial_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Superficial CA1 pyramidal cells|location;;CA1|source_name;;Superficial CA1 pyramidal cells	GEO Accession;;GSM1867256		GSM1867256	superficial_2	3891628300	38916283	2016-01-06 15:50:16	1824933093	3891628300	38916283	1	38916283	index:0,count:38916283,average:100,stdev:0	GSM1867256_r1				in_mesa	26777276	6.01	3.06	0.04	3512554575	3539753900	3258495853	3322216657	100.77	101.96	0	0	0	0	0	0	77.89	84.04	40559283	28117023	40559283	28117023	72.77	75.46	40559283	26268444	40559283	25245958	440307932	12.54	3.58	0	6.78	0	0.27	0	0.23	0	0.00	0	6.74	0	36096325	0	100	0	97.39	0	3.24	0	0.02	0	2.28	0	0.02	0	418.20	0	0.34	0	1391391	0	38916283	0	2639637	0	105344	0	91022	0	0	0	2623592	0	5977	0	0	0	39405	0	4491249	0	28860	0	4565491	0	85.97	0	33456688	0	126685	4705925	37.146662982989	38916283.0	36096325.0	1391391.0	2639637.0	105344.0	91022.0	0.0	2623592.0	33456688.0	92.8	3.6	6.8	0.3	0.2	0.0	6.7	86.0	100	100	100.00	8	3891628300	26.4	23.6	23.7	26.2	0.0	35.4	19.2	bulk
870790	SRR2229930	SRP056666	SRS1052838	SRX1178475	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867258: deep_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Deep CA1 pyramidal cells|location;;CA1|source_name;;Deep CA1 pyramidal cells	GEO Accession;;GSM1867258		GSM1867258	deep_1	2770112200	27701122	2016-01-06 15:50:16	1304420328	2770112200	27701122	1	27701122	index:0,count:27701122,average:100,stdev:0	GSM1867258_r1				in_mesa	26777276	5.75	2.91	0.06	2461610928	2429478138	2325097956	2313797885	98.69	99.51	0	0	0	0	0	0	66.19	70.13	27784041	16732962	27784041	16732962	62.75	64.14	27784041	15864149	27784041	15304108	628445027	25.53	3.19	0	5.12	0	0.28	0	0.31	0	0.00	0	8.14	0	25280377	0	100	0	97.44	0	2.60	0	0.01	0	2.38	0	0.02	0	407.04	0	0.33	0	882654	0	27701122	0	1419234	0	77385	0	87106	0	0	0	2256254	0	3401	0	0	0	25667	0	2667645	0	19903	0	2716616	0	86.14	0	23861143	0	104685	2798223	26.729932655108	27701122.0	25280377.0	882654.0	1419234.0	77385.0	87106.0	0.0	2256254.0	23861143.0	91.3	3.2	5.1	0.3	0.3	0.0	8.1	86.1	100	100	100.00	8	2770112200	27.1	23.1	23.3	26.5	0.0	35.6	20.0	bulk
870798	SRR2229931	SRP056666	SRS1052837	SRX1178476	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867259: deep_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Deep CA1 pyramidal cells|location;;CA1|source_name;;Deep CA1 pyramidal cells	GEO Accession;;GSM1867259		GSM1867259	deep_2	2298235200	22982352	2016-01-06 15:50:16	1085905508	2298235200	22982352	1	22982352	index:0,count:22982352,average:100,stdev:0	GSM1867259_r1				in_mesa	26777276	6.51	3.17	0.06	2073354667	2057135816	1946229940	1947786162	99.22	100.08	0	0	0	0	0	0	77.81	82.95	23548097	16543432	23548097	16543432	74.33	76.41	23548097	15805422	23548097	15239591	275001035	13.26	3.13	0	5.74	0	0.29	0	0.27	0	0.00	0	6.93	0	21262442	0	100	0	97.58	0	2.67	0	0.01	0	2.52	0	0.02	0	422.12	0	0.33	0	719746	0	22982352	0	1318384	0	65936	0	62241	0	0	0	1591733	0	3635	0	0	0	26733	0	2763028	0	16040	0	2809436	0	86.78	0	19944058	0	106001	2897449	27.334166658805	22982352.0	21262442.0	719746.0	1318384.0	65936.0	62241.0	0.0	1591733.0	19944058.0	92.5	3.1	5.7	0.3	0.3	0.0	6.9	86.8	100	100	100.00	8	2298235200	26.8	23.4	23.5	26.3	0.0	35.5	19.6	bulk
870806	SRR2229932	SRP056666	SRS1052836	SRX1178477	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867260: ca3d_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA3 pyramidal cells|location;;CA3|source_name;;Dorsal CA3 pyramidal cells	GEO Accession;;GSM1867260		GSM1867260	ca3d_0	3713427700	39504550	2016-01-06 15:50:16	1816207301	3713427700	39504550	1	39504550	index:0,count:39504550,average:94,stdev:0	GSM1867260_r1				in_mesa	26777276	10.52	2.91	0.04	3360267452	3390198204	3119467627	3183990465	100.89	102.07	0	0	0	0	0	0	77.95	84.03	41068436	28549038	41068436	28549038	73.56	76.13	41068436	26942934	41068436	25866212	435128432	12.95	3.25	0	6.71	0	0.32	0	0.22	0	0.00	0	6.74	0	36626473	0	94	0	91.82	0	3.02	0	0.02	0	1.34	0	0.01	0	643.51	0	0.38	0	1284650	0	39504550	0	2651754	0	127563	0	87777	0	0	0	2662737	0	5113	0	0	0	35317	0	3911076	0	25082	0	3976588	0	86.00	0	33974719	0	131523	4039076	30.710035507098	39504550.0	36626473.0	1284650.0	2651754.0	127563.0	87777.0	0.0	2662737.0	33974719.0	92.7	3.3	6.7	0.3	0.2	0.0	6.7	86.0	94	94	94.00	8	3713427700	27.1	23.2	23.3	26.4	0.0	34.8	18.4	bulk
870814	SRR2229933	SRP056666	SRS1052835	SRX1178478	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867261: ca3d_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA3 pyramidal cells|location;;CA3|source_name;;Dorsal CA3 pyramidal cells	GEO Accession;;GSM1867261		GSM1867261	ca3d_1	4349032200	43490322	2016-01-06 15:50:16	2188193970	4349032200	43490322	1	43490322	index:0,count:43490322,average:100,stdev:0	GSM1867261_r1				in_mesa	26777276	11.71	3.34	0.04	3991161697	3940110395	3767958727	3753497396	98.72	99.62	0	0	0	0	0	0	79.04	83.77	44647371	32323603	44647371	32323603	77.41	79.02	44647371	31658633	44647371	30489575	529668430	13.27	2.87	0	5.31	0	0.27	0	0.28	0	0.00	0	5.42	0	40894993	0	100	0	97.65	0	1.92	0	0.01	0	2.07	0	0.01	0	599.87	0	0.39	0	1246145	0	43490322	0	2309353	0	116333	0	121204	0	0	0	2357792	0	6622	0	0	0	42981	0	4656207	0	25951	0	4731761	0	88.72	0	38585640	0	126880	4893151	38.565187578815	43490322.0	40894993.0	1246145.0	2309353.0	116333.0	121204.0	0.0	2357792.0	38585640.0	94.0	2.9	5.3	0.3	0.3	0.0	5.4	88.7	100	100	100.00	8	4349032200	28.3	22.3	22.3	27.1	0.0	34.1	17.8	bulk
870822	SRR2229934	SRP056666	SRS1052834	SRX1178479	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867262: ca3d_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal CA3 pyramidal cells|location;;CA3|source_name;;Dorsal CA3 pyramidal cells	GEO Accession;;GSM1867262		GSM1867262	ca3d_2	4291527600	42915276	2016-01-06 15:50:16	2160326100	4291527600	42915276	1	42915276	index:0,count:42915276,average:100,stdev:0	GSM1867262_r1				in_mesa	26777276	12.12	3.25	0.06	3904032461	3857895212	3671342267	3663112385	98.82	99.78	0	0	0	0	0	0	77.36	82.32	44076650	31052136	44076650	31052136	75.57	77.24	44076650	30335176	44076650	29137979	572292809	14.66	3.04	0	5.63	0	0.27	0	0.27	0	0.00	0	5.92	0	40140343	0	100	0	97.32	0	2.15	0	0.01	0	2.08	0	0.01	0	415.31	0	0.41	0	1306566	0	42915276	0	2417131	0	117721	0	116394	0	0	0	2540818	0	6116	0	0	0	39990	0	4372065	0	27075	0	4445246	0	87.90	0	37723212	0	119922	4594695	38.314029118927	42915276.0	40140343.0	1306566.0	2417131.0	117721.0	116394.0	0.0	2540818.0	37723212.0	93.5	3.0	5.6	0.3	0.3	0.0	5.9	87.9	100	100	100.00	8	4291527600	28.2	22.4	22.4	27.0	0.0	34.1	17.7	bulk
870831	SRR2229935	SRP056666	SRS1052833	SRX1178480	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867263: ca3v_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Ventral CA3 pyramidal cells|location;;CA3|source_name;;Ventral CA3 pyramidal cells	GEO Accession;;GSM1867263		GSM1867263	ca3v_0	4303703433	46276381	2016-01-06 15:50:16	2209890151	4303703433	46276381	1	46276381	index:0,count:46276381,average:93,stdev:0	GSM1867263_r1				in_mesa	26777276	9.97	3.1	0.05	3938882777	3940354027	3649220390	3691740743	100.04	101.17	0	0	0	0	0	0	76.79	82.94	48831754	33305267	48831754	33305267	73.07	75.72	48831754	31694508	48831754	30404240	538879870	13.68	3.33	0	6.96	0	0.29	0	0.24	0	0.00	0	5.73	0	43374544	0	93	0	90.88	0	2.70	0	0.01	0	1.28	0	0.01	0	658.48	0	0.46	0	1539525	0	46276381	0	3220425	0	135753	0	113065	0	0	0	2653019	0	5922	0	0	0	41853	0	4533334	0	27771	0	4608880	0	86.77	0	40154119	0	135797	4685673	34.504981700627	46276381.0	43374544.0	1539525.0	3220425.0	135753.0	113065.0	0.0	2653019.0	40154119.0	93.7	3.3	7.0	0.3	0.2	0.0	5.7	86.8	93	93	93.00	8	4303703433	27.2	23.1	23.2	26.5	0.0	33.7	17.2	bulk
870855	SRR2229938	SRP056666	SRS1052830	SRX1178483	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867266: sst_0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;SST interneuron|location;;CA1|source_name;;SST interneurons	GEO Accession;;GSM1867266		GSM1867266	sst_0	3170909050	33377990	2016-01-06 15:50:16	1999306914	3170909050	33377990	1	33377990	index:0,count:33377990,average:95,stdev:0	GSM1867266_r1				in_mesa	26777276	9.51	2.69	0.06	2722717924	2764031277	2441525683	2533105379	101.52	103.75	0	0	0	0	0	0	76.41	85.32	34785509	22521777	34785509	22521777	70.33	74.04	34785509	20729705	34785509	19545205	293637871	10.78	3.58	0	9.22	0	0.31	0	0.28	0	0.00	0	11.10	0	29476440	0	95	0	92.49	0	3.91	0	0.04	0	1.21	0	0.02	0	432.23	0	0.44	0	1193472	0	33377990	0	3079064	0	102147	0	94790	0	0	0	3704613	0	3476	0	0	0	24616	0	2675001	0	21657	0	2724750	0	79.09	0	26397376	0	130538	2797433	21.430028037813	33377990.0	29476440.0	1193472.0	3079064.0	102147.0	94790.0	0.0	3704613.0	26397376.0	88.3	3.6	9.2	0.3	0.3	0.0	11.1	79.1	95	95	95.00	38	3170909050	26.0	24.1	24.1	25.9	0.0	36.3	20.1	bulk
870918	SRR2229940	SRP056666	SRS1052828	SRX1178485	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867268: sst_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;SST interneuron|location;;CA1|source_name;;SST interneurons	GEO Accession;;GSM1867268		GSM1867268	sst_2	4428916625	46620175	2016-01-06 15:50:16	2083435659	4428916625	46620175	1	46620175	index:0,count:46620175,average:95,stdev:0	GSM1867268_r1				in_mesa	26777276	11.91	2.75	0.06	3818576548	3857261913	3479719259	3578858362	101.01	102.85	0	0	0	0	0	0	75.21	82.65	49134328	31338642	49134328	31338642	70.01	73.26	49134328	29174847	49134328	27779289	545274186	14.28	5.21	0	8.05	0	0.30	0	0.24	0	0.00	0	10.08	0	41670207	0	95	0	91.77	0	2.17	0	0.01	0	1.44	0	0.01	0	498.02	0	0.42	0	2427255	0	46620175	0	3750977	0	139037	0	113073	0	0	0	4697858	0	5799	0	0	0	36130	0	3487819	0	37394	0	3567142	0	81.34	0	37919230	0	85744	3628634	42.319392610562	46620175.0	41670207.0	2427255.0	3750977.0	139037.0	113073.0	0.0	4697858.0	37919230.0	89.4	5.2	8.0	0.3	0.2	0.0	10.1	81.3	95	95	95.00	8	4428916625	27.1	23.1	23.2	26.7	0.0	35.3	19.0	bulk
870935	SRR2229942	SRP056666	SRS1052826	SRX1178487	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867271: pv_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;PV interneuron|location;;CA1|source_name;;PV interneurons	GEO Accession;;GSM1867271		GSM1867271	pv_1	4955608880	52164304	2016-01-06 15:50:16	2324403519	4955608880	52164304	1	52164304	index:0,count:52164304,average:95,stdev:0	GSM1867271_r1				in_mesa	26777276	11.06	2.78	0.08	4351030237	4309545491	4011079187	4021737166	99.05	100.27	0	0	0	0	0	0	70.52	76.57	53310052	33093139	53310052	33093139	66.93	69.03	53310052	31409353	53310052	29835531	803191782	18.46	3.24	0	7.11	0	0.33	0	0.42	0	0.00	0	9.28	0	46927363	0	95	0	92.80	0	2.91	0	0.02	0	1.35	0	0.01	0	541.19	0	0.36	0	1687722	0	52164304	0	3706349	0	174622	0	220185	0	0	0	4842134	0	5485	0	0	0	36176	0	3800410	0	41836	0	3883907	0	82.86	0	43221014	0	126750	3974123	31.354027613412	52164304.0	46927363.0	1687722.0	3706349.0	174622.0	220185.0	0.0	4842134.0	43221014.0	90.0	3.2	7.1	0.3	0.4	0.0	9.3	82.9	95	95	95.00	8	4955608880	27.3	22.8	22.8	27.2	0.0	35.5	19.6	bulk
871079	SRR2229954	SRP056666	SRS1052814	SRX1178499	SRA249145	GEO		Spatial gene expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons	Tissue and organ function has been conventionally understood in terms of the interactions among discrete and homogeneous cell types.  This approach has proven difficult in neuroscience due to the marked diversity across different neuron classes, but may also be further hampered by prominent within-class variability.  Here, we considered a well-defined, canonical neuronal population – hippocampal CA1 pyramidal cells – and systematically examined the extent and spatial rules of transcriptional heterogeneity.  Using next-generation RNA sequencing, we identified striking variability in CA1 PCs, such that the differences along the dorsal-ventral axis rivaled differences across distinct pyramidal neuron classes. This variability emerged from a spectrum of continuous expression gradients, producing a profile consistent with a multifarious continuum of cells.  This work reveals an unexpected amount of variability within a canonical and narrowly defined neuronal population and suggests that continuous, within-class heterogeneity may be an important feature of neural circuits. Overall design: Hippocampal RNA profiles were generated by deep sequencing on Illumina HiSeq 2500, with three biological replicates per population		GSM1867290: dgd_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Manual sorting to purify for fluorescent neurons from microdissected slices was performed according to previous methods (Hempel et al., 2007). Total RNA was isolated from each sample using PicoPure RNA Isolation kit (Life Technologies, Frederick, MD) including the on-column RNAseq-free DNaseI treatment (Qiagen, Hilden, Germany) following the manufacturers’ recommendations.  Eluted RNA (11 ul) was dried in a speed vac to approximately 2-4 ul.  ERCC control RNAs (Life Technologies) were added using 1 ul of 1:100,000 dilution for every 50 cells.  cDNA was amplified from this input material using Ovation RNA-seq v2 kit (NuGEN, San Carlos, CA).  Approximately half of the resulting cDNA was used to make the sequencing libraries using the Ovation Rapid DR Multiplexing kit (NuGEN).	Illumina HiSeq 2500	cell population;;Dorsal DG granule cells|location;;DG|source_name;;Dorsal DG granule cells	GEO Accession;;GSM1867290		GSM1867290	dgd_1	3757259900	39970850	2016-01-06 15:50:16	1832948568	3757259900	39970850	1	39970850	index:0,count:39970850,average:94,stdev:0	GSM1867290_r1				in_mesa	26777276	7.72	2.99	0.1	3418579996	3347870987	3256284610	3210001530	97.93	98.58	0	0	0	0	0	0	56.56	59.41	40355692	21033131	40355692	21033131	54.41	55.15	40355692	20234646	40355692	19522947	1243000505	36.36	3.25	0	4.47	0	0.28	0	0.36	0	0.00	0	6.31	0	37190433	0	94	0	91.98	0	2.42	0	0.01	0	1.31	0	0.01	0	888.24	0	0.34	0	1297223	0	39970850	0	1787550	0	111926	0	144352	0	0	0	2524139	0	3848	0	0	0	23209	0	2663863	0	24851	0	2715771	0	88.57	0	35402883	0	127524	2759821	21.641581192560	39970850.0	37190433.0	1297223.0	1787550.0	111926.0	144352.0	0.0	2524139.0	35402883.0	93.0	3.2	4.5	0.3	0.4	0.0	6.3	88.6	94	94	94.00	8	3757259900	28.0	22.3	22.4	27.4	0.0	35.1	19.1	bulk
2795632	SRR1976543	SRP057261	SRS911695	SRX997479	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen Dendritic Cells from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	DC (CD11c+MHCII+ FLT3+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;Dendritic Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;CD11c+MHCII+ FLT3+|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	DC.SP#1	Spleen Dendritic Cells from Mus musculus	3118306200	31183062	2015-04-21 00:00:00	2021973378	3118306200	31183062	2	31183062	index:0,count:31183062,average:50,stdev:0|index:1,count:31183062,average:50,stdev:0	TRA00017431	Harvard Medical School			in_mesa	23631936	1.22	3.12	0.22	2752284920	2721610656	2580666588	2572639513	98.89	99.69	28303736	25062736	183.979	789.824	133	219405	77.09	82.21	31729472	21820390	31729472	21820390	78.99	79.48	31729472	22358526	31729472	21095122	465558342	16.92	4.73	0	5.65	0	0.35	0	0.23	0	0.00	0	8.65	0	28303736	0	100	0	99.03	0	1.72	0	0.01	0	1.13	0	0.00	0	492.36	0	0.29	0	1473794	0	31183062	0	1762860	0	107911	0	72858	0	0	0	2698557	0	3037	0	0	0	25977	0	4131212	0	15056	0	4175282	0	85.11	0	26540876	0	131768	4232195	32.118534090219	31183062.0	28303736.0	1473794.0	1762860.0	107911.0	72858.0	0.0	2698557.0	26540876.0	90.8	4.7	5.7	0.3	0.2	0.0	8.7	85.1	50	50	50.00	38	1559153100	26.0	23.3	24.8	25.8	0.0	37.9	30.0	bulk
2797105	SRR1976571	SRP057261	SRS911734	SRX997518	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen Neutrophil from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Neutrophils (LY66+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;Neutrophil|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;Ly6G+|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	GN.SP#1	Spleen Neutrophil from Mus musculus	3715943800	37159438	2015-04-21 00:00:00	2415860510	3715943800	37159438	2	37159438	index:0,count:37159438,average:50,stdev:0|index:1,count:37159438,average:50,stdev:0	TRA00017430	Harvard Medical School			in_mesa	23631936	0.15	2.71	0.15	3276050043	3165589483	3124905960	3061064360	96.63	97.96	33500079	29877219	189.659	769.652	150	279255	74.54	78.14	36938664	24969906	36938664	24969906	73.6	74.86	36938664	24654575	36938664	23920437	627279250	19.15	4.35	0	4.16	0	0.62	0	0.34	0	0.00	0	8.90	0	33500079	0	100	0	99.06	0	2.00	0	0.01	0	1.13	0	0.00	0	404.15	0	0.30	0	1615744	0	37159438	0	1545956	0	228586	0	125092	0	0	0	3305681	0	2825	0	0	0	30115	0	4306874	0	20728	0	4360542	0	85.99	0	31954123	0	112289	4479488	39.892491695536	37159438.0	33500079.0	1615744.0	1545956.0	228586.0	125092.0	0.0	3305681.0	31954123.0	90.2	4.3	4.2	0.6	0.3	0.0	8.9	86.0	50	50	50.00	38	1857971900	26.0	23.4	24.4	26.2	0.0	37.9	29.7	bulk
2797841	SRR1976588	SRP057261	SRS911741	SRX997535	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Peritoneal Cavity B1ab Cells from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	B1ab cells (CD19+CD43+CD5+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;B Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;CD19+CD43+CD5+|strain;;C57BL/6J|tissue;;Peritoneal Cavity lavage|treatment;;N/A		100	B1ab.PC#1	Peritoneal Cavity B1ab Cells from Mus musculus	4597200200	45972002	2015-04-21 00:00:00	2986998007	4597200200	45972002	2	45972002	index:0,count:45972002,average:50,stdev:0|index:1,count:45972002,average:50,stdev:0	TRA00017432	Harvard Medical School			in_mesa	23631936	2.09	3.0	0.41	4024285368	3925087226	3670710545	3631729041	97.54	98.94	41873464	37895451	172.318	770.344	114	325495	74.57	81.75	49335323	31224809	49335323	31224809	78.28	78.93	49335323	32777131	49335323	30147366	652020500	16.20	3.72	0	8.00	0	0.64	0	0.26	0	0.00	0	8.01	0	41873464	0	100	0	99.06	0	1.67	0	0.01	0	1.11	0	0.00	0	443.70	0	0.30	0	1710546	0	45972002	0	3676008	0	295020	0	119152	0	0	0	3684366	0	4860	0	0	0	41688	0	5528130	0	30464	0	5605142	0	83.09	0	38197456	0	122646	5649958	46.067201539390	45972002.0	41873464.0	1710546.0	3676008.0	295020.0	119152.0	0.0	3684366.0	38197456.0	91.1	3.7	8.0	0.6	0.3	0.0	8.0	83.1	50	50	50.00	38	2298600100	26.4	23.1	24.4	26.1	0.0	37.9	29.8	bulk
2797874	SRR1976589	SRP057261	SRS911752	SRX997537	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen NK Cell from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	NK (NK1.1+TCRB-)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;NK Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;NK1.1+TCRB-|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	NK.SP#1	Spleen NK Cell from Mus musculus	3568631500	35686315	2015-04-21 00:00:00	2327117199	3568631500	35686315	2	35686315	index:0,count:35686315,average:50,stdev:0|index:1,count:35686315,average:50,stdev:0	TRA00017434	Harvard Medical School			in_mesa	23631936	1.11	3.45	0.09	3123355014	3156192415	2860448068	2916613189	101.05	101.96	32485983	28556034	179.986	816.571	117	256929	85.46	93.32	37610292	27763413	37610292	27763413	87.57	88.44	37610292	28447484	37610292	26309531	191667883	6.14	3.96	0	7.67	0	0.29	0	0.15	0	0.00	0	8.52	0	32485983	0	100	0	98.89	0	2.48	0	0.01	0	1.09	0	0.00	0	511.84	0	0.32	0	1411917	0	35686315	0	2736438	0	103765	0	54963	0	0	0	3041604	0	5453	0	0	0	37984	0	5510737	0	23456	0	5577630	0	83.36	0	29749545	0	120586	5698368	47.255634982502	35686315.0	32485983.0	1411917.0	2736438.0	103765.0	54963.0	0.0	3041604.0	29749545.0	91.0	4.0	7.7	0.3	0.2	0.0	8.5	83.4	50	50	50.00	38	1784315750	26.3	23.6	25.3	24.8	0.0	37.8	29.6	bulk
2798097	SRR1976590	SRP057261	SRS911753	SRX997538	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen T regulatory Cells from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Treg (TCRB+CD4+CD25+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;Treg|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;CD4+CD25+CD8-CD19-|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	Treg.Sp#1	Spleen T regulatory Cells from Mus musculus	3160258500	31602585	2015-04-21 00:00:00	2060143102	3160258500	31602585	2	31602585	index:0,count:31602585,average:50,stdev:0|index:1,count:31602585,average:50,stdev:0	TRA00017435	Harvard Medical School			in_mesa	23631936	1.39	2.9	0.12	2474221988	2440763475	2220210166	2231084677	98.65	100.49	25700377	23280076	178.880	819.874	117	208241	72.97	81.38	31714301	18753323	31714301	18753323	73.33	75.38	31714301	18844936	31714301	17372531	401156268	16.21	3.98	0	8.40	0	0.30	0	0.23	0	0.00	0	18.15	0	25700377	0	100	0	98.93	0	2.96	0	0.02	0	1.20	0	0.01	0	345.80	0	0.44	0	1258880	0	31602585	0	2654929	0	94818	0	72641	0	0	0	5734749	0	2424	0	0	0	21834	0	3007395	0	18185	0	3049838	0	72.92	0	23045448	0	90458	3085070	34.104999005063	31602585.0	25700377.0	1258880.0	2654929.0	94818.0	72641.0	0.0	5734749.0	23045448.0	81.3	4.0	8.4	0.3	0.2	0.0	18.1	72.9	50	50	50.00	38	1580129250	26.1	22.9	26.0	25.0	0.0	37.8	29.6	bulk
2798129	SRR1976591	SRP057261	SRS911758	SRX997539	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen CD4 T Cell from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Total CD4 (TCRB+CD4+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;CD4 TConv Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;CD4+TCRB+|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	T4.Sp#1	Spleen CD4 T Cell from Mus musculus	3227653000	32276530	2015-04-21 00:00:00	2095340910	3227653000	32276530	2	32276530	index:0,count:32276530,average:50,stdev:0|index:1,count:32276530,average:50,stdev:0	TRA00017436	Harvard Medical School			in_mesa	23631936	1.47	3.44	0.34	2836248782	2775500377	2551145824	2542417934	97.86	99.66	29233089	25849158	186.925	960.488	129	225257	79.27	88.11	35346326	23173686	35346326	23173686	83.41	84.73	35346326	24382948	35346326	22286059	288109948	10.16	4.12	0	9.08	0	0.76	0	0.29	0	0.00	0	8.38	0	29233089	0	100	0	98.97	0	1.78	0	0.01	0	1.12	0	0.00	0	478.17	0	0.30	0	1328228	0	32276530	0	2931144	0	246182	0	92459	0	0	0	2704800	0	4306	0	0	0	33446	0	4401853	0	17479	0	4457084	0	81.49	0	26301945	0	124768	4528762	36.297464093357	32276530.0	29233089.0	1328228.0	2931144.0	246182.0	92459.0	0.0	2704800.0	26301945.0	90.6	4.1	9.1	0.8	0.3	0.0	8.4	81.5	50	50	50.00	38	1613826500	26.3	23.3	25.0	25.4	0.0	37.9	29.7	bulk
2798161	SRR1976592	SRP057261	SRS911759	SRX997540	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen CD8 T Cell from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Total CD8 (TCRB+CD8+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;CD8 T Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;TCRB+CD8+|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	T8.Sp#1	Spleen CD8 T Cell from Mus musculus	5434298300	54342983	2015-04-21 00:00:00	3522187560	5434298300	54342983	2	54342983	index:0,count:54342983,average:50,stdev:0|index:1,count:54342983,average:50,stdev:0	TRA00017437	Harvard Medical School			in_mesa	23631936	1.59	3.54	0.33	4745738765	4655271272	4239814478	4229061008	98.09	99.75	49405763	44099825	175.629	886.930	117	398985	80.59	90.2	60118027	39818387	60118027	39818387	85.66	86.94	60118027	42320724	60118027	38380329	393777277	8.30	3.65	0	9.68	0	0.71	0	0.25	0	0.00	0	8.12	0	49405763	0	100	0	98.95	0	1.74	0	0.01	0	1.12	0	0.00	0	406.73	0	0.30	0	1981715	0	54342983	0	5260639	0	385042	0	138273	0	0	0	4413905	0	6926	0	0	0	58383	0	7614118	0	35761	0	7715188	0	81.23	0	44145124	0	121588	7818415	64.302521630424	54342983.0	49405763.0	1981715.0	5260639.0	385042.0	138273.0	0.0	4413905.0	44145124.0	90.9	3.6	9.7	0.7	0.3	0.0	8.1	81.2	50	50	50.00	38	2717149150	26.6	23.2	25.0	25.2	0.0	37.9	29.7	bulk
2798194	SRR1976593	SRP057261	SRS911760	SRX997541	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen CD19+ B Cell from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Total CD19+ B (CD19+IgM+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;B Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;CD19+IgM+CD3-|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	BB.SP#1	Spleen CD19+ B Cell from Mus musculus	4061577600	40615776	2015-04-21 00:00:00	2634786775	4061577600	40615776	2	40615776	index:0,count:40615776,average:50,stdev:0|index:1,count:40615776,average:50,stdev:0	TRA00017438	Harvard Medical School			in_mesa	23631936	1.99	3.18	0.19	3617312445	3635693444	3299522341	3351056320	100.51	101.56	36961220	32026926	200.048	976.408	135	266168	83.72	91.75	43284631	30943990	43284631	30943990	86.73	87.52	43284631	32057108	43284631	29517058	273745523	7.57	3.83	0	7.96	0	0.35	0	0.16	0	0.00	0	8.48	0	36961220	0	100	0	98.98	0	2.11	0	0.01	0	1.12	0	0.00	0	606.71	0	0.30	0	1554001	0	40615776	0	3233445	0	143373	0	65461	0	0	0	3445722	0	6020	0	0	0	41885	0	6101598	0	26452	0	6175955	0	83.04	0	33727775	0	116830	6244319	53.447907215612	40615776.0	36961220.0	1554001.0	3233445.0	143373.0	65461.0	0.0	3445722.0	33727775.0	91.0	3.8	8.0	0.4	0.2	0.0	8.5	83.0	50	50	50.00	38	2030788800	26.3	23.7	25.0	25.0	0.0	37.9	29.9	bulk
2798226	SRR1976594	SRP057261	SRS911761	SRX997542	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen TRCgd from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	TCRgd (TCRgd+TCRB-)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;gdT Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;TCRgd+TCRB-|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	Tgd.SP#1	Spleen TRCgd from Mus musculus	1595061500	15950615	2015-04-21 00:00:00	1037336639	1595061500	15950615	2	15950615	index:0,count:15950615,average:50,stdev:0|index:1,count:15950615,average:50,stdev:0	TRA00017439	Harvard Medical School			in_mesa	23631936	1.76	3.15	0.24	1291549732	1291098415	1179055678	1196302000	99.97	101.46	13310570	11807849	186.525	957.670	117	102102	77.23	84.61	15619228	10279664	15619228	10279664	77.92	79.06	15619228	10371033	15619228	9605762	177901007	13.77	4.01	0	7.28	0	0.30	0	0.24	0	0.00	0	16.01	0	13310570	0	100	0	98.90	0	2.84	0	0.02	0	1.18	0	0.01	0	455.73	0	0.44	0	639666	0	15950615	0	1160649	0	48160	0	38891	0	0	0	2552994	0	1459	0	0	0	13101	0	1709845	0	12499	0	1736904	0	76.17	0	12149921	0	68622	1756669	25.599210165836	15950615.0	13310570.0	639666.0	1160649.0	48160.0	38891.0	0.0	2552994.0	12149921.0	83.4	4.0	7.3	0.3	0.2	0.0	16.0	76.2	50	50	50.00	38	797530750	26.4	22.9	25.2	25.5	0.0	37.8	29.7	bulk
2798258	SRR1976595	SRP057261	SRS911762	SRX997543	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen NKT from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	NKT (CD1d Tetramer Sorted, TCRB int)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;NKT Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;CD1dtet+|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	NKT.SP.Tetramer	Spleen NKT from Mus musculus	6320546800	63205468	2015-04-21 00:00:00	4096979478	6320546800	63205468	2	63205468	index:0,count:63205468,average:50,stdev:0|index:1,count:63205468,average:50,stdev:0	TRA00025075	Harvard Medical School			in_mesa	23631936	2.32	1.38	0.07	3964955559	4369886377	3464088888	3962331364	110.21	114.38	41314077	39260442	168.824	483.799	110	572143	66.66	76.55	56463888	27537952	56463888	27537952	48.4	52.17	56463888	19994352	56463888	18767682	752235467	18.97	6.55	0	8.45	0	0.13	0	0.11	0	0.00	0	34.39	0	41314077	0	100	0	98.76	0	3.93	0	0.04	0	1.14	0	0.01	0	341.14	0	0.60	0	4139630	0	63205468	0	5340191	0	82872	0	70835	0	0	0	21737684	0	1846	0	0	0	17792	0	2467598	0	24399	0	2511635	0	56.92	0	35973886	0	69957	2518925	36.006761296225	63205468.0	41314077.0	4139630.0	5340191.0	82872.0	70835.0	0.0	21737684.0	35973886.0	65.4	6.5	8.4	0.1	0.1	0.0	34.4	56.9	50	50	50.00	38	3160273400	26.9	21.7	27.6	23.8	0.0	38.3	31.0	bulk
2798289	SRR1976596	SRP057261	SRS911764	SRX997545	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen NKT from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	NKT (TCRBint NK1.1int)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;NKT Cell|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;TCRBint NK1.1int|strain;;C57BL/6J|tissue;;Spleen|treatment;;N/A		100	NKT.SP#1	Spleen NKT from Mus musculus	2612011600	26120116	2015-04-21 00:00:00	1682061008	2612011600	26120116	2	26120116	index:0,count:26120116,average:50,stdev:0|index:1,count:26120116,average:50,stdev:0	TRA00025076	Harvard Medical School			in_mesa	23631936	1.44	2.89	0.15	2161391600	2127794369	2000666292	1992533055	98.45	99.59	22626953	20433010	172.821	781.133	117	183207	72.79	78.68	26190037	16469459	26190037	16469459	73.9	75.0	26190037	16720321	26190037	15698561	428565565	19.83	3.78	0	6.49	0	0.33	0	0.27	0	0.00	0	12.77	0	22626953	0	100	0	98.92	0	1.68	0	0.01	0	1.18	0	0.00	0	403.57	0	0.39	0	986036	0	26120116	0	1695444	0	87372	0	71184	0	0	0	3334607	0	2166	0	0	0	20297	0	2725635	0	21172	0	2769270	0	80.14	0	20931509	0	102471	2793888	27.265157947127	26120116.0	22626953.0	986036.0	1695444.0	87372.0	71184.0	0.0	3334607.0	20931509.0	86.6	3.8	6.5	0.3	0.3	0.0	12.8	80.1	50	50	50.00	38	1306005800	27.1	21.9	24.6	26.4	0.0	38.5	31.2	bulk
2798320	SRR1976597	SRP057261	SRS911767	SRX997549	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Peritoneal Macrophage from Mus musculus	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	PC Macrophages (F4/80+ICAM2+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell treatment;;N/A|cell_type;;Macrophage|collected_by;;Katie Rothamel|genetic variation;;N/A|organism treatment;;N/A|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;male|sorting markers;;F4/80+ICAM2+|strain;;C57BL/6J|tissue;;Peritoneal Cavity lavage|treatment;;N/A		100	MF.PC#1	Peritoneal Macrophage from Mus musculus	918492200	9184922	2015-04-21 00:00:00	591614117	918492200	9184922	2	9184922	index:0,count:9184922,average:50,stdev:0|index:1,count:9184922,average:50,stdev:0	TRA00025077	Harvard Medical School			in_mesa	23631936	1.52	2.89	0.1	776157882	770453700	721351785	721160661	99.27	99.97	8186311	7451254	161.415	642.558	145	91190	77.49	83.41	9190726	6343353	9190726	6343353	79.31	79.79	9190726	6492872	9190726	6068210	118392143	15.25	4.24	0	6.33	0	0.25	0	0.20	0	0.00	0	10.42	0	8186311	0	100	0	98.85	0	1.82	0	0.01	0	1.13	0	0.00	0	479.21	0	0.38	0	389255	0	9184922	0	580977	0	23292	0	18567	0	0	0	956752	0	917	0	0	0	5184	0	1054668	0	9017	0	1069786	0	82.80	0	7605334	0	86979	1183968	13.612113268720	9184922.0	8186311.0	389255.0	580977.0	23292.0	18567.0	0.0	956752.0	7605334.0	89.1	4.2	6.3	0.3	0.2	0.0	10.4	82.8	50	50	50.00	38	459246100	27.5	22.0	23.9	26.6	0.0	38.5	31.4	bulk
2804817	SRR3932662	SRP057261	SRS1571885	SRX1961985	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Peritoneal Cavity B1ab Cells from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	B1ab cells (CD19+CD43+CD5+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;B Cell|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;CD19+CD43+CD5+|strain;;C57BL/6J|tissue;;Peritoneal Cavity lavage		100	B1ab.Fem.PC#1	Peritoneal Cavity B1ab Cells from Mus musculus (female)	1132008500	11320085	2016-07-20 13:08:33	549967432	1132008500	11320085	2	11320085	index:0,count:11320085,average:50,stdev:0|index:1,count:11320085,average:50,stdev:0	TRA00035661				in_mesa	23631936	1.07	3.29	0.28	830750705	819712576	738707010	738541622	98.67	99.98	9970235	9502521	113.880	520.999	75	129018	78.17	88.07	12373388	7793403	12373388	7793403	84.02	84.8	12373388	8376794	12373388	7504231	87076303	10.48	5.04	0	9.90	0	0.84	0	0.19	0	0.00	0	10.90	0	9970235	0	100	0	98.51	0	1.46	0	0.01	0	1.11	0	0.00	0	342.46	0	0.31	0	570376	0	11320085	0	1121064	0	94710	0	21132	0	0	0	1234008	0	1573	0	0	0	10486	0	1543750	0	6475	0	1562284	0	78.17	0	8849171	0	98970	1468400	14.836819238153	11320085.0	9970235.0	570376.0	1121064.0	94710.0	21132.0	0.0	1234008.0	8849171.0	88.1	5.0	9.9	0.8	0.2	0.0	10.9	78.2	50	50	50.00	17	566004250	25.7	23.9	25.9	24.5	0.0	38.4	32.9	bulk
2804851	SRR3932663	SRP057261	SRS1571886	SRX1961986	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Peritoneal Macrophage from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	PC Macrophages (F4/80+ICAM2+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;Macrophage|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;F4/80+ICAM2+|strain;;C57BL/6J|tissue;;Peritoneal Cavity lavage		100	MF.Fem.PC#1	Peritoneal Macrophage from Mus musculus (female)	347041500	3470415	2016-07-20 12:58:18	171281266	347041500	3470415	2	3470415	index:0,count:3470415,average:50,stdev:0|index:1,count:3470415,average:50,stdev:0	TRA00035662				in_mesa	23631936	0.83	2.76	0.06	246383585	246649515	227196373	228704218	100.11	100.66	3021452	2871533	108.755	444.274	75	42096	85.75	93.11	3481898	2590825	3481898	2590825	88.46	89.27	3481898	2672760	3481898	2483877	15886402	6.45	5.52	0	6.88	0	0.35	0	0.10	0	0.00	0	12.49	0	3021452	0	100	0	98.16	0	1.46	0	0.01	0	1.11	0	0.00	0	244.97	0	0.50	0	191560	0	3470415	0	238919	0	11998	0	3466	0	0	0	433499	0	388	0	0	0	2147	0	509211	0	1771	0	513517	0	80.18	0	2782533	0	64698	496086	7.667717703793	3470415.0	3021452.0	191560.0	238919.0	11998.0	3466.0	0.0	433499.0	2782533.0	87.1	5.5	6.9	0.3	0.1	0.0	12.5	80.2	50	50	50.00	17	173520750	25.6	24.3	25.8	24.3	0.0	38.4	32.7	bulk
2804885	SRR3932664	SRP057261	SRS1571887	SRX1961987	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen CD19+ B Cell from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Total CD19+ B (CD19+IgM+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;B Cell|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;CD19+IgM+CD3-|strain;;C57BL/6J|tissue;;Spleen		100	B.Fem.Sp#1	Spleen CD19+ B Cell from Mus musculus (female)	1013971500	10139715	2016-07-20 13:03:10	494880658	1013971500	10139715	2	10139715	index:0,count:10139715,average:50,stdev:0|index:1,count:10139715,average:50,stdev:0	TRA00035663				in_mesa	23631936	1.44	3.13	0.23	808624678	799811097	737380985	736549371	98.91	99.89	9181127	8696991	125.441	514.611	83	100949	77.31	84.87	10836520	7098163	10836520	7098163	81.03	81.59	10836520	7439419	10836520	6824073	112079355	13.86	4.75	0	8.06	0	0.47	0	0.20	0	0.00	0	8.78	0	9181127	0	100	0	98.82	0	1.60	0	0.01	0	1.14	0	0.00	0	445.16	0	0.29	0	481405	0	10139715	0	817124	0	47439	0	20407	0	0	0	890742	0	1437	0	0	0	8560	0	1322424	0	5710	0	1338131	0	82.49	0	8364003	0	98364	1290788	13.122565166118	10139715.0	9181127.0	481405.0	817124.0	47439.0	20407.0	0.0	890742.0	8364003.0	90.5	4.7	8.1	0.5	0.2	0.0	8.8	82.5	50	50	50.00	17	506985750	25.6	23.8	25.3	25.3	0.0	38.4	32.9	bulk
2804916	SRR3932665	SRP057261	SRS1571888	SRX1961988	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen CD4 T Cell from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Total CD4 (TCRB+CD4+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;CD4 TConv Cell|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;CD4+TCRB+|strain;;C57BL/6J|tissue;;Spleen		100	T4.Fem.Sp#1	Spleen CD4 T Cell from Mus musculus (female)	1549567300	15495673	2016-07-20 13:11:08	745504851	1549567300	15495673	2	15495673	index:0,count:15495673,average:50,stdev:0|index:1,count:15495673,average:50,stdev:0	TRA00035664				in_mesa	23631936	0.45	3.33	0.31	1213984690	1194454101	1092803369	1093204262	98.39	100.04	13915895	13151459	129.395	559.730	75	147021	79.68	88.62	17011984	11088229	17011984	11088229	83.59	84.8	17011984	11631777	17011984	10610823	120369540	9.92	3.54	0	9.06	0	0.91	0	0.27	0	0.00	0	9.01	0	13915895	0	100	0	98.85	0	1.53	0	0.01	0	1.11	0	0.00	0	357.59	0	0.21	0	549126	0	15495673	0	1403794	0	141237	0	42167	0	0	0	1396374	0	2481	0	0	0	15016	0	2167565	0	7515	0	2192577	0	80.75	0	12512101	0	98929	2108652	21.314801524326	15495673.0	13915895.0	549126.0	1403794.0	141237.0	42167.0	0.0	1396374.0	12512101.0	89.8	3.5	9.1	0.9	0.3	0.0	9.0	80.7	50	50	50.00	17	774783650	24.6	23.8	27.3	24.3	0.0	38.5	33.0	bulk
2804947	SRR3932666	SRP057261	SRS1571889	SRX1961989	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen CD8 T Cell from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Total CD8 (TCRB+CD8+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;CD8 T Cell|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;TCRB+CD8+|strain;;C57BL/6J|tissue;;Spleen		100	T8.Fem.Sp#1	Spleen CD8 T Cell from Mus musculus (female)	1260939400	12609394	2016-07-20 13:02:09	604921737	1260939400	12609394	2	12609394	index:0,count:12609394,average:50,stdev:0|index:1,count:12609394,average:50,stdev:0	TRA00035665				in_mesa	23631936	1.25	3.63	0.24	986897054	969818407	869901770	867032527	98.27	99.67	11172614	10586469	126.873	572.601	86	119714	76.04	86.36	13954025	8495668	13954025	8495668	82.25	82.87	13954025	9189732	13954025	8152267	116595931	11.81	5.38	0	10.58	0	0.78	0	0.28	0	0.00	0	10.33	0	11172614	0	100	0	98.70	0	1.54	0	0.01	0	1.12	0	0.00	0	270.20	0	0.32	0	678784	0	12609394	0	1334644	0	98748	0	35401	0	0	0	1302631	0	1579	0	0	0	11401	0	1581226	0	7663	0	1601869	0	78.02	0	9837970	0	104105	1563473	15.018231593103	12609394.0	11172614.0	678784.0	1334644.0	98748.0	35401.0	0.0	1302631.0	9837970.0	88.6	5.4	10.6	0.8	0.3	0.0	10.3	78.0	50	50	50.00	17	630469700	26.0	23.6	25.4	25.0	0.0	38.5	33.1	bulk
2804979	SRR3932667	SRP057261	SRS1571890	SRX1961990	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen Neutrophil from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Neutrophils (LY66+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;Neutrophil|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;Ly6G+|strain;;C57BL/6J|tissue;;Spleen		100	Gn.Fem.Sp#1	Spleen Neutrophil from Mus musculus (female)	597154200	5971542	2016-07-20 12:59:10	290091218	597154200	5971542	2	5971542	index:0,count:5971542,average:50,stdev:0|index:1,count:5971542,average:50,stdev:0	TRA00035666				in_mesa	23631936	0.15	2.91	0.09	458962757	450448255	436129659	432350190	98.14	99.13	5275773	4977529	122.705	459.878	87	59113	83.34	87.79	5835870	4396656	5835870	4396656	83.57	84.73	5835870	4408707	5835870	4243725	48514576	10.57	3.46	0	4.48	0	0.65	0	0.27	0	0.00	0	10.73	0	5275773	0	100	0	98.86	0	1.38	0	0.01	0	1.10	0	0.00	0	341.23	0	0.20	0	206547	0	5971542	0	267531	0	38836	0	16214	0	0	0	640719	0	517	0	0	0	4938	0	848414	0	3416	0	857285	0	83.87	0	5008242	0	69445	829042	11.938109295126	5971542.0	5275773.0	206547.0	267531.0	38836.0	16214.0	0.0	640719.0	5008242.0	88.3	3.5	4.5	0.7	0.3	0.0	10.7	83.9	50	50	50.00	17	298577100	25.3	23.8	25.9	24.9	0.0	38.5	33.0	bulk
2805011	SRR3932668	SRP057261	SRS1571891	SRX1961991	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen Dendritic Cells from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	DC (CD11c+MHCII+ FLT3+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;Dendritic Cell|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;Cd11b+Flt3+|strain;;C57BL/6J|tissue;;Spleen		100	DC.Fem.Sp#1	Spleen Dendritic Cells from Mus musculus (female)	1559486200	15594862	2016-07-20 13:08:33	747632516	1559486200	15594862	2	15594862	index:0,count:15594862,average:50,stdev:0|index:1,count:15594862,average:50,stdev:0	TRA00035667				in_mesa	23631936	0.74	3.13	0.15	1277232826	1269208880	1189174037	1190703419	99.37	100.13	14368435	13326688	137.474	552.100	90	137409	80.39	86.39	16311275	11550083	16311275	11550083	83.18	83.71	16311275	11951871	16311275	11192325	163666030	12.81	3.58	0	6.40	0	0.40	0	0.19	0	0.00	0	7.27	0	14368435	0	100	0	98.93	0	1.39	0	0.01	0	1.10	0	0.00	0	359.88	0	0.20	0	558018	0	15594862	0	998774	0	62266	0	30362	0	0	0	1133799	0	1864	0	0	0	13845	0	2350090	0	10215	0	2376014	0	85.73	0	13369661	0	110651	2296545	20.754850837317	15594862.0	14368435.0	558018.0	998774.0	62266.0	30362.0	0.0	1133799.0	13369661.0	92.1	3.6	6.4	0.4	0.2	0.0	7.3	85.7	50	50	50.00	17	779743100	25.3	24.1	25.4	25.2	0.0	38.5	33.2	bulk
2805042	SRR3932669	SRP057261	SRS1571892	SRX1961992	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen NK Cell from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	NK (NK1.1+TCRB-)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;NK Cell|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;NK1.1+TCRB-|strain;;C57BL/6J|tissue;;Spleen		100	NK.Fem.Sp#1	Spleen NK Cell from Mus musculus (female)	1341782100	13417821	2016-07-20 13:06:34	646342812	1341782100	13417821	2	13417821	index:0,count:13417821,average:50,stdev:0|index:1,count:13417821,average:50,stdev:0	TRA00035668				in_mesa	23631936	0.84	3.46	0.1	1062936352	1064376066	960922953	971735204	100.14	101.13	12154172	11469032	131.832	451.385	83	136090	83.61	92.67	14446399	10162429	14446399	10162429	87.13	88.17	14446399	10590487	14446399	9669395	71137768	6.69	2.96	0	8.85	0	0.37	0	0.13	0	0.00	0	8.92	0	12154172	0	100	0	98.97	0	1.48	0	0.01	0	1.10	0	0.00	0	303.80	0	0.22	0	397296	0	13417821	0	1187999	0	49704	0	17077	0	0	0	1196868	0	1861	0	0	0	9628	0	1731758	0	6278	0	1749525	0	81.73	0	10966173	0	75504	1706349	22.599451684679	13417821.0	12154172.0	397296.0	1187999.0	49704.0	17077.0	0.0	1196868.0	10966173.0	90.6	3.0	8.9	0.4	0.1	0.0	8.9	81.7	50	50	50.00	17	670891050	24.9	23.7	26.2	25.2	0.0	38.5	33.1	bulk
2805268	SRR3932670	SRP057261	SRS1571893	SRX1961993	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen NKT from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	NKT (TCRBint NK1.1int)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;NKT Cell|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;TCRBint NK1.1int|strain;;C57BL/6J|tissue;;Spleen		100	NKT.Fem.Sp#1	Spleen NKT from Mus musculus (female)	1600282800	16002828	2016-07-20 13:11:08	768063898	1600282800	16002828	2	16002828	index:0,count:16002828,average:50,stdev:0|index:1,count:16002828,average:50,stdev:0	TRA00035669				in_mesa	23631936	1.33	3.38	0.12	1300058097	1297068614	1163797894	1173502871	99.77	100.83	14720311	13802994	135.565	572.607	83	158088	83.5	93.41	17722065	12290769	17722065	12290769	88.62	89.58	17722065	13045301	17722065	11786561	77118515	5.93	3.16	0	9.77	0	0.50	0	0.12	0	0.00	0	7.39	0	14720311	0	100	0	98.94	0	1.44	0	0.01	0	1.10	0	0.00	0	357.83	0	0.22	0	505090	0	16002828	0	1562706	0	79669	0	19900	0	0	0	1182948	0	2519	0	0	0	14536	0	2302240	0	9749	0	2329044	0	82.22	0	13157605	0	96974	2268607	23.393971580011	16002828.0	14720311.0	505090.0	1562706.0	79669.0	19900.0	0.0	1182948.0	13157605.0	92.0	3.2	9.8	0.5	0.1	0.0	7.4	82.2	50	50	50.00	17	800141400	25.4	24.1	25.8	24.7	0.0	38.5	33.1	bulk
2805299	SRR3932671	SRP057261	SRS1571896	SRX1961994	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen TCRgd from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	TCRgd (TCRgd+TCRB-)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;gdT Cell|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;TCRgd+TCRB-|strain;;C57BL/6J|tissue;;Spleen		100	Tgd.Fem.Sp#1	Spleen TCRgd from Mus musculus (female)	905865500	9058655	2016-07-20 13:04:09	438582523	905865500	9058655	2	9058655	index:0,count:9058655,average:50,stdev:0|index:1,count:9058655,average:50,stdev:0	TRA00035670				in_mesa	23631936	1.08	3.43	0.13	672956525	671297901	611501200	615735809	99.75	100.69	8045028	7586590	119.902	593.897	72	98656	83.58	92.15	9520794	6724035	9520794	6724035	87.62	88.47	9520794	7049288	9520794	6455194	47556051	7.07	4.38	0	8.26	0	0.52	0	0.19	0	0.00	0	10.48	0	8045028	0	100	0	98.66	0	1.40	0	0.01	0	1.11	0	0.00	0	304.78	0	0.20	0	396891	0	9058655	0	748246	0	47301	0	17207	0	0	0	949119	0	1559	0	0	0	8991	0	1360745	0	4911	0	1376206	0	80.55	0	7296782	0	97145	1288210	13.260692778836	9058655.0	8045028.0	396891.0	748246.0	47301.0	17207.0	0.0	949119.0	7296782.0	88.8	4.4	8.3	0.5	0.2	0.0	10.5	80.6	50	50	50.00	17	452932750	25.5	24.1	26.1	24.3	0.0	38.5	33.0	bulk
2805331	SRR3932672	SRP057261	SRS1571898	SRX1961995	SRA244059	Harvard Medical School	CBDM Laboratory	ImmGen 11-cell set basic RNASeq project	Full depth directional RNA sequencing was performed on the core ImmGen populations to generate reference datasets for the tissues from 5 week-old C57BL/6J (Jackson Laboratory) males and females, double-sorted by flow cytometry, per ImmGen cell preparation SOP. RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer''s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3'' and 5'' adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer. The read depths for the 11-cell set populations range from around 8 to 25 million.		Full depth directional RNA sequencing on Spleen T regulatory Cells from Mus musculus (female)	RNA was prepared from 100,000 cells (final sort collected directly in Trizol). Total RNA was extracted from each sample following ImmGen RNA extraction SOP. PolyA+ RNA was isolated by bead capture (PrepX PolyA mRNA Isolation Kit, Wafergen Biosystems), following the manufacturer’s instructions. Then mRNA libraries were prepared with the PrepX RNA-Seq Library Preparation Kit (Integenex). For first strand synthesis, mRNA was fragmented and ligated to 3’ and 5’ adapters before reverse transcription. Sample libraries then underwent bead clean-up, 2nd strand synthesis and PCR amplification before final sequencing. Libraries were analyzed on an Illumina HiSeq2500 sequencer.	Treg (TCRB+CD4+CD25+)		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired				Illumina HiSeq 2500	age;;5 week-old|BioSampleModel;;Model organism or animal|cell_type;;Treg|separation method;;FACSAria|sequencing machine;;HiSeq|sex;;female|sorting markers;;CD4+CD25+CD8-CD19-|strain;;C57BL/6J|tissue;;Spleen		100	Treg.Fem.Sp#1	Spleen T regulatory Cells from Mus musculus (female)	1849224800	18492248	2016-07-20 13:11:08	899733437	1849224800	18492248	2	18492248	index:0,count:18492248,average:50,stdev:0|index:1,count:18492248,average:50,stdev:0	TRA00035671				in_mesa	23631936	1.19	3.69	0.11	1489708380	1484696124	1312774713	1321644007	99.66	100.68	16854510	15857117	132.308	588.434	83	183579	80.54	91.51	20958839	13574150	20958839	13574150	86.76	87.67	20958839	14622218	20958839	13004743	113416358	7.61	3.75	0	10.93	0	0.49	0	0.18	0	0.00	0	8.19	0	16854510	0	100	0	98.89	0	1.78	0	0.01	0	1.15	0	0.00	0	455.97	0	0.22	0	693706	0	18492248	0	2020833	0	91454	0	32541	0	0	0	1513743	0	2758	0	0	0	18165	0	2686590	0	8625	0	2716138	0	80.22	0	14833677	0	111858	2645871	23.653837901625	18492248.0	16854510.0	693706.0	2020833.0	91454.0	32541.0	0.0	1513743.0	14833677.0	91.1	3.8	10.9	0.5	0.2	0.0	8.2	80.2	50	50	50.00	17	924612400	25.4	24.3	26.1	24.3	0.0	38.5	33.1	bulk
1675820	SRR3532922	SRP059295	SRS1440206	SRX1767514	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154666: RNAseq_WT1_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154666		GSM2154666	RNAseq_WT1_cortex	12168924750	48675699	2016-05-26 12:42:58	7345053325	12168924750	48675699	2	48675699	index:0,count:48675699,average:125,stdev:0|index:1,count:48675699,average:125,stdev:0	GSM2154666_r1						8.25	2.83	0.09	7531694445	7307718803	6734018937	6560840664	97.03	97.43	42264497	39832250	195.200	827.056	158	389189	58.56	65.91	51578409	24748327	51578409	24748327	62.55	63.0	51578409	26435472	51578409	23654433	2211596840	29.36	1.80	0	9.69	0	0.80	0	0.76	0	0.00	0	11.61	0	42264497	0	250	0	245.45	0	2.24	0	0.02	0	1.90	0	0.02	0	133.56	0	0.66	0	875968	0	48675699	0	4715599	0	391268	0	371010	0	0	0	5648924	0	9787	0	0	0	156788	0	11130059	0	79840	0	11376474	0	77.14	0	37548898	0	252296	9324622	36.959056029426	48675699.0	42264497.0	875968.0	4715599.0	391268.0	371010.0	0.0	5648924.0	37548898.0	86.8	1.8	9.7	0.8	0.8	0.0	11.6	77.1	125	125	125.00	24	6084462375	27.6	22.4	22.2	27.8	0.0	33.5	23.9	bulk
1675835	SRR3532923	SRP059295	SRS1440208	SRX1767515	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154667: RNAseq_WT2_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154667		GSM2154667	RNAseq_WT2_cortex	10558170750	42232683	2016-05-26 12:42:58	6358366582	10558170750	42232683	2	42232683	index:0,count:42232683,average:125,stdev:0|index:1,count:42232683,average:125,stdev:0	GSM2154667_r1						5.87	2.68	0.44	6331184048	5638708037	5567535699	4987641860	89.06	89.58	35380387	33474479	196.890	889.440	158	339440	47.65	54.37	44762403	16857508	44762403	16857508	52.9	52.04	44762403	18716460	44762403	16136474	2107090824	33.28	1.85	0	10.36	0	1.26	0	2.36	0	0.00	0	12.61	0	35380387	0	250	0	244.95	0	2.16	0	0.03	0	1.93	0	0.02	0	70.16	0	0.78	0	781001	0	42232683	0	4375325	0	531694	0	994633	0	0	0	5325969	0	7095	0	0	0	127615	0	7297788	0	137511	0	7570009	0	73.41	0	31005062	0	268156	7361131	27.450927818136	42232683.0	35380387.0	781001.0	4375325.0	531694.0	994633.0	0.0	5325969.0	31005062.0	83.8	1.8	10.4	1.3	2.4	0.0	12.6	73.4	125	125	125.00	24	5279085375	28.3	21.6	21.5	28.5	0.0	33.4	23.8	bulk
1675852	SRR3532924	SRP059295	SRS1440207	SRX1767516	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154668: RNAseq_WT3_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154668		GSM2154668	RNAseq_WT3_cortex	14817256750	59269027	2016-05-26 12:42:58	8925238783	14817256750	59269027	2	59269027	index:0,count:59269027,average:125,stdev:0|index:1,count:59269027,average:125,stdev:0	GSM2154668_r1						8.2	2.76	0.08	9129270573	8879203225	8412808411	8198933131	97.26	97.46	51773720	49026638	192.830	801.931	144	496652	54.84	59.81	60027215	28394749	60027215	28394749	57.51	57.3	60027215	29776307	60027215	27203013	3265964284	35.77	2.04	0	7.25	0	0.50	0	0.35	0	0.00	0	11.80	0	51773720	0	250	0	245.98	0	1.47	0	0.01	0	1.17	0	0.00	0	145.64	0	0.53	0	1208313	0	59269027	0	4299874	0	296376	0	207015	0	0	0	6991916	0	10185	0	0	0	99529	0	12866833	0	47491	0	13024038	0	80.10	0	47473846	0	249392	10070899	40.381804548662	59269027.0	51773720.0	1208313.0	4299874.0	296376.0	207015.0	0.0	6991916.0	47473846.0	87.4	2.0	7.3	0.5	0.3	0.0	11.8	80.1	125	125	125.00	24	7408628375	27.8	22.3	22.1	27.8	0.0	33.5	23.9	bulk
1675869	SRR3532925	SRP059295	SRS1440211	SRX1767517	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154669: RNAseq_Nova2-KO1_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova2-ko|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154669		GSM2154669	RNAseq_Nova2-KO1_cortex	11092251750	44369007	2016-05-26 12:42:58	6691280245	11092251750	44369007	2	44369007	index:0,count:44369007,average:125,stdev:0|index:1,count:44369007,average:125,stdev:0	GSM2154669_r1						6.63	2.91	0.14	7084952134	6894062530	6469243215	6311065995	97.31	97.55	39115034	37151168	198.958	792.984	158	360589	52.56	57.9	45735323	20559121	45735323	20559121	55.56	55.34	45735323	21730427	45735323	19650981	2657199441	37.50	1.80	0	8.13	0	0.48	0	0.33	0	0.00	0	11.03	0	39115034	0	250	0	245.86	0	2.32	0	0.02	0	1.93	0	0.02	0	156.75	0	0.65	0	800657	0	44369007	0	3607160	0	215046	0	145114	0	0	0	4893813	0	7899	0	0	0	109836	0	9377972	0	62274	0	9557981	0	80.03	0	35507874	0	222555	7617689	34.228343555526	44369007.0	39115034.0	800657.0	3607160.0	215046.0	145114.0	0.0	4893813.0	35507874.0	88.2	1.8	8.1	0.5	0.3	0.0	11.0	80.0	125	125	125.00	24	5546125875	27.6	22.4	22.2	27.8	0.0	33.5	24.0	bulk
1675885	SRR3532926	SRP059295	SRS1440210	SRX1767518	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154670: RNAseq_Nova2-KO2_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova2-ko|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154670		GSM2154670	RNAseq_Nova2-KO2_cortex	11355152000	45420608	2016-05-26 12:42:58	6871546149	11355152000	45420608	2	45420608	index:0,count:45420608,average:125,stdev:0|index:1,count:45420608,average:125,stdev:0	GSM2154670_r1						6.66	2.86	0.14	7091928338	6898188324	6475398751	6315196025	97.27	97.53	39756607	37749651	194.991	796.514	158	377171	52.33	57.62	46667129	20804892	46667129	20804892	55.2	55.04	46667129	21945490	46667129	19875251	2674389336	37.71	1.81	0	8.03	0	0.53	0	0.33	0	0.00	0	11.61	0	39756607	0	250	0	245.80	0	2.30	0	0.02	0	1.95	0	0.02	0	172.85	0	0.65	0	821496	0	45420608	0	3648814	0	241121	0	151578	0	0	0	5271302	0	8015	0	0	0	110275	0	9460512	0	63567	0	9642369	0	79.50	0	36107793	0	221605	7603932	34.312998352925	45420608.0	39756607.0	821496.0	3648814.0	241121.0	151578.0	0.0	5271302.0	36107793.0	87.5	1.8	8.0	0.5	0.3	0.0	11.6	79.5	125	125	125.00	24	5677576000	27.6	22.4	22.1	27.8	0.0	33.4	23.8	bulk
1675901	SRR3532927	SRP059295	SRS1440209	SRX1767519	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154671: RNAseq_Nova2-KO3_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova2-ko|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154671		GSM2154671	RNAseq_Nova2-KO3_cortex	12301019750	49204079	2016-05-26 12:42:58	7406928821	12301019750	49204079	2	49204079	index:0,count:49204079,average:125,stdev:0|index:1,count:49204079,average:125,stdev:0	GSM2154671_r1						6.05	2.85	0.13	7306348626	7093825175	6699909935	6523907344	97.09	97.37	42200479	40074470	188.963	847.526	139	425382	49.67	54.41	49570987	20960046	49570987	20960046	52.18	51.9	49570987	22021720	49570987	19994065	2985974036	40.87	2.28	0	7.47	0	0.61	0	0.35	0	0.00	0	13.28	0	42200479	0	250	0	245.07	0	2.30	0	0.02	0	1.97	0	0.02	0	120.83	0	0.65	0	1124286	0	49204079	0	3677035	0	299479	0	171390	0	0	0	6532731	0	7895	0	0	0	108869	0	9435610	0	72247	0	9624621	0	78.29	0	38523444	0	228756	7368166	32.209716903600	49204079.0	42200479.0	1124286.0	3677035.0	299479.0	171390.0	0.0	6532731.0	38523444.0	85.8	2.3	7.5	0.6	0.3	0.0	13.3	78.3	125	125	125.00	24	6150509875	27.7	22.4	22.2	27.7	0.0	33.5	23.9	bulk
1675916	SRR3532928	SRP059295	SRS1440212	SRX1767520	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154672: RNAseq_WT4_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154672		GSM2154672	RNAseq_WT4_cortex	13678916500	54715666	2016-05-26 12:42:59	7497957475	13678916500	54715666	2	54715666	index:0,count:54715666,average:125,stdev:0|index:1,count:54715666,average:125,stdev:0	GSM2154672_r1						2.49	2.88	0.36	9200595051	8950674853	8221657729	8018443711	97.28	97.53	48516886	45516918	222.618	952.793	160	351925	48.47	54.66	58356166	23515078	58356166	23515078	52.38	51.67	58356166	25411510	58356166	22230467	3654686602	39.72	1.87	0	10.04	0	0.76	0	0.42	0	0.00	0	10.15	0	48516886	0	250	0	246.11	0	2.41	0	0.02	0	2.10	0	0.02	0	129.08	0	0.46	0	1021233	0	54715666	0	5492811	0	415453	0	228189	0	0	0	5555138	0	9909	0	0	0	162710	0	11679627	0	80157	0	11932403	0	78.63	0	43024075	0	245201	9925331	40.478346336271	54715666.0	48516886.0	1021233.0	5492811.0	415453.0	228189.0	0.0	5555138.0	43024075.0	88.7	1.9	10.0	0.8	0.4	0.0	10.2	78.6	125	125	125.00	24	6839458250	27.0	23.0	22.9	27.2	0.0	34.7	25.3	bulk
1675931	SRR3532929	SRP059295	SRS1440214	SRX1767521	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154673: RNAseq_WT5_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154673		GSM2154673	RNAseq_WT5_cortex	11869306250	47477225	2016-05-26 12:42:59	6531803337	11869306250	47477225	2	47477225	index:0,count:47477225,average:125,stdev:0|index:1,count:47477225,average:125,stdev:0	GSM2154673_r1						1.85	2.94	0.55	7886206253	7650835559	7101970516	6910492082	97.02	97.3	41795852	39334525	219.322	951.288	139	313670	46.45	51.93	49907041	19415722	49907041	19415722	49.92	49.18	49907041	20866125	49907041	18386778	3345529869	42.42	2.01	0	9.28	0	0.66	0	0.51	0	0.00	0	10.79	0	41795852	0	250	0	246.16	0	2.43	0	0.03	0	2.06	0	0.02	0	156.81	0	0.46	0	953473	0	47477225	0	4406847	0	315168	0	241082	0	0	0	5125123	0	8480	0	0	0	154857	0	9857869	0	78781	0	10099987	0	78.75	0	37389005	0	237371	8302817	34.978228174461	47477225.0	41795852.0	953473.0	4406847.0	315168.0	241082.0	0.0	5125123.0	37389005.0	88.0	2.0	9.3	0.7	0.5	0.0	10.8	78.8	125	125	125.00	24	5934653125	27.1	22.9	22.7	27.2	0.0	34.4	24.9	bulk
1676044	SRR3532930	SRP059295	SRS1440213	SRX1767522	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154674: RNAseq_WT6_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154674		GSM2154674	RNAseq_WT6_cortex	15580238250	62320953	2016-05-26 12:42:58	8509292653	15580238250	62320953	2	62320953	index:0,count:62320953,average:125,stdev:0|index:1,count:62320953,average:125,stdev:0	GSM2154674_r1						2.03	2.97	0.37	10547136266	10215892643	9658345320	9383588020	96.86	97.16	55702892	52748684	216.948	876.804	160	416223	45.41	49.88	64601330	25297262	64601330	25297262	48.32	47.44	64601330	26917635	64601330	24059869	4726315064	44.81	1.94	0	8.00	0	0.54	0	0.46	0	0.00	0	9.61	0	55702892	0	250	0	246.42	0	2.43	0	0.03	0	2.06	0	0.02	0	210.86	0	0.46	0	1209794	0	62320953	0	4986089	0	339311	0	289572	0	0	0	5989178	0	11141	0	0	0	192406	0	12812764	0	102062	0	13118373	0	81.38	0	50716803	0	260062	10781139	41.456033561228	62320953.0	55702892.0	1209794.0	4986089.0	339311.0	289572.0	0.0	5989178.0	50716803.0	89.4	1.9	8.0	0.5	0.5	0.0	9.6	81.4	125	125	125.00	24	7790119125	27.3	22.7	22.6	27.4	0.0	34.6	25.2	bulk
1676060	SRR3532931	SRP059295	SRS1440215	SRX1767523	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154675: RNAseq_Nova1-KO1_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova1-ko|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154675		GSM2154675	RNAseq_Nova1-KO1_cortex	13493587250	53974349	2016-05-26 12:42:59	7414236812	13493587250	53974349	2	53974349	index:0,count:53974349,average:125,stdev:0|index:1,count:53974349,average:125,stdev:0	GSM2154675_r1						2.24	2.89	0.32	9065360959	8774147380	8246556880	8002366826	96.79	97.04	47999103	45299398	219.593	919.769	160	361326	45.54	50.38	56052682	21858075	56052682	21858075	48.86	47.84	56052682	23450297	56052682	20756637	3987737969	43.99	1.86	0	8.55	0	0.64	0	0.46	0	0.00	0	9.98	0	47999103	0	250	0	246.38	0	2.45	0	0.03	0	2.17	0	0.02	0	154.95	0	0.46	0	1004061	0	53974349	0	4612682	0	344994	0	245901	0	0	0	5384351	0	9191	0	0	0	180669	0	10972367	0	85295	0	11247522	0	80.38	0	43386421	0	249875	9192748	36.789386693347	53974349.0	47999103.0	1004061.0	4612682.0	344994.0	245901.0	0.0	5384351.0	43386421.0	88.9	1.9	8.5	0.6	0.5	0.0	10.0	80.4	125	125	125.00	24	6746793625	27.1	22.9	22.8	27.2	0.0	34.5	25.1	bulk
1676077	SRR3532932	SRP059295	SRS1440216	SRX1767524	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154676: RNAseq_Nova1-KO2_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova1-ko|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154676		GSM2154676	RNAseq_Nova1-KO2_cortex	14287017500	57148070	2016-05-26 12:42:59	7847776409	14287017500	57148070	2	57148070	index:0,count:57148070,average:125,stdev:0|index:1,count:57148070,average:125,stdev:0	GSM2154676_r1						2.08	2.79	0.5	9607204226	9324792676	8610843463	8378189341	97.06	97.3	50626227	47637391	220.692	932.770	160	372937	47.36	53.23	60663714	23974247	60663714	23974247	51.12	50.33	60663714	25881220	60663714	22666250	3944194157	41.05	1.85	0	9.78	0	0.73	0	0.45	0	0.00	0	10.24	0	50626227	0	250	0	246.25	0	2.43	0	0.02	0	2.10	0	0.02	0	179.37	0	0.46	0	1058878	0	57148070	0	5588839	0	417192	0	255455	0	0	0	5849196	0	10523	0	0	0	211051	0	12065845	0	87364	0	12374783	0	78.81	0	45037388	0	254136	10205481	40.157557370857	57148070.0	50626227.0	1058878.0	5588839.0	417192.0	255455.0	0.0	5849196.0	45037388.0	88.6	1.9	9.8	0.7	0.4	0.0	10.2	78.8	125	125	125.00	24	7143508750	26.9	23.1	23.0	27.0	0.0	34.6	25.2	bulk
1676093	SRR3532933	SRP059295	SRS1440217	SRX1767525	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154677: RNAseq_Nova1-KO3_cortex; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova1-ko|source_name;;cortex|strain background;;CD1|tissue compartment;;cortex|tissue;;brain	GEO Accession;;GSM2154677		GSM2154677	RNAseq_Nova1-KO3_cortex	12118093250	48472373	2016-05-26 12:42:59	6837764870	12118093250	48472373	2	48472373	index:0,count:48472373,average:125,stdev:0|index:1,count:48472373,average:125,stdev:0	GSM2154677_r1						2.19	2.85	0.42	7839239842	7616634322	6998118376	6814560551	97.16	97.38	41805990	39194673	220.103	981.575	139	308845	47.69	53.83	50685382	19936859	50685382	19936859	51.55	50.75	50685382	21552326	50685382	18795807	3164892638	40.37	1.92	0	9.84	0	0.84	0	0.41	0	0.00	0	12.50	0	41805990	0	250	0	245.59	0	2.42	0	0.02	0	2.11	0	0.02	0	209.74	0	0.49	0	930743	0	48472373	0	4768739	0	406825	0	200736	0	0	0	6058822	0	8143	0	0	0	180112	0	9770791	0	70816	0	10029862	0	76.41	0	37037251	0	239109	8194207	34.269755634460	48472373.0	41805990.0	930743.0	4768739.0	406825.0	200736.0	0.0	6058822.0	37037251.0	86.2	1.9	9.8	0.8	0.4	0.0	12.5	76.4	125	125	125.00	24	6059046625	26.9	23.1	23.0	27.0	0.0	34.2	24.7	bulk
1676109	SRR3532934	SRP059295	SRS1440218	SRX1767526	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154678: RNAseq_WT4_midhindbrain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;mid- and hind-brain|strain background;;CD1|tissue compartment;;mid- and hind-brain|tissue;;brain	GEO Accession;;GSM2154678		GSM2154678	RNAseq_WT4_midhindbrain	12745142000	50980568	2016-05-26 12:42:59	7035327833	12745142000	50980568	2	50980568	index:0,count:50980568,average:125,stdev:0|index:1,count:50980568,average:125,stdev:0	GSM2154678_r1						3.3	3.05	0.22	8799153521	8572527828	7697032438	7511303927	97.42	97.59	45330388	42176391	231.842	1005.203	160	335784	53.9	62.24	55001715	24434290	55001715	24434290	59.16	59.1	55001715	26818397	55001715	23201048	2812300321	31.96	1.64	0	11.92	0	0.60	0	0.39	0	0.00	0	10.09	0	45330388	0	250	0	246.46	0	2.39	0	0.02	0	2.06	0	0.02	0	171.20	0	0.47	0	835005	0	50980568	0	6074427	0	304298	0	199907	0	0	0	5145975	0	10929	0	0	0	168629	0	12383630	0	78920	0	12642108	0	77.00	0	39255961	0	248381	10693184	43.051537758524	50980568.0	45330388.0	835005.0	6074427.0	304298.0	199907.0	0.0	5145975.0	39255961.0	88.9	1.6	11.9	0.6	0.4	0.0	10.1	77.0	125	125	125.00	24	6372571000	26.6	23.4	23.2	26.9	0.0	34.6	25.1	bulk
1676125	SRR3532935	SRP059295	SRS1440219	SRX1767527	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154679: RNAseq_WT5_midhindbrain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;mid- and hind-brain|strain background;;CD1|tissue compartment;;mid- and hind-brain|tissue;;brain	GEO Accession;;GSM2154679		GSM2154679	RNAseq_WT5_midhindbrain	12136617250	48546469	2016-05-26 12:42:59	6701350679	12136617250	48546469	2	48546469	index:0,count:48546469,average:125,stdev:0|index:1,count:48546469,average:125,stdev:0	GSM2154679_r1						2.74	3.09	0.34	8135358557	7902781906	7213884484	7021864893	97.14	97.34	42887967	40094504	221.118	979.786	160	329873	51.68	58.79	51542610	22166622	51542610	22166622	55.97	55.89	51542610	24004918	51542610	21075035	2879203542	35.39	1.74	0	10.68	0	0.60	0	0.46	0	0.00	0	10.60	0	42887967	0	250	0	246.34	0	2.38	0	0.02	0	2.08	0	0.02	0	156.32	0	0.47	0	844149	0	48546469	0	5183020	0	291104	0	222127	0	0	0	5145271	0	10224	0	0	0	171655	0	11440424	0	78349	0	11700652	0	77.67	0	37704947	0	242853	9633645	39.668626700103	48546469.0	42887967.0	844149.0	5183020.0	291104.0	222127.0	0.0	5145271.0	37704947.0	88.3	1.7	10.7	0.6	0.5	0.0	10.6	77.7	125	125	125.00	24	6068308625	26.8	23.2	23.0	27.0	0.0	34.5	25.0	bulk
1676141	SRR3532936	SRP059295	SRS1440220	SRX1767528	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154680: RNAseq_WT6_midhindbrain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;wild-type|source_name;;mid- and hind-brain|strain background;;CD1|tissue compartment;;mid- and hind-brain|tissue;;brain	GEO Accession;;GSM2154680		GSM2154680	RNAseq_WT6_midhindbrain	13866006750	55464027	2016-05-26 12:42:59	7550088769	13866006750	55464027	2	55464027	index:0,count:55464027,average:125,stdev:0|index:1,count:55464027,average:125,stdev:0	GSM2154680_r1						2.95	3.13	0.24	9501130011	9242094163	8506739041	8293322992	97.27	97.49	49898553	46730074	220.171	934.982	160	384284	52.92	59.53	59102098	26406949	59102098	26406949	56.74	56.68	59102098	28312330	59102098	25144785	3335663693	35.11	1.80	0	9.98	0	0.49	0	0.44	0	0.00	0	9.11	0	49898553	0	250	0	246.58	0	2.38	0	0.02	0	2.00	0	0.02	0	217.27	0	0.45	0	996785	0	55464027	0	5536434	0	269569	0	242736	0	0	0	5053169	0	12501	0	0	0	194461	0	13807647	0	96742	0	14111351	0	79.98	0	44362119	0	260553	11620985	44.601232762624	55464027.0	49898553.0	996785.0	5536434.0	269569.0	242736.0	0.0	5053169.0	44362119.0	90.0	1.8	10.0	0.5	0.4	0.0	9.1	80.0	125	125	125.00	24	6933003375	26.9	23.0	22.8	27.2	0.0	34.6	25.2	bulk
1676158	SRR3532937	SRP059295	SRS1440221	SRX1767529	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154681: RNAseq_Nova1-KO1_midhindbrain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova1-ko|source_name;;mid- and hind-brain|strain background;;CD1|tissue compartment;;mid- and hind-brain|tissue;;brain	GEO Accession;;GSM2154681		GSM2154681	RNAseq_Nova1-KO1_midhindbrain	16099683750	64398735	2016-05-26 12:42:59	8789281420	16099683750	64398735	2	64398735	index:0,count:64398735,average:125,stdev:0|index:1,count:64398735,average:125,stdev:0	GSM2154681_r1						2.66	3.18	0.22	11012453674	10675220467	9945988252	9662287258	96.94	97.15	58161051	54687535	216.819	900.826	160	462616	51.14	56.97	68033662	29745104	68033662	29745104	54.65	54.32	68033662	31784367	68033662	28360044	4122439348	37.43	1.75	0	9.24	0	0.46	0	0.45	0	0.00	0	8.78	0	58161051	0	250	0	246.66	0	2.41	0	0.02	0	2.01	0	0.02	0	158.03	0	0.46	0	1126329	0	64398735	0	5953214	0	293840	0	291433	0	0	0	5652411	0	13958	0	0	0	220856	0	15662015	0	112184	0	16009013	0	81.07	0	52207837	0	273890	13108864	47.861783927854	64398735.0	58161051.0	1126329.0	5953214.0	293840.0	291433.0	0.0	5652411.0	52207837.0	90.3	1.7	9.2	0.5	0.5	0.0	8.8	81.1	125	125	125.00	24	8049841875	27.0	22.9	22.8	27.3	0.0	34.6	25.2	bulk
1676175	SRR3532938	SRP059295	SRS1440223	SRX1767530	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154682: RNAseq_Nova1-KO2_midhindbrain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova1-ko|source_name;;mid- and hind-brain|strain background;;CD1|tissue compartment;;mid- and hind-brain|tissue;;brain	GEO Accession;;GSM2154682		GSM2154682	RNAseq_Nova1-KO2_midhindbrain	12687851000	50751404	2016-05-26 12:42:59	6992385785	12687851000	50751404	2	50751404	index:0,count:50751404,average:125,stdev:0|index:1,count:50751404,average:125,stdev:0	GSM2154682_r1						2.56	3.02	0.35	7732671365	7487176973	6906604333	6702320393	96.83	97.04	43512795	40758263	200.170	1003.001	139	387149	49.85	56.12	52870885	21692554	52870885	21692554	53.22	53.31	52870885	23156309	52870885	20607743	2925398141	37.83	2.63	0	9.58	0	0.63	0	0.44	0	0.00	0	13.19	0	43512795	0	250	0	244.81	0	2.36	0	0.02	0	1.94	0	0.02	0	175.00	0	0.47	0	1334569	0	50751404	0	4859652	0	319623	0	224396	0	0	0	6694590	0	10016	0	0	0	147513	0	11107018	0	86903	0	11351450	0	76.16	0	38653143	0	245366	8856677	36.095779366334	50751404.0	43512795.0	1334569.0	4859652.0	319623.0	224396.0	0.0	6694590.0	38653143.0	85.7	2.6	9.6	0.6	0.4	0.0	13.2	76.2	125	125	125.00	24	6343925500	27.4	22.7	22.5	27.3	0.0	34.5	25.0	bulk
1676190	SRR3532939	SRP059295	SRS1440222	SRX1767531	SRA272264	GEO		RNAseq in E18.5 wild-type, Nova2-KO, and Nova1-KO mouse cortex and mid- and hind-brain	We sequenced mRNA from E18.5 mouse cortex (3 wild-type vs 3 Nova2-/- and 3 wild-type vs 3 Nova1-/-) and from E18.5 mouse mid- and hind-brain (3 wild-type vs 3 Nova1-/-) to compare gene expression level and alternative splicing events between wild-type and Nova mutant mice. Overall design: Mouse cortex or mid- and hind-brain mRNA profiles of embryonic 18.5 day wild type (WT), Nova2-/-, and Nova1-/- mice were generated by deep sequencing using Illumina Hiseq2500.		GSM2154683: RNAseq_Nova1-KO3_midhindbrain; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Trizol extraction Illumina High-throughput TruSeq RNA Sample preparation: ribozero selection	Illumina HiSeq 2500	developmental stage;;E18.5|genotype;;Nova1-ko|source_name;;mid- and hind-brain|strain background;;CD1|tissue compartment;;mid- and hind-brain|tissue;;brain	GEO Accession;;GSM2154683		GSM2154683	RNAseq_Nova1-KO3_midhindbrain	12286273000	49145092	2016-05-26 12:42:59	6712804096	12286273000	49145092	2	49145092	index:0,count:49145092,average:125,stdev:0|index:1,count:49145092,average:125,stdev:0	GSM2154683_r1						2.73	3.08	0.26	7458592476	7236791326	6626213372	6442745092	97.03	97.23	41966814	39142328	201.140	1028.709	138	371079	52.17	59.08	51553506	21893658	51553506	21893658	55.78	56.1	51553506	23409873	51553506	20788547	2620292892	35.13	2.56	0	9.99	0	0.63	0	0.43	0	0.00	0	13.55	0	41966814	0	250	0	244.77	0	2.37	0	0.02	0	1.91	0	0.02	0	179.25	0	0.46	0	1257548	0	49145092	0	4909930	0	309262	0	211175	0	0	0	6657841	0	10308	0	0	0	148881	0	11338226	0	87891	0	11585306	0	75.40	0	37056884	0	246254	9017538	36.618848830882	49145092.0	41966814.0	1257548.0	4909930.0	309262.0	211175.0	0.0	6657841.0	37056884.0	85.4	2.6	10.0	0.6	0.4	0.0	13.5	75.4	125	125	125.00	24	6143136500	27.3	22.8	22.7	27.1	0.0	34.5	25.0	bulk
1910858	SRR2063284	SRP059509	SRS961430	SRX1059057	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711965: Mouse islet polyA RNA-Seq biological replicate 1 CT0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711965		GSM1711965	Mouse islet polyA RNA-Seq biological replicate 1 CT0	12503799388	44829893	2015-11-10 17:09:03	6214012868	12503799388	44829893	2	44829893	index:0,count:44829893,average:138.91,stdev:17.65|index:1,count:44829893,average:140.01,stdev:17.00	GSM1711965_r1				in_mesa	26542580	5.63	3.22	0.05	6452385043	6435061406	5992496040	6003786941	99.73	100.19	39416075	34202204	198.131	1012.886	128	272891	87.35	94.26	43649891	34428954	43649891	34428954	89.98	90.33	43649891	35465005	43649891	32995528	288120226	4.47	0.28	0	6.45	0	0.22	0	0.07	0	0.00	0	11.79	0	39416449	0	278	0	272.61	0	1.95	0	0.01	0	1.24	0	0.01	0	106.53	0	0.78	0	125084	0	44829893	0	2890625	0	99311	0	29407	0	0	0	5284726	0	13329	0	0	0	136532	0	28220910	0	43211	0	28413982	0	81.48	0	36525824	0	217071	18426983	84.889197543661	44829893.0	39416449.0	125084.0	2890625.0	99311.0	29407.0	0.0	5284726.0	36525824.0	87.9	0.3	6.4	0.2	0.1	0.0	11.8	81.5	35	151	138.91	7	6227154776	25.6	24.1	25.2	25.1	0.0	32.9	20.9	bulk
1910873	SRR2063285	SRP059509	SRS961429	SRX1059058	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711966: Mouse islet polyA RNA-Seq biological replicate 1 CT4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711966		GSM1711966	Mouse islet polyA RNA-Seq biological replicate 1 CT4	9550346890	34369796	2015-11-10 17:09:03	4732016493	9550346890	34369796	2	34369796	index:0,count:34369796,average:138.39,stdev:17.83|index:1,count:34369796,average:139.48,stdev:17.23	GSM1711966_r1				in_mesa	26542580	4.13	3.25	0.05	4902071457	4887447548	4611405354	4616831940	99.7	100.12	30467983	26180998	196.848	1084.549	128	214412	88.17	93.89	33332812	26863269	33332812	26863269	89.57	90.0	33332812	27291294	33332812	25750795	239726429	4.89	0.13	0	5.40	0	0.26	0	0.07	0	0.00	0	11.02	0	30468261	0	277	0	271.68	0	1.82	0	0.01	0	1.24	0	0.00	0	122.75	0	0.76	0	43828	0	34369796	0	1855717	0	89542	0	23367	0	0	0	3788626	0	10423	0	0	0	113140	0	22163833	0	32301	0	22319697	0	83.25	0	28612544	0	213752	14220480	66.527938919870	34369796.0	30468261.0	43828.0	1855717.0	89542.0	23367.0	0.0	3788626.0	28612544.0	88.6	0.1	5.4	0.3	0.1	0.0	11.0	83.2	35	151	138.39	7	4756442731	25.6	24.4	25.1	24.9	0.0	32.9	20.9	bulk
1910889	SRR2063286	SRP059509	SRS961428	SRX1059059	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711967: Mouse islet polyA RNA-Seq biological replicate 1 CT8; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711967		GSM1711967	Mouse islet polyA RNA-Seq biological replicate 1 CT8	9926992414	35915373	2015-11-10 17:09:03	4928604306	9926992414	35915373	2	35915373	index:0,count:35915373,average:137.60,stdev:18.19|index:1,count:35915373,average:138.80,stdev:17.60	GSM1711967_r1				in_mesa	26542580	3.71	3.16	0.05	4996567498	4982338723	4725956571	4730864085	99.72	100.1	31677006	27288635	193.453	1069.626	128	238585	87.76	92.97	34427670	27801237	34427670	27801237	88.73	89.11	34427670	28106994	34427670	26649229	290224655	5.81	0.19	0	4.94	0	0.24	0	0.07	0	0.00	0	11.49	0	31677320	0	276	0	269.99	0	1.80	0	0.01	0	1.20	0	0.01	0	119.50	0	0.76	0	67969	0	35915373	0	1772828	0	85685	0	25346	0	0	0	4127022	0	10357	0	0	0	115679	0	22573255	0	34272	0	22733563	0	83.26	0	29904492	0	216899	14284691	65.858722262436	35915373.0	31677320.0	67969.0	1772828.0	85685.0	25346.0	0.0	4127022.0	29904492.0	88.2	0.2	4.9	0.2	0.1	0.0	11.5	83.3	35	151	137.60	7	4942027474	25.7	24.4	25.2	24.7	0.0	32.9	20.8	bulk
1910907	SRR2063287	SRP059509	SRS961425	SRX1059060	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711968: Mouse islet polyA RNA-Seq biological replicate 1 CT12; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711968		GSM1711968	Mouse islet polyA RNA-Seq biological replicate 1 CT12	7859666572	28093413	2015-11-10 17:09:03	3909023124	7859666572	28093413	2	28093413	index:0,count:28093413,average:139.35,stdev:16.97|index:1,count:28093413,average:140.41,stdev:16.33	GSM1711968_r1				in_mesa	26542580	3.78	3.11	0.05	4027878609	4007969789	3822822715	3817266642	99.51	99.85	24720148	21438019	197.393	1053.765	128	182091	86.65	91.46	26695694	21420407	26695694	21420407	87.45	87.74	26695694	21617226	26695694	20549020	290891470	7.22	0.20	0	4.63	0	0.21	0	0.07	0	0.00	0	11.73	0	24720410	0	279	0	273.45	0	1.76	0	0.01	0	1.22	0	0.01	0	144.69	0	0.78	0	55851	0	28093413	0	1301081	0	57875	0	21037	0	0	0	3294091	0	8048	0	0	0	90507	0	17445556	0	27133	0	17571244	0	83.36	0	23419329	0	205471	11259363	54.797820617021	28093413.0	24720410.0	55851.0	1301081.0	57875.0	21037.0	0.0	3294091.0	23419329.0	88.0	0.2	4.6	0.2	0.1	0.0	11.7	83.4	35	151	139.35	7	3914933178	25.7	24.5	25.2	24.6	0.0	32.8	20.8	bulk
1910924	SRR2063288	SRP059509	SRS961427	SRX1059061	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711969: Mouse islet polyA RNA-Seq biological replicate 1 CT16; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711969		GSM1711969	Mouse islet polyA RNA-Seq biological replicate 1 CT16	6986279816	25294936	2015-11-10 17:09:03	3478265914	6986279816	25294936	2	25294936	index:0,count:25294936,average:137.41,stdev:18.20|index:1,count:25294936,average:138.78,stdev:17.55	GSM1711969_r1				in_mesa	26542580	4.98	3.0	0.04	3441118972	3434870566	3223118886	3231177148	99.82	100.25	21955699	19127145	191.710	991.882	127	169593	87.86	93.97	24068456	19290955	24068456	19290955	89.45	89.88	24068456	19640594	24068456	18451776	160180854	4.65	0.33	0	5.64	0	0.19	0	0.06	0	0.00	0	12.95	0	21955914	0	276	0	269.25	0	2.07	0	0.01	0	1.30	0	0.01	0	58.08	0	0.79	0	83008	0	25294936	0	1426208	0	47290	0	15481	0	0	0	3276251	0	6755	0	0	0	72740	0	15518209	0	24594	0	15622298	0	81.16	0	20529706	0	190516	9762972	51.244892817401	25294936.0	21955914.0	83008.0	1426208.0	47290.0	15481.0	0.0	3276251.0	20529706.0	86.8	0.3	5.6	0.2	0.1	0.0	13.0	81.2	35	151	137.41	7	3475822634	25.7	24.3	25.5	24.6	0.0	32.8	20.8	bulk
1910940	SRR2063289	SRP059509	SRS961426	SRX1059062	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711970: Mouse islet polyA RNA-Seq biological replicate 1 CT020; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711970		GSM1711970	Mouse islet polyA RNA-Seq biological replicate 1 CT020	5926118028	21567597	2015-11-10 17:09:03	2943124080	5926118028	21567597	2	21567597	index:0,count:21567597,average:136.73,stdev:19.03|index:1,count:21567597,average:138.04,stdev:18.43	GSM1711970_r1				in_mesa	26542580	4.14	3.1	0.05	2998519373	2985324827	2834600395	2832605787	99.56	99.93	18988696	16471208	193.093	1041.593	127	138347	87.63	92.89	20610378	16640169	20610378	16640169	88.82	89.18	20610378	16865857	20610378	15977154	173150244	5.77	0.21	0	4.98	0	0.20	0	0.07	0	0.00	0	11.69	0	18988890	0	274	0	268.09	0	1.79	0	0.01	0	1.24	0	0.01	0	60.10	0	0.77	0	44607	0	21567597	0	1074247	0	43072	0	15134	0	0	0	2520501	0	6276	0	0	0	67048	0	13495962	0	21423	0	13590709	0	83.06	0	17914643	0	189937	8577559	45.160021480807	21567597.0	18988890.0	44607.0	1074247.0	43072.0	15134.0	0.0	2520501.0	17914643.0	88.0	0.2	5.0	0.2	0.1	0.0	11.7	83.1	35	151	136.73	7	2948891533	25.6	24.4	25.3	24.6	0.0	32.9	20.8	bulk
1911052	SRR2063290	SRP059509	SRS961424	SRX1059063	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711971: Mouse islet polyA RNA-Seq biological replicate 1 CT24; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711971		GSM1711971	Mouse islet polyA RNA-Seq biological replicate 1 CT24	11676381709	42404469	2015-11-10 17:09:03	5820912191	11676381709	42404469	2	42404469	index:0,count:42404469,average:137.03,stdev:18.66|index:1,count:42404469,average:138.33,stdev:18.06	GSM1711971_r1				in_mesa	26542580	4.86	2.99	0.04	5771022097	5765919703	5402919554	5420034377	99.91	100.32	36924409	32238208	192.467	974.065	127	275706	89.06	95.33	40524312	32885439	40524312	32885439	91.04	91.49	40524312	33615249	40524312	31560003	203630006	3.53	0.28	0	5.73	0	0.20	0	0.05	0	0.00	0	12.67	0	36924776	0	275	0	268.41	0	1.82	0	0.01	0	1.23	0	0.01	0	122.32	0	0.78	0	118460	0	42404469	0	2429920	0	82743	0	23138	0	0	0	5373812	0	11671	0	0	0	121996	0	26506425	0	41210	0	26681302	0	81.35	0	34494856	0	216889	16734556	77.157237112071	42404469.0	36924776.0	118460.0	2429920.0	82743.0	23138.0	0.0	5373812.0	34494856.0	87.1	0.3	5.7	0.2	0.1	0.0	12.7	81.3	35	151	137.03	7	5810620418	25.7	24.4	25.5	24.3	0.0	32.7	20.6	bulk
1911068	SRR2063291	SRP059509	SRS961423	SRX1059064	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711972: Mouse islet polyA RNA-Seq biological replicate 1 CT28; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711972		GSM1711972	Mouse islet polyA RNA-Seq biological replicate 1 CT28	8797308220	32005649	2015-11-10 17:09:03	4380285960	8797308220	32005649	2	32005649	index:0,count:32005649,average:136.75,stdev:19.09|index:1,count:32005649,average:138.12,stdev:18.44	GSM1711972_r1				in_mesa	26542580	4.56	3.19	0.05	4462178156	4452428275	4188404612	4196862935	99.78	100.2	28134414	24478313	193.965	989.677	127	203221	88.27	94.26	30835776	24833382	30835776	24833382	89.91	90.37	30835776	25294733	30835776	23808005	200748039	4.50	0.14	0	5.59	0	0.20	0	0.06	0	0.00	0	11.83	0	28134674	0	274	0	268.21	0	1.86	0	0.01	0	1.26	0	0.01	0	120.52	0	0.78	0	45298	0	32005649	0	1788912	0	63910	0	20217	0	0	0	3786848	0	9065	0	0	0	95390	0	19829353	0	30285	0	19964093	0	82.32	0	26345762	0	206425	12700622	61.526568971782	32005649.0	28134674.0	45298.0	1788912.0	63910.0	20217.0	0.0	3786848.0	26345762.0	87.9	0.1	5.6	0.2	0.1	0.0	11.8	82.3	35	151	136.75	7	4376657350	25.7	24.4	25.2	24.7	0.0	32.8	20.7	bulk
1911086	SRR2063292	SRP059509	SRS961422	SRX1059065	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711973: Mouse islet polyA RNA-Seq biological replicate 1 CT32; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711973		GSM1711973	Mouse islet polyA RNA-Seq biological replicate 1 CT32	4922015640	17869953	2015-11-10 17:09:03	2453053994	4922015640	17869953	2	17869953	index:0,count:17869953,average:137.07,stdev:18.85|index:1,count:17869953,average:138.36,stdev:18.23	GSM1711973_r1				in_mesa	26542580	3.94	3.09	0.06	2484527058	2469948420	2357362317	2351988172	99.41	99.77	15641358	13657952	192.196	1004.892	127	115123	85.93	90.72	16890538	13440654	16890538	13440654	86.78	87.05	16890538	13573582	16890538	12895704	196308239	7.90	0.15	0	4.63	0	0.21	0	0.08	0	0.00	0	12.18	0	15641497	0	275	0	268.73	0	1.75	0	0.01	0	1.20	0	0.01	0	103.26	0	0.77	0	27160	0	17869953	0	826576	0	36928	0	14146	0	0	0	2177382	0	4902	0	0	0	54276	0	10681597	0	17087	0	10757862	0	82.90	0	14814921	0	181243	6817960	37.617783859239	17869953.0	15641497.0	27160.0	826576.0	36928.0	14146.0	0.0	2177382.0	14814921.0	87.5	0.2	4.6	0.2	0.1	0.0	12.2	82.9	35	151	137.07	7	2449511423	26.0	24.3	25.2	24.6	0.0	32.8	20.7	bulk
1911101	SRR2063293	SRP059509	SRS961421	SRX1059066	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711974: Mouse islet polyA RNA-Seq biological replicate 1 CT36; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711974		GSM1711974	Mouse islet polyA RNA-Seq biological replicate 1 CT36	6699706719	24344916	2015-11-10 17:09:03	3346832127	6699706719	24344916	2	24344916	index:0,count:24344916,average:137.07,stdev:18.81|index:1,count:24344916,average:138.13,stdev:18.28	GSM1711974_r1				in_mesa	26542580	3.45	3.28	0.06	3349206067	3332153501	3169074172	3166246931	99.49	99.91	21317169	18411326	190.898	1045.053	127	157237	86.27	91.35	23181130	18391220	23181130	18391220	87.15	87.53	23181130	18579096	23181130	17622632	247152942	7.38	0.14	0	4.87	0	0.24	0	0.08	0	0.00	0	12.11	0	21317365	0	275	0	268.17	0	1.72	0	0.01	0	1.19	0	0.01	0	117.32	0	0.80	0	35160	0	24344916	0	1184630	0	59186	0	19614	0	0	0	2948751	0	7024	0	0	0	75829	0	14702151	0	21224	0	14806228	0	82.70	0	20132735	0	202369	9322406	46.066373802312	24344916.0	21317365.0	35160.0	1184630.0	59186.0	19614.0	0.0	2948751.0	20132735.0	87.6	0.1	4.9	0.2	0.1	0.0	12.1	82.7	35	151	137.07	7	3336918857	25.9	24.3	24.9	24.9	0.0	32.7	20.6	bulk
1911116	SRR2063294	SRP059509	SRS961420	SRX1059067	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711975: Mouse islet polyA RNA-Seq biological replicate 1 CT40; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711975		GSM1711975	Mouse islet polyA RNA-Seq biological replicate 1 CT40	6047314974	22149672	2015-11-10 17:09:03	3024445491	6047314974	22149672	2	22149672	index:0,count:22149672,average:135.68,stdev:19.45|index:1,count:22149672,average:137.35,stdev:18.76	GSM1711975_r1				in_mesa	26542580	4.56	3.16	0.06	2944427609	2930335447	2763627485	2762707895	99.52	99.97	19249938	16767611	186.435	988.818	128	151642	86.77	92.57	21069819	16703144	21069819	16703144	88.35	88.73	21069819	17007697	21069819	16011298	180558380	6.13	0.15	0	5.44	0	0.21	0	0.07	0	0.00	0	12.80	0	19250142	0	273	0	265.85	0	1.80	0	0.01	0	1.21	0	0.01	0	123.63	0	0.80	0	32596	0	22149672	0	1205586	0	47515	0	15996	0	0	0	2836019	0	5969	0	0	0	64672	0	13015894	0	20165	0	13106700	0	81.47	0	18044556	0	186211	8073185	43.355038101938	22149672.0	19250142.0	32596.0	1205586.0	47515.0	15996.0	0.0	2836019.0	18044556.0	86.9	0.1	5.4	0.2	0.1	0.0	12.8	81.5	35	151	135.68	7	3005162944	26.0	24.0	25.0	24.9	0.0	32.8	20.7	bulk
1911133	SRR2063295	SRP059509	SRS961419	SRX1059068	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711976: Mouse islet polyA RNA-Seq biological replicate 1 CT44; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711976		GSM1711976	Mouse islet polyA RNA-Seq biological replicate 1 CT44	8058438218	29287888	2015-11-10 17:09:03	4019721223	8058438218	29287888	2	29287888	index:0,count:29287888,average:136.90,stdev:18.93|index:1,count:29287888,average:138.24,stdev:18.31	GSM1711976_r1				in_mesa	26542580	5.12	3.12	0.05	4051296272	4030676543	3812853553	3808312592	99.49	99.88	25546633	22286674	191.354	1002.069	127	185731	86.83	92.42	27793245	22181939	27793245	22181939	88.37	88.68	27793245	22574714	27793245	21284434	249293889	6.15	0.15	0	5.27	0	0.17	0	0.07	0	0.00	0	12.53	0	25546877	0	275	0	268.28	0	1.85	0	0.01	0	1.24	0	0.01	0	107.15	0	0.78	0	43662	0	29287888	0	1544807	0	49608	0	20314	0	0	0	3671089	0	7913	0	0	0	88093	0	17682752	0	28006	0	17806764	0	81.95	0	24002070	0	198602	11267852	56.735843546389	29287888.0	25546877.0	43662.0	1544807.0	49608.0	20314.0	0.0	3671089.0	24002070.0	87.2	0.1	5.3	0.2	0.1	0.0	12.5	82.0	35	151	136.90	7	4009646144	26.2	24.0	25.0	24.8	0.0	32.8	20.6	bulk
1911148	SRR2063296	SRP059509	SRS961418	SRX1059069	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711977: Mouse islet polyA RNA-Seq biological replicate 2 CT0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711977		GSM1711977	Mouse islet polyA RNA-Seq biological replicate 2 CT0	4233181872	28055847	2015-11-10 17:09:03	1781188127	4233181872	28055847	2	28055847	index:0,count:28055847,average:75.44,stdev:1.40|index:1,count:28055847,average:75.44,stdev:1.42	GSM1711977_r1				in_mesa	26542580	5.01	3.11	0.05	3543903315	3531613124	3292968931	3299909960	99.65	100.21	27170599	25830356	158.043	432.807	126	344507	87.31	94.05	30168470	23724353	30168470	23724353	90.26	90.76	30168470	24525777	30168470	22895184	161845483	4.57	0.20	0	6.93	0	0.25	0	0.09	0	0.00	0	2.81	0	27171444	0	150	0	149.65	0	1.90	0	0.01	0	1.25	0	0.01	0	306.06	0	0.37	0	55677	0	28055847	0	1945492	0	70004	0	26378	0	0	0	788021	0	4130	0	0	0	42727	0	9193166	0	15253	0	9255276	0	89.91	0	25225952	0	183008	8796152	48.064303199860	28055847.0	27171444.0	55677.0	1945492.0	70004.0	26378.0	0.0	788021.0	25225952.0	96.8	0.2	6.9	0.2	0.1	0.0	2.8	89.9	35	76	75.44	7	2116624699	25.0	24.3	25.4	25.3	0.0	34.9	24.3	bulk
1911165	SRR2063297	SRP059509	SRS961417	SRX1059070	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711978: Mouse islet polyA RNA-Seq biological replicate 2 CT4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711978		GSM1711978	Mouse islet polyA RNA-Seq biological replicate 2 CT4	4337349933	28733958	2015-11-10 17:09:03	1823589804	4337349933	28733958	2	28733958	index:0,count:28733958,average:75.48,stdev:1.16|index:1,count:28733958,average:75.47,stdev:1.20	GSM1711978_r1				in_mesa	26542580	4.45	3.29	0.06	3649266672	3630078212	3396879742	3398312931	99.47	100.04	27620384	26159037	161.226	460.991	127	336506	87.19	93.74	30673013	24083259	30673013	24083259	89.98	90.53	30673013	24853537	30673013	23257881	176660358	4.84	0.23	0	6.71	0	0.28	0	0.09	0	0.00	0	3.50	0	27621227	0	150	0	149.71	0	1.80	0	0.01	0	1.29	0	0.01	0	161.88	0	0.37	0	67041	0	28733958	0	1929102	0	79853	0	27146	0	0	0	1005732	0	4364	0	0	0	45559	0	9215909	0	14976	0	9280808	0	89.41	0	25692125	0	190436	8887958	46.671627213342	28733958.0	27621227.0	67041.0	1929102.0	79853.0	27146.0	0.0	1005732.0	25692125.0	96.1	0.2	6.7	0.3	0.1	0.0	3.5	89.4	35	76	75.48	7	2168814851	25.1	24.3	25.1	25.5	0.0	34.9	24.3	bulk
1911180	SRR2063298	SRP059509	SRS961416	SRX1059071	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711979: Mouse islet polyA RNA-Seq biological replicate 2 CT8; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711979		GSM1711979	Mouse islet polyA RNA-Seq biological replicate 2 CT8	4234615036	28047849	2015-11-10 17:09:03	1777691434	4234615036	28047849	2	28047849	index:0,count:28047849,average:75.49,stdev:1.04|index:1,count:28047849,average:75.49,stdev:1.08	GSM1711979_r1				in_mesa	26542580	4.28	3.23	0.06	3644548807	3620202906	3423880231	3417003314	99.33	99.8	27098082	25657701	164.146	465.274	127	331008	86.25	91.84	29654847	23372184	29654847	23372184	88.57	88.91	29654847	24002835	29654847	22626086	246266731	6.76	0.21	0	5.89	0	0.24	0	0.11	0	0.00	0	3.03	0	27099001	0	150	0	149.78	0	1.69	0	0.01	0	1.19	0	0.00	0	282.84	0	0.37	0	57675	0	28047849	0	1650949	0	68214	0	30067	0	0	0	850567	0	4203	0	0	0	45525	0	8884871	0	13947	0	8948546	0	90.73	0	25448052	0	189177	8674366	45.853174540245	28047849.0	27099001.0	57675.0	1650949.0	68214.0	30067.0	0.0	850567.0	25448052.0	96.6	0.2	5.9	0.2	0.1	0.0	3.0	90.7	35	76	75.49	7	2117380331	25.3	24.1	25.0	25.6	0.0	34.9	24.4	bulk
1911195	SRR2063299	SRP059509	SRS961415	SRX1059072	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711980: Mouse islet polyA RNA-Seq biological replicate 2 CT12; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711980		GSM1711980	Mouse islet polyA RNA-Seq biological replicate 2 CT12	2521334596	16695716	2015-11-10 17:09:03	1069042036	2521334596	16695716	2	16695716	index:0,count:16695716,average:75.51,stdev:0.94|index:1,count:16695716,average:75.51,stdev:0.99	GSM1711980_r1				in_mesa	26542580	4.07	3.09	0.06	2245428833	2231939182	2122969172	2118895895	99.4	99.81	16023124	14748224	194.552	664.455	138	144049	85.65	90.63	17369465	13724639	17369465	13724639	87.41	87.66	17369465	14006047	17369465	13274416	178663328	7.96	0.33	0	5.27	0	0.22	0	0.11	0	0.00	0	3.70	0	16023628	0	151	0	149.78	0	1.82	0	0.01	0	1.26	0	0.01	0	264.78	0	0.38	0	54456	0	16695716	0	880627	0	36742	0	17759	0	0	0	617587	0	2529	0	0	0	27433	0	5277479	0	9265	0	5316706	0	90.70	0	15143001	0	169743	5257579	30.973760331796	16695716.0	16023628.0	54456.0	880627.0	36742.0	17759.0	0.0	617587.0	15143001.0	96.0	0.3	5.3	0.2	0.1	0.0	3.7	90.7	35	76	75.51	7	1260673277	24.8	24.7	25.4	25.2	0.0	34.9	24.2	bulk
1912843	SRR2063300	SRP059509	SRS961414	SRX1059073	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711981: Mouse islet polyA RNA-Seq biological replicate 2 CT16; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711981		GSM1711981	Mouse islet polyA RNA-Seq biological replicate 2 CT16	4467615624	29594219	2015-11-10 17:09:03	1885583645	4467615624	29594219	2	29594219	index:0,count:29594219,average:75.48,stdev:1.10|index:1,count:29594219,average:75.48,stdev:1.14	GSM1711981_r1				in_mesa	26542580	4.83	3.26	0.05	3784769031	3764697210	3533044675	3532717183	99.47	99.99	28444994	26983662	160.136	452.810	127	363467	87.26	93.52	31374196	24821437	31374196	24821437	90.0	90.44	31374196	25601564	31374196	24004807	193342875	5.11	0.21	0	6.43	0	0.24	0	0.09	0	0.00	0	3.54	0	28445912	0	150	0	149.73	0	1.73	0	0.01	0	1.22	0	0.00	0	287.94	0	0.37	0	63176	0	29594219	0	1903239	0	72123	0	28114	0	0	0	1048070	0	4394	0	0	0	47413	0	9489399	0	15338	0	9556544	0	89.69	0	26542673	0	192377	9205233	47.849966472083	29594219.0	28445912.0	63176.0	1903239.0	72123.0	28114.0	0.0	1048070.0	26542673.0	96.1	0.2	6.4	0.2	0.1	0.0	3.5	89.7	35	76	75.48	7	2233917103	25.3	24.0	25.0	25.6	0.0	34.8	24.1	bulk
1912862	SRR2063301	SRP059509	SRS961413	SRX1059074	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711982: Mouse islet polyA RNA-Seq biological replicate 2 CT020; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711982		GSM1711982	Mouse islet polyA RNA-Seq biological replicate 2 CT020	3398514794	22513371	2015-11-10 17:09:03	1426244971	3398514794	22513371	2	22513371	index:0,count:22513371,average:75.48,stdev:1.11|index:1,count:22513371,average:75.48,stdev:1.15	GSM1711982_r1				in_mesa	26542580	5.28	3.23	0.06	2856570296	2830666589	2670762711	2660202154	99.09	99.6	21717824	20727015	155.074	420.911	127	293302	85.54	91.52	23843526	18578219	23843526	18578219	88.29	88.59	23843526	19174731	23843526	17984771	195474303	6.84	0.18	0	6.30	0	0.22	0	0.11	0	0.00	0	3.20	0	21718575	0	150	0	149.77	0	1.67	0	0.01	0	1.21	0	0.01	0	290.50	0	0.36	0	41319	0	22513371	0	1418178	0	50113	0	25277	0	0	0	719406	0	3264	0	0	0	36029	0	7005579	0	11250	0	7056122	0	90.17	0	20300397	0	176208	6748725	38.299765050395	22513371.0	21718575.0	41319.0	1418178.0	50113.0	25277.0	0.0	719406.0	20300397.0	96.5	0.2	6.3	0.2	0.1	0.0	3.2	90.2	35	76	75.48	7	1699259917	25.6	23.7	25.0	25.7	0.0	34.9	24.3	bulk
1912879	SRR2063302	SRP059509	SRS961412	SRX1059075	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711983: Mouse islet polyA RNA-Seq biological replicate 2 CT24; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711983		GSM1711983	Mouse islet polyA RNA-Seq biological replicate 2 CT24	4453853469	29512396	2015-11-10 17:09:03	1873158341	4453853469	29512396	2	29512396	index:0,count:29512396,average:75.46,stdev:1.26|index:1,count:29512396,average:75.45,stdev:1.30	GSM1711983_r1				in_mesa	26542580	5.52	3.2	0.05	3652955817	3632373362	3384062229	3383953725	99.44	100.0	28349887	27162764	150.711	387.130	127	396140	86.26	93.19	31574250	24456181	31574250	24456181	89.5	89.94	31574250	25372724	31574250	23602228	192005569	5.26	0.18	0	7.14	0	0.22	0	0.10	0	0.00	0	3.61	0	28350869	0	150	0	149.69	0	1.82	0	0.01	0	1.27	0	0.01	0	256.01	0	0.37	0	53352	0	29512396	0	2108621	0	66187	0	29155	0	0	0	1066185	0	4174	0	0	0	44759	0	9316478	0	15545	0	9380956	0	88.92	0	26242248	0	184821	8871705	48.001606960248	29512396.0	28350869.0	53352.0	2108621.0	66187.0	29155.0	0.0	1066185.0	26242248.0	96.1	0.2	7.1	0.2	0.1	0.0	3.6	88.9	35	76	75.46	7	2227003227	25.4	24.1	25.1	25.5	0.0	34.8	24.0	bulk
1912975	SRR2063308	SRP059509	SRS961406	SRX1059081	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711989: Mouse islet polyA RNA-Seq biological replicate 3 CT0; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711989		GSM1711989	Mouse islet polyA RNA-Seq biological replicate 3 CT0	5107768792	33851848	2015-11-10 17:09:03	2177743173	5107768792	33851848	2	33851848	index:0,count:33851848,average:75.45,stdev:1.34|index:1,count:33851848,average:75.43,stdev:1.40	GSM1711989_r1				in_mesa	26542580	3.85	3.46	0.07	4335276953	4304109294	3972563003	3974301138	99.28	100.04	32612789	31331338	153.794	355.818	130	483584	86.01	93.93	37199085	28050733	37199085	28050733	89.87	90.58	37199085	29310420	37199085	27052547	204120178	4.71	0.16	0	8.12	0	0.44	0	0.10	0	0.00	0	3.12	0	32614288	0	150	0	149.60	0	1.73	0	0.01	0	1.25	0	0.01	0	144.05	0	0.41	0	53512	0	33851848	0	2749698	0	149910	0	32673	0	0	0	1054977	0	4910	0	0	0	46524	0	9764913	0	14445	0	9830792	0	88.22	0	29864590	0	185664	9645547	51.951627671493	33851848.0	32614288.0	53512.0	2749698.0	149910.0	32673.0	0.0	1054977.0	29864590.0	96.3	0.2	8.1	0.4	0.1	0.0	3.1	88.2	35	76	75.45	7	2554255737	25.8	23.7	23.9	26.7	0.0	34.8	24.2	bulk
1912991	SRR2063309	SRP059509	SRS961405	SRX1059082	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711990: Mouse islet polyA RNA-Seq biological replicate 3 CT4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711990		GSM1711990	Mouse islet polyA RNA-Seq biological replicate 3 CT4	6038121880	40129162	2015-11-10 17:09:03	2580385156	6038121880	40129162	2	40129162	index:0,count:40129162,average:75.24,stdev:2.45|index:1,count:40129162,average:75.23,stdev:2.47	GSM1711990_r1				in_mesa	26542580	5.07	3.52	0.07	4862087685	4819609359	4426832181	4422239871	99.13	99.9	38566775	37338870	143.001	314.051	127	577245	85.84	94.44	44155586	33106748	44155586	33106748	90.42	91.16	44155586	34875124	44155586	31957247	198470187	4.08	0.17	0	8.75	0	0.30	0	0.11	0	0.00	0	3.47	0	38568573	0	150	0	149.27	0	1.66	0	0.01	0	1.26	0	0.01	0	274.65	0	0.41	0	66435	0	40129162	0	3511594	0	122058	0	45319	0	0	0	1393212	0	5032	0	0	0	47640	0	10788010	0	17846	0	10858528	0	87.36	0	35056979	0	172318	10185021	59.105961071972	40129162.0	38568573.0	66435.0	3511594.0	122058.0	45319.0	0.0	1393212.0	35056979.0	96.1	0.2	8.8	0.3	0.1	0.0	3.5	87.4	35	76	75.24	7	3019353589	26.2	23.4	23.8	26.6	0.0	34.8	24.1	bulk
1913119	SRR2063311	SRP059509	SRS961403	SRX1059084	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711992: Mouse islet polyA RNA-Seq biological replicate 3 CT12; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711992		GSM1711992	Mouse islet polyA RNA-Seq biological replicate 3 CT12	4308911976	28539005	2015-11-10 17:09:03	1837369238	4308911976	28539005	2	28539005	index:0,count:28539005,average:75.50,stdev:1.04|index:1,count:28539005,average:75.48,stdev:1.11	GSM1711992_r1				in_mesa	26542580	4.96	3.15	0.06	3771478704	3739732695	3515128973	3502157371	99.16	99.63	27497449	25860027	168.748	506.220	132	361558	85.46	91.67	30467317	23499909	30467317	23499909	88.61	88.85	30467317	24366351	30467317	22776716	261052381	6.92	0.17	0	6.53	0	0.34	0	0.11	0	0.00	0	3.19	0	27498702	0	150	0	149.66	0	1.72	0	0.00	0	1.24	0	0.00	0	127.00	0	0.40	0	49234	0	28539005	0	1863683	0	97927	0	32754	0	0	0	909622	0	4443	0	0	0	48250	0	9610833	0	15348	0	9678874	0	89.82	0	25635019	0	195656	9608496	49.109130310341	28539005.0	27498702.0	49234.0	1863683.0	97927.0	32754.0	0.0	909622.0	25635019.0	96.4	0.2	6.5	0.3	0.1	0.0	3.2	89.8	35	76	75.50	7	2154670639	24.7	24.0	25.4	25.9	0.0	34.8	24.3	bulk
1913134	SRR2063312	SRP059509	SRS961402	SRX1059085	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711993: Mouse islet polyA RNA-Seq biological replicate 3 CT16; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711993		GSM1711993	Mouse islet polyA RNA-Seq biological replicate 3 CT16	4714633643	31294639	2015-11-10 17:09:03	2019578628	4714633643	31294639	2	31294639	index:0,count:31294639,average:75.33,stdev:1.97|index:1,count:31294639,average:75.32,stdev:1.99	GSM1711993_r1				in_mesa	26542580	9.02	3.28	0.05	3687400169	3640407559	3300975605	3287347144	98.73	99.59	30001126	28992127	137.603	329.921	116	474001	82.71	92.43	34587678	24815460	34587678	24815460	88.92	89.26	34587678	26678742	34587678	23962926	206739296	5.61	0.16	0	10.08	0	0.27	0	0.12	0	0.00	0	3.74	0	30002466	0	150	0	149.36	0	1.73	0	0.01	0	1.27	0	0.01	0	277.49	0	0.41	0	49761	0	31294639	0	3155298	0	84617	0	37528	0	0	0	1170028	0	4049	0	0	0	42551	0	9149625	0	14229	0	9210454	0	85.79	0	26847168	0	174340	8485522	48.672261099002	31294639.0	30002466.0	49761.0	3155298.0	84617.0	37528.0	0.0	1170028.0	26847168.0	95.9	0.2	10.1	0.3	0.1	0.0	3.7	85.8	35	76	75.33	7	2357481456	26.1	22.6	24.4	26.8	0.0	34.7	24.0	bulk
1913150	SRR2063313	SRP059509	SRS961401	SRX1059086	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711994: Mouse islet polyA RNA-Seq biological replicate 3 CT020; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711994		GSM1711994	Mouse islet polyA RNA-Seq biological replicate 3 CT020	4789385318	31748668	2015-11-10 17:09:03	2042588926	4789385318	31748668	2	31748668	index:0,count:31748668,average:75.43,stdev:1.42|index:1,count:31748668,average:75.42,stdev:1.47	GSM1711994_r1				in_mesa	26542580	5.37	3.46	0.06	3937359452	3890598679	3655608889	3634198904	98.81	99.41	30567126	29429591	145.685	359.250	127	471893	84.91	91.49	33956146	25955432	33956146	25955432	88.31	88.67	33956146	26996318	33956146	25156376	268089562	6.81	0.18	0	6.92	0	0.29	0	0.12	0	0.00	0	3.30	0	30568521	0	150	0	149.60	0	1.56	0	0.01	0	1.20	0	0.00	0	335.18	0	0.40	0	56318	0	31748668	0	2197730	0	92479	0	39343	0	0	0	1048325	0	4507	0	0	0	49273	0	9368547	0	14686	0	9437013	0	89.36	0	28370791	0	184919	8994231	48.638760754709	31748668.0	30568521.0	56318.0	2197730.0	92479.0	39343.0	0.0	1048325.0	28370791.0	96.3	0.2	6.9	0.3	0.1	0.0	3.3	89.4	35	76	75.43	7	2394896008	26.2	23.1	24.0	26.7	0.0	34.8	24.1	bulk
1913165	SRR2063314	SRP059509	SRS961400	SRX1059087	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711995: Mouse islet polyA RNA-Seq biological replicate 3 CT24; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711995		GSM1711995	Mouse islet polyA RNA-Seq biological replicate 3 CT24	4666983322	30919604	2015-11-10 17:09:03	1993856964	4666983322	30919604	2	30919604	index:0,count:30919604,average:75.48,stdev:1.16|index:1,count:30919604,average:75.46,stdev:1.22	GSM1711995_r1				in_mesa	26542580	4.19	3.27	0.08	3921522001	3893262493	3649525934	3645125661	99.28	99.88	29651417	28181777	157.021	429.871	128	400245	86.38	92.85	33006544	25613521	33006544	25613521	89.36	89.85	33006544	26498191	33006544	24786938	230603724	5.88	0.16	0	6.68	0	0.36	0	0.11	0	0.00	0	3.64	0	29652791	0	150	0	149.62	0	1.64	0	0.00	0	1.21	0	0.00	0	131.11	0	0.40	0	48248	0	30919604	0	2066486	0	109822	0	32871	0	0	0	1124120	0	4831	0	0	0	50587	0	10018643	0	14661	0	10088722	0	89.22	0	27586305	0	199190	9753141	48.964009237412	30919604.0	29652791.0	48248.0	2066486.0	109822.0	32871.0	0.0	1124120.0	27586305.0	95.9	0.2	6.7	0.4	0.1	0.0	3.6	89.2	35	76	75.48	7	2333738470	25.1	24.1	24.8	26.0	0.0	34.7	23.9	bulk
1913180	SRR2063315	SRP059509	SRS961399	SRX1059088	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711996: Mouse islet polyA RNA-Seq biological replicate 3 CT28; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711996		GSM1711996	Mouse islet polyA RNA-Seq biological replicate 3 CT28	4607668443	30574869	2015-11-10 17:09:03	1973278857	4607668443	30574869	2	30574869	index:0,count:30574869,average:75.36,stdev:1.81|index:1,count:30574869,average:75.34,stdev:1.84	GSM1711996_r1				in_mesa	26542580	5.92	3.48	0.06	3616037094	3586391056	3300159839	3297602515	99.18	99.92	29298497	28270715	138.521	335.472	118	452236	86.04	94.37	33367775	25209134	33367775	25209134	90.52	91.18	33367775	26521297	33367775	24355903	150381824	4.16	0.23	0	8.46	0	0.34	0	0.10	0	0.00	0	3.73	0	29299895	0	150	0	149.45	0	1.64	0	0.01	0	1.26	0	0.00	0	310.06	0	0.41	0	69248	0	30574869	0	2587437	0	103993	0	31835	0	0	0	1139146	0	4532	0	0	0	44875	0	8982924	0	14019	0	9046350	0	87.37	0	26712458	0	180761	8361502	46.257223626778	30574869.0	29299895.0	69248.0	2587437.0	103993.0	31835.0	0.0	1139146.0	26712458.0	95.8	0.2	8.5	0.3	0.1	0.0	3.7	87.4	35	76	75.36	7	2304110422	26.2	23.1	24.0	26.7	0.0	34.7	23.9	bulk
1913196	SRR2063316	SRP059509	SRS961398	SRX1059089	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711997: Mouse islet polyA RNA-Seq biological replicate 3 CT32; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711997		GSM1711997	Mouse islet polyA RNA-Seq biological replicate 3 CT32	3597395283	23845515	2015-11-10 17:09:03	1537263465	3597395283	23845515	2	23845515	index:0,count:23845515,average:75.44,stdev:1.39|index:1,count:23845515,average:75.42,stdev:1.44	GSM1711997_r1				in_mesa	26542580	4.47	3.33	0.07	2934761759	2910357295	2737399017	2730386415	99.17	99.74	22915821	21949966	147.768	386.555	127	322839	85.35	91.56	25407709	19560295	25407709	19560295	88.28	88.67	25407709	20230883	25407709	18942001	209111784	7.13	0.16	0	6.52	0	0.32	0	0.12	0	0.00	0	3.45	0	22916857	0	150	0	149.59	0	1.54	0	0.01	0	1.18	0	0.00	0	337.97	0	0.40	0	38417	0	23845515	0	1553566	0	77350	0	27779	0	0	0	823529	0	3742	0	0	0	38656	0	7338183	0	11236	0	7391817	0	89.59	0	21363291	0	185238	6997144	37.773804510953	23845515.0	22916857.0	38417.0	1553566.0	77350.0	27779.0	0.0	823529.0	21363291.0	96.1	0.2	6.5	0.3	0.1	0.0	3.5	89.6	35	76	75.44	7	1798918855	25.5	23.8	24.5	26.2	0.0	34.7	24.0	bulk
1913211	SRR2063317	SRP059509	SRS961397	SRX1059090	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711998: Mouse islet polyA RNA-Seq biological replicate 3 CT36; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711998		GSM1711998	Mouse islet polyA RNA-Seq biological replicate 3 CT36	3986260269	26673548	2015-11-10 17:09:03	1725031696	3986260269	26673548	2	26673548	index:0,count:26673548,average:74.73,stdev:3.89|index:1,count:26673548,average:74.72,stdev:3.89	GSM1711998_r1				in_mesa	26542580	7.36	3.51	0.07	2874999007	2824942622	2626046995	2600808030	98.26	99.04	25536342	24647041	126.095	332.399	107	394309	81.97	89.85	28935068	20933103	28935068	20933103	86.82	87.1	28935068	22171451	28935068	20291156	232789062	8.10	0.14	0	8.40	0	0.31	0	0.20	0	0.00	0	3.75	0	25537427	0	149	0	148.24	0	1.44	0	0.01	0	1.17	0	0.01	0	297.29	0	0.42	0	38055	0	26673548	0	2240622	0	82421	0	54152	0	0	0	999548	0	3466	0	0	0	36431	0	7215694	0	10919	0	7266510	0	87.34	0	23296805	0	166107	6171061	37.151119459144	26673548.0	25537427.0	38055.0	2240622.0	82421.0	54152.0	0.0	999548.0	23296805.0	95.7	0.1	8.4	0.3	0.2	0.0	3.7	87.3	35	76	74.73	7	1993333403	26.9	22.1	23.3	27.6	0.0	34.7	23.7	bulk
1913227	SRR2063318	SRP059509	SRS961396	SRX1059091	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711999: Mouse islet polyA RNA-Seq biological replicate 3 CT40; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711999		GSM1711999	Mouse islet polyA RNA-Seq biological replicate 3 CT40	4787216970	31768588	2015-11-10 17:09:03	2058991369	4787216970	31768588	2	31768588	index:0,count:31768588,average:75.35,stdev:1.80|index:1,count:31768588,average:75.34,stdev:1.83	GSM1711999_r1				in_mesa	26542580	6.95	3.59	0.06	3723977087	3681477769	3398294543	3383895277	98.86	99.58	30522581	29504580	135.394	329.767	118	496678	85.05	93.25	34582036	25961283	34582036	25961283	89.87	90.36	34582036	27430583	34582036	25157107	193107661	5.19	0.19	0	8.45	0	0.27	0	0.12	0	0.00	0	3.53	0	30524002	0	150	0	149.43	0	1.47	0	0.01	0	1.21	0	0.00	0	133.45	0	0.42	0	60262	0	31768588	0	2683440	0	86200	0	36874	0	0	0	1121512	0	4481	0	0	0	46651	0	9052567	0	13698	0	9117397	0	87.64	0	27840562	0	185183	8303568	44.839796309596	31768588.0	30524002.0	60262.0	2683440.0	86200.0	36874.0	0.0	1121512.0	27840562.0	96.1	0.2	8.4	0.3	0.1	0.0	3.5	87.6	35	76	75.35	7	2393911534	26.5	22.7	23.8	27.0	0.0	34.7	24.0	bulk
1913243	SRR2063319	SRP059509	SRS961395	SRX1059092	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712000: Mouse islet polyA RNA-Seq biological replicate 3 CT44; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1712000		GSM1712000	Mouse islet polyA RNA-Seq biological replicate 3 CT44	5153464722	34275946	2015-11-10 17:09:03	2213605582	5153464722	34275946	2	34275946	index:0,count:34275946,average:75.19,stdev:2.48|index:1,count:34275946,average:75.17,stdev:2.49	GSM1712000_r1				in_mesa	26542580	6.46	3.68	0.09	3856676577	3796027417	3545444041	3518049807	98.43	99.23	32795097	31677936	130.232	335.069	116	538189	82.99	90.33	36877369	27218120	36877369	27218120	87.11	87.52	36877369	28569420	36877369	26371103	301757543	7.82	0.15	0	7.78	0	0.29	0	0.16	0	0.00	0	3.86	0	32796602	0	150	0	149.13	0	1.44	0	0.01	0	1.17	0	0.01	0	127.87	0	0.41	0	51302	0	34275946	0	2666224	0	100071	0	55338	0	0	0	1323935	0	4902	0	0	0	51411	0	9316629	0	13569	0	9386511	0	87.91	0	30130378	0	184400	8240457	44.687944685466	34275946.0	32796602.0	51302.0	2666224.0	100071.0	55338.0	0.0	1323935.0	30130378.0	95.7	0.1	7.8	0.3	0.2	0.0	3.9	87.9	35	76	75.19	7	2577082145	27.0	22.2	23.1	27.7	0.0	34.7	23.8	bulk
1913355	SRR2063320	SRP059509	SRS961394	SRX1059093	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712001: Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;Bmal1flx/flx|source_name;;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712001		GSM1712001	Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 1	2794805600	13974028	2015-11-10 17:09:03	1701433754	2794805600	13974028	2	13974028	index:0,count:13974028,average:100,stdev:0|index:1,count:13974028,average:100,stdev:0	GSM1712001_r1				in_mesa	26542580	4.51	2.23	0.06	2109976293	2091222653	1924992896	1915609343	99.11	99.51	13011807	12048075	203.532	645.447	132	99480	81.31	89.4	15749581	10580414	15749581	10580414	87.03	86.71	15749581	11324049	15749581	10261879	196485954	9.31	0.70	0	8.42	0	3.23	0	0.09	0	0.00	0	3.56	0	13011807	0	200	0	197.68	0	1.70	0	0.01	0	1.12	0	0.01	0	157.21	0	0.29	0	98129	0	13974028	0	1177039	0	451211	0	12889	0	0	0	498121	0	2352	0	0	0	28681	0	6333772	0	11142	0	6375947	0	84.69	0	11834768	0	174525	6909538	39.590534307406	13974028.0	13011807.0	98129.0	1177039.0	451211.0	12889.0	0.0	498121.0	11834768.0	93.1	0.7	8.4	3.2	0.1	0.0	3.6	84.7	100	100	100.00	38	1397402800	24.9	24.4	25.1	25.6	0.0	37.0	22.4	bulk
1913371	SRR2063321	SRP059509	SRS961393	SRX1059094	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712002: Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;Bmal1flx/flx|source_name;;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712002		GSM1712002	Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 2	3634703400	18173517	2015-11-10 17:09:03	2233914833	3634703400	18173517	2	18173517	index:0,count:18173517,average:100,stdev:0|index:1,count:18173517,average:100,stdev:0	GSM1712002_r1				in_mesa	26542580	2.78	1.97	0.07	2533808619	2510682837	2282376116	2272249750	99.09	99.56	16632285	15444765	187.559	674.631	128	147482	81.14	90.41	21207587	13495401	21207587	13495401	87.79	87.63	21207587	14601077	21207587	13080638	211502818	8.35	1.05	0	9.39	0	3.77	0	0.09	0	0.00	0	4.63	0	16632285	0	200	0	197.19	0	1.66	0	0.01	0	1.09	0	0.01	0	127.78	0	0.29	0	190623	0	18173517	0	1705996	0	684965	0	15541	0	0	0	840726	0	2974	0	0	0	36503	0	8505937	0	14041	0	8559455	0	82.13	0	14926289	0	183122	9504384	51.901923307959	18173517.0	16632285.0	190623.0	1705996.0	684965.0	15541.0	0.0	840726.0	14926289.0	91.5	1.0	9.4	3.8	0.1	0.0	4.6	82.1	100	100	100.00	38	1817351700	24.5	24.9	25.3	25.3	0.0	36.8	22.0	bulk
1913387	SRR2063322	SRP059509	SRS961392	SRX1059095	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712003: Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;Bmal1flx/flx|source_name;;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712003		GSM1712003	Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 3	3928398600	19641993	2015-11-10 17:09:03	2402373395	3928398600	19641993	2	19641993	index:0,count:19641993,average:100,stdev:0|index:1,count:19641993,average:100,stdev:0	GSM1712003_r1				in_mesa	26542580	2.78	2.06	0.04	2895105461	2874163273	2622501210	2612882266	99.28	99.63	18092195	16762263	202.032	620.031	132	146981	82.02	90.9	22687334	14838856	22687334	14838856	88.42	88.17	22687334	15997141	22687334	14393423	232034647	8.01	0.68	0	9.00	0	4.33	0	0.08	0	0.00	0	3.49	0	18092195	0	200	0	197.63	0	1.70	0	0.01	0	1.14	0	0.01	0	135.46	0	0.29	0	133374	0	19641993	0	1767309	0	850078	0	14961	0	0	0	684759	0	3214	0	0	0	36218	0	9048305	0	15632	0	9103369	0	83.11	0	16324886	0	181409	10349701	57.051750464420	19641993.0	18092195.0	133374.0	1767309.0	850078.0	14961.0	0.0	684759.0	16324886.0	92.1	0.7	9.0	4.3	0.1	0.0	3.5	83.1	100	100	100.00	38	1964199300	24.8	24.7	25.0	25.4	0.0	36.9	22.3	bulk
1913403	SRR2063323	SRP059509	SRS961391	SRX1059096	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712004: Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;PdxCre;Bmal1flx/flx|source_name;;PdxCre;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712004		GSM1712004	Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 1	3777009000	18885045	2015-11-10 17:09:03	2328613459	3777009000	18885045	2	18885045	index:0,count:18885045,average:100,stdev:0|index:1,count:18885045,average:100,stdev:0	GSM1712004_r1				in_mesa	26542580	2.7	1.43	0.03	2716621757	2706629195	2385895229	2384586536	99.63	99.95	16976796	15585879	205.991	637.576	132	132797	82.24	94.18	23072520	13961461	23072520	13961461	91.64	91.34	23072520	15557311	23072520	13540190	132254349	4.87	0.63	0	11.40	0	6.60	0	0.04	0	0.00	0	3.46	0	16976796	0	200	0	197.47	0	1.63	0	0.00	0	1.11	0	0.01	0	128.52	0	0.29	0	119080	0	18885045	0	2152566	0	1245769	0	8416	0	0	0	654064	0	2548	0	0	0	29705	0	9517558	0	13419	0	9563230	0	78.50	0	14824230	0	171451	11937684	69.627380417729	18885045.0	16976796.0	119080.0	2152566.0	1245769.0	8416.0	0.0	654064.0	14824230.0	89.9	0.6	11.4	6.6	0.0	0.0	3.5	78.5	100	100	100.00	38	1888504500	24.5	24.9	25.5	25.1	0.0	36.9	22.2	bulk
1913419	SRR2063324	SRP059509	SRS961390	SRX1059097	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712005: Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;PdxCre;Bmal1flx/flx|source_name;;PdxCre;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712005		GSM1712005	Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 2	4542062400	22710312	2015-11-10 17:09:03	2786832984	4542062400	22710312	2	22710312	index:0,count:22710312,average:100,stdev:0|index:1,count:22710312,average:100,stdev:0	GSM1712005_r1				in_mesa	26542580	4.63	2.04	0.04	3372815720	3358766864	3106611518	3105403720	99.58	99.96	21309380	19944072	193.576	572.977	132	186453	85.46	93.01	25004328	18211757	25004328	18211757	90.29	90.28	25004328	19240470	25004328	17676637	205730972	6.10	0.81	0	7.61	0	2.32	0	0.07	0	0.00	0	3.78	0	21309380	0	200	0	197.61	0	1.68	0	0.01	0	1.11	0	0.01	0	169.97	0	0.29	0	183017	0	22710312	0	1729260	0	526194	0	16158	0	0	0	858580	0	4186	0	0	0	46580	0	10850793	0	20630	0	10922189	0	86.22	0	19580120	0	185436	11078812	59.744666623525	22710312.0	21309380.0	183017.0	1729260.0	526194.0	16158.0	0.0	858580.0	19580120.0	93.8	0.8	7.6	2.3	0.1	0.0	3.8	86.2	100	100	100.00	38	2271031200	24.4	24.8	25.9	24.9	0.0	36.7	21.9	bulk
1913435	SRR2063325	SRP059509	SRS961389	SRX1059098	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712006: Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;PdxCre;Bmal1flx/flx|source_name;;PdxCre;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712006		GSM1712006	Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 3	3948448000	19742240	2015-11-10 17:09:03	2392764434	3948448000	19742240	2	19742240	index:0,count:19742240,average:100,stdev:0|index:1,count:19742240,average:100,stdev:0	GSM1712006_r1				in_mesa	26542580	1.54	0.87	0.02	2455481641	2451056123	2002081253	2004591055	99.82	100.13	17217250	16016593	183.776	760.091	128	185561	78.49	96.6	27176076	13514557	27176076	13514557	93.88	93.78	27176076	16163617	27176076	13120357	66845787	2.72	0.89	0	16.35	0	8.06	0	0.02	0	0.00	0	4.71	0	17217250	0	200	0	196.76	0	1.67	0	0.00	0	1.08	0	0.01	0	52.37	0	0.28	0	175981	0	19742240	0	3227280	0	1590355	0	4817	0	0	0	929818	0	1680	0	0	0	20756	0	10281828	0	11236	0	10315500	0	70.86	0	13989970	0	146541	14242340	97.190137913621	19742240.0	17217250.0	175981.0	3227280.0	1590355.0	4817.0	0.0	929818.0	13989970.0	87.2	0.9	16.3	8.1	0.0	0.0	4.7	70.9	100	100	100.00	38	1974224000	24.4	25.0	25.3	25.2	0.0	37.0	22.5	bulk
1918795	SRR2479474	SRP059509	SRS961394	SRX1059093	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712001: Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;Bmal1flx/flx|source_name;;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712001		GSM1712001	Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 1	6408915600	32044578	2015-11-10 17:09:03	2634824519	6408915600	32044578	2	32044578	index:0,count:32044578,average:100,stdev:0|index:1,count:32044578,average:100,stdev:0	GSM1712001_r2				in_mesa	26542580	4.55	2.23	0.06	4902621721	4858028007	4474107968	4451366859	99.09	99.49	30134459	27921716	203.612	638.804	132	228793	81.29	89.35	36467849	24497002	36467849	24497002	87.01	86.67	36467849	26220231	36467849	23761501	457770129	9.34	0.72	0	8.48	0	3.29	0	0.11	0	0.00	0	2.56	0	30134459	0	200	0	198.48	0	1.70	0	0.01	0	1.29	0	0.01	0	192.59	0	0.13	0	229316	0	32044578	0	2718287	0	1054459	0	34871	0	0	0	820789	0	5701	0	0	0	68072	0	14898710	0	22626	0	14995109	0	85.56	0	27416172	0	210724	16238068	77.058465101270	32044578.0	30134459.0	229316.0	2718287.0	1054459.0	34871.0	0.0	820789.0	27416172.0	94.0	0.7	8.5	3.3	0.1	0.0	2.6	85.6	100	100	100.00	8	3204457800	24.9	24.4	25.0	25.7	0.0	36.9	25.5	bulk
1918813	SRR2479475	SRP059509	SRS961393	SRX1059094	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712002: Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;Bmal1flx/flx|source_name;;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712002		GSM1712002	Mouse Islet polyA RNA-Seq in Bmal1flx/flx islets biological replicate 2	7040645800	35203229	2015-11-10 17:09:03	2969817247	7040645800	35203229	2	35203229	index:0,count:35203229,average:100,stdev:0|index:1,count:35203229,average:100,stdev:0	GSM1712002_r2				in_mesa	26542580	2.81	1.97	0.06	4991501964	4945182711	4496929731	4476220224	99.07	99.54	32577627	30253394	188.544	671.169	128	286147	81.07	90.33	41554685	26409154	41554685	26409154	87.75	87.56	41554685	28585419	41554685	25599721	419223932	8.40	1.06	0	9.49	0	3.87	0	0.10	0	0.00	0	3.49	0	32577627	0	200	0	198.04	0	1.65	0	0.01	0	1.34	0	0.00	0	100.26	0	0.13	0	371985	0	35203229	0	3340858	0	1361661	0	35540	0	0	0	1228401	0	6029	0	0	0	73771	0	16920400	0	24000	0	17024200	0	83.05	0	29236769	0	212826	18932835	88.959220208057	35203229.0	32577627.0	371985.0	3340858.0	1361661.0	35540.0	0.0	1228401.0	29236769.0	92.5	1.1	9.5	3.9	0.1	0.0	3.5	83.1	100	100	100.00	8	3520322900	24.5	24.9	25.2	25.4	0.0	36.7	24.8	bulk
1918861	SRR2479478	SRP059509	SRS961391	SRX1059096	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712004: Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;PdxCre;Bmal1flx/flx|source_name;;PdxCre;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712004		GSM1712004	Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 1	5406695000	27033475	2015-11-10 17:09:03	2233608833	5406695000	27033475	2	27033475	index:0,count:27033475,average:100,stdev:0|index:1,count:27033475,average:100,stdev:0	GSM1712004_r2				in_mesa	26542580	2.73	1.44	0.03	3945720725	3930673184	3466116565	3463693900	99.62	99.93	24558168	22565398	206.405	625.740	132	190532	82.23	94.15	33370041	20193976	33370041	20193976	91.64	91.32	33370041	22506110	33370041	19586819	192395949	4.88	0.63	0	11.50	0	6.78	0	0.05	0	0.00	0	2.33	0	24558168	0	200	0	198.33	0	1.63	0	0.00	0	1.30	0	0.00	0	138.24	0	0.12	0	169887	0	27033475	0	3110126	0	1831949	0	14234	0	0	0	629124	0	3859	0	0	0	44876	0	14010509	0	16145	0	14075389	0	79.34	0	21448042	0	185485	17588203	94.822778122220	27033475.0	24558168.0	169887.0	3110126.0	1831949.0	14234.0	0.0	629124.0	21448042.0	90.8	0.6	11.5	6.8	0.1	0.0	2.3	79.3	100	100	100.00	8	2703347500	24.5	24.9	25.4	25.2	0.0	36.9	25.8	bulk
1918987	SRR2479480	SRP059509	SRS961390	SRX1059097	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712005: Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;PdxCre;Bmal1flx/flx|source_name;;PdxCre;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712005		GSM1712005	Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 2	6477929200	32389646	2015-11-10 17:09:03	2665737062	6477929200	32389646	2	32389646	index:0,count:32389646,average:100,stdev:0|index:1,count:32389646,average:100,stdev:0	GSM1712005_r2				in_mesa	26542580	4.69	2.05	0.04	4881972949	4861067930	4498847978	4496551457	99.57	99.95	30703470	28739153	194.176	566.834	132	265813	85.47	92.98	35989115	26243577	35989115	26243577	90.27	90.25	35989115	27717323	35989115	25472745	298803046	6.12	0.82	0	7.65	0	2.38	0	0.08	0	0.00	0	2.74	0	30703470	0	200	0	198.43	0	1.67	0	0.01	0	1.28	0	0.01	0	178.29	0	0.12	0	264400	0	32389646	0	2478011	0	772063	0	26923	0	0	0	887190	0	6136	0	0	0	69591	0	15915466	0	25567	0	16016760	0	87.14	0	28225459	0	200712	16215148	80.788134242098	32389646.0	30703470.0	264400.0	2478011.0	772063.0	26923.0	0.0	887190.0	28225459.0	94.8	0.8	7.7	2.4	0.1	0.0	2.7	87.1	100	100	100.00	8	3238964600	24.4	24.8	25.8	25.0	0.0	36.9	25.4	bulk
1919003	SRR2479481	SRP059509	SRS961389	SRX1059098	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1712006: Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	Illumina HiSeq 2500	cell type;;Pancreatic islet cells|genotype;;PdxCre;Bmal1flx/flx|source_name;;PdxCre;Bmal1flx/flx mice|strain;;none	GEO Accession;;GSM1712006		GSM1712006	Mouse Islet polyA RNA-Seq in PdxCre;Bmal1flx/flx islets biological replicate 3	6713943400	33569717	2015-11-10 17:09:03	2745081223	6713943400	33569717	2	33569717	index:0,count:33569717,average:100,stdev:0|index:1,count:33569717,average:100,stdev:0	GSM1712006_r2				in_mesa	26542580	1.55	0.87	0.02	4234760869	4227261800	3452371302	3456904376	99.82	100.13	29582055	27509154	184.899	752.586	128	315800	78.45	96.58	46698960	23208001	46698960	23208001	93.88	93.76	46698960	27770385	46698960	22529229	115570947	2.73	0.91	0	16.54	0	8.25	0	0.03	0	0.00	0	3.60	0	29582055	0	200	0	197.62	0	1.65	0	0.00	0	1.41	0	0.00	0	96.68	0	0.13	0	305740	0	33569717	0	5552454	0	2770405	0	9509	0	0	0	1207748	0	3110	0	0	0	38224	0	17954639	0	15978	0	18011951	0	71.58	0	24029601	0	163981	24854074	151.566791274599	33569717.0	29582055.0	305740.0	5552454.0	2770405.0	9509.0	0.0	1207748.0	24029601.0	88.1	0.9	16.5	8.3	0.0	0.0	3.6	71.6	100	100	100.00	8	3356971700	24.4	25.0	25.2	25.3	0.0	37.0	26.0	bulk
3825777	SRR2063303	SRP059509	SRS961411	SRX1059076	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711984: Mouse islet polyA RNA-Seq biological replicate 2 CT28; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711984		GSM1711984	Mouse islet polyA RNA-Seq biological replicate 2 CT28	4206745560	27878607	2015-11-10 17:09:03	1767641967	4206745560	27878607	2	27878607	index:0,count:27878607,average:75.45,stdev:1.30|index:1,count:27878607,average:75.44,stdev:1.33	GSM1711984_r1				in_mesa	26542580	5.14	3.35	0.06	3423890939	3401459824	3167809341	3168016236	99.34	100.01	26827550	25693115	147.624	386.071	127	371307	85.78	92.79	29983684	23014211	29983684	23014211	88.67	89.25	29983684	23789204	29983684	22136534	186338551	5.44	0.18	0	7.27	0	0.25	0	0.10	0	0.00	0	3.42	0	26828406	0	150	0	149.65	0	1.93	0	0.01	0	1.33	0	0.01	0	406.33	0	0.38	0	50951	0	27878607	0	2026497	0	68501	0	28831	0	0	0	952869	0	4122	0	0	0	42789	0	8599401	0	13131	0	8659443	0	88.96	0	24801909	0	185395	8113315	43.762318293374	27878607.0	26828406.0	50951.0	2026497.0	68501.0	28831.0	0.0	952869.0	24801909.0	96.2	0.2	7.3	0.2	0.1	0.0	3.4	89.0	35	76	75.45	7	2103540130	25.5	23.9	24.8	25.9	0.0	34.9	24.2	bulk
3825810	SRR2063304	SRP059509	SRS961410	SRX1059077	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711985: Mouse islet polyA RNA-Seq biological replicate 2 CT32; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711985		GSM1711985	Mouse islet polyA RNA-Seq biological replicate 2 CT32	4280413706	28367981	2015-11-10 17:09:03	1802621961	4280413706	28367981	2	28367981	index:0,count:28367981,average:75.45,stdev:1.31|index:1,count:28367981,average:75.44,stdev:1.34	GSM1711985_r1				in_mesa	26542580	5.0	3.24	0.06	3471589089	3441272508	3240800025	3229757127	99.13	99.66	27222124	26158477	145.870	374.281	126	400206	85.07	91.18	30028391	23157561	30028391	23157561	87.81	88.15	30028391	23903701	30028391	22390299	250503400	7.22	0.19	0	6.43	0	0.25	0	0.12	0	0.00	0	3.68	0	27223012	0	150	0	149.70	0	1.66	0	0.01	0	1.21	0	0.01	0	297.74	0	0.37	0	53373	0	28367981	0	1824014	0	69638	0	32667	0	0	0	1042664	0	4108	0	0	0	43939	0	8671025	0	13764	0	8732836	0	89.53	0	25398998	0	184294	8196007	44.472457052319	28367981.0	27223012.0	53373.0	1824014.0	69638.0	32667.0	0.0	1042664.0	25398998.0	96.0	0.2	6.4	0.2	0.1	0.0	3.7	89.5	35	76	75.45	7	2140230191	25.8	23.6	24.9	25.7	0.0	34.8	24.0	bulk
3825840	SRR2063305	SRP059509	SRS961409	SRX1059078	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711986: Mouse islet polyA RNA-Seq biological replicate 2 CT36; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711986		GSM1711986	Mouse islet polyA RNA-Seq biological replicate 2 CT36	4353981958	28849959	2015-11-10 17:09:03	1842088500	4353981958	28849959	2	28849959	index:0,count:28849959,average:75.46,stdev:1.23|index:1,count:28849959,average:75.46,stdev:1.26	GSM1711986_r1				in_mesa	26542580	4.9	3.33	0.07	3627271351	3597545220	3383406723	3374026267	99.18	99.72	27812302	26549041	153.013	408.125	127	369621	85.09	91.28	30731801	23667471	30731801	23667471	87.9	88.25	30731801	24446587	30731801	22881901	260705464	7.19	0.19	0	6.53	0	0.25	0	0.12	0	0.00	0	3.22	0	27813155	0	150	0	149.70	0	1.66	0	0.01	0	1.21	0	0.01	0	130.64	0	0.39	0	53826	0	28849959	0	1883374	0	73352	0	34020	0	0	0	929432	0	4242	0	0	0	44579	0	8847455	0	13683	0	8909959	0	89.88	0	25929781	0	191654	8474834	44.219447546099	28849959.0	27813155.0	53826.0	1883374.0	73352.0	34020.0	0.0	929432.0	25929781.0	96.4	0.2	6.5	0.3	0.1	0.0	3.2	89.9	35	76	75.46	7	2177099015	25.6	23.8	24.8	25.8	0.0	34.8	24.1	bulk
3825873	SRR2063306	SRP059509	SRS961408	SRX1059079	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711987: Mouse islet polyA RNA-Seq biological replicate 2 CT40; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711987		GSM1711987	Mouse islet polyA RNA-Seq biological replicate 2 CT40	4567446302	30296644	2015-11-10 17:09:03	1931620584	4567446302	30296644	2	30296644	index:0,count:30296644,average:75.39,stdev:1.65|index:1,count:30296644,average:75.37,stdev:1.66	GSM1711987_r1				in_mesa	26542580	5.39	3.34	0.06	3511088473	3486880590	3238717746	3237587972	99.31	99.97	29062873	28045836	135.409	343.204	115	471530	86.31	93.66	32616680	25085400	32616680	25085400	89.78	90.36	32616680	26093197	32616680	24203199	169675341	4.83	0.16	0	7.52	0	0.26	0	0.11	0	0.00	0	3.70	0	29063815	0	150	0	149.55	0	1.68	0	0.01	0	1.22	0	0.01	0	315.23	0	0.38	0	49865	0	30296644	0	2279123	0	80234	0	32047	0	0	0	1120548	0	4544	0	0	0	45377	0	9279194	0	14115	0	9343230	0	88.41	0	26784692	0	183222	8417634	45.942266758359	30296644.0	29063815.0	49865.0	2279123.0	80234.0	32047.0	0.0	1120548.0	26784692.0	95.9	0.2	7.5	0.3	0.1	0.0	3.7	88.4	35	76	75.39	7	2283913603	25.9	23.5	24.6	26.0	0.0	34.8	24.1	bulk
3825905	SRR2063307	SRP059509	SRS961407	SRX1059080	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711988: Mouse islet polyA RNA-Seq biological replicate 2 CT44; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711988		GSM1711988	Mouse islet polyA RNA-Seq biological replicate 2 CT44	5667819381	37548701	2015-11-10 17:09:03	2387283806	5667819381	37548701	2	37548701	index:0,count:37548701,average:75.47,stdev:1.14|index:1,count:37548701,average:75.47,stdev:1.17	GSM1711988_r1				in_mesa	26542580	5.08	3.31	0.06	4718344367	4681451719	4398945842	4389403270	99.22	99.78	36107634	34506877	152.701	407.196	126	495761	85.76	92.02	39864935	30965941	39864935	30965941	88.52	88.92	39864935	31961901	39864935	29923295	301427792	6.39	0.18	0	6.54	0	0.25	0	0.11	0	0.00	0	3.48	0	36108781	0	150	0	149.74	0	1.72	0	0.01	0	1.24	0	0.01	0	136.96	0	0.37	0	68628	0	37548701	0	2456835	0	93863	0	41080	0	0	0	1304977	0	5567	0	0	0	59797	0	11675402	0	17963	0	11758729	0	89.62	0	33651946	0	199272	11202268	56.215966116665	37548701.0	36108781.0	68628.0	2456835.0	93863.0	41080.0	0.0	1304977.0	33651946.0	96.2	0.2	6.5	0.2	0.1	0.0	3.5	89.6	35	76	75.47	7	2833980536	25.7	23.7	24.7	25.8	0.0	34.8	24.1	bulk
3826193	SRR2063310	SRP059509	SRS961404	SRX1059083	SRA272961	GEO		Genome-wide Circadian Control of Transcription at Active Enhancers Regulates Insulin Secretion and Diabetes Risk	The molecular clock is a transcriptional oscillator present in brain and peripheral cells that coordinates behavior and physiology with the solar cycle. Here we reveal that the clock gates insulin secretion through genome-wide transcriptional control of the pancreatic exocyst across species. Clock transcription factors bind to unique enhancer sites in cycling genes in beta cells that diverge from those in liver, revealing the dynamics of inter-tissue clock control of genomic and physiologic processes important in glucose homeostasis. Overall design: Transcriptome profiling in mouse and human islets at serial 4-hour time intervals by polyA RNA-Seq		GSM1711991: Mouse islet polyA RNA-Seq biological replicate 3 CT8; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Mouse islets were isolated by perfusing the pancreatic bile duct with collagenase Illumina stranded LT kit for RNA-Seq	NextSeq 500	cell type;;Pancreatic islet cells|genotype;;wild type|source_name;;C57BL/6 wild type mice|strain;;C57BL/6	GEO Accession;;GSM1711991		GSM1711991	Mouse islet polyA RNA-Seq biological replicate 3 CT8	4557780805	30218062	2015-11-10 17:09:03	1942677387	4557780805	30218062	2	30218062	index:0,count:30218062,average:75.42,stdev:1.51|index:1,count:30218062,average:75.41,stdev:1.55	GSM1711991_r1				in_mesa	26542580	5.35	3.51	0.07	3864540275	3817546797	3593229532	3571126957	98.78	99.38	29137563	28015341	150.920	368.431	132	437591	84.13	90.51	32284004	24514922	32284004	24514922	87.43	87.72	32284004	25476222	32284004	23761155	303665162	7.86	0.17	0	6.79	0	0.28	0	0.13	0	0.00	0	3.17	0	29138874	0	150	0	149.58	0	1.55	0	0.01	0	1.20	0	0.00	0	142.02	0	0.40	0	51803	0	30218062	0	2052140	0	84694	0	37821	0	0	0	956673	0	4558	0	0	0	47030	0	8628877	0	13499	0	8693964	0	89.64	0	27086734	0	189603	8435040	44.487903672410	30218062.0	29138874.0	51803.0	2052140.0	84694.0	37821.0	0.0	956673.0	27086734.0	96.4	0.2	6.8	0.3	0.1	0.0	3.2	89.6	35	76	75.42	7	2279092880	26.4	23.0	23.8	26.9	0.0	34.8	24.2	bulk
1463593	SRR2075552	SRP059792	SRS969747	SRX1070581	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_WT.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;WT|ID;;1|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_WT.1	RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	4655386153	31018381	2015-09-15 00:00:00	2231170851	4655386153	31018381	2	31018381	index:0,count:31014676,average:75.23,stdev:3.99|index:1,count:31017303,average:74.86,stdev:5.14	SAMN03785068.bam						2.42	3.35	0.14	4374784779	4310726165	4114335361	4071342837	98.54	98.96	30649914	27960651	201.811	992.545	154	253653	79.44	84.5	33813634	24349357	33813634	24349357	81.45	81.43	33813634	24963440	33813634	23467110	620916172	14.19	0.29	0.00	5.91	18.54	0.17	1.19	0.00	0.04	0.00	0.00	1.00	0.02	30650545	4723	150	75	149.28	75.86	1.51	0.00	0.00	0.00	1.18	0.00	0.00	0.00	487.55	17.22	0.11	0.01	88408	0	31013598	4783	1833137	887	52737	57	207	2	0	0	310109	1	6453	1	0	0	59220	0	8420297	298	14096	0	8500066	299	92.92	80.20	28817408	3836	158869	8598895	54.125694754798	31018381.0	30655268.0	88408.0	1834024.0	52794.0	209.0	0.0	310110.0	28821244.0	98.8	0.3	5.9	0.2	0.0	0.0	1.0	92.9	67	76	75.94	38	363240	27.3	22.7	22.9	27.0	0.0	37.2	30.4	bulk
1463610	SRR2075553	SRP059792	SRS969738	SRX1070582	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_WT.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;WT|ID;;2|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_WT.2	RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	3389132120	22582964	2015-09-15 00:00:00	1625308492	3389132120	22582964	2	22582964	index:0,count:22581444,average:75.22,stdev:4.03|index:1,count:22582199,average:74.86,stdev:5.14	SAMN03785069.bam						2.71	3.25	0.15	3170701583	3130341354	2971749863	2946502615	98.73	99.15	22297796	20354612	201.996	996.942	155	175559	79.02	84.34	24693483	17619240	24693483	17619240	81.29	81.21	24693483	18125308	24693483	16966551	458867583	14.47	0.30	0.00	6.23	15.97	0.17	0.66	0.00	0.00	0.00	0.00	1.08	0.04	22298295	2269	150	75	149.27	75.83	1.66	0.00	0.00	0.00	1.22	0.00	0.00	0.00	298.86	4.11	0.11	0.01	67312	0	22580679	2285	1407221	365	37566	15	133	0	0	0	244685	1	4592	0	0	0	41907	0	6002752	113	9939	0	6059190	113	92.52	83.33	20891074	1904	144553	6105512	42.237186360712	22582964.0	22300564.0	67312.0	1407586.0	37581.0	133.0	0.0	244686.0	20892978.0	98.7	0.3	6.2	0.2	0.0	0.0	1.1	92.5	69	76	75.95	37	173539	27.6	22.6	22.7	27.1	0.0	37.0	29.9	bulk
1463626	SRR2075554	SRP059792	SRS969737	SRX1070583	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_WT.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;WT|ID;;3|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_WT.3	RNA-seq of WT P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	3271395288	21799477	2015-09-15 00:00:00	1565180083	3271395288	21799477	2	21799477	index:0,count:21797567,average:75.22,stdev:4.04|index:1,count:21798586,average:74.86,stdev:5.14	SAMN03785070.bam						2.55	3.27	0.16	3059571786	3016778223	2866054641	2838556398	98.6	99.04	21525754	19745785	200.061	990.741	148	176141	77.66	82.93	23890740	16716960	23890740	16716960	79.94	79.82	23890740	17207667	23890740	16089249	486104887	15.89	0.27	0.00	6.28	19.31	0.18	0.96	0.00	0.00	0.00	0.00	1.06	0.00	21526225	2774	150	75	149.31	75.87	1.57	0.00	0.00	0.00	1.20	0.00	0.00	0.00	516.24	10.08	0.10	0.01	58563	0	21796676	2801	1369406	541	39441	27	116	0	0	0	230894	0	4390	0	0	0	40097	0	5697633	160	9490	0	5751610	160	92.48	79.72	20156819	2233	146367	5797760	39.611114527182	21799477.0	21528999.0	58563.0	1369947.0	39468.0	116.0	0.0	230894.0	20159052.0	98.8	0.3	6.3	0.2	0.0	0.0	1.1	92.5	68	76	75.94	37	212712	27.7	22.8	22.8	26.6	0.0	37.1	30.1	bulk
1463642	SRR2075555	SRP059792	SRS969765	SRX1070584	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_Zeb2-KO.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;Zeb2-KO|ID;;4|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Zeb2-KO.1	RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	4697472880	31421204	2015-09-15 00:00:00	2365849366	4697472880	31421204	2	31421204	index:0,count:31418646,average:74.78,stdev:4.91|index:1,count:31419973,average:74.73,stdev:5.34	SAMN03785071.bam						3.17	3.45	0.07	4180626032	4146201995	3848486382	3837139003	99.18	99.71	30907663	28489174	182.836	998.611	130	284404	83.39	90.66	35189515	25773942	35189515	25773942	86.75	86.97	35189515	26811812	35189515	24723063	340538070	8.15	0.39	0.00	7.89	16.28	0.23	1.11	0.00	0.00	0.00	0.00	1.39	0.00	30908633	3747	149	75	148.55	75.82	1.62	0.00	0.01	0.00	1.25	0.00	0.00	0.00	377.01	13.64	0.13	0.01	121465	0	31417415	3789	2480129	617	73096	42	130	0	0	0	435556	0	7385	0	0	0	60988	2	9144810	238	16359	0	9229542	240	90.49	82.61	28428504	3130	168262	9111411	54.150140851767	31421204.0	30912380.0	121465.0	2480746.0	73138.0	130.0	0.0	435556.0	28431634.0	98.4	0.4	7.9	0.2	0.0	0.0	1.4	90.5	68	76	75.93	38	287694	27.4	22.6	22.4	27.6	0.0	36.8	29.6	bulk
1463657	SRR2075556	SRP059792	SRS969764	SRX1070585	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_Zeb2-KO.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;Zeb2-KO|ID;;5|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Zeb2-KO.2	RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	10618535578	70671364	2015-09-15 00:00:00	4561325664	10618535578	70671364	2	70671364	index:0,count:70668536,average:75.18,stdev:4.12|index:1,count:70668754,average:75.07,stdev:4.66	SAMN03785072.bam						3.1	3.45	0.07	9344063878	9311161641	8636393482	8649154155	99.65	100.15	69454935	63367435	181.987	1092.197	126	627189	84.92	91.96	78756210	58979249	78756210	58979249	87.92	88.18	78756210	61063011	78756210	56558086	666384994	7.13	0.34	0.02	7.53	13.74	0.27	0.99	0.00	0.07	0.00	0.00	1.45	0.00	69456716	5380	150	75	149.34	75.72	1.69	0.00	0.00	0.00	1.30	0.00	0.00	0.00	439.37	9.79	0.10	0.02	237249	1	70665926	5438	5319970	747	187805	54	276	4	0	0	1021129	0	19758	0	0	0	160717	2	23084395	601	32977	0	23297847	603	90.76	85.20	64136746	4633	228666	22637353	98.997459176266	70671364.0	69462096.0	237250.0	5320717.0	187859.0	280.0	0.0	1021129.0	64141379.0	98.3	0.3	7.5	0.3	0.0	0.0	1.4	90.8	67	76	75.90	38	412760	26.0	23.3	23.0	27.8	0.0	36.4	28.9	bulk
1463673	SRR2075557	SRP059792	SRS969736	SRX1070586	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_Zeb2-KO.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;Zeb2-KO|ID;;6|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Zeb2-KO.3	RNA-seq of Zeb2-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	7155862794	47650619	2015-09-15 00:00:00	3241177393	7155862794	47650619	2	47650619	index:0,count:47648596,average:75.20,stdev:4.11|index:1,count:47648774,average:74.98,stdev:4.89	SAMN03785073.bam						2.84	3.49	0.06	6468975618	6439034933	5936734199	5938482042	99.54	100.03	46859483	42789257	191.628	1069.024	134	419066	85.4	93.13	53605529	40019266	53605529	40019266	88.93	89.3	53605529	41674381	53605529	38370829	384276545	5.94	0.36	0.03	8.16	15.07	0.22	0.85	0.00	0.05	0.00	0.00	1.42	0.00	46860945	3833	150	75	149.24	75.70	1.70	1.00	0.01	0.00	1.30	0.00	0.00	0.00	443.23	13.92	0.11	0.02	170074	1	47646751	3868	3890157	583	106946	33	177	2	0	0	678683	0	11878	0	0	0	96304	1	14573865	403	26496	0	14708543	404	90.19	84.02	42970788	3250	171398	14685013	85.677855050817	47650619.0	46864778.0	170075.0	3890740.0	106979.0	179.0	0.0	678683.0	42974038.0	98.4	0.4	8.2	0.2	0.0	0.0	1.4	90.2	68	76	75.92	37	293658	26.4	23.3	23.0	27.3	0.0	36.3	28.7	bulk
1463689	SRR2075558	SRP059792	SRS969735	SRX1070587	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_Tbx21-KO.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;Tbx21-KO|ID;;7|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Tbx21-KO.1	RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	4250084294	28647636	2015-09-15 00:00:00	2232260061	4250084294	28647636	2	28647636	index:0,count:28645345,average:74.28,stdev:5.52|index:1,count:28644439,average:74.09,stdev:6.43	SAMN03785074.bam						3.69	3.49	0.08	3805732993	3760040568	3457173185	3441882514	98.8	99.56	28542452	26275044	181.386	688.141	126	254893	81.14	89.43	33123617	23160080	33123617	23160080	85.71	86.0	33123617	24462873	33123617	22270740	352338520	9.26	0.11	0.00	9.24	16.42	0.29	1.08	0.00	0.11	0.00	0.00	0.06	0.00	28542796	5423	148	75	147.52	75.58	1.63	0.00	0.00	0.00	1.25	0.00	0.00	0.00	346.01	9.88	0.13	0.03	31392	0	28642148	5488	2645269	901	82460	59	217	6	0	0	16675	0	6549	0	0	0	57565	7	8345815	794	11573	0	8421502	801	90.42	82.40	25897527	4522	137840	8236121	59.751313116657	28647636.0	28548219.0	31392.0	2646170.0	82519.0	223.0	0.0	16675.0	25902049.0	99.7	0.1	9.2	0.3	0.0	0.0	0.1	90.4	67	76	75.86	38	416296	26.3	23.5	23.0	27.2	0.0	36.6	29.2	bulk
1463705	SRR2075559	SRP059792	SRS969734	SRX1070588	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_Tbx21-KO.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;Tbx21-KO|ID;;8|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Tbx21-KO.2	RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	1966072108	13247236	2015-09-15 00:00:00	1021333298	1966072108	13247236	2	13247236	index:0,count:13245526,average:74.31,stdev:5.48|index:1,count:13245738,average:74.12,stdev:6.38	SAMN03785075.bam						4.77	3.62	0.06	1719798722	1712078663	1531135901	1533384981	99.55	100.15	12953574	11864598	181.453	1060.061	126	116598	82.86	93.17	15441704	10733376	15441704	10733376	89.08	89.3	15441704	11539637	15441704	10286767	100116527	5.82	0.50	0.03	10.83	21.63	0.25	0.84	0.00	0.06	0.00	0.00	1.94	0.00	12954274	3179	148	75	147.49	75.58	1.66	0.00	0.00	0.00	1.28	0.00	0.00	0.00	541.80	5.77	0.15	0.02	66660	1	13244028	3208	1434488	694	32975	27	108	2	0	0	256671	0	3539	0	0	0	26018	1	4007553	388	5789	0	4042899	389	86.98	77.46	11519786	2485	95628	4064657	42.504883506923	13247236.0	12957453.0	66661.0	1435182.0	33002.0	110.0	0.0	256671.0	11522271.0	97.8	0.5	10.8	0.2	0.0	0.0	1.9	87.0	67	76	75.87	37	243377	26.9	23.1	22.7	27.2	0.0	36.7	29.4	bulk
1463896	SRR2075565	SRP059792	SRS969728	SRX1070594	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_TE.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi IL7Rlo T cells|genotype;;WT|ID;;14|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_TE.2	RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	4118172833	27555039	2015-09-15 00:00:00	2017844767	4118172833	27555039	2	27555039	index:0,count:27553292,average:74.83,stdev:4.75|index:1,count:27554000,average:74.63,stdev:5.52	SAMN03785081.bam						1.73	3.22	0.08	3693599548	3664883363	3491323028	3479530643	99.22	99.66	27242730	24935938	185.083	998.548	127	236223	81.48	86.25	29922170	22199061	29922170	22199061	82.86	82.99	29922170	22574975	29922170	21357678	477451117	12.93	0.26	0.00	5.47	13.10	0.18	0.83	0.00	0.07	0.00	0.00	0.94	0.00	27243415	2761	149	75	148.66	75.80	1.62	0.00	0.00	0.00	1.26	0.00	0.00	0.00	495.94	10.03	0.11	0.01	71350	0	27552253	2786	1506752	365	50207	23	131	2	0	0	258500	0	6756	0	0	0	57223	0	7986557	165	11387	0	8061923	165	93.41	86.00	25736663	2396	158303	7901725	49.915194279325	27555039.0	27246176.0	71350.0	1507117.0	50230.0	133.0	0.0	258500.0	25739059.0	98.9	0.3	5.5	0.2	0.0	0.0	0.9	93.4	67	76	75.92	37	211501	27.6	22.2	22.2	28.0	0.0	37.2	30.1	bulk
1463912	SRR2075566	SRP059792	SRS969727	SRX1070595	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_TE.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi IL7Rlo T cells|genotype;;WT|ID;;15|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_TE.3	RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	4785349480	32017867	2015-09-15 00:00:00	2345609463	4785349480	32017867	2	32017867	index:0,count:32010795,average:74.84,stdev:4.73|index:1,count:32016521,average:74.64,stdev:5.50	SAMN03785082.bam						1.74	3.25	0.07	4324288748	4284823699	4093830223	4074907678	99.09	99.54	31650321	28813391	189.228	1095.777	130	261998	83.17	87.89	34679513	26323158	34679513	26323158	84.48	84.69	34679513	26739824	34679513	25363180	485029597	11.22	0.27	0.01	5.32	18.78	0.18	0.87	0.00	0.05	0.00	0.00	0.94	0.00	31651064	8341	149	75	148.67	75.86	1.56	0.00	0.00	0.00	1.25	0.00	0.00	0.00	533.49	30.30	0.11	0.02	87957	1	32009449	8418	1702323	1581	58078	73	140	4	0	0	300167	0	7775	0	0	0	66330	1	9399453	487	13228	0	9486786	488	93.56	80.30	29948741	6760	158929	9341574	58.778284642828	32017867.0	31659405.0	87958.0	1703904.0	58151.0	144.0	0.0	300167.0	29955501.0	98.9	0.3	5.3	0.2	0.0	0.0	0.9	93.6	68	76	75.94	38	639244	28.1	22.5	22.1	27.3	0.0	37.5	31.3	bulk
1464088	SRR2075571	SRP059792	SRS969722	SRX1070600	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_Klrg1hi_WT.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;WT|ID;;20|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_WT.1	RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	3712894099	24779744	2015-09-15 00:00:00	1848546765	3712894099	24779744	2	24779744	index:0,count:24779372,average:75.30,stdev:3.90|index:1,count:24778820,average:74.54,stdev:5.72	SAMN03785087.bam						8.34	3.9	0.04	3215330897	3207536906	2737021492	2752610468	99.76	100.57	24180687	22026811	184.939	1008.035	124	202900	82.68	97.32	29674814	19992855	29674814	19992855	92.66	93.01	29674814	22406215	29674814	19106762	61448375	1.91	0.41	0.00	14.69	17.13	0.18	0.85	0.00	0.08	0.00	0.00	2.22	0.00	24182276	1284	149	75	148.80	75.58	1.99	0.00	0.01	0.00	1.31	0.00	0.00	0.00	474.48	4.67	0.13	0.03	102699	0	24778448	1296	3639896	222	45207	11	131	1	0	0	550834	0	6285	0	0	0	43620	1	7364714	203	10512	0	7425131	204	82.90	81.94	20542380	1062	125464	7270533	57.949156730217	24779744.0	24183560.0	102699.0	3640118.0	45218.0	132.0	0.0	550834.0	20543442.0	97.6	0.4	14.7	0.2	0.0	0.0	2.2	82.9	67	76	75.87	37	98325	24.8	24.6	24.0	26.6	0.0	35.2	27.1	bulk
1464104	SRR2075572	SRP059792	SRS969721	SRX1070601	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_Klrg1hi_WT.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;WT|ID;;21|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_WT.2	RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	3759476667	25068707	2015-09-15 00:00:00	1831394615	3759476667	25068707	2	25068707	index:0,count:25068228,average:75.31,stdev:3.88|index:1,count:25067783,average:74.66,stdev:5.48	SAMN03785088.bam						2.68	3.38	0.09	3342942530	3320290730	3129804029	3123916188	99.32	99.81	24722956	22255420	193.214	1084.719	124	191152	82.63	88.34	27474055	20430454	27474055	20430454	84.96	85.08	27474055	21006355	27474055	19677171	359712549	10.76	0.26	0.00	6.37	8.77	0.21	0.86	0.00	0.50	0.00	0.00	1.16	0.00	24723854	1384	149	75	149.11	75.65	1.58	0.00	0.01	0.00	1.24	0.00	0.00	0.00	379.17	5.05	0.11	0.03	66353	0	25067304	1403	1596250	123	51430	12	108	7	0	0	291912	0	6534	0	0	0	51485	2	7604293	184	12239	0	7674551	186	92.26	89.88	23127604	1261	167967	7449908	44.353402751731	25068707.0	24725238.0	66353.0	1596373.0	51442.0	115.0	0.0	291912.0	23128865.0	98.6	0.3	6.4	0.2	0.0	0.0	1.2	92.3	67	76	75.89	37	106478	25.7	23.7	22.9	27.7	0.0	35.7	27.6	bulk
1464120	SRR2075573	SRP059792	SRS969720	SRX1070602	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_Klrg1hi_WT.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;WT|ID;;22|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_WT.3	RNA-seq of WT KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	3338654728	22265761	2015-09-15 00:00:00	1628060615	3338654728	22265761	2	22265761	index:0,count:22265306,average:75.32,stdev:3.85|index:1,count:22264829,average:74.63,stdev:5.55	SAMN03785089.bam						2.49	3.32	0.09	2925083450	2905982801	2745831693	2740629614	99.35	99.81	21962559	20039055	184.559	992.765	124	180303	79.65	84.94	24336435	17494659	24336435	17494659	81.58	81.56	24336435	17917023	24336435	16797507	409110777	13.99	0.27	0.00	6.14	9.23	0.19	0.65	0.00	0.22	0.00	0.00	1.16	0.00	21963389	1375	149	75	149.10	75.60	1.83	0.00	0.01	0.00	1.31	0.00	0.00	0.00	568.45	4.99	0.11	0.01	60093	0	22264374	1387	1366955	128	42766	9	84	3	0	0	258135	0	5563	0	0	0	43945	4	6349550	164	10515	0	6409573	168	92.51	89.91	20596434	1247	164225	6147522	37.433533262293	22265761.0	21964764.0	60093.0	1367083.0	42775.0	87.0	0.0	258135.0	20597681.0	98.6	0.3	6.1	0.2	0.0	0.0	1.2	92.5	67	76	75.89	37	105255	25.0	24.3	22.9	27.7	0.0	35.5	27.2	bulk
1464136	SRR2075574	SRP059792	SRS969718	SRX1070604	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_Klrg1hi_Zeb2-KO.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;Zeb2-KO|ID;;23|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_Zeb2-KO.1	RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	3566044494	23747291	2015-09-15 00:00:00	1659852141	3566044494	23747291	2	23747291	index:0,count:23746881,average:75.44,stdev:3.50|index:1,count:23746481,average:74.73,stdev:5.35	SAMN03785090.bam						2.58	3.28	0.1	3187366876	3170279139	2985056898	2984021272	99.46	99.97	23408682	21196776	191.103	1070.461	134	186810	83.02	88.71	26031507	19434942	26031507	19434942	85.12	85.27	26031507	19925211	26031507	18681638	330780248	10.38	0.25	0.00	6.32	9.10	0.23	0.57	0.00	0.00	0.00	0.00	1.19	0.08	23409492	1212	150	75	149.32	75.62	1.67	0.00	0.01	0.00	1.24	0.00	0.00	0.00	467.14	4.39	0.10	0.02	59611	0	23746071	1220	1500240	111	54196	7	111	0	0	0	282272	1	6461	0	0	0	50085	1	7369324	162	11689	0	7437559	163	92.26	90.25	21909252	1101	167126	7261324	43.448200758709	23747291.0	23410704.0	59611.0	1500351.0	54203.0	111.0	0.0	282273.0	21910353.0	98.6	0.3	6.3	0.2	0.0	0.0	1.2	92.3	70	76	75.89	37	92591	25.3	23.6	23.4	27.7	0.0	36.1	28.4	bulk
1464153	SRR2075575	SRP059792	SRS969717	SRX1070605	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_Klrg1hi_Zeb2-KO.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;Zeb2-KO|ID;;24|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_Zeb2-KO.2	RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	4151874227	27627259	2015-09-15 00:00:00	1911500375	4151874227	27627259	2	27627259	index:0,count:27626759,average:75.43,stdev:3.55|index:1,count:27626333,average:74.86,stdev:5.07	SAMN03785091.bam						1.99	3.27	0.1	3700536629	3671823816	3471728957	3461225413	99.22	99.7	27259861	24737719	189.793	1060.864	124	217459	82.54	88.05	30276089	22501806	30276089	22501806	84.46	84.64	30276089	23023519	30276089	21630824	401123841	10.84	0.23	0.00	6.17	9.33	0.22	1.05	0.00	0.14	0.00	0.00	1.10	0.00	27260665	1409	150	75	149.47	75.71	1.59	0.00	0.00	0.00	1.22	0.00	0.00	0.00	355.19	5.13	0.10	0.03	64064	0	27625833	1426	1703666	133	60955	15	134	2	0	0	304079	0	7256	0	0	0	57276	1	8430756	161	13103	0	8508391	162	92.51	89.48	25556999	1276	168074	8301209	49.390203124814	27627259.0	27262074.0	64064.0	1703799.0	60970.0	136.0	0.0	304079.0	25558275.0	98.7	0.2	6.2	0.2	0.0	0.0	1.1	92.5	68	76	75.91	37	108249	25.2	23.6	23.3	28.0	0.0	36.2	28.4	bulk
1464168	SRR2075576	SRP059792	SRS969716	SRX1070606	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_Klrg1hi_Zeb2-KO.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;Zeb2-KO|ID;;25|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_Zeb2-KO.3	RNA-seq of Zeb2-KO KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	3611146465	24030261	2015-09-15 00:00:00	1669196530	3611146465	24030261	2	24030261	index:0,count:24029847,average:75.44,stdev:3.52|index:1,count:24029540,average:74.84,stdev:5.12	SAMN03785092.bam						3.24	3.39	0.1	3116313942	3104340801	2895116969	2899349870	99.62	100.15	23638927	21430937	183.174	1041.748	115	192493	83.57	90.07	26609752	19756379	26609752	19756379	86.41	86.59	26609752	20427644	26609752	18992425	284191826	9.12	0.27	0.09	7.10	9.52	0.25	0.53	0.00	0.00	0.00	0.00	1.37	0.00	23639697	1129	150	75	149.39	75.62	1.71	0.00	0.01	0.00	1.26	0.00	0.00	0.00	371.27	2.04	0.10	0.02	65359	1	24029126	1135	1705136	108	59566	6	108	0	0	0	329755	0	7176	0	0	0	51526	1	7622541	167	11599	0	7692842	168	91.28	89.96	21934561	1021	165970	7299932	43.983442790866	24030261.0	23640826.0	65360.0	1705244.0	59572.0	108.0	0.0	329755.0	21935582.0	98.4	0.3	7.1	0.2	0.0	0.0	1.4	91.3	68	76	75.92	37	86174	24.6	23.7	23.6	28.2	0.0	36.1	28.1	bulk
1464185	SRR2075577	SRP059792	SRS969715	SRX1070607	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_Klrg1hi_TBET-RV.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;T-bet RV|ID;;26|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_TBET-RV.1	RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	3567718971	25031584	2015-09-15 00:00:00	1815351030	3567718971	25031584	2	25031584	index:0,count:25031572,average:75.43,stdev:3.61|index:1,count:25030879,average:67.10,stdev:4.97	SAMN03785093.bam						2.09	3.16	0.07	3256492188	3231233021	3056336232	3044891826	99.22	99.63	24715119	22185173	195.226	1125.147	124	191314	81.39	86.76	27339622	20116386	27339622	20116386	83.48	83.5	27339622	20632810	27339622	19360664	395965083	12.16	0.60	0.00	6.11	7.39	0.16	0.84	0.00	0.00	0.00	0.00	1.10	0.00	24715657	711	142	75	140.24	75.66	1.67	0.00	0.01	0.00	1.25	0.00	0.00	0.00	549.46	2.58	0.15	0.02	150914	0	25030867	717	1529735	53	39577	6	89	0	0	0	275544	0	5289	0	0	0	44107	0	6355126	99	10520	0	6415042	99	92.63	91.77	23185922	658	157174	6454523	41.066098718618	25031584.0	24716368.0	150914.0	1529788.0	39583.0	89.0	0.0	275544.0	23186580.0	98.7	0.6	6.1	0.2	0.0	0.0	1.1	92.6	67	76	75.88	37	54406	25.6	23.7	23.4	27.2	0.0	35.1	26.7	bulk
1464203	SRR2075578	SRP059792	SRS969714	SRX1070608	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_Klrg1hi_TBET-RV.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;T-bet RV|ID;;27|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_TBET-RV.2	RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	3771368958	26448480	2015-09-15 00:00:00	1918594250	3771368958	26448480	2	26448480	index:0,count:26448469,average:75.39,stdev:3.75|index:1,count:26447839,average:67.20,stdev:4.82	SAMN03785094.bam						2.81	3.36	0.08	3318589880	3306801154	3085953890	3090596748	99.64	100.15	26024446	23386365	186.006	1143.483	114	208298	83.06	89.41	29212558	21616548	29212558	21616548	85.79	85.93	29212558	22325683	29212558	20775059	322265942	9.71	0.74	0.00	6.99	7.82	0.21	0.61	0.00	0.00	0.00	0.00	1.39	0.00	26025017	648	142	75	140.20	75.56	1.82	0.00	0.01	0.00	1.27	0.00	0.00	0.00	534.90	2.35	0.15	0.03	195740	0	26447828	652	1848071	51	56127	4	115	0	0	0	366569	0	6278	0	0	0	47728	0	7114443	85	11946	0	7180395	85	91.41	91.56	24176946	597	165875	7053564	42.523370007536	26448480.0	26025665.0	195740.0	1848122.0	56131.0	115.0	0.0	366569.0	24177543.0	98.4	0.7	7.0	0.2	0.0	0.0	1.4	91.4	67	76	75.87	37	49467	25.2	23.9	23.9	27.0	0.0	35.4	26.6	bulk
1464219	SRR2075579	SRP059792	SRS969712	SRX1070609	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_Klrg1hi_TBET-RV.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;T-bet RV|ID;;28|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_TBET-RV.3	RNA-seq of T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	3591505504	25184020	2015-09-15 00:00:00	1824034508	3591505504	25184020	2	25184020	index:0,count:25184009,average:75.42,stdev:3.67|index:1,count:25183458,average:67.19,stdev:4.83	SAMN03785095.bam						2.85	3.34	0.08	3167691387	3156444898	2948221574	2952499391	99.64	100.15	24790213	22278479	186.478	1125.290	113	198944	82.78	89.02	27776612	20521361	27776612	20521361	85.5	85.61	27776612	21195878	27776612	19735296	320581086	10.12	0.74	0.00	6.91	8.38	0.20	0.70	0.00	0.00	0.00	0.00	1.35	0.00	24790806	569	142	75	140.22	75.48	1.81	0.00	0.01	0.00	1.26	0.00	0.00	0.00	460.21	2.06	0.16	0.03	186068	0	25183447	573	1739041	48	51596	4	104	0	0	0	340941	0	6013	0	0	0	45230	0	6701979	89	11637	0	6764859	89	91.54	90.92	23051765	521	164315	6654566	40.498834555579	25184020.0	24791375.0	186068.0	1739089.0	51600.0	104.0	0.0	340941.0	23052286.0	98.4	0.7	6.9	0.2	0.0	0.0	1.4	91.5	67	76	75.87	38	43476	24.9	23.7	23.6	27.9	0.0	34.9	26.3	bulk
1464331	SRR2075580	SRP059792	SRS969711	SRX1070610	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_Klrg1hi_Zeb2-KO_TBET-RV.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;Zeb2-KO T-bet RV|ID;;29|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_Zeb2-KO_TBET-RV.1	RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	3084072007	21637092	2015-09-15 00:00:00	1578321861	3084072007	21637092	2	21637092	index:0,count:21637086,average:75.43,stdev:3.64|index:1,count:21636495,average:67.11,stdev:4.93	SAMN03785096.bam						2.67	3.28	0.08	2771768599	2760070440	2580592006	2582467868	99.58	100.07	21295340	19130025	191.128	1125.488	124	171624	82.94	89.13	23860310	17662826	23860310	17662826	85.67	85.8	23860310	18243883	23860310	17003272	280145749	10.11	0.71	0.00	6.84	9.12	0.22	0.66	0.00	0.00	0.00	0.00	1.36	0.00	21295851	599	142	75	140.19	75.67	1.64	0.00	0.01	0.00	1.24	0.00	0.00	0.00	350.86	2.17	0.16	0.05	152939	0	21636489	603	1479610	55	46623	4	67	0	0	0	293948	0	5037	0	0	0	39652	1	5783881	81	9927	0	5838497	82	91.59	90.22	19816241	544	157491	5825178	36.987370706898	21637092.0	21296450.0	152939.0	1479665.0	46627.0	67.0	0.0	293948.0	19816785.0	98.4	0.7	6.8	0.2	0.0	0.0	1.4	91.6	67	76	75.87	37	45751	24.9	24.0	23.1	28.0	0.0	35.1	26.2	bulk
1464347	SRR2075581	SRP059792	SRS969710	SRX1070611	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_Klrg1hi_Zeb2-KO_TBET-RV.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;Zeb2-KO T-bet RV|ID;;30|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_Zeb2-KO_TBET-RV.2	RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	3814902302	26750736	2015-09-15 00:00:00	1943335003	3814902302	26750736	2	26750736	index:0,count:26750728,average:75.41,stdev:3.70|index:1,count:26750153,average:67.20,stdev:4.81	SAMN03785097.bam						2.66	3.28	0.09	3353275844	3338897991	3126654296	3128958120	99.57	100.07	26322598	23756265	184.126	1109.236	113	220101	81.84	87.85	29446955	21542460	29446955	21542460	84.47	84.53	29446955	22235296	29446955	20729786	382609026	11.41	0.74	0.17	6.73	9.64	0.23	1.18	0.00	0.00	0.00	0.00	1.36	0.00	26323080	584	142	75	140.20	75.54	1.63	0.00	0.01	0.00	1.26	0.00	0.00	0.00	501.57	2.13	0.16	0.03	197943	1	26750145	591	1799828	57	62626	7	113	0	0	0	364326	0	6260	1	0	0	47411	0	7067134	85	12504	0	7133309	86	91.68	89.17	24523252	527	164528	7012208	42.620149761743	26750736.0	26323664.0	197944.0	1799885.0	62633.0	113.0	0.0	364326.0	24523779.0	98.4	0.7	6.7	0.2	0.0	0.0	1.4	91.7	67	76	75.88	37	44843	24.8	23.9	24.0	27.3	0.0	35.1	26.4	bulk
1464366	SRR2075582	SRP059792	SRS969709	SRX1070612	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_Klrg1hi_Zeb2-KO_TBET-RV.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi T cells|genotype;;Zeb2-KO T-bet RV|ID;;31|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Klrg1hi_Zeb2-KO_TBET-RV.3	RNA-seq of Zeb2-KO T-bet RV KLRG1hi P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	3433999353	24082710	2015-09-15 00:00:00	1753599394	3433999353	24082710	2	24082710	index:0,count:24082702,average:75.41,stdev:3.68|index:1,count:24082167,average:67.18,stdev:4.82	SAMN03785098.bam						2.68	3.3	0.08	3017545626	3002746030	2815453920	2815079406	99.51	99.99	23704632	21399487	184.195	1104.470	114	196239	81.77	87.72	26495602	19384713	26495602	19384713	84.38	84.43	26495602	20003044	26495602	18656428	346608783	11.49	0.73	0.18	6.67	7.62	0.23	0.73	0.00	0.36	0.00	0.00	1.34	0.00	23705055	545	142	75	140.23	75.66	1.62	0.00	0.00	0.00	1.26	0.00	0.00	0.00	453.90	1.98	0.15	0.02	176067	1	24082159	551	1607257	42	54703	4	84	2	0	0	322317	0	5633	0	0	0	42869	2	6343750	65	10660	0	6402912	67	91.76	91.29	22097798	503	161895	6286733	38.832162821582	24082710.0	23705600.0	176068.0	1607299.0	54707.0	86.0	0.0	322317.0	22098301.0	98.4	0.7	6.7	0.2	0.0	0.0	1.3	91.8	69	76	75.89	37	41815	25.4	23.9	23.8	27.0	0.0	35.3	27.1	bulk
731910	SRR2075560	SRP059792	SRS969733	SRX1070589	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_Tbx21-KO.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ T cells|genotype;;Tbx21-KO|ID;;9|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_Tbx21-KO.3	RNA-seq of Tbx21-KO P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	4194733009	28146901	2015-09-15 00:00:00	2027967467	4194733009	28146901	2	28146901	index:0,count:28145421,average:74.59,stdev:4.75|index:1,count:28144648,average:74.45,stdev:5.92	SAMN03785076.bam						3.33	3.39	0.06	3743187806	3736734870	3394989509	3407281833	99.83	100.36	27608874	25072126	188.542	1049.675	126	243613	84.78	93.56	32234346	23408079	32234346	23408079	89.52	89.82	32234346	24716572	32234346	22473157	211004065	5.64	0.51	0.03	9.20	17.73	0.24	1.18	0.00	0.05	0.00	0.00	1.66	0.03	27610299	3686	149	75	148.13	75.51	1.79	0.00	0.00	0.00	1.28	0.00	0.00	0.00	541.79	6.72	0.14	0.02	143643	1	28143168	3733	2589753	662	66830	44	129	2	0	0	465910	1	8586	0	0	0	59179	3	8945303	609	12225	0	9025293	612	88.90	81.01	25020546	3024	107263	9225622	86.009360170795	28146901.0	27613985.0	143644.0	2590415.0	66874.0	131.0	0.0	465911.0	25023570.0	98.1	0.5	9.2	0.2	0.0	0.0	1.7	88.9	67	76	75.80	37	282959	25.6	23.8	23.2	27.4	0.0	36.5	28.9	bulk
731918	SRR2075561	SRP059792	SRS969732	SRX1070590	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_MP.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1lo IL7Rhi T cells|genotype;;WT|ID;;10|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_MP.1	RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	4937775836	33043797	2015-09-15 00:00:00	2437119860	4937775836	33043797	2	33043797	index:0,count:33042378,average:74.74,stdev:5.00|index:1,count:33042754,average:74.70,stdev:5.40	SAMN03785077.bam						1.85	3.34	0.09	4356412648	4306930215	4099746803	4074110498	98.86	99.37	32635444	30123306	178.677	1030.218	126	286900	80.75	85.87	36100781	26354845	36100781	26354845	82.48	82.64	36100781	26917019	36100781	25363518	567329328	13.02	0.26	0.04	5.89	10.07	0.21	0.89	0.00	0.20	0.00	0.00	1.02	0.00	32636251	2435	149	75	148.66	75.80	1.61	0.00	0.00	0.00	1.23	0.00	0.00	0.00	466.47	4.43	0.10	0.01	84890	1	33041335	2462	1945247	248	68115	22	178	5	0	0	336791	0	7302	0	0	0	65953	2	9289153	140	13336	0	9375744	142	92.89	88.83	30691004	2187	160329	9102012	56.770839960332	33043797.0	32638686.0	84891.0	1945495.0	68137.0	183.0	0.0	336791.0	30693191.0	98.8	0.3	5.9	0.2	0.0	0.0	1.0	92.9	67	76	75.91	37	186891	27.0	22.2	21.9	28.9	0.0	36.7	29.0	bulk
731926	SRR2075562	SRP059792	SRS969731	SRX1070591	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 2		RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	CD8_MP.2	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1lo IL7Rhi T cells|genotype;;WT|ID;;11|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_MP.2	RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 2	4175098150	27939785	2015-09-15 00:00:00	2055957673	4175098150	27939785	2	27939785	index:0,count:27938614,average:74.74,stdev:4.99|index:1,count:27938912,average:74.69,stdev:5.41	SAMN03785078.bam						2.19	3.34	0.09	3685121842	3651606676	3441412905	3428190498	99.09	99.62	27561502	25371576	179.538	1012.047	126	244964	81.18	87.0	30817948	22374066	30817948	22374066	83.48	83.61	30817948	23007651	30817948	21502855	439672170	11.93	0.28	0.00	6.60	13.01	0.22	0.44	0.00	0.10	0.00	0.00	1.13	0.00	27562259	2033	149	75	148.63	75.81	1.68	0.00	0.00	0.00	1.25	0.00	0.00	0.00	523.83	7.36	0.10	0.01	76953	0	27937741	2044	1843574	266	60095	9	166	2	0	0	315221	0	6468	0	0	0	57643	1	8082322	134	11363	0	8157796	135	92.06	86.45	25718685	1767	153718	7943054	51.672894521136	27939785.0	27564292.0	76953.0	1843840.0	60104.0	168.0	0.0	315221.0	25720452.0	98.7	0.3	6.6	0.2	0.0	0.0	1.1	92.1	67	76	75.90	37	155132	27.0	22.5	22.5	28.0	0.0	36.7	29.0	bulk
731934	SRR2075563	SRP059792	SRS969730	SRX1070592	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 3		RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	CD8_MP.3	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1lo IL7Rhi T cells|genotype;;WT|ID;;12|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_MP.3	RNA-seq of MP (KLRG1lo IL7Rhi) P14 CTLs isolated 8 d.p.i. with LCMV replicate 3	3712913814	24838555	2015-09-15 00:00:00	1826755768	3712913814	24838555	2	24838555	index:0,count:24836929,average:74.77,stdev:4.95|index:1,count:24837798,average:74.72,stdev:5.35	SAMN03785079.bam						1.88	3.35	0.09	3278983220	3240735076	3084434257	3064299784	98.83	99.35	24526299	22611406	179.862	1031.295	125	215273	80.78	85.94	27154430	19812780	27154430	19812780	82.5	82.67	27154430	20233966	27154430	19057426	423663994	12.92	0.27	0.00	5.93	15.65	0.21	1.01	0.00	0.04	0.00	0.00	1.04	0.00	24526924	2358	149	75	148.71	75.81	1.64	0.00	0.00	0.00	1.25	0.00	0.00	0.00	516.82	8.58	0.10	0.02	66078	0	24836172	2383	1473219	373	52054	24	131	1	0	0	257063	0	5769	0	0	0	49683	0	6985485	129	10117	0	7051054	129	92.82	83.30	23053705	1985	150860	6853476	45.429378231473	24838555.0	24529282.0	66078.0	1473592.0	52078.0	132.0	0.0	257063.0	23055690.0	98.8	0.3	5.9	0.2	0.0	0.0	1.0	92.8	68	76	75.92	37	180911	27.1	22.5	22.0	28.4	0.0	37.0	29.6	bulk
731942	SRR2075564	SRP059792	SRS969729	SRX1070593	SRA273724	Yale University	Kaech Lab	The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation	T-bet is critical for cytotoxic T lymphocyte (CTL) differentiation, but it is unclear how it operates in a graded manner in the formation of both terminal effector and memory precursor cells during infection. We find that at high concentrations T-bet induced expression of Zeb2 mRNA, which then triggered CTLs to adopt terminally differentiated states. ZEB2 and T-bet cooperate to switch on a terminal CTL differentiation program, while simultaneously repressing genes necessary for central memory CTL development. Chromatin Immunoprecipitation sequencing (ChIP-seq) showed that a large proportion of these genes were bound by T-bet, and this binding was altered by ZEB2 deficiency. Furthermore, T-bet overexpression could not fully bypass ZEB2 function. Thus, the coordinated actions of T-bet and ZEB2 outline a novel genetic pathway that forces commitment of CTLs to terminal differentiation, thereby restricting their memory cell potential.		RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 1		RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	CD8_TE.1	RNA-Seq	TRANSCRIPTOMIC	other	paired				Illumina HiSeq 2500	age;;6-8 weeks|BioSampleModel;;Model organism or animal|breed;;C57BL/6|cell_type;;P14 CD8+ KLRG1hi IL7Rlo T cells|genotype;;WT|ID;;13|sex;;female|tissue;;Splenocytes	alignment_software;;STAR	150	CD8_TE.1	RNA-seq of TE (KLRGhi IL7Rlo) P14 CTLs isolated 8 d.p.i. with LCMV replicate 1	4799024730	32097932	2015-09-15 00:00:00	2348757290	4799024730	32097932	2	32097932	index:0,count:32095565,average:74.86,stdev:4.69|index:1,count:32096782,average:74.66,stdev:5.46	SAMN03785080.bam						1.74	3.27	0.07	4270701167	4232975307	4039610576	4021017208	99.12	99.54	31736713	29093409	182.587	1041.994	125	276378	82.35	87.12	34812375	26136255	34812375	26136255	83.72	83.88	34812375	26569571	34812375	25164618	511985710	11.99	0.27	0.00	5.41	14.96	0.18	0.97	0.00	0.09	0.00	0.00	0.93	0.00	31737407	3480	149	75	148.71	75.79	1.54	0.00	0.00	0.00	1.23	0.00	0.00	0.00	552.82	12.66	0.11	0.01	87206	0	32094415	3517	1735425	526	57016	34	140	3	0	0	299852	0	7834	0	0	0	65891	2	9309732	214	13598	0	9397055	216	93.48	83.99	30001982	2954	156936	9154851	58.334932711424	32097932.0	31740887.0	87206.0	1735951.0	57050.0	143.0	0.0	299852.0	30004936.0	98.9	0.3	5.4	0.2	0.0	0.0	0.9	93.5	69	76	75.92	38	266994	27.3	22.6	22.5	27.6	0.0	37.2	30.2	bulk
1347848	SRR2097910	SRP060340	SRS988460	SRX1092968	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of K918		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K918|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW32_QW28_K918	TW32_QW28_K918-pri_03_11_2013	6160279300	61602793	2016-02-12 14:00:02	3696484788	6160279300	61602793	2	61602793	index:0,count:61602793,average:50,stdev:0|index:1,count:61602793,average:50,stdev:0	TW32_QW28_K918				in_mesa	26977878	3.26	2.56	0.19	5360816650	5414536323	4878225159	5000456832	101.0	102.51	54318424	42855516	268.469	1509.184	148	261765	80.14	88.04	62682946	43529454	62682946	43529454	81.22	81.93	62682946	44119524	62682946	40509119	546912739	10.20	4.01	0	7.92	0	0.33	0	0.18	0	0.00	0	11.31	0	54318424	0	100	0	98.79	0	3.41	0	0.02	0	1.47	0	0.01	0	350.90	0	0.28	0	2467245	0	61602793	0	4877237	0	204755	0	112989	0	0	0	6966625	0	5698	0	0	0	43950	0	8058390	0	26062	0	8134100	0	80.26	0	49441187	0	182513	8382978	45.930854240520	61602793.0	54318424.0	2467245.0	4877237.0	204755.0	112989.0	0.0	6966625.0	49441187.0	88.2	4.0	7.9	0.3	0.2	0.0	11.3	80.3	50	50	50.00	38	3080139650	24.7	25.2	25.1	25.0	0.0	38.3	26.8	bulk
1347864	SRR2097911	SRP060340	SRS988461	SRX1092969	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of K249		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K249|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW33_QW29_K249	TW33_QW29_K249-pri_03_11_2013	7849304800	78493048	2016-02-12 14:03:08	4775967856	7849304800	78493048	2	78493048	index:0,count:78493048,average:50,stdev:0|index:1,count:78493048,average:50,stdev:0	TW33_QW29_K249				in_mesa	26977878	4.85	3.15	0.13	7021496848	6992402170	6235852839	6281073711	99.59	100.73	71143442	58772471	241.762	1201.635	137	425700	78.97	88.88	84816857	56181350	84816857	56181350	85.29	85.4	84816857	60675113	84816857	53980010	719034994	10.24	2.89	0	10.11	0	0.52	0	0.34	0	0.00	0	8.50	0	71143442	0	100	0	98.80	0	2.18	0	0.01	0	1.40	0	0.01	0	491.43	0	0.26	0	2265380	0	78493048	0	7931727	0	405041	0	270638	0	0	0	6673927	0	7757	0	0	0	58429	0	10367189	0	33377	0	10466752	0	80.53	0	63211715	0	202446	10886664	53.775643875404	78493048.0	71143442.0	2265380.0	7931727.0	405041.0	270638.0	0.0	6673927.0	63211715.0	90.6	2.9	10.1	0.5	0.3	0.0	8.5	80.5	50	50	50.00	38	3924652400	25.3	24.5	24.7	25.4	0.0	38.2	26.0	bulk
1347880	SRR2097912	SRP060340	SRS988462	SRX1092970	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of K424		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K424|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW34_QW30_K424	TW34_QW30_K424-pri_03_11_2013	7192436300	71924363	2016-02-12 14:03:03	4376518591	7192436300	71924363	2	71924363	index:0,count:71924363,average:50,stdev:0|index:1,count:71924363,average:50,stdev:0	TW34_QW30_K424				in_mesa	26977878	3.36	2.94	0.21	6428489600	6418434943	5922957109	5976504133	99.84	100.9	65128163	52526218	248.732	1366.137	136	358970	81.15	88.06	73877275	52853217	73877275	52853217	83.68	84.18	73877275	54499481	73877275	50525315	704815875	10.96	2.99	0	7.10	0	0.30	0	0.32	0	0.00	0	8.83	0	65128163	0	100	0	98.82	0	2.39	0	0.01	0	1.45	0	0.01	0	195.71	0	0.27	0	2149699	0	71924363	0	5106920	0	215916	0	231528	0	0	0	6348756	0	6536	0	0	0	52649	0	10259142	0	28356	0	10346683	0	83.45	0	60021243	0	197359	10671492	54.071473811683	71924363.0	65128163.0	2149699.0	5106920.0	215916.0	231528.0	0.0	6348756.0	60021243.0	90.6	3.0	7.1	0.3	0.3	0.0	8.8	83.5	50	50	50.00	38	3596218150	25.3	24.6	24.7	25.4	0.0	38.2	25.6	bulk
1348152	SRR2097923	SRP060340	SRS988472	SRX1092981	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of B10-R23		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;B10-R23|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW35_QW54_B10_R23	TW35_QW54_B10-R23-pri_03_11_2013	7471681500	74716815	2016-02-12 14:02:58	4522085336	7471681500	74716815	2	74716815	index:0,count:74716815,average:50,stdev:0|index:1,count:74716815,average:50,stdev:0	TW35_QW54_B10_R23				in_mesa	26977878	4.84	2.94	0.09	6516472788	6553708305	5783704707	5906223939	100.57	102.12	66007645	55436830	243.421	1119.486	136	396647	81.96	92.29	78599719	54096591	78599719	54096591	86.34	87.15	78599719	56988298	78599719	51079475	418228232	6.42	3.59	0	9.90	0	0.41	0	0.26	0	0.00	0	10.98	0	66007645	0	100	0	98.81	0	2.60	0	0.01	0	1.40	0	0.01	0	470.25	0	0.27	0	2685404	0	74716815	0	7394142	0	309511	0	195828	0	0	0	8203831	0	7393	0	0	0	49660	0	9141428	0	28362	0	9226843	0	78.45	0	58613503	0	184446	9481348	51.404465263546	74716815.0	66007645.0	2685404.0	7394142.0	309511.0	195828.0	0.0	8203831.0	58613503.0	88.3	3.6	9.9	0.4	0.3	0.0	11.0	78.4	50	50	50.00	38	3735840750	25.0	24.9	25.0	25.1	0.0	38.2	25.6	bulk
329111	SRR2098165	SRP060340	SRS988669	SRX1093177	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of L917L1		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;L917L1|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW42_QW36_L917L1	TW42_QW36_L917L1-rec_03_11_2013	3403639300	34036393	2016-02-12 14:02:13	2009587465	3403639300	34036393	2	34036393	index:0,count:34036393,average:50,stdev:0|index:1,count:34036393,average:50,stdev:0	TW42_QW36_L917L1				in_mesa	26977878	1.84	3.26	0.22	3114382687	3115405827	2858472395	2885747738	100.03	100.95	31541111	24997686	258.174	1617.986	142	162501	82.41	89.76	36310907	25992639	36310907	25992639	85.68	86.21	36310907	27024744	36310907	24963389	306672134	9.85	3.06	0	7.59	0	0.47	0	0.31	0	0.00	0	6.55	0	31541111	0	100	0	98.86	0	2.18	0	0.01	0	1.43	0	0.01	0	373.57	0	0.26	0	1040829	0	34036393	0	2583837	0	160054	0	104753	0	0	0	2230475	0	3748	0	0	0	30302	0	4980048	0	14252	0	5028350	0	85.08	0	28957274	0	163575	5166341	31.583927861837	34036393.0	31541111.0	1040829.0	2583837.0	160054.0	104753.0	0.0	2230475.0	28957274.0	92.7	3.1	7.6	0.5	0.3	0.0	6.6	85.1	50	50	50.00	38	1701819650	24.8	25.1	25.0	25.0	0.0	38.5	26.6	bulk
329115	SRR2098166	SRP060340	SRS988670	SRX1093178	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of K285R		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K285R|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW43_QW51_K285R	TW43_QW51_K285R-rec_03_11_2013	4862660500	48626605	2016-02-12 14:02:06	2725252428	4862660500	48626605	2	48626605	index:0,count:48626605,average:50,stdev:0|index:1,count:48626605,average:50,stdev:0	TW43_QW51_K285R				in_mesa	26977878	2.57	3.08	0.13	4483203593	4472784625	4045979611	4079019263	99.77	100.82	45385034	37434859	246.802	1218.195	136	272747	85.32	94.5	53426906	38721309	53426906	38721309	90.2	91.11	53426906	40936938	53426906	37333440	229989295	5.13	2.84	0	9.07	0	0.54	0	0.37	0	0.00	0	5.75	0	45385034	0	100	0	98.90	0	1.83	0	0.01	0	1.41	0	0.01	0	414.82	0	0.21	0	1379197	0	48626605	0	4409569	0	264727	0	179462	0	0	0	2797382	0	6383	0	0	0	41081	0	7040617	0	19456	0	7107537	0	84.27	0	40975465	0	156833	7250977	46.233745448981	48626605.0	45385034.0	1379197.0	4409569.0	264727.0	179462.0	0.0	2797382.0	40975465.0	93.3	2.8	9.1	0.5	0.4	0.0	5.8	84.3	50	50	50.00	38	2431330250	24.8	25.1	25.1	25.0	0.0	38.8	27.6	bulk
329119	SRR2098167	SRP060340	SRS988671	SRX1093179	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of K424-L2L3,1		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K424-L2L3-1|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW44_QW52_K424-L2L3	TW44_QW52_K424-L2L3-rec_03_11_2013	4362969800	43629698	2016-02-12 14:02:01	2442755945	4362969800	43629698	2	43629698	index:0,count:43629698,average:50,stdev:0|index:1,count:43629698,average:50,stdev:0	TW44_QW52_K424_L2L3				in_mesa	26977878	2.47	3.47	0.1	4070456394	4069311065	3732914360	3761524278	99.97	100.77	41206007	33395071	246.046	1341.835	136	250724	85.55	93.25	47373008	35250900	47373008	35250900	89.66	90.18	47373008	36945296	47373008	34089852	269369474	6.62	2.66	0	7.80	0	0.45	0	0.20	0	0.00	0	4.91	0	41206007	0	100	0	98.91	0	1.86	0	0.01	0	1.42	0	0.01	0	211.97	0	0.20	0	1160799	0	43629698	0	3403839	0	194752	0	85660	0	0	0	2143279	0	5295	0	0	0	39084	0	6977657	0	17092	0	7039128	0	86.64	0	37802168	0	169482	7202805	42.498937940312	43629698.0	41206007.0	1160799.0	3403839.0	194752.0	85660.0	0.0	2143279.0	37802168.0	94.4	2.7	7.8	0.4	0.2	0.0	4.9	86.6	50	50	50.00	38	2181484900	24.8	25.2	25.1	24.9	0.0	38.9	27.9	bulk
329123	SRR2098168	SRP060340	SRS988672	SRX1093180	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of K424-L2L3,2		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K424-L2L3-2|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW45_QW53_K424-L2L3	TW45_QW53_K424-L2L3-rec_03_11_2013	8575302600	85753026	2016-02-12 14:01:55	5274537742	8575302600	85753026	2	85753026	index:0,count:85753026,average:50,stdev:0|index:1,count:85753026,average:50,stdev:0	TW45_QW53_K424_L2L3				in_mesa	26977878	3.06	3.31	0.22	7938912059	7944473842	7142709169	7214621836	100.07	101.01	80394263	68512134	233.615	1027.463	136	542641	84.32	93.68	94766687	67790449	94766687	67790449	89.52	90.11	94766687	71966501	94766687	65205868	475549203	5.99	2.57	0	9.36	0	0.45	0	0.16	0	0.00	0	5.64	0	80394263	0	100	0	98.86	0	2.01	0	0.01	0	1.39	0	0.01	0	208.03	0	0.27	0	2204397	0	85753026	0	8027808	0	382043	0	138125	0	0	0	4838595	0	9732	0	0	0	61389	0	11334030	0	31691	0	11436842	0	84.39	0	72366455	0	180066	11783263	65.438578076927	85753026.0	80394263.0	2204397.0	8027808.0	382043.0	138125.0	0.0	4838595.0	72366455.0	93.8	2.6	9.4	0.4	0.2	0.0	5.6	84.4	50	50	50.00	38	4287651300	24.7	25.1	25.0	24.8	0.3	37.9	23.7	bulk
329127	SRR2098169	SRP060340	SRS988673	SRX1093181	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of K310-L45		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K310-L45|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW46_QW56_K310-L45	TW46_QW56_K310-L45-rec_03_11_2013	6804897500	68048975	2016-02-12 14:01:50	4281236119	6804897500	68048975	2	68048975	index:0,count:68048975,average:50,stdev:0|index:1,count:68048975,average:50,stdev:0	TW46_QW56_K310_L4				in_mesa	26977878	1.09	3.33	0.04	5937263302	5988091575	5401667378	5528114553	100.86	102.34	60309895	44419988	282.123	2072.389	148	255648	85.23	93.64	70478125	51403534	70478125	51403534	86.68	87.99	70478125	52276288	70478125	48302091	279790747	4.71	4.31	0	7.96	0	0.47	0	0.08	0	0.00	0	10.83	0	60309895	0	100	0	98.56	0	3.48	0	0.02	0	1.54	0	0.01	0	416.63	0	0.33	0	2931969	0	68048975	0	5414307	0	316820	0	54477	0	0	0	7367783	0	8067	0	0	0	61408	0	10109471	0	29338	0	10208284	0	80.67	0	54895588	0	178753	10395234	58.154179230558	68048975.0	60309895.0	2931969.0	5414307.0	316820.0	54477.0	0.0	7367783.0	54895588.0	88.6	4.3	8.0	0.5	0.1	0.0	10.8	80.7	50	50	50.00	38	3402448750	24.1	25.8	25.6	24.2	0.3	37.6	22.9	bulk
329159	SRR2098171	SRP060340	SRS988675	SRX1093183	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		normal mammary gland,1		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;MM1|dev_stage;;normal|phenotype;;normal|sex;;not applicable|tissue;;mammary gland		100	TW49_QW48_MTB	TW49_QW48_MTB-Her2-Mg-1_03_11_2013	6349158800	63491588	2016-02-12 14:01:38	3817768672	6349158800	63491588	2	63491588	index:0,count:63491588,average:50,stdev:0|index:1,count:63491588,average:50,stdev:0	TW49_QW48_MTB_Her2				in_mesa	26977878	2.87	3.03	0.24	5684873426	5640340549	5165867094	5209153167	99.22	100.84	57703063	45181948	266.220	1795.875	148	275511	78.71	86.6	67995977	45418220	67995977	45418220	82.08	82.92	67995977	47360300	67995977	43486922	705933231	12.42	3.78	0	8.28	0	0.82	0	0.29	0	0.00	0	8.01	0	57703063	0	100	0	98.69	0	2.48	0	0.01	0	1.50	0	0.01	0	500.15	0	0.27	0	2400062	0	63491588	0	5256106	0	518648	0	183316	0	0	0	5086561	0	6085	0	0	0	62145	0	8463285	0	34221	0	8565736	0	82.60	0	52446957	0	205093	8759258	42.708712632806	63491588.0	57703063.0	2400062.0	5256106.0	518648.0	183316.0	0.0	5086561.0	52446957.0	90.9	3.8	8.3	0.8	0.3	0.0	8.0	82.6	50	50	50.00	38	3174579400	25.0	24.9	25.0	25.2	0.0	38.3	26.3	bulk
329163	SRR2098172	SRP060340	SRS988676	SRX1093184	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		normal mammary gland,2		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;MM2|dev_stage;;normal|phenotype;;normal|sex;;not applicable|tissue;;mammary gland		100	TW50_QW49_MTB	TW50_QW49_MTB-Her2-Mg-2_03_11_2013	6601815100	66018151	2016-02-12 14:01:32	3931549362	6601815100	66018151	2	66018151	index:0,count:66018151,average:50,stdev:0|index:1,count:66018151,average:50,stdev:0	TW50_QW49_MTB_Her2_Mg				in_mesa	26977878	2.36	2.99	0.25	5942616982	5856829767	5443438661	5451881698	98.56	100.16	60236190	47856376	256.503	1581.918	146	314152	77.83	84.95	70430657	46884530	70430657	46884530	80.69	81.6	70430657	48604980	70430657	45032750	815432681	13.72	3.33	0	7.64	0	0.84	0	0.34	0	0.00	0	7.57	0	60236190	0	100	0	98.81	0	2.24	0	0.01	0	1.46	0	0.01	0	508.92	0	0.26	0	2201025	0	66018151	0	5046957	0	557485	0	225611	0	0	0	4998865	0	5683	0	0	0	63239	0	9146651	0	29757	0	9245330	0	83.60	0	55189233	0	204572	9492170	46.400142737031	66018151.0	60236190.0	2201025.0	5046957.0	557485.0	225611.0	0.0	4998865.0	55189233.0	91.2	3.3	7.6	0.8	0.3	0.0	7.6	83.6	50	50	50.00	38	3300907550	25.3	24.6	24.5	25.6	0.0	38.4	26.3	bulk
329170	SRR2098174	SRP060340	SRS988677	SRX1093185	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		normal mammary gland,3		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;MM3|dev_stage;;normal|phenotype;;normal|sex;;not applicable|tissue;;mammary gland		100	TW1_QW45	TW1_QW45_10ML/L_MG_c_1	5783633800	57836338	2016-02-12 14:01:24	3349966289	5783633800	57836338	2	57836338	index:0,count:57836338,average:50,stdev:0|index:1,count:57836338,average:50,stdev:0	TW1_QW45				in_mesa	26977878	14.39	2.89	0.06	5279846446	5207785544	4382690031	4374773252	98.64	99.82	53472904	47035648	211.508	916.581	136	446542	75.35	90.69	66548277	40294267	66548277	40294267	87.59	87.25	66548277	46834355	66548277	38766101	372561645	7.06	2.74	0	15.63	0	0.40	0	0.19	0	0.00	0	6.96	0	53472904	0	100	0	98.87	0	1.81	0	0.01	0	1.39	0	0.01	0	428.42	0	0.36	0	1584097	0	57836338	0	9040983	0	230637	0	107037	0	0	0	4025760	0	4652	0	0	0	34329	0	6776570	0	19259	0	6834810	0	76.82	0	44431921	0	157333	7054236	44.836340754959	57836338.0	53472904.0	1584097.0	9040983.0	230637.0	107037.0	0.0	4025760.0	44431921.0	92.5	2.7	15.6	0.4	0.2	0.0	7.0	76.8	50	50	50.00	38	2891816900	25.6	24.3	24.3	25.7	0.2	38.5	26.1	bulk
329174	SRR2098175	SRP060340	SRS988678	SRX1093186	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		normal mammary gland,4		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;MM4|dev_stage;;normal|phenotype;;normal|sex;;not applicable|tissue;;mammary gland		100	TW2_QW46	TW2_QW46_10ML/L_MG_c_2	5755894500	57558945	2016-02-12 14:01:16	3303641881	5755894500	57558945	2	57558945	index:0,count:57558945,average:50,stdev:0|index:1,count:57558945,average:50,stdev:0	TW2_QW46				in_mesa	26977878	2.43	3.03	0.17	5347769061	5250116144	4859352994	4840050121	98.17	99.6	54151459	46267061	210.719	1035.491	134	443905	80.63	88.7	64178154	43662980	64178154	43662980	85.15	86.19	64178154	46111445	64178154	42424996	543900142	10.17	2.38	0	8.56	0	1.05	0	0.32	0	0.00	0	4.55	0	54151459	0	100	0	98.95	0	1.66	0	0.01	0	1.42	0	0.01	0	409.51	0	0.33	0	1369030	0	57558945	0	4928491	0	605603	0	181813	0	0	0	2620070	0	5067	0	0	0	61441	0	8096818	0	20845	0	8184171	0	85.52	0	49222968	0	201355	8384579	41.640778724144	57558945.0	54151459.0	1369030.0	4928491.0	605603.0	181813.0	0.0	2620070.0	49222968.0	94.1	2.4	8.6	1.1	0.3	0.0	4.6	85.5	50	50	50.00	38	2877947250	25.2	24.9	24.6	25.2	0.2	38.5	26.4	bulk
329178	SRR2098176	SRP060340	SRS988679	SRX1093187	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		normal mammary gland,5		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;MM5|dev_stage;;normal|phenotype;;normal|sex;;not applicable|tissue;;mammary gland		100	TW3_QW47	TW3_QW47_10ML/L_MG_c_3	8435492100	84354921	2016-02-12 14:00:25	5223698856	8435492100	84354921	2	84354921	index:0,count:84354921,average:50,stdev:0|index:1,count:84354921,average:50,stdev:0	TW3_QW47				in_mesa	26977878	2.43	3.12	0.15	7830812593	7723323834	7127587020	7123704247	98.63	99.95	79201290	67222366	216.996	1109.006	136	624512	80.67	88.6	93418123	63889760	93418123	63889760	85.19	86.05	93418123	67474156	93418123	62055901	827547621	10.57	2.60	0	8.40	0	0.92	0	0.32	0	0.00	0	4.86	0	79201290	0	100	0	98.99	0	1.70	0	0.01	0	1.40	0	0.01	0	586.25	0	0.21	0	2194867	0	84354921	0	7087931	0	780241	0	273486	0	0	0	4099904	0	8503	0	0	0	88420	0	12094541	0	31615	0	12223079	0	85.49	0	72113359	0	221183	12442370	56.253735594508	84354921.0	79201290.0	2194867.0	7087931.0	780241.0	273486.0	0.0	4099904.0	72113359.0	93.9	2.6	8.4	0.9	0.3	0.0	4.9	85.5	50	50	50.00	38	4217746050	25.1	25.0	24.7	25.2	0.0	38.1	27.1	bulk
655501	SRR2098011	SRP060340	SRS988497	SRX1093001	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of K249		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K249|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW37_QW31_K249	TW37_QW31_K249-rec_03_11_2013	8501726800	85017268	2016-02-12 14:02:45	5134075478	8501726800	85017268	2	85017268	index:0,count:85017268,average:50,stdev:0|index:1,count:85017268,average:50,stdev:0	TW37_QW31_K249				in_mesa	26977878	2.18	3.35	0.13	7787740378	7791321049	7170241362	7240456613	100.05	100.98	78836795	62403573	260.523	1583.465	146	389466	82.39	89.46	90105870	64957495	90105870	64957495	85.44	85.87	90105870	67357206	90105870	62348961	784915955	10.08	3.02	0	7.33	0	0.46	0	0.16	0	0.00	0	6.65	0	78836795	0	100	0	98.88	0	2.17	0	0.01	0	1.47	0	0.01	0	404.84	0	0.26	0	2566946	0	85017268	0	6228328	0	387673	0	138345	0	0	0	5654455	0	9928	0	0	0	74506	0	12318435	0	32961	0	12435830	0	85.40	0	72608467	0	196222	12645477	64.444746256791	85017268.0	78836795.0	2566946.0	6228328.0	387673.0	138345.0	0.0	5654455.0	72608467.0	92.7	3.0	7.3	0.5	0.2	0.0	6.7	85.4	50	50	50.00	38	4250863400	25.0	25.0	24.9	25.1	0.0	38.2	25.8	bulk
655509	SRR2098012	SRP060340	SRS988515	SRX1093024	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of K915		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K915|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW38_QW32_K915	TW38_QW32_K915-rec_03_11_2013	5884866600	58848666	2016-02-12 14:02:38	3610736238	5884866600	58848666	2	58848666	index:0,count:58848666,average:50,stdev:0|index:1,count:58848666,average:50,stdev:0	TW38_QW32_K915				in_mesa	26977878	6.15	2.88	0.14	5020489047	5080298137	4461976976	4600024390	101.19	103.09	50964798	40434493	279.075	1701.080	148	227284	76.24	85.75	60052804	38854107	60052804	38854107	78.41	78.77	60052804	39961723	60052804	35692624	600441504	11.96	5.08	0	9.60	0	0.34	0	0.33	0	0.00	0	12.73	0	50964798	0	100	0	98.64	0	3.75	0	0.03	0	1.51	0	0.01	0	406.63	0	0.34	0	2989061	0	58848666	0	5652141	0	198758	0	192592	0	0	0	7492518	0	4497	0	0	0	36875	0	6373720	0	27093	0	6442185	0	77.00	0	45312657	0	172622	6572686	38.075598707001	58848666.0	50964798.0	2989061.0	5652141.0	198758.0	192592.0	0.0	7492518.0	45312657.0	86.6	5.1	9.6	0.3	0.3	0.0	12.7	77.0	50	50	50.00	38	2942433300	25.0	24.9	24.9	25.2	0.0	38.0	24.8	bulk
655517	SRR2098013	SRP060340	SRS988516	SRX1093025	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		returrent tissue of K918		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K918|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW39_QW33_K918	TW39_QW33_K-918-rec_03_11_2013	7993907500	79939075	2016-02-12 14:02:29	4844004459	7993907500	79939075	2	79939075	index:0,count:79939075,average:50,stdev:0|index:1,count:79939075,average:50,stdev:0	TW39_QW33_K_918				in_mesa	26977878	3.55	2.97	0.16	7206948116	7235056012	6496772364	6599220950	100.39	101.58	73028653	57922691	271.048	1505.506	134	344462	84.19	93.35	85749645	61481038	85749645	61481038	88.32	88.99	85749645	64499115	85749645	58606656	428040267	5.94	3.39	0	8.97	0	0.41	0	0.14	0	0.00	0	8.10	0	73028653	0	100	0	98.82	0	2.45	0	0.01	0	1.50	0	0.01	0	470.23	0	0.27	0	2707940	0	79939075	0	7167939	0	328757	0	108270	0	0	0	6473395	0	9494	0	0	0	62174	0	11189718	0	30960	0	11292346	0	82.39	0	65860714	0	182568	11541297	63.216428947022	79939075.0	73028653.0	2707940.0	7167939.0	328757.0	108270.0	0.0	6473395.0	65860714.0	91.4	3.4	9.0	0.4	0.1	0.0	8.1	82.4	50	50	50.00	38	3996953750	24.5	25.5	25.4	24.6	0.0	38.2	25.7	bulk
655557	SRR2087018	SRP060340	SRS978926	SRX1081060	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of E681		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;E681|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW28_QW24_E681	TW28_QW24_E681-pri_03_11_2013	8088503900	80885039	2016-02-12 13:59:22	4849571355	8088503900	80885039	2	80885039	index:0,count:80885039,average:50,stdev:0|index:1,count:80885039,average:50,stdev:0	SAMN03839921				in_mesa	26977878	2.77	2.62	0.13	7255891485	7234764284	6712933451	6748915406	99.71	100.54	73617383	59849549	233.385	1165.384	129	469662	83.14	89.85	83228012	61208891	83228012	61208891	86.14	86.62	83228012	63410945	83228012	59011993	684578628	9.43	2.72	0	6.79	0	0.31	0	0.23	0	0.00	0	8.45	0	73617383	0	100	0	98.75	0	2.15	0	0.01	0	1.42	0	0.01	0	207.40	0	0.24	0	2201005	0	80885039	0	5492176	0	249753	0	182463	0	0	0	6835440	0	7445	0	0	0	56553	0	13358785	0	31610	0	13454393	0	84.22	0	68125207	0	192091	13938262	72.560723823604	80885039.0	73617383.0	2201005.0	5492176.0	249753.0	182463.0	0.0	6835440.0	68125207.0	91.0	2.7	6.8	0.3	0.2	0.0	8.5	84.2	50	50	50.00	38	4044251950	25.2	24.8	24.8	25.3	0.0	38.3	26.9	bulk
655749	SRR2087030	SRP060340	SRS978911	SRX1081074	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of K915		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K915|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW29_QW25_K915	TW29_QW25_K915-pri_03_11_2013	7755437700	77554377	2016-02-12 13:54:17	4842608422	7755437700	77554377	2	77554377	index:0,count:77554377,average:50,stdev:0|index:1,count:77554377,average:50,stdev:0	TW29_QW25				in_mesa	26977878	5.95	2.39	0.07	6881682767	6881877036	6158848524	6227775123	100.0	101.12	69894251	51688782	255.063	1364.692	146	358393	83.04	92.72	81685696	58036939	81685696	58036939	88.88	89.33	81685696	62123896	81685696	55915134	454553562	6.61	2.98	0	9.41	0	0.25	0	0.30	0	0.00	0	9.33	0	69894251	0	100	0	98.51	0	2.45	0	0.01	0	1.39	0	0.01	0	187.00	0	0.23	0	2312231	0	77554377	0	7297657	0	195076	0	230353	0	0	0	7234697	0	5272	0	0	0	40541	0	17410814	0	27493	0	17484120	0	80.71	0	62596594	0	173457	18511134	106.718864041232	77554377.0	69894251.0	2312231.0	7297657.0	195076.0	230353.0	0.0	7234697.0	62596594.0	90.1	3.0	9.4	0.3	0.3	0.0	9.3	80.7	50	50	50.00	38	3877718850	25.7	24.0	24.2	26.1	0.0	38.0	26.1	bulk
658204	SRR2098163	SRP060340	SRS988667	SRX1093175	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of E775		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;E775|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW40_QW34_E775	TW40_QW34_E775-rec_03_11_2013	6050228300	60502283	2016-02-12 14:02:24	3663959741	6050228300	60502283	2	60502283	index:0,count:60502283,average:50,stdev:0|index:1,count:60502283,average:50,stdev:0	TW40_QW34_E775				in_mesa	26977878	1.86	3.13	0.21	5352428776	5396355610	4886991560	4993872370	100.82	102.19	54272355	42396116	264.288	1711.781	148	270160	80.85	88.53	62842344	43878142	62842344	43878142	82.3	83.08	62842344	44665233	62842344	41179957	546694984	10.21	3.97	0	7.78	0	0.41	0	0.42	0	0.00	0	9.47	0	54272355	0	100	0	98.75	0	3.12	0	0.02	0	1.52	0	0.01	0	487.27	0	0.28	0	2398977	0	60502283	0	4707258	0	247434	0	251115	0	0	0	5731379	0	6875	0	0	0	53344	0	8558531	0	27924	0	8646674	0	81.92	0	49565097	0	183336	8799046	47.994098267662	60502283.0	54272355.0	2398977.0	4707258.0	247434.0	251115.0	0.0	5731379.0	49565097.0	89.7	4.0	7.8	0.4	0.4	0.0	9.5	81.9	50	50	50.00	38	3025114150	24.6	25.4	25.2	24.8	0.0	38.2	25.7	bulk
658212	SRR2098164	SRP060340	SRS988668	SRX1093176	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of BL-917-R2R3		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;BL-917R2R3|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW41_QW35_BL_917_R2R3	TW41_QW35_BL-917-R2R3-rec_03_11_2013	8839805400	88398054	2016-02-12 14:02:18	5206326594	8839805400	88398054	2	88398054	index:0,count:88398054,average:50,stdev:0|index:1,count:88398054,average:50,stdev:0	TW41_QW35_BL_917_R2R3				in_mesa	26977878	2.44	3.46	0.27	8116915457	8126503414	7394969933	7477497829	100.12	101.12	82224195	65413000	258.057	1543.804	145	431983	82.07	90.06	95555343	67483066	95555343	67483066	86.06	86.51	95555343	70759930	95555343	64824572	777656047	9.58	2.97	0	8.25	0	0.54	0	0.35	0	0.00	0	6.10	0	82224195	0	100	0	98.82	0	2.18	0	0.01	0	1.41	0	0.01	0	452.04	0	0.26	0	2624385	0	88398054	0	7289171	0	476952	0	305204	0	0	0	5391703	0	11271	0	0	0	80347	0	12766166	0	38148	0	12895932	0	84.77	0	74935024	0	205679	13166006	64.012397959928	88398054.0	82224195.0	2624385.0	7289171.0	476952.0	305204.0	0.0	5391703.0	74935024.0	93.0	3.0	8.2	0.5	0.3	0.0	6.1	84.8	50	50	50.00	38	4419902700	24.9	25.0	25.0	25.0	0.0	38.5	27.0	bulk
658308	SRR2098170	SRP060340	SRS988674	SRX1093182	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		recurrent tissue of K817-R23		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K817-R23|dev_stage;;recurrent|phenotype;;HER2 recurrent|sex;;not applicable|tissue;;mammary gland		100	TW47_QW57_K817-R23	TW47_QW57_K817-R23-rec_03_11_2013	8251149900	82511499	2016-02-12 14:01:44	5112348450	8251149900	82511499	2	82511499	index:0,count:82511499,average:50,stdev:0|index:1,count:82511499,average:50,stdev:0	TW47_QW57_K817_R23				in_mesa	26977878	4.39	2.74	0.08	7029520851	7076056937	6146922402	6317384698	100.66	102.77	71233081	62323959	236.517	965.982	136	455869	75.72	86.55	86771491	53940216	86771491	53940216	77.93	78.71	86771491	55509041	86771491	49050713	704649365	10.02	4.80	0	10.80	0	0.32	0	0.13	0	0.00	0	13.21	0	71233081	0	100	0	98.77	0	3.08	0	0.02	0	1.54	0	0.02	0	192.51	0	0.40	0	3958939	0	82511499	0	8913360	0	265561	0	109899	0	0	0	10902958	0	6567	0	0	0	44793	0	7465859	0	26978	0	7544197	0	75.53	0	62319721	0	183536	7997471	43.574399572836	82511499.0	71233081.0	3958939.0	8913360.0	265561.0	109899.0	0.0	10902958.0	62319721.0	86.3	4.8	10.8	0.3	0.1	0.0	13.2	75.5	50	50	50.00	38	4125574950	24.6	25.3	25.3	24.8	0.0	37.9	24.9	bulk
673845	SRR2097906	SRP060340	SRS988458	SRX1092966	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of K917		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K917|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW30_QW26_K917	TW30_QW26_K917-pri_03_11_2013	8541721300	85417213	2016-02-12 13:59:33	5387090878	8541721300	85417213	2	85417213	index:0,count:85417213,average:50,stdev:0|index:1,count:85417213,average:50,stdev:0	TW30_QW26_K917				in_mesa	26977878	6.26	2.98	0.41	7354904798	7371186228	6445994434	6576762844	100.22	102.03	74532389	62318790	255.133	1276.588	134	388293	76.41	87.15	89735396	56946933	89735396	56946933	80.81	81.1	89735396	60226421	89735396	52995027	785021015	10.67	4.39	0	10.75	0	0.44	0	0.30	0	0.00	0	12.01	0	74532389	0	100	0	98.81	0	3.12	0	0.02	0	1.45	0	0.01	0	415.54	0	0.28	0	3750883	0	85417213	0	9185489	0	371865	0	253156	0	0	0	10259803	0	7397	0	0	0	58384	0	8992450	0	37303	0	9095534	0	76.50	0	65346900	0	190476	9364213	49.162167412167	85417213.0	74532389.0	3750883.0	9185489.0	371865.0	253156.0	0.0	10259803.0	65346900.0	87.3	4.4	10.8	0.4	0.3	0.0	12.0	76.5	50	50	50.00	38	4270860650	25.0	24.9	24.9	25.2	0.0	37.8	25.2	bulk
673854	SRR2097907	SRP060340	SRS988459	SRX1092967	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of K919		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;K919|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW31_QW27_K919	TW31_QW27_K919-pri_03_11_2013	6842459700	68424597	2016-02-12 13:59:45	4152589416	6842459700	68424597	2	68424597	index:0,count:68424597,average:50,stdev:0|index:1,count:68424597,average:50,stdev:0	TW31_QW27_K919				in_mesa	26977878	3.83	2.37	0.2	5668478273	5743390263	5140745951	5299834770	101.32	103.09	57524494	44879305	281.603	1728.139	170	261427	78.19	86.2	66405835	44978836	66405835	44978836	77.99	78.92	66405835	44864762	66405835	41178514	648937506	11.45	5.23	0	7.82	0	0.27	0	0.21	0	0.00	0	15.45	0	57524494	0	100	0	98.69	0	4.09	0	0.03	0	1.54	0	0.01	0	205.10	0	0.30	0	3580167	0	68424597	0	5347828	0	181758	0	145797	0	0	0	10572548	0	5843	0	0	0	43815	0	8060944	0	34825	0	8145427	0	76.25	0	52176666	0	186809	8455651	45.263616849295	68424597.0	57524494.0	3580167.0	5347828.0	181758.0	145797.0	0.0	10572548.0	52176666.0	84.1	5.2	7.8	0.3	0.2	0.0	15.5	76.3	50	50	50.00	38	3421229850	24.5	25.4	25.4	24.7	0.0	38.2	25.7	bulk
674087	SRR2097924	SRP060340	SRS988473	SRX1092982	SRA275699	Dana-Farber Cancer Institute		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors	Resistance to anti-HER2 therapy leads to relapse and progression of HER2-positive breast cancers. Here, we show that tumor cells that resist HER2 pathway blockade retain expression of cyclin D1, and in a new transgenic mouse model ultimately give rise to cyclin D1/CDK4-dependent recurrences. Furthermore, the cyclin D1/CDK4 axis functionally mediates de novo and acquired resistance to anti-HER2 therapies, and a CDK4/6 inhibitor overcomes this. When combined, HER2 and CDK4/6 inhibitors synergistically reduce tumor cell viability by enhancing cell cycle arrest at the G1/S checkpoint, in association with reduced phosphorylation of both RB and S6RP. In vivo, CDK4/6 inhibition improves the efficacy of HER2 targeted therapy in both sensitive and resistant xenografts, and importantly also delays spontaneous tumor recurrence.		Overcoming Therapeutic Resistance in  HER2-Positive Breast Cancers With CDK4/6 Inhibitors		primary tissue of B10-L23		RNA-Seq	TRANSCRIPTOMIC	PolyA	paired		0.0E0		Illumina HiSeq 3000	age;;not applicable|BioSampleModel;;Model organism or animal|breed;;B10-L23|dev_stage;;primary|phenotype;;HER2 primary|sex;;not applicable|tissue;;mammary gland		100	TW36_QW55_B10_L23	TW36_QW55_B10-L23-pri_03_11_2013	7265606800	72656068	2016-02-12 14:02:52	4421624236	7265606800	72656068	2	72656068	index:0,count:72656068,average:50,stdev:0|index:1,count:72656068,average:50,stdev:0	TW36_QW55_B10_L23				in_mesa	26977878	4.32	2.76	0.12	6261257251	6294934776	5675578083	5787303842	100.54	101.97	63585781	51800098	249.075	1308.699	142	357564	82.52	91.01	73493254	52471464	73493254	52471464	85.0	85.89	73493254	54050703	73493254	49522973	475922287	7.60	4.32	0	8.16	0	0.31	0	0.21	0	0.00	0	11.97	0	63585781	0	100	0	98.62	0	2.75	0	0.01	0	1.40	0	0.01	0	488.90	0	0.28	0	3136786	0	72656068	0	5929325	0	225805	0	150321	0	0	0	8694161	0	6635	0	0	0	48667	0	9628055	0	31964	0	9715321	0	79.36	0	57656456	0	181222	9993001	55.142317157961	72656068.0	63585781.0	3136786.0	5929325.0	225805.0	150321.0	0.0	8694161.0	57656456.0	87.5	4.3	8.2	0.3	0.2	0.0	12.0	79.4	50	50	50.00	38	3632803400	25.0	24.8	25.0	25.1	0.0	38.1	25.1	bulk
1648942	SRR2120292	SRP061355	SRS1007827	SRX1113437	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827980: RNA_SNL1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SNL|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827980		GSM1827980	RNA_SNL1	2155589052	21133226	2016-05-12 16:05:14	1259224359	2155589052	21133226	2	21133226	index:0,count:21133226,average:51,stdev:0|index:1,count:21133226,average:51,stdev:0	GSM1827980_r1				in_mesa	27184839	3.63	2.78	0.12	1901663143	1866635403	1781280828	1756346438	98.16	98.6	19469084	17108154	223.293	1210.631	173	145492	58.88	63.01	21721593	11462777	21721593	11462777	61.75	60.44	21721593	12023036	21721593	10995918	665610828	35.00	2.76	0	6.04	0	0.50	0	0.27	0	0.00	0	7.10	0	19469084	0	102	0	97.94	0	1.24	0	0.01	0	1.16	0	0.00	0	322.37	0	0.18	0	583137	0	21133226	0	1276624	0	105166	0	57810	0	0	0	1501166	0	862	0	0	0	9564	0	1793502	0	64991	0	1868919	0	86.08	0	18192460	0	112061	1922289	17.153951865502	21133226.0	19469084.0	583137.0	1276624.0	105166.0	57810.0	0.0	1501166.0	18192460.0	92.1	2.8	6.0	0.5	0.3	0.0	7.1	86.1	51	51	51.00	38	1077794526	26.5	23.7	23.4	26.4	0.0	38.5	32.0	bulk
1648956	SRR2120293	SRP061355	SRS1007827	SRX1113437	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827980: RNA_SNL1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SNL|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827980		GSM1827980	RNA_SNL1	2135146926	20932813	2016-05-12 16:05:14	1247081744	2135146926	20932813	2	20932813	index:0,count:20932813,average:51,stdev:0|index:1,count:20932813,average:51,stdev:0	GSM1827980_r2				in_mesa	27184839	3.62	2.79	0.12	1888522419	1853862226	1768992842	1744348917	98.16	98.61	19332955	16988884	223.223	1200.015	177	144718	58.89	63.02	21570293	11384934	21570293	11384934	61.76	60.44	21570293	11939678	21570293	10919636	660922270	35.00	2.75	0	6.05	0	0.50	0	0.27	0	0.00	0	6.87	0	19332955	0	102	0	97.94	0	1.24	0	0.01	0	1.15	0	0.00	0	378.68	0	0.20	0	576669	0	20932813	0	1267211	0	104631	0	56286	0	0	0	1438941	0	854	0	0	0	9606	0	1775859	0	64039	0	1850358	0	86.30	0	18065744	0	112147	1903893	16.976762641890	20932813.0	19332955.0	576669.0	1267211.0	104631.0	56286.0	0.0	1438941.0	18065744.0	92.4	2.8	6.1	0.5	0.3	0.0	6.9	86.3	51	51	51.00	38	1067573463	26.5	23.7	23.4	26.4	0.0	38.5	31.7	bulk
1648972	SRR2120294	SRP061355	SRS1007826	SRX1113438	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827981: RNA_SNL2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SNL|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827981		GSM1827981	RNA_SNL2	1491269886	14620293	2016-05-12 16:05:14	879539267	1491269886	14620293	2	14620293	index:0,count:14620293,average:51,stdev:0|index:1,count:14620293,average:51,stdev:0	GSM1827981_r1				in_mesa	27184839	5.11	2.74	0.11	1309852088	1296361740	1214076938	1207981853	98.97	99.5	13451315	11407833	235.568	1318.623	180	95637	69.04	74.66	15175005	9286305	15175005	9286305	72.49	71.58	15175005	9750404	15175005	8902799	312811493	23.88	2.69	0	6.93	0	0.52	0	0.20	0	0.00	0	7.28	0	13451315	0	102	0	97.62	0	1.25	0	0.01	0	1.15	0	0.00	0	250.63	0	0.19	0	392856	0	14620293	0	1013369	0	75347	0	29604	0	0	0	1064027	0	668	0	0	0	7568	0	1545173	0	53283	0	1606692	0	85.07	0	12437946	0	104607	1616131	15.449549265346	14620293.0	13451315.0	392856.0	1013369.0	75347.0	29604.0	0.0	1064027.0	12437946.0	92.0	2.7	6.9	0.5	0.2	0.0	7.3	85.1	51	51	51.00	38	745634943	26.1	24.1	23.9	26.0	0.0	38.5	31.9	bulk
1648989	SRR2120295	SRP061355	SRS1007826	SRX1113438	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827981: RNA_SNL2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SNL|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827981		GSM1827981	RNA_SNL2	1469263896	14404548	2016-05-12 16:05:14	866494713	1469263896	14404548	2	14404548	index:0,count:14404548,average:51,stdev:0|index:1,count:14404548,average:51,stdev:0	GSM1827981_r2				in_mesa	27184839	5.1	2.75	0.11	1293480089	1280265596	1199058105	1193159011	98.98	99.51	13283593	11268939	235.635	1309.486	180	93991	69.04	74.66	14982931	9171012	14982931	9171012	72.47	71.56	14982931	9625997	14982931	8790557	308996362	23.89	2.69	0	6.94	0	0.52	0	0.20	0	0.00	0	7.07	0	13283593	0	102	0	97.62	0	1.24	0	0.01	0	1.15	0	0.00	0	367.78	0	0.21	0	388012	0	14404548	0	999428	0	74194	0	28832	0	0	0	1017929	0	656	0	0	0	7467	0	1521410	0	52373	0	1581906	0	85.28	0	12284165	0	104177	1591969	15.281386486461	14404548.0	13283593.0	388012.0	999428.0	74194.0	28832.0	0.0	1017929.0	12284165.0	92.2	2.7	6.9	0.5	0.2	0.0	7.1	85.3	51	51	51.00	38	734631948	26.1	24.1	23.9	26.0	0.0	38.5	31.6	bulk
1649004	SRR2120296	SRP061355	SRS1007825	SRX1113439	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827982: RNA_SNL3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SNL|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827982		GSM1827982	RNA_SNL3	2308113936	22628568	2016-05-12 16:05:14	1355852333	2308113936	22628568	2	22628568	index:0,count:22628568,average:51,stdev:0|index:1,count:22628568,average:51,stdev:0	GSM1827982_r1				in_mesa	27184839	2.82	2.69	0.12	2018668022	2002653114	1893826363	1888178556	99.21	99.7	20665598	17249259	238.759	1375.960	178	139792	72.19	77.11	23067588	14918023	23067588	14918023	74.28	73.81	23067588	15349760	23067588	14279049	443303488	21.96	2.42	0	5.83	0	0.52	0	0.19	0	0.00	0	7.97	0	20665598	0	102	0	97.91	0	1.25	0	0.01	0	1.15	0	0.00	0	267.97	0	0.19	0	547220	0	22628568	0	1318873	0	117567	0	42088	0	0	0	1803315	0	1085	0	0	0	12171	0	2647503	0	79915	0	2740674	0	85.50	0	19346725	0	120017	2765080	23.039069465159	22628568.0	20665598.0	547220.0	1318873.0	117567.0	42088.0	0.0	1803315.0	19346725.0	91.3	2.4	5.8	0.5	0.2	0.0	8.0	85.5	51	51	51.00	38	1154056968	26.2	24.3	23.9	25.5	0.0	38.4	31.8	bulk
1649019	SRR2120297	SRP061355	SRS1007825	SRX1113439	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827982: RNA_SNL3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SNL|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827982		GSM1827982	RNA_SNL3	2288226282	22433591	2016-05-12 16:05:14	1343964797	2288226282	22433591	2	22433591	index:0,count:22433591,average:51,stdev:0|index:1,count:22433591,average:51,stdev:0	GSM1827982_r2				in_mesa	27184839	2.83	2.69	0.12	2006004383	1990019229	1881985098	1876339441	99.2	99.7	20534972	17143577	238.871	1362.817	178	139052	72.2	77.12	22919676	14826868	22919676	14826868	74.28	73.81	22919676	15254347	22919676	14190571	440086514	21.94	2.42	0	5.84	0	0.52	0	0.18	0	0.00	0	7.76	0	20534972	0	102	0	97.91	0	1.25	0	0.01	0	1.15	0	0.00	0	281.40	0	0.20	0	542845	0	22433591	0	1310259	0	116310	0	41373	0	0	0	1740936	0	1107	0	0	0	12088	0	2627172	0	79790	0	2720157	0	85.70	0	19224713	0	119369	2743868	22.986437014635	22433591.0	20534972.0	542845.0	1310259.0	116310.0	41373.0	0.0	1740936.0	19224713.0	91.5	2.4	5.8	0.5	0.2	0.0	7.8	85.7	51	51	51.00	38	1144113141	26.2	24.3	24.0	25.5	0.0	38.4	31.6	bulk
1649034	SRR2120298	SRP061355	SRS1007824	SRX1113440	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827983: RNA_SNL4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SNL|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827983		GSM1827983	RNA_SNL4	2254865346	22106523	2016-05-12 16:05:14	1337334877	2254865346	22106523	2	22106523	index:0,count:22106523,average:51,stdev:0|index:1,count:22106523,average:51,stdev:0	GSM1827983_r1				in_mesa	27184839	4.9	2.86	0.09	1991356247	1972875211	1840245804	1833261504	99.07	99.62	20470420	17078251	236.252	1380.124	179	139298	74.24	80.53	23149238	15197685	23149238	15197685	78.0	77.43	23149238	15967244	23149238	14613565	363164560	18.24	2.58	0	7.23	0	0.51	0	0.17	0	0.00	0	6.72	0	20470420	0	102	0	97.53	0	1.23	0	0.00	0	1.15	0	0.00	0	282.21	0	0.19	0	569457	0	22106523	0	1597786	0	113156	0	37314	0	0	0	1485633	0	1122	0	0	0	12497	0	2655415	0	74774	0	2743808	0	85.37	0	18872634	0	125199	2759910	22.044185656435	22106523.0	20470420.0	569457.0	1597786.0	113156.0	37314.0	0.0	1485633.0	18872634.0	92.6	2.6	7.2	0.5	0.2	0.0	6.7	85.4	51	51	51.00	38	1127432673	25.5	24.7	24.3	25.5	0.0	38.4	31.8	bulk
1649050	SRR2120299	SRP061355	SRS1007824	SRX1113440	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827983: RNA_SNL4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SNL|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827983		GSM1827983	RNA_SNL4	2237804622	21939261	2016-05-12 16:05:14	1326865136	2237804622	21939261	2	21939261	index:0,count:21939261,average:51,stdev:0|index:1,count:21939261,average:51,stdev:0	GSM1827983_r2				in_mesa	27184839	4.9	2.86	0.09	1980363679	1961949169	1830040486	1823080189	99.07	99.62	20355797	16982976	236.268	1373.527	179	138701	74.25	80.54	23024436	15114633	23024436	15114633	78.02	77.45	23024436	15881099	23024436	14534548	360898987	18.22	2.57	0	7.24	0	0.51	0	0.17	0	0.00	0	6.54	0	20355797	0	102	0	97.54	0	1.23	0	0.00	0	1.15	0	0.00	0	276.16	0	0.21	0	564890	0	21939261	0	1589089	0	112500	0	36442	0	0	0	1434522	0	1212	0	0	0	12374	0	2638197	0	73718	0	2725501	0	85.54	0	18766708	0	125008	2744336	21.953282989889	21939261.0	20355797.0	564890.0	1589089.0	112500.0	36442.0	0.0	1434522.0	18766708.0	92.8	2.6	7.2	0.5	0.2	0.0	6.5	85.5	51	51	51.00	38	1118902311	25.5	24.7	24.3	25.5	0.0	38.4	31.6	bulk
1650698	SRR2120300	SRP061355	SRS1007823	SRX1113441	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827984: RNA_SHAM1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SHAM|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827984		GSM1827984	RNA_SHAM1	1929470148	18916374	2016-05-12 16:05:14	1143133604	1929470148	18916374	2	18916374	index:0,count:18916374,average:51,stdev:0|index:1,count:18916374,average:51,stdev:0	GSM1827984_r1				in_mesa	27184839	5.52	2.85	0.12	1435183735	1416114417	1330643150	1320056197	98.67	99.2	14746970	12790250	220.350	1300.997	171	110613	66.41	71.8	16574855	9792952	16574855	9792952	70.05	69.01	16574855	10330570	16574855	9412926	379156239	26.42	2.34	0	5.86	0	0.42	0	0.19	0	0.00	0	21.43	0	14746970	0	102	0	97.59	0	1.24	0	0.01	0	1.15	0	0.00	0	205.74	0	0.19	0	441704	0	18916374	0	1107969	0	80069	0	35497	0	0	0	4053838	0	778	0	0	0	8071	0	1569350	0	54913	0	1633112	0	72.10	0	13639001	0	108659	1639825	15.091478846667	18916374.0	14746970.0	441704.0	1107969.0	80069.0	35497.0	0.0	4053838.0	13639001.0	78.0	2.3	5.9	0.4	0.2	0.0	21.4	72.1	51	51	51.00	38	964735074	25.8	24.4	23.3	26.5	0.0	38.4	31.5	bulk
1650715	SRR2120301	SRP061355	SRS1007823	SRX1113441	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827984: RNA_SHAM1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SHAM|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827984		GSM1827984	RNA_SHAM1	1905008712	18676556	2016-05-12 16:05:14	1129518015	1905008712	18676556	2	18676556	index:0,count:18676556,average:51,stdev:0|index:1,count:18676556,average:51,stdev:0	GSM1827984_r2				in_mesa	27184839	5.52	2.85	0.13	1420397958	1401628076	1317085800	1306698843	98.68	99.21	14594082	12662794	220.282	1286.708	169	109949	66.4	71.79	16398625	9690718	16398625	9690718	70.04	69.0	16398625	10221660	16398625	9315075	375474015	26.43	2.33	0	5.86	0	0.42	0	0.18	0	0.00	0	21.25	0	14594082	0	102	0	97.60	0	1.24	0	0.01	0	1.15	0	0.00	0	210.11	0	0.20	0	436069	0	18676556	0	1094709	0	78940	0	34455	0	0	0	3969079	0	735	0	0	0	7981	0	1549726	0	54410	0	1612852	0	72.28	0	13499373	0	108434	1619447	14.934863603667	18676556.0	14594082.0	436069.0	1094709.0	78940.0	34455.0	0.0	3969079.0	13499373.0	78.1	2.3	5.9	0.4	0.2	0.0	21.3	72.3	51	51	51.00	38	952504356	25.8	24.4	23.3	26.5	0.0	38.4	31.2	bulk
1650731	SRR2120302	SRP061355	SRS1007822	SRX1113442	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827985: RNA_SHAM2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SHAM|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827985		GSM1827985	RNA_SHAM2	1572025224	15412012	2016-05-12 16:05:14	929011336	1572025224	15412012	2	15412012	index:0,count:15412012,average:51,stdev:0|index:1,count:15412012,average:51,stdev:0	GSM1827985_r1				in_mesa	27184839	5.04	2.75	0.12	1361963161	1346788030	1266084297	1259056622	98.89	99.44	13976166	11919331	231.755	1346.488	179	99263	68.38	73.73	15674080	9557209	15674080	9557209	71.57	70.76	15674080	10003132	15674080	9172961	337461806	24.78	2.62	0	6.57	0	0.48	0	0.21	0	0.00	0	8.63	0	13976166	0	102	0	97.69	0	1.25	0	0.01	0	1.15	0	0.00	0	276.04	0	0.19	0	403625	0	15412012	0	1013072	0	73420	0	33029	0	0	0	1329397	0	760	0	0	0	7929	0	1591104	0	55862	0	1655655	0	84.11	0	12963094	0	108557	1658248	15.275366857964	15412012.0	13976166.0	403625.0	1013072.0	73420.0	33029.0	0.0	1329397.0	12963094.0	90.7	2.6	6.6	0.5	0.2	0.0	8.6	84.1	51	51	51.00	38	786012612	26.4	23.9	23.8	25.9	0.0	38.4	31.8	bulk
1650746	SRR2120303	SRP061355	SRS1007822	SRX1113442	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827985: RNA_SHAM2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SHAM|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827985		GSM1827985	RNA_SHAM2	1552827498	15223799	2016-05-12 16:05:14	917719620	1552827498	15223799	2	15223799	index:0,count:15223799,average:51,stdev:0|index:1,count:15223799,average:51,stdev:0	GSM1827985_r2				in_mesa	27184839	5.03	2.75	0.13	1348251641	1333182094	1253488055	1246513189	98.88	99.44	13833691	11797864	231.761	1339.303	177	98265	68.4	73.73	15511002	9461861	15511002	9461861	71.57	70.76	15511002	9900441	15511002	9080784	333814170	24.76	2.61	0	6.58	0	0.48	0	0.21	0	0.00	0	8.44	0	13833691	0	102	0	97.70	0	1.25	0	0.01	0	1.14	0	0.00	0	360.56	0	0.21	0	397199	0	15223799	0	1001105	0	72865	0	32271	0	0	0	1284972	0	721	0	0	0	7999	0	1573588	0	54969	0	1637277	0	84.29	0	12832586	0	108310	1639305	15.135306065922	15223799.0	13833691.0	397199.0	1001105.0	72865.0	32271.0	0.0	1284972.0	12832586.0	90.9	2.6	6.6	0.5	0.2	0.0	8.4	84.3	51	51	51.00	38	776413749	26.4	23.9	23.8	25.9	0.0	38.4	31.6	bulk
1650762	SRR2120304	SRP061355	SRS1007821	SRX1113443	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827986: RNA_SHAM3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SHAM|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827986		GSM1827986	RNA_SHAM3	2301351642	22562271	2016-05-12 16:05:14	1367243471	2301351642	22562271	2	22562271	index:0,count:22562271,average:51,stdev:0|index:1,count:22562271,average:51,stdev:0	GSM1827986_r1				in_mesa	27184839	5.15	2.74	0.14	1960429039	1942276259	1815014592	1809070983	99.07	99.67	20189964	17083334	237.265	1382.248	181	139431	70.15	75.96	22801235	14163197	22801235	14163197	73.51	72.75	22801235	14841704	22801235	13563731	440526642	22.47	2.78	0	6.85	0	0.47	0	0.20	0	0.00	0	9.85	0	20189964	0	102	0	97.36	0	1.26	0	0.01	0	1.15	0	0.00	0	319.78	0	0.20	0	626347	0	22562271	0	1545098	0	105236	0	44501	0	0	0	2222570	0	1143	0	0	0	11422	0	2332835	0	85294	0	2430694	0	82.64	0	18644866	0	115247	2457635	21.324936874713	22562271.0	20189964.0	626347.0	1545098.0	105236.0	44501.0	0.0	2222570.0	18644866.0	89.5	2.8	6.8	0.5	0.2	0.0	9.9	82.6	51	51	51.00	38	1150675821	26.8	23.8	23.4	25.9	0.0	38.4	31.7	bulk
1650778	SRR2120305	SRP061355	SRS1007821	SRX1113443	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827986: RNA_SHAM3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SHAM|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827986		GSM1827986	RNA_SHAM3	2278549950	22338725	2016-05-12 16:05:14	1353668142	2278549950	22338725	2	22338725	index:0,count:22338725,average:51,stdev:0|index:1,count:22338725,average:51,stdev:0	GSM1827986_r2				in_mesa	27184839	5.16	2.74	0.13	1946793185	1928822458	1802253216	1796435436	99.08	99.68	20048521	16965113	237.258	1369.978	179	139234	70.14	75.96	22637622	14061473	22637622	14061473	73.5	72.74	22637622	14736516	22637622	13466166	437734094	22.48	2.78	0	6.87	0	0.47	0	0.20	0	0.00	0	9.59	0	20048521	0	102	0	97.37	0	1.26	0	0.01	0	1.15	0	0.00	0	237.23	0	0.21	0	620971	0	22338725	0	1535716	0	104808	0	43582	0	0	0	2141814	0	1170	0	0	0	11011	0	2315503	0	84931	0	2412615	0	82.87	0	18512805	0	115168	2438627	21.174518963601	22338725.0	20048521.0	620971.0	1535716.0	104808.0	43582.0	0.0	2141814.0	18512805.0	89.7	2.8	6.9	0.5	0.2	0.0	9.6	82.9	51	51	51.00	38	1139274975	26.8	23.8	23.4	25.9	0.0	38.4	31.5	bulk
1650794	SRR2120306	SRP061355	SRS1007820	SRX1113444	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827987: RNA_SHAM4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SHAM|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827987		GSM1827987	RNA_SHAM4	2323769610	22782055	2016-05-12 16:05:14	1367902171	2323769610	22782055	2	22782055	index:0,count:22782055,average:51,stdev:0|index:1,count:22782055,average:51,stdev:0	GSM1827987_r1				in_mesa	27184839	3.77	2.74	0.12	2028871017	1993848784	1905385917	1881279504	98.27	98.73	20749601	17990274	229.871	1249.954	182	149220	62.99	67.21	23026729	13069444	23026729	13069444	65.49	64.51	23026729	13588712	23026729	12543815	629262135	31.02	2.56	0	5.73	0	0.47	0	0.24	0	0.00	0	8.21	0	20749601	0	102	0	98.01	0	1.24	0	0.01	0	1.15	0	0.00	0	344.60	0	0.18	0	583935	0	22782055	0	1305262	0	106518	0	55599	0	0	0	1870337	0	981	0	0	0	10586	0	2099352	0	70830	0	2181749	0	85.35	0	19444339	0	118248	2190054	18.520854475340	22782055.0	20749601.0	583935.0	1305262.0	106518.0	55599.0	0.0	1870337.0	19444339.0	91.1	2.6	5.7	0.5	0.2	0.0	8.2	85.3	51	51	51.00	38	1161884805	26.3	24.0	23.7	26.1	0.0	38.5	31.9	bulk
1650811	SRR2120307	SRP061355	SRS1007820	SRX1113444	SRA278928	GEO		Injury-induced enhancer remodelling in spinal microglia - a novel mechanism for pain chronification? [RNA-Seq]	Chronic pain is common and devastating. Yet, its precise molecular origins remain unclear. The condition induces well-characterised changes in neurons and microglia, but it is unknown why they persist long after the precipitating injury has healed. We posit a role for enhancers - regions of open chromatin that define a cell’s transcription factor binding profile. Enhancer profiles can alter upon environmental stimulation, functioning as a kind of molecular memory. Here, a mouse model of persistent neuropathic pain was used to examine microglial enhancers with flow cytometry and sequencing. We observed injury-specific alterations of enhancers in close proximity to transcriptionally regulated genes. Our data also shine light on details relating to the spinal cord immune response and provide the first genome-wide gene expression profile of isolated microglia in a pain state. We hypothesise that enhancer deposition may constitute a novel mechanism by which painful experiences are encoded on a molecular level. Overall design: ChIP-seq and RNA-seq of isolated spinal cord microglia after peripheral spinal nerve ligation or sham surgery in mice (day 7)		GSM1827987: RNA_SHAM4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Spinal cord microglia were isolated via a Percoll gradient Sequencing was performed by the High Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics (Oxford University). RNA libraries were prepared using a SMARTer Ultra Low Input HV kit (634820, Clontech). Custom adaptor and barcode tags were used (5'- P-GATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, 5’-ACACTCTTTCCCTACACGACGCTCTTCCGATCT). Samples were amplified (13 cycles for RNA) and multiplexed in replicate flow cells on an Illumina HiSeq2500 platform to yield 50bp paired-end reads at a depth of at least 20M. All libraries were prepared together to avoid batch effects.	Illumina HiSeq 2500	age;;6-8 weeks old|gender;;male|injury condition;;SHAM|source_name;;mouse spinal cord microglia|strain;;C57BL/6	GEO Accession;;GSM1827987		GSM1827987	RNA_SHAM4	2303273424	22581112	2016-05-12 16:05:14	1355989887	2303273424	22581112	2	22581112	index:0,count:22581112,average:51,stdev:0|index:1,count:22581112,average:51,stdev:0	GSM1827987_r2				in_mesa	27184839	3.77	2.74	0.12	2015414137	1980628469	1892566147	1868700060	98.27	98.74	20610323	17873671	229.894	1237.567	180	148691	62.99	67.22	22878320	12982286	22878320	12982286	65.5	64.53	22878320	13500115	22878320	12461334	625046696	31.01	2.56	0	5.75	0	0.47	0	0.24	0	0.00	0	8.01	0	20610323	0	102	0	98.02	0	1.24	0	0.01	0	1.15	0	0.00	0	361.30	0	0.20	0	578682	0	22581112	0	1298234	0	106306	0	54642	0	0	0	1809841	0	1006	0	0	0	10722	0	2084251	0	70196	0	2166175	0	85.52	0	19312089	0	117748	2175443	18.475413595135	22581112.0	20610323.0	578682.0	1298234.0	106306.0	54642.0	0.0	1809841.0	19312089.0	91.3	2.6	5.7	0.5	0.2	0.0	8.0	85.5	51	51	51.00	38	1151636712	26.3	24.0	23.7	26.1	0.0	38.5	31.6	bulk
1856794	SRR3710551	SRP061708	SRS1520871	SRX1870353	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211219: n7.1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211219		GSM2211219	n7.1	387626700	2584178	2016-08-26 15:44:09	166277111	387626700	2584178	2	2584178	index:0,count:2584178,average:75,stdev:0|index:1,count:2584178,average:75,stdev:0	GSM2211219_r1						1.92	1.64	0.01	344391355	435912167	322359763	414776865	126.57	128.67	2419854	2149149	295.458	1344.911	254	8150	83.22	89.12	2629576	2013722	2629576	2013722	57.19	57.73	2629576	1383825	2629576	1304460	23337158	6.78	3.18	0	6.21	0	0.16	0	0.08	0	0.00	0	6.12	0	2419854	0	150	0	147.23	0	4.56	0	0.08	0	1.15	0	0.03	0	258.42	0	0.68	0	82290	0	2584178	0	160399	0	4176	0	2075	0	0	0	158073	0	201	0	0	0	2207	0	318592	0	3552	0	324552	0	87.43	0	2259455	0	64214	320944	4.998037811069	2584178.0	2419854.0	82290.0	160399.0	4176.0	2075.0	0.0	158073.0	2259455.0	93.6	3.2	6.2	0.2	0.1	0.0	6.1	87.4	75	75	75.00	6	193813350	23.9	25.7	26.1	24.3	0.0	33.7	25.5	smartseq
1856811	SRR3710552	SRP061708	SRS1520872	SRX1870354	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211220: n7.2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211220		GSM2211220	n7.2	327922200	2186148	2016-08-26 15:44:09	138644856	327922200	2186148	2	2186148	index:0,count:2186148,average:75,stdev:0|index:1,count:2186148,average:75,stdev:0	GSM2211220_r1						1.72	1.74	0.01	280646174	344809173	262682159	327842418	122.86	124.81	2010744	1770295	281.600	1437.584	254	6085	82.41	88.37	2196080	1657069	2196080	1657069	59.65	60.43	2196080	1199457	2196080	1133193	21028380	7.49	3.16	0	6.20	0	0.14	0	0.08	0	0.00	0	7.80	0	2010744	0	150	0	146.94	0	4.49	0	0.06	0	1.18	0	0.02	0	171.09	0	0.63	0	69121	0	2186148	0	135511	0	3108	0	1796	0	0	0	170500	0	195	0	0	0	1938	0	294365	0	2860	0	299358	0	85.78	0	1875233	0	63519	293175	4.615548103717	2186148.0	2010744.0	69121.0	135511.0	3108.0	1796.0	0.0	170500.0	1875233.0	92.0	3.2	6.2	0.1	0.1	0.0	7.8	85.8	75	75	75.00	6	163961100	24.2	25.6	25.7	24.6	0.0	33.9	25.7	smartseq
1856826	SRR3710553	SRP061708	SRS1520873	SRX1870355	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211221: n7.3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211221		GSM2211221	n7.3	480073650	3200491	2016-08-26 15:44:09	198446498	480073650	3200491	2	3200491	index:0,count:3200491,average:75,stdev:0|index:1,count:3200491,average:75,stdev:0	GSM2211221_r1						2.28	1.73	0.01	405613674	508968583	379577818	484490883	125.48	127.64	2929822	2653439	260.981	1136.445	207	10634	81.55	87.46	3194851	2389194	3194851	2389194	55.38	56.03	3194851	1622431	3194851	1530607	32089297	7.91	3.44	0	6.19	0	0.14	0	0.09	0	0.00	0	8.23	0	2929822	0	150	0	146.82	0	4.28	0	0.06	0	1.22	0	0.02	0	303.20	0	0.57	0	109947	0	3200491	0	197976	0	4352	0	3001	0	0	0	263316	0	250	0	0	0	2820	0	374037	0	3693	0	380800	0	85.36	0	2731846	0	68718	371079	5.400026194010	3200491.0	2929822.0	109947.0	197976.0	4352.0	3001.0	0.0	263316.0	2731846.0	91.5	3.4	6.2	0.1	0.1	0.0	8.2	85.4	75	75	75.00	6	240036825	24.2	25.5	25.7	24.7	0.0	34.0	26.2	smartseq
1856841	SRR3710554	SRP061708	SRS1520874	SRX1870356	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211222: n7.4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211222		GSM2211222	n7.4	412106100	2747374	2016-08-26 15:44:09	170315343	412106100	2747374	2	2747374	index:0,count:2747374,average:75,stdev:0|index:1,count:2747374,average:75,stdev:0	GSM2211222_r1						1.94	1.9	0.01	348358121	424199358	323735619	401331331	121.77	123.97	2533135	2295871	231.211	1067.228	174	11252	81.89	88.45	2788537	2074269	2788537	2074269	59.21	60.21	2788537	1499770	2788537	1412106	25903476	7.44	2.78	0	6.84	0	0.14	0	0.08	0	0.00	0	7.57	0	2533135	0	150	0	147.13	0	4.20	0	0.05	0	1.19	0	0.02	0	235.49	0	0.55	0	76382	0	2747374	0	188021	0	3909	0	2260	0	0	0	208070	0	271	0	0	0	2625	0	390193	0	3116	0	396205	0	85.36	0	2345114	0	71107	385937	5.427552842899	2747374.0	2533135.0	76382.0	188021.0	3909.0	2260.0	0.0	208070.0	2345114.0	92.2	2.8	6.8	0.1	0.1	0.0	7.6	85.4	75	75	75.00	6	206053050	24.5	25.2	25.4	24.9	0.0	34.0	26.0	smartseq
1856857	SRR3710555	SRP061708	SRS1520875	SRX1870357	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211223: n7.5; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211223		GSM2211223	n7.5	424925550	2832837	2016-08-26 15:44:09	179556191	424925550	2832837	2	2832837	index:0,count:2832837,average:75,stdev:0|index:1,count:2832837,average:75,stdev:0	GSM2211223_r1						0.9	1.46	0.01	383326399	478341333	359194723	454821820	124.79	126.62	2666012	2320227	294.907	1556.020	254	11078	84.69	90.56	2892951	2257952	2892951	2257952	60.12	60.97	2892951	1602713	2892951	1520197	21348469	5.57	3.18	0	6.10	0	0.15	0	0.07	0	0.00	0	5.68	0	2666012	0	150	0	147.27	0	4.81	0	0.09	0	1.16	0	0.03	0	261.49	0	0.63	0	90073	0	2832837	0	172689	0	4117	0	1866	0	0	0	160842	0	283	0	0	0	2838	0	406052	0	4195	0	413368	0	88.02	0	2493323	0	71434	412144	5.769577512109	2832837.0	2666012.0	90073.0	172689.0	4117.0	1866.0	0.0	160842.0	2493323.0	94.1	3.2	6.1	0.1	0.1	0.0	5.7	88.0	75	75	75.00	6	212462775	23.4	26.2	26.6	23.8	0.0	33.9	25.9	smartseq
1856874	SRR3710556	SRP061708	SRS1520876	SRX1870358	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211224: n7.6; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211224		GSM2211224	n7.6	290435250	1936235	2016-08-26 15:44:09	124109317	290435250	1936235	2	1936235	index:0,count:1936235,average:75,stdev:0|index:1,count:1936235,average:75,stdev:0	GSM2211224_r1						2.04	1.96	0.01	235796122	286513783	219773833	271768865	121.51	123.66	1742535	1578340	232.009	1080.821	207	6451	81.73	88.08	1918512	1424205	1918512	1424205	59.49	60.45	1918512	1036721	1918512	977497	18561591	7.87	2.85	0	6.49	0	0.17	0	0.11	0	0.00	0	9.72	0	1742535	0	150	0	146.69	0	4.24	0	0.05	0	1.19	0	0.02	0	278.82	0	0.64	0	55092	0	1936235	0	125576	0	3315	0	2169	0	0	0	188216	0	154	0	0	0	1804	0	261561	0	2239	0	265758	0	83.51	0	1616959	0	61574	255323	4.146604086140	1936235.0	1742535.0	55092.0	125576.0	3315.0	2169.0	0.0	188216.0	1616959.0	90.0	2.8	6.5	0.2	0.1	0.0	9.7	83.5	75	75	75.00	6	145217625	24.5	25.3	25.2	25.0	0.0	33.7	25.3	smartseq
1856889	SRR3710557	SRP061708	SRS1520877	SRX1870359	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211225: n7.7; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211225		GSM2211225	n7.7	212906850	1419379	2016-08-26 15:44:09	91521088	212906850	1419379	2	1419379	index:0,count:1419379,average:75,stdev:0|index:1,count:1419379,average:75,stdev:0	GSM2211225_r1						0.98	1.8	0.01	197488307	240783691	185123140	228792429	121.92	123.59	1364630	1131320	331.957	1844.516	301	4280	86.74	92.72	1487776	1183743	1487776	1183743	67.27	67.88	1487776	917983	1487776	866633	9184589	4.65	2.64	0	6.20	0	0.17	0	0.06	0	0.00	0	3.62	0	1364630	0	150	0	147.65	0	4.74	0	0.08	0	1.03	0	0.02	0	189.25	0	0.62	0	37407	0	1419379	0	87936	0	2466	0	876	0	0	0	51407	0	136	0	0	0	1725	0	240827	0	2140	0	244828	0	89.95	0	1276694	0	57366	245607	4.281403618868	1419379.0	1364630.0	37407.0	87936.0	2466.0	876.0	0.0	51407.0	1276694.0	96.1	2.6	6.2	0.2	0.1	0.0	3.6	89.9	75	75	75.00	6	106453425	23.8	25.8	26.2	24.2	0.0	33.8	25.6	smartseq
1857080	SRR3710563	SRP061708	SRS1520883	SRX1870365	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211231: n7.13; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211231		GSM2211231	n7.13	345958050	2306387	2016-08-26 15:44:09	150529611	345958050	2306387	2	2306387	index:0,count:2306387,average:75,stdev:0|index:1,count:2306387,average:75,stdev:0	GSM2211231_r1						1.35	1.29	0.01	298214679	400442648	282963880	385088107	134.28	136.09	2102273	1951453	294.055	974.952	308	8884	79.79	84.24	2250574	1677383	2250574	1677383	43.88	43.99	2250574	922581	2250574	875945	31858412	10.68	5.39	0	4.82	0	0.18	0	0.11	0	0.00	0	8.56	0	2102273	0	150	0	145.96	0	4.00	0	0.05	0	1.18	0	0.02	0	197.69	0	0.79	0	124265	0	2306387	0	111067	0	4104	0	2581	0	0	0	197429	0	90	0	0	0	1148	0	163750	0	2354	0	167342	0	86.33	0	1991206	0	45587	164984	3.619101936956	2306387.0	2102273.0	124265.0	111067.0	4104.0	2581.0	0.0	197429.0	1991206.0	91.2	5.4	4.8	0.2	0.1	0.0	8.6	86.3	75	75	75.00	6	172979025	23.9	25.6	26.5	24.0	0.0	33.6	25.3	smartseq
1857096	SRR3710564	SRP061708	SRS1520884	SRX1870366	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211232: n7.14; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211232		GSM2211232	n7.14	333584550	2223897	2016-08-26 15:44:09	144120717	333584550	2223897	2	2223897	index:0,count:2223897,average:75,stdev:0|index:1,count:2223897,average:75,stdev:0	GSM2211232_r1						0.71	1.54	0.01	305721404	381091011	285641810	361289754	124.65	126.48	2121885	1846793	306.257	1526.113	301	8222	85.07	91.26	2310903	1805072	2310903	1805072	61.71	62.56	2310903	1309350	2310903	1237425	15587512	5.10	2.99	0	6.47	0	0.14	0	0.08	0	0.00	0	4.38	0	2121885	0	150	0	147.47	0	4.93	0	0.10	0	1.04	0	0.03	0	177.91	0	0.67	0	66511	0	2223897	0	143894	0	3018	0	1683	0	0	0	97311	0	232	0	0	0	2120	0	307474	0	3220	0	313046	0	88.94	0	1977991	0	61399	312661	5.092281633251	2223897.0	2121885.0	66511.0	143894.0	3018.0	1683.0	0.0	97311.0	1977991.0	95.4	3.0	6.5	0.1	0.1	0.0	4.4	88.9	75	75	75.00	6	166792275	23.5	26.1	26.4	24.0	0.0	33.7	25.5	smartseq
1857112	SRR3710565	SRP061708	SRS1520885	SRX1870367	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211233: s7.1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211233		GSM2211233	s7.1	280682400	1871216	2016-08-26 15:44:09	125617213	280682400	1871216	2	1871216	index:0,count:1871216,average:75,stdev:0|index:1,count:1871216,average:75,stdev:0	GSM2211233_r1						1.48	1.7	0.02	241262332	294205144	224655565	278641766	121.94	124.03	1733779	1560232	253.466	1212.221	207	6660	82.5	88.91	1899909	1430452	1899909	1430452	60.16	61.34	1899909	1043039	1899909	986796	16766590	6.95	2.82	0	6.68	0	0.14	0	0.07	0	0.00	0	7.14	0	1733779	0	150	0	147.07	0	4.27	0	0.06	0	1.15	0	0.02	0	259.09	0	0.66	0	52721	0	1871216	0	124962	0	2607	0	1296	0	0	0	133534	0	197	0	0	0	1616	0	253796	0	2424	0	258033	0	85.98	0	1608817	0	60448	252084	4.170262043409	1871216.0	1733779.0	52721.0	124962.0	2607.0	1296.0	0.0	133534.0	1608817.0	92.7	2.8	6.7	0.1	0.1	0.0	7.1	86.0	75	75	75.00	6	140341200	24.5	25.3	25.5	24.8	0.0	33.2	24.5	smartseq
1857130	SRR3710566	SRP061708	SRS1520886	SRX1870368	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211234: s7.2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211234		GSM2211234	s7.2	131103000	874020	2016-08-26 15:44:09	56622676	131103000	874020	2	874020	index:0,count:874020,average:75,stdev:0|index:1,count:874020,average:75,stdev:0	GSM2211234_r1						5.27	2.26	0.01	113719607	134254493	106510009	127623500	118.06	119.82	810232	722794	288.330	1310.135	254	2338	79.37	84.97	881466	643116	881466	643116	61.2	61.6	881466	495873	881466	466225	12451944	10.95	3.18	0	6.11	0	0.16	0	0.11	0	0.00	0	7.03	0	810232	0	150	0	147.00	0	3.73	0	0.04	0	1.17	0	0.02	0	174.80	0	0.65	0	27819	0	874020	0	53391	0	1370	0	1005	0	0	0	61413	0	63	0	0	0	795	0	103021	0	917	0	104796	0	86.59	0	756841	0	36177	102679	2.838239765597	874020.0	810232.0	27819.0	53391.0	1370.0	1005.0	0.0	61413.0	756841.0	92.7	3.2	6.1	0.2	0.1	0.0	7.0	86.6	75	75	75.00	6	65551500	25.5	24.2	24.5	25.8	0.0	33.5	25.0	smartseq
1857146	SRR3710567	SRP061708	SRS1520887	SRX1870369	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211235: s7.3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211235		GSM2211235	s7.3	389834550	2598897	2016-08-26 15:44:09	163971294	389834550	2598897	2	2598897	index:0,count:2598897,average:75,stdev:0|index:1,count:2598897,average:75,stdev:0	GSM2211235_r1						3.25	1.7	0.01	306416795	385527471	286518971	367092329	125.82	128.12	2292139	2146983	232.435	848.892	105	9567	77.67	83.43	2505843	1780412	2505843	1780412	49.87	50.5	2505843	1143027	2505843	1077680	33730352	11.01	4.01	0	6.09	0	0.14	0	0.11	0	0.00	0	11.56	0	2292139	0	150	0	145.92	0	3.69	0	0.04	0	1.29	0	0.02	0	252.87	0	0.64	0	104299	0	2598897	0	158206	0	3619	0	2770	0	0	0	300369	0	165	0	0	0	1526	0	220843	0	2421	0	224955	0	82.11	0	2133933	0	53749	214131	3.983906677334	2598897.0	2292139.0	104299.0	158206.0	3619.0	2770.0	0.0	300369.0	2133933.0	88.2	4.0	6.1	0.1	0.1	0.0	11.6	82.1	75	75	75.00	6	194917275	24.7	25.1	25.1	25.1	0.0	33.7	25.4	smartseq
1857161	SRR3710568	SRP061708	SRS1520889	SRX1870370	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211236: s7.4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211236		GSM2211236	s7.4	525514950	3503433	2016-08-26 15:44:09	252698082	525514950	3503433	2	3503433	index:0,count:3503433,average:75,stdev:0|index:1,count:3503433,average:75,stdev:0	GSM2211236_r1						3.5	1.54	0.01	425483989	543273580	391894905	511613841	127.68	130.55	3160186	2991756	213.997	713.220	157	15978	81.27	88.57	3516586	2568173	3516586	2568173	51.03	51.83	3516586	1612530	3516586	1503033	22657078	5.33	4.27	0	7.44	0	0.17	0	0.07	0	0.00	0	9.56	0	3160186	0	150	0	145.91	0	3.92	0	0.04	0	1.32	0	0.02	0	221.27	0	0.76	0	149682	0	3503433	0	260531	0	5979	0	2283	0	0	0	334985	0	158	0	0	0	1986	0	288039	0	3351	0	293534	0	82.77	0	2899655	0	57127	284329	4.977138655977	3503433.0	3160186.0	149682.0	260531.0	5979.0	2283.0	0.0	334985.0	2899655.0	90.2	4.3	7.4	0.2	0.1	0.0	9.6	82.8	75	75	75.00	6	262757475	24.3	25.6	25.8	24.3	0.0	32.8	23.8	smartseq
1857176	SRR3710569	SRP061708	SRS1520888	SRX1870371	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211237: s7.5; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211237		GSM2211237	s7.5	311526450	2076843	2016-08-26 15:44:09	131036732	311526450	2076843	2	2076843	index:0,count:2076843,average:75,stdev:0|index:1,count:2076843,average:75,stdev:0	GSM2211237_r1						2.85	2.14	0.01	260979720	303902126	241699239	286743647	116.45	118.64	1925843	1763443	221.252	976.576	146	8900	78.32	84.94	2138722	1508269	2138722	1508269	60.68	61.64	2138722	1168566	2138722	1094516	28974169	11.10	2.67	0	7.23	0	0.18	0	0.14	0	0.00	0	6.95	0	1925843	0	150	0	147.19	0	3.72	0	0.04	0	1.18	0	0.02	0	202.07	0	0.48	0	55382	0	2076843	0	150210	0	3742	0	2898	0	0	0	144360	0	170	0	0	0	1928	0	282541	0	1963	0	286602	0	85.50	0	1775633	0	59151	277597	4.693022941286	2076843.0	1925843.0	55382.0	150210.0	3742.0	2898.0	0.0	144360.0	1775633.0	92.7	2.7	7.2	0.2	0.1	0.0	7.0	85.5	75	75	75.00	6	155763225	25.6	24.2	24.3	25.9	0.0	33.8	25.7	smartseq
1857289	SRR3710570	SRP061708	SRS1520890	SRX1870372	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211238: s7.6; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211238		GSM2211238	s7.6	335224800	2234832	2016-08-26 15:44:09	145418708	335224800	2234832	2	2234832	index:0,count:2234832,average:75,stdev:0|index:1,count:2234832,average:75,stdev:0	GSM2211238_r1						2.93	1.84	0.02	273964285	338570602	254641967	320380712	123.58	125.82	2019928	1902185	219.517	742.148	207	9840	75.98	82.02	2215645	1534661	2215645	1534661	50.13	50.81	2215645	1012495	2215645	950741	33829848	12.35	3.61	0	6.66	0	0.12	0	0.10	0	0.00	0	9.39	0	2019928	0	150	0	146.47	0	3.68	0	0.04	0	1.20	0	0.02	0	287.34	0	0.60	0	80750	0	2234832	0	148942	0	2762	0	2343	0	0	0	209799	0	178	0	0	0	1434	0	204335	0	1865	0	207812	0	83.72	0	1870986	0	51935	200565	3.861846538943	2234832.0	2019928.0	80750.0	148942.0	2762.0	2343.0	0.0	209799.0	1870986.0	90.4	3.6	6.7	0.1	0.1	0.0	9.4	83.7	75	75	75.00	6	167612400	24.9	24.8	25.1	25.2	0.0	33.5	25.1	smartseq
1857592	SRR3710583	SRP061708	SRS1520903	SRX1870385	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211251: s7.19; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211251		GSM2211251	s7.19	246624900	1644166	2016-08-26 15:44:09	105231298	246624900	1644166	2	1644166	index:0,count:1644166,average:75,stdev:0|index:1,count:1644166,average:75,stdev:0	GSM2211251_r1						2.01	1.58	0.01	203157130	256588353	189858210	244067086	126.3	128.55	1492446	1411406	231.420	713.455	207	6679	77.62	83.36	1625951	1158409	1625951	1158409	49.81	50.48	1625951	743372	1625951	701539	23668104	11.65	3.61	0	6.25	0	0.14	0	0.11	0	0.00	0	8.98	0	1492446	0	150	0	146.55	0	4.01	0	0.05	0	1.09	0	0.02	0	219.22	0	0.63	0	59353	0	1644166	0	102763	0	2253	0	1865	0	0	0	147602	0	87	0	0	0	871	0	130806	0	1686	0	133450	0	84.52	0	1389683	0	40496	127966	3.159966416436	1644166.0	1492446.0	59353.0	102763.0	2253.0	1865.0	0.0	147602.0	1389683.0	90.8	3.6	6.3	0.1	0.1	0.0	9.0	84.5	75	75	75.00	6	123312450	24.7	24.9	25.1	25.2	0.0	33.7	25.4	smartseq
1857640	SRR3710586	SRP061708	SRS1520906	SRX1870388	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211254: s7.22; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211254		GSM2211254	s7.22	308063250	2053755	2016-08-26 15:44:09	132078019	308063250	2053755	2	2053755	index:0,count:2053755,average:75,stdev:0|index:1,count:2053755,average:75,stdev:0	GSM2211254_r1						1.79	1.35	0.02	269656634	348638940	252732352	331741034	129.29	131.26	1907172	1792236	251.047	792.168	207	10797	78.79	84.22	2065023	1502664	2065023	1502664	47.38	47.9	2065023	903574	2065023	854729	27702353	10.27	4.77	0	5.98	0	0.14	0	0.12	0	0.00	0	6.88	0	1907172	0	150	0	146.38	0	4.35	0	0.07	0	1.16	0	0.02	0	284.37	0	0.69	0	98000	0	2053755	0	122892	0	2862	0	2400	0	0	0	141321	0	114	0	0	0	1234	0	161095	0	2154	0	164597	0	86.88	0	1784280	0	45839	162080	3.535853748991	2053755.0	1907172.0	98000.0	122892.0	2862.0	2400.0	0.0	141321.0	1784280.0	92.9	4.8	6.0	0.1	0.1	0.0	6.9	86.9	75	75	75.00	6	154031625	23.8	25.8	26.4	24.0	0.0	33.7	25.4	smartseq
1857657	SRR3710587	SRP061708	SRS1520907	SRX1870389	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211255: s7.23; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211255		GSM2211255	s7.23	393140550	2620937	2016-08-26 15:44:09	168324957	393140550	2620937	2	2620937	index:0,count:2620937,average:75,stdev:0|index:1,count:2620937,average:75,stdev:0	GSM2211255_r1						1.99	1.62	0.02	354925611	454941090	334380496	434612302	128.18	129.98	2470496	2225545	302.101	1186.774	254	10128	82.09	87.27	2662778	2028034	2662778	2028034	53.94	54.26	2662778	1332569	2662778	1260968	30966641	8.72	4.17	0	5.60	0	0.15	0	0.10	0	0.00	0	5.49	0	2470496	0	150	0	146.81	0	4.32	0	0.07	0	1.10	0	0.02	0	262.09	0	0.68	0	109236	0	2620937	0	146649	0	3911	0	2643	0	0	0	143887	0	157	0	0	0	2070	0	267226	0	3134	0	272587	0	88.66	0	2323847	0	61133	271407	4.439615265078	2620937.0	2470496.0	109236.0	146649.0	3911.0	2643.0	0.0	143887.0	2323847.0	94.3	4.2	5.6	0.1	0.1	0.0	5.5	88.7	75	75	75.00	6	196570275	24.1	25.4	26.1	24.3	0.0	33.8	25.6	smartseq
1857672	SRR3710588	SRP061708	SRS1520908	SRX1870390	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211256: s7.24; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211256		GSM2211256	s7.24	303162750	2021085	2016-08-26 15:44:09	131976234	303162750	2021085	2	2021085	index:0,count:2021085,average:75,stdev:0|index:1,count:2021085,average:75,stdev:0	GSM2211256_r1						3.5	1.39	0.02	267113302	355478421	251921277	340295558	133.08	135.08	1866742	1754787	303.424	850.114	308	8190	78.83	83.71	2001858	1471508	2001858	1471508	45.3	45.27	2001858	845541	2001858	795844	30283902	11.34	4.90	0	5.38	0	0.12	0	0.12	0	0.00	0	7.40	0	1866742	0	150	0	146.34	0	4.21	0	0.07	0	1.12	0	0.02	0	259.85	0	0.78	0	98969	0	2021085	0	108827	0	2502	0	2354	0	0	0	149487	0	74	0	0	0	943	0	118428	0	2096	0	121541	0	86.98	0	1757915	0	35737	119811	3.352575761815	2021085.0	1866742.0	98969.0	108827.0	2502.0	2354.0	0.0	149487.0	1757915.0	92.4	4.9	5.4	0.1	0.1	0.0	7.4	87.0	75	75	75.00	6	151581375	24.2	25.3	26.1	24.4	0.0	33.6	25.2	smartseq
1857690	SRR3710589	SRP061708	SRS1520909	SRX1870391	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211257: s7.25; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211257		GSM2211257	s7.25	294015900	1960106	2016-08-26 15:44:09	127385712	294015900	1960106	2	1960106	index:0,count:1960106,average:75,stdev:0|index:1,count:1960106,average:75,stdev:0	GSM2211257_r1						2.25	1.66	0.02	260731242	335280021	246418482	321115774	128.59	130.31	1826306	1680060	287.825	1011.462	254	7759	78.69	83.39	1960908	1437102	1960908	1437102	49.01	49.19	1960908	895044	1960908	847720	31081780	11.92	4.44	0	5.25	0	0.14	0	0.13	0	0.00	0	6.56	0	1826306	0	150	0	146.59	0	4.11	0	0.06	0	1.14	0	0.02	0	220.51	0	0.72	0	87077	0	1960106	0	102971	0	2732	0	2534	0	0	0	128534	0	110	0	0	0	1267	0	165958	0	2146	0	169481	0	87.92	0	1723335	0	48260	167499	3.470762536262	1960106.0	1826306.0	87077.0	102971.0	2732.0	2534.0	0.0	128534.0	1723335.0	93.2	4.4	5.3	0.1	0.1	0.0	6.6	87.9	75	75	75.00	6	147007950	24.3	25.3	26.0	24.4	0.0	33.6	25.3	smartseq
1857802	SRR3710590	SRP061708	SRS1520910	SRX1870392	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211258: s7.26; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211258		GSM2211258	s7.26	348716400	2324776	2016-08-26 15:44:09	147409657	348716400	2324776	2	2324776	index:0,count:2324776,average:75,stdev:0|index:1,count:2324776,average:75,stdev:0	GSM2211258_r1						1.67	1.35	0.03	300321468	403524266	285928575	388991237	134.36	136.04	2130418	2025049	274.168	740.359	271	10227	75.51	79.46	2273008	1608702	2273008	1608702	38.61	38.58	2273008	822638	2273008	781037	46053248	15.33	5.77	0	4.55	0	0.15	0	0.16	0	0.00	0	8.06	0	2130418	0	150	0	145.67	0	3.45	0	0.04	0	1.30	0	0.02	0	363.88	0	0.68	0	134109	0	2324776	0	105872	0	3384	0	3669	0	0	0	187305	0	78	0	0	0	874	0	125428	0	1961	0	128341	0	87.09	0	2024546	0	38982	125726	3.225232158432	2324776.0	2130418.0	134109.0	105872.0	3384.0	3669.0	0.0	187305.0	2024546.0	91.6	5.8	4.6	0.1	0.2	0.0	8.1	87.1	75	75	75.00	6	174358200	24.3	25.1	26.2	24.4	0.0	33.9	25.8	smartseq
1857817	SRR3710591	SRP061708	SRS1520911	SRX1870393	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211259: s7.27; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211259		GSM2211259	s7.27	339280950	2261873	2016-08-26 15:44:09	144728278	339280950	2261873	2	2261873	index:0,count:2261873,average:75,stdev:0|index:1,count:2261873,average:75,stdev:0	GSM2211259_r1						1.27	1.47	0.02	289395975	383591857	275876109	369995603	132.55	134.12	2059187	1961115	266.006	728.810	271	10394	74.17	77.94	2195466	1527242	2195466	1527242	38.84	38.89	2195466	799698	2195466	761983	49499144	17.10	5.98	0	4.41	0	0.15	0	0.15	0	0.00	0	8.66	0	2059187	0	150	0	145.38	0	3.36	0	0.04	0	1.38	0	0.02	0	226.19	0	0.72	0	135259	0	2261873	0	99702	0	3461	0	3381	0	0	0	195844	0	81	0	0	0	830	0	121717	0	1789	0	124417	0	86.63	0	1959485	0	37424	121990	3.259672937153	2261873.0	2059187.0	135259.0	99702.0	3461.0	3381.0	0.0	195844.0	1959485.0	91.0	6.0	4.4	0.2	0.1	0.0	8.7	86.6	75	75	75.00	6	169640475	24.4	25.0	26.0	24.6	0.0	33.8	25.5	smartseq
1857834	SRR3710592	SRP061708	SRS1520912	SRX1870394	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211260: s7.28; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211260		GSM2211260	s7.28	320302200	2135348	2016-08-26 15:44:09	136029931	320302200	2135348	2	2135348	index:0,count:2135348,average:75,stdev:0|index:1,count:2135348,average:75,stdev:0	GSM2211260_r1						1.49	1.63	0.02	292783380	364858330	272735391	345318832	124.62	126.61	2037234	1804159	290.611	1200.594	254	8400	83.18	89.48	2233518	1694532	2233518	1694532	59.35	59.88	2233518	1209023	2233518	1134049	19748996	6.75	3.08	0	6.72	0	0.22	0	0.11	0	0.00	0	4.26	0	2037234	0	150	0	147.44	0	4.61	0	0.08	0	1.05	0	0.02	0	274.54	0	0.61	0	65692	0	2135348	0	143391	0	4737	0	2331	0	0	0	91046	0	162	0	0	0	1983	0	279192	0	2713	0	284050	0	88.69	0	1893843	0	62170	284401	4.574569728165	2135348.0	2037234.0	65692.0	143391.0	4737.0	2331.0	0.0	91046.0	1893843.0	95.4	3.1	6.7	0.2	0.1	0.0	4.3	88.7	75	75	75.00	6	160151100	23.7	25.9	26.3	24.1	0.0	33.9	25.8	smartseq
1857849	SRR3710593	SRP061708	SRS1520913	SRX1870395	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211261: s7.29; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211261		GSM2211261	s7.29	373706100	2491374	2016-08-26 15:44:09	160039532	373706100	2491374	2	2491374	index:0,count:2491374,average:75,stdev:0|index:1,count:2491374,average:75,stdev:0	GSM2211261_r1						1.33	1.31	0.02	320687253	425637388	302931992	408150402	132.73	134.73	2265107	2115967	288.370	878.923	308	9803	77.16	81.84	2445666	1747730	2445666	1747730	42.93	42.79	2445666	972440	2445666	913846	42042948	13.11	5.36	0	5.20	0	0.17	0	0.13	0	0.00	0	8.78	0	2265107	0	150	0	145.94	0	3.83	0	0.05	0	1.21	0	0.02	0	271.79	0	0.74	0	133447	0	2491374	0	129624	0	4201	0	3327	0	0	0	218739	0	98	0	0	0	1156	0	168052	0	2266	0	171572	0	85.72	0	2135483	0	41480	172833	4.166658630665	2491374.0	2265107.0	133447.0	129624.0	4201.0	3327.0	0.0	218739.0	2135483.0	90.9	5.4	5.2	0.2	0.1	0.0	8.8	85.7	75	75	75.00	6	186853050	24.1	25.4	26.3	24.2	0.0	33.8	25.6	smartseq
1857865	SRR3710594	SRP061708	SRS1520914	SRX1870396	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211262: s7.30; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211262		GSM2211262	s7.30	272591400	1817276	2016-08-26 15:44:09	117957377	272591400	1817276	2	1817276	index:0,count:1817276,average:75,stdev:0|index:1,count:1817276,average:75,stdev:0	GSM2211262_r1						1.96	1.52	0.04	229236594	307510893	218957036	297435028	134.15	135.84	1631629	1549047	300.714	820.535	308	6612	73.26	76.89	1741048	1195338	1741048	1195338	36.92	36.68	1741048	602447	1741048	570233	41705054	18.19	5.72	0	4.23	0	0.20	0	0.19	0	0.00	0	9.83	0	1631629	0	150	0	145.53	0	3.42	0	0.04	0	1.25	0	0.01	0	130.84	0	0.80	0	103928	0	1817276	0	76946	0	3567	0	3393	0	0	0	178687	0	47	0	0	0	608	0	84309	0	1474	0	86438	0	85.55	0	1554683	0	31292	84555	2.702128339512	1817276.0	1631629.0	103928.0	76946.0	3567.0	3393.0	0.0	178687.0	1554683.0	89.8	5.7	4.2	0.2	0.2	0.0	9.8	85.6	75	75	75.00	6	136295700	24.6	24.8	25.9	24.7	0.0	33.6	25.2	smartseq
1857882	SRR3710595	SRP061708	SRS1520915	SRX1870397	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211263: s7.31; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211263		GSM2211263	s7.31	242023200	1613488	2016-08-26 15:44:09	104911656	242023200	1613488	2	1613488	index:0,count:1613488,average:75,stdev:0|index:1,count:1613488,average:75,stdev:0	GSM2211263_r1						1.23	1.78	0.01	220447583	271792086	207766207	259416197	123.29	124.86	1525716	1300750	332.263	1677.443	301	5048	83.65	88.9	1650975	1276296	1650975	1276296	61.39	61.79	1650975	936679	1650975	887056	16523520	7.50	3.39	0	5.58	0	0.15	0	0.08	0	0.00	0	5.21	0	1525716	0	150	0	147.21	0	4.52	0	0.07	0	1.10	0	0.02	0	232.34	0	0.70	0	54710	0	1613488	0	90080	0	2369	0	1333	0	0	0	84070	0	165	0	0	0	1498	0	223856	0	2239	0	227758	0	88.98	0	1435636	0	58030	227854	3.926486300190	1613488.0	1525716.0	54710.0	90080.0	2369.0	1333.0	0.0	84070.0	1435636.0	94.6	3.4	5.6	0.1	0.1	0.0	5.2	89.0	75	75	75.00	6	121011600	24.1	25.5	26.1	24.3	0.0	33.7	25.4	smartseq
1872792	SRR2131939	SRP061708	SRS1015152	SRX1122442	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834927: DRG_bulk_Nor_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact bulk cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834927		GSM1834927	DRG_bulk_Nor_1	194687400	3817400	2016-08-26 15:44:09	145422413	194687400	3817400	1	3817400	index:0,count:3817400,average:51,stdev:0	GSM1834927_r1						0.85	1.81	0.04	189068317	206093478	139704277	163510644	109.0	117.04	0	0	0	0	0	0	65.65	88.88	5101924	2458034	5101924	2458034	55.93	65.37	5101924	2094192	5101924	1807960	13907398	7.36	0.61	0	25.63	0	0.38	0	0.25	0	0.00	0	1.29	0	3744120	0	51	0	50.51	0	3.23	0	0.03	0	1.06	0	0.03	0	473.88	0	0.40	0	23262	0	3817400	0	978504	0	14493	0	9542	0	0	0	49245	0	98	0	0	0	1124	0	154944	0	2331	0	158497	0	72.45	0	2765616	0	47518	166204	3.497706132413	3817400.0	3744120.0	23262.0	978504.0	14493.0	9542.0	0.0	49245.0	2765616.0	98.1	0.6	25.6	0.4	0.2	0.0	1.3	72.4	51	51	51.00	38	194687400	24.2	25.6	25.9	24.3	0.0	36.1	25.2	smartseq
1872904	SRR2131940	SRP061708	SRS1015151	SRX1122443	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834928: DRG_bulk_Nor_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact bulk cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834928		GSM1834928	DRG_bulk_Nor_2	136094469	2668519	2016-08-26 15:44:09	106063500	136094469	2668519	1	2668519	index:0,count:2668519,average:51,stdev:0	GSM1834928_r1						0.81	1.75	0.04	131986035	147533924	98311648	116956874	111.78	118.97	0	0	0	0	0	0	66.24	88.95	3542849	1731915	3542849	1731915	55.09	63.47	3542849	1440372	3542849	1235836	9174298	6.95	0.61	0	25.02	0	0.37	0	0.24	0	0.00	0	1.40	0	2614713	0	51	0	50.49	0	3.29	0	0.03	0	1.06	0	0.03	0	457.46	0	0.47	0	16211	0	2668519	0	667700	0	9925	0	6389	0	0	0	37492	0	56	0	0	0	829	0	108997	0	1373	0	111255	0	72.96	0	1947013	0	38997	116885	2.997281842193	2668519.0	2614713.0	16211.0	667700.0	9925.0	6389.0	0.0	37492.0	1947013.0	98.0	0.6	25.0	0.4	0.2	0.0	1.4	73.0	51	51	51.00	38	136094469	24.3	25.3	26.6	23.8	0.0	35.4	24.0	smartseq
1872922	SRR2131941	SRP061708	SRS1015149	SRX1122444	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834929: DRG_bulk_Nor_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact bulk cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834929		GSM1834929	DRG_bulk_Nor_3	227715510	4465010	2016-08-26 15:44:09	176113333	227715510	4465010	1	4465010	index:0,count:4465010,average:51,stdev:0	GSM1834929_r1						0.88	1.77	0.03	220804088	245913777	166120326	197199370	111.37	118.71	0	0	0	0	0	0	67.17	89.3	5912707	2937717	5912707	2937717	55.95	64.08	5912707	2446784	5912707	2107991	14577186	6.60	0.59	0	24.27	0	0.38	0	0.26	0	0.00	0	1.41	0	4373446	0	51	0	50.49	0	3.35	0	0.03	0	1.05	0	0.03	0	535.80	0	0.46	0	26501	0	4465010	0	1083570	0	17028	0	11575	0	0	0	62961	0	88	0	0	0	1335	0	192226	0	2390	0	196039	0	73.68	0	3289876	0	51617	207673	4.023345021989	4465010.0	4373446.0	26501.0	1083570.0	17028.0	11575.0	0.0	62961.0	3289876.0	97.9	0.6	24.3	0.4	0.3	0.0	1.4	73.7	51	51	51.00	38	227715510	24.0	25.5	26.7	23.7	0.0	35.5	24.3	smartseq
1872938	SRR2131942	SRP061708	SRS1015148	SRX1122445	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834930: DRG_bulk_SNI_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact bulk cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834930		GSM1834930	DRG_bulk_SNI_1	119536707	2343857	2016-08-26 15:44:09	92256121	119536707	2343857	1	2343857	index:0,count:2343857,average:51,stdev:0	GSM1834930_r1						1.14	1.55	0.03	115921814	130642317	81705423	100703381	112.7	123.25	0	0	0	0	0	0	62.75	89.11	3122864	1442005	3122864	1442005	47.88	58.46	3122864	1100342	3122864	946145	7908529	6.82	0.81	0	29.01	0	0.25	0	0.14	0	0.00	0	1.55	0	2298173	0	51	0	50.49	0	3.63	0	0.04	0	1.04	0	0.04	0	496.35	0	0.46	0	19076	0	2343857	0	679860	0	5958	0	3319	0	0	0	36407	0	43	0	0	0	440	0	65803	0	1388	0	67674	0	69.04	0	1618313	0	29461	69480	2.358372085129	2343857.0	2298173.0	19076.0	679860.0	5958.0	3319.0	0.0	36407.0	1618313.0	98.1	0.8	29.0	0.3	0.1	0.0	1.6	69.0	51	51	51.00	38	119536707	24.2	25.5	26.1	24.2	0.0	35.5	24.1	smartseq
1872954	SRR2131943	SRP061708	SRS1015150	SRX1122446	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834931: DRG_bulk_SNI_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact bulk cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834931		GSM1834931	DRG_bulk_SNI_2	135832686	2663386	2016-08-26 15:44:09	106559621	135832686	2663386	1	2663386	index:0,count:2663386,average:51,stdev:0	GSM1834931_r1						0.74	1.39	0.02	132281870	151963087	93744691	117107764	114.88	124.92	0	0	0	0	0	0	63.31	89.33	3549201	1658302	3549201	1658302	47.12	56.89	3549201	1234260	3549201	1055995	7983871	6.04	0.59	0	28.65	0	0.22	0	0.13	0	0.00	0	1.31	0	2619271	0	51	0	50.50	0	3.68	0	0.04	0	1.03	0	0.04	0	504.64	0	0.51	0	15606	0	2663386	0	762971	0	5791	0	3490	0	0	0	34834	0	52	0	0	0	614	0	82190	0	1483	0	84339	0	69.70	0	1856300	0	33417	87051	2.604991471407	2663386.0	2619271.0	15606.0	762971.0	5791.0	3490.0	0.0	34834.0	1856300.0	98.3	0.6	28.6	0.2	0.1	0.0	1.3	69.7	51	51	51.00	38	135832686	23.8	25.8	27.0	23.4	0.0	35.2	23.6	smartseq
1872971	SRR2131944	SRP061708	SRS1015146	SRX1122447	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834932: DRG_bulk_SNI_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact bulk cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834932		GSM1834932	DRG_bulk_SNI_3	74359275	1458025	2016-08-26 15:44:09	58662549	74359275	1458025	1	1458025	index:0,count:1458025,average:51,stdev:0	GSM1834932_r1						1.05	1.82	0.04	72139412	80414169	53120431	63494576	111.47	119.53	0	0	0	0	0	0	65.45	88.93	1917338	935752	1917338	935752	53.43	62.49	1917338	763905	1917338	657527	4584546	6.36	0.67	0	25.89	0	0.32	0	0.17	0	0.00	0	1.45	0	1429762	0	51	0	50.48	0	3.37	0	0.03	0	1.05	0	0.04	0	349.93	0	0.50	0	9810	0	1458025	0	377496	0	4600	0	2504	0	0	0	21159	0	34	0	0	0	368	0	53879	0	766	0	55047	0	72.17	0	1052266	0	25747	56645	2.200062143162	1458025.0	1429762.0	9810.0	377496.0	4600.0	2504.0	0.0	21159.0	1052266.0	98.1	0.7	25.9	0.3	0.2	0.0	1.5	72.2	51	51	51.00	38	74359275	24.4	25.1	26.4	24.1	0.0	35.2	23.6	smartseq
1872987	SRR2131945	SRP061708	SRS1015145	SRX1122448	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834933: n3.1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834933		GSM1834933	n3.1	178900350	3507850	2016-08-26 15:44:09	130620484	178900350	3507850	1	3507850	index:0,count:3507850,average:51,stdev:0	GSM1834933_r1						0.79	1.88	0.03	172428524	193578063	130892712	157852624	112.27	120.6	0	0	0	0	0	0	65.18	85.93	4532981	2227906	4532981	2227906	50.4	58.35	4532981	1722666	4532981	1512953	15117898	8.77	0.78	0	23.53	0	0.36	0	0.29	0	0.00	0	1.91	0	3418097	0	51	0	50.48	0	3.18	0	0.03	0	1.07	0	0.03	0	467.71	0	0.41	0	27300	0	3507850	0	825385	0	12638	0	10093	0	0	0	67022	0	96	0	0	0	787	0	111343	0	2102	0	114328	0	73.91	0	2592712	0	38265	118915	3.107670194695	3507850.0	3418097.0	27300.0	825385.0	12638.0	10093.0	0.0	67022.0	2592712.0	97.4	0.8	23.5	0.4	0.3	0.0	1.9	73.9	51	51	51.00	38	178900350	23.9	25.8	26.1	24.2	0.0	36.4	25.8	smartseq
1873003	SRR2131946	SRP061708	SRS1015147	SRX1122449	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834934: n3.2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834934		GSM1834934	n3.2	184537533	3618383	2016-08-26 15:44:09	134760505	184537533	3618383	1	3618383	index:0,count:3618383,average:51,stdev:0	GSM1834934_r1						0.49	1.55	0.02	178915090	198908252	130925039	158200931	111.17	120.83	0	0	0	0	0	0	63.84	87.26	4747563	2262327	4747563	2262327	49.62	59.43	4747563	1758373	4747563	1540773	14530324	8.12	0.65	0	26.30	0	0.28	0	0.24	0	0.00	0	1.53	0	3544014	0	51	0	50.50	0	3.60	0	0.04	0	1.04	0	0.03	0	372.18	0	0.40	0	23646	0	3618383	0	951485	0	10183	0	8704	0	0	0	55482	0	78	0	0	0	872	0	117649	0	2279	0	120878	0	71.65	0	2592529	0	39453	124873	3.165107849847	3618383.0	3544014.0	23646.0	951485.0	10183.0	8704.0	0.0	55482.0	2592529.0	97.9	0.7	26.3	0.3	0.2	0.0	1.5	71.6	51	51	51.00	38	184537533	23.8	25.9	26.1	24.2	0.0	36.4	25.6	smartseq
1873017	SRR2131947	SRP061708	SRS1015144	SRX1122450	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834935: n3.3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834935		GSM1834935	n3.3	112662162	2209062	2016-08-26 15:44:09	85594320	112662162	2209062	1	2209062	index:0,count:2209062,average:51,stdev:0	GSM1834935_r1						1.35	1.58	0.04	108719785	124234329	80716682	99481329	114.27	123.25	0	0	0	0	0	0	62.89	84.81	2861147	1354931	2861147	1354931	45.51	53.74	2861147	980407	2861147	858513	9547573	8.78	0.82	0	25.21	0	0.36	0	0.25	0	0.00	0	1.86	0	2154485	0	51	0	50.52	0	3.08	0	0.03	0	1.06	0	0.03	0	418.56	0	0.45	0	18221	0	2209062	0	556894	0	7985	0	5540	0	0	0	41052	0	39	0	0	0	505	0	57974	0	1313	0	59831	0	72.32	0	1597591	0	26861	61033	2.272178995570	2209062.0	2154485.0	18221.0	556894.0	7985.0	5540.0	0.0	41052.0	1597591.0	97.5	0.8	25.2	0.4	0.3	0.0	1.9	72.3	51	51	51.00	38	112662162	24.3	25.3	26.0	24.5	0.0	35.8	24.6	smartseq
1873033	SRR2131948	SRP061708	SRS1015143	SRX1122451	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834936: n3.4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834936		GSM1834936	n3.4	142462176	2793376	2016-08-26 15:44:09	103996343	142462176	2793376	1	2793376	index:0,count:2793376,average:51,stdev:0	GSM1834936_r1						0.58	1.45	0.03	138225226	154061512	99645597	121315938	111.46	121.75	0	0	0	0	0	0	63.18	87.68	3674257	1729477	3674257	1729477	48.06	58.6	3674257	1315703	3674257	1155830	10342788	7.48	0.69	0	27.39	0	0.26	0	0.18	0	0.00	0	1.56	0	2737484	0	51	0	50.52	0	3.51	0	0.04	0	1.04	0	0.04	0	478.86	0	0.39	0	19413	0	2793376	0	765107	0	7245	0	5130	0	0	0	43517	0	51	0	0	0	612	0	80204	0	1727	0	82594	0	70.61	0	1972377	0	32670	84344	2.581695745332	2793376.0	2737484.0	19413.0	765107.0	7245.0	5130.0	0.0	43517.0	1972377.0	98.0	0.7	27.4	0.3	0.2	0.0	1.6	70.6	51	51	51.00	38	142462176	23.8	25.8	26.0	24.3	0.0	36.4	25.6	smartseq
1873160	SRR2131950	SRP061708	SRS1015141	SRX1122453	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834938: n3.6; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834938		GSM1834938	n3.6	184264836	3613036	2016-08-26 15:44:09	134959588	184264836	3613036	1	3613036	index:0,count:3613036,average:51,stdev:0	GSM1834938_r1						0.56	1.54	0.02	177995784	200153260	130906084	160022031	112.45	122.24	0	0	0	0	0	0	63.84	86.85	4711412	2251494	4711412	2251494	47.9	57.35	4711412	1689560	4711412	1486627	14193575	7.97	0.75	0	25.87	0	0.28	0	0.22	0	0.00	0	1.89	0	3526928	0	51	0	50.50	0	3.39	0	0.04	0	1.05	0	0.03	0	481.74	0	0.41	0	27240	0	3613036	0	934559	0	9984	0	7906	0	0	0	68218	0	74	0	0	0	759	0	101440	0	2248	0	104521	0	71.75	0	2592369	0	35627	107286	3.011367782861	3613036.0	3526928.0	27240.0	934559.0	9984.0	7906.0	0.0	68218.0	2592369.0	97.6	0.8	25.9	0.3	0.2	0.0	1.9	71.8	51	51	51.00	38	184264836	23.8	25.9	26.2	24.2	0.0	36.3	25.6	smartseq
1873176	SRR2131951	SRP061708	SRS1015140	SRX1122454	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834939: n3.7; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834939		GSM1834939	n3.7	217349301	4261751	2016-08-26 15:44:09	156223148	217349301	4261751	1	4261751	index:0,count:4261751,average:51,stdev:0	GSM1834939_r1						0.74	1.51	0.03	210893054	233701788	156255038	187235461	110.82	119.83	0	0	0	0	0	0	63.78	86.1	5535664	2663347	5535664	2663347	49.7	59.16	5535664	2075394	5535664	1829948	18433119	8.74	0.63	0	25.41	0	0.29	0	0.25	0	0.00	0	1.47	0	4176139	0	51	0	50.52	0	3.58	0	0.04	0	1.05	0	0.04	0	568.23	0	0.38	0	26670	0	4261751	0	1082927	0	12296	0	10707	0	0	0	62609	0	105	0	0	0	924	0	132316	0	2918	0	136263	0	72.58	0	3093212	0	43632	140026	3.209250091676	4261751.0	4176139.0	26670.0	1082927.0	12296.0	10707.0	0.0	62609.0	3093212.0	98.0	0.6	25.4	0.3	0.3	0.0	1.5	72.6	51	51	51.00	38	217349301	23.8	25.8	26.1	24.2	0.0	36.6	26.1	smartseq
1873192	SRR2131952	SRP061708	SRS1015139	SRX1122455	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834940: n3.8; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834940		GSM1834940	n3.8	148820397	2918047	2016-08-26 15:44:09	111072016	148820397	2918047	1	2918047	index:0,count:2918047,average:51,stdev:0	GSM1834940_r1						0.46	1.56	0.03	144249890	160906964	105424235	127640186	111.55	121.07	0	0	0	0	0	0	63.18	86.51	3833613	1806369	3833613	1806369	48.6	58.33	3833613	1389377	3833613	1218007	12468702	8.64	0.69	0	26.42	0	0.29	0	0.22	0	0.00	0	1.52	0	2858932	0	51	0	50.49	0	3.50	0	0.04	0	1.05	0	0.03	0	328.28	0	0.41	0	20007	0	2918047	0	770846	0	8407	0	6294	0	0	0	44414	0	69	0	0	0	696	0	90056	0	1869	0	92690	0	71.56	0	2088086	0	34215	95212	2.782756101125	2918047.0	2858932.0	20007.0	770846.0	8407.0	6294.0	0.0	44414.0	2088086.0	98.0	0.7	26.4	0.3	0.2	0.0	1.5	71.6	51	51	51.00	38	148820397	24.0	25.7	26.0	24.4	0.0	36.1	25.1	smartseq
1873210	SRR2131953	SRP061708	SRS1015138	SRX1122456	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834941: n3.9; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834941		GSM1834941	n3.9	130039035	2549785	2016-08-26 15:44:09	96667709	130039035	2549785	1	2549785	index:0,count:2549785,average:51,stdev:0	GSM1834941_r1						0.7	1.75	0.03	125999713	137855180	93409448	110002218	109.41	117.76	0	0	0	0	0	0	65.78	88.77	3363622	1642211	3363622	1642211	54.67	64.43	3363622	1364808	3363622	1191885	9426812	7.48	0.69	0	25.35	0	0.34	0	0.22	0	0.00	0	1.53	0	2496372	0	51	0	50.49	0	3.51	0	0.04	0	1.06	0	0.03	0	353.05	0	0.40	0	17656	0	2549785	0	646344	0	8723	0	5561	0	0	0	39129	0	57	0	0	0	677	0	97662	0	1528	0	99924	0	72.56	0	1850028	0	36212	104113	2.875096653043	2549785.0	2496372.0	17656.0	646344.0	8723.0	5561.0	0.0	39129.0	1850028.0	97.9	0.7	25.3	0.3	0.2	0.0	1.5	72.6	51	51	51.00	38	130039035	24.0	25.7	26.0	24.3	0.0	36.2	25.3	smartseq
1873224	SRR2131954	SRP061708	SRS1015137	SRX1122457	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834942: n3.10; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834942		GSM1834942	n3.10	204426054	4008354	2016-08-26 15:44:09	149626920	204426054	4008354	1	4008354	index:0,count:4008354,average:51,stdev:0	GSM1834942_r1						0.42	1.43	0.02	198696440	221633374	144023318	175204044	111.54	121.65	0	0	0	0	0	0	63.89	88.15	5285231	2513764	5285231	2513764	48.94	59.25	5285231	1925700	5285231	1689507	14364735	7.23	0.62	0	27.02	0	0.27	0	0.19	0	0.00	0	1.38	0	3934747	0	51	0	50.51	0	3.73	0	0.04	0	1.04	0	0.04	0	534.45	0	0.39	0	24752	0	4008354	0	1083203	0	10623	0	7574	0	0	0	55410	0	78	0	0	0	886	0	122682	0	2740	0	126386	0	71.14	0	2851544	0	40119	130480	3.252324335103	4008354.0	3934747.0	24752.0	1083203.0	10623.0	7574.0	0.0	55410.0	2851544.0	98.2	0.6	27.0	0.3	0.2	0.0	1.4	71.1	51	51	51.00	38	204426054	23.7	26.0	26.3	24.0	0.0	36.3	25.6	smartseq
1873240	SRR2131955	SRP061708	SRS1015136	SRX1122458	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834943: n3.11; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834943		GSM1834943	n3.11	133487247	2617397	2016-08-26 15:44:09	98687615	133487247	2617397	1	2617397	index:0,count:2617397,average:51,stdev:0	GSM1834943_r1						0.63	1.64	0.03	129263587	142189707	94074881	112527513	110.0	119.61	0	0	0	0	0	0	62.99	86.59	3447673	1613550	3447673	1613550	49.81	59.81	3447673	1275857	3447673	1114582	11136368	8.62	0.71	0	26.67	0	0.30	0	0.24	0	0.00	0	1.59	0	2561564	0	51	0	50.48	0	3.56	0	0.04	0	1.05	0	0.04	0	523.48	0	0.41	0	18588	0	2617397	0	698122	0	7817	0	6407	0	0	0	41609	0	64	0	0	0	642	0	84872	0	1539	0	87117	0	71.19	0	1863442	0	33191	89890	2.708264288512	2617397.0	2561564.0	18588.0	698122.0	7817.0	6407.0	0.0	41609.0	1863442.0	97.9	0.7	26.7	0.3	0.2	0.0	1.6	71.2	51	51	51.00	38	133487247	23.9	25.8	26.0	24.3	0.0	36.2	25.4	smartseq
1873256	SRR2131956	SRP061708	SRS1015135	SRX1122459	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834944: n3.12; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834944		GSM1834944	n3.12	84554379	1657929	2016-08-26 15:44:09	63750053	84554379	1657929	1	1657929	index:0,count:1657929,average:51,stdev:0	GSM1834944_r1						0.78	1.63	0.04	81685558	92126318	59565210	72763866	112.78	122.16	0	0	0	0	0	0	62.57	85.91	2188979	1013416	2188979	1013416	46.97	56.11	2188979	760699	2188979	661948	6947439	8.51	0.82	0	26.54	0	0.35	0	0.20	0	0.00	0	1.76	0	1619620	0	51	0	50.49	0	3.28	0	0.03	0	1.06	0	0.03	0	397.90	0	0.43	0	13530	0	1657929	0	439974	0	5749	0	3390	0	0	0	29170	0	32	0	0	0	356	0	45957	0	1102	0	47447	0	71.15	0	1179646	0	22391	48669	2.173596534322	1657929.0	1619620.0	13530.0	439974.0	5749.0	3390.0	0.0	29170.0	1179646.0	97.7	0.8	26.5	0.3	0.2	0.0	1.8	71.2	51	51	51.00	38	84554379	24.2	25.4	25.9	24.5	0.0	36.0	25.0	smartseq
1873432	SRR2131961	SRP061708	SRS1015130	SRX1122464	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834949: n3.16; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834949		GSM1834949	n3.16	78946419	1547969	2016-08-26 15:44:09	61351100	78946419	1547969	1	1547969	index:0,count:1547969,average:51,stdev:0	GSM1834949_r1						6.68	1.53	0.03	75410625	83985183	52351139	64218674	111.37	122.67	0	0	0	0	0	0	60.34	87.05	2150922	903198	2150922	903198	45.02	54.26	2150922	673824	2150922	562968	4654840	6.17	1.30	0	29.66	0	0.38	0	0.06	0	0.00	0	2.87	0	1496729	0	51	0	50.46	0	3.35	0	0.03	0	1.07	0	0.03	0	398.05	0	0.46	0	20100	0	1547969	0	459167	0	5923	0	941	0	0	0	44376	0	18	0	0	0	132	0	20037	0	728	0	20915	0	67.03	0	1037562	0	11463	20880	1.821512693012	1547969.0	1496729.0	20100.0	459167.0	5923.0	941.0	0.0	44376.0	1037562.0	96.7	1.3	29.7	0.4	0.1	0.0	2.9	67.0	51	51	51.00	38	78946419	24.3	25.3	26.1	24.3	0.0	35.4	23.9	smartseq
1873449	SRR2131962	SRP061708	SRS1015075	SRX1122465	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834950: n3.17; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834950		GSM1834950	n3.17	99811692	1957092	2016-08-26 15:44:09	75790767	99811692	1957092	1	1957092	index:0,count:1957092,average:51,stdev:0	GSM1834950_r1						3.75	1.27	0.02	95708872	112980512	63063822	84679208	118.05	134.28	0	0	0	0	0	0	55.94	85.0	2703552	1062213	2703552	1062213	31.91	38.86	2703552	606017	2703552	485645	5713013	5.97	1.20	0	33.18	0	0.23	0	0.08	0	0.00	0	2.66	0	1898957	0	51	0	50.46	0	3.62	0	0.04	0	1.03	0	0.04	0	391.42	0	0.49	0	23445	0	1957092	0	649286	0	4552	0	1482	0	0	0	52101	0	6	0	0	0	97	0	12496	0	1095	0	13694	0	63.85	0	1249671	0	8210	13097	1.595249695493	1957092.0	1898957.0	23445.0	649286.0	4552.0	1482.0	0.0	52101.0	1249671.0	97.0	1.2	33.2	0.2	0.1	0.0	2.7	63.9	51	51	51.00	38	99811692	23.6	26.1	26.6	23.7	0.0	35.7	24.4	smartseq
1873467	SRR2131963	SRP061708	SRS1015129	SRX1122466	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834951: n3.18; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834951		GSM1834951	n3.18	42319392	829792	2016-08-26 15:44:09	33682999	42319392	829792	1	829792	index:0,count:829792,average:51,stdev:0	GSM1834951_r1						1.2	1.95	0.05	40843394	46237737	31173451	37234486	113.21	119.44	0	0	0	0	0	0	68.15	89.38	1071166	552056	1071166	552056	54.85	63.18	1071166	444271	1071166	390260	2431705	5.95	0.75	0	23.18	0	0.39	0	0.19	0	0.00	0	1.80	0	810002	0	51	0	50.47	0	3.01	0	0.02	0	1.09	0	0.02	0	271.57	0	0.51	0	6191	0	829792	0	192325	0	3261	0	1584	0	0	0	14945	0	20	0	0	0	235	0	34796	0	436	0	35487	0	74.44	0	617677	0	19095	36311	1.901597276774	829792.0	810002.0	6191.0	192325.0	3261.0	1584.0	0.0	14945.0	617677.0	97.6	0.7	23.2	0.4	0.2	0.0	1.8	74.4	51	51	51.00	38	42319392	24.6	24.7	26.6	24.1	0.0	35.0	23.4	smartseq
1873481	SRR2131964	SRP061708	SRS1015128	SRX1122467	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834952: n3.19; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834952		GSM1834952	n3.19	33460539	656089	2016-08-26 15:44:09	26854173	33460539	656089	1	656089	index:0,count:656089,average:51,stdev:0	GSM1834952_r1						0.76	1.86	0.03	32188237	36913111	25017957	30275399	114.68	121.01	0	0	0	0	0	0	68.81	88.6	836855	438928	836855	438928	54.77	61.46	836855	349367	836855	304486	2238751	6.96	0.76	0	21.72	0	0.42	0	0.27	0	0.00	0	2.09	0	637926	0	51	0	50.50	0	3.24	0	0.03	0	1.07	0	0.02	0	236.19	0	0.53	0	5007	0	656089	0	142501	0	2735	0	1746	0	0	0	13682	0	19	0	0	0	198	0	27139	0	390	0	27746	0	75.51	0	495425	0	15051	28452	1.890372732709	656089.0	637926.0	5007.0	142501.0	2735.0	1746.0	0.0	13682.0	495425.0	97.2	0.8	21.7	0.4	0.3	0.0	2.1	75.5	51	51	51.00	38	33460539	24.7	24.5	27.4	23.4	0.0	34.8	23.2	smartseq
1873497	SRR2131965	SRP061708	SRS1015127	SRX1122468	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834953: n3.20; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834953		GSM1834953	n3.20	61973211	1215161	2016-08-26 15:44:09	49095137	61973211	1215161	1	1215161	index:0,count:1215161,average:51,stdev:0	GSM1834953_r1						4.49	1.38	0.03	59253549	68965759	40329383	51887712	116.39	128.66	0	0	0	0	0	0	58.96	86.72	1681474	693269	1681474	693269	39.5	47.67	1681474	464447	1681474	381065	3746708	6.32	1.19	0	30.98	0	0.34	0	0.07	0	0.00	0	2.83	0	1175858	0	51	0	50.45	0	3.54	0	0.04	0	1.06	0	0.04	0	437.46	0	0.55	0	14487	0	1215161	0	376445	0	4152	0	822	0	0	0	34329	0	10	0	0	0	104	0	16588	0	533	0	17235	0	65.79	0	799413	0	10354	17238	1.664863820746	1215161.0	1175858.0	14487.0	376445.0	4152.0	822.0	0.0	34329.0	799413.0	96.8	1.2	31.0	0.3	0.1	0.0	2.8	65.8	51	51	51.00	38	61973211	24.0	25.3	27.1	23.5	0.0	35.0	23.2	smartseq
1873513	SRR2131966	SRP061708	SRS1015126	SRX1122469	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834954: n3.21; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834954		GSM1834954	n3.21	102899997	2017647	2016-08-26 15:44:09	79464869	102899997	2017647	1	2017647	index:0,count:2017647,average:51,stdev:0	GSM1834954_r1						0.48	1.69	0.03	100013888	111121497	73482740	88292608	111.11	120.15	0	0	0	0	0	0	65.48	89.13	2649839	1296506	2649839	1296506	52.39	62.33	2649839	1037393	2649839	906673	6541119	6.54	0.60	0	26.05	0	0.26	0	0.18	0	0.00	0	1.41	0	1980126	0	51	0	50.52	0	3.49	0	0.04	0	1.04	0	0.03	0	290.54	0	0.45	0	12081	0	2017647	0	525510	0	5332	0	3649	0	0	0	28540	0	45	0	0	0	471	0	72431	0	1066	0	74013	0	72.09	0	1454616	0	29667	76751	2.587083291199	2017647.0	1980126.0	12081.0	525510.0	5332.0	3649.0	0.0	28540.0	1454616.0	98.1	0.6	26.0	0.3	0.2	0.0	1.4	72.1	51	51	51.00	38	102899997	24.1	25.5	26.4	24.0	0.0	35.5	24.2	smartseq
1873530	SRR2131967	SRP061708	SRS1015125	SRX1122470	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834955: n3.22; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834955		GSM1834955	n3.22	82970217	1626867	2016-08-26 15:44:09	64413729	82970217	1626867	1	1626867	index:0,count:1626867,average:51,stdev:0	GSM1834955_r1						9.33	1.14	0.02	79634712	91044196	56598107	70949336	114.33	125.36	0	0	0	0	0	0	62.61	88.22	2178365	989047	2178365	989047	46.29	54.06	2178365	731271	2178365	606097	4668237	5.86	1.13	0	28.18	0	0.30	0	0.07	0	0.00	0	2.54	0	1579608	0	51	0	50.48	0	3.62	0	0.04	0	1.05	0	0.03	0	450.52	0	0.43	0	18326	0	1626867	0	458519	0	4811	0	1151	0	0	0	41297	0	13	0	0	0	101	0	19815	0	829	0	20758	0	68.91	0	1121089	0	11322	20889	1.844992050874	1626867.0	1579608.0	18326.0	458519.0	4811.0	1151.0	0.0	41297.0	1121089.0	97.1	1.1	28.2	0.3	0.1	0.0	2.5	68.9	51	51	51.00	38	82970217	24.6	25.0	25.7	24.6	0.0	35.4	24.0	smartseq
1873545	SRR2131968	SRP061708	SRS1015124	SRX1122471	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834956: s3.1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834956		GSM1834956	s3.1	167234406	3279106	2016-08-26 15:44:09	121592279	167234406	3279106	1	3279106	index:0,count:3279106,average:51,stdev:0	GSM1834956_r1						0.88	1.52	0.03	161437726	180654449	118846936	144189152	111.9	121.32	0	0	0	0	0	0	64.65	87.9	4294711	2070783	4294711	2070783	49.69	59.26	4294711	1591674	4294711	1396171	11855483	7.34	0.79	0	25.84	0	0.34	0	0.25	0	0.00	0	1.72	0	3203059	0	51	0	50.45	0	3.40	0	0.04	0	1.05	0	0.03	0	562.13	0	0.39	0	25876	0	3279106	0	847169	0	11190	0	8339	0	0	0	56518	0	59	0	0	0	768	0	99005	0	2303	0	102135	0	71.85	0	2355890	0	35909	105402	2.935253000641	3279106.0	3203059.0	25876.0	847169.0	11190.0	8339.0	0.0	56518.0	2355890.0	97.7	0.8	25.8	0.3	0.3	0.0	1.7	71.8	51	51	51.00	38	167234406	23.9	25.7	25.9	24.4	0.0	36.4	25.7	smartseq
1873563	SRR2131969	SRP061708	SRS1015123	SRX1122472	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834957: s3.2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834957		GSM1834957	s3.2	172412028	3380628	2016-08-26 15:44:09	125287614	172412028	3380628	1	3380628	index:0,count:3380628,average:51,stdev:0	GSM1834957_r1						0.67	1.56	0.05	166641818	186894347	121423217	148021321	112.15	121.91	0	0	0	0	0	0	63.85	87.68	4504677	2109327	4504677	2109327	49.72	59.06	4504677	1642534	4504677	1420768	13223452	7.94	0.70	0	26.56	0	0.39	0	0.32	0	0.00	0	1.57	0	3303795	0	51	0	50.47	0	3.44	0	0.04	0	1.05	0	0.03	0	486.81	0	0.39	0	23699	0	3380628	0	897989	0	13089	0	10655	0	0	0	53089	0	60	0	0	0	693	0	102111	0	2244	0	105108	0	71.16	0	2405806	0	36506	109657	3.003807593272	3380628.0	3303795.0	23699.0	897989.0	13089.0	10655.0	0.0	53089.0	2405806.0	97.7	0.7	26.6	0.4	0.3	0.0	1.6	71.2	51	51	51.00	38	172412028	23.8	25.9	26.1	24.3	0.0	36.4	25.8	smartseq
1873676	SRR2131970	SRP061708	SRS1015122	SRX1122473	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834958: s3.3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834958		GSM1834958	s3.3	180721662	3543562	2016-08-26 15:44:09	131488560	180721662	3543562	1	3543562	index:0,count:3543562,average:51,stdev:0	GSM1834958_r1						1.45	1.59	0.02	175270047	196937651	125454587	154110536	112.36	122.84	0	0	0	0	0	0	66.06	92.31	4782213	2293835	4782213	2293835	52.2	62.37	4782213	1812668	4782213	1549921	7975403	4.55	0.62	0	27.86	0	0.40	0	0.25	0	0.00	0	1.37	0	3472263	0	51	0	50.49	0	3.68	0	0.04	0	1.04	0	0.03	0	637.84	0	0.39	0	21965	0	3543562	0	987337	0	14010	0	8720	0	0	0	48569	0	64	0	0	0	923	0	124017	0	2367	0	127371	0	70.13	0	2484926	0	38634	134448	3.480043485013	3543562.0	3472263.0	21965.0	987337.0	14010.0	8720.0	0.0	48569.0	2484926.0	98.0	0.6	27.9	0.4	0.2	0.0	1.4	70.1	51	51	51.00	38	180721662	23.6	26.1	26.3	24.0	0.0	36.4	25.8	smartseq
1873692	SRR2131971	SRP061708	SRS1015121	SRX1122474	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834959: s3.4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834959		GSM1834959	s3.4	175940616	3449816	2016-08-26 15:44:09	128027034	175940616	3449816	1	3449816	index:0,count:3449816,average:51,stdev:0	GSM1834959_r1						1.03	1.82	0.04	170422119	187009204	127558521	150141169	109.73	117.7	0	0	0	0	0	0	67.6	90.35	4593662	2282955	4593662	2282955	57.31	66.31	4593662	1935278	4593662	1675519	10757743	6.31	0.61	0	24.65	0	0.46	0	0.29	0	0.00	0	1.36	0	3377014	0	51	0	50.48	0	3.36	0	0.03	0	1.06	0	0.03	0	413.98	0	0.38	0	21052	0	3449816	0	850276	0	15877	0	9842	0	0	0	47083	0	86	0	0	0	1166	0	145955	0	2274	0	149481	0	73.24	0	2526738	0	43986	158087	3.594029918610	3449816.0	3377014.0	21052.0	850276.0	15877.0	9842.0	0.0	47083.0	2526738.0	97.9	0.6	24.6	0.5	0.3	0.0	1.4	73.2	51	51	51.00	38	175940616	23.9	25.8	26.0	24.3	0.0	36.5	25.9	smartseq
1873708	SRR2131972	SRP061708	SRS1015120	SRX1122475	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834960: s3.5; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834960		GSM1834960	s3.5	160564728	3148328	2016-08-26 15:44:09	114728959	160564728	3148328	1	3148328	index:0,count:3148328,average:51,stdev:0	GSM1834960_r1						0.75	1.49	0.04	155682359	171098426	113578843	135409126	109.9	119.22	0	0	0	0	0	0	62.65	85.89	4175140	1931292	4175140	1931292	50.34	59.85	4175140	1551866	4175140	1345820	14684003	9.43	0.64	0	26.50	0	0.33	0	0.30	0	0.00	0	1.45	0	3082875	0	51	0	50.51	0	3.67	0	0.04	0	1.04	0	0.04	0	472.25	0	0.38	0	20006	0	3148328	0	834242	0	10377	0	9375	0	0	0	45701	0	65	0	0	0	688	0	93883	0	2206	0	96842	0	71.42	0	2248633	0	35828	100759	2.812297644301	3148328.0	3082875.0	20006.0	834242.0	10377.0	9375.0	0.0	45701.0	2248633.0	97.9	0.6	26.5	0.3	0.3	0.0	1.5	71.4	51	51	51.00	38	160564728	23.8	25.9	26.1	24.1	0.0	36.7	26.4	smartseq
1873723	SRR2131973	SRP061708	SRS1015119	SRX1122476	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834961: s3.6; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834961		GSM1834961	s3.6	120133152	2355552	2016-08-26 15:44:09	88733819	120133152	2355552	1	2355552	index:0,count:2355552,average:51,stdev:0	GSM1834961_r1						0.52	1.65	0.03	116829445	129851671	85386855	102997284	111.15	120.62	0	0	0	0	0	0	65.21	89.25	3108114	1508895	3108114	1508895	51.69	61.93	3108114	1196112	3108114	1047081	8181949	7.00	0.61	0	26.46	0	0.27	0	0.18	0	0.00	0	1.32	0	2314038	0	51	0	50.50	0	3.52	0	0.04	0	1.04	0	0.03	0	498.82	0	0.40	0	14364	0	2355552	0	623312	0	6391	0	4147	0	0	0	30976	0	63	0	0	0	616	0	84688	0	1598	0	86965	0	71.78	0	1690726	0	33775	89746	2.657172464841	2355552.0	2314038.0	14364.0	623312.0	6391.0	4147.0	0.0	30976.0	1690726.0	98.2	0.6	26.5	0.3	0.2	0.0	1.3	71.8	51	51	51.00	38	120133152	23.8	25.9	26.1	24.2	0.0	36.2	25.5	smartseq
1873739	SRR2131974	SRP061708	SRS1015118	SRX1122477	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834962: s3.7; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834962		GSM1834962	s3.7	171486888	3362488	2016-08-26 15:44:09	125149121	171486888	3362488	1	3362488	index:0,count:3362488,average:51,stdev:0	GSM1834962_r1						0.35	1.39	0.03	165510516	179429018	118865070	140099451	108.41	117.86	0	0	0	0	0	0	65.05	90.57	4519194	2132907	4519194	2132907	55.1	66.34	4519194	1806759	4519194	1562396	11040063	6.67	0.72	0	27.48	0	0.29	0	0.17	0	0.00	0	2.02	0	3279090	0	51	0	50.47	0	3.99	0	0.05	0	1.03	0	0.04	0	504.37	0	0.38	0	24346	0	3362488	0	924050	0	9788	0	5581	0	0	0	68029	0	64	0	0	0	773	0	114112	0	2189	0	117138	0	70.04	0	2355040	0	38011	123195	3.241035489727	3362488.0	3279090.0	24346.0	924050.0	9788.0	5581.0	0.0	68029.0	2355040.0	97.5	0.7	27.5	0.3	0.2	0.0	2.0	70.0	51	51	51.00	38	171486888	23.5	26.2	26.4	23.9	0.0	36.4	25.6	smartseq
1873756	SRR2131975	SRP061708	SRS1015117	SRX1122478	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834963: s3.8; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834963		GSM1834963	s3.8	130438008	2557608	2016-08-26 15:44:09	97214766	130438008	2557608	1	2557608	index:0,count:2557608,average:51,stdev:0	GSM1834963_r1						0.59	1.69	0.02	125848821	135307054	91942145	106961035	107.52	116.34	0	0	0	0	0	0	64.7	88.56	3365348	1612946	3365348	1612946	55.05	65.74	3365348	1372364	3365348	1197207	9929758	7.89	0.74	0	26.26	0	0.29	0	0.21	0	0.00	0	2.03	0	2492917	0	51	0	50.48	0	3.75	0	0.04	0	1.04	0	0.04	0	354.13	0	0.41	0	18897	0	2557608	0	671683	0	7460	0	5288	0	0	0	51943	0	61	0	0	0	628	0	97622	0	1557	0	99868	0	71.21	0	1821234	0	36317	103835	2.859129333370	2557608.0	2492917.0	18897.0	671683.0	7460.0	5288.0	0.0	51943.0	1821234.0	97.5	0.7	26.3	0.3	0.2	0.0	2.0	71.2	51	51	51.00	38	130438008	23.8	25.9	26.2	24.1	0.0	36.1	25.2	smartseq
1873772	SRR2131976	SRP061708	SRS1015116	SRX1122479	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834964: s3.9; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834964		GSM1834964	s3.9	224860734	4409034	2016-08-26 15:44:09	163905257	224860734	4409034	1	4409034	index:0,count:4409034,average:51,stdev:0	GSM1834964_r1						0.81	1.52	0.03	216200592	244043090	157643668	193587825	112.88	122.8	0	0	0	0	0	0	63.87	87.67	5778667	2738332	5778667	2738332	47.99	57.5	5778667	2057456	5778667	1795963	15993735	7.40	0.85	0	26.40	0	0.32	0	0.22	0	0.00	0	2.22	0	4287548	0	51	0	50.47	0	3.42	0	0.04	0	1.05	0	0.03	0	721.48	0	0.40	0	37321	0	4409034	0	1163961	0	14150	0	9533	0	0	0	97803	0	80	0	0	0	926	0	125204	0	2901	0	129111	0	70.85	0	3123587	0	40486	134222	3.315269475868	4409034.0	4287548.0	37321.0	1163961.0	14150.0	9533.0	0.0	97803.0	3123587.0	97.2	0.8	26.4	0.3	0.2	0.0	2.2	70.8	51	51	51.00	38	224860734	23.9	25.8	25.9	24.4	0.0	36.4	25.6	smartseq
1873786	SRR2131977	SRP061708	SRS1015115	SRX1122480	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834965: s3.10; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834965		GSM1834965	s3.10	164805837	3231487	2016-08-26 15:44:09	120608977	164805837	3231487	1	3231487	index:0,count:3231487,average:51,stdev:0	GSM1834965_r1						0.58	1.43	0.05	159014787	177597833	113511857	138634222	111.69	122.13	0	0	0	0	0	0	64.5	90.39	4356715	2032976	4356715	2032976	50.84	61.32	4356715	1602327	4356715	1379073	9797260	6.16	0.73	0	27.94	0	0.35	0	0.24	0	0.00	0	1.87	0	3151994	0	51	0	50.47	0	3.73	0	0.04	0	1.04	0	0.04	0	505.80	0	0.39	0	23458	0	3231487	0	902892	0	11375	0	7828	0	0	0	60290	0	65	0	0	0	738	0	95967	0	2291	0	99061	0	69.60	0	2249102	0	35035	103507	2.954388468674	3231487.0	3151994.0	23458.0	902892.0	11375.0	7828.0	0.0	60290.0	2249102.0	97.5	0.7	27.9	0.4	0.2	0.0	1.9	69.6	51	51	51.00	38	164805837	23.6	26.1	26.3	24.0	0.0	36.3	25.5	smartseq
1873801	SRR2131978	SRP061708	SRS1015114	SRX1122481	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834966: s3.11; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834966		GSM1834966	s3.11	220936029	4332079	2016-08-26 15:44:09	160756511	220936029	4332079	1	4332079	index:0,count:4332079,average:51,stdev:0	GSM1834966_r1						0.55	1.68	0.03	213818874	234494599	157530639	186145899	109.67	118.16	0	0	0	0	0	0	66.23	89.92	5803476	2807022	5803476	2807022	55.5	65.27	5803476	2352325	5803476	2037694	14555426	6.81	0.64	0	25.77	0	0.37	0	0.26	0	0.00	0	1.53	0	4238302	0	51	0	50.46	0	3.58	0	0.04	0	1.05	0	0.03	0	487.36	0	0.39	0	27590	0	4332079	0	1116450	0	16117	0	11258	0	0	0	66402	0	93	0	0	0	1252	0	172535	0	2862	0	176742	0	72.06	0	3121852	0	47471	186080	3.919866866087	4332079.0	4238302.0	27590.0	1116450.0	16117.0	11258.0	0.0	66402.0	3121852.0	97.8	0.6	25.8	0.4	0.3	0.0	1.5	72.1	51	51	51.00	38	220936029	23.7	26.0	26.2	24.1	0.0	36.4	25.8	smartseq
1873816	SRR2131979	SRP061708	SRS1015113	SRX1122482	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834967: s3.12; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834967		GSM1834967	s3.12	214860195	4212945	2016-08-26 15:44:09	157858188	214860195	4212945	1	4212945	index:0,count:4212945,average:51,stdev:0	GSM1834967_r1						0.66	1.37	0.03	207820217	232808596	148266589	181761677	112.02	122.59	0	0	0	0	0	0	64.12	89.9	5663652	2640997	5663652	2640997	50.19	60.57	5663652	2067011	5663652	1779387	13826434	6.65	0.68	0	28.03	0	0.29	0	0.17	0	0.00	0	1.78	0	4118636	0	51	0	50.47	0	3.90	0	0.05	0	1.03	0	0.04	0	421.29	0	0.39	0	28820	0	4212945	0	1181084	0	12009	0	7343	0	0	0	74957	0	67	0	0	0	891	0	120832	0	2831	0	124621	0	69.73	0	2937552	0	38533	130874	3.396413463784	4212945.0	4118636.0	28820.0	1181084.0	12009.0	7343.0	0.0	74957.0	2937552.0	97.8	0.7	28.0	0.3	0.2	0.0	1.8	69.7	51	51	51.00	38	214860195	23.6	26.1	26.3	24.0	0.0	36.3	25.4	smartseq
1873928	SRR2131980	SRP061708	SRS1015112	SRX1122483	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834968: s3.13; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834968		GSM1834968	s3.13	194985648	3823248	2016-08-26 15:44:09	143146796	194985648	3823248	1	3823248	index:0,count:3823248,average:51,stdev:0	GSM1834968_r1						0.54	1.52	0.04	188642822	209149195	138874990	166633685	110.87	119.99	0	0	0	0	0	0	65.58	89.1	5018658	2448703	5018658	2448703	52.96	63.01	5018658	1977563	5018658	1731623	14139389	7.50	0.65	0	25.79	0	0.29	0	0.20	0	0.00	0	1.84	0	3734168	0	51	0	50.53	0	3.53	0	0.04	0	1.04	0	0.04	0	417.08	0	0.39	0	24948	0	3823248	0	985858	0	10984	0	7819	0	0	0	70277	0	79	0	0	0	935	0	126076	0	2458	0	129548	0	71.88	0	2748310	0	42571	134897	3.168753376712	3823248.0	3734168.0	24948.0	985858.0	10984.0	7819.0	0.0	70277.0	2748310.0	97.7	0.7	25.8	0.3	0.2	0.0	1.8	71.9	51	51	51.00	38	194985648	23.8	25.9	26.1	24.2	0.0	36.3	25.6	smartseq
1873946	SRR2131981	SRP061708	SRS1015111	SRX1122484	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834969: s3.14; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834969		GSM1834969	s3.14	211355016	4144216	2016-08-26 15:44:09	154100129	211355016	4144216	1	4144216	index:0,count:4144216,average:51,stdev:0	GSM1834969_r1						0.85	1.7	0.03	204671764	225775472	151907098	180128802	110.31	118.58	0	0	0	0	0	0	66.9	90.15	5538746	2713280	5538746	2713280	56.12	65.24	5538746	2276297	5538746	1963434	13401864	6.55	0.58	0	25.24	0	0.42	0	0.36	0	0.00	0	1.35	0	4055788	0	51	0	50.47	0	3.52	0	0.04	0	1.05	0	0.03	0	678.14	0	0.39	0	23995	0	4144216	0	1046150	0	17542	0	15036	0	0	0	55850	0	96	0	0	0	1371	0	169899	0	2627	0	173993	0	72.62	0	3009638	0	47842	184438	3.855148196146	4144216.0	4055788.0	23995.0	1046150.0	17542.0	15036.0	0.0	55850.0	3009638.0	97.9	0.6	25.2	0.4	0.4	0.0	1.3	72.6	51	51	51.00	38	211355016	23.8	25.9	26.2	24.1	0.0	36.4	25.8	smartseq
1873962	SRR2131982	SRP061708	SRS1015110	SRX1122485	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834970: s3.15; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834970		GSM1834970	s3.15	194010885	3804135	2016-08-26 15:44:09	141817979	194010885	3804135	1	3804135	index:0,count:3804135,average:51,stdev:0	GSM1834970_r1						0.39	1.45	0.03	188646511	210864536	131627465	162358679	111.78	123.35	0	0	0	0	0	0	64.85	92.95	5224252	2422821	5224252	2422821	51.37	62.67	5224252	1919227	5224252	1633589	8373133	4.44	0.61	0	29.68	0	0.32	0	0.16	0	0.00	0	1.32	0	3735772	0	51	0	50.50	0	3.95	0	0.04	0	1.03	0	0.04	0	547.80	0	0.39	0	23226	0	3804135	0	1129145	0	12132	0	6008	0	0	0	50223	0	86	0	0	0	904	0	126946	0	2513	0	130449	0	68.52	0	2606627	0	40586	137057	3.376952643769	3804135.0	3735772.0	23226.0	1129145.0	12132.0	6008.0	0.0	50223.0	2606627.0	98.2	0.6	29.7	0.3	0.2	0.0	1.3	68.5	51	51	51.00	38	194010885	23.4	26.4	26.6	23.7	0.0	36.3	25.5	smartseq
1873978	SRR2131983	SRP061708	SRS1015109	SRX1122486	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834971: s3.16; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834971		GSM1834971	s3.16	99720657	1955307	2016-08-26 15:44:09	76727560	99720657	1955307	1	1955307	index:0,count:1955307,average:51,stdev:0	GSM1834971_r1						0.55	1.51	0.02	96893592	108866456	69437723	85073807	112.36	122.52	0	0	0	0	0	0	64.36	89.82	2605583	1234842	2605583	1234842	50.02	60.21	2605583	959791	2605583	827803	5956702	6.15	0.60	0	27.82	0	0.27	0	0.23	0	0.00	0	1.37	0	1918699	0	51	0	50.51	0	3.73	0	0.04	0	1.04	0	0.04	0	469.27	0	0.45	0	11734	0	1955307	0	543928	0	5327	0	4441	0	0	0	26840	0	48	0	0	0	422	0	63995	0	1173	0	65638	0	70.31	0	1374771	0	27854	67851	2.435951748402	1955307.0	1918699.0	11734.0	543928.0	5327.0	4441.0	0.0	26840.0	1374771.0	98.1	0.6	27.8	0.3	0.2	0.0	1.4	70.3	51	51	51.00	38	99720657	23.8	25.8	26.4	23.9	0.0	35.6	24.3	smartseq
1873992	SRR2131984	SRP061708	SRS1015108	SRX1122487	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834972: s3.17; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834972		GSM1834972	s3.17	82489542	1617442	2016-08-26 15:44:09	62578012	82489542	1617442	1	1617442	index:0,count:1617442,average:51,stdev:0	GSM1834972_r1						0.61	1.67	0.03	80116874	89544772	59593849	71982770	111.77	120.79	0	0	0	0	0	0	66.46	89.36	2117416	1054182	2117416	1054182	52.92	61.93	2117416	839532	2117416	730584	5390102	6.73	0.59	0	25.14	0	0.28	0	0.21	0	0.00	0	1.44	0	1586292	0	51	0	50.52	0	3.63	0	0.04	0	1.04	0	0.03	0	342.52	0	0.42	0	9536	0	1617442	0	406636	0	4533	0	3396	0	0	0	23221	0	41	0	0	0	410	0	61049	0	974	0	62474	0	72.93	0	1179656	0	26715	64561	2.416657308628	1617442.0	1586292.0	9536.0	406636.0	4533.0	3396.0	0.0	23221.0	1179656.0	98.1	0.6	25.1	0.3	0.2	0.0	1.4	72.9	51	51	51.00	38	82489542	23.9	25.9	26.5	23.8	0.0	35.9	25.0	smartseq
1874008	SRR2131985	SRP061708	SRS1015107	SRX1122488	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834973: s3.18; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834973		GSM1834973	s3.18	177860460	3487460	2016-08-26 15:44:09	129496598	177860460	3487460	1	3487460	index:0,count:3487460,average:51,stdev:0	GSM1834973_r1						0.89	1.65	0.03	172612196	190444858	127763607	152163287	110.33	119.1	0	0	0	0	0	0	65.82	88.95	4556059	2250696	4556059	2250696	53.23	63.27	4556059	1820382	4556059	1600850	12605240	7.30	0.65	0	25.50	0	0.32	0	0.19	0	0.00	0	1.43	0	3419542	0	51	0	50.50	0	3.43	0	0.03	0	1.06	0	0.03	0	348.75	0	0.39	0	22783	0	3487460	0	889382	0	11275	0	6775	0	0	0	49868	0	68	0	0	0	1046	0	132734	0	2364	0	136212	0	72.55	0	2530160	0	43245	141256	3.266412302000	3487460.0	3419542.0	22783.0	889382.0	11275.0	6775.0	0.0	49868.0	2530160.0	98.1	0.7	25.5	0.3	0.2	0.0	1.4	72.6	51	51	51.00	38	177860460	24.0	25.7	25.9	24.4	0.0	36.5	25.9	smartseq
1874040	SRR2131987	SRP061708	SRS1015105	SRX1122490	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834975: s3.20; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834975		GSM1834975	s3.20	186235374	3651674	2016-08-26 15:44:09	135811749	186235374	3651674	1	3651674	index:0,count:3651674,average:51,stdev:0	GSM1834975_r1						0.74	1.77	0.02	180422210	201366147	136358914	163348224	111.61	119.79	0	0	0	0	0	0	67.61	89.48	4771906	2417993	4771906	2417993	54.75	63.34	4771906	1958080	4771906	1711629	12540071	6.95	0.61	0	23.95	0	0.35	0	0.25	0	0.00	0	1.46	0	3576538	0	51	0	50.46	0	3.52	0	0.04	0	1.05	0	0.03	0	486.89	0	0.39	0	22416	0	3651674	0	874394	0	12924	0	8981	0	0	0	53231	0	93	0	0	0	1056	0	148197	0	2510	0	151856	0	74.00	0	2702144	0	43453	158661	3.651324419488	3651674.0	3576538.0	22416.0	874394.0	12924.0	8981.0	0.0	53231.0	2702144.0	97.9	0.6	23.9	0.4	0.2	0.0	1.5	74.0	51	51	51.00	38	186235374	23.7	26.1	26.4	23.9	0.0	36.4	25.9	smartseq
917509	SRR2132000	SRP061708	SRS1015092	SRX1122503	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834988: s3.33; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834988		GSM1834988	s3.33	196910300	3938206	2016-08-26 15:44:09	80272448	196910300	3938206	1	3938206	index:0,count:3938206,average:50,stdev:0	GSM1834988_r1						6.83	1.14	0.04	190024352	208820705	147035103	172462425	109.89	117.29	0	0	0	0	0	0	72.5	93.93	4940186	2786821	4940186	2786821	62.15	72.65	4940186	2388895	4940186	2155542	9104061	4.79	0.72	0	22.27	0	0.37	0	0.11	0	0.00	0	1.91	0	3843816	0	50	0	49.56	0	3.74	0	0.04	0	1.04	0	0.03	0	567.10	0	0.23	0	28443	0	3938206	0	876856	0	14524	0	4478	0	0	0	75388	0	48	0	0	0	352	0	56000	0	2879	0	59279	0	75.34	0	2966960	0	23170	59668	2.575226586103	3938206.0	3843816.0	28443.0	876856.0	14524.0	4478.0	0.0	75388.0	2966960.0	97.6	0.7	22.3	0.4	0.1	0.0	1.9	75.3	50	50	50.00	6	196910300	24.8	24.5	24.8	25.9	0.0	35.4	28.4	smartseq
917518	SRR2132001	SRP061708	SRS1015091	SRX1122504	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834989: s3.34; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834989		GSM1834989	s3.34	162093500	3241870	2016-08-26 15:44:09	66320817	162093500	3241870	1	3241870	index:0,count:3241870,average:50,stdev:0	GSM1834989_r1						5.64	1.13	0.05	157262097	171752250	120293341	140577485	109.21	116.86	0	0	0	0	0	0	72.11	94.45	4080138	2291016	4080138	2291016	62.18	73.52	4080138	1975412	4080138	1783430	7008809	4.46	0.63	0	23.18	0	0.26	0	0.07	0	0.00	0	1.66	0	3177082	0	50	0	49.59	0	3.78	0	0.04	0	1.03	0	0.03	0	466.83	0	0.24	0	20426	0	3241870	0	751359	0	8577	0	2316	0	0	0	53895	0	32	0	0	0	397	0	55516	0	2446	0	58391	0	74.82	0	2425723	0	23584	58699	2.488933175034	3241870.0	3177082.0	20426.0	751359.0	8577.0	2316.0	0.0	53895.0	2425723.0	98.0	0.6	23.2	0.3	0.1	0.0	1.7	74.8	50	50	50.00	6	162093500	24.5	24.8	25.1	25.5	0.0	35.4	28.4	smartseq
917527	SRR2132002	SRP061708	SRS1015090	SRX1122505	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834990: s3.35; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834990		GSM1834990	s3.35	154804450	3096089	2016-08-26 15:44:09	63576275	154804450	3096089	1	3096089	index:0,count:3096089,average:50,stdev:0	GSM1834990_r1						1.2	1.71	0.03	149770628	163303923	112435206	131536768	109.04	116.99	0	0	0	0	0	0	67.05	89.4	4050831	2030314	4050831	2030314	56.99	66.93	4050831	1725720	4050831	1520112	11481740	7.67	0.67	0	24.45	0	0.42	0	0.27	0	0.00	0	1.51	0	3028158	0	50	0	49.51	0	3.67	0	0.04	0	1.05	0	0.03	0	359.55	0	0.30	0	20717	0	3096089	0	757127	0	13029	0	8247	0	0	0	46655	0	51	0	0	0	730	0	102260	0	2272	0	105313	0	73.35	0	2271031	0	36129	109729	3.037144676022	3096089.0	3028158.0	20717.0	757127.0	13029.0	8247.0	0.0	46655.0	2271031.0	97.8	0.7	24.5	0.4	0.3	0.0	1.5	73.4	50	50	50.00	6	154804450	24.2	25.3	25.7	24.9	0.0	35.4	28.3	smartseq
917535	SRR2132003	SRP061708	SRS1015089	SRX1122506	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834991: s3.36; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834991		GSM1834991	s3.36	171924600	3438492	2016-08-26 15:44:09	70471033	171924600	3438492	1	3438492	index:0,count:3438492,average:50,stdev:0	GSM1834991_r1						1.24	1.99	0.05	166095240	179537192	125412480	144974328	108.09	115.6	0	0	0	0	0	0	67.66	89.69	4558951	2273245	4558951	2273245	59.38	68.48	4558951	1995124	4558951	1735506	12373297	7.45	0.66	0	24.01	0	0.51	0	0.31	0	0.00	0	1.47	0	3359923	0	50	0	49.48	0	3.57	0	0.04	0	1.06	0	0.03	0	495.14	0	0.31	0	22523	0	3438492	0	825427	0	17590	0	10548	0	0	0	50431	0	79	0	0	0	1071	0	137139	0	2718	0	141007	0	73.71	0	2534496	0	42661	149204	3.497433252854	3438492.0	3359923.0	22523.0	825427.0	17590.0	10548.0	0.0	50431.0	2534496.0	97.7	0.7	24.0	0.5	0.3	0.0	1.5	73.7	50	50	50.00	6	171924600	24.2	25.2	25.6	24.9	0.0	35.4	28.3	smartseq
917543	SRR2132004	SRP061708	SRS1015088	SRX1122507	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834992: s3.37; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834992		GSM1834992	s3.37	91352850	1827057	2016-08-26 15:44:09	37679762	91352850	1827057	1	1827057	index:0,count:1827057,average:50,stdev:0	GSM1834992_r1						6.11	1.03	0.05	86586606	93085030	70336555	79500413	107.51	113.03	0	0	0	0	0	0	76.83	94.88	2188929	1345389	2188929	1345389	68.58	78.65	2188929	1200856	2188929	1115194	3740275	4.32	0.98	0	18.23	0	0.37	0	0.07	0	0.00	0	3.72	0	1751070	0	50	0	49.60	0	3.24	0	0.03	0	1.05	0	0.02	0	438.49	0	0.20	0	17927	0	1827057	0	333117	0	6749	0	1324	0	0	0	67914	0	14	0	0	0	118	0	19624	0	995	0	20751	0	77.61	0	1417953	0	11587	20254	1.747993440925	1827057.0	1751070.0	17927.0	333117.0	6749.0	1324.0	0.0	67914.0	1417953.0	95.8	1.0	18.2	0.4	0.1	0.0	3.7	77.6	50	50	50.00	6	91352850	25.2	24.1	24.4	26.3	0.0	35.4	28.3	smartseq
917551	SRR2132005	SRP061708	SRS1015087	SRX1122508	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834993: s3.38; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834993		GSM1834993	s3.38	197380450	3947609	2016-08-26 15:44:09	81146297	197380450	3947609	1	3947609	index:0,count:3947609,average:50,stdev:0	GSM1834993_r1						3.06	0.95	0.04	189550864	223503584	132963416	175491451	117.91	131.98	0	0	0	0	0	0	60.18	85.98	5191777	2309909	5191777	2309909	37.9	46.68	5191777	1454509	5191777	1253977	16481232	8.69	0.95	0	29.17	0	0.33	0	0.24	0	0.00	0	2.21	0	3838138	0	50	0	49.49	0	3.89	0	0.05	0	1.03	0	0.04	0	373.98	0	0.32	0	37443	0	3947609	0	1151579	0	12997	0	9324	0	0	0	87150	0	19	0	0	0	210	0	28208	0	3257	0	31694	0	68.06	0	2686559	0	16201	29303	1.808715511388	3947609.0	3838138.0	37443.0	1151579.0	12997.0	9324.0	0.0	87150.0	2686559.0	97.2	0.9	29.2	0.3	0.2	0.0	2.2	68.1	50	50	50.00	6	197380450	23.7	25.6	26.1	24.6	0.0	35.4	28.3	smartseq
917558	SRR2132006	SRP061708	SRS1015086	SRX1122509	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834994: s3.39; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834994		GSM1834994	s3.39	205601700	4112034	2016-08-26 15:44:09	84089291	205601700	4112034	1	4112034	index:0,count:4112034,average:50,stdev:0	GSM1834994_r1						0.8	1.66	0.04	198914666	218786309	144715519	173005063	109.99	119.55	0	0	0	0	0	0	65.3	89.82	5472639	2625250	5472639	2625250	53.88	64.43	5472639	2166226	5472639	1883276	14728237	7.40	0.67	0	26.69	0	0.40	0	0.25	0	0.00	0	1.58	0	4020374	0	50	0	49.51	0	3.95	0	0.05	0	1.04	0	0.04	0	400.09	0	0.31	0	27523	0	4112034	0	1097493	0	16307	0	10282	0	0	0	65071	0	68	0	0	0	928	0	123529	0	3355	0	127880	0	71.08	0	2922881	0	40210	132709	3.300397910967	4112034.0	4020374.0	27523.0	1097493.0	16307.0	10282.0	0.0	65071.0	2922881.0	97.8	0.7	26.7	0.4	0.3	0.0	1.6	71.1	50	50	50.00	6	205601700	23.8	25.7	26.1	24.5	0.0	35.4	28.4	smartseq
917565	SRR2132007	SRP061708	SRS1015085	SRX1122510	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834995: s3.40; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834995		GSM1834995	s3.40	166348550	3326971	2016-08-26 15:44:09	68426070	166348550	3326971	1	3326971	index:0,count:3326971,average:50,stdev:0	GSM1834995_r1						2.74	1.03	0.04	160197497	186666193	110708012	144815844	116.52	130.81	0	0	0	0	0	0	57.29	83.01	4404624	1855674	4404624	1855674	35.84	43.92	4404624	1160964	4404624	981878	16362879	10.21	0.84	0	30.17	0	0.33	0	0.30	0	0.00	0	2.00	0	3239196	0	50	0	49.52	0	3.92	0	0.06	0	1.03	0	0.04	0	399.24	0	0.34	0	28084	0	3326971	0	1003623	0	11011	0	10135	0	0	0	66629	0	10	0	0	0	198	0	26016	0	2851	0	29075	0	67.20	0	2235573	0	15600	26984	1.729743589744	3326971.0	3239196.0	28084.0	1003623.0	11011.0	10135.0	0.0	66629.0	2235573.0	97.4	0.8	30.2	0.3	0.3	0.0	2.0	67.2	50	50	50.00	6	166348550	23.7	25.7	26.2	24.4	0.0	35.4	28.3	smartseq
917573	SRR2132008	SRP061708	SRS1015084	SRX1122511	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834996: s3.41; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834996		GSM1834996	s3.41	240760650	4815213	2016-08-26 15:44:09	98027546	240760650	4815213	1	4815213	index:0,count:4815213,average:50,stdev:0	GSM1834996_r1						15.33	1.03	0.07	229263761	240529555	185995529	204516192	104.91	109.96	0	0	0	0	0	0	75.81	93.83	5899838	3521970	5899838	3521970	72.57	80.76	5899838	3371333	5899838	3031318	10924622	4.77	0.95	0	18.53	0	0.54	0	0.15	0	0.00	0	2.83	0	4645769	0	50	0	49.55	0	3.03	0	0.02	0	1.08	0	0.02	0	456.18	0	0.20	0	45787	0	4815213	0	892280	0	26233	0	7139	0	0	0	136072	0	19	0	0	0	229	0	31048	0	2434	0	33730	0	77.95	0	3753489	0	15620	32936	2.108578745198	4815213.0	4645769.0	45787.0	892280.0	26233.0	7139.0	0.0	136072.0	3753489.0	96.5	1.0	18.5	0.5	0.1	0.0	2.8	78.0	50	50	50.00	6	240760650	26.1	23.0	23.3	27.5	0.0	35.4	28.3	smartseq
917581	SRR2132009	SRP061708	SRS1015083	SRX1122512	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834997: s3.42; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834997		GSM1834997	s3.42	141518000	2830360	2016-08-26 15:44:09	60360843	141518000	2830360	1	2830360	index:0,count:2830360,average:50,stdev:0	GSM1834997_r1						1.34	1.76	0.04	136855640	149666315	100158336	118643641	109.36	118.46	0	0	0	0	0	0	65.11	89.05	3768921	1802710	3768921	1802710	54.55	64.69	3768921	1510410	3768921	1309560	10836973	7.92	0.67	0	26.29	0	0.43	0	0.26	0	0.00	0	1.49	0	2768614	0	50	0	49.47	0	3.84	0	0.05	0	1.04	0	0.04	0	407.57	0	0.32	0	19002	0	2830360	0	744179	0	12262	0	7232	0	0	0	42252	0	47	0	0	0	721	0	91807	0	2504	0	95079	0	71.53	0	2024435	0	34667	98720	2.847664926299	2830360.0	2768614.0	19002.0	744179.0	12262.0	7232.0	0.0	42252.0	2024435.0	97.8	0.7	26.3	0.4	0.3	0.0	1.5	71.5	50	50	50.00	6	141518000	24.0	25.5	25.8	24.7	0.0	35.2	27.6	smartseq
917636	SRR2132010	SRP061708	SRS1015076	SRX1122513	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834998: s3.43; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834998		GSM1834998	s3.43	215229800	4304596	2016-08-26 15:44:09	88496533	215229800	4304596	1	4304596	index:0,count:4304596,average:50,stdev:0	GSM1834998_r1						0.72	1.54	0.04	208644843	227702404	152869080	180771999	109.13	118.25	0	0	0	0	0	0	67.49	92.21	5706050	2847332	5706050	2847332	57.2	68.75	5706050	2412897	5706050	2123006	12678233	6.08	0.67	0	26.27	0	0.33	0	0.16	0	0.00	0	1.51	0	4218623	0	50	0	49.51	0	4.02	0	0.05	0	1.03	0	0.04	0	516.55	0	0.29	0	29040	0	4304596	0	1130690	0	14266	0	6848	0	0	0	64859	0	85	0	0	0	1007	0	136063	0	3535	0	140690	0	71.74	0	3087933	0	42064	146610	3.485403195131	4304596.0	4218623.0	29040.0	1130690.0	14266.0	6848.0	0.0	64859.0	3087933.0	98.0	0.7	26.3	0.3	0.2	0.0	1.5	71.7	50	50	50.00	6	215229800	23.9	25.6	25.9	24.7	0.0	35.4	28.2	smartseq
917644	SRR2132011	SRP061708	SRS1015082	SRX1122514	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834999: s3.44; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834999		GSM1834999	s3.44	177785550	3555711	2016-08-26 15:44:09	77065024	177785550	3555711	1	3555711	index:0,count:3555711,average:50,stdev:0	GSM1834999_r1						0.67	1.55	0.04	172301704	188646815	125297376	149168251	109.49	119.05	0	0	0	0	0	0	66.07	90.93	4696482	2302238	4696482	2302238	55.0	66.42	4696482	1916774	4696482	1681559	12070238	7.01	0.71	0	26.80	0	0.30	0	0.16	0	0.00	0	1.54	0	3484739	0	50	0	49.49	0	4.10	0	0.06	0	1.03	0	0.04	0	492.33	0	0.32	0	25152	0	3555711	0	952954	0	10585	0	5634	0	0	0	54753	0	62	0	0	0	720	0	108478	0	2959	0	112219	0	71.20	0	2531785	0	38141	116688	3.059384913872	3555711.0	3484739.0	25152.0	952954.0	10585.0	5634.0	0.0	54753.0	2531785.0	98.0	0.7	26.8	0.3	0.2	0.0	1.5	71.2	50	50	50.00	6	177785550	23.9	25.6	26.0	24.6	0.0	35.0	27.3	smartseq
917652	SRR2132012	SRP061708	SRS1015081	SRX1122515	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1835000: s3.45; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1835000		GSM1835000	s3.45	206414900	4128298	2016-08-26 15:44:09	84673389	206414900	4128298	1	4128298	index:0,count:4128298,average:50,stdev:0	GSM1835000_r1						0.78	1.56	0.04	166513299	183026640	121561301	145078005	109.92	119.35	0	0	0	0	0	0	65.6	89.94	4568592	2208795	4568592	2208795	54.06	64.88	4568592	1820311	4568592	1593341	12262606	7.36	4.00	0	22.08	0	0.29	0	0.19	0	0.00	0	17.95	0	3367261	0	50	0	49.50	0	3.93	0	0.05	0	1.04	0	0.04	0	619.24	0	0.37	0	165159	0	4128298	0	911472	0	12094	0	7978	0	0	0	740965	0	58	0	0	0	662	0	97222	0	2990	0	100932	0	59.49	0	2455789	0	36332	104335	2.871710888473	4128298.0	3367261.0	165159.0	911472.0	12094.0	7978.0	0.0	740965.0	2455789.0	81.6	4.0	22.1	0.3	0.2	0.0	17.9	59.5	50	50	50.00	6	206414900	24.9	24.7	25.0	25.5	0.0	35.4	28.3	smartseq
917661	SRR2132013	SRP061708	SRS1015080	SRX1122516	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1835001: s3.46; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1835001		GSM1835001	s3.46	253375850	5067517	2016-08-26 15:44:09	103533943	253375850	5067517	1	5067517	index:0,count:5067517,average:50,stdev:0	GSM1835001_r1						0.61	1.46	0.03	245405084	268519000	180844334	213907812	109.42	118.28	0	0	0	0	0	0	67.91	92.24	6687892	3369027	6687892	3369027	57.3	68.81	6687892	2842598	6687892	2513221	14679499	5.98	0.65	0	25.83	0	0.33	0	0.16	0	0.00	0	1.61	0	4961208	0	50	0	49.51	0	4.04	0	0.05	0	1.03	0	0.04	0	570.10	0	0.28	0	32837	0	5067517	0	1308773	0	16854	0	7950	0	0	0	81505	0	84	0	0	0	985	0	138136	0	4112	0	143317	0	72.08	0	3652435	0	42890	149397	3.483259501049	5067517.0	4961208.0	32837.0	1308773.0	16854.0	7950.0	0.0	81505.0	3652435.0	97.9	0.6	25.8	0.3	0.2	0.0	1.6	72.1	50	50	50.00	6	253375850	23.8	25.6	25.9	24.7	0.0	35.4	28.4	smartseq
917670	SRR2132014	SRP061708	SRS1015079	SRX1122517	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1835002: s3.47; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1835002		GSM1835002	s3.47	220543450	4410869	2016-08-26 15:44:09	90706840	220543450	4410869	1	4410869	index:0,count:4410869,average:50,stdev:0	GSM1835002_r1						0.74	1.44	0.04	214269877	238215114	153983583	187144789	111.18	121.54	0	0	0	0	0	0	66.35	92.4	5893508	2873084	5893508	2873084	53.75	65.27	5893508	2327528	5893508	2029631	12195094	5.69	0.60	0	27.67	0	0.32	0	0.18	0	0.00	0	1.33	0	4329932	0	50	0	49.52	0	4.11	0	0.06	0	1.03	0	0.04	0	610.74	0	0.30	0	26274	0	4410869	0	1220408	0	14157	0	8027	0	0	0	58753	0	77	0	0	0	853	0	124242	0	3815	0	128987	0	70.50	0	3109524	0	41204	133826	3.247888554509	4410869.0	4329932.0	26274.0	1220408.0	14157.0	8027.0	0.0	58753.0	3109524.0	98.2	0.6	27.7	0.3	0.2	0.0	1.3	70.5	50	50	50.00	6	220543450	23.6	25.9	26.2	24.3	0.0	35.4	28.2	smartseq
917687	SRR2132016	SRP061708	SRS1015077	SRX1122519	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1835004: s3.48; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1835004		GSM1835004	s3.48	215802800	4316056	2016-08-26 15:44:09	88353534	215802800	4316056	1	4316056	index:0,count:4316056,average:50,stdev:0	GSM1835004_r1						1.04	1.7	0.03	208927769	231228530	154939025	185190309	110.67	119.52	0	0	0	0	0	0	66.5	89.75	5700898	2810312	5700898	2810312	54.6	64.31	5700898	2307443	5700898	2013886	15163357	7.26	0.63	0	25.36	0	0.42	0	0.25	0	0.00	0	1.42	0	4225966	0	50	0	49.48	0	3.74	0	0.05	0	1.05	0	0.03	0	535.79	0	0.32	0	27037	0	4316056	0	1094616	0	17994	0	10995	0	0	0	61101	0	124	0	0	0	1067	0	146670	0	3476	0	151337	0	72.55	0	3131350	0	45203	157773	3.490321438843	4316056.0	4225966.0	27037.0	1094616.0	17994.0	10995.0	0.0	61101.0	3131350.0	97.9	0.6	25.4	0.4	0.3	0.0	1.4	72.6	50	50	50.00	6	215802800	23.8	25.6	26.0	24.5	0.0	35.4	28.4	smartseq
928455	SRR3710558	SRP061708	SRS1520878	SRX1870360	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211226: n7.8; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211226		GSM2211226	n7.8	241490700	1609938	2016-08-26 15:44:09	105534457	241490700	1609938	2	1609938	index:0,count:1609938,average:75,stdev:0|index:1,count:1609938,average:75,stdev:0	GSM2211226_r1						1.83	1.82	0.02	221403621	271168106	208779395	259083475	122.48	124.09	1531701	1279690	328.948	1803.950	351	4889	85.76	91.09	1658190	1313626	1658190	1313626	64.91	65.18	1658190	994243	1658190	939897	13495787	6.10	2.83	0	5.57	0	0.16	0	0.09	0	0.00	0	4.61	0	1531701	0	150	0	147.43	0	4.42	0	0.06	0	1.07	0	0.02	0	305.04	0	0.72	0	45620	0	1609938	0	89642	0	2566	0	1393	0	0	0	74278	0	150	0	0	0	1859	0	254066	0	2297	0	258372	0	89.57	0	1442059	0	60884	258602	4.247454175153	1609938.0	1531701.0	45620.0	89642.0	2566.0	1393.0	0.0	74278.0	1442059.0	95.1	2.8	5.6	0.2	0.1	0.0	4.6	89.6	75	75	75.00	6	120745350	24.2	25.4	25.9	24.4	0.0	33.6	25.2	smartseq
928463	SRR3710559	SRP061708	SRS1520879	SRX1870361	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211227: n7.9; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211227		GSM2211227	n7.9	358752600	2391684	2016-08-26 15:44:09	149231547	358752600	2391684	2	2391684	index:0,count:2391684,average:75,stdev:0|index:1,count:2391684,average:75,stdev:0	GSM2211227_r1						1.47	1.54	0.01	318371398	402684661	298746889	383750128	126.48	128.45	2244815	2044400	256.068	1042.790	207	11509	81.16	86.64	2435623	1821795	2435623	1821795	53.26	53.8	2435623	1195500	2435623	1131331	27804195	8.73	3.91	0	5.94	0	0.15	0	0.10	0	0.00	0	5.88	0	2244815	0	150	0	146.87	0	4.24	0	0.06	0	1.21	0	0.02	0	232.70	0	0.58	0	93457	0	2391684	0	142115	0	3686	0	2483	0	0	0	140700	0	185	0	0	0	2004	0	282413	0	2731	0	287333	0	87.92	0	2102700	0	61030	284422	4.660363755530	2391684.0	2244815.0	93457.0	142115.0	3686.0	2483.0	0.0	140700.0	2102700.0	93.9	3.9	5.9	0.2	0.1	0.0	5.9	87.9	75	75	75.00	6	179376300	23.9	25.7	26.4	24.0	0.0	34.0	26.1	smartseq
928519	SRR3710560	SRP061708	SRS1520880	SRX1870362	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211228: n7.10; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211228		GSM2211228	n7.10	279829650	1865531	2016-08-26 15:44:09	121680277	279829650	1865531	2	1865531	index:0,count:1865531,average:75,stdev:0|index:1,count:1865531,average:75,stdev:0	GSM2211228_r1						1.45	1.87	0.02	257630825	314563070	242743148	300093961	122.1	123.63	1779377	1505404	329.735	1739.066	301	5944	83.39	88.65	1924674	1483885	1924674	1483885	63.06	63.44	1924674	1122079	1924674	1061978	21574145	8.37	2.78	0	5.66	0	0.17	0	0.10	0	0.00	0	4.35	0	1779377	0	150	0	147.53	0	4.55	0	0.07	0	1.03	0	0.02	0	305.27	0	0.69	0	51792	0	1865531	0	105512	0	3134	0	1847	0	0	0	81173	0	164	0	0	0	2083	0	277264	0	2690	0	282201	0	89.73	0	1673865	0	63244	282774	4.471159319461	1865531.0	1779377.0	51792.0	105512.0	3134.0	1847.0	0.0	81173.0	1673865.0	95.4	2.8	5.7	0.2	0.1	0.0	4.4	89.7	75	75	75.00	6	139914825	24.3	25.4	25.8	24.6	0.0	33.7	25.4	smartseq
928527	SRR3710561	SRP061708	SRS1520881	SRX1870363	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211229: n7.11; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211229		GSM2211229	n7.11	262567350	1750449	2016-08-26 15:44:09	116944621	262567350	1750449	2	1750449	index:0,count:1750449,average:75,stdev:0|index:1,count:1750449,average:75,stdev:0	GSM2211229_r1						0.95	1.76	0.01	240319223	292076089	226348151	278512470	121.54	123.05	1662044	1366529	352.904	2036.979	351	4957	86.48	92.0	1806734	1437346	1806734	1437346	67.62	68.1	1806734	1123875	1806734	1063959	12824923	5.34	2.79	0	5.69	0	0.21	0	0.07	0	0.00	0	4.77	0	1662044	0	150	0	147.38	0	4.84	0	0.08	0	1.03	0	0.02	0	210.05	0	0.81	0	48843	0	1750449	0	99663	0	3623	0	1275	0	0	0	83507	0	176	0	0	0	1979	0	274059	0	2605	0	278819	0	89.26	0	1562381	0	63123	280313	4.440742676996	1750449.0	1662044.0	48843.0	99663.0	3623.0	1275.0	0.0	83507.0	1562381.0	94.9	2.8	5.7	0.2	0.1	0.0	4.8	89.3	75	75	75.00	6	131283675	23.9	25.8	26.0	24.3	0.0	33.5	24.9	smartseq
928535	SRR3710562	SRP061708	SRS1520882	SRX1870364	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211230: n7.12; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from control side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211230		GSM2211230	n7.12	360218400	2401456	2016-08-26 15:44:09	153349415	360218400	2401456	2	2401456	index:0,count:2401456,average:75,stdev:0|index:1,count:2401456,average:75,stdev:0	GSM2211230_r1						2.21	1.44	0.02	302496605	406491796	287001888	391332948	134.38	136.35	2182949	2051619	267.971	848.834	207	8349	78.63	83.09	2342900	1716471	2342900	1716471	42.74	42.71	2342900	933078	2342900	882157	36203379	11.97	5.50	0	4.88	0	0.17	0	0.15	0	0.00	0	8.78	0	2182949	0	150	0	145.69	0	3.76	0	0.05	0	1.23	0	0.02	0	308.76	0	0.73	0	132151	0	2401456	0	117257	0	4049	0	3547	0	0	0	210911	0	98	0	0	0	1202	0	159877	0	2380	0	163557	0	86.02	0	2065692	0	45592	159411	3.496468678716	2401456.0	2182949.0	132151.0	117257.0	4049.0	3547.0	0.0	210911.0	2065692.0	90.9	5.5	4.9	0.2	0.1	0.0	8.8	86.0	75	75	75.00	6	180109200	24.2	25.4	26.1	24.3	0.0	33.8	25.6	smartseq
928655	SRR3710571	SRP061708	SRS1520891	SRX1870373	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211239: s7.7; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211239		GSM2211239	s7.7	313195800	2087972	2016-08-26 15:44:09	138826590	313195800	2087972	2	2087972	index:0,count:2087972,average:75,stdev:0|index:1,count:2087972,average:75,stdev:0	GSM2211239_r1						3.51	1.58	0.02	264107306	343380249	249010470	328398777	130.02	131.88	1878551	1768728	258.188	783.781	254	9740	77.55	82.38	2022866	1456891	2022866	1456891	44.47	44.57	2022866	835425	2022866	788253	29767117	11.27	5.91	0	5.27	0	0.13	0	0.11	0	0.00	0	9.79	0	1878551	0	150	0	145.39	0	3.52	0	0.04	0	1.56	0	0.02	0	289.10	0	0.76	0	123420	0	2087972	0	110025	0	2809	0	2237	0	0	0	204375	0	77	0	0	0	1059	0	138062	0	1850	0	141048	0	84.70	0	1768526	0	38929	138565	3.559428703537	2087972.0	1878551.0	123420.0	110025.0	2809.0	2237.0	0.0	204375.0	1768526.0	90.0	5.9	5.3	0.1	0.1	0.0	9.8	84.7	75	75	75.00	6	156597900	24.1	25.5	26.3	24.0	0.0	33.3	24.7	smartseq
928662	SRR3710572	SRP061708	SRS1520892	SRX1870374	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211240: s7.8; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211240		GSM2211240	s7.8	432833250	2885555	2016-08-26 15:44:09	184928010	432833250	2885555	2	2885555	index:0,count:2885555,average:75,stdev:0|index:1,count:2885555,average:75,stdev:0	GSM2211240_r1						1.72	1.55	0.02	374212193	487052713	352650339	465905248	130.15	132.12	2632840	2421571	285.935	1024.201	254	11058	79.28	84.27	2846485	2087237	2846485	2087237	47.54	47.7	2846485	1251657	2846485	1181504	38704318	10.34	4.61	0	5.41	0	0.18	0	0.13	0	0.00	0	8.44	0	2632840	0	150	0	146.38	0	4.02	0	0.05	0	1.26	0	0.02	0	230.84	0	0.73	0	133133	0	2885555	0	156142	0	5311	0	3873	0	0	0	243531	0	135	0	0	0	1742	0	239775	0	2989	0	244641	0	85.83	0	2476698	0	54152	242714	4.482087457527	2885555.0	2632840.0	133133.0	156142.0	5311.0	3873.0	0.0	243531.0	2476698.0	91.2	4.6	5.4	0.2	0.1	0.0	8.4	85.8	75	75	75.00	6	216416625	24.2	25.4	26.2	24.3	0.0	33.8	25.5	smartseq
928671	SRR3710573	SRP061708	SRS1520893	SRX1870375	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211241: s7.9; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211241		GSM2211241	s7.9	406744500	2711630	2016-08-26 15:44:09	169796547	406744500	2711630	2	2711630	index:0,count:2711630,average:75,stdev:0|index:1,count:2711630,average:75,stdev:0	GSM2211241_r1						1.78	1.62	0.01	333484225	424801287	308692324	401140690	127.38	129.95	2438938	2205319	259.354	1103.638	207	8699	84.99	92.25	2704092	2072771	2704092	2072771	57.41	58.43	2704092	1400246	2704092	1312838	10103153	3.03	3.80	0	7.08	0	0.21	0	0.06	0	0.00	0	9.79	0	2438938	0	150	0	146.36	0	4.49	0	0.07	0	1.23	0	0.03	0	361.55	0	0.64	0	103058	0	2711630	0	191977	0	5693	0	1597	0	0	0	265402	0	155	0	0	0	2101	0	310112	0	2874	0	315242	0	82.86	0	2246961	0	60030	307036	5.114709312011	2711630.0	2438938.0	103058.0	191977.0	5693.0	1597.0	0.0	265402.0	2246961.0	89.9	3.8	7.1	0.2	0.1	0.0	9.8	82.9	75	75	75.00	6	203372250	23.7	26.1	26.1	24.1	0.0	33.9	25.9	smartseq
928679	SRR3710574	SRP061708	SRS1520894	SRX1870376	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211242: s7.10; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211242		GSM2211242	s7.10	379511250	2530075	2016-08-26 15:44:09	163352466	379511250	2530075	2	2530075	index:0,count:2530075,average:75,stdev:0|index:1,count:2530075,average:75,stdev:0	GSM2211242_r1						2.34	1.72	0.01	337960258	423886895	316163062	402921454	125.43	127.44	2366337	2085337	295.743	1409.475	254	8666	83.49	89.44	2572473	1975645	2572473	1975645	58.51	59.04	2572473	1384609	2572473	1304220	21665064	6.41	3.12	0	6.22	0	0.14	0	0.07	0	0.00	0	6.26	0	2366337	0	150	0	147.21	0	4.52	0	0.07	0	1.17	0	0.03	0	253.01	0	0.69	0	78877	0	2530075	0	157431	0	3556	0	1851	0	0	0	158331	0	239	0	0	0	2248	0	329710	0	3220	0	335417	0	87.31	0	2208906	0	65836	333066	5.059025457197	2530075.0	2366337.0	78877.0	157431.0	3556.0	1851.0	0.0	158331.0	2208906.0	93.5	3.1	6.2	0.1	0.1	0.0	6.3	87.3	75	75	75.00	6	189755625	24.0	25.6	26.0	24.4	0.0	33.7	25.4	smartseq
928687	SRR3710575	SRP061708	SRS1520895	SRX1870377	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211243: s7.11; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211243		GSM2211243	s7.11	420994650	2806631	2016-08-26 15:44:09	173727656	420994650	2806631	2	2806631	index:0,count:2806631,average:75,stdev:0|index:1,count:2806631,average:75,stdev:0	GSM2211243_r1						2.98	1.76	0.02	343961499	430208607	322376236	409940071	125.07	127.16	2530295	2370105	229.011	842.029	207	11550	77.24	82.68	2754821	1954379	2754821	1954379	49.4	49.96	2754821	1249983	2754821	1181038	39684542	11.54	4.12	0	5.93	0	0.14	0	0.13	0	0.00	0	9.58	0	2530295	0	150	0	146.18	0	3.93	0	0.05	0	1.34	0	0.02	0	280.66	0	0.60	0	115520	0	2806631	0	166533	0	3957	0	3588	0	0	0	268791	0	165	0	0	0	1853	0	248621	0	2722	0	253361	0	84.22	0	2363762	0	56425	244487	4.332955250332	2806631.0	2530295.0	115520.0	166533.0	3957.0	3588.0	0.0	268791.0	2363762.0	90.2	4.1	5.9	0.1	0.1	0.0	9.6	84.2	75	75	75.00	6	210497325	24.5	25.2	25.4	24.9	0.0	34.0	26.1	smartseq
928694	SRR3710576	SRP061708	SRS1520897	SRX1870378	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211244: s7.12; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211244		GSM2211244	s7.12	264955500	1766370	2016-08-26 15:44:09	114783123	264955500	1766370	2	1766370	index:0,count:1766370,average:75,stdev:0|index:1,count:1766370,average:75,stdev:0	GSM2211244_r1						2.28	1.58	0.02	231701592	294479674	218993342	282175418	127.09	128.85	1614147	1463331	332.048	1202.083	351	6019	78.27	82.94	1741473	1263453	1741473	1263453	50.24	50.24	1741473	810882	1741473	765239	27177648	11.73	4.68	0	5.14	0	0.19	0	0.14	0	0.00	0	8.28	0	1614147	0	150	0	146.51	0	4.11	0	0.05	0	1.27	0	0.02	0	187.03	0	0.75	0	82656	0	1766370	0	90871	0	3338	0	2554	0	0	0	146331	0	83	0	0	0	1129	0	145694	0	1760	0	148666	0	86.24	0	1523276	0	42692	148595	3.480628689216	1766370.0	1614147.0	82656.0	90871.0	3338.0	2554.0	0.0	146331.0	1523276.0	91.4	4.7	5.1	0.2	0.1	0.0	8.3	86.2	75	75	75.00	6	132477750	24.5	25.1	25.8	24.6	0.0	33.8	25.5	smartseq
928702	SRR3710577	SRP061708	SRS1520896	SRX1870379	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211245: s7.13; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211245		GSM2211245	s7.13	326311200	2175408	2016-08-26 15:44:09	139202940	326311200	2175408	2	2175408	index:0,count:2175408,average:75,stdev:0|index:1,count:2175408,average:75,stdev:0	GSM2211245_r1						2.84	1.39	0.01	271863793	359810612	253853340	342339991	132.35	134.86	1949656	1803115	275.245	970.020	207	7517	84.11	90.33	2133637	1639883	2133637	1639883	50.47	50.79	2133637	984049	2133637	922002	10802010	3.97	5.10	0	6.17	0	0.16	0	0.06	0	0.00	0	10.15	0	1949656	0	150	0	145.84	0	4.04	0	0.05	0	1.39	0	0.02	0	326.31	0	0.76	0	110862	0	2175408	0	134178	0	3577	0	1328	0	0	0	220847	0	84	0	0	0	1251	0	175056	0	1893	0	178284	0	83.45	0	1815478	0	44674	175571	3.930048797959	2175408.0	1949656.0	110862.0	134178.0	3577.0	1328.0	0.0	220847.0	1815478.0	89.6	5.1	6.2	0.2	0.1	0.0	10.2	83.5	75	75	75.00	6	163155600	23.9	25.6	26.4	24.1	0.0	33.7	25.5	smartseq
928710	SRR3710578	SRP061708	SRS1520898	SRX1870380	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211246: s7.14; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211246		GSM2211246	s7.14	409071000	2727140	2016-08-26 15:44:09	172788806	409071000	2727140	2	2727140	index:0,count:2727140,average:75,stdev:0|index:1,count:2727140,average:75,stdev:0	GSM2211246_r1						1.14	1.51	0.02	365519998	458949689	340882617	434779334	125.56	127.55	2555652	2285293	283.616	1203.709	254	11008	81.68	87.77	2796561	2087492	2796561	2087492	55.6	56.2	2796561	1420875	2796561	1336781	26723082	7.31	3.42	0	6.50	0	0.21	0	0.11	0	0.00	0	5.97	0	2555652	0	150	0	147.11	0	4.72	0	0.08	0	1.21	0	0.03	0	265.34	0	0.65	0	93338	0	2727140	0	177193	0	5631	0	3028	0	0	0	162829	0	215	0	0	0	2236	0	325862	0	3648	0	331961	0	87.21	0	2378459	0	64084	330760	5.161350727171	2727140.0	2555652.0	93338.0	177193.0	5631.0	3028.0	0.0	162829.0	2378459.0	93.7	3.4	6.5	0.2	0.1	0.0	6.0	87.2	75	75	75.00	6	204535500	23.5	26.1	26.5	23.8	0.0	33.9	25.9	smartseq
928718	SRR3710579	SRP061708	SRS1520899	SRX1870381	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211247: s7.15; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211247		GSM2211247	s7.15	362996250	2419975	2016-08-26 15:44:09	156224426	362996250	2419975	2	2419975	index:0,count:2419975,average:75,stdev:0|index:1,count:2419975,average:75,stdev:0	GSM2211247_r1						2.55	1.57	0.01	320881726	406136045	301967164	387857711	126.57	128.44	2242339	1975584	309.508	1412.893	301	7747	82.8	88.16	2421878	1856561	2421878	1856561	56.72	57.11	2421878	1271966	2421878	1202745	24729195	7.71	3.48	0	5.64	0	0.16	0	0.08	0	0.00	0	7.09	0	2242339	0	150	0	147.03	0	4.48	0	0.07	0	1.17	0	0.02	0	256.23	0	0.73	0	84184	0	2419975	0	136458	0	3934	0	2039	0	0	0	171663	0	163	0	0	0	2102	0	283244	0	3176	0	288685	0	87.02	0	2105881	0	59757	286710	4.797931623073	2419975.0	2242339.0	84184.0	136458.0	3934.0	2039.0	0.0	171663.0	2105881.0	92.7	3.5	5.6	0.2	0.1	0.0	7.1	87.0	75	75	75.00	6	181498125	23.9	25.7	26.1	24.3	0.0	33.7	25.4	smartseq
928775	SRR3710580	SRP061708	SRS1520900	SRX1870382	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211248: s7.16; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;female|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211248		GSM2211248	s7.16	498616800	3324112	2016-08-26 15:44:09	206137067	498616800	3324112	2	3324112	index:0,count:3324112,average:75,stdev:0|index:1,count:3324112,average:75,stdev:0	GSM2211248_r1						2.46	1.67	0.03	405541828	512791068	379204204	487814273	126.45	128.64	2970591	2765001	243.235	893.973	207	12650	77.01	82.65	3255293	2287532	3255293	2287532	48.56	48.86	3255293	1442373	3255293	1352368	46702078	11.52	4.32	0	6.10	0	0.18	0	0.15	0	0.00	0	10.30	0	2970591	0	150	0	146.01	0	4.04	0	0.05	0	1.35	0	0.02	0	184.10	0	0.62	0	143501	0	3324112	0	202900	0	6046	0	5048	0	0	0	342427	0	180	0	0	0	1974	0	286002	0	3239	0	291395	0	83.26	0	2767691	0	60987	282672	4.634954990408	3324112.0	2970591.0	143501.0	202900.0	6046.0	5048.0	0.0	342427.0	2767691.0	89.4	4.3	6.1	0.2	0.2	0.0	10.3	83.3	75	75	75.00	6	249308400	24.2	25.5	25.7	24.6	0.0	34.0	26.0	smartseq
928782	SRR3710581	SRP061708	SRS1520901	SRX1870383	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211249: s7.17; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211249		GSM2211249	s7.17	310833000	2072220	2016-08-26 15:44:09	131615014	310833000	2072220	2	2072220	index:0,count:2072220,average:75,stdev:0|index:1,count:2072220,average:75,stdev:0	GSM2211249_r1						2.29	1.87	0.02	261048611	323758574	244148595	307778082	124.02	126.06	1910065	1798449	218.486	730.015	207	9748	76.99	82.56	2081735	1470482	2081735	1470482	50.88	51.47	2081735	971886	2081735	916675	32458517	12.43	3.56	0	6.22	0	0.13	0	0.12	0	0.00	0	7.58	0	1910065	0	150	0	146.71	0	3.80	0	0.04	0	1.14	0	0.02	0	310.83	0	0.59	0	73873	0	2072220	0	128942	0	2591	0	2555	0	0	0	157009	0	162	0	0	0	1376	0	193661	0	1913	0	197112	0	85.95	0	1781123	0	50713	190979	3.765878571569	2072220.0	1910065.0	73873.0	128942.0	2591.0	2555.0	0.0	157009.0	1781123.0	92.2	3.6	6.2	0.1	0.1	0.0	7.6	86.0	75	75	75.00	6	155416500	24.9	24.7	25.1	25.3	0.0	33.8	25.5	smartseq
928790	SRR3710582	SRP061708	SRS1520902	SRX1870384	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211250: s7.18; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211250		GSM2211250	s7.18	256174950	1707833	2016-08-26 15:44:09	110205968	256174950	1707833	2	1707833	index:0,count:1707833,average:75,stdev:0|index:1,count:1707833,average:75,stdev:0	GSM2211250_r1						2.37	1.55	0.02	207525390	265813665	195393110	254246325	128.09	130.12	1525664	1455977	231.000	683.841	207	6988	75.08	80.0	1653105	1145489	1653105	1145489	44.48	44.79	1653105	678636	1653105	641351	29751888	14.34	4.42	0	5.49	0	0.15	0	0.13	0	0.00	0	10.39	0	1525664	0	150	0	145.90	0	3.56	0	0.04	0	1.22	0	0.02	0	267.31	0	0.69	0	75417	0	1707833	0	93799	0	2502	0	2177	0	0	0	177490	0	69	0	0	0	729	0	105487	0	1417	0	107702	0	83.84	0	1431865	0	36020	103352	2.869294836202	1707833.0	1525664.0	75417.0	93799.0	2502.0	2177.0	0.0	177490.0	1431865.0	89.3	4.4	5.5	0.1	0.1	0.0	10.4	83.8	75	75	75.00	6	128087475	24.8	24.7	25.2	25.2	0.0	33.6	25.1	smartseq
928807	SRR3710584	SRP061708	SRS1520904	SRX1870386	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211252: s7.20; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211252		GSM2211252	s7.20	209068500	1393790	2016-08-26 15:44:09	89024542	209068500	1393790	2	1393790	index:0,count:1393790,average:75,stdev:0|index:1,count:1393790,average:75,stdev:0	GSM2211252_r1						1.62	1.33	0.02	173627439	231371296	165364663	223139413	133.26	134.94	1256483	1213389	238.137	597.664	207	6806	73.39	77.23	1342787	922112	1342787	922112	36.42	36.48	1342787	457551	1342787	435616	29191653	16.81	5.87	0	4.49	0	0.15	0	0.15	0	0.00	0	9.55	0	1256483	0	150	0	145.25	0	3.28	0	0.03	0	1.44	0	0.02	0	192.99	0	0.69	0	81805	0	1393790	0	62523	0	2096	0	2121	0	0	0	133090	0	26	0	0	0	440	0	61841	0	1147	0	63454	0	85.66	0	1193960	0	25424	61143	2.404932347388	1393790.0	1256483.0	81805.0	62523.0	2096.0	2121.0	0.0	133090.0	1193960.0	90.1	5.9	4.5	0.2	0.2	0.0	9.5	85.7	75	75	75.00	6	104534250	24.5	24.8	25.9	24.9	0.0	33.7	25.5	smartseq
928815	SRR3710585	SRP061708	SRS1520905	SRX1870387	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211253: s7.21; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211253		GSM2211253	s7.21	241261050	1608407	2016-08-26 15:44:09	102984954	241261050	1608407	2	1608407	index:0,count:1608407,average:75,stdev:0|index:1,count:1608407,average:75,stdev:0	GSM2211253_r1						2.82	1.57	0.03	188867656	245596257	178677930	235887634	130.04	132.02	1412548	1366485	213.265	551.443	207	7174	72.19	76.57	1525718	1019658	1525718	1019658	39.32	39.27	1525718	555353	1525718	522939	33298466	17.63	5.00	0	5.03	0	0.16	0	0.14	0	0.00	0	11.88	0	1412548	0	150	0	145.27	0	3.19	0	0.03	0	1.36	0	0.01	0	175.46	0	0.68	0	80423	0	1608407	0	80919	0	2519	0	2230	0	0	0	191110	0	54	0	0	0	587	0	77023	0	1224	0	78888	0	82.79	0	1331629	0	29670	74883	2.523862487361	1608407.0	1412548.0	80423.0	80919.0	2519.0	2230.0	0.0	191110.0	1331629.0	87.8	5.0	5.0	0.2	0.1	0.0	11.9	82.8	75	75	75.00	6	120630525	24.8	24.6	25.1	25.4	0.0	33.6	25.2	smartseq
928951	SRR3710596	SRP061708	SRS1520916	SRX1870398	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211264: s7.32; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211264		GSM2211264	s7.32	289795500	1931970	2016-08-26 15:44:09	125608357	289795500	1931970	2	1931970	index:0,count:1931970,average:75,stdev:0|index:1,count:1931970,average:75,stdev:0	GSM2211264_r1						1.52	1.56	0.03	260821211	335069431	245802400	320381034	128.47	130.34	1818937	1657821	300.823	1071.949	308	7148	78.26	83.18	1968273	1423572	1968273	1423572	49.6	49.57	1968273	902136	1968273	848394	32942860	12.63	4.02	0	5.57	0	0.16	0	0.16	0	0.00	0	5.53	0	1818937	0	150	0	146.88	0	4.14	0	0.06	0	1.07	0	0.02	0	257.60	0	0.70	0	77580	0	1931970	0	107517	0	3161	0	3062	0	0	0	106810	0	84	0	0	0	1285	0	174294	0	2172	0	177835	0	88.58	0	1711420	0	47167	177269	3.758326796277	1931970.0	1818937.0	77580.0	107517.0	3161.0	3062.0	0.0	106810.0	1711420.0	94.1	4.0	5.6	0.2	0.2	0.0	5.5	88.6	75	75	75.00	6	144897750	24.4	25.1	25.9	24.6	0.0	33.7	25.3	smartseq
928959	SRR3710597	SRP061708	SRS1520917	SRX1870399	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM2211265: s7.33; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			The experiment was performed on two month old adult C57BL/6 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 and 7 days of the surgery, animals were euthanased by CO2  and decapitated, L3-L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol(Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. These libraries were sequenced 75bp pair ended on illumina Next-seq500 pipeline.	NextSeq 500	gender;;male|source_name;;single DRG from SNT side|strain;;C57BL/6|tissue;;dorsal root ganglion	GEO Accession;;GSM2211265		GSM2211265	s7.33	277184700	1847898	2016-08-26 15:44:09	119649431	277184700	1847898	2	1847898	index:0,count:1847898,average:75,stdev:0|index:1,count:1847898,average:75,stdev:0	GSM2211265_r1						2.37	1.51	0.01	251339759	319014336	236239574	304203762	126.93	128.77	1743458	1533489	317.512	1399.610	301	6348	84.67	90.25	1881803	1476213	1881803	1476213	58.93	59.41	1881803	1027356	1881803	971812	14958022	5.95	3.52	0	5.83	0	0.18	0	0.07	0	0.00	0	5.40	0	1743458	0	150	0	147.21	0	4.66	0	0.08	0	1.08	0	0.03	0	302.38	0	0.69	0	65053	0	1847898	0	107704	0	3337	0	1329	0	0	0	99774	0	132	0	0	0	1720	0	220276	0	2744	0	224872	0	88.52	0	1635754	0	53116	223324	4.204458167031	1847898.0	1743458.0	65053.0	107704.0	3337.0	1329.0	0.0	99774.0	1635754.0	94.3	3.5	5.8	0.2	0.1	0.0	5.4	88.5	75	75	75.00	6	138592350	23.8	25.8	26.3	24.1	0.0	33.8	25.5	smartseq
936527	SRR2131949	SRP061708	SRS1015142	SRX1122452	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834937: n3.5; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834937		GSM1834937	n3.5	155821575	3055325	2016-08-26 15:44:09	115932950	155821575	3055325	1	3055325	index:0,count:3055325,average:51,stdev:0	GSM1834937_r1						0.97	1.72	0.03	149813737	171986299	112820105	140009935	114.8	124.1	0	0	0	0	0	0	65.09	86.54	3962155	1933869	3962155	1933869	46.62	54.43	3962155	1385055	3962155	1216313	10793341	7.20	0.89	0	24.11	0	0.34	0	0.20	0	0.00	0	2.21	0	2971160	0	51	0	50.49	0	2.98	0	0.03	0	1.06	0	0.02	0	407.38	0	0.42	0	27285	0	3055325	0	736493	0	10410	0	6218	0	0	0	67537	0	50	0	0	0	533	0	77802	0	1777	0	80162	0	73.14	0	2234667	0	29027	82966	2.858235435973	3055325.0	2971160.0	27285.0	736493.0	10410.0	6218.0	0.0	67537.0	2234667.0	97.2	0.9	24.1	0.3	0.2	0.0	2.2	73.1	51	51	51.00	38	155821575	23.9	25.8	26.2	24.2	0.0	36.1	25.2	smartseq
936639	SRR2131957	SRP061708	SRS1015134	SRX1122460	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834945: n3.13; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834945		GSM1834945	n3.13	123725286	2425986	2016-08-26 15:44:09	93020747	123725286	2425986	1	2425986	index:0,count:2425986,average:51,stdev:0	GSM1834945_r1						0.38	1.56	0.02	120192370	130975447	86997256	103016956	108.97	118.41	0	0	0	0	0	0	63.54	87.8	3207110	1512203	3207110	1512203	51.69	62.51	3207110	1230288	3207110	1076650	9619526	8.00	0.63	0	27.10	0	0.27	0	0.19	0	0.00	0	1.44	0	2379930	0	51	0	50.51	0	3.68	0	0.04	0	1.04	0	0.04	0	459.66	0	0.42	0	15302	0	2425986	0	657511	0	6594	0	4642	0	0	0	34820	0	50	0	0	0	597	0	82862	0	1514	0	85023	0	71.00	0	1722419	0	32279	87764	2.718919421296	2425986.0	2379930.0	15302.0	657511.0	6594.0	4642.0	0.0	34820.0	1722419.0	98.1	0.6	27.1	0.3	0.2	0.0	1.4	71.0	51	51	51.00	38	123725286	23.8	25.9	26.2	24.1	0.0	36.0	25.0	smartseq
936655	SRR2131959	SRP061708	SRS1015132	SRX1122462	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834947: n3.14; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834947		GSM1834947	n3.14	52873587	1036737	2016-08-26 15:44:09	41494638	52873587	1036737	1	1036737	index:0,count:1036737,average:51,stdev:0	GSM1834947_r1						0.97	1.79	0.03	51197909	58151006	38404087	46555571	113.58	121.23	0	0	0	0	0	0	68.54	91.43	1357202	695319	1357202	695319	54.37	63.21	1357202	551534	1357202	480692	2309791	4.51	0.66	0	24.50	0	0.37	0	0.16	0	0.00	0	1.62	0	1014494	0	51	0	50.50	0	3.29	0	0.03	0	1.06	0	0.03	0	287.10	0	0.49	0	6811	0	1036737	0	253996	0	3790	0	1684	0	0	0	16769	0	27	0	0	0	334	0	42301	0	602	0	43264	0	73.35	0	760498	0	21114	44813	2.122430614758	1036737.0	1014494.0	6811.0	253996.0	3790.0	1684.0	0.0	16769.0	760498.0	97.9	0.7	24.5	0.4	0.2	0.0	1.6	73.4	51	51	51.00	38	52873587	24.3	25.2	26.8	23.7	0.0	35.3	23.8	smartseq
936711	SRR2131960	SRP061708	SRS1015131	SRX1122463	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834948: n3.15; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG intact single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834948		GSM1834948	n3.15	91607016	1796216	2016-08-26 15:44:09	70161626	91607016	1796216	1	1796216	index:0,count:1796216,average:51,stdev:0	GSM1834948_r1						0.78	1.6	0.03	88896912	98304417	64392349	77263086	110.58	119.99	0	0	0	0	0	0	63.83	88.16	2374253	1124044	2374253	1124044	50.9	61.06	2374253	896337	2374253	778545	6587952	7.41	0.67	0	27.05	0	0.31	0	0.17	0	0.00	0	1.48	0	1760922	0	51	0	50.50	0	3.58	0	0.04	0	1.04	0	0.04	0	497.41	0	0.44	0	12057	0	1796216	0	485900	0	5575	0	3075	0	0	0	26644	0	40	0	0	0	440	0	60321	0	1110	0	61911	0	70.98	0	1275022	0	27654	63566	2.298618644681	1796216.0	1760922.0	12057.0	485900.0	5575.0	3075.0	0.0	26644.0	1275022.0	98.0	0.7	27.1	0.3	0.2	0.0	1.5	71.0	51	51	51.00	38	91607016	24.0	25.6	26.2	24.2	0.0	35.7	24.4	smartseq
937015	SRR2131986	SRP061708	SRS1015106	SRX1122489	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834974: s3.19; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834974		GSM1834974	s3.19	178858020	3507020	2016-08-26 15:44:09	130167213	178858020	3507020	1	3507020	index:0,count:3507020,average:51,stdev:0	GSM1834974_r1						0.76	1.57	0.03	173527226	192822895	125824666	151750719	111.12	120.6	0	0	0	0	0	0	64.7	89.25	4720874	2223629	4720874	2223629	52.0	61.84	4720874	1787325	4720874	1540764	11809995	6.81	0.63	0	26.96	0	0.36	0	0.25	0	0.00	0	1.39	0	3436984	0	51	0	50.50	0	3.53	0	0.04	0	1.04	0	0.03	0	350.70	0	0.39	0	22068	0	3507020	0	945399	0	12696	0	8639	0	0	0	48701	0	67	0	0	0	887	0	125868	0	2391	0	129213	0	71.05	0	2491585	0	41096	135291	3.292072221141	3507020.0	3436984.0	22068.0	945399.0	12696.0	8639.0	0.0	48701.0	2491585.0	98.0	0.6	27.0	0.4	0.2	0.0	1.4	71.0	51	51	51.00	38	178858020	23.7	26.0	26.2	24.1	0.0	36.4	25.9	smartseq
937030	SRR2131988	SRP061708	SRS1015104	SRX1122491	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834976: s3.21; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834976		GSM1834976	s3.21	215752083	4230433	2016-08-26 15:44:09	156514766	215752083	4230433	1	4230433	index:0,count:4230433,average:51,stdev:0	GSM1834976_r1						0.67	1.67	0.04	207021837	224178056	151149953	177018048	108.29	117.11	0	0	0	0	0	0	62.74	85.96	5606900	2574485	5606900	2574485	52.62	62.29	5606900	2159250	5606900	1865484	19936123	9.63	0.85	0	26.20	0	0.35	0	0.29	0	0.00	0	2.37	0	4103268	0	51	0	50.47	0	3.63	0	0.04	0	1.05	0	0.04	0	725.22	0	0.39	0	35755	0	4230433	0	1108210	0	14799	0	12248	0	0	0	100118	0	88	0	0	0	937	0	140305	0	2679	0	144009	0	70.80	0	2995058	0	45684	150604	3.296646528325	4230433.0	4103268.0	35755.0	1108210.0	14799.0	12248.0	0.0	100118.0	2995058.0	97.0	0.8	26.2	0.3	0.3	0.0	2.4	70.8	51	51	51.00	38	215752083	23.8	25.8	26.0	24.3	0.0	36.5	25.9	smartseq
937039	SRR2131989	SRP061708	SRS1015103	SRX1122492	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834977: s3.22; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834977		GSM1834977	s3.22	150656805	2954055	2016-08-26 15:44:09	114191050	150656805	2954055	1	2954055	index:0,count:2954055,average:51,stdev:0	GSM1834977_r1						0.61	1.65	0.05	145359219	160713145	106261094	127259291	110.56	119.76	0	0	0	0	0	0	63.19	86.49	3934217	1820407	3934217	1820407	50.95	60.11	3934217	1467828	3934217	1265211	13282001	9.14	0.72	0	26.27	0	0.39	0	0.34	0	0.00	0	1.75	0	2880904	0	51	0	50.48	0	3.50	0	0.04	0	1.05	0	0.03	0	322.26	0	0.43	0	21212	0	2954055	0	776029	0	11548	0	9948	0	0	0	51655	0	62	0	0	0	663	0	93055	0	1602	0	95382	0	71.25	0	2104875	0	34296	100205	2.921769302543	2954055.0	2880904.0	21212.0	776029.0	11548.0	9948.0	0.0	51655.0	2104875.0	97.5	0.7	26.3	0.4	0.3	0.0	1.7	71.3	51	51	51.00	38	150656805	24.0	25.6	26.0	24.3	0.0	35.8	24.7	smartseq
937095	SRR2131990	SRP061708	SRS1015102	SRX1122493	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834978: s3.23; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834978		GSM1834978	s3.23	213721620	4190620	2016-08-26 15:44:09	155872674	213721620	4190620	1	4190620	index:0,count:4190620,average:51,stdev:0	GSM1834978_r1						0.77	1.48	0.02	207318018	230212272	152032057	183187964	111.04	120.49	0	0	0	0	0	0	65.41	89.21	5504742	2686494	5504742	2686494	51.87	61.97	5504742	2130535	5504742	1866176	14341078	6.92	0.64	0	26.15	0	0.27	0	0.19	0	0.00	0	1.53	0	4107213	0	51	0	50.49	0	3.73	0	0.04	0	1.04	0	0.04	0	502.87	0	0.39	0	26813	0	4190620	0	1095873	0	11243	0	8040	0	0	0	64124	0	90	0	0	0	1073	0	144373	0	2624	0	148160	0	71.86	0	3011340	0	44249	153774	3.475197179597	4190620.0	4107213.0	26813.0	1095873.0	11243.0	8040.0	0.0	64124.0	3011340.0	98.0	0.6	26.2	0.3	0.2	0.0	1.5	71.9	51	51	51.00	38	213721620	23.7	26.0	26.3	24.0	0.0	36.4	25.7	smartseq
937103	SRR2131991	SRP061708	SRS1015101	SRX1122494	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834979: s3.24; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834979		GSM1834979	s3.24	201103659	3943209	2016-08-26 15:44:09	146607737	201103659	3943209	1	3943209	index:0,count:3943209,average:51,stdev:0	GSM1834979_r1						0.26	1.38	0.03	194843083	216341534	136006796	166631313	111.03	122.52	0	0	0	0	0	0	64.8	92.84	5344411	2501600	5344411	2501600	51.23	63.31	5344411	1977775	5344411	1705918	8693721	4.46	0.72	0	29.58	0	0.27	0	0.10	0	0.00	0	1.72	0	3860665	0	51	0	50.48	0	4.03	0	0.05	0	1.02	0	0.04	0	473.19	0	0.38	0	28503	0	3943209	0	1166259	0	10773	0	3933	0	0	0	67838	0	71	0	0	0	801	0	117066	0	2438	0	120376	0	68.33	0	2694406	0	38201	125819	3.293604879453	3943209.0	3860665.0	28503.0	1166259.0	10773.0	3933.0	0.0	67838.0	2694406.0	97.9	0.7	29.6	0.3	0.1	0.0	1.7	68.3	51	51	51.00	38	201103659	23.3	26.4	26.5	23.8	0.0	36.4	25.5	smartseq
937111	SRR2131992	SRP061708	SRS1015100	SRX1122495	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834980: s3.25; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834980		GSM1834980	s3.25	151730712	2975112	2016-08-26 15:44:09	111988979	151730712	2975112	1	2975112	index:0,count:2975112,average:51,stdev:0	GSM1834980_r1						0.58	1.46	0.04	146431279	162110755	103241314	125535933	110.71	121.59	0	0	0	0	0	0	63.62	90.29	4028091	1846679	4028091	1846679	50.69	61.66	4028091	1471308	4028091	1261090	9080656	6.20	0.82	0	28.81	0	0.33	0	0.19	0	0.00	0	1.92	0	2902549	0	51	0	50.48	0	3.69	0	0.04	0	1.04	0	0.04	0	396.68	0	0.40	0	24255	0	2975112	0	857262	0	9789	0	5682	0	0	0	57092	0	41	0	0	0	646	0	91243	0	1792	0	93722	0	68.75	0	2045287	0	33423	97750	2.924632737935	2975112.0	2902549.0	24255.0	857262.0	9789.0	5682.0	0.0	57092.0	2045287.0	97.6	0.8	28.8	0.3	0.2	0.0	1.9	68.7	51	51	51.00	38	151730712	23.8	25.9	26.0	24.3	0.0	36.2	25.3	smartseq
937118	SRR2131993	SRP061708	SRS1015099	SRX1122496	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834981: s3.26; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834981		GSM1834981	s3.26	218859513	4291363	2016-08-26 15:44:09	159128548	218859513	4291363	1	4291363	index:0,count:4291363,average:51,stdev:0	GSM1834981_r1						0.54	1.56	0.06	211893777	233383092	152247200	183062876	110.14	120.24	0	0	0	0	0	0	63.63	88.59	5739147	2670350	5739147	2670350	51.22	61.63	5739147	2149530	5739147	1857718	15975564	7.54	0.70	0	27.56	0	0.31	0	0.23	0	0.00	0	1.65	0	4196895	0	51	0	50.51	0	3.64	0	0.04	0	1.05	0	0.04	0	406.55	0	0.39	0	30153	0	4291363	0	1182606	0	13489	0	10037	0	0	0	70942	0	68	0	0	0	1034	0	138819	0	2519	0	142440	0	70.24	0	3014289	0	42561	149011	3.501116045206	4291363.0	4196895.0	30153.0	1182606.0	13489.0	10037.0	0.0	70942.0	3014289.0	97.8	0.7	27.6	0.3	0.2	0.0	1.7	70.2	51	51	51.00	38	218859513	23.9	25.8	26.0	24.3	0.0	36.4	25.7	smartseq
937126	SRR2131994	SRP061708	SRS1015098	SRX1122497	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834982: s3.27; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834982		GSM1834982	s3.27	184193028	3611628	2016-08-26 15:44:09	134041567	184193028	3611628	1	3611628	index:0,count:3611628,average:51,stdev:0	GSM1834982_r1						0.46	1.57	0.03	178348548	197607875	129338625	155557619	110.8	120.27	0	0	0	0	0	0	65.63	90.52	4869399	2319843	4869399	2319843	53.67	63.73	4869399	1897181	4869399	1633169	11060549	6.20	0.63	0	26.91	0	0.39	0	0.24	0	0.00	0	1.49	0	3534853	0	51	0	50.47	0	3.60	0	0.04	0	1.05	0	0.03	0	419.41	0	0.39	0	22915	0	3611628	0	972016	0	14078	0	8707	0	0	0	53990	0	101	0	0	0	1032	0	139462	0	2429	0	143024	0	70.96	0	2562837	0	40635	151212	3.721225544481	3611628.0	3534853.0	22915.0	972016.0	14078.0	8707.0	0.0	53990.0	2562837.0	97.9	0.6	26.9	0.4	0.2	0.0	1.5	71.0	51	51	51.00	38	184193028	23.7	26.0	26.2	24.1	0.0	36.4	25.8	smartseq
937134	SRR2131995	SRP061708	SRS1015097	SRX1122498	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834983: s3.28; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834983		GSM1834983	s3.28	153772956	3015156	2016-08-26 15:44:09	112346744	153772956	3015156	1	3015156	index:0,count:3015156,average:51,stdev:0	GSM1834983_r1						1.53	1.88	0.04	146576098	166062175	109592435	134352328	113.29	122.59	0	0	0	0	0	0	63.18	84.62	3963978	1839705	3963978	1839705	46.63	53.51	3963978	1357690	3963978	1163480	12611596	8.60	1.02	0	24.46	0	0.56	0	0.39	0	0.00	0	2.48	0	2911770	0	51	0	50.41	0	3.07	0	0.03	0	1.07	0	0.02	0	387.66	0	0.43	0	30711	0	3015156	0	737634	0	16793	0	11900	0	0	0	74693	0	33	0	0	0	663	0	84963	0	1808	0	87467	0	72.11	0	2174136	0	30252	91539	3.025882586275	3015156.0	2911770.0	30711.0	737634.0	16793.0	11900.0	0.0	74693.0	2174136.0	96.6	1.0	24.5	0.6	0.4	0.0	2.5	72.1	51	51	51.00	38	153772956	23.7	25.9	26.3	24.1	0.0	36.4	25.6	smartseq
937141	SRR2131996	SRP061708	SRS1015096	SRX1122499	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834984: s3.29; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834984		GSM1834984	s3.29	98124867	1924017	2016-08-26 15:44:09	76060234	98124867	1924017	1	1924017	index:0,count:1924017,average:51,stdev:0	GSM1834984_r1						1.17	1.79	0.04	93758880	108274294	70812273	87797247	115.48	123.99	0	0	0	0	0	0	63.17	83.8	2495997	1175804	2495997	1175804	44.49	51.38	2495997	828016	2495997	720906	8534886	9.10	1.03	0	23.81	0	0.50	0	0.31	0	0.00	0	2.45	0	1861196	0	51	0	50.47	0	2.81	0	0.03	0	1.09	0	0.02	0	407.44	0	0.48	0	19873	0	1924017	0	458169	0	9644	0	6021	0	0	0	47156	0	35	0	0	0	364	0	47074	0	973	0	48446	0	72.92	0	1403027	0	21400	50098	2.341028037383	1924017.0	1861196.0	19873.0	458169.0	9644.0	6021.0	0.0	47156.0	1403027.0	96.7	1.0	23.8	0.5	0.3	0.0	2.5	72.9	51	51	51.00	38	98124867	24.3	25.1	26.2	24.3	0.0	35.5	24.2	smartseq
937149	SRR2131997	SRP061708	SRS1015095	SRX1122500	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834985: s3.30; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834985		GSM1834985	s3.30	138777100	2775542	2016-08-26 15:44:09	56870371	138777100	2775542	1	2775542	index:0,count:2775542,average:50,stdev:0	GSM1834985_r1						6.67	1.17	0.07	132055908	145799119	98718662	118127978	110.41	119.66	0	0	0	0	0	0	67.21	90.23	3567798	1801729	3567798	1801729	55.07	65.41	3567798	1476282	3567798	1306055	9073745	6.87	1.12	0	24.65	0	0.55	0	0.17	0	0.00	0	2.70	0	2680845	0	50	0	49.44	0	3.69	0	0.04	0	1.04	0	0.03	0	525.89	0	0.27	0	31189	0	2775542	0	684103	0	15149	0	4592	0	0	0	74956	0	20	0	0	0	230	0	29794	0	2276	0	32320	0	71.94	0	1996742	0	15974	31175	1.951608864405	2775542.0	2680845.0	31189.0	684103.0	15149.0	4592.0	0.0	74956.0	1996742.0	96.6	1.1	24.6	0.5	0.2	0.0	2.7	71.9	50	50	50.00	6	138777100	24.5	24.5	24.9	26.0	0.0	35.4	28.3	smartseq
937158	SRR2131998	SRP061708	SRS1015094	SRX1122501	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834986: s3.31; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834986		GSM1834986	s3.31	157693850	3153877	2016-08-26 15:44:09	64614726	157693850	3153877	1	3153877	index:0,count:3153877,average:50,stdev:0	GSM1834986_r1						0.94	1.92	0.04	152922990	165004778	113879448	132224458	107.9	116.11	0	0	0	0	0	0	67.81	91.13	4144280	2096792	4144280	2096792	58.99	69.72	4144280	1823903	4144280	1604154	10309866	6.74	0.66	0	25.08	0	0.36	0	0.17	0	0.00	0	1.42	0	3091974	0	50	0	49.49	0	3.88	0	0.05	0	1.05	0	0.03	0	315.39	0	0.30	0	20923	0	3153877	0	790975	0	11482	0	5482	0	0	0	44939	0	96	0	0	0	888	0	122276	0	2517	0	125777	0	72.96	0	2300999	0	41007	131311	3.202160606726	3153877.0	3091974.0	20923.0	790975.0	11482.0	5482.0	0.0	44939.0	2300999.0	98.0	0.7	25.1	0.4	0.2	0.0	1.4	73.0	50	50	50.00	6	157693850	24.0	25.5	25.8	24.7	0.0	35.4	28.4	smartseq
937165	SRR2131999	SRP061708	SRS1015093	SRX1122502	SRA280498	GEO		Single cell RNA-seq analysis of sensory neurons reveal diverse injury responses after sciatic nerve transection	We  reported the gene expression analysis of different types of sensory neuron with peripheral nerve transection treatment on single cell level. We found substantial variation between myelinated large diameter neurons and small diameter nonpeptidergic nociceptors, in both terms of regeneration response genes regulation as well as fraction of cells respond to nerve injury. Overall design: Two month old adult CAST/Eij ? cross C57BL/6?F1 and C57BL/6 mice were performed sciatic nerve transection on the right side. Single DRG soma from L3-5 on both side were manually picked in the lowest possible volume and then performed single cell RNA-seq using smart-seq2 protocol.  A total of 106 dissociated DRG neurons for each side with almost equal number of small, medium and large diameter neurons were lysed and split into three parts in order to constructed bulk cell control.		GSM1834987: s3.32; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			The experiment was performed on two month old adult CAST/Eij ♂ cross C57BL/6♀F1 mice. All surgical procedures were performed under general anesthesia with intraperitoneal injections using a mixture of ketamine（100mg/kg) and xylazine（10mg/kg). For the sciatic nerve transection (axotomy), the right side sciatic nerve was exposed at the mid thigh level and sectioned distally. The wound was sutured in two layers, and the animals were allowed to recover. After 3 days of the surgery, animals were euthanased by CO2  and decapitated, L5 DRG from both ipsilateral and contralateral side were dissected and dissociated into single cell. Single DRG soma was manually picked in the lowest possible volume (preferably ≤0.5μl, possibly 0.3μl) using a micro capillary pipette into a 0.2-ml thin-walled PCR tube contains 4μl smart-seq2 lysis buffer. Cell sizes were measured and recorded during the picking. Except for the enzyme dissociation, all the dissection procedure were performed on ice in order to reduce RNA degradation. Whole transcriptome amplification in tubes were performed following Smart-seq2 protocol (Picelli, Faridani et al. 2014) with minor edition. Briefly, the nuclei were lysised  and ploy-A RNA was reverse transcribed by superscript III reverse transcription enzyme using a template switch fashion. cDNA were then amplified by KAPA polymerase for 18 PCR cycles. After purification, 0.2ng cDNA were used for Nextera tagmentation and library construction. ERCC RNA spike-in Mix (Ambion, Life Technologies) was added to the lysis reaction and processed in parallel with ploy-A RNA. All libraries were sequenced 50bp single end on illumina Hi-seq2000 pipeline.	Illumina HiSeq 2000	source_name;;L5 DRG injury single cell|strain;;CAST/Eij male X C57BL/6 female|tissue;;dorsal root ganglion	GEO Accession;;GSM1834987		GSM1834987	s3.32	179859300	3597186	2016-08-26 15:44:09	73574128	179859300	3597186	1	3597186	index:0,count:3597186,average:50,stdev:0	GSM1834987_r1						1.16	1.97	0.04	174030058	190504449	129262945	152489705	109.47	117.97	0	0	0	0	0	0	67.7	91.24	4794618	2383355	4794618	2383355	57.84	67.76	4794618	2036408	4794618	1770058	11023929	6.33	0.63	0	25.25	0	0.49	0	0.28	0	0.00	0	1.36	0	3520463	0	50	0	49.48	0	3.70	0	0.04	0	1.05	0	0.03	0	681.57	0	0.30	0	22698	0	3597186	0	908271	0	17514	0	10161	0	0	0	49048	0	101	0	0	0	996	0	130261	0	2927	0	134285	0	72.62	0	2612192	0	40967	141914	3.464105255450	3597186.0	3520463.0	22698.0	908271.0	17514.0	10161.0	0.0	49048.0	2612192.0	97.9	0.6	25.2	0.5	0.3	0.0	1.4	72.6	50	50	50.00	6	179859300	24.0	25.4	25.8	24.8	0.0	35.4	28.4	smartseq
1478687	SRR2153901	SRP062242	SRS1028434	SRX1140952	SRA288475	GEO		Gene expression profiling of neurons with Rbfox1 and Rbfox3 knockdown and rescue with cytoplasmic or nuclear Rbfox1 isoform [RNA-seq]	Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes induced by knockdown, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that in nascent RNA Rbfox1 bound predominantly to introns, while cytoplasmic Rbox1 bound to 3'' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and overlapped significantly with miRNA binding sites. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease. In this data set, we included the data from RNA-seq experiments. Overall design: We performed RNA-seq to profile gene expression and splicing changes. The expression levels of Rbfox1 and Rbfox3 in cultured mouse hippocampal neurons were reduced by siRNAs. The reduction of Rbfox1 and 3 was rescued by expression of cytoplasmic or nuclear Rbfox1 splice isoform. The gene expression and splicing profiles were compared between different treatments. Eight samples were analyzed.		GSM1847354: siNT_EGFP_Rep1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted by RNeasy Mini kit (Qiagen) according to manufacturer's instruction. Ribosomal RNA was removed using Ribo-Zero™ rRNA Removal Kits (Epicentre), and the cDNA libraries were prepared using TruSeq RNA Sample Preparation Kit (Illumina). RNA-Seq HiSeq2000 (Illumina) paired-end 50 nt, non-strand specific.	Illumina HiSeq 2000	age;;14 DIV|cell_type;;hippocampal neurons|sirna;;Non-targeting|source_name;;Hippocampal culture_Control siRNAs_EGFP|treated with;;AAV2/9-SynI-EGFP and Non-targeting siRNAs	GEO Accession;;GSM1847354		GSM1847354	siNT_EGFP_Rep1	10076426300	100764263	2015-12-10 18:37:12	8937200346	10076426300	100764263	2	100764263	index:0,count:100764263,average:50,stdev:0|index:1,count:100764263,average:50,stdev:0	GSM1847354_r1						1.0	3.8	0.03	9389044176	9350721926	8517771451	8530161918	99.59	100.15	94942925	80214892	202.134	1452.172	136	870587	82.54	90.94	108914280	78366654	108914280	78366654	87.76	87.96	108914280	83324381	108914280	75792214	727106205	7.74	1.52	0	8.71	0	0.28	0	0.16	0	0.00	0	5.34	0	94942925	0	100	0	98.99	0	1.36	0	0.00	0	1.14	0	0.00	0	472.95	0	0.25	0	1531819	0	100764263	0	8773438	0	283098	0	159348	0	0	0	5378892	0	12537	0	0	0	109421	0	14266486	0	29101	0	14417545	0	85.52	0	86169487	0	232175	14634761	63.033319694196	100764263.0	94942925.0	1531819.0	8773438.0	283098.0	159348.0	0.0	5378892.0	86169487.0	94.2	1.5	8.7	0.3	0.2	0.0	5.3	85.5	50	50	50.00	38	5038213150	24.6	25.1	25.5	24.8	0.0	35.9	21.6	bulk
1478703	SRR2153902	SRP062242	SRS1028433	SRX1140953	SRA288475	GEO		Gene expression profiling of neurons with Rbfox1 and Rbfox3 knockdown and rescue with cytoplasmic or nuclear Rbfox1 isoform [RNA-seq]	Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes induced by knockdown, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that in nascent RNA Rbfox1 bound predominantly to introns, while cytoplasmic Rbox1 bound to 3'' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and overlapped significantly with miRNA binding sites. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease. In this data set, we included the data from RNA-seq experiments. Overall design: We performed RNA-seq to profile gene expression and splicing changes. The expression levels of Rbfox1 and Rbfox3 in cultured mouse hippocampal neurons were reduced by siRNAs. The reduction of Rbfox1 and 3 was rescued by expression of cytoplasmic or nuclear Rbfox1 splice isoform. The gene expression and splicing profiles were compared between different treatments. Eight samples were analyzed.		GSM1847355: siNT_EGFP_Rep2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted by RNeasy Mini kit (Qiagen) according to manufacturer's instruction. Ribosomal RNA was removed using Ribo-Zero™ rRNA Removal Kits (Epicentre), and the cDNA libraries were prepared using TruSeq RNA Sample Preparation Kit (Illumina). RNA-Seq HiSeq2000 (Illumina) paired-end 50 nt, non-strand specific.	Illumina HiSeq 2000	age;;14 DIV|cell_type;;hippocampal neurons|sirna;;Non-targeting|source_name;;Hippocampal culture_Control siRNAs_EGFP|treated with;;AAV2/9-SynI-EGFP and Non-targeting siRNAs	GEO Accession;;GSM1847355		GSM1847355	siNT_EGFP_Rep2	9273132100	92731321	2015-12-10 18:37:12	8213307065	9273132100	92731321	2	92731321	index:0,count:92731321,average:50,stdev:0|index:1,count:92731321,average:50,stdev:0	GSM1847355_r1						1.24	3.87	0.03	8695159710	8665514169	7908043776	7927595158	99.66	100.25	87908020	73911324	202.124	1472.719	135	796303	84.45	92.81	100724416	74236709	100724416	74236709	89.44	89.8	100724416	78620549	100724416	71825470	525858957	6.05	1.42	0	8.54	0	0.28	0	0.14	0	0.00	0	4.79	0	87908020	0	100	0	99.03	0	1.44	0	0.00	0	1.16	0	0.00	0	431.87	0	0.24	0	1317831	0	92731321	0	7923079	0	258601	0	126914	0	0	0	4437786	0	12128	0	0	0	104854	0	13626271	0	25611	0	13768864	0	86.25	0	79984941	0	227233	13986241	61.550219378347	92731321.0	87908020.0	1317831.0	7923079.0	258601.0	126914.0	0.0	4437786.0	79984941.0	94.8	1.4	8.5	0.3	0.1	0.0	4.8	86.3	50	50	50.00	38	4636566050	24.8	24.9	25.3	25.0	0.0	36.0	21.9	bulk
1478719	SRR2153903	SRP062242	SRS1028432	SRX1140954	SRA288475	GEO		Gene expression profiling of neurons with Rbfox1 and Rbfox3 knockdown and rescue with cytoplasmic or nuclear Rbfox1 isoform [RNA-seq]	Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes induced by knockdown, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that in nascent RNA Rbfox1 bound predominantly to introns, while cytoplasmic Rbox1 bound to 3'' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and overlapped significantly with miRNA binding sites. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease. In this data set, we included the data from RNA-seq experiments. Overall design: We performed RNA-seq to profile gene expression and splicing changes. The expression levels of Rbfox1 and Rbfox3 in cultured mouse hippocampal neurons were reduced by siRNAs. The reduction of Rbfox1 and 3 was rescued by expression of cytoplasmic or nuclear Rbfox1 splice isoform. The gene expression and splicing profiles were compared between different treatments. Eight samples were analyzed.		GSM1847356: siRbfox1&3_EGFP_Rep1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted by RNeasy Mini kit (Qiagen) according to manufacturer's instruction. Ribosomal RNA was removed using Ribo-Zero™ rRNA Removal Kits (Epicentre), and the cDNA libraries were prepared using TruSeq RNA Sample Preparation Kit (Illumina). RNA-Seq HiSeq2000 (Illumina) paired-end 50 nt, non-strand specific.	Illumina HiSeq 2000	age;;14 DIV|cell_type;;hippocampal neurons|sirna;;Rbfox1 and Rbfox3|source_name;;Hippocampal culture_Rbfox1 and Rbfox3 siRNAs_EGFP|treated with;;AAV2/9-SynI-EGFP and Rbfox1 and Rbfox3 siRNAs	GEO Accession;;GSM1847356		GSM1847356	siRbfox1&3_EGFP_Rep1	10884832600	108848326	2015-12-10 18:37:12	9662418821	10884832600	108848326	2	108848326	index:0,count:108848326,average:50,stdev:0|index:1,count:108848326,average:50,stdev:0	GSM1847356_r1						1.38	3.88	0.03	10218936059	10188563007	9292127127	9316595298	99.7	100.26	103301556	87155702	201.412	1424.388	136	960679	83.92	92.25	118611270	86688673	118611270	86688673	89.0	89.28	118611270	91941206	118611270	83902932	681272644	6.67	1.31	0	8.57	0	0.28	0	0.15	0	0.00	0	4.66	0	103301556	0	100	0	99.04	0	1.35	0	0.00	0	1.14	0	0.00	0	441.28	0	0.25	0	1429901	0	108848326	0	9327947	0	308582	0	160964	0	0	0	5077224	0	14203	0	0	0	121572	0	15913848	0	30593	0	16080216	0	86.33	0	93973609	0	235329	16344308	69.453012590883	108848326.0	103301556.0	1429901.0	9327947.0	308582.0	160964.0	0.0	5077224.0	93973609.0	94.9	1.3	8.6	0.3	0.1	0.0	4.7	86.3	50	50	50.00	38	5442416300	24.8	24.9	25.2	25.1	0.0	35.9	21.8	bulk
1478735	SRR2153904	SRP062242	SRS1028431	SRX1140955	SRA288475	GEO		Gene expression profiling of neurons with Rbfox1 and Rbfox3 knockdown and rescue with cytoplasmic or nuclear Rbfox1 isoform [RNA-seq]	Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes induced by knockdown, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that in nascent RNA Rbfox1 bound predominantly to introns, while cytoplasmic Rbox1 bound to 3'' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and overlapped significantly with miRNA binding sites. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease. In this data set, we included the data from RNA-seq experiments. Overall design: We performed RNA-seq to profile gene expression and splicing changes. The expression levels of Rbfox1 and Rbfox3 in cultured mouse hippocampal neurons were reduced by siRNAs. The reduction of Rbfox1 and 3 was rescued by expression of cytoplasmic or nuclear Rbfox1 splice isoform. The gene expression and splicing profiles were compared between different treatments. Eight samples were analyzed.		GSM1847357: siRbfox1&3_EGFP_Rep2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted by RNeasy Mini kit (Qiagen) according to manufacturer's instruction. Ribosomal RNA was removed using Ribo-Zero™ rRNA Removal Kits (Epicentre), and the cDNA libraries were prepared using TruSeq RNA Sample Preparation Kit (Illumina). RNA-Seq HiSeq2000 (Illumina) paired-end 50 nt, non-strand specific.	Illumina HiSeq 2000	age;;14 DIV|cell_type;;hippocampal neurons|sirna;;Rbfox1 and Rbfox3|source_name;;Hippocampal culture_Rbfox1 and Rbfox3 siRNAs_EGFP|treated with;;AAV2/9-SynI-EGFP and Rbfox1 and Rbfox3 siRNAs	GEO Accession;;GSM1847357		GSM1847357	siRbfox1&3_EGFP_Rep2	10230244900	102302449	2015-12-10 18:37:12	9068525859	10230244900	102302449	2	102302449	index:0,count:102302449,average:50,stdev:0|index:1,count:102302449,average:50,stdev:0	GSM1847357_r1						1.2	3.81	0.03	9557881888	9534451777	8651687829	8683473996	99.75	100.37	96614946	81164891	203.884	1461.126	136	863403	83.73	92.45	111573366	80892591	111573366	80892591	88.81	89.18	111573366	85807557	111573366	78029573	605376581	6.33	1.48	0	8.91	0	0.28	0	0.14	0	0.00	0	5.14	0	96614946	0	100	0	99.03	0	1.61	0	0.00	0	1.18	0	0.00	0	499.71	0	0.25	0	1512962	0	102302449	0	9118611	0	286231	0	143406	0	0	0	5257866	0	13429	0	0	0	113740	0	14886302	0	28628	0	15042099	0	85.53	0	87496335	0	229044	15298518	66.792921884005	102302449.0	96614946.0	1512962.0	9118611.0	286231.0	143406.0	0.0	5257866.0	87496335.0	94.4	1.5	8.9	0.3	0.1	0.0	5.1	85.5	50	50	50.00	38	5115122450	24.6	25.0	25.4	24.9	0.0	35.9	21.7	bulk
1478750	SRR2153905	SRP062242	SRS1028430	SRX1140956	SRA288475	GEO		Gene expression profiling of neurons with Rbfox1 and Rbfox3 knockdown and rescue with cytoplasmic or nuclear Rbfox1 isoform [RNA-seq]	Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes induced by knockdown, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that in nascent RNA Rbfox1 bound predominantly to introns, while cytoplasmic Rbox1 bound to 3'' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and overlapped significantly with miRNA binding sites. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease. In this data set, we included the data from RNA-seq experiments. Overall design: We performed RNA-seq to profile gene expression and splicing changes. The expression levels of Rbfox1 and Rbfox3 in cultured mouse hippocampal neurons were reduced by siRNAs. The reduction of Rbfox1 and 3 was rescued by expression of cytoplasmic or nuclear Rbfox1 splice isoform. The gene expression and splicing profiles were compared between different treatments. Eight samples were analyzed.		GSM1847358: siRbfox1&3_Flag-Rbfox1_C_Rep1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted by RNeasy Mini kit (Qiagen) according to manufacturer's instruction. Ribosomal RNA was removed using Ribo-Zero™ rRNA Removal Kits (Epicentre), and the cDNA libraries were prepared using TruSeq RNA Sample Preparation Kit (Illumina). RNA-Seq HiSeq2000 (Illumina) paired-end 50 nt, non-strand specific.	Illumina HiSeq 2000	age;;14 DIV|cell_type;;hippocampal neurons|sirna;;Rbfox1 and Rbfox3|source_name;;Hippocampal culture_Rbfox1 and Rbfox3 siRNAs_Flag_Rbfox1_C|treated with;;AAV2/9-SynI-Flag-Rbfox1_C_siMt and Rbfox1 and Rbfox3 siRNAs	GEO Accession;;GSM1847358		GSM1847358	siRbfox1&3_Flag-Rbfox1_C_Rep1	10842318300	108423183	2015-12-10 18:37:12	9584759115	10842318300	108423183	2	108423183	index:0,count:108423183,average:50,stdev:0|index:1,count:108423183,average:50,stdev:0	GSM1847358_r1						1.25	3.69	0.04	10172786970	10124427063	9204890917	9213323076	99.52	100.09	102783480	87092511	201.580	1412.786	136	929580	80.13	88.52	118553359	82362272	118553359	82362272	85.46	85.43	118553359	87836022	118553359	79486351	1000265820	9.83	1.45	0	8.98	0	0.28	0	0.20	0	0.00	0	4.72	0	102783480	0	100	0	99.07	0	1.59	0	0.00	0	1.18	0	0.00	0	451.76	0	0.25	0	1567631	0	108423183	0	9736491	0	307169	0	216912	0	0	0	5115622	0	13616	0	0	0	117853	0	15126260	0	33123	0	15290852	0	85.82	0	93046989	0	229781	15527131	67.573607043228	108423183.0	102783480.0	1567631.0	9736491.0	307169.0	216912.0	0.0	5115622.0	93046989.0	94.8	1.4	9.0	0.3	0.2	0.0	4.7	85.8	50	50	50.00	38	5421159150	24.8	24.9	25.3	25.1	0.0	36.0	22.0	bulk
1478767	SRR2153906	SRP062242	SRS1028429	SRX1140957	SRA288475	GEO		Gene expression profiling of neurons with Rbfox1 and Rbfox3 knockdown and rescue with cytoplasmic or nuclear Rbfox1 isoform [RNA-seq]	Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes induced by knockdown, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that in nascent RNA Rbfox1 bound predominantly to introns, while cytoplasmic Rbox1 bound to 3'' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and overlapped significantly with miRNA binding sites. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease. In this data set, we included the data from RNA-seq experiments. Overall design: We performed RNA-seq to profile gene expression and splicing changes. The expression levels of Rbfox1 and Rbfox3 in cultured mouse hippocampal neurons were reduced by siRNAs. The reduction of Rbfox1 and 3 was rescued by expression of cytoplasmic or nuclear Rbfox1 splice isoform. The gene expression and splicing profiles were compared between different treatments. Eight samples were analyzed.		GSM1847359: siRbfox1&3_Flag-Rbfox1_C_Rep2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted by RNeasy Mini kit (Qiagen) according to manufacturer's instruction. Ribosomal RNA was removed using Ribo-Zero™ rRNA Removal Kits (Epicentre), and the cDNA libraries were prepared using TruSeq RNA Sample Preparation Kit (Illumina). RNA-Seq HiSeq2000 (Illumina) paired-end 50 nt, non-strand specific.	Illumina HiSeq 2000	age;;14 DIV|cell_type;;hippocampal neurons|sirna;;Rbfox1 and Rbfox3|source_name;;Hippocampal culture_Rbfox1 and Rbfox3 siRNAs_Flag_Rbfox1_C|treated with;;AAV2/9-SynI-Flag-Rbfox1_C_siMt and Rbfox1 and Rbfox3 siRNAs	GEO Accession;;GSM1847359		GSM1847359	siRbfox1&3_Flag-Rbfox1_C_Rep2	11283711900	112837119	2015-12-10 18:37:12	10009806274	11283711900	112837119	2	112837119	index:0,count:112837119,average:50,stdev:0|index:1,count:112837119,average:50,stdev:0	GSM1847359_r1						1.13	3.77	0.04	10541975145	10507092632	9474816237	9497761657	99.67	100.24	106585972	90030137	202.918	1425.232	136	958067	81.79	90.95	123776948	87171739	123776948	87171739	87.72	87.86	123776948	93499657	123776948	84204979	816483828	7.75	1.50	0	9.52	0	0.29	0	0.16	0	0.00	0	5.09	0	106585972	0	100	0	99.01	0	1.41	0	0.00	0	1.15	0	0.00	0	541.62	0	0.26	0	1691522	0	112837119	0	10742604	0	329096	0	182290	0	0	0	5739761	0	14227	0	0	0	123317	0	15993755	0	33226	0	16164525	0	84.94	0	95843368	0	235169	16425362	69.844928540752	112837119.0	106585972.0	1691522.0	10742604.0	329096.0	182290.0	0.0	5739761.0	95843368.0	94.5	1.5	9.5	0.3	0.2	0.0	5.1	84.9	50	50	50.00	38	5641855950	24.6	25.1	25.4	24.9	0.0	35.9	21.7	bulk
1478783	SRR2153907	SRP062242	SRS1028428	SRX1140958	SRA288475	GEO		Gene expression profiling of neurons with Rbfox1 and Rbfox3 knockdown and rescue with cytoplasmic or nuclear Rbfox1 isoform [RNA-seq]	Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes induced by knockdown, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that in nascent RNA Rbfox1 bound predominantly to introns, while cytoplasmic Rbox1 bound to 3'' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and overlapped significantly with miRNA binding sites. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease. In this data set, we included the data from RNA-seq experiments. Overall design: We performed RNA-seq to profile gene expression and splicing changes. The expression levels of Rbfox1 and Rbfox3 in cultured mouse hippocampal neurons were reduced by siRNAs. The reduction of Rbfox1 and 3 was rescued by expression of cytoplasmic or nuclear Rbfox1 splice isoform. The gene expression and splicing profiles were compared between different treatments. Eight samples were analyzed.		GSM1847360: siRbfox1&3_Flag-Rbfox1_N_Rep1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted by RNeasy Mini kit (Qiagen) according to manufacturer's instruction. Ribosomal RNA was removed using Ribo-Zero™ rRNA Removal Kits (Epicentre), and the cDNA libraries were prepared using TruSeq RNA Sample Preparation Kit (Illumina). RNA-Seq HiSeq2000 (Illumina) paired-end 50 nt, non-strand specific.	Illumina HiSeq 2000	age;;14 DIV|cell_type;;hippocampal neurons|sirna;;Rbfox1 and Rbfox3|source_name;;Hippocampal culture_Rbfox1 and Rbfox3 siRNAs_Flag_Rbfox1_N|treated with;;AAV2/9-SynI-Flag-Rbfox1_N_siMt and Rbfox1 and Rbfox3 siRNAs	GEO Accession;;GSM1847360		GSM1847360	siRbfox1&3_Flag-Rbfox1_N_Rep1	11409464700	114094647	2015-12-10 18:37:12	10135210147	11409464700	114094647	2	114094647	index:0,count:114094647,average:50,stdev:0|index:1,count:114094647,average:50,stdev:0	GSM1847360_r1						1.08	3.45	0.03	10204534749	10203292169	9113530455	9208454653	99.99	101.04	103269352	88073736	200.889	1356.112	136	941570	80.94	90.58	121117995	83586879	121117995	83586879	84.54	85.36	121117995	87306044	121117995	78764583	727240064	7.13	2.62	0	9.63	0	0.27	0	0.12	0	0.00	0	9.10	0	103269352	0	100	0	98.90	0	2.84	0	0.01	0	1.25	0	0.01	0	517.31	0	0.31	0	2986019	0	114094647	0	10991674	0	305968	0	142030	0	0	0	10377297	0	13550	0	0	0	112801	0	14726777	0	32257	0	14885385	0	80.88	0	92277678	0	230699	15130027	65.583409550973	114094647.0	103269352.0	2986019.0	10991674.0	305968.0	142030.0	0.0	10377297.0	92277678.0	90.5	2.6	9.6	0.3	0.1	0.0	9.1	80.9	50	50	50.00	38	5704732350	24.0	25.7	26.1	24.2	0.0	35.7	21.2	bulk
1478799	SRR2153908	SRP062242	SRS1028427	SRX1140959	SRA288475	GEO		Gene expression profiling of neurons with Rbfox1 and Rbfox3 knockdown and rescue with cytoplasmic or nuclear Rbfox1 isoform [RNA-seq]	Human genetic studies have identified the neuronal RNA binding protein, Rbfox1, as a candidate gene for autism spectrum disorders. While Rbfox1 functions as a splicing regulator in the nucleus, it is also alternatively spliced to produce cytoplasmic isoforms. To investigate cytoplasmic Rbfox1, we knocked down Rbfox proteins in mouse neurons and rescued with cytoplasmic or nuclear Rbfox1. Transcriptome profiling showed that nuclear Rbfox1 rescued splicing changes induced by knockdown, whereas cytoplasmic Rbfox1 rescued changes in mRNA levels. iCLIP-seq of subcellular fractions revealed that in nascent RNA Rbfox1 bound predominantly to introns, while cytoplasmic Rbox1 bound to 3'' UTRs. Cytoplasmic Rbfox1 binding increased target mRNA stability and translation, and overlapped significantly with miRNA binding sites. Cytoplasmic Rbfox1 target mRNAs were enriched in genes involved in cortical development and autism. Our results uncover a new Rbfox1 regulatory network and highlight the importance of cytoplasmic RNA metabolism to cortical development and disease. In this data set, we included the data from RNA-seq experiments. Overall design: We performed RNA-seq to profile gene expression and splicing changes. The expression levels of Rbfox1 and Rbfox3 in cultured mouse hippocampal neurons were reduced by siRNAs. The reduction of Rbfox1 and 3 was rescued by expression of cytoplasmic or nuclear Rbfox1 splice isoform. The gene expression and splicing profiles were compared between different treatments. Eight samples were analyzed.		GSM1847361: siRbfox1&3_Flag-Rbfox1_N_Rep2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted by RNeasy Mini kit (Qiagen) according to manufacturer's instruction. Ribosomal RNA was removed using Ribo-Zero™ rRNA Removal Kits (Epicentre), and the cDNA libraries were prepared using TruSeq RNA Sample Preparation Kit (Illumina). RNA-Seq HiSeq2000 (Illumina) paired-end 50 nt, non-strand specific.	Illumina HiSeq 2000	age;;14 DIV|cell_type;;hippocampal neurons|sirna;;Rbfox1 and Rbfox3|source_name;;Hippocampal culture_Rbfox1 and Rbfox3 siRNAs_Flag_Rbfox1_N|treated with;;AAV2/9-SynI-Flag-Rbfox1_N_siMt and Rbfox1 and Rbfox3 siRNAs	GEO Accession;;GSM1847361		GSM1847361	siRbfox1&3_Flag-Rbfox1_N_Rep2	10854008400	108540084	2015-12-10 18:37:12	9616248337	10854008400	108540084	2	108540084	index:0,count:108540084,average:50,stdev:0|index:1,count:108540084,average:50,stdev:0	GSM1847361_r1						1.37	3.66	0.03	10142445358	10107805684	9097620446	9119449830	99.66	100.24	102489273	86533801	202.096	1433.442	136	923300	81.97	91.33	119251857	84009551	119251857	84009551	87.94	88.1	119251857	90127062	119251857	81034545	739323709	7.29	1.46	0	9.68	0	0.28	0	0.15	0	0.00	0	5.15	0	102489273	0	100	0	99.06	0	1.56	0	0.00	0	1.18	0	0.00	0	516.17	0	0.25	0	1580107	0	108540084	0	10507544	0	302438	0	157998	0	0	0	5590375	0	14046	0	0	0	119122	0	15430258	0	28962	0	15592388	0	84.74	0	91981729	0	230962	15849753	68.624938301539	108540084.0	102489273.0	1580107.0	10507544.0	302438.0	157998.0	0.0	5590375.0	91981729.0	94.4	1.5	9.7	0.3	0.1	0.0	5.2	84.7	50	50	50.00	38	5427004200	24.6	25.1	25.5	24.9	0.0	35.9	21.8	bulk
1904728	SRR2443105	SRP063829	SRS1073638	SRX1258024	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888151: Bone_SCA1p_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888151		GSM1888151	Bone_SCA1p_1	5185978200	25929891	2016-02-26 22:54:03	3578698938	5185978200	25929891	2	25929891	index:0,count:25929891,average:100,stdev:0|index:1,count:25929891,average:100,stdev:0	GSM1888151_r1				in_mesa	27183606	3.4	2.7	0.07	2879160524	2877405951	2711915155	2723300878	99.94	100.42	21506802	19780387	169.497	656.262	107	179843	86.68	92.25	23704051	18642912	23704051	18642912	88.85	89.17	23704051	19108533	23704051	18020000	208456700	7.24	1.12	0	5.01	0	0.28	0	0.08	0	0.00	0	16.70	0	21506802	0	200	0	190.51	0	1.50	0	0.01	0	1.22	0	0.00	0	243.09	0	0.22	0	289377	0	25929891	0	1298613	0	71808	0	21289	0	0	0	4329992	0	4142	0	0	0	52005	0	10141380	0	13187	0	10210714	0	77.93	0	20208189	0	101381	7952771	78.444392933587	25929891.0	21506802.0	289377.0	1298613.0	71808.0	21289.0	0.0	4329992.0	20208189.0	82.9	1.1	5.0	0.3	0.1	0.0	16.7	77.9	100	100	100.00	38	2592989100	21.5	21.4	22.7	24.1	10.3	35.0	18.2	bulk
1904744	SRR2443106	SRP063829	SRS1073638	SRX1258024	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888151: Bone_SCA1p_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888151		GSM1888151	Bone_SCA1p_1	5227755800	26138779	2016-02-26 22:54:03	3602834427	5227755800	26138779	2	26138779	index:0,count:26138779,average:100,stdev:0|index:1,count:26138779,average:100,stdev:0	GSM1888151_r2				in_mesa	27183606	3.4	2.71	0.07	2892876536	2891353917	2724767193	2736377690	99.95	100.43	21632761	19896018	169.403	655.876	107	181062	86.68	92.26	23846915	18751928	23846915	18751928	88.85	89.17	23846915	19219837	23846915	18125244	209431943	7.24	1.12	0	5.00	0	0.28	0	0.08	0	0.00	0	16.88	0	21632761	0	200	0	190.50	0	1.49	0	0.01	0	1.22	0	0.00	0	321.16	0	0.21	0	293025	0	26138779	0	1306619	0	72539	0	22002	0	0	0	4411477	0	4290	0	0	0	52783	0	10217475	0	13208	0	10287756	0	77.76	0	20326142	0	101195	8001448	79.069598300311	26138779.0	21632761.0	293025.0	1306619.0	72539.0	22002.0	0.0	4411477.0	20326142.0	82.8	1.1	5.0	0.3	0.1	0.0	16.9	77.8	100	100	100.00	38	2613877900	21.5	21.3	22.7	24.0	10.4	35.0	18.3	bulk
1904921	SRR2443111	SRP063829	SRS1073635	SRX1258026	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888153: Bone_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888153		GSM1888153	Bone_SCA1p_3	4496567200	22482836	2016-02-26 22:54:03	3076397147	4496567200	22482836	2	22482836	index:0,count:22482836,average:100,stdev:0|index:1,count:22482836,average:100,stdev:0	GSM1888153_r1				in_mesa	27183606	3.7	2.74	0.09	2552493673	2549097033	2396540952	2405522574	99.87	100.37	19024686	17459328	170.359	657.124	107	158197	86.91	92.79	21053891	16534270	21053891	16534270	89.53	89.87	21053891	17033467	21053891	16014017	172374398	6.75	1.17	0	5.36	0	0.29	0	0.08	0	0.00	0	15.01	0	19024686	0	200	0	190.99	0	1.48	0	0.01	0	1.18	0	0.00	0	304.28	0	0.20	0	262160	0	22482836	0	1205034	0	64523	0	18549	0	0	0	3375078	0	3926	0	0	0	48893	0	9210958	0	11792	0	9275569	0	79.26	0	17819652	0	143738	7196732	50.068402231838	22482836.0	19024686.0	262160.0	1205034.0	64523.0	18549.0	0.0	3375078.0	17819652.0	84.6	1.2	5.4	0.3	0.1	0.0	15.0	79.3	100	100	100.00	38	2248283600	21.8	21.5	23.2	24.4	9.1	35.3	18.8	bulk
1904936	SRR2443112	SRP063829	SRS1073635	SRX1258026	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888153: Bone_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888153		GSM1888153	Bone_SCA1p_3	4482913200	22414566	2016-02-26 22:54:03	3062984841	4482913200	22414566	2	22414566	index:0,count:22414566,average:100,stdev:0|index:1,count:22414566,average:100,stdev:0	GSM1888153_r2				in_mesa	27183606	3.71	2.75	0.09	2539415038	2535804566	2384017908	2392756956	99.86	100.37	18944330	17384827	170.221	656.947	106	157998	86.9	92.79	20969677	16463240	20969677	16463240	89.54	89.88	20969677	16963583	20969677	15946564	171257085	6.74	1.17	0	5.36	0	0.29	0	0.08	0	0.00	0	15.11	0	18944330	0	200	0	190.98	0	1.49	0	0.01	0	1.18	0	0.00	0	274.46	0	0.19	0	261819	0	22414566	0	1202045	0	64662	0	18721	0	0	0	3386853	0	3996	0	0	0	48871	0	9177930	0	11502	0	9242299	0	79.16	0	17742285	0	143776	7167368	49.850934787447	22414566.0	18944330.0	261819.0	1202045.0	64662.0	18721.0	0.0	3386853.0	17742285.0	84.5	1.2	5.4	0.3	0.1	0.0	15.1	79.2	100	100	100.00	38	2241456600	21.7	21.5	23.2	24.4	9.2	35.3	18.9	bulk
1904953	SRR2443113	SRP063829	SRS1073635	SRX1258026	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888153: Bone_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888153		GSM1888153	Bone_SCA1p_3	4471209200	22356046	2016-02-26 22:54:03	3038882713	4471209200	22356046	2	22356046	index:0,count:22356046,average:100,stdev:0|index:1,count:22356046,average:100,stdev:0	GSM1888153_r3				in_mesa	27183606	3.7	2.74	0.09	2540953812	2537506841	2385651745	2394425820	99.86	100.37	18930432	17371261	170.479	656.243	106	156570	86.91	92.79	20952698	16451564	20952698	16451564	89.54	89.87	20952698	16950865	20952698	15935256	171459143	6.75	1.16	0	5.37	0	0.29	0	0.08	0	0.00	0	14.95	0	18930432	0	200	0	191.02	0	1.49	0	0.01	0	1.19	0	0.00	0	256.31	0	0.19	0	259783	0	22356046	0	1199878	0	64226	0	18727	0	0	0	3342661	0	3913	0	0	0	48690	0	9177385	0	11703	0	9241691	0	79.31	0	17730554	0	143872	7173270	49.858693838968	22356046.0	18930432.0	259783.0	1199878.0	64226.0	18727.0	0.0	3342661.0	17730554.0	84.7	1.2	5.4	0.3	0.1	0.0	15.0	79.3	100	100	100.00	38	2235604600	21.7	21.5	23.2	24.4	9.2	35.4	19.1	bulk
1904970	SRR2443114	SRP063829	SRS1073640	SRX1258027	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888154: Skin_SCA1p_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888154		GSM1888154	Skin_SCA1p_1	493262000	2466310	2016-02-26 22:54:03	339092247	493262000	2466310	2	2466310	index:0,count:2466310,average:100,stdev:0|index:1,count:2466310,average:100,stdev:0	GSM1888154_r1				in_mesa	27183606	2.37	2.08	0.04	318441364	319785685	304232264	306544592	100.42	100.76	2248534	2053848	186.291	622.147	118	20487	93.1	97.61	2426672	2093371	2426672	2093371	94.33	94.83	2426672	2120973	2426672	2033640	6642828	2.09	0.85	0	4.22	0	0.24	0	0.03	0	0.00	0	8.56	0	2248534	0	200	0	194.31	0	1.54	0	0.00	0	1.29	0	0.00	0	79.27	0	0.21	0	21057	0	2466310	0	103965	0	5942	0	796	0	0	0	211038	0	375	0	0	0	4856	0	1482976	0	1227	0	1489434	0	86.95	0	2144569	0	82581	1183395	14.330112253424	2466310.0	2248534.0	21057.0	103965.0	5942.0	796.0	0.0	211038.0	2144569.0	91.2	0.9	4.2	0.2	0.0	0.0	8.6	87.0	100	100	100.00	38	246631000	21.3	23.6	25.0	24.0	6.2	34.9	18.0	bulk
1904985	SRR2443115	SRP063829	SRS1073640	SRX1258027	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888154: Skin_SCA1p_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888154		GSM1888154	Skin_SCA1p_1	491868200	2459341	2016-02-26 22:54:03	337672120	491868200	2459341	2	2459341	index:0,count:2459341,average:100,stdev:0|index:1,count:2459341,average:100,stdev:0	GSM1888154_r2				in_mesa	27183606	2.4	2.06	0.04	316994642	318330484	302777486	305070066	100.42	100.76	2240136	2046260	186.048	616.513	118	20353	93.07	97.6	2419110	2084968	2419110	2084968	94.3	94.79	2419110	2112472	2419110	2025042	6593776	2.08	0.86	0	4.22	0	0.24	0	0.03	0	0.00	0	8.64	0	2240136	0	200	0	194.32	0	1.51	0	0.00	0	1.27	0	0.00	0	196.75	0	0.20	0	21190	0	2459341	0	103895	0	5974	0	784	0	0	0	212447	0	386	0	0	0	4825	0	1477546	0	1150	0	1483907	0	86.86	0	2136241	0	82464	1178308	14.288756305782	2459341.0	2240136.0	21190.0	103895.0	5974.0	784.0	0.0	212447.0	2136241.0	91.1	0.9	4.2	0.2	0.0	0.0	8.6	86.9	100	100	100.00	38	245934100	21.3	23.5	24.9	24.0	6.3	34.9	18.1	bulk
1905002	SRR2443116	SRP063829	SRS1073640	SRX1258027	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888154: Skin_SCA1p_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888154		GSM1888154	Skin_SCA1p_1	496703400	2483517	2016-02-26 22:54:03	339382936	496703400	2483517	2	2483517	index:0,count:2483517,average:100,stdev:0|index:1,count:2483517,average:100,stdev:0	GSM1888154_r3				in_mesa	27183606	2.38	2.07	0.04	320431477	321819268	306059723	308414379	100.43	100.77	2263962	2066808	186.089	628.195	118	20212	93.08	97.61	2444129	2107290	2444129	2107290	94.3	94.8	2444129	2134902	2444129	2046482	6635802	2.07	0.85	0	4.23	0	0.24	0	0.03	0	0.00	0	8.57	0	2263962	0	200	0	194.33	0	1.54	0	0.00	0	1.28	0	0.00	0	80.55	0	0.20	0	21197	0	2483517	0	105166	0	5963	0	803	0	0	0	212789	0	428	0	0	0	4703	0	1494619	0	1119	0	1500869	0	86.92	0	2158796	0	82928	1191844	14.372033571291	2483517.0	2263962.0	21197.0	105166.0	5963.0	803.0	0.0	212789.0	2158796.0	91.2	0.9	4.2	0.2	0.0	0.0	8.6	86.9	100	100	100.00	38	248351700	21.2	23.5	24.9	24.0	6.3	35.0	18.3	bulk
1905018	SRR2443117	SRP063829	SRS1073640	SRX1258027	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888154: Skin_SCA1p_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888154		GSM1888154	Skin_SCA1p_1	5894803200	29474016	2016-02-26 22:54:03	3796651644	5894803200	29474016	2	29474016	index:0,count:29474016,average:100,stdev:0|index:1,count:29474016,average:100,stdev:0	GSM1888154_r4				in_mesa	27183606	2.32	2.04	0.04	3793262113	3810085014	3626290422	3654224827	100.44	100.77	26712630	24340525	187.637	634.475	118	234940	93.22	97.68	28812792	24902160	28812792	24902160	94.4	94.89	28812792	25216236	28812792	24191442	76311996	2.01	0.87	0	4.14	0	0.24	0	0.08	0	0.00	0	9.05	0	26712630	0	200	0	194.34	0	1.55	0	0.00	0	1.28	0	0.00	0	237.37	0	0.14	0	255271	0	29474016	0	1219268	0	69624	0	24955	0	0	0	2666807	0	4920	0	0	0	57254	0	17906288	0	14302	0	17982764	0	86.49	0	25493362	0	137463	14301199	104.036715334308	29474016.0	26712630.0	255271.0	1219268.0	69624.0	24955.0	0.0	2666807.0	25493362.0	90.6	0.9	4.1	0.2	0.1	0.0	9.0	86.5	100	100	100.00	38	2947401600	21.0	23.4	24.8	23.8	7.0	35.8	19.1	bulk
1905036	SRR2443118	SRP063829	SRS1073640	SRX1258027	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888154: Skin_SCA1p_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888154		GSM1888154	Skin_SCA1p_1	8131548800	40657744	2016-02-26 22:54:03	5171948516	8131548800	40657744	2	40657744	index:0,count:40657744,average:100,stdev:0|index:1,count:40657744,average:100,stdev:0	GSM1888154_r5				in_mesa	27183606	2.32	2.04	0.04	5225239710	5248757472	4994971758	5033633244	100.45	100.77	36814101	33540507	187.668	635.229	118	323095	93.22	97.68	39709243	34317092	39709243	34317092	94.39	94.89	39709243	34750165	39709243	33337184	105623239	2.02	0.87	0	4.14	0	0.24	0	0.03	0	0.00	0	9.19	0	36814101	0	200	0	194.32	0	1.54	0	0.00	0	1.28	0	0.00	0	146.81	0	0.13	0	352693	0	40657744	0	1681696	0	96850	0	12289	0	0	0	3734504	0	6726	0	0	0	78739	0	24735363	0	19393	0	24840221	0	86.41	0	35132405	0	140520	19733934	140.435055508113	40657744.0	36814101.0	352693.0	1681696.0	96850.0	12289.0	0.0	3734504.0	35132405.0	90.5	0.9	4.1	0.2	0.0	0.0	9.2	86.4	100	100	100.00	38	4065774400	21.0	23.4	24.7	23.8	7.1	35.9	19.3	bulk
1905051	SRR2443119	SRP063829	SRS1073634	SRX1258028	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888155: Skin_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888155		GSM1888155	Skin_SCA1p_2	1795183600	8975918	2016-02-26 22:54:03	1138557433	1795183600	8975918	2	8975918	index:0,count:8975918,average:100,stdev:0|index:1,count:8975918,average:100,stdev:0	GSM1888155_r1				in_mesa	27183606	2.03	1.94	0.03	1236134922	1243554976	1182549181	1193062694	100.6	100.89	8482021	7721359	192.534	634.611	128	69814	93.76	98.18	9142788	7952522	9142788	7952522	94.92	95.4	9142788	8051034	9142788	7726925	19660342	1.59	0.80	0	4.26	0	0.24	0	0.02	0	0.00	0	5.24	0	8482021	0	200	0	194.82	0	1.50	0	0.00	0	1.30	0	0.00	0	260.59	0	0.15	0	72066	0	8975918	0	382131	0	21950	0	2031	0	0	0	469916	0	1601	0	0	0	18158	0	5779436	0	4265	0	5803460	0	90.24	0	8099890	0	119103	4721785	39.644551354710	8975918.0	8482021.0	72066.0	382131.0	21950.0	2031.0	0.0	469916.0	8099890.0	94.5	0.8	4.3	0.2	0.0	0.0	5.2	90.2	100	100	100.00	38	897591800	21.7	24.5	26.5	24.4	3.0	36.4	22.1	bulk
1905163	SRR2443120	SRP063829	SRS1073634	SRX1258028	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888155: Skin_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888155		GSM1888155	Skin_SCA1p_2	4413817200	22069086	2016-02-26 22:54:03	2866436689	4413817200	22069086	2	22069086	index:0,count:22069086,average:100,stdev:0|index:1,count:22069086,average:100,stdev:0	GSM1888155_r2				in_mesa	27183606	2.06	1.96	0.04	3035430953	3053638999	2902129742	2928054761	100.6	100.89	20846920	18971927	192.515	637.929	128	171941	93.69	98.17	22488590	19531840	22488590	19531840	94.89	95.37	22488590	19781462	22488590	18975233	48833735	1.61	0.81	0	4.31	0	0.24	0	0.03	0	0.00	0	5.26	0	20846920	0	200	0	194.74	0	1.52	0	0.00	0	1.29	0	0.00	0	383.81	0	0.14	0	179553	0	22069086	0	950705	0	53928	0	6619	0	0	0	1161619	0	3977	0	0	0	45122	0	14221786	0	10660	0	14281545	0	90.15	0	19896215	0	141060	11608060	82.291648943712	22069086.0	20846920.0	179553.0	950705.0	53928.0	6619.0	0.0	1161619.0	19896215.0	94.5	0.8	4.3	0.2	0.0	0.0	5.3	90.2	100	100	100.00	38	2206908600	21.8	24.5	26.3	24.5	3.0	36.1	21.8	bulk
1905179	SRR2443121	SRP063829	SRS1073634	SRX1258028	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888155: Skin_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888155		GSM1888155	Skin_SCA1p_2	6096519600	30482598	2016-02-26 22:54:03	3907489125	6096519600	30482598	2	30482598	index:0,count:30482598,average:100,stdev:0|index:1,count:30482598,average:100,stdev:0	GSM1888155_r3				in_mesa	27183606	2.06	1.96	0.04	4191293976	4216156193	4007501470	4043113941	100.59	100.89	28797519	26201884	192.520	638.947	128	237062	93.7	98.17	31059762	26982507	31059762	26982507	94.89	95.38	31059762	27327103	31059762	26215498	67436256	1.61	0.81	0	4.30	0	0.25	0	0.02	0	0.00	0	5.26	0	28797519	0	200	0	194.72	0	1.51	0	0.00	0	1.29	0	0.00	0	292.63	0	0.13	0	247958	0	30482598	0	1310771	0	75007	0	6931	0	0	0	1603141	0	5578	0	0	0	62603	0	19682941	0	14763	0	19765885	0	90.17	0	27486748	0	148073	16059072	108.453749164264	30482598.0	28797519.0	247958.0	1310771.0	75007.0	6931.0	0.0	1603141.0	27486748.0	94.5	0.8	4.3	0.2	0.0	0.0	5.3	90.2	100	100	100.00	38	3048259800	21.8	24.5	26.2	24.5	3.0	36.3	22.3	bulk
1905194	SRR2443122	SRP063829	SRS1073637	SRX1258029	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888156: Skin_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888156		GSM1888156	Skin_SCA1p_3	972818000	4864090	2016-02-26 22:54:03	668891608	972818000	4864090	2	4864090	index:0,count:4864090,average:100,stdev:0|index:1,count:4864090,average:100,stdev:0	GSM1888156_r1				in_mesa	27183606	2.33	2.06	0.04	655088883	657575539	622144625	626738746	100.38	100.74	4471652	4108142	189.018	598.810	128	38564	93.08	98.2	4868893	4162196	4868893	4162196	94.96	95.51	4868893	4246396	4868893	4048059	9832072	1.50	0.89	0	4.79	0	0.24	0	0.02	0	0.00	0	7.81	0	4471652	0	200	0	195.04	0	1.51	0	0.00	0	1.22	0	0.00	0	233.48	0	0.23	0	43089	0	4864090	0	233135	0	11464	0	1153	0	0	0	379821	0	900	0	0	0	8858	0	2741022	0	2304	0	2753084	0	87.14	0	4238517	0	100090	2268806	22.667659106804	4864090.0	4471652.0	43089.0	233135.0	11464.0	1153.0	0.0	379821.0	4238517.0	91.9	0.9	4.8	0.2	0.0	0.0	7.8	87.1	100	100	100.00	38	486409000	22.4	24.0	26.2	25.0	2.4	35.3	19.9	bulk
1905210	SRR2443123	SRP063829	SRS1073637	SRX1258029	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888156: Skin_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888156		GSM1888156	Skin_SCA1p_3	970703400	4853517	2016-02-26 22:54:03	666803586	970703400	4853517	2	4853517	index:0,count:4853517,average:100,stdev:0|index:1,count:4853517,average:100,stdev:0	GSM1888156_r2				in_mesa	27183606	2.34	2.08	0.04	654215033	656662515	621217935	625770197	100.37	100.73	4467939	4103986	188.725	597.373	128	38616	93.06	98.19	4867912	4157825	4867912	4157825	94.95	95.5	4867912	4242245	4867912	4044008	9922284	1.52	0.89	0	4.81	0	0.24	0	0.02	0	0.00	0	7.68	0	4467939	0	200	0	195.06	0	1.52	0	0.00	0	1.22	0	0.00	0	232.97	0	0.22	0	43174	0	4853517	0	233366	0	11674	0	1210	0	0	0	372694	0	849	0	0	0	8807	0	2738975	0	2398	0	2751029	0	87.25	0	4234573	0	100074	2264241	22.625667006415	4853517.0	4467939.0	43174.0	233366.0	11674.0	1210.0	0.0	372694.0	4234573.0	92.1	0.9	4.8	0.2	0.0	0.0	7.7	87.2	100	100	100.00	38	485351700	22.4	24.0	26.2	25.0	2.4	35.3	20.1	bulk
1905225	SRR2443124	SRP063829	SRS1073637	SRX1258029	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888156: Skin_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888156		GSM1888156	Skin_SCA1p_3	986865800	4934329	2016-02-26 22:54:03	675162550	986865800	4934329	2	4934329	index:0,count:4934329,average:100,stdev:0|index:1,count:4934329,average:100,stdev:0	GSM1888156_r3				in_mesa	27183606	2.33	2.07	0.04	668683158	671184676	634973709	639632065	100.37	100.73	4562788	4191096	189.068	599.206	128	39110	93.07	98.2	4968883	4246630	4968883	4246630	94.97	95.51	4968883	4333145	4968883	4130428	10057463	1.50	0.89	0	4.83	0	0.24	0	0.03	0	0.00	0	7.27	0	4562788	0	200	0	195.07	0	1.51	0	0.00	0	1.21	0	0.00	0	208.98	0	0.22	0	43834	0	4934329	0	238384	0	11752	0	1272	0	0	0	358517	0	869	0	0	0	9381	0	2804282	0	2273	0	2816805	0	87.64	0	4324404	0	100643	2321462	23.066303667418	4934329.0	4562788.0	43834.0	238384.0	11752.0	1272.0	0.0	358517.0	4324404.0	92.5	0.9	4.8	0.2	0.0	0.0	7.3	87.6	100	100	100.00	38	493432900	22.4	24.0	26.2	25.0	2.4	35.4	20.3	bulk
1905464	SRR2443133	SRP063829	SRS1073631	SRX1258032	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888159: Thymus_SCA1p_1-3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Thymus|strain;;C57BL/6|tissue;;Thymus	GEO Accession;;GSM1888159		GSM1888159	Thymus_SCA1p_1-3	4301652400	21508262	2016-02-26 22:54:03	2784693875	4301652400	21508262	2	21508262	index:0,count:21508262,average:100,stdev:0|index:1,count:21508262,average:100,stdev:0	GSM1888159_r1				in_mesa	27183606	3.85	3.26	0.07	2604592041	2599918819	2462497160	2471108127	99.82	100.35	19697979	18043326	163.657	693.918	104	211723	89.54	94.93	21570346	17637779	21570346	17637779	91.23	91.75	21570346	17970486	21570346	17047003	115956859	4.45	1.31	0	5.20	0	0.24	0	0.05	0	0.00	0	8.12	0	19697979	0	200	0	192.44	0	1.52	0	0.00	0	1.20	0	0.00	0	227.07	0	0.13	0	282607	0	21508262	0	1117439	0	52561	0	10363	0	0	0	1747359	0	3697	0	0	0	61002	0	9452198	0	9966	0	9526863	0	86.39	0	18580540	0	148423	7152808	48.192045707202	21508262.0	19697979.0	282607.0	1117439.0	52561.0	10363.0	0.0	1747359.0	18580540.0	91.6	1.3	5.2	0.2	0.0	0.0	8.1	86.4	100	100	100.00	38	2150826200	22.7	22.3	25.5	25.2	4.3	36.3	22.4	bulk
1905481	SRR2443134	SRP063829	SRS1073631	SRX1258032	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888159: Thymus_SCA1p_1-3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Thymus|strain;;C57BL/6|tissue;;Thymus	GEO Accession;;GSM1888159		GSM1888159	Thymus_SCA1p_1-3	9417297600	47086488	2016-02-26 22:54:03	6003279833	9417297600	47086488	2	47086488	index:0,count:47086488,average:100,stdev:0|index:1,count:47086488,average:100,stdev:0	GSM1888159_r2				in_mesa	27183606	3.84	3.26	0.07	5697439916	5686911947	5385909014	5404770933	99.82	100.35	43118644	39492511	163.589	691.879	104	464226	89.52	94.92	47227154	38599416	47227154	38599416	91.22	91.73	47227154	39330767	47227154	37304999	254348757	4.46	1.32	0	5.21	0	0.24	0	0.05	0	0.00	0	8.14	0	43118644	0	200	0	192.41	0	1.52	0	0.00	0	1.21	0	0.00	0	140.91	0	0.12	0	619848	0	47086488	0	2452362	0	114944	0	21211	0	0	0	3831689	0	8476	0	0	0	134761	0	20712947	0	21530	0	20877714	0	86.37	0	40666282	0	165967	15659529	94.353269023360	47086488.0	43118644.0	619848.0	2452362.0	114944.0	21211.0	0.0	3831689.0	40666282.0	91.6	1.3	5.2	0.2	0.0	0.0	8.1	86.4	100	100	100.00	38	4708648800	22.7	22.3	25.4	25.3	4.4	36.4	23.0	bulk
952383	SRR2443107	SRP063829	SRS1073638	SRX1258024	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888151: Bone_SCA1p_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888151		GSM1888151	Bone_SCA1p_1	5258056400	26290282	2016-02-26 22:54:03	3606115477	5258056400	26290282	2	26290282	index:0,count:26290282,average:100,stdev:0|index:1,count:26290282,average:100,stdev:0	GSM1888151_r3				in_mesa	27183606	3.39	2.71	0.07	2916318271	2914769138	2746856789	2758549473	99.95	100.43	21790493	20038207	169.489	656.273	107	182037	86.7	92.28	24021997	18892931	24021997	18892931	88.87	89.2	24021997	19365130	24021997	18262566	210600383	7.22	1.12	0	5.01	0	0.28	0	0.08	0	0.00	0	16.75	0	21790493	0	200	0	190.51	0	1.50	0	0.01	0	1.22	0	0.00	0	144.28	0	0.21	0	294009	0	26290282	0	1316088	0	72739	0	22311	0	0	0	4404739	0	4345	0	0	0	53113	0	10293148	0	13529	0	10364135	0	77.88	0	20474405	0	101368	8068718	79.598275589930	26290282.0	21790493.0	294009.0	1316088.0	72739.0	22311.0	0.0	4404739.0	20474405.0	82.9	1.1	5.0	0.3	0.1	0.0	16.8	77.9	100	100	100.00	38	2629028200	21.5	21.3	22.7	24.0	10.4	35.1	18.4	bulk
952391	SRR2443108	SRP063829	SRS1073636	SRX1258025	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888152: Bone_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888152		GSM1888152	Bone_SCA1p_2	5065071400	25325357	2016-02-26 22:54:03	3503560424	5065071400	25325357	2	25325357	index:0,count:25325357,average:100,stdev:0|index:1,count:25325357,average:100,stdev:0	GSM1888152_r1				in_mesa	27183606	3.2	2.83	0.07	3109603823	3105426139	2941207825	2950524893	99.87	100.32	22503374	20690800	173.529	649.833	116	177233	86.57	91.73	24634036	19481728	24634036	19481728	88.4	88.7	24634036	19893381	24634036	18837685	242080733	7.78	1.27	0	4.99	0	0.28	0	0.09	0	0.00	0	10.78	0	22503374	0	200	0	192.02	0	1.51	0	0.01	0	1.22	0	0.00	0	241.83	0	0.21	0	321088	0	25325357	0	1264664	0	70380	0	21530	0	0	0	2730073	0	4843	0	0	0	54027	0	10871366	0	13755	0	10943991	0	83.86	0	21238710	0	132955	8664596	65.169388138844	25325357.0	22503374.0	321088.0	1264664.0	70380.0	21530.0	0.0	2730073.0	21238710.0	88.9	1.3	5.0	0.3	0.1	0.0	10.8	83.9	100	100	100.00	38	2532535700	22.7	22.4	24.1	24.9	5.9	35.4	19.7	bulk
952399	SRR2443109	SRP063829	SRS1073636	SRX1258025	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888152: Bone_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888152		GSM1888152	Bone_SCA1p_2	5094580000	25472900	2016-02-26 22:54:03	3519467448	5094580000	25472900	2	25472900	index:0,count:25472900,average:100,stdev:0|index:1,count:25472900,average:100,stdev:0	GSM1888152_r2				in_mesa	27183606	3.21	2.83	0.07	3123281472	3118772688	2953919963	2963015091	99.86	100.31	22623906	20800860	173.407	652.901	106	179008	86.55	91.71	24772897	19580872	24772897	19580872	88.39	88.68	24772897	19996343	24772897	18933124	243286728	7.79	1.27	0	5.00	0	0.28	0	0.09	0	0.00	0	10.82	0	22623906	0	200	0	192.01	0	1.52	0	0.01	0	1.22	0	0.00	0	115.64	0	0.20	0	323791	0	25472900	0	1273361	0	71198	0	21793	0	0	0	2756003	0	4602	0	0	0	54688	0	10939841	0	13713	0	11012844	0	83.82	0	21350545	0	132921	8707664	65.510069891138	25472900.0	22623906.0	323791.0	1273361.0	71198.0	21793.0	0.0	2756003.0	21350545.0	88.8	1.3	5.0	0.3	0.1	0.0	10.8	83.8	100	100	100.00	38	2547290000	22.6	22.4	24.1	24.9	5.9	35.4	19.9	bulk
952455	SRR2443110	SRP063829	SRS1073636	SRX1258025	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888152: Bone_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Bone|strain;;C57BL/6|tissue;;Femur, tibia and pelvis	GEO Accession;;GSM1888152		GSM1888152	Bone_SCA1p_2	5118917000	25594585	2016-02-26 22:54:03	3516895786	5118917000	25594585	2	25594585	index:0,count:25594585,average:100,stdev:0|index:1,count:25594585,average:100,stdev:0	GSM1888152_r3				in_mesa	27183606	3.2	2.83	0.07	3145113224	3140963281	2974890027	2984340450	99.87	100.32	22760185	20921410	173.609	652.276	116	179485	86.57	91.72	24914528	19703398	24914528	19703398	88.39	88.68	24914528	20118125	24914528	19049421	244698186	7.78	1.27	0	5.00	0	0.28	0	0.09	0	0.00	0	10.71	0	22760185	0	200	0	192.03	0	1.51	0	0.01	0	1.22	0	0.00	0	253.13	0	0.20	0	324478	0	25594585	0	1278720	0	71222	0	21917	0	0	0	2741261	0	4720	0	0	0	55318	0	11011113	0	13904	0	11085055	0	83.93	0	21481465	0	133048	8770057	65.916488786002	25594585.0	22760185.0	324478.0	1278720.0	71222.0	21917.0	0.0	2741261.0	21481465.0	88.9	1.3	5.0	0.3	0.1	0.0	10.7	83.9	100	100	100.00	38	2559458500	22.6	22.4	24.1	24.9	5.9	35.5	20.1	bulk
952623	SRR2443125	SRP063829	SRS1073637	SRX1258029	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888156: Skin_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888156		GSM1888156	Skin_SCA1p_3	5092070600	25460353	2016-02-26 22:54:03	3295331522	5092070600	25460353	2	25460353	index:0,count:25460353,average:100,stdev:0|index:1,count:25460353,average:100,stdev:0	GSM1888156_r4				in_mesa	27183606	2.28	2.06	0.04	3463916864	3477942914	3291387833	3316090625	100.4	100.75	23555678	21589816	190.518	610.164	127	198009	93.15	98.22	25636774	21941521	25636774	21941521	94.99	95.53	25636774	22375536	25636774	21340711	51829070	1.50	0.92	0	4.78	0	0.24	0	0.03	0	0.00	0	7.22	0	23555678	0	200	0	195.07	0	1.52	0	0.00	0	1.22	0	0.00	0	277.75	0	0.16	0	234504	0	25460353	0	1216238	0	60486	0	6836	0	0	0	1837353	0	4504	0	0	0	48682	0	14645132	0	12578	0	14710896	0	87.74	0	22339440	0	137186	12131803	88.433243917018	25460353.0	23555678.0	234504.0	1216238.0	60486.0	6836.0	0.0	1837353.0	22339440.0	92.5	0.9	4.8	0.2	0.0	0.0	7.2	87.7	100	100	100.00	38	2546035300	22.3	24.1	26.2	25.0	2.4	36.2	22.1	bulk
952631	SRR2443126	SRP063829	SRS1073637	SRX1258029	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888156: Skin_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Skin|strain;;C57BL/6|tissue;;abdominal and back dermis (truncal skin)	GEO Accession;;GSM1888156		GSM1888156	Skin_SCA1p_3	6885948200	34429741	2016-02-26 22:54:03	4392327813	6885948200	34429741	2	34429741	index:0,count:34429741,average:100,stdev:0|index:1,count:34429741,average:100,stdev:0	GSM1888156_r5				in_mesa	27183606	2.28	2.06	0.04	4686525946	4705622277	4452877617	4486375521	100.41	100.75	31879304	29215856	190.550	610.858	127	267352	93.14	98.22	34698203	29693334	34698203	29693334	94.99	95.53	34698203	30283044	34698203	28881348	70209509	1.50	0.92	0	4.79	0	0.24	0	0.02	0	0.00	0	7.15	0	31879304	0	200	0	195.07	0	1.51	0	0.00	0	1.23	0	0.00	0	150.79	0	0.14	0	318383	0	34429741	0	1647597	0	81896	0	8128	0	0	0	2460413	0	5955	0	0	0	65879	0	19862222	0	17281	0	19951337	0	87.81	0	30231707	0	141393	16449958	116.342096143373	34429741.0	31879304.0	318383.0	1647597.0	81896.0	8128.0	0.0	2460413.0	30231707.0	92.6	0.9	4.8	0.2	0.0	0.0	7.1	87.8	100	100	100.00	38	3442974100	22.3	24.1	26.2	25.0	2.4	36.4	22.8	bulk
952639	SRR2443127	SRP063829	SRS1073633	SRX1258030	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888157: Thymus_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Thymus|strain;;C57BL/6|tissue;;Thymus	GEO Accession;;GSM1888157		GSM1888157	Thymus_SCA1p_2	5511880600	27559403	2016-02-26 22:54:03	3833609487	5511880600	27559403	2	27559403	index:0,count:27559403,average:100,stdev:0|index:1,count:27559403,average:100,stdev:0	GSM1888157_r1				in_mesa	27183606	2.09	3.17	0.06	3160674715	3162229446	3012217705	3026493483	100.05	100.47	23611366	21375847	171.214	775.791	105	191080	89.64	94.29	25657063	21165716	25657063	21165716	90.63	91.13	25657063	21398438	25657063	20456886	165765233	5.24	1.15	0	4.22	0	0.24	0	0.05	0	0.00	0	14.04	0	23611366	0	200	0	190.45	0	1.52	0	0.01	0	1.17	0	0.00	0	311.02	0	0.21	0	317068	0	27559403	0	1162878	0	65207	0	14703	0	0	0	3868127	0	5203	0	0	0	82283	0	12660039	0	13778	0	12761303	0	81.45	0	22448488	0	129343	9781337	75.623242077267	27559403.0	23611366.0	317068.0	1162878.0	65207.0	14703.0	0.0	3868127.0	22448488.0	85.7	1.2	4.2	0.2	0.1	0.0	14.0	81.5	100	100	100.00	38	2755940300	22.1	22.6	23.5	24.1	7.8	35.3	19.8	bulk
952646	SRR2443128	SRP063829	SRS1073633	SRX1258030	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888157: Thymus_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Thymus|strain;;C57BL/6|tissue;;Thymus	GEO Accession;;GSM1888157		GSM1888157	Thymus_SCA1p_2	5566826400	27834132	2016-02-26 22:54:03	3866518143	5566826400	27834132	2	27834132	index:0,count:27834132,average:100,stdev:0|index:1,count:27834132,average:100,stdev:0	GSM1888157_r2				in_mesa	27183606	2.09	3.17	0.06	3186679038	3188198053	3036750012	3051212668	100.05	100.48	23826522	21570708	171.008	776.199	105	193802	89.63	94.28	25895494	21356710	25895494	21356710	90.62	91.12	25895494	21590475	25895494	20639461	167285963	5.25	1.15	0	4.22	0	0.24	0	0.05	0	0.00	0	14.11	0	23826522	0	200	0	190.44	0	1.52	0	0.01	0	1.17	0	0.00	0	310.23	0	0.20	0	321012	0	27834132	0	1175175	0	66096	0	15116	0	0	0	3926398	0	5390	0	0	0	83098	0	12780168	0	13951	0	12882607	0	81.38	0	22651347	0	129303	9864557	76.290240752341	27834132.0	23826522.0	321012.0	1175175.0	66096.0	15116.0	0.0	3926398.0	22651347.0	85.6	1.2	4.2	0.2	0.1	0.0	14.1	81.4	100	100	100.00	38	2783413200	22.1	22.6	23.4	24.0	7.8	35.4	20.0	bulk
952654	SRR2443129	SRP063829	SRS1073633	SRX1258030	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888157: Thymus_SCA1p_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Thymus|strain;;C57BL/6|tissue;;Thymus	GEO Accession;;GSM1888157		GSM1888157	Thymus_SCA1p_2	5616852800	28084264	2016-02-26 22:54:03	3878967566	5616852800	28084264	2	28084264	index:0,count:28084264,average:100,stdev:0|index:1,count:28084264,average:100,stdev:0	GSM1888157_r3				in_mesa	27183606	2.08	3.17	0.06	3224045645	3225864767	3072681942	3087563738	100.06	100.48	24080789	21797655	171.244	774.686	105	195379	89.64	94.28	26168144	21585679	26168144	21585679	90.62	91.12	26168144	21820935	26168144	20861492	169380942	5.25	1.15	0	4.22	0	0.24	0	0.05	0	0.00	0	13.96	0	24080789	0	200	0	190.47	0	1.52	0	0.01	0	1.17	0	0.00	0	346.24	0	0.20	0	322119	0	28084264	0	1185515	0	66347	0	15416	0	0	0	3921712	0	5336	0	0	0	83945	0	12928994	0	14008	0	13032283	0	81.52	0	22895274	0	129505	9989680	77.137407822092	28084264.0	24080789.0	322119.0	1185515.0	66347.0	15416.0	0.0	3921712.0	22895274.0	85.7	1.1	4.2	0.2	0.1	0.0	14.0	81.5	100	100	100.00	38	2808426400	22.1	22.6	23.5	24.0	7.8	35.5	20.2	bulk
952710	SRR2443130	SRP063829	SRS1073632	SRX1258031	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888158: Thymus_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Thymus|strain;;C57BL/6|tissue;;Thymus	GEO Accession;;GSM1888158		GSM1888158	Thymus_SCA1p_3	5249543200	26247716	2016-02-26 22:54:03	3624206425	5249543200	26247716	2	26247716	index:0,count:26247716,average:100,stdev:0|index:1,count:26247716,average:100,stdev:0	GSM1888158_r1				in_mesa	27183606	2.56	3.14	0.06	3138474454	3136294223	2975246413	2987617020	99.93	100.42	22975560	20827056	173.584	747.961	106	179209	89.76	94.92	25150840	20622020	25150840	20622020	91.22	91.77	25150840	20959177	25150840	19939046	141575339	4.51	1.25	0	4.76	0	0.26	0	0.06	0	0.00	0	12.15	0	22975560	0	200	0	191.28	0	1.52	0	0.01	0	1.20	0	0.00	0	306.79	0	0.20	0	327150	0	26247716	0	1249511	0	68159	0	15651	0	0	0	3188346	0	5222	0	0	0	78328	0	12286016	0	13277	0	12382843	0	82.77	0	21726049	0	147665	9665351	65.454583008838	26247716.0	22975560.0	327150.0	1249511.0	68159.0	15651.0	0.0	3188346.0	21726049.0	87.5	1.2	4.8	0.3	0.1	0.0	12.1	82.8	100	100	100.00	38	2624771600	22.3	22.8	23.5	24.6	6.8	35.5	20.1	bulk
952719	SRR2443131	SRP063829	SRS1073632	SRX1258031	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888158: Thymus_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Thymus|strain;;C57BL/6|tissue;;Thymus	GEO Accession;;GSM1888158		GSM1888158	Thymus_SCA1p_3	5238871400	26194357	2016-02-26 22:54:03	3611870653	5238871400	26194357	2	26194357	index:0,count:26194357,average:100,stdev:0|index:1,count:26194357,average:100,stdev:0	GSM1888158_r2				in_mesa	27183606	2.56	3.14	0.06	3126229135	3124220113	2963857120	2976129149	99.94	100.41	22905947	20762686	173.438	749.465	106	178807	89.76	94.92	25074778	20559975	25074778	20559975	91.22	91.77	25074778	20895578	25074778	19878584	140954957	4.51	1.25	0	4.75	0	0.26	0	0.06	0	0.00	0	12.23	0	22905947	0	200	0	191.27	0	1.52	0	0.01	0	1.20	0	0.00	0	287.50	0	0.19	0	327397	0	26194357	0	1244640	0	68058	0	15898	0	0	0	3204454	0	5174	0	0	0	77020	0	12260998	0	13163	0	12356355	0	82.69	0	21661307	0	147567	9637794	65.311309439102	26194357.0	22905947.0	327397.0	1244640.0	68058.0	15898.0	0.0	3204454.0	21661307.0	87.4	1.2	4.8	0.3	0.1	0.0	12.2	82.7	100	100	100.00	38	2619435700	22.3	22.7	23.5	24.6	6.9	35.6	20.3	bulk
952727	SRR2443132	SRP063829	SRS1073632	SRX1258031	SRA299328	GEO		RNA sequencing of primary thymic, bone and skin mesenchymal cells	Purpose : Elucidate post-natal role of SCA1+ thymic mesenchymal cells (tMCs) and evaluate the functional overlap between thymic, bone and skin MCs. Method : By high speed cell sorting, we isolated primary MCs (Lin- SCA1+ cells) from mouse thymus, bone and skin. We extracted their respective total RNA and compared their transcriptome by high-throughput RNA-sequencing. Results : We found a total of 2036 differentially expressed genes (FC>5, p-adj<0.1 and RPKM>1) between the 3 MC populations. IPA analyses revealed that each MC population was enriched for genes associated to phagocyte chemotaxis. We also denoted 2850 genes with shared expression across MC populations. IPA analysis of those shared genes also revealed an enrichment for genes influencing phagocyte migration, chemotaxis and function. Finally, MC transcriptomes showed that all 3 MC populations were expressing genes associated with hematopoietic stem and progenitor cell (HSPC) support, strongly suggesting that MCs from thymic, bone and skin all possess the ability to support HSPCs. Conclusion : Overall, our study highlighted 3 potential novel roles for tMCs : 1) Promoting macrophage/monocyte chemotaxis, 2) Enhacing the apoptotic cell clearance process and 3) setting an inviting niche for hematopoietic progenitors. These novel biological roles for tMCs could have substantial effets on thymic biology. Finally, our RNA-seq data offer a valuable resource to the community that can be mined to explore multiple questions related mesenchymal cell biology. Overall design: Transcriptome comparison between MC populations		GSM1888158: Thymus_SCA1p_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			(thymus MCs): Thymi were extracted, mechanically disrupted and enzymatically digested at 37oC for 3x15 minutes using 0.01% (w/v) Liberase TM (Roche) and 0.1% (w/v) DNase I (Sigma-Aldrich). Final digests were harvested, pooled and maintained at 4oC in FACS buffer (PBS, 0.1% (w/v) BSA, 0.02% (w/v) NaN3). Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Bone MCs) Femurs, tibias and pelvis were collected, cleaned and washed 3 times in cold PBS. Using sharp surgical scissors, each bone was first cut longitudinally and then transversely to generate tiny fragments of ~1 mm2.  Bone fragments were then washed 3 times in cold PBS and incubated with agitation (80 RPM) for 3x20 minutes at 37oC in the same enzymatic cocktail as above. Following each incubation, supernatants were added to HBSS medium (Invitrogen) supplemented with 2% (v/v) FBS, 10mM HEPES and 1% (v/v) penicillin-streptomycin. To further retrieve endosteal stromal cells, remaining bone fragments were gently crushed in supplemented HBSS medium using a pestle and mortar (5 x 50 gentle taps) and supernatants were pooled to previous ones. Red blood cell lysis was then performed on the resulting cell suspension prior to its filtration and resuspension in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). (Skin MCs) Mouse trunk and dorsal skin (~12 cm2 / mouse) was aseptically dissected and incubated for 45 minutes in 0.01% (w/v) liberase. Dermis was then mechanically isolated and incubated with agitation (80 RPM) at 37oC for 2x30 minutes in the same enzymatic cocktail as above. Post-incubation, supernatants were filtered and pooled to 25 mL of PBS supplemented with 1% FBS and 5mM EDTA. Final cell suspension was then centrifuged and resuspended in FACS buffer. Primary cells were then stained with monoclonal antibodies prior to being sorted by FACS directly in 300 ul of Trizol reagent. Sorted cells were sorted according to the cell surface phenotype Lin- SCA1+ (Lineage negative cocktail being CD45, CD2, CD4, CD11b, GR-1,  B220, TER119, CD41, EpCAM, CD31). A minimum of 25 000 primary sorted cells were used per sample. Total RNA was extracted using TRIzol reagent (Invitrogen) and further purified using the RNeasy micro kit (Qiagen). Transcriptome librairies were generated from total RNA using the TruSeq Stranded mRNA Library Prep Kit (Illumina) following the manufacturer’s protocol. Enrichment of RNA-seq stranded libraries with adapter molecules on both ends was done using 15 cycles of PCR amplification using the Illumina PCR mix and primers cocktail. Paired-end (2 x 100 bp) sequencing was peformed using the Illumina HiSeq 2000 running TruSeq v3 chemistry. Three RNA-seq librairies were sequenced per lane (8 lanes per flow cell).	Illumina HiSeq 2000	age;;3 to 4 wks-old|cell type;;Mesenchymal cells (Lin- SCA1+ cells)|source_name;;Thymus|strain;;C57BL/6|tissue;;Thymus	GEO Accession;;GSM1888158		GSM1888158	Thymus_SCA1p_3	5213010400	26065052	2016-02-26 22:54:03	3572742825	5213010400	26065052	2	26065052	index:0,count:26065052,average:100,stdev:0|index:1,count:26065052,average:100,stdev:0	GSM1888158_r3				in_mesa	27183606	2.57	3.14	0.06	3118127469	3116464404	2955975453	2968588215	99.95	100.43	22825375	20689501	173.615	749.808	106	177732	89.76	94.92	24986091	20488394	24986091	20488394	91.23	91.78	24986091	20822468	24986091	19809002	140625169	4.51	1.25	0	4.76	0	0.26	0	0.06	0	0.00	0	12.11	0	22825375	0	200	0	191.29	0	1.53	0	0.01	0	1.19	0	0.00	0	302.69	0	0.19	0	324578	0	26065052	0	1241177	0	67484	0	15706	0	0	0	3156487	0	5147	0	0	0	76778	0	12210625	0	13019	0	12305569	0	82.81	0	21584198	0	147530	9607089	65.119562122958	26065052.0	22825375.0	324578.0	1241177.0	67484.0	15706.0	0.0	3156487.0	21584198.0	87.6	1.2	4.8	0.3	0.1	0.0	12.1	82.8	100	100	100.00	38	2606505200	22.3	22.7	23.5	24.6	6.8	35.6	20.5	bulk
1803119	SRR2936836	SRP065767	SRS1145944	SRX1411331	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924968: P2_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924968		GSM1924968	P2_rep1_seq	2416487640	31795890	2016-06-21 16:03:06	1012972120	2416487640	31795890	1	31795890	index:0,count:31795890,average:76,stdev:0	GSM1924968_r1				in_mesa	27326930	2.61	3.43	0.08	2345980264	2311697683	2125175466	2116746585	98.54	99.6	0	0	0	0	0	0	75.49	83.31	36804878	23492321	36804878	23492321	79.2	79.53	36804878	24645403	36804878	22424764	337439337	14.38	0.34	0	9.19	0	0.53	0	0.32	0	0.00	0	1.28	0	31119584	0	76	0	75.37	0	1.64	0	0.01	0	1.21	0	0.01	0	1090.14	0	0.37	0	107517	0	31795890	0	2922079	0	167076	0	103138	0	0	0	406092	0	3117	0	0	0	24403	0	3613151	0	8321	0	3648992	0	88.68	0	28197505	0	179688	3804610	21.173422821780	31795890.0	31119584.0	107517.0	2922079.0	167076.0	103138.0	0.0	406092.0	28197505.0	97.9	0.3	9.2	0.5	0.3	0.0	1.3	88.7	76	76	76.00	39	2416487640	25.8	24.1	23.8	26.2	0.2	35.1	16.8	bulk
1803135	SRR2936837	SRP065767	SRS1145943	SRX1411332	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924969: P2_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924969		GSM1924969	P2_rep2_seq	2572243408	33845308	2016-06-21 16:03:06	1209172974	2572243408	33845308	1	33845308	index:0,count:33845308,average:76,stdev:0	GSM1924969_r1				in_mesa	27326930	2.81	3.53	0.09	2491059056	2419272643	2266799714	2223702849	97.12	98.1	0	0	0	0	0	0	74.26	81.59	38794840	24541411	38794840	24541411	77.97	78.22	38794840	25766410	38794840	23528130	370860952	14.89	0.45	0	8.77	0	0.56	0	0.36	0	0.00	0	1.44	0	33046125	0	76	0	75.36	0	1.52	0	0.00	0	1.19	0	0.00	0	1032.57	0	0.41	0	151360	0	33845308	0	2968074	0	190474	0	122521	0	0	0	486188	0	3487	0	0	0	27595	0	4067732	0	8929	0	4107743	0	88.87	0	30078051	0	183357	4279206	23.338110898411	33845308.0	33046125.0	151360.0	2968074.0	190474.0	122521.0	0.0	486188.0	30078051.0	97.6	0.4	8.8	0.6	0.4	0.0	1.4	88.9	76	76	76.00	39	2572243408	26.1	23.8	23.6	26.5	0.0	33.6	15.8	bulk
1803150	SRR2936838	SRP065767	SRS1145942	SRX1411333	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924970: P4_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924970		GSM1924970	P4_rep1_seq	2463295888	32411788	2016-06-21 16:03:06	1265476179	2463295888	32411788	1	32411788	index:0,count:32411788,average:76,stdev:0	GSM1924970_r1				in_mesa	27326930	3.42	3.36	0.1	2364645001	2313735917	2146407277	2125690867	97.85	99.03	0	0	0	0	0	0	74.98	82.59	36794157	23526479	36794157	23526479	78.63	79.14	36794157	24672147	36794157	22543655	348524385	14.74	0.34	0	8.91	0	0.45	0	0.32	0	0.00	0	2.43	0	31376235	0	76	0	75.35	0	1.96	0	0.01	0	1.37	0	0.00	0	833.45	0	0.44	0	111497	0	32411788	0	2888645	0	145103	0	103320	0	0	0	787130	0	2924	0	0	0	25222	0	3670979	0	7190	0	3706315	0	87.89	0	28487590	0	153117	3857986	25.196326991778	32411788.0	31376235.0	111497.0	2888645.0	145103.0	103320.0	0.0	787130.0	28487590.0	96.8	0.3	8.9	0.4	0.3	0.0	2.4	87.9	76	76	76.00	38	2463295888	26.1	23.5	23.5	26.9	0.0	34.7	18.4	bulk
1803165	SRR2936839	SRP065767	SRS1145941	SRX1411334	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924971: P4_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924971		GSM1924971	P4_rep2_seq	2317622812	30495037	2016-06-21 16:03:06	1176812774	2317622812	30495037	1	30495037	index:0,count:30495037,average:76,stdev:0	GSM1924971_r1				in_mesa	27326930	4.07	3.55	0.09	2172753011	2107667494	1969288836	1929625201	97.0	97.99	0	0	0	0	0	0	72.66	80.14	33765323	20941578	33765323	20941578	76.89	76.94	33765323	22162682	33765323	20104941	349225583	16.07	0.33	0	8.83	0	0.52	0	0.38	0	0.00	0	4.59	0	28823091	0	76	0	75.36	0	1.60	0	0.00	0	1.23	0	0.00	0	741.77	0	0.40	0	99855	0	30495037	0	2692926	0	157096	0	115784	0	0	0	1399066	0	2612	0	0	0	22662	0	3269587	0	6930	0	3301791	0	85.69	0	26130165	0	148584	3441269	23.160427771496	30495037.0	28823091.0	99855.0	2692926.0	157096.0	115784.0	0.0	1399066.0	26130165.0	94.5	0.3	8.8	0.5	0.4	0.0	4.6	85.7	76	76	76.00	38	2317622812	26.2	23.2	23.6	26.9	0.0	34.7	17.8	bulk
1803275	SRR2936840	SRP065767	SRS1145940	SRX1411335	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924972: P6_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924972		GSM1924972	P6_rep1_seq	2562943896	33722946	2016-06-21 16:03:06	1047041896	2562943896	33722946	1	33722946	index:0,count:33722946,average:76,stdev:0	GSM1924972_r1				in_mesa	27326930	5.79	3.12	0.09	2244570143	2113335426	1969195596	1887114497	94.15	95.83	0	0	0	0	0	0	67.38	76.79	36435400	20054162	36435400	20054162	71.66	72.32	36435400	21330515	36435400	18887968	360942297	16.08	0.70	0	10.82	0	0.50	0	0.36	0	0.00	0	10.88	0	29764466	0	76	0	75.40	0	2.88	0	0.01	0	1.71	0	0.01	0	697.72	0	0.30	0	235045	0	33722946	0	3648071	0	167866	0	120962	0	0	0	3669652	0	3076	0	0	0	22803	0	3205788	0	10581	0	3242248	0	77.44	0	26116395	0	158890	3377478	21.256705897162	33722946.0	29764466.0	235045.0	3648071.0	167866.0	120962.0	0.0	3669652.0	26116395.0	88.3	0.7	10.8	0.5	0.4	0.0	10.9	77.4	76	76	76.00	39	2562943896	25.6	24.3	23.7	26.4	0.0	36.0	18.0	bulk
1803295	SRR2936841	SRP065767	SRS1145939	SRX1411336	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924973: P6_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924973		GSM1924973	P6_rep2_seq	2292969780	30170655	2016-06-21 16:03:06	1043581397	2292969780	30170655	1	30170655	index:0,count:30170655,average:76,stdev:0	GSM1924973_r1				in_mesa	27326930	3.35	3.25	0.08	2190244929	2152509460	1987194453	1974344637	98.28	99.35	0	0	0	0	0	0	75.88	83.61	34076021	22060150	34076021	22060150	79.65	80.02	34076021	23156431	34076021	21111558	307234334	14.03	0.42	0	8.91	0	0.45	0	0.27	0	0.00	0	2.92	0	29073057	0	76	0	75.32	0	1.67	0	0.01	0	1.22	0	0.01	0	1015.09	0	0.50	0	127243	0	30170655	0	2689199	0	134636	0	82814	0	0	0	880148	0	3114	0	0	0	23156	0	3373598	0	7492	0	3407360	0	87.45	0	26383858	0	160122	3546530	22.148923945492	30170655.0	29073057.0	127243.0	2689199.0	134636.0	82814.0	0.0	880148.0	26383858.0	96.4	0.4	8.9	0.4	0.3	0.0	2.9	87.4	76	76	76.00	39	2292969780	26.2	24.0	23.5	26.3	0.0	33.0	14.1	bulk
1803311	SRR2936842	SRP065767	SRS1145938	SRX1411337	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924974: P6_rep3_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924974		GSM1924974	P6_rep3_seq	2327749280	30628280	2016-06-21 16:03:06	1206382927	2327749280	30628280	1	30628280	index:0,count:30628280,average:76,stdev:0	GSM1924974_r1				in_mesa	27326930	3.68	3.42	0.06	2206549843	2167286745	2009454946	1994138077	98.22	99.24	0	0	0	0	0	0	77.17	84.72	34017040	22596012	34017040	22596012	80.98	81.38	34017040	23710191	34017040	21705370	283753555	12.86	0.34	0	8.52	0	0.43	0	0.29	0	0.00	0	3.69	0	29280742	0	76	0	75.34	0	1.75	0	0.00	0	1.24	0	0.00	0	1081.00	0	0.41	0	102843	0	30628280	0	2608557	0	130486	0	87875	0	0	0	1129177	0	2930	0	0	0	24930	0	3548292	0	6797	0	3582949	0	87.08	0	26672185	0	148926	3716799	24.957354659361	30628280.0	29280742.0	102843.0	2608557.0	130486.0	87875.0	0.0	1129177.0	26672185.0	95.6	0.3	8.5	0.4	0.3	0.0	3.7	87.1	76	76	76.00	38	2327749280	26.2	23.3	23.6	26.9	0.0	34.4	17.8	bulk
1803327	SRR2936843	SRP065767	SRS1145967	SRX1411338	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924975: P10_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924975		GSM1924975	P10_rep1_seq	2807803052	36944777	2016-06-21 16:03:06	1097981821	2807803052	36944777	1	36944777	index:0,count:36944777,average:76,stdev:0	GSM1924975_r1				in_mesa	27326930	8.73	2.55	0.02	2643318700	2588342090	2270862557	2262982036	97.92	99.65	0	0	0	0	0	0	75.0	87.27	43261262	26297394	43261262	26297394	81.48	82.43	43261262	28567935	43261262	24838498	247787086	9.37	0.73	0	13.34	0	0.47	0	0.18	0	0.00	0	4.45	0	35063358	0	76	0	75.36	0	3.11	0	0.02	0	1.67	0	0.01	0	1047.25	0	0.29	0	270527	0	36944777	0	4929934	0	173549	0	64872	0	0	0	1642998	0	4034	0	0	0	28393	0	4275017	0	11015	0	4318459	0	81.56	0	30133424	0	155314	4485181	28.878150070180	36944777.0	35063358.0	270527.0	4929934.0	173549.0	64872.0	0.0	1642998.0	30133424.0	94.9	0.7	13.3	0.5	0.2	0.0	4.4	81.6	76	76	76.00	39	2807803052	25.2	24.0	24.4	26.4	0.0	36.1	18.4	bulk
1803359	SRR2936845	SRP065767	SRS1145965	SRX1411340	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924977: P10_rep3_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924977		GSM1924977	P10_rep3_seq	2741119512	36067362	2016-06-21 16:03:06	1193260359	2741119512	36067362	1	36067362	index:0,count:36067362,average:76,stdev:0	GSM1924977_r1				in_mesa	27326930	8.78	2.63	0.02	2548785084	2504168898	2188331145	2176938983	98.25	99.48	0	0	0	0	0	0	79.63	92.7	41795337	26946377	41795337	26946377	88.1	89.11	41795337	29811246	41795337	25904181	139074299	5.46	0.37	0	13.22	0	0.52	0	0.13	0	0.00	0	5.53	0	33838877	0	76	0	75.28	0	1.84	0	0.01	0	1.41	0	0.01	0	843.13	0	0.37	0	132464	0	36067362	0	4769629	0	186679	0	48210	0	0	0	1993596	0	4275	0	0	0	29027	0	4522569	0	9065	0	4564936	0	80.60	0	29069248	0	117739	4768500	40.500598782052	36067362.0	33838877.0	132464.0	4769629.0	186679.0	48210.0	0.0	1993596.0	29069248.0	93.8	0.4	13.2	0.5	0.1	0.0	5.5	80.6	76	76	76.00	39	2741119512	25.0	24.0	24.8	26.2	0.0	34.7	16.6	bulk
1803391	SRR2936847	SRP065767	SRS1145963	SRX1411342	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924979: P14_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924979		GSM1924979	P14_rep2_seq	2717536104	35757054	2016-06-21 16:03:06	1096634767	2717536104	35757054	1	35757054	index:0,count:35757054,average:76,stdev:0	GSM1924979_r1				in_mesa	27326930	6.29	2.7	0.02	2586557248	2554692203	2291570601	2286427282	98.77	99.78	0	0	0	0	0	0	84.36	95.18	40859900	28962240	40859900	28962240	90.97	92.06	40859900	31232146	40859900	28014988	94049342	3.64	0.35	0	10.91	0	0.59	0	0.14	0	0.00	0	3.26	0	34332747	0	76	0	75.31	0	1.60	0	0.00	0	1.33	0	0.01	0	1100.22	0	0.31	0	125294	0	35757054	0	3902602	0	209638	0	48662	0	0	0	1166007	0	4276	0	0	0	31483	0	4949056	0	8937	0	4993752	0	85.10	0	30430145	0	112071	5190786	46.316941938592	35757054.0	34332747.0	125294.0	3902602.0	209638.0	48662.0	0.0	1166007.0	30430145.0	96.0	0.4	10.9	0.6	0.1	0.0	3.3	85.1	76	76	76.00	39	2717536104	24.8	24.4	24.9	25.9	0.0	35.6	17.9	bulk
1803407	SRR2936848	SRP065767	SRS1145962	SRX1411343	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924980: P28_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924980		GSM1924980	P28_rep1_seq	2582699412	33982887	2016-06-21 16:03:06	1176097095	2582699412	33982887	1	33982887	index:0,count:33982887,average:76,stdev:0	GSM1924980_r1				in_mesa	27326930	10.06	2.74	0.02	2501657332	2453039516	2177765051	2173675754	98.06	99.81	0	0	0	0	0	0	82.31	94.52	39787156	27281382	39787156	27281382	88.59	90.6	39787156	29359901	39787156	26147771	90099389	3.60	0.54	0	12.60	0	0.45	0	0.16	0	0.00	0	1.86	0	33142784	0	76	0	75.45	0	3.16	0	0.01	0	1.59	0	0.01	0	955.77	0	0.32	0	182837	0	33982887	0	4280535	0	154364	0	54447	0	0	0	631292	0	3028	0	0	0	28126	0	4485429	0	7682	0	4524265	0	84.93	0	28862249	0	133799	4678263	34.964857734363	33982887.0	33142784.0	182837.0	4280535.0	154364.0	54447.0	0.0	631292.0	28862249.0	97.5	0.5	12.6	0.5	0.2	0.0	1.9	84.9	76	76	76.00	39	2582699412	26.2	23.4	23.9	26.4	0.1	34.1	16.5	bulk
1803535	SRR2936850	SRP065767	SRS1145960	SRX1411345	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924982: P28_rep3_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924982		GSM1924982	P28_rep3_seq	2461084060	32382685	2016-06-21 16:03:06	982246065	2461084060	32382685	1	32382685	index:0,count:32382685,average:76,stdev:0	GSM1924982_r1				in_mesa	27326930	8.18	2.59	0.02	2382498172	2361979768	2115061079	2115791731	99.14	100.03	0	0	0	0	0	0	86.26	97.12	37119070	27290083	37119070	27290083	93.4	94.42	37119070	29549869	37119070	26531260	52026070	2.18	0.37	0	10.93	0	0.65	0	0.13	0	0.00	0	1.52	0	31637258	0	76	0	75.27	0	1.63	0	0.00	0	1.30	0	0.01	0	1050.25	0	0.38	0	120024	0	32382685	0	3537930	0	210923	0	42650	0	0	0	491854	0	3506	0	0	0	27772	0	4788850	0	8126	0	4828254	0	86.77	0	28099328	0	120627	4990454	41.370953434969	32382685.0	31637258.0	120024.0	3537930.0	210923.0	42650.0	0.0	491854.0	28099328.0	97.7	0.4	10.9	0.7	0.1	0.0	1.5	86.8	76	76	76.00	39	2461084060	24.4	24.2	25.5	25.8	0.1	35.1	16.2	bulk
1803550	SRR2936851	SRP065767	SRS1145959	SRX1411346	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924983: P28_rep4_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924983		GSM1924983	P28_rep4_seq	2419871312	31840412	2016-06-21 16:03:06	937351772	2419871312	31840412	1	31840412	index:0,count:31840412,average:76,stdev:0	GSM1924983_r1				in_mesa	27326930	7.82	2.63	0.02	2336384543	2313149782	2081467645	2079857760	99.01	99.92	0	0	0	0	0	0	86.31	96.84	36299207	26777590	36299207	26777590	93.02	94.1	36299207	28859119	36299207	26020262	54030400	2.31	0.38	0	10.59	0	0.62	0	0.14	0	0.00	0	1.81	0	31023381	0	76	0	75.28	0	1.66	0	0.00	0	1.34	0	0.01	0	947.32	0	0.33	0	122438	0	31840412	0	3373043	0	198740	0	43338	0	0	0	574953	0	3604	0	0	0	28134	0	4645862	0	8059	0	4685659	0	86.84	0	27650338	0	114367	4834934	42.275603976672	31840412.0	31023381.0	122438.0	3373043.0	198740.0	43338.0	0.0	574953.0	27650338.0	97.4	0.4	10.6	0.6	0.1	0.0	1.8	86.8	76	76	76.00	39	2419871312	24.5	24.2	25.5	25.8	0.0	35.4	16.7	bulk
1803566	SRR2936852	SRP065767	SRS1145958	SRX1411347	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924984: P2KO_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924984		GSM1924984	P2KO_rep1_seq	3213566596	42283771	2016-06-21 16:03:06	1359146767	3213566596	42283771	1	42283771	index:0,count:42283771,average:76,stdev:0	GSM1924984_r1				in_mesa	27326930	2.88	3.36	0.06	2950371951	2871222476	2655357300	2616089478	97.32	98.52	0	0	0	0	0	0	76.19	84.64	46686587	29805126	46686587	29805126	79.93	80.67	46686587	31267206	46686587	28407915	358264233	12.14	0.39	0	9.24	0	0.46	0	0.27	0	0.00	0	6.75	0	39119847	0	76	0	75.40	0	2.02	0	0.01	0	1.59	0	0.01	0	1049.80	0	0.36	0	166310	0	42283771	0	3905048	0	194089	0	114489	0	0	0	2855346	0	4448	0	0	0	33049	0	4791111	0	11514	0	4840122	0	83.28	0	35214799	0	147528	5032957	34.115266254542	42283771.0	39119847.0	166310.0	3905048.0	194089.0	114489.0	0.0	2855346.0	35214799.0	92.5	0.4	9.2	0.5	0.3	0.0	6.8	83.3	76	76	76.00	39	3213566596	25.2	24.2	24.4	26.2	0.0	35.5	18.0	bulk
1803583	SRR2936853	SRP065767	SRS1145957	SRX1411348	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924985: P2KO_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924985		GSM1924985	P2KO_rep2_seq	2271628145	26725037	2016-06-21 16:03:06	741749063	2271628145	26725037	1	26725037	index:0,count:26725037,average:85,stdev:0	GSM1924985_r1				in_mesa	27326930	2.8	3.36	0.08	2207504469	2180054265	1937724003	1935293069	98.76	99.87	0	0	0	0	0	0	79.44	90.49	32277370	20758839	32277370	20758839	84.94	85.78	32277370	22196034	32277370	19678750	164908653	7.47	0.40	0	11.93	0	0.65	0	0.22	0	0.00	0	1.35	0	26130248	0	85	0	84.46	0	1.74	0	0.01	0	1.45	0	0.00	0	1105.86	0	0.19	0	106720	0	26725037	0	3188858	0	174650	0	59978	0	0	0	360161	0	3946	0	0	0	22459	0	3546455	0	8370	0	3581230	0	85.84	0	22941390	0	108499	3745146	34.517792790717	26725037.0	26130248.0	106720.0	3188858.0	174650.0	59978.0	0.0	360161.0	22941390.0	97.8	0.4	11.9	0.7	0.2	0.0	1.3	85.8	85	85	85.00	39	2271628145	25.1	24.5	24.4	26.0	0.0	37.3	20.5	bulk
1803598	SRR2936854	SRP065767	SRS1145956	SRX1411349	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924986: P4KO_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924986		GSM1924986	P4KO_rep1_seq	3702889708	48722233	2016-06-21 16:03:06	1503531837	3702889708	48722233	1	48722233	index:0,count:48722233,average:76,stdev:0	GSM1924986_r1				in_mesa	27326930	3.63	3.62	0.06	3224925956	3155491073	2882858388	2846670462	97.85	98.74	0	0	0	0	0	0	74.73	83.58	51329778	31932250	51329778	31932250	79.85	79.92	51329778	34120707	51329778	30535640	431142327	13.37	0.25	0	9.28	0	0.51	0	0.33	0	0.00	0	11.45	0	42730993	0	76	0	75.45	0	1.70	0	0.01	0	1.28	0	0.01	0	721.81	0	0.24	0	122061	0	48722233	0	4523599	0	249030	0	162029	0	0	0	5580181	0	4919	0	0	0	36801	0	5383065	0	12462	0	5437247	0	78.42	0	38207394	0	192183	5667930	29.492358845475	48722233.0	42730993.0	122061.0	4523599.0	249030.0	162029.0	0.0	5580181.0	38207394.0	87.7	0.3	9.3	0.5	0.3	0.0	11.5	78.4	76	76	76.00	39	3702889708	25.0	24.7	23.8	26.4	0.0	36.5	19.6	bulk
1803614	SRR2936855	SRP065767	SRS1145955	SRX1411350	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924987: P4KO_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924987		GSM1924987	P4KO_rep2_seq	3641629908	47916183	2016-06-21 16:03:06	1429906925	3641629908	47916183	1	47916183	index:0,count:47916183,average:76,stdev:0	GSM1924987_r1				in_mesa	27326930	3.51	3.57	0.1	3551094390	3477433003	3183488632	3148139823	97.93	98.89	0	0	0	0	0	0	75.71	84.43	56239190	35627082	56239190	35627082	80.91	81.06	56239190	38075640	56239190	34202596	459143757	12.93	0.34	0	10.14	0	0.54	0	0.37	0	0.00	0	0.88	0	47056488	0	76	0	75.44	0	1.69	0	0.01	0	1.30	0	0.01	0	974.57	0	0.25	0	161291	0	47916183	0	4859800	0	260195	0	176981	0	0	0	422519	0	6149	0	0	0	45030	0	6487515	0	13175	0	6551869	0	88.06	0	42196688	0	181134	6844534	37.787129970077	47916183.0	47056488.0	161291.0	4859800.0	260195.0	176981.0	0.0	422519.0	42196688.0	98.2	0.3	10.1	0.5	0.4	0.0	0.9	88.1	76	76	76.00	39	3641629908	26.5	23.4	23.4	26.6	0.0	36.2	18.7	bulk
1803630	SRR2936856	SRP065767	SRS1145954	SRX1411351	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924988: P6KO_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924988		GSM1924988	P6KO_rep1_seq	3383159608	44515258	2016-06-21 16:03:06	1486790967	3383159608	44515258	1	44515258	index:0,count:44515258,average:76,stdev:0	GSM1924988_r1				in_mesa	27326930	4.54	3.31	0.09	3296089227	3210201481	2930585269	2886676210	97.39	98.5	0	0	0	0	0	0	76.19	85.67	52493655	33279881	52493655	33279881	81.43	81.88	52493655	35566178	52493655	31804974	363384426	11.02	0.35	0	10.86	0	0.49	0	0.29	0	0.00	0	1.10	0	43679270	0	76	0	75.44	0	1.73	0	0.01	0	1.42	0	0.00	0	1090.17	0	0.34	0	157082	0	44515258	0	4834242	0	218235	0	129129	0	0	0	488624	0	4966	0	0	0	32371	0	4910450	0	12697	0	4960484	0	87.26	0	38845028	0	158075	5187672	32.817789024197	44515258.0	43679270.0	157082.0	4834242.0	218235.0	129129.0	0.0	488624.0	38845028.0	98.1	0.4	10.9	0.5	0.3	0.0	1.1	87.3	76	76	76.00	39	3383159608	26.0	23.3	24.1	26.6	0.0	34.7	17.4	bulk
1803645	SRR2936857	SRP065767	SRS1145953	SRX1411352	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924989: P6KO_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924989		GSM1924989	P6KO_rep2_seq	3562850816	46879616	2016-06-21 16:03:06	1477651070	3562850816	46879616	1	46879616	index:0,count:46879616,average:76,stdev:0	GSM1924989_r1				in_mesa	27326930	2.86	3.64	0.05	2974031748	2914032765	2726381384	2692318745	97.98	98.75	0	0	0	0	0	0	73.67	80.35	45532693	29033559	45532693	29033559	76.99	76.92	45532693	30340406	45532693	27794159	500099466	16.82	0.22	0	6.99	0	0.40	0	0.35	0	0.00	0	15.18	0	39408736	0	76	0	75.45	0	1.69	0	0.01	0	1.29	0	0.01	0	627.39	0	0.23	0	104284	0	46879616	0	3276170	0	188999	0	164047	0	0	0	7117834	0	4385	0	0	0	33793	0	4811888	0	10593	0	4860659	0	77.08	0	36132566	0	174512	5045824	28.913908499129	46879616.0	39408736.0	104284.0	3276170.0	188999.0	164047.0	0.0	7117834.0	36132566.0	84.1	0.2	7.0	0.4	0.3	0.0	15.2	77.1	76	76	76.00	39	3562850816	24.9	25.0	23.7	26.4	0.0	36.5	19.8	bulk
1803662	SRR2936858	SRP065767	SRS1145952	SRX1411353	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924990: P6KO_rep3_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924990		GSM1924990	P6KO_rep3_seq	3748986596	49328771	2016-06-21 16:03:06	1580874979	3748986596	49328771	1	49328771	index:0,count:49328771,average:76,stdev:0	GSM1924990_r1				in_mesa	27326930	3.38	3.32	0.09	3275996347	3205061547	2992367818	2950706521	97.83	98.61	0	0	0	0	0	0	74.91	82.0	50287964	32517599	50287964	32517599	78.6	78.61	50287964	34116723	50287964	31172294	493148592	15.05	0.23	0	7.60	0	0.40	0	0.27	0	0.00	0	11.33	0	43407491	0	76	0	75.46	0	1.65	0	0.01	0	1.29	0	0.01	0	688.31	0	0.24	0	113487	0	49328771	0	3750992	0	197018	0	135031	0	0	0	5589231	0	5025	0	0	0	38185	0	5397662	0	11903	0	5452775	0	80.39	0	39656499	0	184622	5654754	30.628819967285	49328771.0	43407491.0	113487.0	3750992.0	197018.0	135031.0	0.0	5589231.0	39656499.0	88.0	0.2	7.6	0.4	0.3	0.0	11.3	80.4	76	76	76.00	39	3748986596	25.1	24.7	23.8	26.4	0.0	36.0	19.0	bulk
1803678	SRR2936859	SRP065767	SRS1145951	SRX1411354	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924991: P10KO_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924991		GSM1924991	P10KO_rep1_seq	3388852236	44590161	2016-06-21 16:03:06	1482794010	3388852236	44590161	1	44590161	index:0,count:44590161,average:76,stdev:0	GSM1924991_r1				in_mesa	27326930	4.82	3.29	0.07	3301643877	3206454346	2944819615	2895533937	97.12	98.33	0	0	0	0	0	0	76.21	85.42	52243201	33339997	52243201	33339997	81.11	81.71	52243201	35484886	52243201	31888649	369780168	11.20	0.37	0	10.58	0	0.46	0	0.26	0	0.00	0	1.17	0	43748193	0	76	0	75.45	0	1.81	0	0.01	0	1.48	0	0.01	0	1263.97	0	0.34	0	162929	0	44590161	0	4719438	0	205032	0	115118	0	0	0	521818	0	4951	0	0	0	31905	0	4708283	0	12086	0	4757225	0	87.53	0	39028755	0	146529	4970135	33.919121812065	44590161.0	43748193.0	162929.0	4719438.0	205032.0	115118.0	0.0	521818.0	39028755.0	98.1	0.4	10.6	0.5	0.3	0.0	1.2	87.5	76	76	76.00	39	3388852236	26.2	23.2	24.0	26.6	0.0	34.8	17.5	bulk
1803807	SRR2936861	SRP065767	SRS1145949	SRX1411356	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924993: P10KO_rep3_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924993		GSM1924993	P10KO_rep3_seq	3615501336	47572386	2016-06-21 16:03:06	1407706920	3615501336	47572386	1	47572386	index:0,count:47572386,average:76,stdev:0	GSM1924993_r1				in_mesa	27326930	3.27	3.59	0.07	3531368864	3427708817	3254184561	3181781035	97.06	97.78	0	0	0	0	0	0	73.67	79.93	53411154	34474962	53411154	34474962	77.01	76.92	53411154	36037275	53411154	33175221	583310573	16.52	0.32	0	7.70	0	0.44	0	0.38	0	0.00	0	0.82	0	46794733	0	76	0	75.45	0	1.66	0	0.01	0	1.33	0	0.01	0	1083.93	0	0.25	0	150616	0	47572386	0	3665252	0	207013	0	180644	0	0	0	389996	0	6169	0	0	0	46630	0	6365998	0	12789	0	6431586	0	90.66	0	43129481	0	180032	6677788	37.092228048347	47572386.0	46794733.0	150616.0	3665252.0	207013.0	180644.0	0.0	389996.0	43129481.0	98.4	0.3	7.7	0.4	0.4	0.0	0.8	90.7	76	76	76.00	39	3615501336	26.4	23.5	23.6	26.5	0.0	36.3	19.1	bulk
1803839	SRR2936863	SRP065767	SRS1145947	SRX1411358	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924995: P14KO_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924995		GSM1924995	P14KO_rep2_seq	3244489248	42690648	2016-06-21 16:03:06	1295477272	3244489248	42690648	1	42690648	index:0,count:42690648,average:76,stdev:0	GSM1924995_r1				in_mesa	27326930	3.38	3.4	0.07	2867568746	2797371710	2653959964	2605414356	97.55	98.17	0	0	0	0	0	0	77.09	83.28	42898735	29308481	42898735	29308481	79.76	79.82	42898735	30325420	42898735	28091950	387581615	13.52	0.26	0	6.62	0	0.40	0	0.34	0	0.00	0	10.21	0	38020417	0	76	0	75.41	0	1.67	0	0.01	0	1.29	0	0.01	0	701.76	0	0.24	0	108965	0	42690648	0	2826293	0	169411	0	143358	0	0	0	4357462	0	4431	0	0	0	32756	0	4791988	0	10778	0	4839953	0	82.44	0	35194124	0	162366	5003541	30.816433243413	42690648.0	38020417.0	108965.0	2826293.0	169411.0	143358.0	0.0	4357462.0	35194124.0	89.1	0.3	6.6	0.4	0.3	0.0	10.2	82.4	76	76	76.00	39	3244489248	24.8	24.9	24.2	26.1	0.0	36.5	19.8	bulk
1803871	SRR2936865	SRP065767	SRS1145945	SRX1411360	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924997: P28KO_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924997		GSM1924997	P28KO_rep2_seq	3711873060	48840435	2016-06-21 16:03:06	1459760278	3711873060	48840435	1	48840435	index:0,count:48840435,average:76,stdev:0	GSM1924997_r1				in_mesa	27326930	2.99	4.1	0.06	3611250419	3466732312	3385982896	3268388606	96.0	96.53	0	0	0	0	0	0	71.9	76.67	53091001	34410596	53091001	34410596	73.87	73.71	53091001	35357112	53091001	33083022	681947394	18.88	0.33	0	6.10	0	0.46	0	0.52	0	0.00	0	1.02	0	47861239	0	76	0	75.44	0	1.66	0	0.01	0	1.31	0	0.01	0	1092.08	0	0.26	0	161708	0	48840435	0	2979730	0	225159	0	253431	0	0	0	500606	0	5493	0	0	0	43866	0	6209241	0	13271	0	6271871	0	91.89	0	44881509	0	159482	6483514	40.653578460265	48840435.0	47861239.0	161708.0	2979730.0	225159.0	253431.0	0.0	500606.0	44881509.0	98.0	0.3	6.1	0.5	0.5	0.0	1.0	91.9	76	76	76.00	39	3711873060	26.1	23.8	24.0	26.1	0.0	36.1	18.7	bulk
3606674	SRR2936844	SRP065767	SRS1145966	SRX1411339	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924976: P10_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924976		GSM1924976	P10_rep2_seq	2639848904	34734854	2016-06-21 16:03:06	1039159983	2639848904	34734854	1	34734854	index:0,count:34734854,average:76,stdev:0	GSM1924976_r1				in_mesa	27326930	14.5	2.45	0.02	2539891111	2517675482	2101768683	2105107985	99.13	100.16	0	0	0	0	0	0	79.2	95.63	42524360	26680944	42524360	26680944	91.76	92.34	42524360	30912447	42524360	25761988	85520203	3.37	0.42	0	16.67	0	0.57	0	0.11	0	0.00	0	2.33	0	33689884	0	76	0	75.34	0	1.44	0	0.00	0	1.22	0	0.01	0	811.98	0	0.31	0	145726	0	34734854	0	5791120	0	197274	0	39742	0	0	0	807954	0	4219	0	0	0	29283	0	4588809	0	9603	0	4631914	0	80.32	0	27898764	0	155649	4836063	31.070312048262	34734854.0	33689884.0	145726.0	5791120.0	197274.0	39742.0	0.0	807954.0	27898764.0	97.0	0.4	16.7	0.6	0.1	0.0	2.3	80.3	76	76	76.00	39	2639848904	25.0	23.1	24.9	27.0	0.0	35.8	17.9	bulk
3606736	SRR2936846	SRP065767	SRS1145964	SRX1411341	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924978: P14_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924978		GSM1924978	P14_rep1_seq	2864154848	37686248	2016-06-21 16:03:06	1173467332	2864154848	37686248	1	37686248	index:0,count:37686248,average:76,stdev:0	GSM1924978_r1				in_mesa	27326930	7.59	2.67	0.02	2718907242	2660717929	2365869337	2356381576	97.86	99.6	0	0	0	0	0	0	79.22	91.01	43809706	28564260	43809706	28564260	84.82	86.4	43809706	30585484	43809706	27118688	165776304	6.10	0.70	0	12.40	0	0.51	0	0.17	0	0.00	0	3.64	0	36058494	0	76	0	75.38	0	3.25	0	0.02	0	1.64	0	0.01	0	976.05	0	0.29	0	265395	0	37686248	0	4671943	0	191697	0	63144	0	0	0	1372913	0	3812	0	0	0	30458	0	4619674	0	10572	0	4664516	0	83.28	0	31386551	0	147150	4836015	32.864525993884	37686248.0	36058494.0	265395.0	4671943.0	191697.0	63144.0	0.0	1372913.0	31386551.0	95.7	0.7	12.4	0.5	0.2	0.0	3.6	83.3	76	76	76.00	39	2864154848	25.3	23.9	24.4	26.4	0.1	35.6	18.0	bulk
3606832	SRR2936849	SRP065767	SRS1145961	SRX1411344	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924981: P28_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924981		GSM1924981	P28_rep2_seq	2634483684	34664259	2016-06-21 16:03:06	1063721295	2634483684	34664259	1	34664259	index:0,count:34664259,average:76,stdev:0	GSM1924981_r1				in_mesa	27326930	9.9	2.5	0.02	2543569880	2520155301	2233112017	2233533076	99.08	100.02	0	0	0	0	0	0	85.45	97.28	39917468	28841501	39917468	28841501	93.78	94.73	39917468	31653774	39917468	28085178	53151818	2.09	0.49	0	11.84	0	0.66	0	0.11	0	0.00	0	1.85	0	33753922	0	76	0	75.32	0	1.40	0	0.00	0	1.26	0	0.01	0	1014.56	0	0.35	0	168831	0	34664259	0	4104946	0	228738	0	38911	0	0	0	642688	0	3504	0	0	0	28399	0	4987726	0	9056	0	5028685	0	85.53	0	29648976	0	126836	5194310	40.952962881201	34664259.0	33753922.0	168831.0	4104946.0	228738.0	38911.0	0.0	642688.0	29648976.0	97.4	0.5	11.8	0.7	0.1	0.0	1.9	85.5	76	76	76.00	39	2634483684	24.6	23.7	25.5	26.2	0.0	35.5	17.6	bulk
3607568	SRR2936860	SRP065767	SRS1145950	SRX1411355	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924992: P10KO_rep2_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924992		GSM1924992	P10KO_rep2_seq	3538809128	46563278	2016-06-21 16:03:06	1478387775	3538809128	46563278	1	46563278	index:0,count:46563278,average:76,stdev:0	GSM1924992_r1				in_mesa	27326930	2.77	3.26	0.09	2983675178	2875318808	2747451982	2672641444	96.37	97.28	0	0	0	0	0	0	73.52	79.83	45338128	29073734	45338128	29073734	76.0	76.31	45338128	30053148	45338128	27790287	474813669	15.91	0.25	0	6.71	0	0.43	0	0.37	0	0.00	0	14.28	0	39543605	0	76	0	75.44	0	1.86	0	0.01	0	1.36	0	0.01	0	748.34	0	0.25	0	114473	0	46563278	0	3125935	0	198354	0	172052	0	0	0	6649267	0	4497	0	0	0	32895	0	4749492	0	10863	0	4797747	0	78.21	0	36417670	0	169968	4978442	29.290466440742	46563278.0	39543605.0	114473.0	3125935.0	198354.0	172052.0	0.0	6649267.0	36417670.0	84.9	0.2	6.7	0.4	0.4	0.0	14.3	78.2	76	76	76.00	39	3538809128	24.9	25.0	23.9	26.2	0.0	36.3	19.6	bulk
3607632	SRR2936862	SRP065767	SRS1145948	SRX1411357	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924994: P14KO_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924994		GSM1924994	P14KO_rep1_seq	3269072436	43014111	2016-06-21 16:03:06	1494528273	3269072436	43014111	1	43014111	index:0,count:43014111,average:76,stdev:0	GSM1924994_r1				in_mesa	27326930	4.57	3.41	0.08	3149679305	3030667622	2875563178	2795874927	96.22	97.23	0	0	0	0	0	0	73.07	80.02	48055344	30496337	48055344	30496337	76.49	76.75	48055344	31923310	48055344	29250485	494034453	15.69	0.34	0	8.43	0	0.45	0	0.41	0	0.00	0	2.11	0	41736892	0	76	0	75.45	0	1.99	0	0.01	0	1.53	0	0.01	0	980.07	0	0.35	0	147300	0	43014111	0	3625975	0	191717	0	175839	0	0	0	909663	0	4261	0	0	0	31513	0	4507849	0	10705	0	4554328	0	88.60	0	38110917	0	138795	4736095	34.122951114954	43014111.0	41736892.0	147300.0	3625975.0	191717.0	175839.0	0.0	909663.0	38110917.0	97.0	0.3	8.4	0.4	0.4	0.0	2.1	88.6	76	76	76.00	39	3269072436	26.3	23.2	23.8	26.7	0.0	34.2	16.9	bulk
3607696	SRR2936864	SRP065767	SRS1145946	SRX1411359	SRA309283	GEO		Recruitment of Rod Photoreceptors from Short Wavelength Sensitive Cones during the Evolution of Nocturnal Vision in Mammals	Vertebrate ancestors had only cone-like photoreceptors. The duplex retina evolved in jawless vertebrates with the advent of highly photosensitive rod-like photoreceptors. Despite cones being the arbiters of high-resolution color vision, rods emerged as the dominant photoreceptor in mammals during a nocturnal phase early in their evolution. We investigated the evolutionary and developmental origins of rods in two divergent vertebrate retinae. In mice, we discovered genetic and epigenetic vestiges of short wavelength cones in developing rods and cell lineage tracing validated the genesis of rods from S-cones. Curiously, rods did not derive from S-cones in zebrafish. Our study illuminates several questions regarding the evolution of duplex retina and supports the hypothesis that, in mammals, the S-cone lineage was recruited via the Maf-family transcription factor NRL to augment rod photoreceptors. We propose that this developmental mechanism allowed the adaptive exploitation of scotopic niches during the nocturnal bottleneck early in mammalian evolution. Overall design: GFP positive cells from Nrlp-GFP or Nrlp-GFP;Nrl-KO mouse retinas at post-natal ages P2, P4, P6, P10, P14, and P28 were isolated by flow sorting by FACSAria II (Becton Dickinson). Total RNA was extracted by Trizol LS (Life Technologies) and analyzed by 2100 Bioanalyzer (Agilent Technologies Genomics). High quality of total RNA (RIN: >7.0) was subjected to sequencing library construction using 20 ng of total RNA as input. Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter.		GSM1924996: P28KO_rep1_seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Total RNA was extracted by Trizol LS (Life Tech). Libraries were constructed using a stranded modification of the Illumina TruSeq mRNA (Brooks, et al. Meth Mol Biol 2012). Each library was single-end sequenced in an independent lane of a GAIIx at a length of 76 bases.  Fastq files were generated from reads passing chastity filter. Stranded mRNA-seq (dUTP method)	Illumina Genome Analyzer IIx	cell type;;GFP positive retina cells|genotype;;Nrlp-GFP;Nrl-/-|source_name;;retina|strain;;C57BL/6	GEO Accession;;GSM1924996		GSM1924996	P28KO_rep1_seq	3044100504	40053954	2016-06-21 16:03:06	1395051406	3044100504	40053954	1	40053954	index:0,count:40053954,average:76,stdev:0	GSM1924996_r1				in_mesa	27326930	5.23	3.87	0.11	2948252719	2720178896	2683030359	2496976316	92.26	93.07	0	0	0	0	0	0	66.41	72.97	45098686	25933408	45098686	25933408	70.24	69.98	45098686	27428124	45098686	24872682	546219979	18.53	0.35	0	8.76	0	0.70	0	0.65	0	0.00	0	1.17	0	39048990	0	76	0	75.49	0	1.74	0	0.01	0	1.47	0	0.01	0	833.49	0	0.36	0	138691	0	40053954	0	3508214	0	279421	0	258795	0	0	0	466748	0	3598	0	0	0	23896	0	3558128	0	10471	0	3596093	0	88.73	0	35540776	0	143711	3782109	26.317463520538	40053954.0	39048990.0	138691.0	3508214.0	279421.0	258795.0	0.0	466748.0	35540776.0	97.5	0.3	8.8	0.7	0.6	0.0	1.2	88.7	76	76	76.00	39	3044100504	26.8	22.6	23.8	26.7	0.0	34.3	17.2	bulk
1572888	SRR2926001	SRP066154	SRS1161566	SRX1427340	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937811: CD8_92 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_93|cousin 2;;CD8_94|hours since division;;7.4|sister;;CD8_91|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937811		GSM1937811	CD8_92 scRNA-seq	114926528	1795727	2015-12-22 15:48:11	57166363	114926528	1795727	2	1795727	index:0,count:1795727,average:32,stdev:0|index:1,count:1795727,average:32,stdev:0	GSM1937811_r1						1.87	2.13	0.08	80930264	90365526	66491881	77699528	111.66	116.86	1404387	1271631	208.022	943.946	100	6530	70.13	85.39	1830867	984926	1830867	984926	63.12	64.96	1830867	886395	1830867	749328	8722085	10.78	1.99	0	13.97	0	0.55	0	0.31	0	0.00	0	20.93	0	1404387	0	64	0	58.05	0	1.15	0	0.00	0	1.02	0	0.01	0	359.15	0	0.75	0	35726	0	1795727	0	250928	0	9909	0	5585	0	0	0	375846	0	21	0	0	0	170	0	21834	0	1217	0	23242	0	64.23	0	1153459	0	10849	19507	1.798045902848	1795727.0	1404387.0	35726.0	250928.0	9909.0	5585.0	0.0	375846.0	1153459.0	78.2	2.0	14.0	0.6	0.3	0.0	20.9	64.2	32	32	32.00	6	57463264	22.1	23.6	24.9	21.6	7.8	30.2	13.7	smartseq
1572905	SRR2926002	SRP066154	SRS1161565	SRX1427341	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937812: CD8_93 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_91|cousin 2;;CD8_92|hours since division;;6.6|sister;;CD8_94|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937812		GSM1937812	CD8_93 scRNA-seq	26744832	417888	2015-12-22 15:48:11	14342273	26744832	417888	2	417888	index:0,count:417888,average:32,stdev:0|index:1,count:417888,average:32,stdev:0	GSM1937812_r1						1.67	2.51	0.05	18293152	20702348	14613887	17296131	113.17	118.35	316286	276038	229.396	1225.123	143	1344	74.13	92.69	437926	234472	437926	234472	71.5	72.26	437926	226136	437926	182788	971310	5.31	1.90	0	15.16	0	0.70	0	0.22	0	0.00	0	23.39	0	316286	0	64	0	57.89	0	1.14	0	0.00	0	1.01	0	0.01	0	100.29	0	0.85	0	7947	0	417888	0	63333	0	2936	0	908	0	0	0	97758	0	7	0	0	0	36	0	5676	0	383	0	6102	0	60.53	0	252953	0	3334	4774	1.431913617277	417888.0	316286.0	7947.0	63333.0	2936.0	908.0	0.0	97758.0	252953.0	75.7	1.9	15.2	0.7	0.2	0.0	23.4	60.5	32	32	32.00	6	13372416	21.1	24.1	26.1	21.0	7.7	29.2	13.5	smartseq
1572920	SRR2926003	SRP066154	SRS1161564	SRX1427342	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937813: CD8_94 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_91|cousin 2;;CD8_92|hours since division;;6.6167|sister;;CD8_93|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937813		GSM1937813	CD8_94 scRNA-seq	208596224	3259316	2015-12-22 15:48:11	102807501	208596224	3259316	2	3259316	index:0,count:3259316,average:32,stdev:0|index:1,count:3259316,average:32,stdev:0	GSM1937813_r1						1.61	3.11	0.07	151715013	163052330	115362157	129905275	107.47	112.61	2635592	2227784	207.076	1223.011	110	11749	72.43	95.16	3954600	1909022	3954600	1909022	79.24	80.5	3954600	2088569	3954600	1614924	6403331	4.22	1.65	0	19.32	0	0.97	0	0.34	0	0.00	0	17.82	0	2635592	0	64	0	58.01	0	1.21	0	0.00	0	1.01	0	0.01	0	391.12	0	0.66	0	53906	0	3259316	0	629562	0	31714	0	11061	0	0	0	580949	0	75	0	0	0	504	0	70677	0	1579	0	72835	0	61.55	0	2006030	0	18043	70669	3.916698996841	3259316.0	2635592.0	53906.0	629562.0	31714.0	11061.0	0.0	580949.0	2006030.0	80.9	1.7	19.3	1.0	0.3	0.0	17.8	61.5	32	32	32.00	6	104298112	22.5	23.2	24.5	22.0	7.8	30.3	13.7	smartseq
1572936	SRR2926004	SRP066154	SRS1161563	SRX1427343	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937814: CD8_95 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_96|cousin 2;;CD8_98|hours since division;;3.7333|sister;;CD8_97|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937814		GSM1937814	CD8_95 scRNA-seq	83372096	1302689	2015-12-22 15:48:11	43265512	83372096	1302689	2	1302689	index:0,count:1302689,average:32,stdev:0|index:1,count:1302689,average:32,stdev:0	GSM1937814_r1						2.37	2.01	0.04	59540333	69071568	47686055	58513437	116.01	122.71	1029008	942964	201.492	822.658	117	5265	72.34	90.28	1379263	744346	1379263	744346	62.98	64.77	1379263	648092	1379263	534036	4123042	6.92	2.16	0	15.70	0	0.59	0	0.17	0	0.00	0	20.25	0	1029008	0	64	0	58.05	0	1.15	0	0.00	0	1.01	0	0.01	0	293.11	0	0.80	0	28132	0	1302689	0	204506	0	7700	0	2229	0	0	0	263752	0	16	0	0	0	127	0	14396	0	1195	0	15734	0	63.29	0	824502	0	7120	12899	1.811657303371	1302689.0	1029008.0	28132.0	204506.0	7700.0	2229.0	0.0	263752.0	824502.0	79.0	2.2	15.7	0.6	0.2	0.0	20.2	63.3	32	32	32.00	6	41686048	21.6	24.0	25.3	21.3	7.7	29.8	13.6	smartseq
1572953	SRR2926005	SRP066154	SRS1161562	SRX1427344	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937815: CD8_96 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_95|cousin 2;;CD8_97|hours since division;;3.6|sister;;CD8_98|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937815		GSM1937815	CD8_96 scRNA-seq	85458112	1335283	2015-12-22 15:48:11	43317939	85458112	1335283	2	1335283	index:0,count:1335283,average:32,stdev:0|index:1,count:1335283,average:32,stdev:0	GSM1937815_r1						2.26	1.96	0.09	61499962	69929129	50861178	60531593	113.71	119.01	1065555	970964	206.305	890.595	100	5085	70.29	85.02	1371707	749031	1371707	749031	61.12	63.06	1371707	651229	1371707	555522	7117262	11.57	2.00	0	13.82	0	0.56	0	0.25	0	0.00	0	19.38	0	1065555	0	64	0	58.10	0	1.12	0	0.00	0	1.02	0	0.01	0	300.44	0	0.74	0	26712	0	1335283	0	184572	0	7510	0	3385	0	0	0	258833	0	16	0	0	0	132	0	15718	0	984	0	16850	0	65.98	0	880983	0	8551	13648	1.596070635013	1335283.0	1065555.0	26712.0	184572.0	7510.0	3385.0	0.0	258833.0	880983.0	79.8	2.0	13.8	0.6	0.3	0.0	19.4	66.0	32	32	32.00	6	42729056	21.9	23.7	25.0	21.6	7.8	30.0	13.7	smartseq
1572968	SRR2926006	SRP066154	SRS1161561	SRX1427345	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937816: CD8_97 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_96|cousin 2;;CD8_98|hours since division;;3.7833|sister;;CD8_95|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937816		GSM1937816	CD8_97 scRNA-seq	8831488	137992	2015-12-22 15:48:11	4809485	8831488	137992	2	137992	index:0,count:137992,average:32,stdev:0|index:1,count:137992,average:32,stdev:0	GSM1937816_r1						2.18	1.6	0.04	5239844	5935763	4434790	5183079	113.28	116.87	91068	83275	252.521	1017.447	210	385	73.59	86.9	113265	67020	113265	67020	66.26	68.24	113265	60344	113265	52625	491509	9.38	1.96	0	10.11	0	0.33	0	0.13	0	0.00	0	33.54	0	91068	0	64	0	57.58	0	1.19	0	0.00	0	1.02	0	0.02	0	62.10	0	0.99	0	2700	0	137992	0	13947	0	456	0	185	0	0	0	46283	0	0	0	0	0	7	0	900	0	175	0	1082	0	55.89	0	77121	0	633	677	1.069510268562	137992.0	91068.0	2700.0	13947.0	456.0	185.0	0.0	46283.0	77121.0	66.0	2.0	10.1	0.3	0.1	0.0	33.5	55.9	32	32	32.00	6	4415744	20.0	24.0	28.9	19.4	7.7	28.5	13.5	smartseq
1572984	SRR2926007	SRP066154	SRS1161560	SRX1427346	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937817: CD8_98 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_95|cousin 2;;CD8_97|hours since division;;3.65|sister;;CD8_96|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937817		GSM1937817	CD8_98 scRNA-seq	27489856	429529	2015-12-22 15:48:11	14194086	27489856	429529	2	429529	index:0,count:429529,average:32,stdev:0|index:1,count:429529,average:32,stdev:0	GSM1937817_r1						2.65	2.19	0.08	18854905	21296891	15018067	17833010	112.95	118.74	328243	308231	166.012	649.995	98	2104	70.78	88.9	443469	232325	443469	232325	63.62	66.35	443469	208840	443469	173404	1521396	8.07	1.85	0	15.58	0	0.63	0	0.23	0	0.00	0	22.72	0	328243	0	64	0	58.05	0	1.23	0	0.00	0	1.02	0	0.02	0	103.09	0	0.86	0	7926	0	429529	0	66906	0	2703	0	985	0	0	0	97598	0	0	0	0	0	40	0	4270	0	362	0	4672	0	60.84	0	261337	0	2592	3649	1.407793209877	429529.0	328243.0	7926.0	66906.0	2703.0	985.0	0.0	97598.0	261337.0	76.4	1.8	15.6	0.6	0.2	0.0	22.7	60.8	32	32	32.00	6	13744928	21.8	23.9	25.3	21.3	7.7	29.6	13.6	smartseq
1573000	SRR2926008	SRP066154	SRS1161559	SRX1427347	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937818: CD8_99 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_101|cousin 2;;CD8_102|hours since division;;5.2431|sister;;CD8_100|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937818		GSM1937818	CD8_99 scRNA-seq	195035904	3047436	2015-12-22 15:48:11	95044842	195035904	3047436	2	3047436	index:0,count:3047436,average:32,stdev:0|index:1,count:3047436,average:32,stdev:0	GSM1937818_r1						3.08	3.0	0.04	141445673	151974700	108113650	121707894	107.44	112.57	2456620	2049057	227.931	1565.172	100	9182	71.71	93.74	3666010	1761602	3666010	1761602	78.6	79.32	3666010	1930916	3666010	1490561	7670011	5.42	1.75	0	18.95	0	0.93	0	0.30	0	0.00	0	18.15	0	2456620	0	64	0	58.02	0	1.17	0	0.00	0	1.01	0	0.01	0	378.30	0	0.58	0	53284	0	3047436	0	577337	0	28381	0	9210	0	0	0	553225	0	80	0	0	0	424	0	62963	0	1446	0	64913	0	61.67	0	1879283	0	15906	62804	3.948447126870	3047436.0	2456620.0	53284.0	577337.0	28381.0	9210.0	0.0	553225.0	1879283.0	80.6	1.7	18.9	0.9	0.3	0.0	18.2	61.7	32	32	32.00	6	97517952	22.7	22.8	24.2	22.5	7.8	30.7	13.8	smartseq
1573016	SRR2926009	SRP066154	SRS1161558	SRX1427348	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937819: CD8_100 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_101|cousin 2;;CD8_102|hours since division;;5.2603|sister;;CD8_99|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937819		GSM1937819	CD8_100 scRNA-seq	264362880	4130670	2015-12-22 15:48:11	128596445	264362880	4130670	2	4130670	index:0,count:4130670,average:32,stdev:0|index:1,count:4130670,average:32,stdev:0	GSM1937819_r1						2.4	1.95	0.08	190020731	211884909	157845209	183844793	111.51	116.47	3296187	2921500	223.245	1062.990	100	13262	70.71	85.14	4238537	2330689	4238537	2330689	64.07	66.03	4238537	2111969	4238537	1807564	22061022	11.61	2.00	0	13.53	0	0.58	0	0.27	0	0.00	0	19.35	0	3296187	0	64	0	58.06	0	1.16	0	0.00	0	1.02	0	0.01	0	464.70	0	0.63	0	82585	0	4130670	0	558810	0	23998	0	11258	0	0	0	799227	0	52	0	0	0	405	0	57734	0	2558	0	60749	0	66.27	0	2737377	0	21401	54202	2.532685388533	4130670.0	3296187.0	82585.0	558810.0	23998.0	11258.0	0.0	799227.0	2737377.0	79.8	2.0	13.5	0.6	0.3	0.0	19.3	66.3	32	32	32.00	6	132181440	22.4	23.3	24.7	21.9	7.8	30.7	13.8	smartseq
1573128	SRR2926010	SRP066154	SRS1161556	SRX1427349	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937820: CD8_101 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_99|cousin 2;;CD8_100|hours since division;;5.4833|sister;;CD8_102|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937820		GSM1937820	CD8_101 scRNA-seq	231486016	3616969	2015-12-22 15:48:11	112578824	231486016	3616969	2	3616969	index:0,count:3616969,average:32,stdev:0|index:1,count:3616969,average:32,stdev:0	GSM1937820_r1						2.01	2.65	0.09	163790729	168576308	136629146	145371811	102.92	106.4	2841344	2530360	219.681	1128.184	100	11568	62.74	75.24	3694284	1782667	3694284	1782667	60.04	60.87	3694284	1705836	3694284	1442248	26322437	16.07	1.82	0	13.05	0	0.72	0	0.64	0	0.00	0	20.09	0	2841344	0	64	0	58.10	0	1.12	0	0.00	0	1.02	0	0.01	0	351.92	0	0.62	0	65913	0	3616969	0	471947	0	26036	0	23030	0	0	0	726559	0	37	0	0	0	327	0	47285	0	1912	0	49561	0	65.51	0	2369397	0	18915	44256	2.339730372720	3616969.0	2841344.0	65913.0	471947.0	26036.0	23030.0	0.0	726559.0	2369397.0	78.6	1.8	13.0	0.7	0.6	0.0	20.1	65.5	32	32	32.00	6	115743008	23.0	22.7	24.2	22.4	7.8	30.7	13.8	smartseq
1573144	SRR2926011	SRP066154	SRS1161557	SRX1427350	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937821: CD8_102 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_99|cousin 2;;CD8_100|hours since division;;5.5|sister;;CD8_101|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937821		GSM1937821	CD8_102 scRNA-seq	262200640	4096885	2015-12-22 15:48:11	127770036	262200640	4096885	2	4096885	index:0,count:4096885,average:32,stdev:0|index:1,count:4096885,average:32,stdev:0	GSM1937821_r1						2.42	3.15	0.05	189379986	200804062	145802070	161529338	106.03	110.79	3287827	2711200	224.275	1519.740	110	12325	71.47	92.73	4883506	2349700	4883506	2349700	79.06	79.8	4883506	2599224	4883506	2022083	11790925	6.23	1.68	0	18.40	0	1.04	0	0.48	0	0.00	0	18.23	0	3287827	0	64	0	57.97	0	1.14	0	0.00	0	1.01	0	0.01	0	409.69	0	0.58	0	68837	0	4096885	0	753869	0	42654	0	19479	0	0	0	746925	0	89	0	0	0	621	0	91039	0	2027	0	93776	0	61.85	0	2533958	0	24415	90195	3.694245340979	4096885.0	3287827.0	68837.0	753869.0	42654.0	19479.0	0.0	746925.0	2533958.0	80.3	1.7	18.4	1.0	0.5	0.0	18.2	61.9	32	32	32.00	6	131100320	22.8	22.7	24.2	22.4	7.8	30.7	13.8	smartseq
1573209	SRR2926015	SRP066154	SRS1161552	SRX1427354	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937825: CD8_106 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_104|cousin 2;;CD8_105|hours since division;;5.6139|sister;;CD8_103|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937825		GSM1937825	CD8_106 scRNA-seq	190803712	2981308	2015-12-22 15:48:11	92799797	190803712	2981308	2	2981308	index:0,count:2981308,average:32,stdev:0|index:1,count:2981308,average:32,stdev:0	GSM1937825_r1						2.46	2.55	0.04	138415357	153151539	109112875	126667322	110.65	116.09	2402766	2090468	221.300	1179.312	100	9886	70.91	89.93	3419222	1703873	3419222	1703873	70.56	70.85	3419222	1695314	3419222	1342397	10064795	7.27	1.92	0	17.04	0	1.01	0	0.39	0	0.00	0	18.01	0	2402766	0	64	0	58.08	0	1.17	0	0.00	0	1.01	0	0.01	0	357.76	0	0.59	0	57371	0	2981308	0	508150	0	30168	0	11589	0	0	0	536785	0	39	0	0	0	311	0	50579	0	1569	0	52498	0	63.55	0	1894616	0	13783	49658	3.602844083291	2981308.0	2402766.0	57371.0	508150.0	30168.0	11589.0	0.0	536785.0	1894616.0	80.6	1.9	17.0	1.0	0.4	0.0	18.0	63.5	32	32	32.00	6	95401856	22.3	23.4	24.8	21.8	7.8	30.7	13.8	smartseq
1606186	SRR2925822	SRP066154	SRS1161744	SRX1427161	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937632: L1210_1 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_24|cousin 2;;L1210_35|hours since division;;6.7614|sister;;L1210_13|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937632		GSM1937632	L1210_1 scRNA-seq	109695168	1713987	2015-12-22 15:48:11	52953642	109695168	1713987	2	1713987	index:0,count:1713987,average:32,stdev:0|index:1,count:1713987,average:32,stdev:0	GSM1937632_r1						3.41	2.06	0.35	78732124	84434120	63874956	71704188	107.24	112.26	1360959	1192511	215.008	1223.053	125	6706	69.2	85.27	1816251	941805	1816251	941805	66.94	69.24	1816251	911014	1816251	764801	8644008	10.98	1.99	0	14.96	0	0.74	0	0.59	0	0.00	0	19.27	0	1360959	0	64	0	58.04	0	1.23	0	0.00	0	1.02	0	0.01	0	293.83	0	0.66	0	34129	0	1713987	0	256440	0	12636	0	10190	0	0	0	330202	0	25	0	0	0	197	0	25974	0	1109	0	27305	0	64.44	0	1104519	0	12420	23321	1.877697262480	1713987.0	1360959.0	34129.0	256440.0	12636.0	10190.0	0.0	330202.0	1104519.0	79.4	2.0	15.0	0.7	0.6	0.0	19.3	64.4	32	32	32.00	6	54847584	22.5	23.1	24.6	22.0	7.8	30.9	13.8	smartseq
1606203	SRR2925823	SRP066154	SRS1161745	SRX1427162	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937633: L1210_2 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_14|cousin 2;;L1210_80|hours since division;;2.5833|sister;;L1210_69|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937633		GSM1937633	L1210_2 scRNA-seq	77057728	1204027	2015-12-22 15:48:11	37286020	77057728	1204027	2	1204027	index:0,count:1204027,average:32,stdev:0|index:1,count:1204027,average:32,stdev:0	GSM1937633_r1						3.32	1.72	0.36	54572994	60210976	44581166	51757617	110.33	116.1	943276	849212	213.294	1080.552	125	4713	69.16	84.65	1225728	652334	1225728	652334	62.0	64.89	1225728	584791	1225728	500057	6199918	11.36	2.22	0	14.34	0	0.59	0	0.39	0	0.00	0	20.67	0	943276	0	64	0	58.07	0	1.25	0	0.00	0	1.02	0	0.02	0	309.61	0	0.68	0	26742	0	1204027	0	172618	0	7095	0	4753	0	0	0	248903	0	25	0	0	0	122	0	14342	0	861	0	15350	0	64.01	0	770658	0	8019	12381	1.543958099514	1204027.0	943276.0	26742.0	172618.0	7095.0	4753.0	0.0	248903.0	770658.0	78.3	2.2	14.3	0.6	0.4	0.0	20.7	64.0	32	32	32.00	6	38528864	22.4	23.2	24.8	21.9	7.7	30.9	13.8	smartseq
1606218	SRR2925824	SRP066154	SRS1161743	SRX1427163	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937634: L1210_3 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_26|cousin 2;;L1210_37|hours since division;;8.1333|sister;;L1210_15|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937634		GSM1937634	L1210_3 scRNA-seq	81985536	1281024	2015-12-22 15:48:11	39701975	81985536	1281024	2	1281024	index:0,count:1281024,average:32,stdev:0|index:1,count:1281024,average:32,stdev:0	GSM1937634_r1						3.55	1.95	0.19	58508094	63854214	47563674	54478691	109.14	114.54	1011017	895319	218.770	1177.557	117	4853	68.01	83.65	1329393	687641	1329393	687641	62.94	65.29	1329393	636356	1329393	536761	6943318	11.87	2.16	0	14.75	0	0.76	0	0.57	0	0.00	0	19.74	0	1011017	0	64	0	58.06	0	1.21	0	0.00	0	1.02	0	0.01	0	288.23	0	0.65	0	27645	0	1281024	0	188942	0	9706	0	7363	0	0	0	252938	0	23	0	0	0	136	0	17496	0	943	0	18598	0	64.17	0	822075	0	9355	15305	1.636023516836	1281024.0	1011017.0	27645.0	188942.0	9706.0	7363.0	0.0	252938.0	822075.0	78.9	2.2	14.7	0.8	0.6	0.0	19.7	64.2	32	32	32.00	6	40992768	22.7	22.9	24.5	22.2	7.7	30.9	13.8	smartseq
1606234	SRR2925825	SRP066154	SRS1161742	SRX1427164	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937635: L1210_4 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_27|cousin 2;;L1210_38|hours since division;;2.7936|sister;;L1210_16|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937635		GSM1937635	L1210_4 scRNA-seq	66129024	1033266	2015-12-22 15:48:11	32036437	66129024	1033266	2	1033266	index:0,count:1033266,average:32,stdev:0|index:1,count:1033266,average:32,stdev:0	GSM1937635_r1						3.25	1.73	0.29	46194916	51719362	37563207	44446485	111.96	118.32	798875	721851	212.311	1079.339	125	4224	69.3	85.21	1046556	553598	1046556	553598	60.45	63.16	1046556	482934	1046556	410315	5007089	10.84	2.26	0	14.44	0	0.53	0	0.47	0	0.00	0	21.69	0	798875	0	64	0	58.03	0	1.21	0	0.00	0	1.02	0	0.01	0	206.65	0	0.70	0	23361	0	1033266	0	149189	0	5450	0	4870	0	0	0	224071	0	17	0	0	0	97	0	11716	0	696	0	12526	0	62.88	0	649686	0	6750	9924	1.470222222222	1033266.0	798875.0	23361.0	149189.0	5450.0	4870.0	0.0	224071.0	649686.0	77.3	2.3	14.4	0.5	0.5	0.0	21.7	62.9	32	32	32.00	6	33064512	22.4	23.2	24.9	21.8	7.7	30.9	13.8	smartseq
1606296	SRR2925829	SRP066154	SRS1161738	SRX1427168	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937639: L1210_8 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;10.35|sister;;L1210_84|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937639		GSM1937639	L1210_8 scRNA-seq	23820096	372189	2015-12-22 15:48:11	11647744	23820096	372189	2	372189	index:0,count:372189,average:32,stdev:0|index:1,count:372189,average:32,stdev:0	GSM1937639_r1						0.31	0.54	0.01	5858456	7334120	4435863	6219858	125.19	140.22	101638	99897	222.373	506.099	174	591	69.45	91.66	129978	70592	129978	70592	43.27	48.51	129978	43979	129978	37357	137869	2.35	2.01	0	6.62	0	0.01	0	0.00	0	0.00	0	72.68	0	101638	0	64	0	57.69	0	1.27	0	0.01	0	1.01	0	0.01	0	53.60	0	1.24	0	7473	0	372189	0	24626	0	55	0	1	0	0	0	270495	0	0	0	0	0	2	0	90	0	10	0	102	0	20.69	0	77012	0	50	57	1.140000000000	372189.0	101638.0	7473.0	24626.0	55.0	1.0	0.0	270495.0	77012.0	27.3	2.0	6.6	0.0	0.0	0.0	72.7	20.7	32	32	32.00	6	11910048	24.1	21.6	23.3	23.2	7.7	30.8	13.8	smartseq
1606425	SRR2925831	SRP066154	SRS1161736	SRX1427170	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937641: L1210_10 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_21|cousin 2;;L1210_43|hours since division;;2.7667|sister;;L1210_32|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937641		GSM1937641	L1210_10 scRNA-seq	59932672	936448	2015-12-22 15:48:11	28732025	59932672	936448	2	936448	index:0,count:936448,average:32,stdev:0|index:1,count:936448,average:32,stdev:0	GSM1937641_r1						3.1	2.17	0.26	38373650	35447629	29745741	29547995	92.37	99.34	667511	612992	189.121	1112.583	129	5598	50.03	64.76	980172	333943	980172	333943	45.52	49.94	980172	303843	980172	257543	7976562	20.79	2.19	0	16.21	0	0.68	0	0.82	0	0.00	0	27.22	0	667511	0	64	0	58.00	0	1.19	0	0.00	0	1.03	0	0.01	0	168.56	0	0.72	0	20473	0	936448	0	151826	0	6353	0	7682	0	0	0	254902	0	7	0	0	0	58	0	6848	0	548	0	7461	0	55.07	0	515685	0	4379	5795	1.323361498059	936448.0	667511.0	20473.0	151826.0	6353.0	7682.0	0.0	254902.0	515685.0	71.3	2.2	16.2	0.7	0.8	0.0	27.2	55.1	32	32	32.00	6	29966336	25.0	20.7	22.6	24.1	7.6	31.0	13.9	smartseq
1606440	SRR2925832	SRP066154	SRS1161735	SRX1427171	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937642: L1210_11 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_33|cousin 2;;L1210_44|hours since division;;1.7744|sister;;L1210_22|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937642		GSM1937642	L1210_11 scRNA-seq	46125504	720711	2015-12-22 15:48:11	22336154	46125504	720711	2	720711	index:0,count:720711,average:32,stdev:0|index:1,count:720711,average:32,stdev:0	GSM1937642_r1						7.85	2.06	1.68	30160898	31329458	23679634	25975991	103.87	109.7	522895	465862	210.691	2102.339	125	2490	64.9	82.68	745237	339347	745237	339347	65.96	68.36	745237	344905	745237	280574	3947663	13.09	2.40	0	15.60	0	1.12	0	1.58	0	0.00	0	24.75	0	522895	0	64	0	57.98	0	1.24	0	0.00	0	1.02	0	0.01	0	162.16	0	0.74	0	17263	0	720711	0	112448	0	8060	0	11391	0	0	0	178365	0	8	0	0	0	54	0	7876	0	449	0	8387	0	56.95	0	410447	0	4693	6615	1.409546132538	720711.0	522895.0	17263.0	112448.0	8060.0	11391.0	0.0	178365.0	410447.0	72.6	2.4	15.6	1.1	1.6	0.0	24.7	57.0	32	32	32.00	6	23062752	22.9	22.7	24.4	22.3	7.7	30.8	13.8	smartseq
1606456	SRR2925833	SRP066154	SRS1161734	SRX1427172	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937643: L1210_12 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;11.7167|sister;;L1210_23|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937643		GSM1937643	L1210_12 scRNA-seq	96147008	1502297	2015-12-22 15:48:11	46585411	96147008	1502297	2	1502297	index:0,count:1502297,average:32,stdev:0|index:1,count:1502297,average:32,stdev:0	GSM1937643_r1						3.48	1.92	0.34	68614881	74369794	55414994	63037501	108.39	113.76	1186430	1048487	215.329	1145.684	125	5763	69.46	85.98	1585655	824125	1585655	824125	66.33	68.82	1585655	786980	1585655	659605	7261747	10.58	2.04	0	15.17	0	0.79	0	0.46	0	0.00	0	19.78	0	1186430	0	64	0	58.04	0	1.22	0	0.00	0	1.02	0	0.01	0	318.13	0	0.67	0	30686	0	1502297	0	227923	0	11845	0	6912	0	0	0	297110	0	21	0	0	0	186	0	21224	0	1048	0	22479	0	63.80	0	958507	0	10584	18668	1.763794406652	1502297.0	1186430.0	30686.0	227923.0	11845.0	6912.0	0.0	297110.0	958507.0	79.0	2.0	15.2	0.8	0.5	0.0	19.8	63.8	32	32	32.00	6	48073504	22.5	23.1	24.7	22.0	7.8	30.9	13.8	smartseq
1606489	SRR2925835	SRP066154	SRS1161732	SRX1427174	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937645: L1210_14 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_2|cousin 2;;L1210_69|hours since division;;2.5|sister;;L1210_80|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937645		GSM1937645	L1210_14 scRNA-seq	59787008	934172	2015-12-22 15:48:11	29509724	59787008	934172	2	934172	index:0,count:934172,average:32,stdev:0|index:1,count:934172,average:32,stdev:0	GSM1937645_r1						3.81	1.96	0.37	42707142	46188263	34685005	39345358	108.15	113.44	737739	659722	204.903	1073.432	117	3776	69.51	85.56	970356	512812	970356	512812	65.23	68.22	970356	481209	970356	408877	4528186	10.60	2.04	0	14.81	0	0.66	0	0.47	0	0.00	0	19.90	0	737739	0	64	0	58.07	0	1.19	0	0.00	0	1.02	0	0.01	0	224.20	0	0.67	0	19097	0	934172	0	138374	0	6178	0	4396	0	0	0	185859	0	16	0	0	0	107	0	12945	0	621	0	13689	0	64.16	0	599365	0	7374	11064	1.500406834825	934172.0	737739.0	19097.0	138374.0	6178.0	4396.0	0.0	185859.0	599365.0	79.0	2.0	14.8	0.7	0.5	0.0	19.9	64.2	32	32	32.00	6	29893504	22.4	22.9	24.6	22.3	7.7	30.5	13.8	smartseq
1606505	SRR2925836	SRP066154	SRS1161731	SRX1427175	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937646: L1210_15 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_26|cousin 2;;L1210_37|hours since division;;8.1556|sister;;L1210_3|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937646		GSM1937646	L1210_15 scRNA-seq	59179584	924681	2015-12-22 15:48:11	28968222	59179584	924681	2	924681	index:0,count:924681,average:32,stdev:0|index:1,count:924681,average:32,stdev:0	GSM1937646_r1						2.22	0.57	0.06	36555562	43074747	31238400	38625623	117.83	123.65	631538	617681	187.807	466.237	146	3878	79.57	93.19	755208	502533	755208	502533	61.26	65.79	755208	386889	755208	354767	1170622	3.20	2.11	0	9.98	0	0.21	0	0.17	0	0.00	0	31.32	0	631538	0	64	0	58.16	0	1.35	0	0.01	0	1.02	0	0.02	0	221.92	0	0.68	0	19536	0	924681	0	92298	0	1911	0	1605	0	0	0	289627	0	6	0	0	0	19	0	2118	0	532	0	2675	0	58.32	0	539240	0	1038	1893	1.823699421965	924681.0	631538.0	19536.0	92298.0	1911.0	1605.0	0.0	289627.0	539240.0	68.3	2.1	10.0	0.2	0.2	0.0	31.3	58.3	32	32	32.00	6	29589792	22.4	23.1	24.9	21.9	7.7	30.6	13.8	smartseq
1606520	SRR2925837	SRP066154	SRS1161730	SRX1427176	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937647: L1210_16 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_27|cousin 2;;L1210_38|hours since division;;2.8078|sister;;L1210_4|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937647		GSM1937647	L1210_16 scRNA-seq	49458112	772783	2015-12-22 15:48:11	24182764	49458112	772783	2	772783	index:0,count:772783,average:32,stdev:0|index:1,count:772783,average:32,stdev:0	GSM1937647_r1						3.36	1.86	0.29	34866579	38178479	28280737	32620514	109.5	115.35	602431	545079	201.585	1104.251	125	3326	68.21	84.09	790898	410918	790898	410918	61.89	64.76	790898	372843	790898	316459	4125406	11.83	2.22	0	14.72	0	0.57	0	0.60	0	0.00	0	20.88	0	602431	0	64	0	58.09	0	1.22	0	0.00	0	1.02	0	0.01	0	185.47	0	0.68	0	17150	0	772783	0	113750	0	4393	0	4610	0	0	0	161349	0	11	0	0	0	75	0	9226	0	538	0	9850	0	63.24	0	488681	0	5606	7849	1.400107028184	772783.0	602431.0	17150.0	113750.0	4393.0	4610.0	0.0	161349.0	488681.0	78.0	2.2	14.7	0.6	0.6	0.0	20.9	63.2	32	32	32.00	6	24729056	22.6	22.9	24.6	22.3	7.7	30.6	13.8	smartseq
1606536	SRR2925838	SRP066154	SRS1161729	SRX1427177	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937648: L1210_17 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_28|cousin 2;;L1210_39|hours since division;;3.9386|sister;;L1210_5|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937648		GSM1937648	L1210_17 scRNA-seq	57410240	897035	2015-12-22 15:48:11	28119614	57410240	897035	2	897035	index:0,count:897035,average:32,stdev:0|index:1,count:897035,average:32,stdev:0	GSM1937648_r1						4.61	2.03	0.37	40937666	44439008	33157427	37778597	108.55	113.94	707614	628118	203.464	1221.747	117	3706	69.49	85.76	940591	491703	940591	491703	65.57	68.03	940591	463978	940591	390037	4370025	10.67	2.11	0	14.97	0	0.64	0	0.63	0	0.00	0	19.85	0	707614	0	64	0	58.08	0	1.23	0	0.00	0	1.02	0	0.01	0	189.96	0	0.67	0	18941	0	897035	0	134295	0	5719	0	5651	0	0	0	178051	0	17	0	0	0	121	0	12996	0	582	0	13716	0	63.91	0	573319	0	7553	11208	1.483913676685	897035.0	707614.0	18941.0	134295.0	5719.0	5651.0	0.0	178051.0	573319.0	78.9	2.1	15.0	0.6	0.6	0.0	19.8	63.9	32	32	32.00	6	28705120	22.7	22.7	24.3	22.6	7.7	30.6	13.8	smartseq
1606552	SRR2925839	SRP066154	SRS1161728	SRX1427178	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937649: L1210_18 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_6|cousin 2;;L1210_29|hours since division;;1.1333|sister;;L1210_82|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937649		GSM1937649	L1210_18 scRNA-seq	60564992	946328	2015-12-22 15:48:11	29815079	60564992	946328	2	946328	index:0,count:946328,average:32,stdev:0|index:1,count:946328,average:32,stdev:0	GSM1937649_r1						4.38	1.69	0.19	43511073	47513037	35601550	40791281	109.2	114.58	751532	681679	199.371	973.022	117	4158	68.61	83.83	966785	515597	966785	515597	62.05	64.95	966785	466320	966785	399490	5042440	11.59	2.17	0	14.42	0	0.52	0	0.40	0	0.00	0	19.67	0	751532	0	64	0	58.11	0	1.21	0	0.00	0	1.03	0	0.01	0	200.40	0	0.67	0	20514	0	946328	0	136491	0	4885	0	3781	0	0	0	186130	0	17	0	0	0	82	0	11569	0	684	0	12352	0	64.99	0	615041	0	6864	9850	1.435023310023	946328.0	751532.0	20514.0	136491.0	4885.0	3781.0	0.0	186130.0	615041.0	79.4	2.2	14.4	0.5	0.4	0.0	19.7	65.0	32	32	32.00	6	30282496	22.7	22.8	24.4	22.4	7.7	30.5	13.8	smartseq
1606664	SRR2925840	SRP066154	SRS1161727	SRX1427179	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937650: L1210_19 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_83|cousin 2;;L1210_30|hours since division;;0.8083|sister;;L1210_7|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937650		GSM1937650	L1210_19 scRNA-seq	59847040	935110	2015-12-22 15:48:11	29204220	59847040	935110	2	935110	index:0,count:935110,average:32,stdev:0|index:1,count:935110,average:32,stdev:0	GSM1937650_r1						3.87	1.96	0.37	43012419	47094760	34844416	40101636	109.49	115.09	743106	669184	202.322	1029.265	117	3887	68.97	85.12	982153	512502	982153	512502	63.1	65.46	982153	468895	982153	394146	4443445	10.33	2.16	0	15.08	0	0.65	0	0.52	0	0.00	0	19.36	0	743106	0	64	0	58.11	0	1.25	0	0.00	0	1.02	0	0.01	0	240.46	0	0.66	0	20171	0	935110	0	141007	0	6087	0	4881	0	0	0	181036	0	15	0	0	0	90	0	12229	0	643	0	12977	0	64.39	0	602099	0	6900	10454	1.515072463768	935110.0	743106.0	20171.0	141007.0	6087.0	4881.0	0.0	181036.0	602099.0	79.5	2.2	15.1	0.7	0.5	0.0	19.4	64.4	32	32	32.00	6	29923520	22.6	22.8	24.4	22.4	7.7	30.6	13.8	smartseq
1606680	SRR2925841	SRP066154	SRS1161726	SRX1427180	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937651: L1210_20 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_31|cousin 2;;L1210_42|hours since division;;5.2167|sister;;L1210_9|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937651		GSM1937651	L1210_20 scRNA-seq	65640384	1025631	2015-12-22 15:48:11	32038452	65640384	1025631	2	1025631	index:0,count:1025631,average:32,stdev:0|index:1,count:1025631,average:32,stdev:0	GSM1937651_r1						5.44	2.11	0.43	46361688	48360138	38710724	41897108	104.31	108.23	801234	707306	205.255	1248.668	125	4043	66.2	79.27	1039813	530434	1039813	530434	64.62	66.31	1039813	517737	1039813	443668	7472354	16.12	1.87	0	12.88	0	0.75	0	0.61	0	0.00	0	20.52	0	801234	0	64	0	58.08	0	1.22	0	0.00	0	1.02	0	0.01	0	205.13	0	0.67	0	19135	0	1025631	0	132106	0	7698	0	6255	0	0	0	210444	0	21	0	0	0	142	0	15105	0	605	0	15873	0	65.24	0	669128	0	8847	12970	1.466033683735	1025631.0	801234.0	19135.0	132106.0	7698.0	6255.0	0.0	210444.0	669128.0	78.1	1.9	12.9	0.8	0.6	0.0	20.5	65.2	32	32	32.00	6	32820192	23.0	22.5	24.1	22.6	7.7	30.6	13.8	smartseq
1606697	SRR2925842	SRP066154	SRS1161725	SRX1427181	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937652: L1210_21 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_10|cousin 2;;L1210_32|hours since division;;0.5667|sister;;L1210_43|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937652		GSM1937652	L1210_21 scRNA-seq	50153408	783647	2015-12-22 15:48:11	25068113	50153408	783647	2	783647	index:0,count:783647,average:32,stdev:0|index:1,count:783647,average:32,stdev:0	GSM1937652_r1						3.94	1.93	0.26	35233472	38083285	28752819	32668646	108.09	113.62	608877	554514	197.623	1008.556	125	3376	67.44	82.63	790147	410612	790147	410612	60.29	63.42	790147	367094	790147	315164	4097390	11.63	2.18	0	14.29	0	0.58	0	0.62	0	0.00	0	21.10	0	608877	0	64	0	58.08	0	1.20	0	0.00	0	1.02	0	0.02	0	217.01	0	0.69	0	17075	0	783647	0	111946	0	4575	0	4833	0	0	0	165362	0	8	0	0	0	57	0	8894	0	598	0	9557	0	63.41	0	496931	0	5403	7412	1.371830464557	783647.0	608877.0	17075.0	111946.0	4575.0	4833.0	0.0	165362.0	496931.0	77.7	2.2	14.3	0.6	0.6	0.0	21.1	63.4	32	32	32.00	6	25076704	22.6	22.7	24.5	22.5	7.7	30.4	13.8	smartseq
1606776	SRR2925847	SRP066154	SRS1161720	SRX1427186	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937657: L1210_26 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_3|cousin 2;;L1210_15|hours since division;;7.85|sister;;L1210_37|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937657		GSM1937657	L1210_26 scRNA-seq	62285312	973208	2015-12-22 15:48:11	30463589	62285312	973208	2	973208	index:0,count:973208,average:32,stdev:0|index:1,count:973208,average:32,stdev:0	GSM1937657_r1						0.16	1.59	0.06	42578460	49237882	34758170	42525426	115.64	122.35	734915	665756	224.005	881.216	125	3579	76.5	93.68	941678	562179	941678	562179	64.95	69.0	941678	477298	941678	414079	1438663	3.38	2.27	0	13.85	0	0.40	0	0.19	0	0.00	0	23.89	0	734915	0	64	0	58.07	0	1.27	0	0.01	0	1.02	0	0.02	0	218.97	0	0.74	0	22049	0	973208	0	134794	0	3926	0	1884	0	0	0	232483	0	18	0	0	0	56	0	10236	0	815	0	11125	0	61.66	0	600121	0	4703	9203	1.956836062088	973208.0	734915.0	22049.0	134794.0	3926.0	1884.0	0.0	232483.0	600121.0	75.5	2.3	13.9	0.4	0.2	0.0	23.9	61.7	32	32	32.00	6	31142656	22.0	23.8	25.2	21.3	7.7	30.7	13.8	smartseq
1606792	SRR2925848	SRP066154	SRS1161719	SRX1427187	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937658: L1210_27 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_4|cousin 2;;L1210_16|hours since division;;4.4183|sister;;L1210_38|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937658		GSM1937658	L1210_27 scRNA-seq	55091904	860811	2015-12-22 15:48:11	26876246	55091904	860811	2	860811	index:0,count:860811,average:32,stdev:0|index:1,count:860811,average:32,stdev:0	GSM1937658_r1						26.69	1.1	0.14	37225123	40089249	30890516	34590994	107.69	111.98	641861	605641	203.345	649.659	125	3385	76.12	91.74	800763	488567	800763	488567	73.23	75.92	800763	470054	800763	404314	1764291	4.74	1.50	0	12.69	0	0.35	0	0.26	0	0.00	0	24.82	0	641861	0	64	0	58.23	0	1.23	0	0.00	0	1.01	0	0.01	0	238.38	0	0.70	0	12887	0	860811	0	109279	0	3043	0	2273	0	0	0	213634	0	6	0	0	0	46	0	5389	0	395	0	5836	0	61.87	0	532582	0	3082	4613	1.496755353666	860811.0	641861.0	12887.0	109279.0	3043.0	2273.0	0.0	213634.0	532582.0	74.6	1.5	12.7	0.4	0.3	0.0	24.8	61.9	32	32	32.00	6	27545952	24.3	21.9	23.4	22.9	7.6	30.7	13.8	smartseq
1606809	SRR2925849	SRP066154	SRS1161718	SRX1427188	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937659: L1210_28 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_5|cousin 2;;L1210_17|hours since division;;3.7819|sister;;L1210_39|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937659		GSM1937659	L1210_28 scRNA-seq	62968704	983886	2015-12-22 15:48:11	30886887	62968704	983886	2	983886	index:0,count:983886,average:32,stdev:0|index:1,count:983886,average:32,stdev:0	GSM1937659_r1						2.92	1.95	0.31	44433840	48125260	36380234	41270900	108.31	113.44	768426	669515	218.616	1328.435	125	3667	70.98	86.66	1010557	545402	1010557	545402	66.67	69.57	1010557	512278	1010557	437867	4389992	9.88	2.02	0	14.13	0	0.59	0	0.54	0	0.00	0	20.77	0	768426	0	64	0	58.03	0	1.25	0	0.00	0	1.02	0	0.01	0	236.13	0	0.76	0	19833	0	983886	0	139049	0	5835	0	5282	0	0	0	204343	0	12	0	0	0	100	0	14849	0	770	0	15731	0	63.97	0	629377	0	8532	12636	1.481012658228	983886.0	768426.0	19833.0	139049.0	5835.0	5282.0	0.0	204343.0	629377.0	78.1	2.0	14.1	0.6	0.5	0.0	20.8	64.0	32	32	32.00	6	31484352	22.5	23.3	24.7	21.8	7.8	30.6	13.8	smartseq
1606922	SRR2925850	SRP066154	SRS1161716	SRX1427189	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937660: L1210_29 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_82|cousin 2;;L1210_18|hours since division;;1.2667|sister;;L1210_6|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937660		GSM1937660	L1210_29 scRNA-seq	65526656	1023854	2015-12-22 15:48:11	32015075	65526656	1023854	2	1023854	index:0,count:1023854,average:32,stdev:0|index:1,count:1023854,average:32,stdev:0	GSM1937660_r1						4.09	1.74	0.19	46468531	50841105	38242552	43865604	109.41	114.7	803228	722654	211.171	995.440	125	4056	68.91	83.72	1032417	553498	1032417	553498	62.14	64.75	1032417	499120	1032417	428066	5362790	11.54	2.03	0	13.88	0	0.54	0	0.36	0	0.00	0	20.65	0	803228	0	64	0	58.09	0	1.22	0	0.00	0	1.02	0	0.01	0	245.72	0	0.74	0	20820	0	1023854	0	142124	0	5494	0	3706	0	0	0	211426	0	14	0	0	0	95	0	12159	0	810	0	13078	0	64.57	0	661104	0	7086	10332	1.458086367485	1023854.0	803228.0	20820.0	142124.0	5494.0	3706.0	0.0	211426.0	661104.0	78.5	2.0	13.9	0.5	0.4	0.0	20.7	64.6	32	32	32.00	6	32763328	22.7	23.2	24.6	21.8	7.7	30.6	13.8	smartseq
1606937	SRR2925851	SRP066154	SRS1161717	SRX1427190	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937661: L1210_30 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_7|cousin 2;;L1210_19|hours since division;;1.625|sister;;L1210_83|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937661		GSM1937661	L1210_30 scRNA-seq	54449152	850768	2015-12-22 15:48:11	26587722	54449152	850768	2	850768	index:0,count:850768,average:32,stdev:0|index:1,count:850768,average:32,stdev:0	GSM1937661_r1						3.87	1.7	0.34	38241306	41059763	31837597	35702494	107.37	112.14	660777	599711	212.401	963.956	125	3205	65.04	78.12	841819	429759	841819	429759	58.52	60.59	841819	386684	841819	333330	5977023	15.63	1.96	0	13.00	0	0.61	0	0.53	0	0.00	0	21.19	0	660777	0	64	0	58.10	0	1.24	0	0.00	0	1.02	0	0.01	0	235.60	0	0.73	0	16676	0	850768	0	110641	0	5216	0	4470	0	0	0	180305	0	20	0	0	0	71	0	9068	0	595	0	9754	0	64.66	0	550136	0	5455	7645	1.401466544455	850768.0	660777.0	16676.0	110641.0	5216.0	4470.0	0.0	180305.0	550136.0	77.7	2.0	13.0	0.6	0.5	0.0	21.2	64.7	32	32	32.00	6	27224576	22.8	23.0	24.4	22.0	7.7	30.7	13.8	smartseq
1606953	SRR2925852	SRP066154	SRS1161714	SRX1427191	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937662: L1210_31 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_9|cousin 2;;L1210_20|hours since division;;4.5167|sister;;L1210_42|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937662		GSM1937662	L1210_31 scRNA-seq	61139712	955308	2015-12-22 15:48:11	29911081	61139712	955308	2	955308	index:0,count:955308,average:32,stdev:0|index:1,count:955308,average:32,stdev:0	GSM1937662_r1						4.61	2.13	0.36	42388434	44850570	35145380	38717284	105.81	110.16	732736	646499	216.824	1247.767	125	3459	66.76	80.5	956294	489156	956294	489156	63.23	65.03	956294	463275	956294	395191	5989466	14.13	1.92	0	13.09	0	0.67	0	0.56	0	0.00	0	22.07	0	732736	0	64	0	58.04	0	1.19	0	0.00	0	1.03	0	0.01	0	264.55	0	0.75	0	18357	0	955308	0	125077	0	6420	0	5313	0	0	0	210839	0	9	0	0	0	103	0	12555	0	631	0	13298	0	63.61	0	607659	0	7589	10668	1.405718803531	955308.0	732736.0	18357.0	125077.0	6420.0	5313.0	0.0	210839.0	607659.0	76.7	1.9	13.1	0.7	0.6	0.0	22.1	63.6	32	32	32.00	6	30569856	23.0	22.9	24.4	22.0	7.7	30.6	13.8	smartseq
1606971	SRR2925853	SRP066154	SRS1161713	SRX1427192	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937663: L1210_32 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_21|cousin 2;;L1210_43|hours since division;;2.8583|sister;;L1210_10|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937663		GSM1937663	L1210_32 scRNA-seq	59493184	929581	2015-12-22 15:48:11	29074830	59493184	929581	2	929581	index:0,count:929581,average:32,stdev:0|index:1,count:929581,average:32,stdev:0	GSM1937663_r1						3.36	1.95	0.4	41273456	44920714	33696010	38517905	108.84	114.31	713367	635943	217.090	1177.599	117	3500	68.65	84.07	931044	489745	931044	489745	62.73	65.43	931044	447507	931044	381151	4633072	11.23	2.10	0	14.08	0	0.66	0	0.58	0	0.00	0	22.02	0	713367	0	64	0	58.05	0	1.23	0	0.00	0	1.02	0	0.01	0	223.10	0	0.76	0	19531	0	929581	0	130848	0	6115	0	5425	0	0	0	204674	0	13	0	0	0	90	0	11466	0	681	0	12250	0	62.66	0	582519	0	6715	9745	1.451228592703	929581.0	713367.0	19531.0	130848.0	6115.0	5425.0	0.0	204674.0	582519.0	76.7	2.1	14.1	0.7	0.6	0.0	22.0	62.7	32	32	32.00	6	29746592	22.6	23.2	24.7	21.8	7.7	30.7	13.8	smartseq
1606989	SRR2925854	SRP066154	SRS1161712	SRX1427193	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937664: L1210_33 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_11|cousin 2;;L1210_22|hours since division;;0.3544|sister;;L1210_44|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937664		GSM1937664	L1210_33 scRNA-seq	56830464	887976	2015-12-22 15:48:11	27735907	56830464	887976	2	887976	index:0,count:887976,average:32,stdev:0|index:1,count:887976,average:32,stdev:0	GSM1937664_r1						4.88	2.25	0.59	39365516	40888785	32959327	35459660	103.87	107.59	681295	583954	217.909	1578.547	117	3079	67.24	80.29	895731	458122	895731	458122	66.99	68.46	895731	456431	895731	390649	6272103	15.93	1.76	0	12.46	0	0.83	0	0.71	0	0.00	0	21.73	0	681295	0	64	0	57.99	0	1.26	0	0.00	0	1.02	0	0.01	0	199.79	0	0.74	0	15632	0	887976	0	110681	0	7386	0	6314	0	0	0	192981	0	12	0	0	0	110	0	14649	0	504	0	15275	0	64.26	0	570614	0	8564	12324	1.439047174218	887976.0	681295.0	15632.0	110681.0	7386.0	6314.0	0.0	192981.0	570614.0	76.7	1.8	12.5	0.8	0.7	0.0	21.7	64.3	32	32	32.00	6	28415232	22.9	22.9	24.4	22.0	7.8	30.6	13.8	smartseq
1607005	SRR2925855	SRP066154	SRS1161711	SRX1427194	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937665: L1210_34 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_45|cousin 2;;L1210_56|hours since division;;1.3333|sister;;L1210_67|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937665		GSM1937665	L1210_34 scRNA-seq	85922112	1342533	2015-12-22 15:48:11	42035098	85922112	1342533	2	1342533	index:0,count:1342533,average:32,stdev:0|index:1,count:1342533,average:32,stdev:0	GSM1937665_r1						3.57	1.77	0.33	61087264	66469890	50286300	57236445	108.81	113.82	1055408	933765	222.323	1099.378	125	5015	69.7	84.64	1365998	735633	1365998	735633	64.93	67.61	1365998	685247	1365998	587553	7155218	11.71	1.96	0	13.88	0	0.66	0	0.33	0	0.00	0	20.40	0	1055408	0	64	0	58.06	0	1.20	0	0.00	0	1.02	0	0.01	0	268.51	0	0.76	0	26294	0	1342533	0	186319	0	8817	0	4467	0	0	0	273841	0	22	0	0	0	131	0	17949	0	977	0	19079	0	64.74	0	869089	0	9742	15506	1.591664955861	1342533.0	1055408.0	26294.0	186319.0	8817.0	4467.0	0.0	273841.0	869089.0	78.6	2.0	13.9	0.7	0.3	0.0	20.4	64.7	32	32	32.00	6	42961056	22.4	23.4	24.8	21.7	7.8	30.6	13.8	smartseq
1607021	SRR2925856	SRP066154	SRS1161710	SRX1427195	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937666: L1210_35 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_1|cousin 2;;L1210_13|hours since division;;4.6761|sister;;L1210_24|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937666		GSM1937666	L1210_35 scRNA-seq	46446720	725730	2015-12-22 15:48:11	23554179	46446720	725730	2	725730	index:0,count:725730,average:32,stdev:0|index:1,count:725730,average:32,stdev:0	GSM1937666_r1						3.03	1.87	0.28	32927152	35599874	26427496	30066965	108.12	113.77	570012	513394	189.853	1173.219	125	3398	68.04	84.76	759764	387828	759764	387828	63.01	66.5	759764	359169	759764	304250	3640420	11.06	2.07	0	15.50	0	0.73	0	0.89	0	0.00	0	19.83	0	570012	0	64	0	58.06	0	1.20	0	0.00	0	1.02	0	0.01	0	163.29	0	0.71	0	15034	0	725730	0	112474	0	5305	0	6469	0	0	0	143944	0	8	0	0	0	73	0	9766	0	539	0	10386	0	63.05	0	457538	0	5874	8317	1.415900578822	725730.0	570012.0	15034.0	112474.0	5305.0	6469.0	0.0	143944.0	457538.0	78.5	2.1	15.5	0.7	0.9	0.0	19.8	63.0	32	32	32.00	6	23223360	22.3	23.1	24.7	22.2	7.7	30.2	13.7	smartseq
1607037	SRR2925857	SRP066154	SRS1161709	SRX1427196	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937667: L1210_36 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_25|cousin 2;;L1210_47|hours since division;;2.05|sister;;L1210_58|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937667		GSM1937667	L1210_36 scRNA-seq	76350784	1192981	2015-12-22 15:48:11	37353764	76350784	1192981	2	1192981	index:0,count:1192981,average:32,stdev:0|index:1,count:1192981,average:32,stdev:0	GSM1937667_r1						2.85	1.77	0.19	54207583	59224803	44392051	50846137	109.26	114.54	937506	840933	200.801	1014.868	125	5018	70.01	85.47	1213439	656378	1213439	656378	63.94	66.82	1213439	599438	1213439	513094	5661653	10.44	2.05	0	14.21	0	0.58	0	0.49	0	0.00	0	20.35	0	937506	0	64	0	58.05	0	1.21	0	0.00	0	1.02	0	0.01	0	252.63	0	0.71	0	24407	0	1192981	0	169576	0	6934	0	5794	0	0	0	242747	0	12	0	0	0	120	0	16206	0	887	0	17225	0	64.37	0	767930	0	8892	14151	1.591430499325	1192981.0	937506.0	24407.0	169576.0	6934.0	5794.0	0.0	242747.0	767930.0	78.6	2.0	14.2	0.6	0.5	0.0	20.3	64.4	32	32	32.00	6	38175392	22.2	23.3	24.8	21.9	7.8	30.6	13.8	smartseq
1607054	SRR2925858	SRP066154	SRS1161708	SRX1427197	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937668: L1210_37 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_3|cousin 2;;L1210_15|hours since division;;7.8833|sister;;L1210_26|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937668		GSM1937668	L1210_37 scRNA-seq	81443264	1272551	2015-12-22 15:48:11	39925592	81443264	1272551	2	1272551	index:0,count:1272551,average:32,stdev:0|index:1,count:1272551,average:32,stdev:0	GSM1937668_r1						3.24	1.9	0.23	58029124	62813719	47484273	53812279	108.25	113.33	1002530	889694	211.402	1076.310	125	5092	70.26	85.83	1311858	704345	1311858	704345	66.11	68.95	1311858	662780	1311858	565875	6104051	10.52	2.02	0	14.29	0	0.72	0	0.42	0	0.00	0	20.07	0	1002530	0	64	0	58.04	0	1.22	0	0.00	0	1.03	0	0.01	0	241.11	0	0.71	0	25667	0	1272551	0	181866	0	9207	0	5359	0	0	0	255455	0	17	0	0	0	113	0	18121	0	883	0	19134	0	64.49	0	820664	0	9571	15586	1.628460975865	1272551.0	1002530.0	25667.0	181866.0	9207.0	5359.0	0.0	255455.0	820664.0	78.8	2.0	14.3	0.7	0.4	0.0	20.1	64.5	32	32	32.00	6	40721632	22.3	23.2	24.7	22.0	7.8	30.6	13.8	smartseq
1607070	SRR2925859	SRP066154	SRS1161715	SRX1427198	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937669: L1210_38 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_4|cousin 2;;L1210_16|hours since division;;4.4511|sister;;L1210_27|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937669		GSM1937669	L1210_38 scRNA-seq	57831744	903621	2015-12-22 15:48:11	28695080	57831744	903621	2	903621	index:0,count:903621,average:32,stdev:0|index:1,count:903621,average:32,stdev:0	GSM1937669_r1						2.02	1.5	0.04	41032435	47206728	31898337	39404836	115.05	123.53	708897	650424	200.832	782.508	125	4173	73.22	94.14	949023	519084	949023	519084	62.85	67.4	949023	445574	949023	371667	1152211	2.81	2.54	0	17.43	0	0.47	0	0.19	0	0.00	0	20.89	0	708897	0	64	0	58.03	0	1.19	0	0.00	0	1.02	0	0.02	0	216.87	0	0.74	0	22989	0	903621	0	157496	0	4237	0	1733	0	0	0	188754	0	10	0	0	0	85	0	9501	0	863	0	10459	0	61.02	0	551401	0	5330	8132	1.525703564728	903621.0	708897.0	22989.0	157496.0	4237.0	1733.0	0.0	188754.0	551401.0	78.5	2.5	17.4	0.5	0.2	0.0	20.9	61.0	32	32	32.00	6	28915872	21.8	23.7	25.1	21.7	7.7	30.4	13.8	smartseq
1607182	SRR2925860	SRP066154	SRS1161707	SRX1427199	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937670: L1210_39 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_5|cousin 2;;L1210_17|hours since division;;3.8033|sister;;L1210_28|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937670		GSM1937670	L1210_39 scRNA-seq	60346880	942920	2015-12-22 15:48:11	29797956	60346880	942920	2	942920	index:0,count:942920,average:32,stdev:0|index:1,count:942920,average:32,stdev:0	GSM1937670_r1						3.78	1.64	0.24	42850790	45834618	35228746	39437069	106.96	111.95	740612	666258	199.574	1091.652	117	4034	68.22	82.97	960717	505230	960717	505230	62.89	65.97	960717	465743	960717	401694	5170841	12.07	2.05	0	13.96	0	0.60	0	0.62	0	0.00	0	20.24	0	740612	0	64	0	58.08	0	1.24	0	0.00	0	1.02	0	0.01	0	188.58	0	0.73	0	19291	0	942920	0	131662	0	5631	0	5810	0	0	0	190867	0	18	0	0	0	111	0	12046	0	633	0	12808	0	64.58	0	608950	0	7241	10242	1.414445518575	942920.0	740612.0	19291.0	131662.0	5631.0	5810.0	0.0	190867.0	608950.0	78.5	2.0	14.0	0.6	0.6	0.0	20.2	64.6	32	32	32.00	6	30173440	22.4	23.0	24.6	22.2	7.7	30.5	13.8	smartseq
1607198	SRR2925861	SRP066154	SRS1161706	SRX1427200	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937671: L1210_40 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_62|cousin 2;;L1210_73|hours since division;;2.2667|sister;;L1210_51|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937671		GSM1937671	L1210_40 scRNA-seq	66383232	1037238	2015-12-22 15:48:11	32604980	66383232	1037238	2	1037238	index:0,count:1037238,average:32,stdev:0|index:1,count:1037238,average:32,stdev:0	GSM1937671_r1						3.83	1.73	0.34	47547952	51555366	38789724	44099129	108.43	113.69	821788	736415	200.872	1030.521	117	4437	70.01	85.8	1073753	575347	1073753	575347	64.99	67.77	1073753	534101	1073753	454468	4777652	10.05	2.04	0	14.58	0	0.62	0	0.43	0	0.00	0	19.72	0	821788	0	64	0	58.09	0	1.22	0	0.00	0	1.02	0	0.01	0	248.94	0	0.71	0	21135	0	1037238	0	151204	0	6479	0	4409	0	0	0	204562	0	7	0	0	0	130	0	14017	0	717	0	14871	0	64.65	0	670584	0	7772	12022	1.546834791559	1037238.0	821788.0	21135.0	151204.0	6479.0	4409.0	0.0	204562.0	670584.0	79.2	2.0	14.6	0.6	0.4	0.0	19.7	64.7	32	32	32.00	6	33191616	22.3	23.2	24.6	22.1	7.8	30.6	13.8	smartseq
1607212	SRR2925862	SRP066154	SRS1161705	SRX1427201	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937672: L1210_41 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;10.6|sister;;L1210_52|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937672		GSM1937672	L1210_41 scRNA-seq	217920	3405	2015-12-22 15:48:11	193265	217920	3405	2	3405	index:0,count:3405,average:32,stdev:0|index:1,count:3405,average:32,stdev:0	GSM1937672_r1						1.9	1.45	0.09	149109	169546	121522	144818	113.71	119.17	2577	2352	202.808	725.079	125	28	71.13	87.16	3314	1833	3314	1833	62.05	64.24	3314	1599	3314	1351	13713	9.20	2.61	0	13.92	0	0.53	0	0.29	0	0.00	0	23.49	0	2577	0	64	0	57.88	0	1.00	0	0.00	0	1.05	0	0.02	0	12.26	0	0.79	0	89	0	3405	0	474	0	18	0	10	0	0	0	800	0	0	0	0	0	1	0	42	0	2	0	45	0	61.76	0	2103	0	25	25	1.000000000000	3405.0	2577.0	89.0	474.0	18.0	10.0	0.0	800.0	2103.0	75.7	2.6	13.9	0.5	0.3	0.0	23.5	61.8	32	32	32.00	6	108960	21.5	24.1	25.7	20.9	7.8	30.2	13.7	smartseq
1607228	SRR2925863	SRP066154	SRS1161704	SRX1427202	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937673: L1210_42 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_9|cousin 2;;L1210_20|hours since division;;4.55|sister;;L1210_31|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937673		GSM1937673	L1210_42 scRNA-seq	29141504	455336	2015-12-22 15:48:11	15256521	29141504	455336	2	455336	index:0,count:455336,average:32,stdev:0|index:1,count:455336,average:32,stdev:0	GSM1937673_r1						4.08	2.08	0.26	20461227	21713428	16724618	18513493	106.12	110.7	353516	311676	201.872	1255.445	125	1898	69.28	84.72	466889	244925	466889	244925	66.7	69.41	466889	235801	466889	200654	2249503	10.99	2.03	0	14.15	0	0.66	0	0.52	0	0.00	0	21.18	0	353516	0	64	0	58.00	0	1.22	0	0.00	0	1.03	0	0.01	0	91.07	0	0.75	0	9246	0	455336	0	64411	0	2985	0	2387	0	0	0	96448	0	8	0	0	0	45	0	6621	0	371	0	7045	0	63.49	0	289105	0	4397	5434	1.235842619968	455336.0	353516.0	9246.0	64411.0	2985.0	2387.0	0.0	96448.0	289105.0	77.6	2.0	14.1	0.7	0.5	0.0	21.2	63.5	32	32	32.00	6	14570752	22.4	22.7	24.6	22.6	7.7	30.0	13.7	smartseq
1607243	SRR2925864	SRP066154	SRS1161703	SRX1427203	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937674: L1210_43 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_10|cousin 2;;L1210_32|hours since division;;0.6333|sister;;L1210_21|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937674		GSM1937674	L1210_43 scRNA-seq	59408192	928253	2015-12-22 15:48:11	29217410	59408192	928253	2	928253	index:0,count:928253,average:32,stdev:0|index:1,count:928253,average:32,stdev:0	GSM1937674_r1						3.43	1.84	0.42	39578850	42843336	32240262	36696668	108.25	113.82	684290	622546	198.435	1015.332	117	3781	67.84	83.28	892068	464249	892068	464249	61.19	64.37	892068	418688	892068	358846	4581169	11.57	2.02	0	13.67	0	0.57	0	0.58	0	0.00	0	25.12	0	684290	0	64	0	58.08	0	1.21	0	0.00	0	1.02	0	0.02	0	238.69	0	0.73	0	18742	0	928253	0	126850	0	5333	0	5429	0	0	0	233201	0	16	0	0	0	78	0	9967	0	648	0	10709	0	60.05	0	557440	0	6030	8379	1.389552238806	928253.0	684290.0	18742.0	126850.0	5333.0	5429.0	0.0	233201.0	557440.0	73.7	2.0	13.7	0.6	0.6	0.0	25.1	60.1	32	32	32.00	6	29704096	22.5	23.0	24.5	22.3	7.7	30.6	13.8	smartseq
1607258	SRR2925865	SRP066154	SRS1161702	SRX1427204	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937675: L1210_44 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_11|cousin 2;;L1210_22|hours since division;;0.3722|sister;;L1210_33|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937675		GSM1937675	L1210_44 scRNA-seq	76832896	1200514	2015-12-22 15:48:11	37585232	76832896	1200514	2	1200514	index:0,count:1200514,average:32,stdev:0|index:1,count:1200514,average:32,stdev:0	GSM1937675_r1						4.25	2.15	0.46	54566874	56911439	45664422	49355635	104.3	108.08	944588	821364	202.850	1332.371	125	4747	67.83	81.03	1231201	640696	1231201	640696	66.88	68.66	1231201	631752	1231201	542861	8243117	15.11	1.73	0	12.82	0	0.77	0	0.70	0	0.00	0	19.85	0	944588	0	64	0	58.03	0	1.26	0	0.00	0	1.02	0	0.01	0	308.70	0	0.69	0	20757	0	1200514	0	153939	0	9265	0	8360	0	0	0	238301	0	29	0	0	0	153	0	20444	0	641	0	21267	0	65.86	0	790649	0	11175	17749	1.588277404922	1200514.0	944588.0	20757.0	153939.0	9265.0	8360.0	0.0	238301.0	790649.0	78.7	1.7	12.8	0.8	0.7	0.0	19.8	65.9	32	32	32.00	6	38416448	22.7	22.8	24.4	22.3	7.8	30.6	13.8	smartseq
1607275	SRR2925866	SRP066154	SRS1161701	SRX1427205	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937676: L1210_45 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_34|cousin 2;;L1210_67|hours since division;;2.5|sister;;L1210_56|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937676		GSM1937676	L1210_45 scRNA-seq	30109760	470465	2015-12-22 15:48:11	14763723	30109760	470465	2	470465	index:0,count:470465,average:32,stdev:0|index:1,count:470465,average:32,stdev:0	GSM1937676_r1						1.33	1.57	0.38	21164592	23784925	16977528	20261038	112.38	119.34	367446	338475	174.368	815.117	117	2549	68.73	85.71	485517	252541	485517	252541	58.58	62.0	485517	215244	485517	182686	2302803	10.88	2.29	0	15.47	0	0.63	0	0.48	0	0.00	0	20.78	0	367446	0	64	0	58.02	0	1.21	0	0.00	0	1.03	0	0.01	0	112.91	0	0.72	0	10766	0	470465	0	72796	0	2966	0	2268	0	0	0	97785	0	7	0	0	0	55	0	5562	0	413	0	6037	0	62.63	0	294650	0	3510	4594	1.308831908832	470465.0	367446.0	10766.0	72796.0	2966.0	2268.0	0.0	97785.0	294650.0	78.1	2.3	15.5	0.6	0.5	0.0	20.8	62.6	32	32	32.00	6	15054880	21.6	24.0	25.6	21.0	7.8	30.6	13.8	smartseq
1607291	SRR2925867	SRP066154	SRS1161700	SRX1427206	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937677: L1210_46 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_68|cousin 2;;L1210_79|hours since division;;5.1536|sister;;L1210_57|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937677		GSM1937677	L1210_46 scRNA-seq	52364096	818189	2015-12-22 15:48:11	25446324	52364096	818189	2	818189	index:0,count:818189,average:32,stdev:0|index:1,count:818189,average:32,stdev:0	GSM1937677_r1						3.16	1.86	0.35	37474324	40717699	30356196	34721010	108.65	114.38	648139	581399	200.241	1097.628	117	3531	68.94	85.1	852705	446852	852705	446852	63.37	66.51	852705	410751	852705	349252	4016215	10.72	2.12	0	15.04	0	0.62	0	0.52	0	0.00	0	19.64	0	648139	0	64	0	58.06	0	1.23	0	0.00	0	1.03	0	0.01	0	196.37	0	0.65	0	17381	0	818189	0	123040	0	5109	0	4246	0	0	0	160695	0	7	0	0	0	83	0	11089	0	579	0	11758	0	64.18	0	525099	0	6385	9452	1.480344557557	818189.0	648139.0	17381.0	123040.0	5109.0	4246.0	0.0	160695.0	525099.0	79.2	2.1	15.0	0.6	0.5	0.0	19.6	64.2	32	32	32.00	6	26182048	22.6	23.0	24.6	22.0	7.7	30.6	13.8	smartseq
1607307	SRR2925868	SRP066154	SRS1161699	SRX1427207	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937678: L1210_47 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_36|cousin 2;;L1210_58|hours since division;;4.9833|sister;;L1210_25|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937678		GSM1937678	L1210_47 scRNA-seq	58979776	921559	2015-12-22 15:48:11	29222670	58979776	921559	2	921559	index:0,count:921559,average:32,stdev:0|index:1,count:921559,average:32,stdev:0	GSM1937678_r1						3.31	1.96	0.35	42187460	45721679	34315321	38979763	108.38	113.59	728828	645416	211.981	1217.777	125	3705	69.68	85.63	958643	507862	958643	507862	65.52	68.2	958643	477514	958643	404464	4409047	10.45	2.07	0	14.73	0	0.68	0	0.65	0	0.00	0	19.57	0	728828	0	64	0	58.03	0	1.21	0	0.00	0	1.02	0	0.01	0	195.15	0	0.66	0	19099	0	921559	0	135744	0	6309	0	6027	0	0	0	180395	0	15	0	0	0	99	0	13161	0	703	0	13978	0	64.36	0	593084	0	7332	11336	1.546099290780	921559.0	728828.0	19099.0	135744.0	6309.0	6027.0	0.0	180395.0	593084.0	79.1	2.1	14.7	0.7	0.7	0.0	19.6	64.4	32	32	32.00	6	29489888	22.5	23.0	24.7	22.1	7.7	30.4	13.7	smartseq
1607323	SRR2925869	SRP066154	SRS1161698	SRX1427208	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937679: L1210_48 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;7.0583|sister;;#N/A!|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937679		GSM1937679	L1210_48 scRNA-seq	55974784	874606	2015-12-22 15:48:11	27168867	55974784	874606	2	874606	index:0,count:874606,average:32,stdev:0|index:1,count:874606,average:32,stdev:0	GSM1937679_r1						1.65	0.88	0.11	33888233	40075677	28226918	35313727	118.26	125.11	585179	568339	191.910	466.406	146	3522	76.99	92.48	723327	450518	723327	450518	59.29	63.88	723327	346961	723327	311164	1304173	3.85	2.18	0	11.21	0	0.23	0	0.13	0	0.00	0	32.73	0	585179	0	64	0	58.16	0	1.31	0	0.01	0	1.02	0	0.02	0	224.90	0	0.67	0	19096	0	874606	0	98034	0	1970	0	1174	0	0	0	286283	0	12	0	0	0	44	0	2928	0	515	0	3499	0	55.70	0	487145	0	1168	2732	2.339041095890	874606.0	585179.0	19096.0	98034.0	1970.0	1174.0	0.0	286283.0	487145.0	66.9	2.2	11.2	0.2	0.1	0.0	32.7	55.7	32	32	32.00	6	27987392	22.3	23.3	25.0	21.8	7.7	30.7	13.8	smartseq
1607433	SRR2925870	SRP066154	SRS1161697	SRX1427209	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937680: L1210_49 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_71|cousin 2;;L1210_81|hours since division;;6.325|sister;;L1210_60|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937680		GSM1937680	L1210_49 scRNA-seq	52438848	819357	2015-12-22 15:48:11	25521711	52438848	819357	2	819357	index:0,count:819357,average:32,stdev:0|index:1,count:819357,average:32,stdev:0	GSM1937680_r1						4.24	1.98	0.42	37330543	40494098	30357213	34522119	108.47	113.72	644699	567167	217.301	1281.549	125	3023	69.8	85.8	855748	450017	855748	450017	66.52	68.77	855748	428865	855748	360716	4041305	10.83	2.06	0	14.67	0	0.65	0	0.60	0	0.00	0	20.07	0	644699	0	64	0	58.05	0	1.23	0	0.00	0	1.02	0	0.01	0	226.90	0	0.67	0	16899	0	819357	0	120191	0	5345	0	4896	0	0	0	164417	0	12	0	0	0	82	0	11961	0	543	0	12598	0	64.01	0	524508	0	6905	10212	1.478928312817	819357.0	644699.0	16899.0	120191.0	5345.0	4896.0	0.0	164417.0	524508.0	78.7	2.1	14.7	0.7	0.6	0.0	20.1	64.0	32	32	32.00	6	26219424	22.8	22.8	24.4	22.3	7.7	30.6	13.8	smartseq
1607449	SRR2925871	SRP066154	SRS1161696	SRX1427210	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937681: L1210_50 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;1.2667|sister;;#N/A!|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937681		GSM1937681	L1210_50 scRNA-seq	85815616	1340869	2015-12-22 15:48:11	41638759	85815616	1340869	2	1340869	index:0,count:1340869,average:32,stdev:0|index:1,count:1340869,average:32,stdev:0	GSM1937681_r1						7.84	1.58	0.07	58101064	58143035	46851769	49257414	100.07	105.13	1004817	951715	196.559	849.891	129	5882	58.26	72.31	1318917	585419	1318917	585419	50.54	52.97	1318917	507876	1318917	428859	7321684	12.60	2.31	0	14.56	0	0.60	0	0.71	0	0.00	0	23.76	0	1004817	0	64	0	58.10	0	1.17	0	0.00	0	1.02	0	0.01	0	283.95	0	0.67	0	30944	0	1340869	0	195208	0	7995	0	9499	0	0	0	318558	0	8	0	0	0	72	0	7060	0	926	0	8066	0	60.38	0	809609	0	4001	6054	1.513121719570	1340869.0	1004817.0	30944.0	195208.0	7995.0	9499.0	0.0	318558.0	809609.0	74.9	2.3	14.6	0.6	0.7	0.0	23.8	60.4	32	32	32.00	6	42907808	24.1	21.6	23.4	23.3	7.7	30.7	13.8	smartseq
1607465	SRR2925872	SRP066154	SRS1161695	SRX1427211	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937682: L1210_51 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_62|cousin 2;;L1210_73|hours since division;;2.2833|sister;;L1210_40|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937682		GSM1937682	L1210_51 scRNA-seq	67949888	1061717	2015-12-22 15:48:11	33308457	67949888	1061717	2	1061717	index:0,count:1061717,average:32,stdev:0|index:1,count:1061717,average:32,stdev:0	GSM1937682_r1						3.28	1.82	0.27	49220638	53198477	40344081	45654670	108.08	113.16	849980	755528	211.716	1069.760	125	4262	68.8	83.91	1099663	584767	1099663	584767	63.67	66.53	1099663	541143	1099663	463644	5684939	11.55	2.10	0	14.42	0	0.66	0	0.38	0	0.00	0	18.90	0	849980	0	64	0	58.06	0	1.22	0	0.00	0	1.02	0	0.01	0	273.01	0	0.65	0	22317	0	1061717	0	153074	0	7054	0	4025	0	0	0	200658	0	29	0	0	0	114	0	14886	0	795	0	15824	0	65.64	0	696906	0	8244	12803	1.553008248423	1061717.0	849980.0	22317.0	153074.0	7054.0	4025.0	0.0	200658.0	696906.0	80.1	2.1	14.4	0.7	0.4	0.0	18.9	65.6	32	32	32.00	6	33974944	22.8	22.8	24.4	22.2	7.7	30.5	13.8	smartseq
1607480	SRR2925873	SRP066154	SRS1161694	SRX1427212	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937683: L1210_52 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;10.6167|sister;;L1210_41|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937683		GSM1937683	L1210_52 scRNA-seq	74575744	1165246	2015-12-22 15:48:11	36146666	74575744	1165246	2	1165246	index:0,count:1165246,average:32,stdev:0|index:1,count:1165246,average:32,stdev:0	GSM1937683_r1						3.45	2.34	0.34	51024114	47750963	43071057	41541638	93.59	96.45	881975	806410	206.192	1186.396	125	4532	53.43	63.32	1130843	471276	1130843	471276	49.81	50.82	1130843	439294	1130843	378236	10152859	19.90	1.96	0	11.82	0	0.79	0	1.20	0	0.00	0	22.33	0	881975	0	64	0	58.07	0	1.22	0	0.01	0	1.02	0	0.01	0	262.18	0	0.66	0	22818	0	1165246	0	137743	0	9176	0	13947	0	0	0	260148	0	11	0	0	0	80	0	10722	0	632	0	11445	0	63.87	0	744232	0	6398	9190	1.436386370741	1165246.0	881975.0	22818.0	137743.0	9176.0	13947.0	0.0	260148.0	744232.0	75.7	2.0	11.8	0.8	1.2	0.0	22.3	63.9	32	32	32.00	6	37287872	23.9	21.8	23.5	23.1	7.7	30.7	13.8	smartseq
1607498	SRR2925874	SRP066154	SRS1161693	SRX1427213	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937684: L1210_53 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_64|cousin 2;;L1210_85|hours since division;;5.0667|sister;;L1210_75|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937684		GSM1937684	L1210_53 scRNA-seq	78305280	1223520	2015-12-22 15:48:11	38116761	78305280	1223520	2	1223520	index:0,count:1223520,average:32,stdev:0|index:1,count:1223520,average:32,stdev:0	GSM1937684_r1						4.54	2.09	0.35	55950498	59503577	46510091	51427985	106.35	110.57	966642	838989	219.773	1280.685	125	4450	69.38	83.43	1258017	670698	1258017	670698	67.07	69.11	1258017	648352	1258017	555567	7250587	12.96	1.99	0	13.30	0	0.73	0	0.48	0	0.00	0	19.78	0	966642	0	64	0	58.02	0	1.21	0	0.00	0	1.02	0	0.01	0	293.64	0	0.67	0	24310	0	1223520	0	162732	0	8911	0	5900	0	0	0	242067	0	22	0	0	0	139	0	19727	0	789	0	20677	0	65.70	0	803910	0	10763	17077	1.586639412803	1223520.0	966642.0	24310.0	162732.0	8911.0	5900.0	0.0	242067.0	803910.0	79.0	2.0	13.3	0.7	0.5	0.0	19.8	65.7	32	32	32.00	6	39152640	22.8	22.8	24.4	22.2	7.7	30.7	13.8	smartseq
1607512	SRR2925875	SRP066154	SRS1161692	SRX1427214	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937685: L1210_54 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_65|cousin 2;;L1210_76|hours since division;;8.3167|sister;;L1210_86|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937685		GSM1937685	L1210_54 scRNA-seq	67602496	1056289	2015-12-22 15:48:11	32919704	67602496	1056289	2	1056289	index:0,count:1056289,average:32,stdev:0|index:1,count:1056289,average:32,stdev:0	GSM1937685_r1						3.3	1.77	0.39	48061611	52279306	39552006	45143291	108.78	114.14	830528	743975	209.050	1061.942	125	4333	69.14	84.0	1068135	574208	1068135	574208	62.34	65.49	1068135	517712	1068135	447672	5503665	11.45	2.15	0	13.91	0	0.57	0	0.36	0	0.00	0	20.44	0	830528	0	64	0	58.06	0	1.22	0	0.00	0	1.02	0	0.01	0	200.14	0	0.68	0	22697	0	1056289	0	146951	0	5998	0	3825	0	0	0	215938	0	17	0	0	0	98	0	13755	0	773	0	14643	0	64.71	0	683577	0	7605	11618	1.527679158448	1056289.0	830528.0	22697.0	146951.0	5998.0	3825.0	0.0	215938.0	683577.0	78.6	2.1	13.9	0.6	0.4	0.0	20.4	64.7	32	32	32.00	6	33801248	22.5	23.1	24.7	21.9	7.7	30.6	13.8	smartseq
1607529	SRR2925876	SRP066154	SRS1161690	SRX1427215	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937686: L1210_55 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;9.3194|sister;;L1210_66|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937686		GSM1937686	L1210_55 scRNA-seq	67907776	1061059	2015-12-22 15:48:11	33411131	67907776	1061059	2	1061059	index:0,count:1061059,average:32,stdev:0|index:1,count:1061059,average:32,stdev:0	GSM1937686_r1						4.73	2.22	0.38	48983555	50965208	41059825	44225867	104.05	107.71	846957	731014	211.539	1293.181	125	4140	68.32	81.47	1102950	578629	1102950	578629	67.86	69.55	1102950	574771	1102950	493913	7232523	14.77	1.76	0	12.89	0	0.79	0	0.54	0	0.00	0	18.85	0	846957	0	64	0	58.02	0	1.24	0	0.00	0	1.02	0	0.01	0	201.04	0	0.65	0	18725	0	1061059	0	136752	0	8378	0	5744	0	0	0	199980	0	9	0	0	0	129	0	18947	0	609	0	19694	0	66.93	0	710205	0	10552	16289	1.543688400303	1061059.0	846957.0	18725.0	136752.0	8378.0	5744.0	0.0	199980.0	710205.0	79.8	1.8	12.9	0.8	0.5	0.0	18.8	66.9	32	32	32.00	6	33953888	22.9	22.7	24.3	22.3	7.8	30.5	13.7	smartseq
1607545	SRR2925877	SRP066154	SRS1161691	SRX1427216	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937687: L1210_56 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_34|cousin 2;;L1210_67|hours since division;;2.5167|sister;;L1210_45|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937687		GSM1937687	L1210_56 scRNA-seq	76668352	1197943	2015-12-22 15:48:11	37671372	76668352	1197943	2	1197943	index:0,count:1197943,average:32,stdev:0|index:1,count:1197943,average:32,stdev:0	GSM1937687_r1						3.73	1.63	0.5	55187517	60722421	45269931	52391766	110.03	115.73	953409	864705	203.025	948.987	125	5245	68.52	83.52	1220573	653243	1220573	653243	60.52	63.83	1220573	577005	1220573	499255	6741287	12.22	2.15	0	14.29	0	0.55	0	0.44	0	0.00	0	19.42	0	953409	0	64	0	58.08	0	1.19	0	0.00	0	1.02	0	0.02	0	269.54	0	0.67	0	25751	0	1197943	0	171244	0	6593	0	5311	0	0	0	232630	0	14	0	0	0	123	0	14392	0	904	0	15433	0	65.29	0	782165	0	8050	12283	1.525838509317	1197943.0	953409.0	25751.0	171244.0	6593.0	5311.0	0.0	232630.0	782165.0	79.6	2.1	14.3	0.6	0.4	0.0	19.4	65.3	32	32	32.00	6	38334176	22.4	23.2	24.8	21.8	7.7	30.5	13.8	smartseq
1607560	SRR2925878	SRP066154	SRS1161689	SRX1427217	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937688: L1210_57 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_68|cousin 2;;L1210_79|hours since division;;5.1708|sister;;L1210_46|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937688		GSM1937688	L1210_57 scRNA-seq	47125120	736330	2015-12-22 15:48:11	22879977	47125120	736330	2	736330	index:0,count:736330,average:32,stdev:0|index:1,count:736330,average:32,stdev:0	GSM1937688_r1						3.13	1.77	0.38	31928680	34745300	26013740	29782514	108.82	114.49	551600	491618	210.571	1129.912	125	2792	69.39	85.15	717806	382753	717806	382753	63.66	66.88	717806	351126	717806	300635	3478352	10.89	2.04	0	13.86	0	0.53	0	0.39	0	0.00	0	24.17	0	551600	0	64	0	58.10	0	1.22	0	0.00	0	1.02	0	0.01	0	176.72	0	0.67	0	15036	0	736330	0	102084	0	3934	0	2853	0	0	0	177943	0	13	0	0	0	60	0	9535	0	513	0	10121	0	61.05	0	449516	0	5680	8020	1.411971830986	736330.0	551600.0	15036.0	102084.0	3934.0	2853.0	0.0	177943.0	449516.0	74.9	2.0	13.9	0.5	0.4	0.0	24.2	61.0	32	32	32.00	6	23562560	22.5	23.0	24.6	22.2	7.7	30.8	13.8	smartseq
1607704	SRR2925881	SRP066154	SRS1161686	SRX1427220	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937691: L1210_60 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_71|cousin 2;;L1210_81|hours since division;;6.3611|sister;;L1210_49|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937691		GSM1937691	L1210_60 scRNA-seq	29957184	468081	2015-12-22 15:48:11	14603810	29957184	468081	2	468081	index:0,count:468081,average:32,stdev:0|index:1,count:468081,average:32,stdev:0	GSM1937691_r1						3.92	1.86	0.4	20922489	22675311	16992853	19365555	108.38	113.96	361453	323140	208.099	1251.459	117	1883	67.75	83.4	479075	244884	479075	244884	63.36	65.73	479075	229004	479075	193007	2651619	12.67	2.10	0	14.49	0	0.64	0	0.65	0	0.00	0	21.49	0	361453	0	64	0	58.08	0	1.21	0	0.00	0	1.02	0	0.01	0	112.34	0	0.69	0	9842	0	468081	0	67813	0	3000	0	3024	0	0	0	100604	0	8	0	0	0	32	0	5830	0	321	0	6191	0	62.73	0	293640	0	3779	4800	1.270177295581	468081.0	361453.0	9842.0	67813.0	3000.0	3024.0	0.0	100604.0	293640.0	77.2	2.1	14.5	0.6	0.6	0.0	21.5	62.7	32	32	32.00	6	14978592	22.6	22.9	24.5	22.3	7.7	30.8	13.8	smartseq
1607720	SRR2925882	SRP066154	SRS1161685	SRX1427221	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937692: L1210_61 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;2.2833|sister;;L1210_72|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937692		GSM1937692	L1210_61 scRNA-seq	66330432	1036413	2015-12-22 15:48:11	32324068	66330432	1036413	2	1036413	index:0,count:1036413,average:32,stdev:0|index:1,count:1036413,average:32,stdev:0	GSM1937692_r1						6.4	1.9	0.28	46372025	48396238	38164956	41582844	104.37	108.96	801129	727148	208.417	1060.154	125	4052	64.76	78.68	1038568	518813	1038568	518813	59.65	61.68	1038568	477845	1038568	406699	5965908	12.87	2.10	0	13.68	0	0.69	0	0.66	0	0.00	0	21.36	0	801129	0	64	0	58.11	0	1.21	0	0.00	0	1.02	0	0.01	0	248.74	0	0.68	0	21770	0	1036413	0	141730	0	7112	0	6826	0	0	0	221346	0	8	0	0	0	66	0	11188	0	648	0	11910	0	63.62	0	659399	0	6425	9497	1.478132295720	1036413.0	801129.0	21770.0	141730.0	7112.0	6826.0	0.0	221346.0	659399.0	77.3	2.1	13.7	0.7	0.7	0.0	21.4	63.6	32	32	32.00	6	33165216	23.1	22.4	24.0	22.7	7.7	30.8	13.8	smartseq
1607736	SRR2925883	SRP066154	SRS1161684	SRX1427222	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937693: L1210_62 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_40|cousin 2;;L1210_51|hours since division;;2.3|sister;;L1210_73|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937693		GSM1937693	L1210_62 scRNA-seq	51334464	802101	2015-12-22 15:48:11	24988802	51334464	802101	2	802101	index:0,count:802101,average:32,stdev:0|index:1,count:802101,average:32,stdev:0	GSM1937693_r1						3.76	1.75	0.31	36765644	40432152	30096582	34754330	109.97	115.48	635236	571046	206.956	990.595	125	3269	69.65	85.07	821226	442430	821226	442430	63.1	65.96	821226	400834	821226	343051	4070446	11.07	2.12	0	14.35	0	0.58	0	0.33	0	0.00	0	19.89	0	635236	0	64	0	58.11	0	1.21	0	0.00	0	1.02	0	0.01	0	160.42	0	0.68	0	17041	0	802101	0	115131	0	4628	0	2685	0	0	0	159552	0	16	0	0	0	77	0	10173	0	583	0	10849	0	64.84	0	520105	0	6099	8659	1.419740941138	802101.0	635236.0	17041.0	115131.0	4628.0	2685.0	0.0	159552.0	520105.0	79.2	2.1	14.4	0.6	0.3	0.0	19.9	64.8	32	32	32.00	6	25667232	22.5	23.0	24.6	22.1	7.7	30.8	13.8	smartseq
1607754	SRR2925884	SRP066154	SRS1161683	SRX1427223	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937694: L1210_63 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;11.55|sister;;L1210_74|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937694		GSM1937694	L1210_63 scRNA-seq	51358784	802481	2015-12-22 15:48:11	24987975	51358784	802481	2	802481	index:0,count:802481,average:32,stdev:0|index:1,count:802481,average:32,stdev:0	GSM1937694_r1						3.45	1.93	0.36	36933667	40148718	30163725	34393170	108.7	114.02	638297	569102	209.183	1061.741	125	3286	68.81	84.25	837369	439232	837369	439232	63.51	66.25	837369	405383	837369	345427	4232563	11.46	2.11	0	14.57	0	0.74	0	0.37	0	0.00	0	19.34	0	638297	0	64	0	58.11	0	1.26	0	0.00	0	1.02	0	0.01	0	206.35	0	0.66	0	16950	0	802481	0	116934	0	5973	0	3002	0	0	0	155209	0	16	0	0	0	93	0	11248	0	593	0	11950	0	64.97	0	521363	0	6598	9548	1.447105183389	802481.0	638297.0	16950.0	116934.0	5973.0	3002.0	0.0	155209.0	521363.0	79.5	2.1	14.6	0.7	0.4	0.0	19.3	65.0	32	32	32.00	6	25679392	22.5	23.1	24.5	22.2	7.7	30.8	13.8	smartseq
1607773	SRR2925885	SRP066154	SRS1161682	SRX1427224	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937695: L1210_64 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_53|cousin 2;;L1210_75|hours since division;;4.3833|sister;;L1210_85|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937695		GSM1937695	L1210_64 scRNA-seq	58580416	915319	2015-12-22 15:48:11	28554434	58580416	915319	2	915319	index:0,count:915319,average:32,stdev:0|index:1,count:915319,average:32,stdev:0	GSM1937695_r1						4.28	2.03	0.29	41471250	44807681	33956687	38391794	108.05	113.06	716858	629436	211.891	1250.982	117	3511	69.58	84.95	946762	498825	946762	498825	65.48	67.71	946762	469381	946762	397562	4595233	11.08	2.09	0	14.17	0	0.73	0	0.53	0	0.00	0	20.42	0	716858	0	64	0	58.05	0	1.23	0	0.00	0	1.03	0	0.01	0	235.37	0	0.68	0	19175	0	915319	0	129676	0	6641	0	4880	0	0	0	186940	0	20	0	0	0	116	0	14044	0	544	0	14724	0	64.15	0	587182	0	8165	12114	1.483649724434	915319.0	716858.0	19175.0	129676.0	6641.0	4880.0	0.0	186940.0	587182.0	78.3	2.1	14.2	0.7	0.5	0.0	20.4	64.2	32	32	32.00	6	29290208	22.7	22.8	24.4	22.3	7.7	30.8	13.8	smartseq
1607789	SRR2925886	SRP066154	SRS1161681	SRX1427225	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937696: L1210_65 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_54|cousin 2;;L1210_86|hours since division;;8.2833|sister;;L1210_76|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937696		GSM1937696	L1210_65 scRNA-seq	71070208	1110472	2015-12-22 15:48:11	34590570	71070208	1110472	2	1110472	index:0,count:1110472,average:32,stdev:0|index:1,count:1110472,average:32,stdev:0	GSM1937696_r1						3.81	1.85	0.3	50066605	54225067	41304517	46885972	108.31	113.51	864985	769182	215.971	1118.069	125	4200	69.09	83.73	1112977	597592	1112977	597592	63.07	66.0	1112977	545543	1112977	471040	5858032	11.70	2.11	0	13.62	0	0.59	0	0.40	0	0.00	0	21.11	0	864985	0	64	0	58.07	0	1.21	0	0.00	0	1.03	0	0.01	0	249.86	0	0.70	0	23444	0	1110472	0	151291	0	6547	0	4496	0	0	0	234444	0	9	0	0	0	96	0	14658	0	793	0	15556	0	64.27	0	713694	0	8322	12671	1.522590723384	1110472.0	864985.0	23444.0	151291.0	6547.0	4496.0	0.0	234444.0	713694.0	77.9	2.1	13.6	0.6	0.4	0.0	21.1	64.3	32	32	32.00	6	35535104	22.5	23.0	24.5	22.2	7.7	30.8	13.8	smartseq
1607804	SRR2925887	SRP066154	SRS1161680	SRX1427226	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937697: L1210_66 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;9.3375|sister;;L1210_55|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937697		GSM1937697	L1210_66 scRNA-seq	69463296	1085364	2015-12-22 15:48:11	33722038	69463296	1085364	2	1085364	index:0,count:1085364,average:32,stdev:0|index:1,count:1085364,average:32,stdev:0	GSM1937697_r1						4.89	2.25	0.43	49368260	51106884	41285893	44241166	103.52	107.16	853764	738738	213.794	1413.293	110	3923	66.38	79.35	1117685	566688	1117685	566688	66.17	67.48	1117685	564954	1117685	481897	7984425	16.17	1.79	0	12.86	0	0.80	0	0.68	0	0.00	0	19.86	0	853764	0	64	0	58.06	0	1.21	0	0.00	0	1.02	0	0.01	0	260.49	0	0.66	0	19469	0	1085364	0	139580	0	8667	0	7348	0	0	0	215585	0	14	0	0	0	123	0	18210	0	559	0	18906	0	65.80	0	714184	0	10133	15666	1.546037698609	1085364.0	853764.0	19469.0	139580.0	8667.0	7348.0	0.0	215585.0	714184.0	78.7	1.8	12.9	0.8	0.7	0.0	19.9	65.8	32	32	32.00	6	34731648	23.0	22.5	24.1	22.6	7.8	30.8	13.8	smartseq
1607819	SRR2925888	SRP066154	SRS1161679	SRX1427227	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937698: L1210_67 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_45|cousin 2;;L1210_56|hours since division;;1.3833|sister;;L1210_34|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937698		GSM1937698	L1210_67 scRNA-seq	60818112	950283	2015-12-22 15:48:11	29560769	60818112	950283	2	950283	index:0,count:950283,average:32,stdev:0|index:1,count:950283,average:32,stdev:0	GSM1937698_r1						3.44	1.76	0.31	43063426	47417319	34825192	40411543	110.11	116.04	745002	667961	203.763	1039.956	117	4003	69.53	85.98	980269	518033	980269	518033	63.01	66.05	980269	469426	980269	397939	4356581	10.12	2.16	0	14.99	0	0.64	0	0.42	0	0.00	0	20.54	0	745002	0	64	0	58.07	0	1.18	0	0.00	0	1.02	0	0.01	0	228.07	0	0.69	0	20484	0	950283	0	142475	0	6104	0	4000	0	0	0	195177	0	12	0	0	0	82	0	12505	0	697	0	13296	0	63.41	0	602527	0	7334	10731	1.463185164985	950283.0	745002.0	20484.0	142475.0	6104.0	4000.0	0.0	195177.0	602527.0	78.4	2.2	15.0	0.6	0.4	0.0	20.5	63.4	32	32	32.00	6	30409056	22.4	23.1	24.6	22.1	7.7	30.8	13.8	smartseq
1607835	SRR2925889	SRP066154	SRS1161678	SRX1427228	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937699: L1210_68 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_46|cousin 2;;L1210_57|hours since division;;6.0986|sister;;L1210_79|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937699		GSM1937699	L1210_68 scRNA-seq	53467456	835429	2015-12-22 15:48:11	25871229	53467456	835429	2	835429	index:0,count:835429,average:32,stdev:0|index:1,count:835429,average:32,stdev:0	GSM1937699_r1						3.41	1.83	0.26	38222622	42332112	31419789	36608527	110.75	116.51	660061	590453	214.118	1111.239	117	3188	68.63	83.47	851029	453008	851029	453008	60.61	63.12	851029	400037	851029	342565	4676088	12.23	2.18	0	14.05	0	0.69	0	0.38	0	0.00	0	19.92	0	660061	0	64	0	58.10	0	1.23	0	0.00	0	1.02	0	0.01	0	176.91	0	0.68	0	18184	0	835429	0	117373	0	5745	0	3166	0	0	0	166457	0	8	0	0	0	72	0	11035	0	592	0	11707	0	64.96	0	542688	0	6294	9316	1.480139815697	835429.0	660061.0	18184.0	117373.0	5745.0	3166.0	0.0	166457.0	542688.0	79.0	2.2	14.0	0.7	0.4	0.0	19.9	65.0	32	32	32.00	6	26733728	22.6	23.0	24.4	22.3	7.7	30.9	13.8	smartseq
1607947	SRR2925890	SRP066154	SRS1161677	SRX1427229	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937700: L1210_69 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_14|cousin 2;;L1210_80|hours since division;;2.725|sister;;L1210_2|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937700		GSM1937700	L1210_69 scRNA-seq	63820416	997194	2015-12-22 15:48:11	30901998	63820416	997194	2	997194	index:0,count:997194,average:32,stdev:0|index:1,count:997194,average:32,stdev:0	GSM1937700_r1						4.14	1.77	0.28	45278804	49485828	37103608	42618990	109.29	114.86	781909	697703	218.086	1095.738	125	3757	70.06	85.48	1010934	547832	1010934	547832	64.29	67.27	1010934	502664	1010934	431162	4904311	10.83	2.09	0	14.14	0	0.61	0	0.43	0	0.00	0	20.55	0	781909	0	64	0	58.08	0	1.23	0	0.00	0	1.02	0	0.01	0	188.94	0	0.68	0	20862	0	997194	0	141004	0	6121	0	4242	0	0	0	204922	0	11	0	0	0	97	0	12988	0	707	0	13803	0	64.27	0	640905	0	7412	11116	1.499730167296	997194.0	781909.0	20862.0	141004.0	6121.0	4242.0	0.0	204922.0	640905.0	78.4	2.1	14.1	0.6	0.4	0.0	20.5	64.3	32	32	32.00	6	31910208	22.6	23.0	24.5	22.2	7.7	30.9	13.8	smartseq
1607963	SRR2925891	SRP066154	SRS1161676	SRX1427230	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937701: L1210_70 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;7.5667|sister;;L1210_59|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937701		GSM1937701	L1210_70 scRNA-seq	47575232	743363	2015-12-22 15:48:11	23064957	47575232	743363	2	743363	index:0,count:743363,average:32,stdev:0|index:1,count:743363,average:32,stdev:0	GSM1937701_r1						3.72	1.67	0.3	32125103	35397802	26203894	30414191	110.19	116.07	554839	497042	215.446	1097.814	125	2724	70.21	86.05	719631	389546	719631	389546	63.19	66.28	719631	350601	719631	300054	3171406	9.87	2.13	0	13.74	0	0.59	0	0.49	0	0.00	0	24.27	0	554839	0	64	0	58.07	0	1.24	0	0.00	0	1.02	0	0.01	0	157.42	0	0.68	0	15814	0	743363	0	102135	0	4401	0	3673	0	0	0	180450	0	11	0	0	0	65	0	8969	0	491	0	9536	0	60.90	0	452704	0	5486	7453	1.358549033904	743363.0	554839.0	15814.0	102135.0	4401.0	3673.0	0.0	180450.0	452704.0	74.6	2.1	13.7	0.6	0.5	0.0	24.3	60.9	32	32	32.00	6	23787616	22.6	22.9	24.5	22.3	7.7	30.9	13.8	smartseq
1607978	SRR2925892	SRP066154	SRS1161675	SRX1427231	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937702: L1210_71 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_49|cousin 2;;L1210_60|hours since division;;6.3125|sister;;L1210_81|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937702		GSM1937702	L1210_71 scRNA-seq	55554304	868036	2015-12-22 15:48:11	26994414	55554304	868036	2	868036	index:0,count:868036,average:32,stdev:0|index:1,count:868036,average:32,stdev:0	GSM1937702_r1						0.19	1.71	0.13	39321988	44855559	31156680	37897325	114.07	121.63	679213	597792	230.440	1058.228	125	3220	74.33	93.74	902181	504853	902181	504853	65.58	69.8	902181	445421	902181	375916	1353188	3.44	2.56	0	16.20	0	0.58	0	0.19	0	0.00	0	20.98	0	679213	0	64	0	57.99	0	1.17	0	0.00	0	1.02	0	0.02	0	240.38	0	0.70	0	22198	0	868036	0	140633	0	5065	0	1676	0	0	0	182082	0	12	0	0	0	103	0	12176	0	729	0	13020	0	62.05	0	538580	0	6811	10612	1.558067831449	868036.0	679213.0	22198.0	140633.0	5065.0	1676.0	0.0	182082.0	538580.0	78.2	2.6	16.2	0.6	0.2	0.0	21.0	62.0	32	32	32.00	6	27777152	21.9	23.6	25.1	21.6	7.8	30.9	13.8	smartseq
1607994	SRR2925893	SRP066154	SRS1161674	SRX1427232	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937703: L1210_72 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;2.4167|sister;;L1210_61|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937703		GSM1937703	L1210_72 scRNA-seq	78442432	1225663	2015-12-22 15:48:11	38210676	78442432	1225663	2	1225663	index:0,count:1225663,average:32,stdev:0|index:1,count:1225663,average:32,stdev:0	GSM1937703_r1						3.92	2.1	0.29	54752170	56492943	45163622	48535538	103.18	107.47	945577	844684	217.890	1165.023	125	4450	64.73	78.46	1236318	612114	1236318	612114	61.35	63.32	1236318	580137	1236318	493973	7323449	13.38	2.02	0	13.50	0	0.72	0	0.63	0	0.00	0	21.50	0	945577	0	64	0	58.08	0	1.20	0	0.00	0	1.03	0	0.01	0	220.62	0	0.69	0	24717	0	1225663	0	165447	0	8883	0	7704	0	0	0	263499	0	17	0	0	0	116	0	14879	0	794	0	15806	0	63.65	0	780130	0	8175	12864	1.573577981651	1225663.0	945577.0	24717.0	165447.0	8883.0	7704.0	0.0	263499.0	780130.0	77.1	2.0	13.5	0.7	0.6	0.0	21.5	63.6	32	32	32.00	6	39221216	23.1	22.5	24.1	22.6	7.7	30.9	13.8	smartseq
1608010	SRR2925894	SRP066154	SRS1161673	SRX1427233	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937704: L1210_73 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_40|cousin 2;;L1210_51|hours since division;;2.325|sister;;L1210_62|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937704		GSM1937704	L1210_73 scRNA-seq	96444608	1506947	2015-12-22 15:48:11	46786121	96444608	1506947	2	1506947	index:0,count:1506947,average:32,stdev:0|index:1,count:1506947,average:32,stdev:0	GSM1937704_r1						2.96	1.82	0.34	69321572	75022002	57673743	65122494	108.22	112.92	1196479	1058551	220.837	1108.339	125	5719	69.68	83.73	1530333	833732	1530333	833732	64.74	67.25	1530333	774640	1530333	669647	8583220	12.38	2.02	0	13.32	0	0.66	0	0.41	0	0.00	0	19.54	0	1196479	0	64	0	58.10	0	1.25	0	0.00	0	1.03	0	0.01	0	271.25	0	0.68	0	30490	0	1506947	0	200757	0	9881	0	6169	0	0	0	294418	0	15	0	0	0	150	0	20886	0	1002	0	22053	0	66.08	0	995722	0	10715	18356	1.713112459169	1506947.0	1196479.0	30490.0	200757.0	9881.0	6169.0	0.0	294418.0	995722.0	79.4	2.0	13.3	0.7	0.4	0.0	19.5	66.1	32	32	32.00	6	48222304	22.5	23.1	24.6	22.1	7.8	30.8	13.8	smartseq
1608028	SRR2925895	SRP066154	SRS1161672	SRX1427234	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937705: L1210_74 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;11.5667|sister;;L1210_63|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937705		GSM1937705	L1210_74 scRNA-seq	64882880	1013795	2015-12-22 15:48:11	31389986	64882880	1013795	2	1013795	index:0,count:1013795,average:32,stdev:0|index:1,count:1013795,average:32,stdev:0	GSM1937705_r1						3.64	2.03	0.4	45761140	47995076	37259276	41112236	104.88	110.34	791517	708633	209.368	1119.755	125	4021	64.63	79.41	1048605	511547	1048605	511547	59.4	62.48	1048605	470137	1048605	402512	6306530	13.78	2.16	0	14.53	0	0.76	0	0.49	0	0.00	0	20.67	0	791517	0	64	0	58.08	0	1.19	0	0.00	0	1.02	0	0.01	0	260.69	0	0.68	0	21860	0	1013795	0	147310	0	7685	0	5005	0	0	0	209588	0	15	0	0	0	86	0	12609	0	670	0	13380	0	63.54	0	644207	0	7376	10560	1.431670281996	1013795.0	791517.0	21860.0	147310.0	7685.0	5005.0	0.0	209588.0	644207.0	78.1	2.2	14.5	0.8	0.5	0.0	20.7	63.5	32	32	32.00	6	32441440	23.1	22.5	24.1	22.6	7.7	30.9	13.8	smartseq
1608043	SRR2925896	SRP066154	SRS1161670	SRX1427235	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937706: L1210_75 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_64|cousin 2;;L1210_85|hours since division;;5.1|sister;;L1210_53|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937706		GSM1937706	L1210_75 scRNA-seq	81306944	1270421	2015-12-22 15:48:11	39455166	81306944	1270421	2	1270421	index:0,count:1270421,average:32,stdev:0|index:1,count:1270421,average:32,stdev:0	GSM1937706_r1						3.2	1.88	0.35	58173867	62871301	48034665	54308683	108.07	113.06	1005542	883897	215.631	1189.547	117	4886	69.66	84.34	1303236	700417	1303236	700417	64.66	67.41	1303236	650194	1303236	559807	6825650	11.73	2.08	0	13.78	0	0.69	0	0.51	0	0.00	0	19.65	0	1005542	0	64	0	58.06	0	1.26	0	0.00	0	1.02	0	0.01	0	228.68	0	0.68	0	26377	0	1270421	0	175051	0	8805	0	6464	0	0	0	249610	0	22	0	0	0	130	0	19133	0	838	0	20123	0	65.37	0	830491	0	10507	16644	1.584086799277	1270421.0	1005542.0	26377.0	175051.0	8805.0	6464.0	0.0	249610.0	830491.0	79.2	2.1	13.8	0.7	0.5	0.0	19.6	65.4	32	32	32.00	6	40653472	22.5	23.1	24.6	22.1	7.8	30.9	13.8	smartseq
1608060	SRR2925897	SRP066154	SRS1161671	SRX1427236	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937707: L1210_76 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_54|cousin 2;;L1210_86|hours since division;;8.3167|sister;;L1210_65|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937707		GSM1937707	L1210_76 scRNA-seq	67649920	1057030	2015-12-22 15:48:11	34336603	67649920	1057030	2	1057030	index:0,count:1057030,average:32,stdev:0|index:1,count:1057030,average:32,stdev:0	GSM1937707_r1						3.9	1.85	0.39	45382758	49297030	37337768	42501213	108.63	113.83	783484	694672	214.230	1147.134	125	4020	69.48	84.42	1009341	544344	1009341	544344	63.95	66.9	1009341	501047	1009341	431355	5264690	11.60	1.96	0	13.12	0	0.56	0	0.31	0	0.00	0	25.01	0	783484	0	64	0	58.07	0	1.23	0	0.00	0	1.02	0	0.01	0	223.84	0	0.87	0	20668	0	1057030	0	138661	0	5923	0	3284	0	0	0	264339	0	10	0	0	0	113	0	13187	0	690	0	14000	0	61.00	0	644823	0	7597	11314	1.489272081085	1057030.0	783484.0	20668.0	138661.0	5923.0	3284.0	0.0	264339.0	644823.0	74.1	2.0	13.1	0.6	0.3	0.0	25.0	61.0	32	32	32.00	6	33824960	22.5	23.1	24.5	22.2	7.7	30.9	13.8	smartseq
1608075	SRR2925898	SRP066154	SRS1161669	SRX1427237	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937708: L1210_77 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;11.5667|sister;;L1210_87|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937708		GSM1937708	L1210_77 scRNA-seq	91357376	1427459	2015-12-22 15:48:11	44186160	91357376	1427459	2	1427459	index:0,count:1427459,average:32,stdev:0|index:1,count:1427459,average:32,stdev:0	GSM1937708_r1						3.41	1.73	0.38	65407678	71474374	53496069	61387047	109.28	114.75	1129826	1005001	217.298	1064.762	125	5526	69.34	84.76	1470213	783369	1470213	783369	63.8	66.64	1470213	720842	1470213	615925	7508370	11.48	2.12	0	14.40	0	0.73	0	0.34	0	0.00	0	19.78	0	1129826	0	64	0	58.08	0	1.21	0	0.00	0	1.02	0	0.01	0	285.49	0	0.67	0	30303	0	1427459	0	205562	0	10443	0	4788	0	0	0	282402	0	22	0	0	0	147	0	19209	0	971	0	20349	0	64.75	0	924264	0	10112	16665	1.648041930380	1427459.0	1129826.0	30303.0	205562.0	10443.0	4788.0	0.0	282402.0	924264.0	79.1	2.1	14.4	0.7	0.3	0.0	19.8	64.7	32	32	32.00	6	45678688	22.4	23.2	24.7	22.0	7.8	30.9	13.8	smartseq
1608092	SRR2925899	SRP066154	SRS1161668	SRX1427238	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937709: L1210_78 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;12.8|sister;;L1210_88|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937709		GSM1937709	L1210_78 scRNA-seq	49836736	778699	2015-12-22 15:48:11	24167588	49836736	778699	2	778699	index:0,count:778699,average:32,stdev:0|index:1,count:778699,average:32,stdev:0	GSM1937709_r1						4.52	1.85	0.36	35386138	38524729	28776479	32961881	108.87	114.54	611593	548251	210.427	1116.645	125	3091	68.85	84.66	798973	421085	798973	421085	63.09	66.25	798973	385861	798973	329541	3956782	11.18	2.17	0	14.67	0	0.65	0	0.46	0	0.00	0	20.35	0	611593	0	64	0	58.10	0	1.24	0	0.00	0	1.02	0	0.01	0	200.24	0	0.68	0	16929	0	778699	0	114206	0	5036	0	3616	0	0	0	158454	0	6	0	0	0	73	0	9990	0	497	0	10566	0	63.87	0	497387	0	6164	8377	1.359020116807	778699.0	611593.0	16929.0	114206.0	5036.0	3616.0	0.0	158454.0	497387.0	78.5	2.2	14.7	0.6	0.5	0.0	20.3	63.9	32	32	32.00	6	24918368	22.6	22.9	24.4	22.3	7.7	30.9	13.8	smartseq
1609739	SRR2925900	SRP066154	SRS1161667	SRX1427239	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937710: L1210_79 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_46|cousin 2;;L1210_57|hours since division;;6.1142|sister;;L1210_68|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937710		GSM1937710	L1210_79 scRNA-seq	7936	124	2015-12-22 15:48:11	86052	7936	124	2	124	index:0,count:124,average:32,stdev:0|index:1,count:124,average:32,stdev:0	GSM1937710_r1						2.27	4.55	2.27	1714	1701	1301	1466	99.24	112.68	30	28	147.321	232.067	133	2	66.67	86.96	44	20	44	20	63.33	69.57	44	19	44	16	123	7.18	0.00	0	5.65	0	0.00	0	0.00	0	0.00	0	75.81	0	30	0	64	0	57.43	0	0.00	0	0.00	0	0.00	0	0.00	0	0.45	0	1.14	0	0	0	124	0	7	0	0	0	0	0	0	0	94	0	0	0	0	0	0	0	0	0	0	0	0	0	18.55	0	23	0	0	0	-nan	124.0	30.0	0.0	7.0	0.0	0.0	0.0	94.0	23.0	24.2	0.0	5.6	0.0	0.0	0.0	75.8	18.5	32	32	32.00	6	3968	24.4	20.3	25.1	23.1	7.2	26.2	13.3	smartseq
1609754	SRR2925901	SRP066154	SRS1161666	SRX1427240	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937711: L1210_80 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_2|cousin 2;;L1210_69|hours since division;;2.6417|sister;;L1210_14|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937711		GSM1937711	L1210_80 scRNA-seq	5624960	87890	2015-12-22 15:48:11	3112680	5624960	87890	2	87890	index:0,count:87890,average:32,stdev:0|index:1,count:87890,average:32,stdev:0	GSM1937711_r1						3.8	2.11	0.25	3759166	4133243	3079590	3518669	109.95	114.26	64929	58626	202.453	1138.438	141	356	71.58	87.32	85264	46473	85264	46473	66.3	68.81	85264	43048	85264	36624	336524	8.95	2.03	0	13.32	0	0.58	0	0.46	0	0.00	0	25.08	0	64929	0	64	0	57.97	0	1.26	0	0.00	0	1.02	0	0.01	0	39.55	0	0.88	0	1786	0	87890	0	11706	0	513	0	405	0	0	0	22043	0	1	0	0	0	10	0	967	0	90	0	1068	0	60.56	0	53223	0	695	750	1.079136690647	87890.0	64929.0	1786.0	11706.0	513.0	405.0	0.0	22043.0	53223.0	73.9	2.0	13.3	0.6	0.5	0.0	25.1	60.6	32	32	32.00	6	2812480	21.3	22.6	26.0	22.4	7.7	29.0	13.5	smartseq
1609770	SRR2925902	SRP066154	SRS1161665	SRX1427241	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937712: L1210_81 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_49|cousin 2;;L1210_60|hours since division;;6.3306|sister;;L1210_71|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937712		GSM1937712	L1210_81 scRNA-seq	125376	1959	2015-12-22 15:48:11	150380	125376	1959	2	1959	index:0,count:1959,average:32,stdev:0|index:1,count:1959,average:32,stdev:0	GSM1937712_r1						4.48	2.04	0.0	65951	74616	54808	64412	113.14	117.52	1142	1014	246.236	1441.736	143	11	72.24	86.93	1474	825	1474	825	68.04	68.28	1474	777	1474	648	6718	10.19	2.14	0	9.85	0	0.61	0	0.61	0	0.00	0	40.48	0	1142	0	64	0	57.79	0	0.00	0	0.00	0	1.00	0	0.01	0	0	0	1.01	0	42	0	1959	0	193	0	12	0	12	0	0	0	793	0	0	0	0	0	0	0	8	0	1	0	9	0	48.44	0	949	0	6	6	1.000000000000	1959.0	1142.0	42.0	193.0	12.0	12.0	0.0	793.0	949.0	58.3	2.1	9.9	0.6	0.6	0.0	40.5	48.4	32	32	32.00	6	62688	20.8	22.0	27.3	22.2	7.6	28.4	13.5	smartseq
1609787	SRR2925903	SRP066154	SRS1161664	SRX1427242	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937713: L1210_82 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_6|cousin 2;;L1210_29|hours since division;;1.0833|sister;;L1210_18|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937713		GSM1937713	L1210_82 scRNA-seq	4312256	67379	2015-12-22 15:48:11	2412663	4312256	67379	2	67379	index:0,count:67379,average:32,stdev:0|index:1,count:67379,average:32,stdev:0	GSM1937713_r1						4.65	1.86	0.21	2817113	3080349	2324874	2636854	109.34	113.42	48674	44517	201.353	941.343	141	295	70.88	85.86	62714	34500	62714	34500	65.3	67.83	62714	31784	62714	27256	269395	9.56	2.09	0	12.60	0	0.44	0	0.41	0	0.00	0	26.91	0	48674	0	64	0	57.95	0	1.33	0	0.00	0	1.01	0	0.02	0	34.65	0	0.92	0	1408	0	67379	0	8493	0	294	0	276	0	0	0	18135	0	0	0	0	0	6	0	601	0	76	0	683	0	59.63	0	40181	0	448	474	1.058035714286	67379.0	48674.0	1408.0	8493.0	294.0	276.0	0.0	18135.0	40181.0	72.2	2.1	12.6	0.4	0.4	0.0	26.9	59.6	32	32	32.00	6	2156128	21.3	22.6	26.1	22.3	7.7	28.9	13.5	smartseq
1609803	SRR2925904	SRP066154	SRS1161663	SRX1427243	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937714: L1210_83 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_7|cousin 2;;L1210_19|hours since division;;1.55|sister;;L1210_30|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937714		GSM1937714	L1210_83 scRNA-seq	252864	3951	2015-12-22 15:48:11	218023	252864	3951	2	3951	index:0,count:3951,average:32,stdev:0|index:1,count:3951,average:32,stdev:0	GSM1937714_r1						4.55	1.8	0.0	136473	149321	115991	131313	109.41	113.21	2364	2053	245.574	1644.716	152	19	74.2	87.22	2947	1754	2947	1754	69.54	71.56	2947	1644	2947	1439	13125	9.62	1.42	0	8.93	0	0.56	0	0.20	0	0.00	0	39.41	0	2364	0	64	0	57.73	0	1.00	0	0.00	0	1.00	0	0.01	0	14.22	0	1.01	0	56	0	3951	0	353	0	22	0	8	0	0	0	1557	0	0	0	0	0	0	0	30	0	5	0	35	0	50.90	0	2011	0	27	27	1.000000000000	3951.0	2364.0	56.0	353.0	22.0	8.0	0.0	1557.0	2011.0	59.8	1.4	8.9	0.6	0.2	0.0	39.4	50.9	32	32	32.00	6	126432	20.9	21.9	27.4	22.1	7.7	28.4	13.4	smartseq
1609817	SRR2925905	SRP066154	SRS1161662	SRX1427244	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937715: L1210_84 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;10.3333|sister;;L1210_8|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937715		GSM1937715	L1210_84 scRNA-seq	5014144	78346	2015-12-22 15:48:11	2793050	5014144	78346	2	78346	index:0,count:78346,average:32,stdev:0|index:1,count:78346,average:32,stdev:0	GSM1937715_r1						3.78	1.81	0.22	3345980	3625821	2742252	3088082	108.36	112.61	57819	53403	196.644	870.539	125	362	68.75	83.86	74854	39749	74854	39749	62.64	65.94	74854	36216	74854	31254	358043	10.70	2.16	0	13.30	0	0.52	0	0.37	0	0.00	0	25.31	0	57819	0	64	0	57.95	0	1.32	0	0.00	0	1.01	0	0.02	0	56.41	0	0.89	0	1693	0	78346	0	10421	0	411	0	286	0	0	0	19830	0	0	0	0	0	10	0	652	0	75	0	737	0	60.50	0	47398	0	488	506	1.036885245902	78346.0	57819.0	1693.0	10421.0	411.0	286.0	0.0	19830.0	47398.0	73.8	2.2	13.3	0.5	0.4	0.0	25.3	60.5	32	32	32.00	6	2507072	21.3	22.9	26.0	22.1	7.7	29.1	13.5	smartseq
1609833	SRR2925906	SRP066154	SRS1161661	SRX1427245	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937716: L1210_85 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_53|cousin 2;;L1210_75|hours since division;;4.4167|sister;;L1210_64|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937716		GSM1937716	L1210_85 scRNA-seq	4466368	69787	2015-12-22 15:48:11	2495273	4466368	69787	2	69787	index:0,count:69787,average:32,stdev:0|index:1,count:69787,average:32,stdev:0	GSM1937716_r1						6.29	1.71	0.27	2910194	3106373	2413583	2668686	106.74	110.57	50287	45761	197.086	1086.378	141	323	68.3	82.34	65014	34346	65014	34346	64.36	66.95	65014	32366	65014	27927	379545	13.04	1.99	0	12.28	0	0.62	0	0.45	0	0.00	0	26.87	0	50287	0	64	0	57.95	0	1.16	0	0.00	0	1.02	0	0.02	0	41.87	0	0.90	0	1389	0	69787	0	8573	0	432	0	316	0	0	0	18752	0	0	0	0	0	7	0	630	0	67	0	704	0	59.77	0	41714	0	471	484	1.027600849257	69787.0	50287.0	1389.0	8573.0	432.0	316.0	0.0	18752.0	41714.0	72.1	2.0	12.3	0.6	0.5	0.0	26.9	59.8	32	32	32.00	6	2233184	21.7	22.4	25.7	22.5	7.7	29.0	13.5	smartseq
1609849	SRR2925907	SRP066154	SRS1161660	SRX1427246	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937717: L1210_86 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_65|cousin 2;;L1210_76|hours since division;;8.3833|sister;;L1210_54|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937717		GSM1937717	L1210_86 scRNA-seq	5064064	79126	2015-12-22 15:48:11	2808657	5064064	79126	2	79126	index:0,count:79126,average:32,stdev:0|index:1,count:79126,average:32,stdev:0	GSM1937717_r1						3.47	1.89	0.34	3217018	3266486	2589258	2759786	101.54	106.59	55717	51011	191.629	1079.437	133	348	62.46	77.71	76134	34802	76134	34802	57.8	62.01	76134	32203	76134	27772	458388	14.25	2.03	0	13.82	0	0.69	0	0.51	0	0.00	0	28.38	0	55717	0	64	0	57.94	0	1.21	0	0.00	0	1.04	0	0.02	0	47.48	0	0.94	0	1606	0	79126	0	10933	0	549	0	401	0	0	0	22459	0	1	0	0	0	2	0	668	0	80	0	751	0	56.60	0	44784	0	504	523	1.037698412698	79126.0	55717.0	1606.0	10933.0	549.0	401.0	0.0	22459.0	44784.0	70.4	2.0	13.8	0.7	0.5	0.0	28.4	56.6	32	32	32.00	6	2532032	22.3	21.9	25.1	23.0	7.7	29.1	13.6	smartseq
1609865	SRR2925908	SRP066154	SRS1161658	SRX1427247	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937718: L1210_87 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;11.6|sister;;L1210_77|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937718		GSM1937718	L1210_87 scRNA-seq	6865664	107276	2015-12-22 15:48:11	3786988	6865664	107276	2	107276	index:0,count:107276,average:32,stdev:0|index:1,count:107276,average:32,stdev:0	GSM1937718_r1						4.85	1.64	0.17	4508684	4855924	3693691	4131728	107.7	111.86	77951	71475	198.364	948.290	125	454	68.89	84.07	100793	53699	100793	53699	63.18	66.56	100793	49250	100793	42515	469564	10.41	2.12	0	13.12	0	0.55	0	0.48	0	0.00	0	26.31	0	77951	0	64	0	57.93	0	1.20	0	0.00	0	1.03	0	0.02	0	64.37	0	0.87	0	2278	0	107276	0	14074	0	591	0	514	0	0	0	28220	0	2	0	0	0	7	0	949	0	118	0	1076	0	59.54	0	63877	0	694	745	1.073487031700	107276.0	77951.0	2278.0	14074.0	591.0	514.0	0.0	28220.0	63877.0	72.7	2.1	13.1	0.6	0.5	0.0	26.3	59.5	32	32	32.00	6	3432832	21.7	22.5	25.8	22.3	7.7	29.0	13.5	smartseq
1609881	SRR2925909	SRP066154	SRS1161659	SRX1427248	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937719: L1210_88 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;12.8167|sister;;L1210_78|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937719		GSM1937719	L1210_88 scRNA-seq	271680	4245	2015-12-22 15:48:11	228239	271680	4245	2	4245	index:0,count:4245,average:32,stdev:0|index:1,count:4245,average:32,stdev:0	GSM1937719_r1						4.02	1.29	0.92	141194	150550	117309	130414	106.63	111.17	2452	2182	241.648	1260.473	146	15	69.21	83.43	3258	1697	3258	1697	65.05	68.44	3258	1595	3258	1392	18791	13.31	1.79	0	9.85	0	0.80	0	0.42	0	0.00	0	41.01	0	2452	0	64	0	57.79	0	1.00	0	0.00	0	1.06	0	0.02	0	15.28	0	1.05	0	76	0	4245	0	418	0	34	0	18	0	0	0	1741	0	0	0	0	0	0	0	31	0	9	0	40	0	47.92	0	2034	0	23	23	1.000000000000	4245.0	2452.0	76.0	418.0	34.0	18.0	0.0	1741.0	2034.0	57.8	1.8	9.8	0.8	0.4	0.0	41.0	47.9	32	32	32.00	6	135840	21.5	21.6	27.0	22.3	7.6	28.5	13.5	smartseq
1609993	SRR2925910	SRP066154	SRS1161657	SRX1427249	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937720: CD8_1 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_2|cousin 2;;CD8_4|hours since division;;8.35|sister;;CD8_3|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937720		GSM1937720	CD8_1 scRNA-seq	49765504	777586	2015-12-22 15:48:11	23875821	49765504	777586	2	777586	index:0,count:777586,average:32,stdev:0|index:1,count:777586,average:32,stdev:0	GSM1937720_r1						4.91	3.79	0.04	33652056	33895455	24645749	25771825	100.72	104.57	589509	513500	160.295	1141.267	98	3914	70.36	95.91	935520	414761	935520	414761	86.66	88.71	935520	510887	935520	383599	1386834	4.12	1.36	0	20.20	0	0.68	0	0.17	0	0.00	0	23.34	0	589509	0	64	0	58.04	0	1.29	0	0.00	0	1.01	0	0.01	0	199.95	0	0.48	0	10570	0	777586	0	157083	0	5256	0	1352	0	0	0	181469	0	24	0	0	0	93	0	17177	0	190	0	17484	0	55.61	0	432426	0	4601	17428	3.787872201695	777586.0	589509.0	10570.0	157083.0	5256.0	1352.0	0.0	181469.0	432426.0	75.8	1.4	20.2	0.7	0.2	0.0	23.3	55.6	32	32	32.00	6	24882752	24.2	21.1	23.1	23.9	7.7	30.9	13.8	smartseq
1610009	SRR2925911	SRP066154	SRS1161656	SRX1427250	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937721: CD8_2 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_1|cousin 2;;CD8_3|hours since division;;8.0917|sister;;CD8_4|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937721		GSM1937721	CD8_2 scRNA-seq	69539904	1086561	2015-12-22 15:48:11	33758302	69539904	1086561	2	1086561	index:0,count:1086561,average:32,stdev:0|index:1,count:1086561,average:32,stdev:0	GSM1937721_r1						2.09	2.27	0.05	50197257	57480820	41272092	49614343	114.51	120.21	866899	772569	233.183	1093.112	125	3671	70.7	85.97	1136579	612880	1136579	612880	61.63	62.53	1136579	534261	1136579	445792	4974585	9.91	2.28	0	14.17	0	0.69	0	0.33	0	0.00	0	19.20	0	866899	0	64	0	58.13	0	1.15	0	0.00	0	1.02	0	0.01	0	260.77	0	0.63	0	24794	0	1086561	0	153963	0	7484	0	3597	0	0	0	208581	0	19	0	0	0	94	0	14333	0	722	0	15168	0	65.61	0	712936	0	7307	13001	1.779252771315	1086561.0	866899.0	24794.0	153963.0	7484.0	3597.0	0.0	208581.0	712936.0	79.8	2.3	14.2	0.7	0.3	0.0	19.2	65.6	32	32	32.00	6	34769952	22.5	23.1	24.7	22.0	7.7	30.8	13.8	smartseq
1610027	SRR2925912	SRP066154	SRS1161655	SRX1427251	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937722: CD8_3 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_2|cousin 2;;CD8_4|hours since division;;8.425|sister;;CD8_1|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937722		GSM1937722	CD8_3 scRNA-seq	82757312	1293083	2015-12-22 15:48:11	40160078	82757312	1293083	2	1293083	index:0,count:1293083,average:32,stdev:0|index:1,count:1293083,average:32,stdev:0	GSM1937722_r1						1.56	2.39	0.04	59907716	67532034	49363034	58293248	112.73	118.09	1034490	919268	231.572	1103.309	100	4460	70.04	84.97	1356723	724571	1356723	724571	61.78	62.69	1356723	639084	1356723	534549	5971212	9.97	2.19	0	14.06	0	0.64	0	0.37	0	0.00	0	18.98	0	1034490	0	64	0	58.12	0	1.15	0	0.00	0	1.02	0	0.01	0	290.94	0	0.63	0	28365	0	1293083	0	181796	0	8316	0	4847	0	0	0	245430	0	18	0	0	0	111	0	17827	0	777	0	18733	0	65.94	0	852694	0	8515	16119	1.893012331180	1293083.0	1034490.0	28365.0	181796.0	8316.0	4847.0	0.0	245430.0	852694.0	80.0	2.2	14.1	0.6	0.4	0.0	19.0	65.9	32	32	32.00	6	41378656	22.4	23.2	24.8	21.9	7.8	30.8	13.8	smartseq
1610042	SRR2925913	SRP066154	SRS1161654	SRX1427252	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937723: CD8_4 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_1|cousin 2;;CD8_3|hours since division;;8.1667|sister;;CD8_2|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937723		GSM1937723	CD8_4 scRNA-seq	87278400	1363725	2015-12-22 15:48:11	42472358	87278400	1363725	2	1363725	index:0,count:1363725,average:32,stdev:0|index:1,count:1363725,average:32,stdev:0	GSM1937723_r1						2.06	2.61	0.04	64259572	73342999	51437685	61790002	114.14	120.13	1110624	971310	224.868	1117.537	100	4902	73.1	91.28	1528954	811878	1528954	811878	68.27	69.04	1528954	758219	1528954	614058	4188984	6.52	2.11	0	16.22	0	0.87	0	0.26	0	0.00	0	17.43	0	1110624	0	64	0	58.13	0	1.20	0	0.00	0	1.02	0	0.01	0	306.84	0	0.62	0	28774	0	1363725	0	221166	0	11867	0	3516	0	0	0	237718	0	25	0	0	0	153	0	22331	0	865	0	23374	0	65.22	0	889458	0	8980	21058	2.344988864143	1363725.0	1110624.0	28774.0	221166.0	11867.0	3516.0	0.0	237718.0	889458.0	81.4	2.1	16.2	0.9	0.3	0.0	17.4	65.2	32	32	32.00	6	43639200	22.3	23.2	24.8	21.9	7.8	30.8	13.8	smartseq
1610058	SRR2925914	SRP066154	SRS1161653	SRX1427253	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937724: CD8_5 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_6|cousin 2;;CD8_7|hours since division;;9.475|sister;;CD8_8|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937724		GSM1937724	CD8_5 scRNA-seq	155889600	2435775	2015-12-22 15:48:11	75338080	155889600	2435775	2	2435775	index:0,count:2435775,average:32,stdev:0|index:1,count:2435775,average:32,stdev:0	GSM1937724_r1						2.24	2.56	0.05	114494536	129248617	92577194	109774219	112.89	118.58	1981072	1729256	210.464	1189.107	105	9231	73.31	90.63	2690335	1452375	2690335	1452375	68.2	69.42	2690335	1351117	2690335	1112460	8023298	7.01	2.01	0	15.54	0	0.83	0	0.28	0	0.00	0	17.55	0	1981072	0	64	0	58.11	0	1.21	0	0.00	0	1.01	0	0.01	0	381.25	0	0.60	0	49075	0	2435775	0	378480	0	20337	0	6809	0	0	0	427557	0	35	0	0	0	304	0	43393	0	1311	0	45043	0	65.79	0	1602592	0	13324	42600	3.197238066647	2435775.0	1981072.0	49075.0	378480.0	20337.0	6809.0	0.0	427557.0	1602592.0	81.3	2.0	15.5	0.8	0.3	0.0	17.6	65.8	32	32	32.00	6	77944800	22.6	23.0	24.6	22.1	7.8	30.8	13.8	smartseq
1610074	SRR2925915	SRP066154	SRS1161652	SRX1427254	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937725: CD8_6 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_5|cousin 2;;CD8_8|hours since division;;9.3333|sister;;CD8_7|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937725		GSM1937725	CD8_6 scRNA-seq	169222272	2644098	2015-12-22 15:48:11	81612853	169222272	2644098	2	2644098	index:0,count:2644098,average:32,stdev:0|index:1,count:2644098,average:32,stdev:0	GSM1937725_r1						2.51	2.4	0.03	123016336	142337268	97790816	120013649	115.71	122.72	2128038	1892358	216.594	1091.036	117	9554	72.86	91.62	2902742	1550407	2902742	1550407	65.27	66.46	2902742	1389059	2902742	1124674	7353705	5.98	2.27	0	16.48	0	0.77	0	0.26	0	0.00	0	18.49	0	2128038	0	64	0	58.13	0	1.20	0	0.00	0	1.01	0	0.01	0	352.55	0	0.60	0	60095	0	2644098	0	435806	0	20319	0	6878	0	0	0	488863	0	37	0	0	0	271	0	39771	0	1524	0	41603	0	64.00	0	1692232	0	11398	38994	3.421126513423	2644098.0	2128038.0	60095.0	435806.0	20319.0	6878.0	0.0	488863.0	1692232.0	80.5	2.3	16.5	0.8	0.3	0.0	18.5	64.0	32	32	32.00	6	84611136	22.3	23.2	24.8	22.0	7.7	30.9	13.8	smartseq
1610091	SRR2925916	SRP066154	SRS1161650	SRX1427255	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937726: CD8_7 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_5|cousin 2;;CD8_8|hours since division;;9.3583|sister;;CD8_6|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937726		GSM1937726	CD8_7 scRNA-seq	36853504	575836	2015-12-22 15:48:11	17792293	36853504	575836	2	575836	index:0,count:575836,average:32,stdev:0|index:1,count:575836,average:32,stdev:0	GSM1937726_r1						0.11	1.77	0.0	23988679	25197711	21255092	22769297	105.04	107.12	419585	407063	132.270	443.326	90	3345	86.04	97.16	516173	361025	516173	361025	85.16	88.06	516173	357311	516173	327213	432747	1.80	1.29	0	8.34	0	0.26	0	0.12	0	0.00	0	26.75	0	419585	0	64	0	58.48	0	1.35	0	0.02	0	1.02	0	0.01	0	148.07	0	0.55	0	7417	0	575836	0	48016	0	1518	0	711	0	0	0	154022	0	0	0	0	0	35	0	3331	0	142	0	3508	0	64.53	0	371569	0	1014	3260	3.214990138067	575836.0	419585.0	7417.0	48016.0	1518.0	711.0	0.0	154022.0	371569.0	72.9	1.3	8.3	0.3	0.1	0.0	26.7	64.5	32	32	32.00	6	18426752	24.5	20.9	22.6	24.4	7.6	30.9	13.9	smartseq
1610107	SRR2925917	SRP066154	SRS1161651	SRX1427256	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937727: CD8_8 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_6|cousin 2;;CD8_7|hours since division;;9.5667|sister;;CD8_5|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937727		GSM1937727	CD8_8 scRNA-seq	401664	6276	2015-12-22 15:48:11	274870	401664	6276	2	6276	index:0,count:6276,average:32,stdev:0|index:1,count:6276,average:32,stdev:0	GSM1937727_r1						3.83	1.51	0.0	251039	264198	212809	231272	105.24	108.68	4479	4243	138.731	584.134	74	51	76.89	90.73	5775	3444	5775	3444	74.26	76.21	5775	3326	5775	2893	16788	6.69	2.17	0	10.88	0	0.49	0	0.13	0	0.00	0	28.01	0	4479	0	64	0	58.03	0	1.00	0	0.00	0	1.07	0	0.01	0	11.30	0	0.52	0	136	0	6276	0	683	0	31	0	8	0	0	0	1758	0	0	0	0	0	0	0	102	0	3	0	105	0	60.48	0	3796	0	45	87	1.933333333333	6276.0	4479.0	136.0	683.0	31.0	8.0	0.0	1758.0	3796.0	71.4	2.2	10.9	0.5	0.1	0.0	28.0	60.5	32	32	32.00	6	200832	24.0	21.4	23.0	23.9	7.7	30.9	13.8	smartseq
1610123	SRR2925918	SRP066154	SRS1161649	SRX1427257	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937728: CD8_9 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_11|cousin 2;;CD8_12|hours since division;;6.1167|sister;;CD8_10|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937728		GSM1937728	CD8_9 scRNA-seq	141159936	2205624	2015-12-22 15:48:11	68362951	141159936	2205624	2	2205624	index:0,count:2205624,average:32,stdev:0|index:1,count:2205624,average:32,stdev:0	GSM1937728_r1						1.92	2.34	0.04	103535644	120104588	82076575	101008734	116.0	123.07	1789986	1612026	213.449	940.782	100	8516	72.3	91.16	2460420	1294081	2460420	1294081	64.38	65.45	2460420	1152434	2460420	929102	6322042	6.11	2.27	0	16.79	0	0.74	0	0.25	0	0.00	0	17.85	0	1789986	0	64	0	58.12	0	1.21	0	0.00	0	1.01	0	0.01	0	345.23	0	0.63	0	50135	0	2205624	0	370372	0	16311	0	5583	0	0	0	393744	0	35	0	0	0	206	0	29824	0	1372	0	31437	0	64.36	0	1419614	0	9581	28887	3.015029746373	2205624.0	1789986.0	50135.0	370372.0	16311.0	5583.0	0.0	393744.0	1419614.0	81.2	2.3	16.8	0.7	0.3	0.0	17.9	64.4	32	32	32.00	6	70579968	22.2	23.4	25.0	21.7	7.8	30.9	13.8	smartseq
1610139	SRR2925919	SRP066154	SRS1161648	SRX1427258	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937729: CD8_10 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_11|cousin 2;;CD8_12|hours since division;;6.15|sister;;CD8_9|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937729		GSM1937729	CD8_10 scRNA-seq	136716736	2136199	2015-12-22 15:48:11	66126404	136716736	2136199	2	2136199	index:0,count:2136199,average:32,stdev:0|index:1,count:2136199,average:32,stdev:0	GSM1937729_r1						2.4	3.04	0.04	100535790	112306145	77780333	91814184	111.71	118.04	1741644	1516917	201.523	1096.132	105	8548	72.74	93.93	2526906	1266806	2526906	1266806	72.6	73.72	2526906	1264432	2526906	994193	4682759	4.66	1.98	0	18.40	0	0.90	0	0.21	0	0.00	0	17.36	0	1741644	0	64	0	58.08	0	1.23	0	0.00	0	1.01	0	0.01	0	384.52	0	0.60	0	42318	0	2136199	0	393027	0	19182	0	4586	0	0	0	370787	0	33	0	0	0	248	0	39325	0	1334	0	40940	0	63.13	0	1348617	0	9806	39522	4.030389557414	2136199.0	1741644.0	42318.0	393027.0	19182.0	4586.0	0.0	370787.0	1348617.0	81.5	2.0	18.4	0.9	0.2	0.0	17.4	63.1	32	32	32.00	6	68358368	22.7	22.8	24.5	22.3	7.8	30.8	13.8	smartseq
1610249	SRR2925920	SRP066154	SRS1161647	SRX1427259	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937730: CD8_11 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_9|cousin 2;;CD8_10|hours since division;;6.4833|sister;;CD8_12|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937730		GSM1937730	CD8_11 scRNA-seq	87001152	1359393	2015-12-22 15:48:11	42210959	87001152	1359393	2	1359393	index:0,count:1359393,average:32,stdev:0|index:1,count:1359393,average:32,stdev:0	GSM1937730_r1						2.11	2.26	0.05	63955949	70930178	53426664	61595240	110.9	115.29	1102907	961596	231.730	1193.979	110	4698	71.57	85.64	1431724	789339	1431724	789339	65.82	66.79	1431724	725968	1431724	615642	6623729	10.36	1.97	0	13.33	0	0.79	0	0.35	0	0.00	0	17.72	0	1102907	0	64	0	58.13	0	1.15	0	0.00	0	1.02	0	0.01	0	287.87	0	0.60	0	26808	0	1359393	0	181162	0	10805	0	4812	0	0	0	240869	0	15	0	0	0	148	0	21909	0	812	0	22884	0	67.81	0	921745	0	9734	19914	2.045818779536	1359393.0	1102907.0	26808.0	181162.0	10805.0	4812.0	0.0	240869.0	921745.0	81.1	2.0	13.3	0.8	0.4	0.0	17.7	67.8	32	32	32.00	6	43500576	22.4	23.1	24.8	21.9	7.8	30.8	13.8	smartseq
1610265	SRR2925921	SRP066154	SRS1161646	SRX1427260	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937731: CD8_12 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_9|cousin 2;;CD8_10|hours since division;;6.5167|sister;;CD8_11|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937731		GSM1937731	CD8_12 scRNA-seq	11308672	176698	2015-12-22 15:48:11	5510450	11308672	176698	2	176698	index:0,count:176698,average:32,stdev:0|index:1,count:176698,average:32,stdev:0	GSM1937731_r1						14.42	2.34	0.0	7987729	7850900	5617138	5741853	98.29	102.22	138274	119914	178.398	1181.825	102	890	67.7	96.05	208974	93605	208974	93605	91.32	92.57	208974	126265	208974	90213	312303	3.91	1.30	0	23.10	0	0.57	0	0.24	0	0.00	0	20.94	0	138274	0	64	0	58.22	0	1.28	0	0.00	0	1.01	0	0.00	0	57.83	0	0.48	0	2290	0	176698	0	40821	0	1001	0	422	0	0	0	37001	0	18	0	0	0	22	0	3020	0	46	0	3106	0	55.15	0	97453	0	644	3212	4.987577639752	176698.0	138274.0	2290.0	40821.0	1001.0	422.0	0.0	37001.0	97453.0	78.3	1.3	23.1	0.6	0.2	0.0	20.9	55.2	32	32	32.00	6	5654336	26.2	19.1	21.0	26.2	7.6	30.9	13.9	smartseq
1610280	SRR2925922	SRP066154	SRS1161645	SRX1427261	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937732: CD8_13 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;3.25|sister;;CD8_15|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937732		GSM1937732	CD8_13 scRNA-seq	87479680	1366870	2015-12-22 15:48:11	42202035	87479680	1366870	2	1366870	index:0,count:1366870,average:32,stdev:0|index:1,count:1366870,average:32,stdev:0	GSM1937732_r1						2.01	2.27	0.1	63274698	67838246	52773112	58961921	107.21	111.73	1094090	985548	213.930	1002.646	125	5201	66.17	79.35	1391041	723982	1391041	723982	58.45	60.25	1391041	639504	1391041	549750	7956902	12.58	2.08	0	13.29	0	0.56	0	0.51	0	0.00	0	18.88	0	1094090	0	64	0	58.14	0	1.19	0	0.00	0	1.02	0	0.01	0	328.05	0	0.61	0	28485	0	1366870	0	181683	0	7663	0	7003	0	0	0	258114	0	19	0	0	0	147	0	17713	0	827	0	18706	0	66.75	0	912407	0	9180	15584	1.697603485839	1366870.0	1094090.0	28485.0	181683.0	7663.0	7003.0	0.0	258114.0	912407.0	80.0	2.1	13.3	0.6	0.5	0.0	18.9	66.8	32	32	32.00	6	43739840	22.9	22.7	24.3	22.4	7.7	30.9	13.8	smartseq
1610297	SRR2925923	SRP066154	SRS1161644	SRX1427262	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937733: CD8_14 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;3.3167|sister;;CD8_19|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937733		GSM1937733	CD8_14 scRNA-seq	121784576	1902884	2015-12-22 15:48:11	58461335	121784576	1902884	2	1902884	index:0,count:1902884,average:32,stdev:0|index:1,count:1902884,average:32,stdev:0	GSM1937733_r1						2.0	2.25	0.07	90166373	100219979	74367435	86664907	111.15	116.54	1559550	1379308	211.312	1036.173	117	7201	71.63	86.83	2015903	1117070	2015903	1117070	64.11	66.19	2015903	999869	2015903	851610	8077607	8.96	2.06	0	14.35	0	0.55	0	0.31	0	0.00	0	17.19	0	1559550	0	64	0	58.12	0	1.17	0	0.00	0	1.02	0	0.01	0	360.55	0	0.59	0	39258	0	1902884	0	273002	0	10500	0	5806	0	0	0	327028	0	27	0	0	0	220	0	31127	0	1134	0	32508	0	67.61	0	1286548	0	13130	28501	2.170677837014	1902884.0	1559550.0	39258.0	273002.0	10500.0	5806.0	0.0	327028.0	1286548.0	82.0	2.1	14.3	0.6	0.3	0.0	17.2	67.6	32	32	32.00	6	60892288	22.7	22.9	24.4	22.2	7.8	30.9	13.8	smartseq
1610313	SRR2925924	SRP066154	SRS1161643	SRX1427263	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937734: CD8_15 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;3.3|sister;;CD8_13|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937734		GSM1937734	CD8_15 scRNA-seq	114388224	1787316	2015-12-22 15:48:11	54717927	114388224	1787316	2	1787316	index:0,count:1787316,average:32,stdev:0|index:1,count:1787316,average:32,stdev:0	GSM1937734_r1						1.71	1.98	0.04	85183514	98022214	69176142	84250251	115.07	121.79	1476227	1336422	189.238	797.540	117	8203	72.46	89.24	1917554	1069632	1917554	1069632	61.4	64.09	1917554	906379	1917554	768157	6535461	7.67	2.22	0	15.53	0	0.50	0	0.23	0	0.00	0	16.67	0	1476227	0	64	0	58.13	0	1.17	0	0.00	0	1.02	0	0.01	0	402.15	0	0.59	0	39735	0	1787316	0	277596	0	8943	0	4132	0	0	0	298014	0	15	0	0	0	190	0	26800	0	1221	0	28226	0	67.06	0	1198631	0	12254	24290	1.982209890648	1787316.0	1476227.0	39735.0	277596.0	8943.0	4132.0	0.0	298014.0	1198631.0	82.6	2.2	15.5	0.5	0.2	0.0	16.7	67.1	32	32	32.00	6	57194112	22.2	23.3	24.9	21.8	7.8	31.0	13.8	smartseq
1610329	SRR2925925	SRP066154	SRS1161642	SRX1427264	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937735: CD8_16 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;3.5667|sister;;CD8_18|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937735		GSM1937735	CD8_16 scRNA-seq	11958528	186852	2015-12-22 15:48:11	5779690	11958528	186852	2	186852	index:0,count:186852,average:32,stdev:0|index:1,count:186852,average:32,stdev:0	GSM1937735_r1						0.52	3.12	0.01	8765936	9478912	6738355	7688430	108.13	114.1	154097	139266	146.303	772.589	85	1160	74.03	96.29	229110	114078	229110	114078	76.77	79.63	229110	118300	229110	94343	276722	3.16	1.76	0	19.07	0	0.86	0	0.18	0	0.00	0	16.50	0	154097	0	64	0	58.11	0	1.26	0	0.01	0	1.01	0	0.01	0	74.74	0	0.51	0	3295	0	186852	0	35625	0	1598	0	328	0	0	0	30829	0	9	0	0	0	22	0	3945	0	88	0	4064	0	63.40	0	118472	0	2144	3418	1.594216417910	186852.0	154097.0	3295.0	35625.0	1598.0	328.0	0.0	30829.0	118472.0	82.5	1.8	19.1	0.9	0.2	0.0	16.5	63.4	32	32	32.00	6	5979264	22.9	22.6	24.3	22.5	7.7	31.0	13.8	smartseq
1610344	SRR2925926	SRP066154	SRS1161641	SRX1427265	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937736: CD8_17 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;3.0083|sister;;CD8_20|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937736		GSM1937736	CD8_17 scRNA-seq	118396096	1849939	2015-12-22 15:48:11	56597014	118396096	1849939	2	1849939	index:0,count:1849939,average:32,stdev:0|index:1,count:1849939,average:32,stdev:0	GSM1937736_r1						1.85	2.51	0.03	88456488	98909086	69103571	81841669	111.82	118.43	1536918	1361657	181.710	904.387	96	8808	72.89	93.26	2164287	1120184	2164287	1120184	70.09	72.05	2164287	1077248	2164287	865402	4540621	5.13	2.03	0	18.15	0	0.81	0	0.24	0	0.00	0	15.87	0	1536918	0	64	0	58.10	0	1.17	0	0.00	0	1.02	0	0.01	0	416.24	0	0.56	0	37557	0	1849939	0	335778	0	14988	0	4395	0	0	0	293638	0	35	0	0	0	224	0	36225	0	1056	0	37540	0	64.93	0	1201140	0	12922	34558	2.674353815199	1849939.0	1536918.0	37557.0	335778.0	14988.0	4395.0	0.0	293638.0	1201140.0	83.1	2.0	18.2	0.8	0.2	0.0	15.9	64.9	32	32	32.00	6	59198048	22.6	23.0	24.5	22.2	7.8	30.9	13.8	smartseq
1610504	SRR2925930	SRP066154	SRS1161637	SRX1427269	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937740: CD8_21 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_23|cousin 2;;CD8_24|hours since division;;5.15|sister;;CD8_22|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937740		GSM1937740	CD8_21 scRNA-seq	56344960	880390	2015-12-22 15:48:11	27606991	56344960	880390	2	880390	index:0,count:880390,average:32,stdev:0|index:1,count:880390,average:32,stdev:0	GSM1937740_r1						2.66	2.43	0.08	40532066	44709717	33205677	38202068	110.31	115.05	700161	601136	235.417	1309.572	121	2753	71.6	87.35	937085	501332	937085	501332	69.01	69.92	937085	483199	937085	401281	4043994	9.98	2.04	0	14.34	0	0.67	0	0.33	0	0.00	0	19.48	0	700161	0	64	0	58.06	0	1.13	0	0.00	0	1.01	0	0.01	0	226.39	0	0.63	0	17922	0	880390	0	126217	0	5867	0	2889	0	0	0	171473	0	8	0	0	0	105	0	15035	0	477	0	15625	0	65.19	0	573944	0	8275	13154	1.589607250755	880390.0	700161.0	17922.0	126217.0	5867.0	2889.0	0.0	171473.0	573944.0	79.5	2.0	14.3	0.7	0.3	0.0	19.5	65.2	32	32	32.00	6	28172480	22.6	22.9	24.6	22.2	7.8	30.7	13.8	smartseq
1610520	SRR2925931	SRP066154	SRS1161636	SRX1427270	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937741: CD8_22 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_23|cousin 2;;CD8_24|hours since division;;5.175|sister;;CD8_21|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937741		GSM1937741	CD8_22 scRNA-seq	153850496	2403914	2015-12-22 15:48:11	74703376	153850496	2403914	2	2403914	index:0,count:2403914,average:32,stdev:0|index:1,count:2403914,average:32,stdev:0	GSM1937741_r1						1.83	2.24	0.1	111360209	124468307	90740364	106359078	111.77	117.21	1926127	1687886	220.137	1062.684	125	8408	71.64	87.88	2557769	1379805	2557769	1379805	66.07	67.76	2557769	1272608	2557769	1063988	10078292	9.05	2.04	0	14.81	0	0.60	0	0.32	0	0.00	0	18.95	0	1926127	0	64	0	58.06	0	1.15	0	0.00	0	1.02	0	0.01	0	346.16	0	0.63	0	49014	0	2403914	0	356004	0	14413	0	7727	0	0	0	455647	0	24	0	0	0	245	0	38238	0	1557	0	40064	0	65.32	0	1570123	0	16574	35002	2.111861952456	2403914.0	1926127.0	49014.0	356004.0	14413.0	7727.0	0.0	455647.0	1570123.0	80.1	2.0	14.8	0.6	0.3	0.0	19.0	65.3	32	32	32.00	6	76925248	22.4	23.1	24.7	22.0	7.8	30.7	13.8	smartseq
1610536	SRR2925932	SRP066154	SRS1161635	SRX1427271	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937742: CD8_23 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_21|cousin 2;;CD8_22|hours since division;;5.2667|sister;;CD8_24|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937742		GSM1937742	CD8_23 scRNA-seq	165358784	2583731	2015-12-22 15:48:11	79999012	165358784	2583731	2	2583731	index:0,count:2583731,average:32,stdev:0|index:1,count:2583731,average:32,stdev:0	GSM1937742_r1						1.85	1.89	0.06	119024144	136209849	95968584	116538146	114.44	121.43	2058186	1870166	197.557	797.174	117	11153	71.38	88.51	2690595	1469236	2690595	1469236	60.89	63.78	2690595	1253136	2690595	1058622	9648023	8.11	2.27	0	15.42	0	0.42	0	0.22	0	0.00	0	19.70	0	2058186	0	64	0	58.08	0	1.18	0	0.00	0	1.02	0	0.01	0	320.74	0	0.63	0	58622	0	2583731	0	398303	0	10836	0	5735	0	0	0	508974	0	38	0	0	0	261	0	33179	0	1933	0	35411	0	64.24	0	1659883	0	14558	30263	2.078788295095	2583731.0	2058186.0	58622.0	398303.0	10836.0	5735.0	0.0	508974.0	1659883.0	79.7	2.3	15.4	0.4	0.2	0.0	19.7	64.2	32	32	32.00	6	82679392	22.3	23.2	24.9	21.8	7.8	30.8	13.8	smartseq
1610552	SRR2925933	SRP066154	SRS1161634	SRX1427272	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937743: CD8_24 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_21|cousin 2;;CD8_22|hours since division;;5.3|sister;;CD8_23|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937743		GSM1937743	CD8_24 scRNA-seq	89321088	1395642	2015-12-22 15:48:11	43650771	89321088	1395642	2	1395642	index:0,count:1395642,average:32,stdev:0|index:1,count:1395642,average:32,stdev:0	GSM1937743_r1						1.7	2.38	0.04	64941988	74372182	51760248	62506100	114.52	120.76	1123567	979229	221.586	1128.076	125	4996	73.13	91.7	1552505	821679	1552505	821679	67.61	68.71	1552505	759664	1552505	615721	4006121	6.17	2.21	0	16.30	0	0.78	0	0.30	0	0.00	0	18.42	0	1123567	0	64	0	58.05	0	1.11	0	0.00	0	1.02	0	0.01	0	358.88	0	0.64	0	30802	0	1395642	0	227486	0	10911	0	4120	0	0	0	257044	0	20	0	0	0	183	0	23199	0	956	0	24358	0	64.21	0	896081	0	10882	21238	1.951663297188	1395642.0	1123567.0	30802.0	227486.0	10911.0	4120.0	0.0	257044.0	896081.0	80.5	2.2	16.3	0.8	0.3	0.0	18.4	64.2	32	32	32.00	6	44660544	22.1	23.4	25.0	21.7	7.8	30.7	13.8	smartseq
1610617	SRR2925937	SRP066154	SRS1161630	SRX1427276	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937747: CD8_28 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_25|cousin 2;;CD8_27|hours since division;;2.65|sister;;CD8_26|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937747		GSM1937747	CD8_28 scRNA-seq	94360832	1474388	2015-12-22 15:48:11	45876125	94360832	1474388	2	1474388	index:0,count:1474388,average:32,stdev:0|index:1,count:1474388,average:32,stdev:0	GSM1937747_r1						1.51	1.81	0.06	68632735	78359793	56433060	67675051	114.17	119.92	1187179	1063085	219.003	943.070	117	5473	72.19	87.79	1529285	857005	1529285	857005	62.81	65.03	1529285	745671	1529285	634810	6141469	8.95	2.24	0	14.31	0	0.56	0	0.24	0	0.00	0	18.68	0	1187179	0	64	0	58.08	0	1.17	0	0.00	0	1.02	0	0.01	0	353.85	0	0.63	0	33000	0	1474388	0	210933	0	8223	0	3611	0	0	0	275375	0	20	0	0	0	149	0	19984	0	979	0	21132	0	66.21	0	976246	0	9978	17866	1.790539186210	1474388.0	1187179.0	33000.0	210933.0	8223.0	3611.0	0.0	275375.0	976246.0	80.5	2.2	14.3	0.6	0.2	0.0	18.7	66.2	32	32	32.00	6	47180416	22.0	23.5	25.1	21.6	7.8	30.8	13.8	smartseq
1610632	SRR2925938	SRP066154	SRS1161629	SRX1427277	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937748: CD8_29 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_30|cousin 2;;CD8_32|hours since division;;2.25|sister;;CD8_31|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937748		GSM1937748	CD8_29 scRNA-seq	34159808	533747	2015-12-22 15:48:11	17057006	34159808	533747	2	533747	index:0,count:533747,average:32,stdev:0|index:1,count:533747,average:32,stdev:0	GSM1937748_r1						2.39	1.82	0.06	24083157	27540559	19797094	23791100	114.36	120.17	415619	375991	216.508	943.397	125	2037	72.45	88.1	534761	301124	534761	301124	63.19	65.6	534761	262624	534761	224202	2202478	9.15	2.14	0	13.83	0	0.50	0	0.21	0	0.00	0	21.42	0	415619	0	64	0	58.10	0	1.13	0	0.00	0	1.02	0	0.01	0	147.81	0	0.75	0	11425	0	533747	0	73832	0	2676	0	1115	0	0	0	114337	0	4	0	0	0	41	0	6385	0	329	0	6759	0	64.04	0	341787	0	3872	5314	1.372417355372	533747.0	415619.0	11425.0	73832.0	2676.0	1115.0	0.0	114337.0	341787.0	77.9	2.1	13.8	0.5	0.2	0.0	21.4	64.0	32	32	32.00	6	17079904	22.0	23.5	24.9	21.8	7.7	30.4	13.7	smartseq
1610776	SRR2925941	SRP066154	SRS1161626	SRX1427280	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937751: CD8_32 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_29|cousin 2;;CD8_31|hours since division;;2.9333|sister;;CD8_30|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937751		GSM1937751	CD8_32 scRNA-seq	77518208	1211222	2015-12-22 15:48:11	38488274	77518208	1211222	2	1211222	index:0,count:1211222,average:32,stdev:0|index:1,count:1211222,average:32,stdev:0	GSM1937751_r1						1.57	1.72	0.07	55334990	63732933	45843507	55492474	115.18	121.05	957323	876511	200.563	804.234	100	5000	71.69	86.54	1208264	686269	1208264	686269	59.75	62.56	1208264	571986	1208264	496160	5684885	10.27	2.12	0	13.56	0	0.46	0	0.24	0	0.00	0	20.26	0	957323	0	64	0	58.11	0	1.15	0	0.00	0	1.02	0	0.02	0	242.24	0	0.75	0	25718	0	1211222	0	164275	0	5585	0	2928	0	0	0	245386	0	15	0	0	0	95	0	13892	0	920	0	14922	0	65.48	0	793048	0	7898	11920	1.509242846290	1211222.0	957323.0	25718.0	164275.0	5585.0	2928.0	0.0	245386.0	793048.0	79.0	2.1	13.6	0.5	0.2	0.0	20.3	65.5	32	32	32.00	6	38759104	21.8	23.8	25.2	21.5	7.8	30.4	13.7	smartseq
1610793	SRR2925942	SRP066154	SRS1161625	SRX1427281	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937752: CD8_33 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_34|cousin 2;;CD8_35|hours since division;;4.5|sister;;CD8_37|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937752		GSM1937752	CD8_33 scRNA-seq	109169408	1705772	2015-12-22 15:48:11	54017175	109169408	1705772	2	1705772	index:0,count:1705772,average:32,stdev:0|index:1,count:1705772,average:32,stdev:0	GSM1937752_r1						1.87	1.9	0.05	77791551	89163860	62908432	76163851	114.62	121.07	1345934	1225804	197.494	807.195	125	7150	71.88	88.87	1766328	967494	1766328	967494	62.18	64.91	1766328	836960	1766328	706626	6315246	8.12	2.13	0	15.09	0	0.50	0	0.21	0	0.00	0	20.38	0	1345934	0	64	0	58.11	0	1.17	0	0.00	0	1.02	0	0.01	0	383.80	0	0.75	0	36348	0	1705772	0	257325	0	8570	0	3644	0	0	0	347624	0	23	0	0	0	156	0	21331	0	1132	0	22642	0	63.82	0	1088609	0	10115	18992	1.877607513594	1705772.0	1345934.0	36348.0	257325.0	8570.0	3644.0	0.0	347624.0	1088609.0	78.9	2.1	15.1	0.5	0.2	0.0	20.4	63.8	32	32	32.00	6	54584704	21.9	23.6	25.1	21.6	7.8	30.4	13.7	smartseq
1610809	SRR2925943	SRP066154	SRS1161624	SRX1427282	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937753: CD8_34 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_33|cousin 2;;CD8_37|hours since division;;4.3583|sister;;CD8_35|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937753		GSM1937753	CD8_34 scRNA-seq	25310848	395482	2015-12-22 15:48:11	12457376	25310848	395482	2	395482	index:0,count:395482,average:32,stdev:0|index:1,count:395482,average:32,stdev:0	GSM1937753_r1						0.14	3.28	0.03	17472588	19166887	13495881	15595065	109.7	115.55	309335	285678	131.662	771.072	85	2575	74.63	96.65	464083	230866	464083	230866	75.99	78.35	464083	235079	464083	187154	479329	2.74	1.65	0	17.82	0	0.71	0	0.13	0	0.00	0	20.94	0	309335	0	64	0	58.17	0	1.30	0	0.01	0	1.01	0	0.01	0	101.70	0	0.64	0	6517	0	395482	0	70470	0	2824	0	522	0	0	0	82801	0	1	0	0	0	41	0	6211	0	131	0	6384	0	60.40	0	238865	0	2400	5933	2.472083333333	395482.0	309335.0	6517.0	70470.0	2824.0	522.0	0.0	82801.0	238865.0	78.2	1.6	17.8	0.7	0.1	0.0	20.9	60.4	32	32	32.00	6	12655424	23.5	21.9	23.5	23.4	7.7	30.6	13.8	smartseq
1610826	SRR2925944	SRP066154	SRS1161623	SRX1427283	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937754: CD8_35 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_33|cousin 2;;CD8_37|hours since division;;4.3833|sister;;CD8_34|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937754		GSM1937754	CD8_35 scRNA-seq	105852416	1653944	2015-12-22 15:48:11	52647163	105852416	1653944	2	1653944	index:0,count:1653944,average:32,stdev:0|index:1,count:1653944,average:32,stdev:0	GSM1937754_r1						1.77	1.91	0.03	76005623	89690553	59410006	75173911	118.01	126.53	1311889	1213307	191.521	746.133	117	7665	71.42	91.33	1792625	936939	1792625	936939	59.74	61.82	1792625	783779	1792625	634196	4427336	5.83	2.34	0	17.29	0	0.61	0	0.20	0	0.00	0	19.87	0	1311889	0	64	0	58.15	0	1.17	0	0.00	0	1.02	0	0.01	0	396.95	0	0.77	0	38706	0	1653944	0	285967	0	10007	0	3385	0	0	0	328663	0	16	0	0	0	125	0	17847	0	1201	0	19189	0	62.03	0	1025922	0	7918	16235	2.050391513008	1653944.0	1311889.0	38706.0	285967.0	10007.0	3385.0	0.0	328663.0	1025922.0	79.3	2.3	17.3	0.6	0.2	0.0	19.9	62.0	32	32	32.00	6	52926208	21.8	23.7	25.1	21.7	7.7	30.4	13.7	smartseq
1610841	SRR2925945	SRP066154	SRS1161622	SRX1427284	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937755: CD8_36 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.7583|sister;;CD8_42|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937755		GSM1937755	CD8_36 scRNA-seq	85625344	1337896	2015-12-22 15:48:11	42320109	85625344	1337896	2	1337896	index:0,count:1337896,average:32,stdev:0|index:1,count:1337896,average:32,stdev:0	GSM1937755_r1						1.82	1.82	0.08	61873988	71226967	51233868	61924553	115.12	120.87	1071094	980847	195.907	795.252	100	5649	71.04	85.81	1367040	760935	1367040	760935	59.83	62.02	1367040	640859	1367040	549973	6886719	11.13	2.09	0	13.78	0	0.53	0	0.24	0	0.00	0	19.18	0	1071094	0	64	0	58.16	0	1.18	0	0.00	0	1.02	0	0.01	0	301.03	0	0.70	0	27921	0	1337896	0	184319	0	7055	0	3193	0	0	0	256554	0	14	0	0	0	112	0	16008	0	890	0	17024	0	66.28	0	886775	0	7693	14260	1.853633173014	1337896.0	1071094.0	27921.0	184319.0	7055.0	3193.0	0.0	256554.0	886775.0	80.1	2.1	13.8	0.5	0.2	0.0	19.2	66.3	32	32	32.00	6	42812672	21.9	23.6	25.1	21.6	7.8	30.5	13.8	smartseq
1610859	SRR2925946	SRP066154	SRS1161621	SRX1427285	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937756: CD8_37 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_34|cousin 2;;CD8_35|hours since division;;4.6333|sister;;CD8_33|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937756		GSM1937756	CD8_37 scRNA-seq	69785088	1090392	2015-12-22 15:48:11	34647191	69785088	1090392	2	1090392	index:0,count:1090392,average:32,stdev:0|index:1,count:1090392,average:32,stdev:0	GSM1937756_r1						1.52	2.07	0.06	49987561	57773422	40224685	49058667	115.58	121.96	864775	772541	206.391	941.632	110	4338	73.76	91.62	1161351	637866	1161351	637866	65.37	67.17	1161351	565276	1161351	467606	3059433	6.12	2.07	0	15.46	0	0.68	0	0.23	0	0.00	0	19.78	0	864775	0	64	0	58.09	0	1.17	0	0.00	0	1.02	0	0.01	0	261.69	0	0.74	0	22591	0	1090392	0	168602	0	7366	0	2558	0	0	0	215693	0	15	0	0	0	123	0	15757	0	748	0	16643	0	63.85	0	696173	0	7957	13819	1.736709815257	1090392.0	864775.0	22591.0	168602.0	7366.0	2558.0	0.0	215693.0	696173.0	79.3	2.1	15.5	0.7	0.2	0.0	19.8	63.8	32	32	32.00	6	34892544	21.7	23.8	25.3	21.4	7.8	30.4	13.7	smartseq
1610874	SRR2925947	SRP066154	SRS1161620	SRX1427286	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937757: CD8_38 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_39|cousin 2;;CD8_40|hours since division;;6.1917|sister;;CD8_41|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937757		GSM1937757	CD8_38 scRNA-seq	34261568	535337	2015-12-22 15:48:11	17119980	34261568	535337	2	535337	index:0,count:535337,average:32,stdev:0|index:1,count:535337,average:32,stdev:0	GSM1937757_r1						0.81	2.51	0.03	24223471	28054946	18653735	23010432	115.82	123.36	418410	369228	217.435	1076.372	100	2032	74.37	96.46	607046	311163	607046	311163	70.07	71.21	607046	293192	607046	229708	617592	2.55	2.11	0	17.90	0	0.87	0	0.21	0	0.00	0	20.76	0	418410	0	64	0	58.04	0	1.21	0	0.00	0	1.01	0	0.01	0	120.45	0	0.76	0	11297	0	535337	0	95839	0	4675	0	1101	0	0	0	111151	0	6	0	0	0	66	0	8320	0	358	0	8750	0	60.26	0	322571	0	3958	7480	1.889843355230	535337.0	418410.0	11297.0	95839.0	4675.0	1101.0	0.0	111151.0	322571.0	78.2	2.1	17.9	0.9	0.2	0.0	20.8	60.3	32	32	32.00	6	17130784	21.6	23.8	25.2	21.5	7.8	30.3	13.7	smartseq
1610890	SRR2925948	SRP066154	SRS1161619	SRX1427287	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937758: CD8_39 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_38|cousin 2;;CD8_41|hours since division;;6.3667|sister;;CD8_40|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937758		GSM1937758	CD8_39 scRNA-seq	34237952	534968	2015-12-22 15:48:11	17023664	34237952	534968	2	534968	index:0,count:534968,average:32,stdev:0|index:1,count:534968,average:32,stdev:0	GSM1937758_r1						1.29	1.99	0.05	24567270	28745351	20141898	24727097	117.01	122.76	424288	378449	207.529	978.786	117	2258	75.14	91.61	562281	318815	562281	318815	65.13	66.34	562281	276341	562281	230855	1555575	6.33	2.23	0	14.26	0	0.67	0	0.23	0	0.00	0	19.79	0	424288	0	64	0	58.08	0	1.15	0	0.00	0	1.02	0	0.01	0	160.49	0	0.75	0	11927	0	534968	0	76279	0	3564	0	1226	0	0	0	105890	0	4	0	0	0	56	0	7904	0	396	0	8360	0	65.05	0	348009	0	4630	6653	1.436933045356	534968.0	424288.0	11927.0	76279.0	3564.0	1226.0	0.0	105890.0	348009.0	79.3	2.2	14.3	0.7	0.2	0.0	19.8	65.1	32	32	32.00	6	17118976	21.3	24.2	25.7	21.0	7.8	30.5	13.7	smartseq
1610907	SRR2925949	SRP066154	SRS1161618	SRX1427288	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937759: CD8_40 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_38|cousin 2;;CD8_41|hours since division;;6.3833|sister;;CD8_39|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937759		GSM1937759	CD8_40 scRNA-seq	49947904	780436	2015-12-22 15:48:11	24796052	49947904	780436	2	780436	index:0,count:780436,average:32,stdev:0|index:1,count:780436,average:32,stdev:0	GSM1937759_r1						2.44	2.23	0.08	34268736	38627323	27526956	32610470	112.72	118.47	592424	530227	206.569	933.302	100	2948	71.5	88.97	797975	423607	797975	423607	65.99	67.61	797975	390914	797975	321933	2769023	8.08	1.88	0	14.90	0	0.65	0	0.24	0	0.00	0	23.20	0	592424	0	64	0	58.09	0	1.20	0	0.00	0	1.02	0	0.01	0	147.87	0	0.72	0	14685	0	780436	0	116292	0	5061	0	1866	0	0	0	181085	0	11	0	0	0	85	0	10640	0	458	0	11194	0	61.01	0	476132	0	5815	9352	1.608254514187	780436.0	592424.0	14685.0	116292.0	5061.0	1866.0	0.0	181085.0	476132.0	75.9	1.9	14.9	0.6	0.2	0.0	23.2	61.0	32	32	32.00	6	24973952	22.4	23.1	24.6	22.1	7.7	30.4	13.7	smartseq
1611022	SRR2925950	SRP066154	SRS1161617	SRX1427289	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937760: CD8_41 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_39|cousin 2;;CD8_40|hours since division;;6.2667|sister;;CD8_38|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937760		GSM1937760	CD8_41 scRNA-seq	11758464	183726	2015-12-22 15:48:11	6425102	11758464	183726	2	183726	index:0,count:183726,average:32,stdev:0|index:1,count:183726,average:32,stdev:0	GSM1937760_r1						1.49	2.54	0.12	7801284	7590351	6506873	6567957	97.3	100.94	134837	122312	228.040	1174.795	139	607	55.39	66.46	178077	74692	178077	74692	49.53	50.55	178077	66784	178077	56808	1391641	17.84	2.00	0	12.22	0	0.98	0	0.97	0	0.00	0	24.66	0	134837	0	64	0	57.97	0	1.13	0	0.00	0	1.02	0	0.01	0	55.12	0	0.77	0	3672	0	183726	0	22447	0	1794	0	1789	0	0	0	45306	0	1	0	0	0	16	0	1504	0	133	0	1654	0	61.17	0	112390	0	1066	1175	1.102251407129	183726.0	134837.0	3672.0	22447.0	1794.0	1789.0	0.0	45306.0	112390.0	73.4	2.0	12.2	1.0	1.0	0.0	24.7	61.2	32	32	32.00	6	5879232	23.0	22.2	24.2	22.9	7.7	29.2	13.6	smartseq
1611035	SRR2925951	SRP066154	SRS1161616	SRX1427290	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937761: CD8_42 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.95|sister;;CD8_36|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937761		GSM1937761	CD8_42 scRNA-seq	19543808	305372	2015-12-22 15:48:11	10640738	19543808	305372	2	305372	index:0,count:305372,average:32,stdev:0|index:1,count:305372,average:32,stdev:0	GSM1937761_r1						2.12	2.04	0.09	13721477	15485329	11378763	13416588	112.85	117.91	236783	212292	226.643	1014.732	143	1105	70.98	85.53	304254	168063	304254	168063	61.8	63.32	304254	146325	304254	124426	1262569	9.20	2.11	0	13.19	0	0.57	0	0.29	0	0.00	0	21.59	0	236783	0	64	0	57.97	0	1.17	0	0.00	0	1.01	0	0.01	0	84.56	0	0.76	0	6441	0	305372	0	40282	0	1754	0	899	0	0	0	65936	0	3	0	0	0	24	0	3308	0	339	0	3674	0	64.35	0	196501	0	2196	2744	1.249544626594	305372.0	236783.0	6441.0	40282.0	1754.0	899.0	0.0	65936.0	196501.0	77.5	2.1	13.2	0.6	0.3	0.0	21.6	64.3	32	32	32.00	6	9771904	21.7	23.3	25.5	21.8	7.7	28.9	13.5	smartseq
1611052	SRR2925952	SRP066154	SRS1161615	SRX1427291	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937762: CD8_43 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.55|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937762		GSM1937762	CD8_43 scRNA-seq	8260416	129069	2015-12-22 15:48:11	4554386	8260416	129069	2	129069	index:0,count:129069,average:32,stdev:0|index:1,count:129069,average:32,stdev:0	GSM1937762_r1						1.56	2.38	0.05	5661425	6521521	4617966	5566404	115.19	120.54	97905	84983	227.153	1125.269	153	466	74.39	91.09	130064	72832	130064	72832	67.08	68.27	130064	65672	130064	54588	353773	6.25	1.96	0	13.90	0	0.57	0	0.14	0	0.00	0	23.43	0	97905	0	64	0	57.80	0	1.13	0	0.00	0	1.02	0	0.01	0	66.38	0	0.83	0	2527	0	129069	0	17946	0	738	0	180	0	0	0	30246	0	3	0	0	0	4	0	1711	0	162	0	1880	0	61.95	0	79959	0	1190	1396	1.173109243697	129069.0	97905.0	2527.0	17946.0	738.0	180.0	0.0	30246.0	79959.0	75.9	2.0	13.9	0.6	0.1	0.0	23.4	62.0	32	32	32.00	6	4130208	21.0	23.7	26.5	21.0	7.7	28.5	13.4	smartseq
1611069	SRR2925953	SRP066154	SRS1161614	SRX1427292	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937763: CD8_44 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_47|cousin 2;;CD8_48|hours since division;;6.4667|sister;;CD8_45|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937763		GSM1937763	CD8_44 scRNA-seq	62000704	968761	2015-12-22 15:48:11	30494587	62000704	968761	2	968761	index:0,count:968761,average:32,stdev:0|index:1,count:968761,average:32,stdev:0	GSM1937763_r1						1.84	2.0	0.07	44573700	50629701	37427720	44377462	113.59	118.57	769440	687567	228.919	1007.850	125	3349	71.6	85.26	965215	550940	965215	550940	62.25	64.41	965215	478954	965215	416166	5165031	11.59	2.15	0	12.72	0	0.48	0	0.22	0	0.00	0	19.87	0	769440	0	64	0	58.11	0	1.16	0	0.00	0	1.02	0	0.01	0	205.15	0	0.67	0	20826	0	968761	0	123270	0	4620	0	2167	0	0	0	192534	0	15	0	0	0	95	0	12813	0	659	0	13582	0	66.70	0	646170	0	7182	10995	1.530910609858	968761.0	769440.0	20826.0	123270.0	4620.0	2167.0	0.0	192534.0	646170.0	79.4	2.1	12.7	0.5	0.2	0.0	19.9	66.7	32	32	32.00	6	31000352	22.2	23.4	25.0	21.7	7.8	30.7	13.8	smartseq
1611085	SRR2925954	SRP066154	SRS1161613	SRX1427293	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937764: CD8_45 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_47|cousin 2;;CD8_48|hours since division;;6.4944|sister;;CD8_44|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937764		GSM1937764	CD8_45 scRNA-seq	156809984	2450156	2015-12-22 15:48:11	76366841	156809984	2450156	2	2450156	index:0,count:2450156,average:32,stdev:0|index:1,count:2450156,average:32,stdev:0	GSM1937764_r1						0.69	1.62	0.01	110825680	128176905	86378650	107526877	115.66	124.48	1918417	1758153	202.395	745.269	125	10245	73.38	94.13	2543972	1407777	2543972	1407777	61.66	66.71	2543972	1182897	2543972	997650	3213645	2.90	2.43	0	17.26	0	0.37	0	0.13	0	0.00	0	21.20	0	1918417	0	64	0	58.03	0	1.16	0	0.00	0	1.02	0	0.02	0	339.25	0	0.68	0	59551	0	2450156	0	422832	0	9154	0	3131	0	0	0	519454	0	20	0	0	0	171	0	27575	0	2030	0	29796	0	61.04	0	1495585	0	11117	25486	2.292524961770	2450156.0	1918417.0	59551.0	422832.0	9154.0	3131.0	0.0	519454.0	1495585.0	78.3	2.4	17.3	0.4	0.1	0.0	21.2	61.0	32	32	32.00	6	78404992	22.0	23.6	25.2	21.5	7.7	30.7	13.8	smartseq
1611101	SRR2925955	SRP066154	SRS1161612	SRX1427294	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937765: CD8_46 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.3|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937765		GSM1937765	CD8_46 scRNA-seq	121228288	1894192	2015-12-22 15:48:11	59147583	121228288	1894192	2	1894192	index:0,count:1894192,average:32,stdev:0|index:1,count:1894192,average:32,stdev:0	GSM1937765_r1						1.62	2.03	0.06	86826520	95557654	72742096	83578847	110.06	114.9	1502004	1365566	206.226	950.016	117	7578	68.55	81.83	1875867	1029589	1875867	1029589	60.43	63.22	1875867	907615	1875867	795475	12077897	13.91	1.99	0	12.87	0	0.39	0	0.25	0	0.00	0	20.06	0	1502004	0	64	0	58.13	0	1.18	0	0.00	0	1.02	0	0.01	0	340.95	0	0.65	0	37701	0	1894192	0	243809	0	7404	0	4796	0	0	0	379988	0	11	0	0	0	157	0	23153	0	1266	0	24587	0	66.42	0	1258195	0	10977	20814	1.896146488112	1894192.0	1502004.0	37701.0	243809.0	7404.0	4796.0	0.0	379988.0	1258195.0	79.3	2.0	12.9	0.4	0.3	0.0	20.1	66.4	32	32	32.00	6	60614144	22.3	23.3	24.8	21.8	7.8	30.7	13.8	smartseq
1611116	SRR2925956	SRP066154	SRS1161611	SRX1427295	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937766: CD8_47 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_44|cousin 2;;CD8_45|hours since division;;5.5792|sister;;CD8_48|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937766		GSM1937766	CD8_47 scRNA-seq	154500928	2414077	2015-12-22 15:48:11	75549629	154500928	2414077	2	2414077	index:0,count:2414077,average:32,stdev:0|index:1,count:2414077,average:32,stdev:0	GSM1937766_r1						1.46	1.9	0.06	111858970	126658287	92066180	109814444	113.23	119.28	1935607	1760891	200.685	851.599	117	9885	69.96	84.99	2459110	1354054	2459110	1354054	59.59	62.65	2459110	1153386	2459110	998060	12685356	11.34	2.11	0	14.19	0	0.41	0	0.24	0	0.00	0	19.16	0	1935607	0	64	0	58.11	0	1.16	0	0.00	0	1.02	0	0.01	0	321.88	0	0.66	0	50843	0	2414077	0	342493	0	10004	0	5816	0	0	0	462650	0	25	0	0	0	255	0	30899	0	1807	0	32986	0	65.99	0	1593114	0	13954	28037	2.009244661029	2414077.0	1935607.0	50843.0	342493.0	10004.0	5816.0	0.0	462650.0	1593114.0	80.2	2.1	14.2	0.4	0.2	0.0	19.2	66.0	32	32	32.00	6	77250464	22.2	23.3	24.9	21.8	7.8	30.7	13.8	smartseq
1611133	SRR2925957	SRP066154	SRS1161610	SRX1427296	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937767: CD8_48 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_44|cousin 2;;CD8_45|hours since division;;5.6092|sister;;CD8_47|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937767		GSM1937767	CD8_48 scRNA-seq	129887104	2029486	2015-12-22 15:48:11	63446437	129887104	2029486	2	2029486	index:0,count:2029486,average:32,stdev:0|index:1,count:2029486,average:32,stdev:0	GSM1937767_r1						1.75	1.88	0.06	93140923	106114491	76673162	91905488	113.93	119.87	1611114	1464529	207.203	884.771	117	8095	70.49	85.63	2059510	1135706	2059510	1135706	60.27	62.89	2059510	971034	2059510	834090	10128026	10.87	2.14	0	14.04	0	0.47	0	0.23	0	0.00	0	19.92	0	1611114	0	64	0	58.12	0	1.16	0	0.00	0	1.02	0	0.01	0	304.42	0	0.68	0	43389	0	2029486	0	284880	0	9549	0	4583	0	0	0	404240	0	34	0	0	0	142	0	24458	0	1371	0	26005	0	65.35	0	1326234	0	11626	22116	1.902287975228	2029486.0	1611114.0	43389.0	284880.0	9549.0	4583.0	0.0	404240.0	1326234.0	79.4	2.1	14.0	0.5	0.2	0.0	19.9	65.3	32	32	32.00	6	64943552	22.1	23.5	25.0	21.7	7.8	30.7	13.8	smartseq
1611149	SRR2925958	SRP066154	SRS1161609	SRX1427297	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937768: CD8_49 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.5528|sister;;CD8_50|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937768		GSM1937768	CD8_49 scRNA-seq	181091776	2829559	2015-12-22 15:48:11	87799998	181091776	2829559	2	2829559	index:0,count:2829559,average:32,stdev:0|index:1,count:2829559,average:32,stdev:0	GSM1937768_r1						1.53	1.87	0.07	129090223	143896367	106526679	125204161	111.47	117.53	2237677	2084721	181.179	720.938	117	13058	66.58	80.72	2784929	1489781	2784929	1489781	54.97	58.48	2784929	1230082	2784929	1079330	17851068	13.83	2.14	0	13.86	0	0.33	0	0.28	0	0.00	0	20.31	0	2237677	0	64	0	58.17	0	1.18	0	0.00	0	1.02	0	0.02	0	351.26	0	0.64	0	60519	0	2829559	0	392118	0	9306	0	7874	0	0	0	574702	0	38	0	0	0	203	0	28536	0	2011	0	30788	0	65.22	0	1845559	0	12130	26446	2.180214344600	2829559.0	2237677.0	60519.0	392118.0	9306.0	7874.0	0.0	574702.0	1845559.0	79.1	2.1	13.9	0.3	0.3	0.0	20.3	65.2	32	32	32.00	6	90545888	22.5	23.1	24.7	22.0	7.7	30.8	13.8	smartseq
1611165	SRR2925959	SRP066154	SRS1161608	SRX1427298	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937769: CD8_50 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.5667|sister;;CD8_49|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937769		GSM1937769	CD8_50 scRNA-seq	132447808	2069497	2015-12-22 15:48:11	64752459	132447808	2069497	2	2069497	index:0,count:2069497,average:32,stdev:0|index:1,count:2069497,average:32,stdev:0	GSM1937769_r1						1.3	1.82	0.07	94525801	106503460	77850152	92760544	112.67	119.15	1636308	1529286	176.440	682.899	117	9945	66.63	80.93	2035793	1090244	2035793	1090244	53.78	57.45	2035793	879968	2035793	773929	13294986	14.06	2.15	0	13.98	0	0.33	0	0.28	0	0.00	0	20.33	0	1636308	0	64	0	58.18	0	1.17	0	0.00	0	1.02	0	0.02	0	465.64	0	0.66	0	44512	0	2069497	0	289240	0	6740	0	5767	0	0	0	420682	0	17	0	0	0	165	0	20356	0	1582	0	22120	0	65.09	0	1347068	0	9927	18351	1.848594741614	2069497.0	1636308.0	44512.0	289240.0	6740.0	5767.0	0.0	420682.0	1347068.0	79.1	2.2	14.0	0.3	0.3	0.0	20.3	65.1	32	32	32.00	6	66223904	22.5	23.0	24.7	22.0	7.7	30.7	13.8	smartseq
1611278	SRR2925960	SRP066154	SRS1161606	SRX1427299	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937770: CD8_51 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_52|cousin 2;;CD8_53|hours since division;;4.2139|sister;;CD8_54|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937770		GSM1937770	CD8_51 scRNA-seq	88051776	1375809	2015-12-22 15:48:11	43035571	88051776	1375809	2	1375809	index:0,count:1375809,average:32,stdev:0|index:1,count:1375809,average:32,stdev:0	GSM1937770_r1						1.35	1.95	0.06	63079478	70546109	52205519	61153460	111.84	117.14	1091473	987350	215.828	900.907	117	5125	70.31	84.96	1387657	767430	1387657	767430	61.62	64.42	1387657	672551	1387657	581912	6948824	11.02	2.08	0	13.68	0	0.48	0	0.29	0	0.00	0	19.90	0	1091473	0	64	0	58.08	0	1.16	0	0.00	0	1.02	0	0.02	0	275.16	0	0.65	0	28602	0	1375809	0	188233	0	6639	0	3948	0	0	0	273749	0	17	0	0	0	131	0	17066	0	918	0	18132	0	65.65	0	903240	0	9005	14910	1.655746807329	1375809.0	1091473.0	28602.0	188233.0	6639.0	3948.0	0.0	273749.0	903240.0	79.3	2.1	13.7	0.5	0.3	0.0	19.9	65.7	32	32	32.00	6	44025888	21.9	23.6	25.2	21.5	7.8	30.8	13.8	smartseq
1611294	SRR2925961	SRP066154	SRS1161605	SRX1427300	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937771: CD8_52 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_51|cousin 2;;CD8_54|hours since division;;3.6958|sister;;CD8_53|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937771		GSM1937771	CD8_52 scRNA-seq	80521280	1258145	2015-12-22 15:48:11	39486413	80521280	1258145	2	1258145	index:0,count:1258145,average:32,stdev:0|index:1,count:1258145,average:32,stdev:0	GSM1937771_r1						1.36	2.05	0.09	57181419	64438495	47321259	55888142	112.69	118.1	988890	891683	217.635	910.358	117	4613	70.96	85.74	1257891	701742	1257891	701742	61.96	64.66	1257891	612759	1257891	529178	6034585	10.55	2.10	0	13.55	0	0.51	0	0.23	0	0.00	0	20.66	0	988890	0	64	0	58.07	0	1.17	0	0.00	0	1.02	0	0.01	0	283.08	0	0.68	0	26364	0	1258145	0	170469	0	6399	0	2886	0	0	0	259970	0	15	0	0	0	113	0	15547	0	832	0	16507	0	65.05	0	818421	0	8269	13538	1.637199177651	1258145.0	988890.0	26364.0	170469.0	6399.0	2886.0	0.0	259970.0	818421.0	78.6	2.1	13.5	0.5	0.2	0.0	20.7	65.0	32	32	32.00	6	40260640	22.0	23.5	25.1	21.5	7.8	30.7	13.8	smartseq
1611308	SRR2925962	SRP066154	SRS1161607	SRX1427301	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937772: CD8_53 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_51|cousin 2;;CD8_54|hours since division;;3.7306|sister;;CD8_52|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937772		GSM1937772	CD8_53 scRNA-seq	132350720	2067980	2015-12-22 15:48:11	64694152	132350720	2067980	2	2067980	index:0,count:2067980,average:32,stdev:0|index:1,count:2067980,average:32,stdev:0	GSM1937772_r1						1.27	2.02	0.06	95733467	107543561	78220583	92663307	112.34	118.46	1657139	1501390	196.339	833.505	117	8974	70.1	85.8	2118768	1161691	2118768	1161691	60.69	63.99	2118768	1005668	2118768	866401	10050637	10.50	2.08	0	14.66	0	0.43	0	0.23	0	0.00	0	19.21	0	1657139	0	64	0	58.09	0	1.16	0	0.00	0	1.02	0	0.02	0	465.30	0	0.67	0	42948	0	2067980	0	303112	0	8812	0	4681	0	0	0	397348	0	25	0	0	0	214	0	27418	0	1498	0	29155	0	65.48	0	1354027	0	13205	24624	1.864748201439	2067980.0	1657139.0	42948.0	303112.0	8812.0	4681.0	0.0	397348.0	1354027.0	80.1	2.1	14.7	0.4	0.2	0.0	19.2	65.5	32	32	32.00	6	66175360	22.3	23.3	24.9	21.7	7.8	30.7	13.8	smartseq
1611326	SRR2925963	SRP066154	SRS1161604	SRX1427302	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937773: CD8_54 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_52|cousin 2;;CD8_53|hours since division;;4.3117|sister;;CD8_51|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937773		GSM1937773	CD8_54 scRNA-seq	131088640	2048260	2015-12-22 15:48:11	63778891	131088640	2048260	2	2048260	index:0,count:2048260,average:32,stdev:0|index:1,count:2048260,average:32,stdev:0	GSM1937773_r1						1.86	1.86	0.01	92480483	105226157	73286519	89276642	113.78	121.82	1598777	1485199	195.565	707.379	125	8738	69.44	87.63	2095706	1110161	2095706	1110161	55.88	59.5	2095706	893441	2095706	753813	5357366	5.79	2.38	0	16.20	0	0.50	0	0.41	0	0.00	0	21.04	0	1598777	0	64	0	58.11	0	1.17	0	0.00	0	1.02	0	0.01	0	433.75	0	0.67	0	48651	0	2048260	0	331870	0	10252	0	8376	0	0	0	430855	0	18	0	0	0	129	0	20111	0	1643	0	21901	0	61.85	0	1266907	0	9214	18576	2.016062513566	2048260.0	1598777.0	48651.0	331870.0	10252.0	8376.0	0.0	430855.0	1266907.0	78.1	2.4	16.2	0.5	0.4	0.0	21.0	61.9	32	32	32.00	6	65544320	22.5	23.1	24.7	22.0	7.7	30.8	13.8	smartseq
1611341	SRR2925964	SRP066154	SRS1161603	SRX1427303	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937774: CD8_55 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_57|cousin 2;;CD8_58|hours since division;;3.5356|sister;;CD8_56|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937774		GSM1937774	CD8_55 scRNA-seq	2802880	43795	2015-12-22 15:48:11	1590770	2802880	43795	2	43795	index:0,count:43795,average:32,stdev:0|index:1,count:43795,average:32,stdev:0	GSM1937774_r1						1.64	2.61	0.22	1341059	1459421	1113287	1258191	108.83	113.02	23240	20143	235.638	1370.122	105	108	70.26	84.61	30229	16329	30229	16329	67.13	68.11	30229	15602	30229	13145	149837	11.17	1.28	0	9.00	0	0.34	0	0.11	0	0.00	0	46.49	0	23240	0	64	0	57.93	0	1.17	0	0.00	0	1.01	0	0.01	0	31.53	0	1.58	0	559	0	43795	0	3940	0	149	0	47	0	0	0	20359	0	0	0	0	0	4	0	342	0	11	0	357	0	44.07	0	19300	0	253	262	1.035573122530	43795.0	23240.0	559.0	3940.0	149.0	47.0	0.0	20359.0	19300.0	53.1	1.3	9.0	0.3	0.1	0.0	46.5	44.1	32	32	32.00	6	1401440	24.0	22.5	24.8	21.1	7.7	28.4	13.5	smartseq
1611356	SRR2925965	SRP066154	SRS1161602	SRX1427304	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937775: CD8_56 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_57|cousin 2;;CD8_58|hours since division;;3.5592|sister;;CD8_55|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937775		GSM1937775	CD8_56 scRNA-seq	52096512	814008	2015-12-22 15:48:11	25640945	52096512	814008	2	814008	index:0,count:814008,average:32,stdev:0|index:1,count:814008,average:32,stdev:0	GSM1937775_r1						2.17	2.24	0.13	37053402	40701189	31074060	35581304	109.84	114.5	640117	577779	235.292	1012.912	117	2622	67.86	80.92	810720	434392	810720	434392	59.42	61.06	810720	380329	810720	327755	4640933	12.52	2.04	0	12.69	0	0.63	0	0.42	0	0.00	0	20.31	0	640117	0	64	0	58.11	0	1.16	0	0.00	0	1.02	0	0.01	0	209.32	0	0.69	0	16593	0	814008	0	103307	0	5122	0	3421	0	0	0	165348	0	6	0	0	0	59	0	8982	0	557	0	9604	0	65.95	0	536810	0	5324	7578	1.423365890308	814008.0	640117.0	16593.0	103307.0	5122.0	3421.0	0.0	165348.0	536810.0	78.6	2.0	12.7	0.6	0.4	0.0	20.3	65.9	32	32	32.00	6	26048256	22.6	23.2	24.5	21.9	7.7	30.5	13.8	smartseq
1611372	SRR2925966	SRP066154	SRS1161601	SRX1427305	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937776: CD8_57 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_55|cousin 2;;CD8_56|hours since division;;4.1611|sister;;CD8_58|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937776		GSM1937776	CD8_57 scRNA-seq	95843712	1497558	2015-12-22 15:48:11	46865834	95843712	1497558	2	1497558	index:0,count:1497558,average:32,stdev:0|index:1,count:1497558,average:32,stdev:0	GSM1937776_r1						2.2	2.19	0.09	69577090	79402134	57651686	69011075	114.12	119.7	1202282	1063937	228.011	1084.670	117	4985	73.01	88.09	1547553	877794	1547553	877794	64.2	66.03	1547553	771868	1547553	658009	6180059	8.88	2.03	0	13.74	0	0.61	0	0.25	0	0.00	0	18.85	0	1202282	0	64	0	58.10	0	1.18	0	0.00	0	1.02	0	0.01	0	317.13	0	0.69	0	30456	0	1497558	0	205818	0	9142	0	3796	0	0	0	282338	0	11	0	0	0	137	0	20705	0	996	0	21849	0	66.54	0	996464	0	10015	18601	1.857314028957	1497558.0	1202282.0	30456.0	205818.0	9142.0	3796.0	0.0	282338.0	996464.0	80.3	2.0	13.7	0.6	0.3	0.0	18.9	66.5	32	32	32.00	6	47921856	22.5	23.3	24.6	21.8	7.8	30.5	13.8	smartseq
1611388	SRR2925967	SRP066154	SRS1161600	SRX1427306	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937777: CD8_58 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_55|cousin 2;;CD8_56|hours since division;;4.2208|sister;;CD8_57|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937777		GSM1937777	CD8_58 scRNA-seq	43742144	683471	2015-12-22 15:48:11	21493620	43742144	683471	2	683471	index:0,count:683471,average:32,stdev:0|index:1,count:683471,average:32,stdev:0	GSM1937777_r1						1.68	2.17	0.09	31159964	35728513	26161761	31332836	114.66	119.77	538425	480555	241.041	1130.331	125	2176	72.2	85.98	679383	388721	679383	388721	62.38	64.11	679383	335869	679383	289828	3307701	10.62	2.15	0	12.63	0	0.51	0	0.20	0	0.00	0	20.50	0	538425	0	64	0	58.08	0	1.19	0	0.00	0	1.02	0	0.01	0	153.78	0	0.71	0	14676	0	683471	0	86323	0	3515	0	1399	0	0	0	140132	0	3	0	0	0	58	0	8269	0	464	0	8794	0	66.15	0	452102	0	4831	6983	1.445456427241	683471.0	538425.0	14676.0	86323.0	3515.0	1399.0	0.0	140132.0	452102.0	78.8	2.1	12.6	0.5	0.2	0.0	20.5	66.1	32	32	32.00	6	21871072	22.3	23.5	24.8	21.6	7.8	30.6	13.8	smartseq
1611404	SRR2925968	SRP066154	SRS1161599	SRX1427307	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937778: CD8_59 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_60|cousin 2;;CD8_62|hours since division;;6.2486|sister;;CD8_61|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937778		GSM1937778	CD8_59 scRNA-seq	77030592	1203603	2015-12-22 15:48:11	37882109	77030592	1203603	2	1203603	index:0,count:1203603,average:32,stdev:0|index:1,count:1203603,average:32,stdev:0	GSM1937778_r1						2.09	1.69	0.06	55485670	63302294	46612805	55714513	114.09	119.53	958867	866178	226.316	980.007	125	4098	71.21	84.77	1192087	682793	1192087	682793	59.87	62.45	1192087	574027	1192087	503006	6347006	11.44	2.10	0	12.74	0	0.42	0	0.25	0	0.00	0	19.66	0	958867	0	64	0	58.10	0	1.16	0	0.00	0	1.02	0	0.01	0	309.50	0	0.71	0	25296	0	1203603	0	153377	0	5104	0	2961	0	0	0	236671	0	11	0	0	0	95	0	13747	0	902	0	14755	0	66.92	0	805490	0	7637	11890	1.556894068351	1203603.0	958867.0	25296.0	153377.0	5104.0	2961.0	0.0	236671.0	805490.0	79.7	2.1	12.7	0.4	0.2	0.0	19.7	66.9	32	32	32.00	6	38515296	22.2	23.7	24.9	21.5	7.8	30.6	13.8	smartseq
1611420	SRR2925969	SRP066154	SRS1161598	SRX1427308	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937779: CD8_60 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_59|cousin 2;;CD8_61|hours since division;;6.3214|sister;;CD8_62|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937779		GSM1937779	CD8_60 scRNA-seq	66650240	1041410	2015-12-22 15:48:11	32733563	66650240	1041410	2	1041410	index:0,count:1041410,average:32,stdev:0|index:1,count:1041410,average:32,stdev:0	GSM1937779_r1						2.21	2.18	0.05	47870772	54060652	39622199	46743491	112.93	117.97	827476	725482	231.963	1209.083	125	3386	72.14	87.13	1084544	596918	1084544	596918	65.25	66.34	1084544	539901	1084544	454475	4546399	9.50	1.99	0	13.67	0	0.60	0	0.25	0	0.00	0	19.69	0	827476	0	64	0	58.08	0	1.18	0	0.00	0	1.02	0	0.01	0	249.94	0	0.69	0	20725	0	1041410	0	142380	0	6299	0	2599	0	0	0	205036	0	15	0	0	0	114	0	14877	0	681	0	15687	0	65.79	0	685096	0	7621	13149	1.725364125443	1041410.0	827476.0	20725.0	142380.0	6299.0	2599.0	0.0	205036.0	685096.0	79.5	2.0	13.7	0.6	0.2	0.0	19.7	65.8	32	32	32.00	6	33325120	22.4	23.4	24.6	21.8	7.8	30.6	13.8	smartseq
1611531	SRR2925970	SRP066154	SRS1161597	SRX1427309	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937780: CD8_61 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_60|cousin 2;;CD8_62|hours since division;;6.2925|sister;;CD8_59|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937780		GSM1937780	CD8_61 scRNA-seq	99657536	1557149	2015-12-22 15:48:11	48761238	99657536	1557149	2	1557149	index:0,count:1557149,average:32,stdev:0|index:1,count:1557149,average:32,stdev:0	GSM1937780_r1						2.56	1.62	0.05	71898425	84968139	60882385	75663801	118.18	124.28	1242063	1132761	229.055	1024.735	125	5398	72.68	85.86	1514767	902719	1514767	902719	56.0	58.8	1514767	695582	1514767	618234	7361953	10.24	2.28	0	12.24	0	0.43	0	0.29	0	0.00	0	19.52	0	1242063	0	64	0	58.14	0	1.17	0	0.00	0	1.02	0	0.01	0	311.43	0	0.70	0	35485	0	1557149	0	190636	0	6633	0	4545	0	0	0	303908	0	18	0	0	0	127	0	16422	0	1120	0	17687	0	67.52	0	1051427	0	8411	14273	1.696944477470	1557149.0	1242063.0	35485.0	190636.0	6633.0	4545.0	0.0	303908.0	1051427.0	79.8	2.3	12.2	0.4	0.3	0.0	19.5	67.5	32	32	32.00	6	49828768	22.1	23.7	25.0	21.4	7.7	30.6	13.8	smartseq
1611546	SRR2925971	SRP066154	SRS1161595	SRX1427310	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937781: CD8_62 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_59|cousin 2;;CD8_60|hours since division;;6.3736|sister;;CD8_60|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937781		GSM1937781	CD8_62 scRNA-seq	57496320	898380	2015-12-22 15:48:11	28403869	57496320	898380	2	898380	index:0,count:898380,average:32,stdev:0|index:1,count:898380,average:32,stdev:0	GSM1937781_r1						2.59	2.11	0.05	41350698	47049821	34647092	41210848	113.78	118.94	714374	637454	233.024	1106.509	125	2953	72.23	86.19	906036	515973	906036	515973	62.65	64.52	906036	447556	906036	386282	4220526	10.21	2.06	0	12.88	0	0.54	0	0.23	0	0.00	0	19.71	0	714374	0	64	0	58.09	0	1.17	0	0.00	0	1.02	0	0.01	0	231.01	0	0.72	0	18530	0	898380	0	115711	0	4858	0	2074	0	0	0	177074	0	11	0	0	0	87	0	10991	0	621	0	11710	0	66.64	0	598663	0	6231	9399	1.508425613866	898380.0	714374.0	18530.0	115711.0	4858.0	2074.0	0.0	177074.0	598663.0	79.5	2.1	12.9	0.5	0.2	0.0	19.7	66.6	32	32	32.00	6	28748160	22.3	23.5	24.8	21.7	7.7	30.5	13.8	smartseq
1611564	SRR2925972	SRP066154	SRS1161596	SRX1427311	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937782: CD8_63 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.2|sister;;CD8_64|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937782		GSM1937782	CD8_63 scRNA-seq	82230848	1284857	2015-12-22 15:48:11	40348490	82230848	1284857	2	1284857	index:0,count:1284857,average:32,stdev:0|index:1,count:1284857,average:32,stdev:0	GSM1937782_r1						1.9	2.04	0.05	59667777	69481631	48614034	59794268	116.45	123.0	1030204	923154	227.198	958.707	125	4538	73.03	89.59	1347788	752355	1347788	752355	62.37	64.01	1347788	642515	1347788	537534	4271255	7.16	2.20	0	14.82	0	0.53	0	0.20	0	0.00	0	19.09	0	1030204	0	64	0	58.09	0	1.21	0	0.00	0	1.02	0	0.01	0	272.09	0	0.70	0	28309	0	1284857	0	190455	0	6808	0	2549	0	0	0	245296	0	14	0	0	0	123	0	16595	0	966	0	17698	0	65.36	0	839749	0	8128	14689	1.807209645669	1284857.0	1030204.0	28309.0	190455.0	6808.0	2549.0	0.0	245296.0	839749.0	80.2	2.2	14.8	0.5	0.2	0.0	19.1	65.4	32	32	32.00	6	41115424	22.0	23.8	25.0	21.4	7.8	30.6	13.8	smartseq
1611579	SRR2925973	SRP066154	SRS1161594	SRX1427312	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937783: CD8_64 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.2056|sister;;CD8_63|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937783		GSM1937783	CD8_64 scRNA-seq	39130560	611415	2015-12-22 15:48:11	19334649	39130560	611415	2	611415	index:0,count:611415,average:32,stdev:0|index:1,count:611415,average:32,stdev:0	GSM1937783_r1						2.08	1.85	0.03	27699923	32176775	22996426	28073083	116.16	122.08	478480	432191	236.319	986.536	125	2037	72.09	86.83	609273	344956	609273	344956	60.47	62.38	609273	289325	609273	247836	2708413	9.78	2.28	0	13.28	0	0.44	0	0.18	0	0.00	0	21.12	0	478480	0	64	0	58.07	0	1.16	0	0.00	0	1.02	0	0.01	0	146.74	0	0.73	0	13939	0	611415	0	81180	0	2715	0	1107	0	0	0	129113	0	8	0	0	0	54	0	6824	0	432	0	7318	0	64.98	0	397300	0	4128	5736	1.389534883721	611415.0	478480.0	13939.0	81180.0	2715.0	1107.0	0.0	129113.0	397300.0	78.3	2.3	13.3	0.4	0.2	0.0	21.1	65.0	32	32	32.00	6	19565280	22.0	23.9	25.1	21.3	7.8	30.5	13.7	smartseq
1611596	SRR2925974	SRP066154	SRS1161593	SRX1427313	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937784: CD8_65 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_67|cousin 2;;CD8_59|hours since division;;3.9333|sister;;CD8_66|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937784		GSM1937784	CD8_65 scRNA-seq	91871424	1435491	2015-12-22 15:48:11	44709737	91871424	1435491	2	1435491	index:0,count:1435491,average:32,stdev:0|index:1,count:1435491,average:32,stdev:0	GSM1937784_r1						1.89	2.56	0.07	66696057	77132915	51985366	64254601	115.65	123.6	1152994	1043544	194.192	874.401	105	6358	71.48	91.65	1612069	824141	1612069	824141	64.02	65.24	1612069	738195	1612069	586663	3989319	5.98	2.09	0	17.68	0	0.73	0	0.23	0	0.00	0	18.72	0	1152994	0	64	0	58.08	0	1.25	0	0.00	0	1.01	0	0.01	0	287.10	0	0.67	0	30020	0	1435491	0	253807	0	10481	0	3343	0	0	0	268673	0	10	0	0	0	152	0	19549	0	1014	0	20725	0	62.64	0	899187	0	6908	18912	2.737695425594	1435491.0	1152994.0	30020.0	253807.0	10481.0	3343.0	0.0	268673.0	899187.0	80.3	2.1	17.7	0.7	0.2	0.0	18.7	62.6	32	32	32.00	6	45935712	22.3	23.4	24.8	21.7	7.8	30.6	13.8	smartseq
1611614	SRR2925975	SRP066154	SRS1161592	SRX1427314	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937785: CD8_66 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_67|cousin 2;;CD8_68|hours since division;;3.975|sister;;CD8_65|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937785		GSM1937785	CD8_66 scRNA-seq	75265344	1176021	2015-12-22 15:48:11	36651056	75265344	1176021	2	1176021	index:0,count:1176021,average:32,stdev:0|index:1,count:1176021,average:32,stdev:0	GSM1937785_r1						4.99	3.32	0.08	54905359	57087983	42020270	45474034	103.98	108.22	950869	796161	209.683	1400.835	105	4168	72.33	94.36	1403303	687724	1403303	687724	83.17	84.1	1403303	790847	1403303	612966	2883319	5.25	1.44	0	18.88	0	0.81	0	0.19	0	0.00	0	18.14	0	950869	0	64	0	58.03	0	1.28	0	0.00	0	1.01	0	0.01	0	235.20	0	0.59	0	16956	0	1176021	0	222040	0	9570	0	2196	0	0	0	213386	0	31	0	0	0	158	0	25600	0	460	0	26249	0	61.97	0	728829	0	6641	25666	3.864779400693	1176021.0	950869.0	16956.0	222040.0	9570.0	2196.0	0.0	213386.0	728829.0	80.9	1.4	18.9	0.8	0.2	0.0	18.1	62.0	32	32	32.00	6	37632672	23.8	21.9	23.3	23.2	7.7	30.6	13.8	smartseq
1611630	SRR2925976	SRP066154	SRS1161591	SRX1427315	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937786: CD8_67 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_65|cousin 2;;CD8_66|hours since division;;4.4333|sister;;CD8_68|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937786		GSM1937786	CD8_67 scRNA-seq	50867584	794806	2015-12-22 15:48:11	25244076	50867584	794806	2	794806	index:0,count:794806,average:32,stdev:0|index:1,count:794806,average:32,stdev:0	GSM1937786_r1						2.71	2.29	0.04	37649181	43322998	30206015	36906455	115.07	122.18	649167	592273	202.002	812.187	100	3482	72.17	89.9	866658	468504	866658	468504	63.04	65.03	866658	409245	866658	338868	2688756	7.14	2.15	0	16.11	0	0.77	0	0.24	0	0.00	0	17.32	0	649167	0	64	0	58.15	0	1.23	0	0.00	0	1.02	0	0.01	0	178.83	0	0.66	0	17117	0	794806	0	128038	0	6113	0	1896	0	0	0	137630	0	8	0	0	0	85	0	9767	0	596	0	10456	0	65.57	0	521129	0	4945	8774	1.774317492417	794806.0	649167.0	17117.0	128038.0	6113.0	1896.0	0.0	137630.0	521129.0	81.7	2.2	16.1	0.8	0.2	0.0	17.3	65.6	32	32	32.00	6	25433792	22.4	23.0	24.6	22.2	7.7	30.4	13.7	smartseq
1611644	SRR2925977	SRP066154	SRS1161590	SRX1427316	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937787: CD8_68 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_65|cousin 2;;CD8_66|hours since division;;4.5167|sister;;CD8_67|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937787		GSM1937787	CD8_68 scRNA-seq	41983872	655998	2015-12-22 15:48:11	22239444	41983872	655998	2	655998	index:0,count:655998,average:32,stdev:0|index:1,count:655998,average:32,stdev:0	GSM1937787_r1						3.01	2.01	0.05	30668755	34845592	25240545	30127616	113.62	119.36	528639	485118	200.289	820.500	125	2812	70.62	85.76	676441	373310	676441	373310	60.95	63.26	676441	322192	676441	275383	3218311	10.49	2.12	0	14.23	0	0.61	0	0.23	0	0.00	0	18.58	0	528639	0	64	0	58.13	0	1.14	0	0.00	0	1.01	0	0.01	0	157.44	0	0.68	0	13880	0	655998	0	93332	0	3995	0	1504	0	0	0	121860	0	5	0	0	0	52	0	7336	0	609	0	8002	0	66.36	0	435307	0	4303	6227	1.447129909366	655998.0	528639.0	13880.0	93332.0	3995.0	1504.0	0.0	121860.0	435307.0	80.6	2.1	14.2	0.6	0.2	0.0	18.6	66.4	32	32	32.00	6	20991936	22.1	22.8	24.9	22.4	7.7	29.8	13.6	smartseq
1611661	SRR2925978	SRP066154	SRS1161589	SRX1427317	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937788: CD8_69 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;1.9833|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937788		GSM1937788	CD8_69 scRNA-seq	89243648	1394432	2015-12-22 15:48:11	43916378	89243648	1394432	2	1394432	index:0,count:1394432,average:32,stdev:0|index:1,count:1394432,average:32,stdev:0	GSM1937788_r1						1.91	1.86	0.05	65030248	74301115	52971697	63966472	114.26	120.76	1124614	1027061	199.895	820.823	125	5962	71.92	88.28	1441544	808797	1441544	808797	61.53	64.89	1441544	691999	1441544	594436	5704119	8.77	2.20	0	14.95	0	0.38	0	0.19	0	0.00	0	18.78	0	1124614	0	64	0	58.11	0	1.14	0	0.00	0	1.02	0	0.02	0	313.75	0	0.67	0	30617	0	1394432	0	208479	0	5339	0	2630	0	0	0	261849	0	9	0	0	0	117	0	17101	0	1095	0	18322	0	65.70	0	916135	0	8982	14974	1.667112001781	1394432.0	1124614.0	30617.0	208479.0	5339.0	2630.0	0.0	261849.0	916135.0	80.7	2.2	15.0	0.4	0.2	0.0	18.8	65.7	32	32	32.00	6	44621824	22.2	23.3	24.9	21.9	7.7	30.5	13.8	smartseq
1611676	SRR2925979	SRP066154	SRS1161588	SRX1427318	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937789: CD8_70 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;2|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937789		GSM1937789	CD8_70 scRNA-seq	65633024	1025516	2015-12-22 15:48:11	32181195	65633024	1025516	2	1025516	index:0,count:1025516,average:32,stdev:0|index:1,count:1025516,average:32,stdev:0	GSM1937789_r1						2.33	2.03	0.03	48118619	55132135	39889874	47946500	114.58	120.2	831103	753345	213.465	950.473	100	4085	71.07	85.72	1060037	590647	1060037	590647	61.13	63.13	1060037	508017	1060037	435011	5403968	11.23	2.12	0	13.85	0	0.61	0	0.25	0	0.00	0	18.11	0	831103	0	64	0	58.14	0	1.13	0	0.00	0	1.02	0	0.01	0	283.99	0	0.66	0	21692	0	1025516	0	142053	0	6212	0	2513	0	0	0	185688	0	13	0	0	0	86	0	12896	0	686	0	13681	0	67.19	0	689050	0	7360	11164	1.516847826087	1025516.0	831103.0	21692.0	142053.0	6212.0	2513.0	0.0	185688.0	689050.0	81.0	2.1	13.9	0.6	0.2	0.0	18.1	67.2	32	32	32.00	6	32816512	22.2	23.3	24.8	21.9	7.8	30.6	13.8	smartseq
1611789	SRR2925980	SRP066154	SRS1161587	SRX1427319	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937790: CD8_71 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_73|cousin 2;;CD8_74|hours since division;;0.9167|sister;;CD8_72|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937790		GSM1937790	CD8_71 scRNA-seq	79994304	1249911	2015-12-22 15:48:11	39702632	79994304	1249911	2	1249911	index:0,count:1249911,average:32,stdev:0|index:1,count:1249911,average:32,stdev:0	GSM1937790_r1						2.27	1.99	0.12	58335818	66199696	47559990	56975203	113.48	119.8	1007780	927743	196.533	810.363	125	5211	69.26	84.95	1304732	697970	1304732	697970	57.97	60.0	1304732	584200	1304732	493008	5522514	9.47	2.20	0	14.89	0	0.47	0	0.38	0	0.00	0	18.52	0	1007780	0	64	0	58.17	0	1.14	0	0.00	0	1.02	0	0.01	0	264.69	0	0.67	0	27485	0	1249911	0	186144	0	5930	0	4718	0	0	0	231483	0	8	0	0	0	116	0	13617	0	962	0	14703	0	65.74	0	821636	0	7345	12067	1.642886317223	1249911.0	1007780.0	27485.0	186144.0	5930.0	4718.0	0.0	231483.0	821636.0	80.6	2.2	14.9	0.5	0.4	0.0	18.5	65.7	32	32	32.00	6	39997152	22.5	22.9	24.5	22.3	7.7	30.4	13.7	smartseq
1611805	SRR2925981	SRP066154	SRS1161586	SRX1427320	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937791: CD8_72 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_73|cousin 2;;CD8_74|hours since division;;0.95|sister;;CD8_71|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937791		GSM1937791	CD8_72 scRNA-seq	75558528	1180602	2015-12-22 15:48:11	38361215	75558528	1180602	2	1180602	index:0,count:1180602,average:32,stdev:0|index:1,count:1180602,average:32,stdev:0	GSM1937791_r1						2.6	2.21	0.07	55919718	63644476	45501386	54526103	113.81	119.83	965267	875080	206.979	889.164	125	4710	72.41	88.96	1264498	698962	1264498	698962	64.24	66.35	1264498	620101	1264498	521358	4479994	8.01	2.12	0	15.21	0	0.52	0	0.22	0	0.00	0	17.49	0	965267	0	64	0	58.14	0	1.18	0	0.00	0	1.02	0	0.01	0	236.12	0	0.65	0	25060	0	1180602	0	179530	0	6195	0	2605	0	0	0	206535	0	13	0	0	0	114	0	15228	0	917	0	16272	0	66.55	0	785737	0	7785	13652	1.753628773282	1180602.0	965267.0	25060.0	179530.0	6195.0	2605.0	0.0	206535.0	785737.0	81.8	2.1	15.2	0.5	0.2	0.0	17.5	66.6	32	32	32.00	6	37779264	22.1	23.1	24.8	22.3	7.7	30.2	13.7	smartseq
1611819	SRR2925982	SRP066154	SRS1161585	SRX1427321	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937792: CD8_73 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_71|cousin 2;;CD8_72|hours since division;;1.9167|sister;;CD8_74|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937792		GSM1937792	CD8_73 scRNA-seq	90849536	1419524	2015-12-22 15:48:11	44594197	90849536	1419524	2	1419524	index:0,count:1419524,average:32,stdev:0|index:1,count:1419524,average:32,stdev:0	GSM1937792_r1						2.23	1.89	0.11	66603825	76191226	54870709	66226171	114.39	120.69	1149057	1059450	196.738	751.608	117	6240	69.68	84.57	1444692	800619	1444692	800619	58.11	61.21	1444692	667711	1444692	579501	7935917	11.92	2.20	0	14.25	0	0.33	0	0.22	0	0.00	0	18.50	0	1149057	0	64	0	58.17	0	1.17	0	0.00	0	1.02	0	0.02	0	300.61	0	0.67	0	31181	0	1419524	0	202349	0	4732	0	3139	0	0	0	262596	0	21	0	0	0	95	0	15404	0	1100	0	16620	0	66.69	0	946708	0	8163	13590	1.664829106946	1419524.0	1149057.0	31181.0	202349.0	4732.0	3139.0	0.0	262596.0	946708.0	80.9	2.2	14.3	0.3	0.2	0.0	18.5	66.7	32	32	32.00	6	45424768	22.5	23.0	24.6	22.2	7.7	30.5	13.8	smartseq
1611835	SRR2925983	SRP066154	SRS1161584	SRX1427322	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937793: CD8_74 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_71|cousin 2;;CD8_72|hours since division;;1.9417|sister;;CD8_73|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937793		GSM1937793	CD8_74 scRNA-seq	38568320	602630	2015-12-22 15:48:11	19108364	38568320	602630	2	602630	index:0,count:602630,average:32,stdev:0|index:1,count:602630,average:32,stdev:0	GSM1937793_r1						1.96	2.22	0.09	27860793	31742141	22842009	27310446	113.93	119.56	481489	436485	211.946	904.600	100	2293	70.6	86.1	629380	339938	629380	339938	62.41	64.05	629380	300516	629380	252890	3004387	10.78	2.08	0	14.38	0	0.54	0	0.23	0	0.00	0	19.33	0	481489	0	64	0	58.11	0	1.20	0	0.00	0	1.02	0	0.01	0	154.96	0	0.64	0	12531	0	602630	0	86672	0	3242	0	1395	0	0	0	116504	0	4	0	0	0	59	0	7182	0	383	0	7628	0	65.52	0	394817	0	4217	6224	1.475930756462	602630.0	481489.0	12531.0	86672.0	3242.0	1395.0	0.0	116504.0	394817.0	79.9	2.1	14.4	0.5	0.2	0.0	19.3	65.5	32	32	32.00	6	19284160	22.2	23.2	24.8	22.1	7.7	30.5	13.7	smartseq
1611849	SRR2925984	SRP066154	SRS1161583	SRX1427323	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937794: CD8_75 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;6.35|sister;;CD8_76|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937794		GSM1937794	CD8_75 scRNA-seq	164669312	2572958	2015-12-22 15:48:11	85859292	164669312	2572958	2	2572958	index:0,count:2572958,average:32,stdev:0|index:1,count:2572958,average:32,stdev:0	GSM1937794_r1						2.61	2.78	0.07	119472592	130666357	93858060	107814262	109.37	114.87	2080701	1856064	194.466	981.572	100	10172	69.19	88.08	2937056	1439553	2937056	1439553	68.91	70.07	2937056	1433855	2937056	1145110	10790526	9.03	1.80	0	17.35	0	0.69	0	0.34	0	0.00	0	18.10	0	2080701	0	64	0	58.07	0	1.17	0	0.00	0	1.02	0	0.01	0	330.81	0	0.68	0	46222	0	2572958	0	446381	0	17816	0	8809	0	0	0	465632	0	46	0	0	0	269	0	40259	0	1504	0	42078	0	63.52	0	1634320	0	15354	38159	2.485280708610	2572958.0	2080701.0	46222.0	446381.0	17816.0	8809.0	0.0	465632.0	1634320.0	80.9	1.8	17.3	0.7	0.3	0.0	18.1	63.5	32	32	32.00	6	82334656	22.5	23.2	24.3	22.2	7.7	29.9	13.7	smartseq
1611867	SRR2925985	SRP066154	SRS1161582	SRX1427324	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937795: CD8_76 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;6.4333|sister;;CD8_75|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937795		GSM1937795	CD8_76 scRNA-seq	165124416	2580069	2015-12-22 15:48:11	81053675	165124416	2580069	2	2580069	index:0,count:2580069,average:32,stdev:0|index:1,count:2580069,average:32,stdev:0	GSM1937795_r1						2.47	2.17	0.08	119169356	132938951	96804102	113282221	111.55	117.02	2071311	1882615	204.107	895.979	100	9627	67.82	83.54	2728796	1404682	2728796	1404682	61.04	62.79	2728796	1264260	2728796	1055870	14409352	12.09	2.13	0	15.11	0	0.59	0	0.37	0	0.00	0	18.76	0	2071311	0	64	0	58.08	0	1.15	0	0.00	0	1.02	0	0.01	0	320.28	0	0.66	0	54897	0	2580069	0	389799	0	15194	0	9620	0	0	0	483944	0	31	0	0	0	238	0	31074	0	1692	0	33035	0	65.17	0	1681512	0	13987	28353	2.027096589690	2580069.0	2071311.0	54897.0	389799.0	15194.0	9620.0	0.0	483944.0	1681512.0	80.3	2.1	15.1	0.6	0.4	0.0	18.8	65.2	32	32	32.00	6	82562208	22.3	23.5	24.7	21.8	7.8	30.5	13.7	smartseq
1611883	SRR2925986	SRP066154	SRS1161581	SRX1427325	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937796: CD8_77 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;0.5|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937796		GSM1937796	CD8_77 scRNA-seq	84679552	1323118	2015-12-22 15:48:11	41442126	84679552	1323118	2	1323118	index:0,count:1323118,average:32,stdev:0|index:1,count:1323118,average:32,stdev:0	GSM1937796_r1						2.27	2.52	0.09	60215844	66331391	48384070	55762241	110.16	115.25	1044971	912976	222.005	1233.859	110	4300	70.05	87.17	1437747	732010	1437747	732010	67.69	68.5	1437747	707391	1437747	575205	5660605	9.40	2.06	0	15.51	0	0.75	0	0.53	0	0.00	0	19.75	0	1044971	0	64	0	58.02	0	1.17	0	0.00	0	1.02	0	0.01	0	280.19	0	0.66	0	27316	0	1323118	0	205245	0	9882	0	6957	0	0	0	261308	0	27	0	0	0	178	0	20938	0	795	0	21938	0	63.47	0	839726	0	10362	18867	1.820787492762	1323118.0	1044971.0	27316.0	205245.0	9882.0	6957.0	0.0	261308.0	839726.0	79.0	2.1	15.5	0.7	0.5	0.0	19.7	63.5	32	32	32.00	6	42339776	22.2	23.4	24.7	21.9	7.8	30.5	13.7	smartseq
1611899	SRR2925987	SRP066154	SRS1161580	SRX1427326	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937797: CD8_78 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;7.2667|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937797		GSM1937797	CD8_78 scRNA-seq	218415488	3412742	2015-12-22 15:48:11	108397218	218415488	3412742	2	3412742	index:0,count:3412742,average:32,stdev:0|index:1,count:3412742,average:32,stdev:0	GSM1937797_r1						1.91	2.28	0.07	159251774	185231154	124718343	154726591	116.31	124.06	2769320	2480610	198.839	871.044	100	13602	74.78	95.52	3823445	2071021	3823445	2071021	66.36	68.85	3823445	1837636	3823445	1492788	4447327	2.79	2.24	0	17.62	0	0.64	0	0.25	0	0.00	0	17.96	0	2769320	0	64	0	58.04	0	1.17	0	0.00	0	1.02	0	0.01	0	341.27	0	0.68	0	76572	0	3412742	0	601245	0	21853	0	8620	0	0	0	612949	0	47	0	0	0	368	0	51006	0	2695	0	54116	0	63.53	0	2168075	0	17789	48807	2.743661813480	3412742.0	2769320.0	76572.0	601245.0	21853.0	8620.0	0.0	612949.0	2168075.0	81.1	2.2	17.6	0.6	0.3	0.0	18.0	63.5	32	32	32.00	6	109207744	21.8	23.9	25.1	21.4	7.8	30.3	13.7	smartseq
1611915	SRR2925988	SRP066154	SRS1161579	SRX1427327	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937798: CD8_79 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;#N/A!|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937798		GSM1937798	CD8_79 scRNA-seq	3904	61	2015-12-22 15:48:11	83404	3904	61	2	61	index:0,count:61,average:32,stdev:0|index:1,count:61,average:32,stdev:0	GSM1937798_r1						1.82	0.0	0.0	2417	2762	1947	2319	114.27	119.11	42	38	207.105	375.786	280	2	71.43	88.24	55	30	55	30	64.29	67.65	55	27	55	23	199	8.23	3.28	0	13.11	0	0.00	0	0.00	0	0.00	0	31.15	0	42	0	64	0	57.79	0	0.00	0	0.00	0	0.00	0	0.00	0	0.22	0	0.87	0	2	0	61	0	8	0	0	0	0	0	0	0	19	0	0	0	0	0	0	0	0	0	0	0	0	0	55.74	0	34	0	0	0	-nan	61.0	42.0	2.0	8.0	0.0	0.0	0.0	19.0	34.0	68.9	3.3	13.1	0.0	0.0	0.0	31.1	55.7	32	32	32.00	6	1952	24.1	22.8	24.9	20.5	7.6	29.7	13.7	smartseq
1611930	SRR2925989	SRP066154	SRS1161578	SRX1427328	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937799: CD8_80 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;#N/A!|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937799		GSM1937799	CD8_80 scRNA-seq	228813248	3575207	2015-12-22 15:48:11	113247194	228813248	3575207	2	3575207	index:0,count:3575207,average:32,stdev:0|index:1,count:3575207,average:32,stdev:0	GSM1937799_r1						2.6	2.51	0.06	168298475	187830403	135913371	159087925	111.61	117.05	2921156	2584979	203.372	1036.289	100	13754	71.77	88.87	3955927	2096631	3955927	2096631	67.87	69.21	3955927	1982696	3955927	1632775	14593138	8.67	1.89	0	15.72	0	0.69	0	0.25	0	0.00	0	17.36	0	2921156	0	64	0	58.08	0	1.16	0	0.00	0	1.01	0	0.01	0	402.21	0	0.65	0	67735	0	3575207	0	561981	0	24559	0	8883	0	0	0	620609	0	50	0	0	0	414	0	58575	0	2246	0	61285	0	65.99	0	2359175	0	19774	56791	2.872003641145	3575207.0	2921156.0	67735.0	561981.0	24559.0	8883.0	0.0	620609.0	2359175.0	81.7	1.9	15.7	0.7	0.2	0.0	17.4	66.0	32	32	32.00	6	114406624	22.4	23.3	24.6	21.9	7.8	30.4	13.7	smartseq
1612042	SRR2925990	SRP066154	SRS1161576	SRX1427329	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937800: CD8_81 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;#N/A!|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937800		GSM1937800	CD8_81 scRNA-seq	156056000	2438375	2015-12-22 15:48:11	82090239	156056000	2438375	2	2438375	index:0,count:2438375,average:32,stdev:0|index:1,count:2438375,average:32,stdev:0	GSM1937800_r1						4.01	4.06	0.01	111993900	113341184	72953393	76665695	101.2	105.09	1950923	1697753	174.675	1093.842	91	11244	62.2	95.23	3541139	1213546	3541139	1213546	87.19	87.32	3541139	1701075	3541139	1112791	5083638	4.54	1.42	0	27.75	0	1.15	0	0.35	0	0.00	0	18.49	0	1950923	0	64	0	57.94	0	1.24	0	0.00	0	1.01	0	0.01	0	258.18	0	0.62	0	34611	0	2438375	0	676561	0	27923	0	8616	0	0	0	450913	0	41	0	0	0	320	0	49279	0	620	0	50260	0	52.26	0	1274362	0	8711	50724	5.822982436000	2438375.0	1950923.0	34611.0	676561.0	27923.0	8616.0	0.0	450913.0	1274362.0	80.0	1.4	27.7	1.1	0.4	0.0	18.5	52.3	32	32	32.00	6	78028000	23.3	22.4	23.6	23.1	7.7	29.9	13.7	smartseq
1612057	SRR2925991	SRP066154	SRS1161577	SRX1427330	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937801: CD8_82 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;#N/A!|sister;;#N/A!|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937801		GSM1937801	CD8_82 scRNA-seq	262572096	4102689	2015-12-22 15:48:11	127635523	262572096	4102689	2	4102689	index:0,count:4102689,average:32,stdev:0|index:1,count:4102689,average:32,stdev:0	GSM1937801_r1						2.48	2.3	0.06	191368114	223850898	148642541	186073206	116.97	125.18	3329252	3070240	190.292	753.361	100	17450	70.37	90.66	4642388	2342786	4642388	2342786	60.76	62.09	4642388	2022998	4642388	1604561	11756432	6.14	2.28	0	18.16	0	0.68	0	0.29	0	0.00	0	17.88	0	3329252	0	64	0	58.11	0	1.19	0	0.00	0	1.01	0	0.01	0	421.99	0	0.66	0	93655	0	4102689	0	745158	0	27977	0	11870	0	0	0	733590	0	38	0	0	0	351	0	47131	0	3025	0	50545	0	62.99	0	2584094	0	13762	46278	3.362737974132	4102689.0	3329252.0	93655.0	745158.0	27977.0	11870.0	0.0	733590.0	2584094.0	81.1	2.3	18.2	0.7	0.3	0.0	17.9	63.0	32	32	32.00	6	131286048	22.0	23.7	25.0	21.5	7.8	30.6	13.8	smartseq
1612073	SRR2925992	SRP066154	SRS1161575	SRX1427331	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937802: CD8_83 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_85|cousin 2;;CD8_86|hours since division;;4.8167|sister;;CD8_84|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937802		GSM1937802	CD8_83 scRNA-seq	41474432	648038	2015-12-22 15:48:11	22428494	41474432	648038	2	648038	index:0,count:648038,average:32,stdev:0|index:1,count:648038,average:32,stdev:0	GSM1937802_r1						1.89	3.19	0.01	28367265	31044068	20416278	23623557	109.44	115.71	491190	425840	212.167	1113.295	117	2281	68.03	94.35	793319	334168	793319	334168	76.33	75.93	793319	374908	793319	268950	1167505	4.12	1.90	0	21.14	0	1.20	0	0.27	0	0.00	0	22.73	0	491190	0	64	0	57.84	0	1.16	0	0.00	0	1.01	0	0.01	0	137.23	0	0.83	0	12290	0	648038	0	137002	0	7794	0	1775	0	0	0	147279	0	7	0	0	0	89	0	9600	0	455	0	10151	0	54.66	0	354188	0	4198	8918	2.124344926155	648038.0	491190.0	12290.0	137002.0	7794.0	1775.0	0.0	147279.0	354188.0	75.8	1.9	21.1	1.2	0.3	0.0	22.7	54.7	32	32	32.00	6	20737216	21.4	24.1	25.6	21.1	7.8	29.0	13.5	smartseq
1612088	SRR2925993	SRP066154	SRS1161573	SRX1427332	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937803: CD8_84 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_85|cousin 2;;CD8_86|hours since division;;4.85|sister;;CD8_83|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937803		GSM1937803	CD8_84 scRNA-seq	10817792	169028	2015-12-22 15:48:11	5899031	10817792	169028	2	169028	index:0,count:169028,average:32,stdev:0|index:1,count:169028,average:32,stdev:0	GSM1937803_r1						1.94	1.92	0.04	7062346	8687778	5737564	7422315	123.02	129.36	122125	108863	265.686	1048.396	174	443	76.25	93.76	163956	93116	163956	93116	64.39	63.65	163956	78641	163956	63210	262042	3.71	2.30	0	13.50	0	0.59	0	0.17	0	0.00	0	26.99	0	122125	0	64	0	57.84	0	1.17	0	0.00	0	1.01	0	0.01	0	55.32	0	0.99	0	3891	0	169028	0	22817	0	999	0	288	0	0	0	45616	0	1	0	0	0	9	0	1433	0	208	0	1651	0	58.75	0	99308	0	984	1155	1.173780487805	169028.0	122125.0	3891.0	22817.0	999.0	288.0	0.0	45616.0	99308.0	72.3	2.3	13.5	0.6	0.2	0.0	27.0	58.8	32	32	32.00	6	5408896	20.1	24.8	27.6	19.8	7.7	28.6	13.4	smartseq
1612136	SRR2925996	SRP066154	SRS1161571	SRX1427335	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937806: CD8_87 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_89|cousin 2;;CD8_90|hours since division;;1.8833|sister;;CD8_88|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937806		GSM1937806	CD8_87 scRNA-seq	131389504	2052961	2015-12-22 15:48:11	65599585	131389504	2052961	2	2052961	index:0,count:2052961,average:32,stdev:0|index:1,count:2052961,average:32,stdev:0	GSM1937806_r1						2.56	2.06	0.09	93799275	107328685	76212934	91874028	114.42	120.55	1629790	1501100	200.984	829.525	100	7645	69.54	85.66	2139077	1133416	2139077	1133416	60.08	61.95	2139077	979147	2139077	819731	9885570	10.54	2.05	0	14.93	0	0.58	0	0.30	0	0.00	0	19.74	0	1629790	0	64	0	58.15	0	1.17	0	0.00	0	1.01	0	0.01	0	351.94	0	0.74	0	42147	0	2052961	0	306557	0	11936	0	6075	0	0	0	405160	0	31	0	0	0	169	0	22007	0	1471	0	23678	0	64.45	0	1323233	0	9659	20222	2.093591469096	2052961.0	1629790.0	42147.0	306557.0	11936.0	6075.0	0.0	405160.0	1323233.0	79.4	2.1	14.9	0.6	0.3	0.0	19.7	64.5	32	32	32.00	6	65694752	22.3	23.4	24.6	22.0	7.7	30.1	13.7	smartseq
786439	SRR2926000	SRP066154	SRS1161567	SRX1427339	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937810: CD8_91 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_93|cousin 2;;CD8_94|hours since division;;7.3833|sister;;CD8_92|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937810		GSM1937810	CD8_91 scRNA-seq	3008	47	2015-12-22 15:48:11	82583	3008	47	2	47	index:0,count:47,average:32,stdev:0|index:1,count:47,average:32,stdev:0	GSM1937810_r1						2.44	0.0	0.0	1865	2004	1628	1767	107.45	108.54	32	31	210.000	236.125	267	2	75.0	85.71	41	24	41	24	71.88	67.86	41	23	41	19	89	4.77	0.00	0	8.51	0	4.26	0	0.00	0	0.00	0	27.66	0	32	0	64	0	58.14	0	0.00	0	0.00	0	1.00	0	0.06	0	0.17	0	1.11	0	0	0	47	0	4	0	2	0	0	0	0	0	13	0	0	0	0	0	0	0	0	0	0	0	0	0	59.57	0	28	0	0	0	-nan	47.0	32.0	0.0	4.0	2.0	0.0	0.0	13.0	28.0	68.1	0.0	8.5	4.3	0.0	0.0	27.7	59.6	32	32	32.00	6	1504	23.7	23.7	23.7	21.5	7.4	30.2	13.9	smartseq
786582	SRR2926012	SRP066154	SRS1161555	SRX1427351	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937822: CD8_103 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_104|cousin 2;;CD8_105|hours since division;;5.5583|sister;;CD8_106|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937822		GSM1937822	CD8_103 scRNA-seq	4608	72	2015-12-22 15:48:11	82810	4608	72	2	72	index:0,count:72,average:32,stdev:0|index:1,count:72,average:32,stdev:0	GSM1937822_r1						2.63	2.63	0.0	3199	3474	2563	2830	108.6	110.42	56	52	221.442	480.625	115	2	67.86	84.44	76	38	76	38	66.07	68.89	76	37	76	31	401	12.54	1.39	0	15.28	0	0.00	0	0.00	0	0.00	0	22.22	0	56	0	64	0	57.51	0	0.00	0	0.00	0	0.00	0	0.00	0	0.26	0	0.39	0	1	0	72	0	11	0	0	0	0	0	0	0	16	0	0	0	0	0	0	0	1	0	0	0	1	0	62.50	0	45	0	1	1	1.000000000000	72.0	56.0	1.0	11.0	0.0	0.0	0.0	16.0	45.0	77.8	1.4	15.3	0.0	0.0	0.0	22.2	62.5	32	32	32.00	6	2304	21.2	23.7	24.8	22.7	7.5	31.1	14.0	smartseq
786590	SRR2926013	SRP066154	SRS1161554	SRX1427352	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937823: CD8_104 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_103|cousin 2;;CD8_106|hours since division;;5.4278|sister;;CD8_105|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937823		GSM1937823	CD8_104 scRNA-seq	63285312	988833	2015-12-22 15:48:11	31035884	63285312	988833	2	988833	index:0,count:988833,average:32,stdev:0|index:1,count:988833,average:32,stdev:0	GSM1937823_r1						2.75	2.58	0.07	45142499	49624475	35491320	40890139	109.93	115.21	783064	670422	236.501	1337.454	100	3016	71.72	91.18	1121026	561615	1121026	561615	73.31	73.69	1121026	574039	1121026	453901	3136319	6.95	1.95	0	16.90	0	0.96	0	0.33	0	0.00	0	19.51	0	783064	0	64	0	58.02	0	1.14	0	0.00	0	1.01	0	0.01	0	237.32	0	0.62	0	19302	0	988833	0	167122	0	9526	0	3289	0	0	0	192954	0	14	0	0	0	138	0	16880	0	500	0	17532	0	62.29	0	615942	0	7759	15507	1.998582291532	988833.0	783064.0	19302.0	167122.0	9526.0	3289.0	0.0	192954.0	615942.0	79.2	2.0	16.9	1.0	0.3	0.0	19.5	62.3	32	32	32.00	6	31642656	22.2	23.3	24.8	21.9	7.8	30.7	13.8	smartseq
786599	SRR2926014	SRP066154	SRS1161553	SRX1427353	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937824: CD8_105 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_103|cousin 2;;CD8_106|hours since division;;5.4472|sister;;CD8_104|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937824		GSM1937824	CD8_105 scRNA-seq	248277248	3879332	2015-12-22 15:48:11	120876340	248277248	3879332	2	3879332	index:0,count:3879332,average:32,stdev:0|index:1,count:3879332,average:32,stdev:0	GSM1937824_r1						2.83	2.19	0.06	180329297	205041263	144598157	173154222	113.7	119.75	3129922	2776903	214.057	1028.724	100	13693	72.13	89.96	4276204	2257623	4276204	2257623	66.41	67.37	4276204	2078536	4276204	1690813	13099935	7.26	2.10	0	15.99	0	0.82	0	0.32	0	0.00	0	18.18	0	3129922	0	64	0	58.09	0	1.17	0	0.00	0	1.01	0	0.01	0	436.42	0	0.62	0	81449	0	3879332	0	620326	0	31775	0	12288	0	0	0	705347	0	35	0	0	0	426	0	57757	0	2638	0	60856	0	64.69	0	2509596	0	16773	56441	3.364991355154	3879332.0	3129922.0	81449.0	620326.0	31775.0	12288.0	0.0	705347.0	2509596.0	80.7	2.1	16.0	0.8	0.3	0.0	18.2	64.7	32	32	32.00	6	124138624	22.2	23.4	24.8	21.8	7.8	30.7	13.8	smartseq
803127	SRR2925826	SRP066154	SRS1161741	SRX1427165	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937636: L1210_5 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_28|cousin 2;;L1210_39|hours since division;;3.9053|sister;;L1210_17|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937636		GSM1937636	L1210_5 scRNA-seq	72199616	1128119	2015-12-22 15:48:11	35101158	72199616	1128119	2	1128119	index:0,count:1128119,average:32,stdev:0|index:1,count:1128119,average:32,stdev:0	GSM1937636_r1						4.7	1.87	0.33	51193966	55501766	41839665	47582261	108.41	113.73	885285	784821	214.313	1225.489	117	4369	69.27	84.74	1158442	613198	1158442	613198	64.51	67.25	1158442	571087	1158442	486622	5817845	11.36	2.14	0	14.33	0	0.65	0	0.54	0	0.00	0	20.34	0	885285	0	64	0	58.04	0	1.25	0	0.00	0	1.02	0	0.01	0	270.75	0	0.68	0	24129	0	1128119	0	161671	0	7289	0	6061	0	0	0	229484	0	16	0	0	0	110	0	15416	0	777	0	16319	0	64.14	0	723614	0	8621	13264	1.538568611530	1128119.0	885285.0	24129.0	161671.0	7289.0	6061.0	0.0	229484.0	723614.0	78.5	2.1	14.3	0.6	0.5	0.0	20.3	64.1	32	32	32.00	6	36099808	22.6	22.9	24.5	22.2	7.7	30.9	13.8	smartseq
803135	SRR2925827	SRP066154	SRS1161740	SRX1427166	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937637: L1210_6 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_82|cousin 2;;L1210_18|hours since division;;1.2167|sister;;L1210_29|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937637		GSM1937637	L1210_6 scRNA-seq	75388608	1177947	2015-12-22 15:48:11	36456972	75388608	1177947	2	1177947	index:0,count:1177947,average:32,stdev:0|index:1,count:1177947,average:32,stdev:0	GSM1937637_r1						7.41	1.9	0.2	52215295	52604066	43383222	45309523	100.74	104.44	903093	828431	202.427	1068.855	125	4810	60.4	72.71	1161723	545465	1161723	545465	56.22	57.4	1161723	507734	1161723	430625	8222742	15.75	2.06	0	12.98	0	0.67	0	0.81	0	0.00	0	21.86	0	903093	0	64	0	58.10	0	1.19	0	0.00	0	1.02	0	0.01	0	265.04	0	0.66	0	24280	0	1177947	0	152901	0	7858	0	9517	0	0	0	257479	0	13	0	0	0	96	0	10947	0	725	0	11781	0	63.69	0	750192	0	6494	9364	1.441946412073	1177947.0	903093.0	24280.0	152901.0	7858.0	9517.0	0.0	257479.0	750192.0	76.7	2.1	13.0	0.7	0.8	0.0	21.9	63.7	32	32	32.00	6	37694304	23.7	22.0	23.7	22.9	7.7	30.9	13.8	smartseq
803143	SRR2925828	SRP066154	SRS1161739	SRX1427167	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937638: L1210_7 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_83|cousin 2;;L1210_30|hours since division;;0.7667|sister;;L1210_19|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937638		GSM1937638	L1210_7 scRNA-seq	57541952	899093	2015-12-22 15:48:11	27878752	57541952	899093	2	899093	index:0,count:899093,average:32,stdev:0|index:1,count:899093,average:32,stdev:0	GSM1937638_r1						3.72	1.69	0.37	40683429	44524407	33246752	38261641	109.44	115.08	703083	639962	211.571	985.602	117	3592	67.6	82.72	910529	475263	910529	475263	60.16	62.81	910529	422975	910529	360853	4866801	11.96	2.23	0	14.30	0	0.55	0	0.45	0	0.00	0	20.79	0	703083	0	64	0	58.08	0	1.21	0	0.00	0	1.02	0	0.02	0	248.98	0	0.68	0	20086	0	899093	0	128543	0	4974	0	4071	0	0	0	186965	0	9	0	0	0	80	0	9303	0	641	0	10033	0	63.90	0	574540	0	5503	7766	1.411230238052	899093.0	703083.0	20086.0	128543.0	4974.0	4071.0	0.0	186965.0	574540.0	78.2	2.2	14.3	0.6	0.5	0.0	20.8	63.9	32	32	32.00	6	28770976	22.6	23.0	24.6	22.1	7.7	30.9	13.8	smartseq
803207	SRR2925830	SRP066154	SRS1161737	SRX1427169	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937640: L1210_9 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_31|cousin 2;;L1210_42|hours since division;;5.2|sister;;L1210_20|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937640		GSM1937640	L1210_9 scRNA-seq	78529728	1227027	2015-12-22 15:48:11	38112621	78529728	1227027	2	1227027	index:0,count:1227027,average:32,stdev:0|index:1,count:1227027,average:32,stdev:0	GSM1937640_r1						5.03	2.24	0.46	55417308	58169448	46503225	50607365	104.97	108.83	958174	827515	219.387	1445.491	125	4258	67.4	80.3	1245484	645818	1245484	645818	65.9	67.42	1245484	631429	1245484	542194	8773483	15.83	1.89	0	12.55	0	0.76	0	0.66	0	0.00	0	20.50	0	958174	0	64	0	58.03	0	1.23	0	0.00	0	1.02	0	0.01	0	276.08	0	0.67	0	23163	0	1227027	0	153940	0	9291	0	8072	0	0	0	251490	0	17	0	0	0	148	0	19872	0	690	0	20727	0	65.54	0	804234	0	10779	17061	1.582799888672	1227027.0	958174.0	23163.0	153940.0	9291.0	8072.0	0.0	251490.0	804234.0	78.1	1.9	12.5	0.8	0.7	0.0	20.5	65.5	32	32	32.00	6	39264864	23.0	22.6	24.2	22.4	7.7	30.8	13.8	smartseq
803239	SRR2925834	SRP066154	SRS1161733	SRX1427173	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937644: L1210_13 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_24|cousin 2;;L1210_35|hours since division;;6.7797|sister;;L1210_1|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937644		GSM1937644	L1210_13 scRNA-seq	34618944	540921	2015-12-22 15:48:11	16941849	34618944	540921	2	540921	index:0,count:540921,average:32,stdev:0|index:1,count:540921,average:32,stdev:0	GSM1937644_r1						3.67	1.85	0.31	24974244	26981853	20089805	22803051	108.04	113.51	432331	391170	191.357	1051.572	125	2538	67.67	84.15	575186	292580	575186	292580	63.06	66.21	575186	272634	575186	230201	2876262	11.52	2.08	0	15.64	0	0.74	0	0.55	0	0.00	0	18.78	0	432331	0	64	0	58.13	0	1.22	0	0.00	0	1.03	0	0.01	0	129.82	0	0.67	0	11266	0	540921	0	84626	0	3996	0	3000	0	0	0	101594	0	4	0	0	0	69	0	7063	0	365	0	7501	0	64.28	0	347705	0	4379	5794	1.323133135419	540921.0	432331.0	11266.0	84626.0	3996.0	3000.0	0.0	101594.0	347705.0	79.9	2.1	15.6	0.7	0.6	0.0	18.8	64.3	32	32	32.00	6	17309472	22.5	22.9	24.5	22.3	7.7	30.6	13.8	smartseq
803358	SRR2925843	SRP066154	SRS1161724	SRX1427182	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937653: L1210_22 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_33|cousin 2;;L1210_44|hours since division;;1.7917|sister;;L1210_11|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937653		GSM1937653	L1210_22 scRNA-seq	58901184	920331	2015-12-22 15:48:11	28737230	58901184	920331	2	920331	index:0,count:920331,average:32,stdev:0|index:1,count:920331,average:32,stdev:0	GSM1937653_r1						5.4	2.25	0.63	41168434	42066480	34387635	36387467	102.18	105.82	712045	616899	205.855	1729.520	125	3429	65.35	78.22	938319	465300	938319	465300	65.96	67.52	938319	469677	938319	401634	7137784	17.34	1.84	0	12.73	0	0.88	0	1.09	0	0.00	0	20.67	0	712045	0	64	0	58.06	0	1.23	0	0.00	0	1.02	0	0.01	0	207.07	0	0.66	0	16938	0	920331	0	117198	0	8066	0	10029	0	0	0	190191	0	11	0	0	0	118	0	15147	0	448	0	15724	0	64.63	0	594847	0	8847	12954	1.464225161072	920331.0	712045.0	16938.0	117198.0	8066.0	10029.0	0.0	190191.0	594847.0	77.4	1.8	12.7	0.9	1.1	0.0	20.7	64.6	32	32	32.00	6	29450592	23.2	22.3	24.0	22.8	7.7	30.6	13.8	smartseq
803366	SRR2925844	SRP066154	SRS1161723	SRX1427183	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937654: L1210_23 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;11.7333|sister;;L1210_12|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937654		GSM1937654	L1210_23 scRNA-seq	53436672	834948	2015-12-22 15:48:11	26248176	53436672	834948	2	834948	index:0,count:834948,average:32,stdev:0|index:1,count:834948,average:32,stdev:0	GSM1937654_r1						3.82	1.77	0.4	38132072	41637640	30956723	35573325	109.19	114.91	658814	595595	201.711	1016.837	125	3575	68.73	84.65	860514	452794	860514	452794	62.59	65.74	860514	412341	860514	351668	4266836	11.19	2.19	0	14.84	0	0.64	0	0.39	0	0.00	0	20.06	0	658814	0	64	0	58.11	0	1.25	0	0.00	0	1.03	0	0.01	0	176.81	0	0.68	0	18295	0	834948	0	123905	0	5374	0	3245	0	0	0	167515	0	14	0	0	0	89	0	10422	0	559	0	11084	0	64.06	0	534909	0	6313	8719	1.381118327261	834948.0	658814.0	18295.0	123905.0	5374.0	3245.0	0.0	167515.0	534909.0	78.9	2.2	14.8	0.6	0.4	0.0	20.1	64.1	32	32	32.00	6	26718336	22.5	22.9	24.5	22.4	7.7	30.5	13.8	smartseq
803374	SRR2925845	SRP066154	SRS1161722	SRX1427184	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937655: L1210_24 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_1|cousin 2;;L1210_13|hours since division;;4.6561|sister;;L1210_35|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937655		GSM1937655	L1210_24 scRNA-seq	35992832	562388	2015-12-22 15:48:11	17560206	35992832	562388	2	562388	index:0,count:562388,average:32,stdev:0|index:1,count:562388,average:32,stdev:0	GSM1937655_r1						3.61	1.89	0.24	25289519	27630848	20530176	23612173	109.26	115.01	437145	387824	212.804	1235.099	125	2185	69.67	85.81	572630	304557	572630	304557	63.71	66.66	572630	278496	572630	236605	2529899	10.00	2.10	0	14.62	0	0.61	0	0.66	0	0.00	0	21.00	0	437145	0	64	0	58.07	0	1.25	0	0.00	0	1.03	0	0.01	0	144.61	0	0.74	0	11832	0	562388	0	82206	0	3422	0	3738	0	0	0	118083	0	13	0	0	0	67	0	7611	0	405	0	8096	0	63.11	0	354939	0	4754	6320	1.329406815313	562388.0	437145.0	11832.0	82206.0	3422.0	3738.0	0.0	118083.0	354939.0	77.7	2.1	14.6	0.6	0.7	0.0	21.0	63.1	32	32	32.00	6	17996416	22.6	23.2	24.6	21.9	7.7	30.7	13.8	smartseq
803383	SRR2925846	SRP066154	SRS1161721	SRX1427185	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937656: L1210_25 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_36|cousin 2;;L1210_58|hours since division;;4.9333|sister;;L1210_47|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937656		GSM1937656	L1210_25 scRNA-seq	60683648	948182	2015-12-22 15:48:11	29613096	60683648	948182	2	948182	index:0,count:948182,average:32,stdev:0|index:1,count:948182,average:32,stdev:0	GSM1937656_r1						5.33	1.65	0.07	42967696	48554156	34207335	40961972	113.0	119.75	742419	661436	218.148	1060.556	117	3664	73.63	92.46	983885	546675	983885	546675	66.56	69.87	983885	494127	983885	413143	2052965	4.78	2.22	0	15.94	0	0.58	0	0.38	0	0.00	0	20.74	0	742419	0	64	0	58.04	0	1.21	0	0.00	0	1.02	0	0.01	0	262.57	0	0.74	0	21089	0	948182	0	151137	0	5521	0	3588	0	0	0	196654	0	15	0	0	0	95	0	12018	0	819	0	12947	0	62.36	0	591282	0	6628	10345	1.560802655401	948182.0	742419.0	21089.0	151137.0	5521.0	3588.0	0.0	196654.0	591282.0	78.3	2.2	15.9	0.6	0.4	0.0	20.7	62.4	32	32	32.00	6	30341824	22.5	23.4	24.7	21.7	7.7	30.7	13.8	smartseq
803791	SRR2925879	SRP066154	SRS1161688	SRX1427218	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937689: L1210_58 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;L1210_25|cousin 2;;L1210_47|hours since division;;2.1083|sister;;L1210_36|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937689		GSM1937689	L1210_58 scRNA-seq	64720768	1011262	2015-12-22 15:48:11	31445961	64720768	1011262	2	1011262	index:0,count:1011262,average:32,stdev:0|index:1,count:1011262,average:32,stdev:0	GSM1937689_r1						3.26	1.9	0.15	46505663	51515460	37884701	44097960	110.77	116.4	803440	707869	215.028	1143.996	125	3901	70.73	86.8	1052007	568306	1052007	568306	64.73	67.07	1052007	520095	1052007	439131	4509632	9.70	2.09	0	14.71	0	0.65	0	0.44	0	0.00	0	19.46	0	803440	0	64	0	58.08	0	1.22	0	0.00	0	1.02	0	0.01	0	242.70	0	0.67	0	21120	0	1011262	0	148714	0	6524	0	4457	0	0	0	196841	0	13	0	0	0	109	0	15116	0	711	0	15949	0	64.74	0	654726	0	8257	13179	1.596100278552	1011262.0	803440.0	21120.0	148714.0	6524.0	4457.0	0.0	196841.0	654726.0	79.4	2.1	14.7	0.6	0.4	0.0	19.5	64.7	32	32	32.00	6	32360384	22.5	23.0	24.5	22.3	7.7	30.8	13.8	smartseq
803847	SRR2925880	SRP066154	SRS1161687	SRX1427219	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937690: L1210_59 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;L1210 lymphocytic leukemia (ATCC CCL-219)|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;7.5333|sister;;L1210_70|source_name;;Single L1210 cells grown for multiple generations on-chip|strain;;DBA subline 212	GEO Accession;;GSM1937690		GSM1937690	L1210_59 scRNA-seq	61264896	957264	2015-12-22 15:48:11	29800311	61264896	957264	2	957264	index:0,count:957264,average:32,stdev:0|index:1,count:957264,average:32,stdev:0	GSM1937690_r1						3.3	1.84	0.24	43730893	48713813	35479251	41659079	111.39	117.42	755483	673387	215.989	1076.204	125	3895	70.95	87.43	990860	536034	990860	536034	63.7	66.42	990860	481214	990860	407250	3858939	8.82	2.24	0	14.87	0	0.72	0	0.46	0	0.00	0	19.90	0	755483	0	64	0	58.06	0	1.18	0	0.00	0	1.02	0	0.01	0	246.15	0	0.68	0	21480	0	957264	0	142354	0	6878	0	4414	0	0	0	190489	0	16	0	0	0	91	0	12937	0	683	0	13727	0	64.05	0	613129	0	7315	11040	1.509227614491	957264.0	755483.0	21480.0	142354.0	6878.0	4414.0	0.0	190489.0	613129.0	78.9	2.2	14.9	0.7	0.5	0.0	19.9	64.1	32	32	32.00	6	30632448	22.2	23.3	24.8	21.9	7.8	30.9	13.8	smartseq
805183	SRR2925927	SRP066154	SRS1161640	SRX1427266	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937737: CD8_18 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;3.6167|sister;;CD8_16|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937737		GSM1937737	CD8_18 scRNA-seq	111886144	1748221	2015-12-22 15:48:11	53871339	111886144	1748221	2	1748221	index:0,count:1748221,average:32,stdev:0|index:1,count:1748221,average:32,stdev:0	GSM1937737_r1						2.63	2.22	0.05	83288001	94665513	67603019	80716780	113.66	119.4	1438937	1253491	227.669	1118.553	125	6113	73.79	90.87	1918777	1061849	1918777	1061849	67.67	68.96	1918777	973715	1918777	805862	5513814	6.62	2.19	0	15.47	0	0.66	0	0.25	0	0.00	0	16.78	0	1438937	0	64	0	58.12	0	1.15	0	0.00	0	1.02	0	0.01	0	370.21	0	0.58	0	38263	0	1748221	0	270419	0	11533	0	4425	0	0	0	293326	0	32	0	0	0	200	0	29980	0	1003	0	31215	0	66.84	0	1168518	0	11940	27710	2.320770519263	1748221.0	1438937.0	38263.0	270419.0	11533.0	4425.0	0.0	293326.0	1168518.0	82.3	2.2	15.5	0.7	0.3	0.0	16.8	66.8	32	32	32.00	6	55943072	22.3	23.2	24.7	22.0	7.8	30.9	13.8	smartseq
805191	SRR2925928	SRP066154	SRS1161638	SRX1427267	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937738: CD8_19 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;3.5|sister;;CD8_14|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937738		GSM1937738	CD8_19 scRNA-seq	128589184	2009206	2015-12-22 15:48:11	62177082	128589184	2009206	2	2009206	index:0,count:2009206,average:32,stdev:0|index:1,count:2009206,average:32,stdev:0	GSM1937738_r1						1.35	2.33	0.02	95043599	109130467	75130804	91421781	114.82	121.68	1645015	1440785	209.132	1126.447	117	7708	74.03	93.6	2281087	1217867	2281087	1217867	68.03	69.59	2281087	1119078	2281087	905480	4447510	4.68	2.22	0	17.11	0	0.74	0	0.18	0	0.00	0	17.20	0	1645015	0	64	0	58.07	0	1.22	0	0.00	0	1.02	0	0.01	0	425.48	0	0.60	0	44631	0	2009206	0	343822	0	14916	0	3714	0	0	0	345561	0	33	0	0	0	229	0	35891	0	1231	0	37384	0	64.76	0	1301193	0	11931	34211	2.867404241053	2009206.0	1645015.0	44631.0	343822.0	14916.0	3714.0	0.0	345561.0	1301193.0	81.9	2.2	17.1	0.7	0.2	0.0	17.2	64.8	32	32	32.00	6	64294592	22.2	23.3	24.8	22.0	7.8	30.9	13.8	smartseq
805199	SRR2925929	SRP066154	SRS1161639	SRX1427268	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937739: CD8_20 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;#N/A!|cousin 2;;#N/A!|hours since division;;3.0833|sister;;CD8_17|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937739		GSM1937739	CD8_20 scRNA-seq	115001152	1796893	2015-12-22 15:48:11	54835616	115001152	1796893	2	1796893	index:0,count:1796893,average:32,stdev:0|index:1,count:1796893,average:32,stdev:0	GSM1937739_r1						2.16	2.44	0.04	85103897	94634285	66630524	78476581	111.2	117.78	1479826	1331698	176.418	818.598	117	8688	70.51	90.05	2050592	1043408	2050592	1043408	66.55	68.77	2050592	984811	2050592	796825	6176530	7.26	2.10	0	17.87	0	0.65	0	0.25	0	0.00	0	16.75	0	1479826	0	64	0	58.09	0	1.21	0	0.00	0	1.02	0	0.01	0	359.38	0	0.55	0	37803	0	1796893	0	321121	0	11625	0	4486	0	0	0	300956	0	29	0	0	0	205	0	29867	0	1120	0	31221	0	64.48	0	1158705	0	11340	28088	2.476895943563	1796893.0	1479826.0	37803.0	321121.0	11625.0	4486.0	0.0	300956.0	1158705.0	82.4	2.1	17.9	0.6	0.2	0.0	16.7	64.5	32	32	32.00	6	57500576	22.4	23.1	24.7	22.0	7.8	31.0	13.8	smartseq
805287	SRR2925934	SRP066154	SRS1161633	SRX1427273	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937744: CD8_25 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_26|cousin 2;;CD8_28|hours since division;;2.4833|sister;;CD8_27|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937744		GSM1937744	CD8_25 scRNA-seq	148998464	2328101	2015-12-22 15:48:11	72253490	148998464	2328101	2	2328101	index:0,count:2328101,average:32,stdev:0|index:1,count:2328101,average:32,stdev:0	GSM1937744_r1						2.06	2.04	0.06	107775881	125401364	86442561	106736379	116.35	123.48	1866558	1694305	196.622	886.719	117	9778	71.82	89.55	2487044	1340505	2487044	1340505	61.02	62.91	2487044	1139007	2487044	941707	7959999	7.39	2.34	0	15.88	0	0.57	0	0.21	0	0.00	0	19.05	0	1866558	0	64	0	58.13	0	1.18	0	0.00	0	1.02	0	0.01	0	380.96	0	0.63	0	54479	0	2328101	0	369607	0	13196	0	4911	0	0	0	443436	0	25	0	0	0	238	0	31145	0	1582	0	32990	0	64.30	0	1496951	0	12720	28951	2.276022012579	2328101.0	1866558.0	54479.0	369607.0	13196.0	4911.0	0.0	443436.0	1496951.0	80.2	2.3	15.9	0.6	0.2	0.0	19.0	64.3	32	32	32.00	6	74499232	22.3	23.2	24.8	21.9	7.8	30.8	13.8	smartseq
805295	SRR2925935	SRP066154	SRS1161632	SRX1427274	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937745: CD8_26 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_25|cousin 2;;CD8_27|hours since division;;2.6|sister;;CD8_28|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937745		GSM1937745	CD8_26 scRNA-seq	119608448	1868882	2015-12-22 15:48:11	58155659	119608448	1868882	2	1868882	index:0,count:1868882,average:32,stdev:0|index:1,count:1868882,average:32,stdev:0	GSM1937745_r1						2.41	1.86	0.19	86331409	99643974	70948942	86122960	115.42	121.39	1492986	1339434	224.702	1010.103	125	6616	72.36	88.05	1925866	1080257	1925866	1080257	62.21	64.1	1925866	928741	1925866	786447	7520040	8.71	2.37	0	14.24	0	0.53	0	0.24	0	0.00	0	19.35	0	1492986	0	64	0	58.12	0	1.16	0	0.00	0	1.02	0	0.01	0	395.76	0	0.63	0	44302	0	1868882	0	266082	0	9827	0	4411	0	0	0	361658	0	28	0	0	0	177	0	24171	0	1177	0	25553	0	65.65	0	1226904	0	11222	21525	1.918107289253	1868882.0	1492986.0	44302.0	266082.0	9827.0	4411.0	0.0	361658.0	1226904.0	79.9	2.4	14.2	0.5	0.2	0.0	19.4	65.6	32	32	32.00	6	59804224	22.2	23.2	24.8	22.0	7.8	30.8	13.8	smartseq
805303	SRR2925936	SRP066154	SRS1161631	SRX1427275	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937746: CD8_27 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_26|cousin 2;;CD8_28|hours since division;;2.5167|sister;;CD8_25|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937746		GSM1937746	CD8_27 scRNA-seq	71575936	1118374	2015-12-22 15:48:11	35080661	71575936	1118374	2	1118374	index:0,count:1118374,average:32,stdev:0|index:1,count:1118374,average:32,stdev:0	GSM1937746_r1						1.99	1.83	0.1	51395743	59026739	42406710	51168655	114.85	120.66	888879	803095	213.362	955.957	125	4219	70.92	85.96	1138487	630376	1138487	630376	60.09	62.18	1138487	534089	1138487	455963	5352654	10.41	2.29	0	13.91	0	0.53	0	0.25	0	0.00	0	19.74	0	888879	0	64	0	58.12	0	1.16	0	0.00	0	1.02	0	0.01	0	287.58	0	0.66	0	25602	0	1118374	0	155564	0	5972	0	2789	0	0	0	220734	0	7	0	0	0	95	0	14054	0	689	0	14845	0	65.57	0	733315	0	7521	12161	1.616939236804	1118374.0	888879.0	25602.0	155564.0	5972.0	2789.0	0.0	220734.0	733315.0	79.5	2.3	13.9	0.5	0.2	0.0	19.7	65.6	32	32	32.00	6	35787968	22.3	23.1	24.8	22.0	7.7	30.7	13.8	smartseq
805327	SRR2925939	SRP066154	SRS1161628	SRX1427278	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937749: CD8_30 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_29|cousin 2;;CD8_31|hours since division;;2.8333|sister;;CD8_32|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937749		GSM1937749	CD8_30 scRNA-seq	117835136	1841174	2015-12-22 15:48:11	58272141	117835136	1841174	2	1841174	index:0,count:1841174,average:32,stdev:0|index:1,count:1841174,average:32,stdev:0	GSM1937749_r1						2.01	2.15	0.05	83845819	96013075	67926488	82030809	114.51	120.76	1449551	1303316	204.304	926.931	117	7229	72.65	89.65	1917748	1053159	1917748	1053159	64.24	66.21	1917748	931162	1917748	777821	6528534	7.79	2.03	0	14.93	0	0.63	0	0.24	0	0.00	0	20.40	0	1449551	0	64	0	58.11	0	1.13	0	0.00	0	1.02	0	0.01	0	389.90	0	0.72	0	37352	0	1841174	0	274821	0	11626	0	4436	0	0	0	375561	0	31	0	0	0	202	0	25490	0	1241	0	26964	0	63.80	0	1174730	0	11504	23182	2.015125173853	1841174.0	1449551.0	37352.0	274821.0	11626.0	4436.0	0.0	375561.0	1174730.0	78.7	2.0	14.9	0.6	0.2	0.0	20.4	63.8	32	32	32.00	6	58917568	21.9	23.6	25.0	21.6	7.8	30.4	13.7	smartseq
805383	SRR2925940	SRP066154	SRS1161627	SRX1427279	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937750: CD8_31 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_30|cousin 2;;CD8_32|hours since division;;2.3167|sister;;CD8_29|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937750		GSM1937750	CD8_31 scRNA-seq	108722496	1698789	2015-12-22 15:48:11	53734222	108722496	1698789	2	1698789	index:0,count:1698789,average:32,stdev:0|index:1,count:1698789,average:32,stdev:0	GSM1937750_r1						1.65	1.69	0.08	77394140	88267606	63996354	76720224	114.05	119.88	1339394	1217839	199.582	825.592	117	7097	72.11	87.2	1693044	965801	1693044	965801	61.37	64.36	1693044	822041	1693044	712789	7513907	9.71	2.05	0	13.65	0	0.42	0	0.22	0	0.00	0	20.52	0	1339394	0	64	0	58.11	0	1.17	0	0.00	0	1.02	0	0.01	0	359.74	0	0.75	0	34833	0	1698789	0	231860	0	7055	0	3748	0	0	0	348592	0	21	0	0	0	162	0	21160	0	1195	0	22538	0	65.20	0	1107534	0	10836	18926	1.746585455888	1698789.0	1339394.0	34833.0	231860.0	7055.0	3748.0	0.0	348592.0	1107534.0	78.8	2.1	13.6	0.4	0.2	0.0	20.5	65.2	32	32	32.00	6	54361248	21.8	23.7	25.2	21.5	7.8	30.5	13.8	smartseq
806055	SRR2925994	SRP066154	SRS1161574	SRX1427333	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937804: CD8_85 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_83|cousin 2;;CD8_84|hours since division;;4.6333|sister;;CD8_86|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937804		GSM1937804	CD8_85 scRNA-seq	123909632	1936088	2015-12-22 15:48:11	62352484	123909632	1936088	2	1936088	index:0,count:1936088,average:32,stdev:0|index:1,count:1936088,average:32,stdev:0	GSM1937804_r1						2.01	2.17	0.05	90032814	103621039	72035284	87557722	115.09	121.55	1561231	1396040	213.255	909.032	100	7155	73.11	91.37	2114321	1141400	2114321	1141400	65.74	67.44	2114321	1026354	2114321	842451	5745448	6.38	2.17	0	16.11	0	0.66	0	0.25	0	0.00	0	18.45	0	1561231	0	64	0	58.04	0	1.16	0	0.00	0	1.01	0	0.01	0	366.84	0	0.69	0	42087	0	1936088	0	311989	0	12794	0	4857	0	0	0	357206	0	22	0	0	0	190	0	27559	0	1416	0	29187	0	64.52	0	1249242	0	11605	25429	2.191210685050	1936088.0	1561231.0	42087.0	311989.0	12794.0	4857.0	0.0	357206.0	1249242.0	80.6	2.2	16.1	0.7	0.3	0.0	18.4	64.5	32	32	32.00	6	61954816	21.7	24.0	25.2	21.4	7.8	30.2	13.7	smartseq
806063	SRR2925995	SRP066154	SRS1161570	SRX1427334	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937805: CD8_86 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_83|cousin 2;;CD8_84|hours since division;;4.6833|sister;;CD8_85|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937805		GSM1937805	CD8_86 scRNA-seq	30673536	479274	2015-12-22 15:48:11	16374452	30673536	479274	2	479274	index:0,count:479274,average:32,stdev:0|index:1,count:479274,average:32,stdev:0	GSM1937805_r1						2.15	3.75	0.02	20724047	21343533	14326449	15292888	102.99	106.75	362566	323516	162.903	1052.083	89	2314	65.92	95.2	630020	239019	630020	239019	84.76	85.36	630020	307309	630020	214324	913400	4.41	1.43	0	23.26	0	1.28	0	0.38	0	0.00	0	22.69	0	362566	0	64	0	57.92	0	1.22	0	0.00	0	1.02	0	0.01	0	123.24	0	0.75	0	6855	0	479274	0	111497	0	6147	0	1800	0	0	0	108761	0	13	0	0	0	82	0	8367	0	140	0	8602	0	52.39	0	251069	0	3302	7926	2.400363416111	479274.0	362566.0	6855.0	111497.0	6147.0	1800.0	0.0	108761.0	251069.0	75.6	1.4	23.3	1.3	0.4	0.0	22.7	52.4	32	32	32.00	6	15336768	22.7	22.9	24.2	22.5	7.7	29.4	13.6	smartseq
806079	SRR2925997	SRP066154	SRS1161572	SRX1427336	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937807: CD8_88 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_89|cousin 2;;CD8_90|hours since division;;1.9|sister;;CD8_87|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937807		GSM1937807	CD8_88 scRNA-seq	136540800	2133450	2015-12-22 15:48:11	67708715	136540800	2133450	2	2133450	index:0,count:2133450,average:32,stdev:0|index:1,count:2133450,average:32,stdev:0	GSM1937807_r1						1.95	2.08	0.08	95667096	105693696	79188940	91433077	110.48	115.46	1659429	1524274	205.338	830.998	117	7835	68.02	82.22	2127792	1128787	2127792	1128787	60.56	62.91	2127792	1004991	2127792	863635	12725684	13.30	1.88	0	13.43	0	0.56	0	0.29	0	0.00	0	21.37	0	1659429	0	64	0	58.11	0	1.18	0	0.00	0	1.02	0	0.01	0	365.73	0	0.73	0	40057	0	2133450	0	286567	0	11903	0	6130	0	0	0	455988	0	21	0	0	0	181	0	22345	0	1405	0	23952	0	64.35	0	1372862	0	9703	20488	2.111511903535	2133450.0	1659429.0	40057.0	286567.0	11903.0	6130.0	0.0	455988.0	1372862.0	77.8	1.9	13.4	0.6	0.3	0.0	21.4	64.3	32	32	32.00	6	68270400	22.2	23.5	24.8	21.7	7.7	30.3	13.7	smartseq
806087	SRR2925998	SRP066154	SRS1161569	SRX1427337	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937808: CD8_89 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_87|cousin 2;;CD8_88|hours since division;;1.2667|sister;;CD8_90|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937808		GSM1937808	CD8_89 scRNA-seq	182747712	2855433	2015-12-22 15:48:11	90267619	182747712	2855433	2	2855433	index:0,count:2855433,average:32,stdev:0|index:1,count:2855433,average:32,stdev:0	GSM1937808_r1						2.06	2.1	0.08	129979394	147856259	105341564	126244599	113.75	119.84	2253094	2044081	204.816	929.796	100	10783	70.16	86.59	2981534	1580751	2981534	1580751	61.5	63.42	2981534	1385604	2981534	1157677	12634326	9.72	2.06	0	14.97	0	0.63	0	0.30	0	0.00	0	20.17	0	2253094	0	64	0	58.11	0	1.16	0	0.00	0	1.02	0	0.01	0	380.72	0	0.74	0	58756	0	2855433	0	427590	0	17862	0	8500	0	0	0	575977	0	30	0	0	0	237	0	34826	0	1906	0	36999	0	63.93	0	1825504	0	14898	32120	2.155994093167	2855433.0	2253094.0	58756.0	427590.0	17862.0	8500.0	0.0	575977.0	1825504.0	78.9	2.1	15.0	0.6	0.3	0.0	20.2	63.9	32	32	32.00	6	91373856	22.2	23.5	24.8	21.8	7.7	30.3	13.7	smartseq
806094	SRR2925999	SRP066154	SRS1161568	SRX1427338	SRA310903	GEO		A microfluidic platform enabling single cell RNA-seq of multigenerational lineages	We introduce a microfluidic platform that enables off-chip single-cell RNA-seq after multigenerationa lineage tracking under controlled culture conditions. Overall design: Examination of lineage and cell cycle dependent transcriptional profiles in two cell types		GSM1937809: CD8_90 scRNA-seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Single cells were flushed from the device with 5 ul of PBS directly in to 5 ul of 2X TCL lysis buffer (Qiagen) resulting in a total volume of 10 ul of single-cell lysate. These samples were immediately frozen on dry ice and subsequently stored at -80°C prior to library preperation and sequencing. Libraries were constructed using the Smart-Seq2 protocol for single cells.	NextSeq 500	cell type;;Activated CD8+ T cells|cousin 1;;CD8_87|cousin 2;;CD8_88|hours since division;;1.3167|sister;;CD8_89|source_name;;Single CD8+ cells grown for multiple generations on-chip after 30h activation in vitro with anti-CD3/28|strain;;C57BL/6J	GEO Accession;;GSM1937809		GSM1937809	CD8_90 scRNA-seq	151727104	2370736	2015-12-22 15:48:11	76007697	151727104	2370736	2	2370736	index:0,count:2370736,average:32,stdev:0|index:1,count:2370736,average:32,stdev:0	GSM1937809_r1						2.01	2.17	0.07	108406947	121992723	88630407	104524666	112.53	117.93	1879880	1698441	203.062	898.506	100	8956	73.01	89.31	2493081	1372464	2493081	1372464	66.44	68.27	2493081	1249080	2493081	1049143	8388682	7.74	1.90	0	14.47	0	0.66	0	0.29	0	0.00	0	19.75	0	1879880	0	64	0	58.10	0	1.29	0	0.01	0	1.01	0	0.01	0	341.39	0	0.74	0	45031	0	2370736	0	343057	0	15753	0	6860	0	0	0	468243	0	22	0	0	0	209	0	31111	0	1669	0	33011	0	64.82	0	1536823	0	11684	29150	2.494864772338	2370736.0	1879880.0	45031.0	343057.0	15753.0	6860.0	0.0	468243.0	1536823.0	79.3	1.9	14.5	0.7	0.3	0.0	19.8	64.8	32	32	32.00	6	75863552	22.2	23.5	24.8	21.8	7.7	30.1	13.7	smartseq
2786547	SRR2971427	SRP066961	SRS1188248	SRX1460802	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961584: mRNA_Hb9:gfp_WT_rep_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2000	background mutation;;wild type|cell type;;motoneurons|developmental stage;;E12.5|genetic reporter;;Hb9::gfp|sorted fraction;;GFP positive|source_name;;WT_motoneurons	GEO Accession;;GSM1961584		GSM1961584	mRNA_Hb9:gfp_WT_rep_1	6825811200	34129056	2015-12-18 16:31:10	4626011786	6825811200	34129056	2	34129056	index:0,count:34129056,average:100,stdev:0|index:1,count:34129056,average:100,stdev:0	GSM1961584_r1				in_mesa	26680198	1.58	3.79	0.06	5047125332	5022893472	4779940391	4780012694	99.52	100.0	33476830	31385663	171.337	650.776	135	385508	84.88	89.72	36508165	28415120	36508165	28415120	85.72	86.01	36508165	28694939	36508165	27237615	476713445	9.45	1.15	0	5.30	0	0.22	0	0.13	0	0.00	0	1.57	0	33476830	0	200	0	198.37	0	1.94	0	0.01	0	1.73	0	0.01	0	267.68	0	0.29	0	392430	0	34129056	0	1807226	0	73453	0	42813	0	0	0	535960	0	10512	0	0	0	94953	0	13723297	0	31561	0	13860323	0	92.79	0	31669604	0	216989	11512386	53.055159478130	34129056.0	33476830.0	392430.0	1807226.0	73453.0	42813.0	0.0	535960.0	31669604.0	98.1	1.1	5.3	0.2	0.1	0.0	1.6	92.8	100	100	100.00	38	3412905600	25.1	24.9	24.9	25.2	0.0	35.6	21.3	bulk
2786579	SRR2971428	SRP066961	SRS1188247	SRX1460803	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961586: mRNA_Hb9:gfp_WT_rep_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;wild type|cell type;;motoneurons|developmental stage;;E12.5|genetic reporter;;Hb9::gfp|sorted fraction;;GFP positive|source_name;;WT_motoneurons	GEO Accession;;GSM1961586		GSM1961586	mRNA_Hb9:gfp_WT_rep_2	1779260868	34887468	2015-12-18 16:31:10	844628724	1779260868	34887468	1	34887468	index:0,count:34887468,average:51,stdev:0	GSM1961586_r1				in_mesa	26680198	2.07	3.77	0.03	1707243786	1691937903	1520108618	1523413165	99.1	100.22	0	0	0	0	0	0	81.65	91.67	42196540	27558652	42196540	27558652	87.09	88.0	42196540	29393396	42196540	26457474	118647561	6.95	0.47	0	10.57	0	0.49	0	0.32	0	0.00	0	2.45	0	33751258	0	51	0	50.56	0	1.43	0	0.00	0	1.26	0	0.00	0	609.68	0	0.30	0	165150	0	34887468	0	3686825	0	170938	0	110207	0	0	0	855065	0	1990	0	0	0	17663	0	2512821	0	5225	0	2537699	0	86.18	0	30064433	0	151598	2710862	17.881911370862	34887468.0	33751258.0	165150.0	3686825.0	170938.0	110207.0	0.0	855065.0	30064433.0	96.7	0.5	10.6	0.5	0.3	0.0	2.5	86.2	51	51	51.00	8	1779260868	24.6	25.2	25.3	24.8	0.1	36.1	18.0	bulk
2786610	SRR2971429	SRP066961	SRS1188246	SRX1460804	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961587: mRNA_Hb9:gfp_WT_rep_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;wild type|cell type;;motoneurons|developmental stage;;E12.5|genetic reporter;;Hb9::gfp|sorted fraction;;GFP positive|source_name;;WT_motoneurons	GEO Accession;;GSM1961587		GSM1961587	mRNA_Hb9:gfp_WT_rep_3	1557075900	30530900	2015-12-18 16:31:10	735143836	1557075900	30530900	1	30530900	index:0,count:30530900,average:51,stdev:0	GSM1961587_r1				in_mesa	26680198	2.09	3.65	0.05	1486525096	1473451528	1326291087	1329009700	99.12	100.2	0	0	0	0	0	0	80.13	89.78	36570333	23557648	36570333	23557648	85.45	86.2	36570333	25121686	36570333	22617861	130219196	8.76	0.55	0	10.34	0	0.50	0	0.31	0	0.00	0	2.90	0	29397790	0	51	0	50.55	0	1.50	0	0.00	0	1.26	0	0.00	0	642.76	0	0.31	0	169394	0	30530900	0	3158140	0	153652	0	94413	0	0	0	885045	0	1756	0	0	0	15210	0	2155571	0	4529	0	2177066	0	85.94	0	26239650	0	146904	2322486	15.809549093285	30530900.0	29397790.0	169394.0	3158140.0	153652.0	94413.0	0.0	885045.0	26239650.0	96.3	0.6	10.3	0.5	0.3	0.0	2.9	85.9	51	51	51.00	8	1557075900	24.7	25.1	25.3	24.9	0.1	36.1	17.9	bulk
2786834	SRR2971430	SRP066961	SRS1188245	SRX1460805	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961589: mRNA_Hb9:gfp_WT_rep_4; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2000	background mutation;;wild type|cell type;;motoneurons|developmental stage;;E12.5|genetic reporter;;Hb9::gfp|sorted fraction;;GFP positive|source_name;;WT_motoneurons	GEO Accession;;GSM1961589		GSM1961589	mRNA_Hb9:gfp_WT_rep_4	4693044588	23232894	2015-12-18 16:31:10	2990100728	4693044588	23232894	2	23232894	index:0,count:23232894,average:101,stdev:0|index:1,count:23232894,average:101,stdev:0	GSM1961589_r1				in_mesa	26680198	3.03	3.94	0.03	3454448515	3434424202	3229164299	3229639890	99.42	100.01	22470948	21134910	169.907	615.851	146	301436	87.77	93.96	24856596	19722827	24856596	19722827	89.8	90.31	24856596	20178679	24856596	18956727	168617971	4.88	0.44	0	6.37	0	0.20	0	0.10	0	0.00	0	2.99	0	22470948	0	202	0	200.08	0	1.97	0	0.01	0	1.50	0	0.01	0	279.73	0	0.40	0	101895	0	23232894	0	1479884	0	45311	0	22354	0	0	0	694281	0	7686	0	0	0	66814	0	9758912	0	15934	0	9849346	0	90.35	0	20991064	0	178263	8312431	46.630153200608	23232894.0	22470948.0	101895.0	1479884.0	45311.0	22354.0	0.0	694281.0	20991064.0	96.7	0.4	6.4	0.2	0.1	0.0	3.0	90.4	101	101	101.00	38	2346522294	26.1	23.9	23.8	26.3	0.0	35.1	16.3	bulk
2786866	SRR2971431	SRP066961	SRS1188244	SRX1460806	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961591: mRNA_Hb9:gfp_WT_rep_5; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2000	background mutation;;wild type|cell type;;motoneurons|developmental stage;;E12.5|genetic reporter;;Hb9::gfp|sorted fraction;;GFP positive|source_name;;WT_motoneurons	GEO Accession;;GSM1961591		GSM1961591	mRNA_Hb9:gfp_WT_rep_5	2759926606	13663003	2015-12-18 16:31:10	1796249987	2759926606	13663003	2	13663003	index:0,count:13663003,average:101,stdev:0|index:1,count:13663003,average:101,stdev:0	GSM1961591_r1				in_mesa	26680198	1.78	3.51	0.03	2135971329	2144480119	2006618197	2023984603	100.4	100.87	13050684	12136513	188.741	727.955	146	132180	89.68	95.54	14373126	11703863	14373126	11703863	90.63	91.11	14373126	11827808	14373126	11161193	72743361	3.41	0.38	0	5.86	0	0.20	0	0.07	0	0.00	0	4.21	0	13050684	0	202	0	199.77	0	2.21	0	0.01	0	1.58	0	0.01	0	190.65	0	0.48	0	52056	0	13663003	0	800605	0	27413	0	9653	0	0	0	575253	0	4633	0	0	0	43596	0	6091634	0	9950	0	6149813	0	89.66	0	12250079	0	161213	5504952	34.147072506560	13663003.0	13050684.0	52056.0	800605.0	27413.0	9653.0	0.0	575253.0	12250079.0	95.5	0.4	5.9	0.2	0.1	0.0	4.2	89.7	101	101	101.00	38	1379963303	24.5	25.6	25.5	24.5	0.0	34.1	15.1	bulk
2786897	SRR2971432	SRP066961	SRS1188243	SRX1460807	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961593: mRNA_Hb9:gfp_WT_rep_6; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2000	background mutation;;wild type|cell type;;motoneurons|developmental stage;;E12.5|genetic reporter;;Hb9::gfp|sorted fraction;;GFP positive|source_name;;WT_motoneurons	GEO Accession;;GSM1961593		GSM1961593	mRNA_Hb9:gfp_WT_rep_6	3490927842	17281821	2015-12-18 16:31:10	2264079795	3490927842	17281821	2	17281821	index:0,count:17281821,average:101,stdev:0|index:1,count:17281821,average:101,stdev:0	GSM1961593_r1				in_mesa	26680198	1.81	3.67	0.02	2609419490	2617366933	2446310114	2465838974	100.3	100.8	16471819	15366598	179.696	698.876	146	184224	89.94	96.01	18203480	14814458	18203480	14814458	91.22	91.72	18203480	15024926	18203480	14153341	80542300	3.09	0.47	0	6.03	0	0.21	0	0.07	0	0.00	0	4.41	0	16471819	0	202	0	199.68	0	2.04	0	0.01	0	1.56	0	0.01	0	209.48	0	0.47	0	80842	0	17281821	0	1041328	0	35858	0	12303	0	0	0	761841	0	6160	0	0	0	53627	0	7799235	0	13142	0	7872164	0	89.29	0	15430491	0	168747	6838638	40.525982684137	17281821.0	16471819.0	80842.0	1041328.0	35858.0	12303.0	0.0	761841.0	15430491.0	95.3	0.5	6.0	0.2	0.1	0.0	4.4	89.3	101	101	101.00	38	1745463921	24.6	25.3	25.3	24.7	0.0	34.2	15.1	bulk
2786930	SRR2971433	SRP066961	SRS1188242	SRX1460808	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961595: mRNA_Floor_Plate_rep_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2000	background mutation;;wild type|cell type;;floor plate glial cells|developmental stage;;E12.5|genetic reporter;;none|sorted fraction;;unsorted|source_name;;WT_floor_plate_cells	GEO Accession;;GSM1961595		GSM1961595	mRNA_Floor_Plate_rep_1	6381127600	31905638	2015-12-18 16:31:10	4328161667	6381127600	31905638	2	31905638	index:0,count:31905638,average:100,stdev:0|index:1,count:31905638,average:100,stdev:0	GSM1961595_r1				in_mesa	26680198	3.7	3.39	0.05	4867033936	4854215707	4557284878	4566561380	99.74	100.2	31425407	29475655	176.103	592.705	145	354642	86.91	92.94	34673379	27312640	34673379	27312640	88.81	89.1	34673379	27908109	34673379	26184260	301051146	6.19	0.96	0	6.38	0	0.22	0	0.09	0	0.00	0	1.19	0	31425407	0	200	0	198.41	0	1.91	0	0.01	0	1.64	0	0.01	0	298.34	0	0.29	0	304953	0	31905638	0	2036897	0	71583	0	29697	0	0	0	378951	0	10217	0	0	0	87505	0	14071628	0	28039	0	14197389	0	92.11	0	29388510	0	224395	12299054	54.809839791439	31905638.0	31425407.0	304953.0	2036897.0	71583.0	29697.0	0.0	378951.0	29388510.0	98.5	1.0	6.4	0.2	0.1	0.0	1.2	92.1	100	100	100.00	38	3190563800	25.3	24.7	24.7	25.4	0.0	35.7	21.5	bulk
2786961	SRR2971434	SRP066961	SRS1188241	SRX1460809	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961596: mRNA_Hb9:gfp_218DKO_rep_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;218DKO|cell type;;motoneurons|developmental stage;;E12.5|genetic reporter;;Hb9::gfp|sorted fraction;;GFP positive|source_name;;218DKO_motoneurons	GEO Accession;;GSM1961596		GSM1961596	mRNA_Hb9:gfp_218DKO_rep_1	528067158	10354258	2015-12-18 16:31:10	266656462	528067158	10354258	1	10354258	index:0,count:10354258,average:51,stdev:0	GSM1961596_r1				in_mesa	26680198	1.9	4.08	0.04	466978083	460902455	420132333	419169555	98.7	99.77	0	0	0	0	0	0	79.01	87.79	11266678	7290023	11266678	7290023	83.74	84.36	11266678	7726615	11266678	7004949	48074363	10.29	0.83	0	8.91	0	0.47	0	0.30	0	0.00	0	10.13	0	9226365	0	51	0	50.60	0	1.44	0	0.00	0	1.26	0	0.00	0	438.53	0	0.28	0	86323	0	10354258	0	922808	0	48220	0	31200	0	0	0	1048473	0	561	0	0	0	4547	0	647260	0	1510	0	653878	0	80.19	0	8303557	0	107263	694985	6.479261255046	10354258.0	9226365.0	86323.0	922808.0	48220.0	31200.0	0.0	1048473.0	8303557.0	89.1	0.8	8.9	0.5	0.3	0.0	10.1	80.2	51	51	51.00	6	528067158	27.5	24.4	22.9	25.2	0.0	31.4	16.5	bulk
2786993	SRR2971435	SRP066961	SRS1188240	SRX1460810	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961598: mRNA_Hb9:gfp_218DKO_rep_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;218DKO|cell type;;motoneurons|developmental stage;;E12.5|genetic reporter;;Hb9::gfp|sorted fraction;;GFP positive|source_name;;218DKO_motoneurons	GEO Accession;;GSM1961598		GSM1961598	mRNA_Hb9:gfp_218DKO_rep_2	987712920	19366920	2015-12-18 16:31:10	359547725	987712920	19366920	1	19366920	index:0,count:19366920,average:51,stdev:0	GSM1961598_r1				in_mesa	26680198	2.0	4.03	0.08	960606407	946752145	863986838	861286922	98.56	99.69	0	0	0	0	0	0	78.96	87.76	23186490	14985915	23186490	14985915	83.72	84.4	23186490	15889167	23186490	14412717	98977603	10.30	0.34	0	9.83	0	0.53	0	0.40	0	0.00	0	1.07	0	18979559	0	51	0	50.60	0	1.43	0	0.01	0	1.27	0	0.00	0	749.69	0	0.16	0	64963	0	19366920	0	1903561	0	102641	0	78365	0	0	0	206355	0	1068	0	0	0	9267	0	1293388	0	3298	0	1307021	0	88.17	0	17075998	0	126634	1390700	10.982042737338	19366920.0	18979559.0	64963.0	1903561.0	102641.0	78365.0	0.0	206355.0	17075998.0	98.0	0.3	9.8	0.5	0.4	0.0	1.1	88.2	51	51	51.00	6	987712920	25.4	24.6	24.0	25.9	0.0	35.9	23.6	bulk
2787026	SRR2971436	SRP066961	SRS1188239	SRX1460811	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961600: mRNA_Sim1_V3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;wild type|cell type;;V3 spinal interneurons|developmental stage;;E12.5|genetic reporter;;Sim1:cre;Rosa26:LSL:tdTomato|sorted fraction;;tdTomato positive|source_name;;V3_interneurons	GEO Accession;;GSM1961600		GSM1961600	mRNA_Sim1_V3	1076851791	21114741	2015-12-18 16:31:10	371327110	1076851791	21114741	1	21114741	index:0,count:21114741,average:51,stdev:0	GSM1961600_r1				in_mesa	26680198	2.03	3.65	0.07	1054002342	1041942471	952916868	950893247	98.86	99.79	0	0	0	0	0	0	77.43	85.61	25221532	16095846	25221532	16095846	81.81	82.23	25221532	17007424	25221532	15459564	131519376	12.48	0.16	0	9.42	0	0.53	0	0.41	0	0.00	0	0.60	0	20788490	0	51	0	50.69	0	1.42	0	0.00	0	1.22	0	0.00	0	691.03	0	0.18	0	34771	0	21114741	0	1988212	0	112158	0	86909	0	0	0	127184	0	1136	0	0	0	9948	0	1396050	0	2887	0	1410021	0	89.04	0	18800278	0	133206	1499408	11.256309775836	21114741.0	20788490.0	34771.0	1988212.0	112158.0	86909.0	0.0	127184.0	18800278.0	98.5	0.2	9.4	0.5	0.4	0.0	0.6	89.0	51	51	51.00	6	1076851791	25.0	25.2	24.4	25.5	0.0	36.1	26.1	bulk
2787057	SRR2971437	SRP066961	SRS1188238	SRX1460812	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961602: mRNA_Chx10_V2a; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;wild type|cell type;;V2a spinal interneurons|developmental stage;;E12.5|genetic reporter;;Chx10:cre;Rosa26:LSL:tdTomato|sorted fraction;;tdTomato positive|source_name;;V2a_interneurons	GEO Accession;;GSM1961602		GSM1961602	mRNA_Chx10_V2a	1140142383	22355733	2015-12-18 16:31:10	395354622	1140142383	22355733	1	22355733	index:0,count:22355733,average:51,stdev:0	GSM1961602_r1				in_mesa	26680198	2.23	3.73	0.05	1115758354	1101817432	1006254136	1003274810	98.75	99.7	0	0	0	0	0	0	77.48	85.88	26716510	17053106	26716510	17053106	82.13	82.54	26716510	18077874	26716510	16388733	135561292	12.15	0.18	0	9.64	0	0.54	0	0.39	0	0.00	0	0.62	0	22010343	0	51	0	50.68	0	1.39	0	0.00	0	1.19	0	0.00	0	659.68	0	0.18	0	39554	0	22355733	0	2154092	0	120498	0	86199	0	0	0	138693	0	1123	0	0	0	10658	0	1484652	0	3052	0	1499485	0	88.82	0	19856251	0	134379	1595742	11.874935815864	22355733.0	22010343.0	39554.0	2154092.0	120498.0	86199.0	0.0	138693.0	19856251.0	98.5	0.2	9.6	0.5	0.4	0.0	0.6	88.8	51	51	51.00	6	1140142383	25.1	25.1	24.2	25.6	0.0	36.1	25.6	bulk
2787089	SRR2971438	SRP066961	SRS1188237	SRX1460813	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961604: mRNA_En1_V1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;wild type|cell type;;V1 spinal interneurons|developmental stage;;E12.5|genetic reporter;;En1:cre;Rosa26:LSL:tdTomato|sorted fraction;;tdTomato positive|source_name;;V1_interneurons	GEO Accession;;GSM1961604		GSM1961604	mRNA_En1_V1	1091268522	21397422	2015-12-18 16:31:10	377912928	1091268522	21397422	1	21397422	index:0,count:21397422,average:51,stdev:0	GSM1961604_r1				in_mesa	26680198	2.3	3.64	0.07	1067528625	1052303027	969593274	964800378	98.57	99.51	0	0	0	0	0	0	76.7	84.43	25150811	16152400	25150811	16152400	80.8	81.11	25150811	17015068	25150811	15516835	142915249	13.39	0.17	0	9.00	0	0.54	0	0.43	0	0.00	0	0.62	0	21057916	0	51	0	50.68	0	1.43	0	0.01	0	1.23	0	0.01	0	626.27	0	0.19	0	37167	0	21397422	0	1926808	0	115329	0	90946	0	0	0	133231	0	1130	0	0	0	9550	0	1362120	0	2952	0	1375752	0	89.41	0	19131108	0	134998	1457357	10.795396968844	21397422.0	21057916.0	37167.0	1926808.0	115329.0	90946.0	0.0	133231.0	19131108.0	98.4	0.2	9.0	0.5	0.4	0.0	0.6	89.4	51	51	51.00	6	1091268522	25.1	25.0	24.3	25.5	0.0	36.1	25.4	bulk
2787122	SRR2971439	SRP066961	SRS1188236	SRX1460814	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961606: mRNA_mES_pMN; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;wild type|cell type;;motoneuron progenitors|developmental stage;;d4_mES_differentiation|genetic reporter;;Olig2:cre;Rosa26:LSL:tdTomato|sorted fraction;;tdTomato positive|source_name;;Olig2_sorted_progenitors	GEO Accession;;GSM1961606		GSM1961606	mRNA_mES_pMN	1402913508	27508108	2015-12-18 16:31:10	509498352	1402913508	27508108	1	27508108	index:0,count:27508108,average:51,stdev:0	GSM1961606_r1				in_mesa	26680198	2.0	3.67	0.06	1346981056	1339751723	1088721507	1100912918	99.46	101.12	0	0	0	0	0	0	77.41	95.68	38493248	20624678	38493248	20624678	90.08	91.76	38493248	23998682	38493248	19779772	55486789	4.12	0.33	0	18.49	0	1.61	0	0.45	0	0.00	0	1.08	0	26642167	0	51	0	50.51	0	1.40	0	0.00	0	1.20	0	0.00	0	589.46	0	0.16	0	90923	0	27508108	0	5087099	0	443355	0	125074	0	0	0	297512	0	2446	0	0	0	15850	0	2282392	0	4970	0	2305658	0	78.36	0	21555068	0	143585	2560626	17.833520214507	27508108.0	26642167.0	90923.0	5087099.0	443355.0	125074.0	0.0	297512.0	21555068.0	96.9	0.3	18.5	1.6	0.5	0.0	1.1	78.4	51	51	51.00	6	1402913508	24.7	25.4	24.8	25.1	0.0	35.9	23.8	bulk
2787345	SRR2971440	SRP066961	SRS1188235	SRX1460815	SRA314788	GEO		Loss of motoneuron-specific microRNA-218 causes systemic neuromuscular failure [RNA-seq]	We investigated microRNA expression in motoneurons by performing small RNA sequencing of fluorescence-activated cell sorting (FACS)-isolated motoneurons labelled with the Hb9:gfp transgenic reporter and Hb9:gfp negative non-motoneurons including spinal interneurons.  We find that one microRNA, microRNA-218, is highly enriched and abundantly expressed in motoneurons.  Furthermore, we find that miR-218 is transcribed from alternative, motoneuron-specific alternative promoters embedded within the Slit2 and Slit3 genes by performing RNA sequencing of FACS-isolated motoneurons and a dissected embryonic floor plate cells which served as a control.  Next, we performed RNA sequencing of FACS-isolated wild type (WT) motoneurons and motoneurons lacking miR-218 expression (218DKO motoneurons), and find that a large set of genes (named ''TARGET218'' genes) with predicted miR-218 binding sites are de-repressed in the absence of miR-218 expression.  Finally, we examine the expression of TARGET218 genes in other neuronal subpopulations by FACS-isolating  V1, V2a, and V3 interneurons expressing Cre-inducible fluorescent reporters and performing RNA sequencing.  We find that the TARGET218 network of genes is depleted in wild-type motoneurons versus these interneuron types.  Additionally, these genes are expressed at similar levels in 218DKO motoneurons compared with interneuron subtypes, suggesting that this genetic network. Overall design: Examination of mRNA expression in spinal progenitor, glial, and neuronal subpopulations.		GSM1961608: mRNA_mES_NP; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	single			Isolated cells were collected directly into RNA lysis buffer (miRvana kit) and the total RNA isolation protocol was followed. mRNA sequencing libraries were prepared using the TruSeq RNA Library Preparation Kit (v2) according to the manufacturer’s instructions (Illumina). Briefly, RNA with polyA+ tails was selected using oligo-dT beads. mRNA was then fragmented and reverse-transcribed into cDNA. cDNA was end-repaired, index adapter-ligated and PCR amplified. AMPure XP beads (Beckman Coulter) were used to purify nucleic acids after each step.	Illumina HiSeq 2500	background mutation;;wild type|cell type;;spinal neuronal progenitors|developmental stage;;d4_mES_differentiation|genetic reporter;;none|sorted fraction;;unsorted|source_name;;Neural_progenitors	GEO Accession;;GSM1961608		GSM1961608	mRNA_mES_NP	1332892344	26135144	2015-12-18 16:31:10	487490786	1332892344	26135144	1	26135144	index:0,count:26135144,average:51,stdev:0	GSM1961608_r1				in_mesa	26680198	2.07	3.96	0.12	1284456701	1273230363	1060000074	1067560396	99.13	100.71	0	0	0	0	0	0	76.16	92.21	35425923	19332351	35425923	19332351	87.39	88.57	35425923	22183280	35425923	18569377	89199236	6.94	0.26	0	16.91	0	1.39	0	0.70	0	0.00	0	0.79	0	25383152	0	51	0	50.56	0	1.44	0	0.01	0	1.26	0	0.00	0	635.72	0	0.16	0	66663	0	26135144	0	4418390	0	364048	0	182703	0	0	0	205241	0	2066	0	0	0	15982	0	2091231	0	4386	0	2113665	0	80.22	0	20964762	0	148437	2334521	15.727352344766	26135144.0	25383152.0	66663.0	4418390.0	364048.0	182703.0	0.0	205241.0	20964762.0	97.1	0.3	16.9	1.4	0.7	0.0	0.8	80.2	51	51	51.00	6	1332892344	25.2	24.9	24.0	25.9	0.0	35.9	23.8	bulk
1644637	SRR3032185	SRP067565	SRS1212740	SRX1491265	SRA320716	GEO		Gene expression profiling of sensory epithelium of cochleas and vestibules of the inner ears of wild-type C57Bl/6J mice at post-natal day 0 (P0)	The sensory epithelium of cochleas and vestibules of mice were compared. The two tissues are quite similar in structure, but have distinct roles in hearing and balance. By comparing their gene expression, we hoped to identify key regulators of differentiation. Overall design: Cochlear and vestibular sensory epithelium was dissected from 20 inner ears of 10 P0 C57Bl/6J mice, generating 2.4 and 1.5 µg of total RNA, respectively. 450 ng RNA from each sample was used to create libraries with the TruSeq Stranded mRNA Sample Prep Kit (Illumina), followed by high-throughput sequencing at 100 bp paired end (PE) at the Technion Genome Center, Haifa, Israel. Six samples were generated, 3 cochlear and 3 vestibular, for sequencing in triplicate.		GSM1975057: WT_P0_Cochlea_SensoryEpithelium_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Sensory epithelia from 20 cochlea or 20 vestibule were removed and RNA was harvested using QIAgen’s RNeasy micro kit. Illumina TruSeq® Stranded mRNA Sample Preparation Kit (Cat# RS-122-2101) was used with 450 ng of total RNA for the construction of sequencing libraries.	Illumina HiSeq 2500	age;;newborns (P0)|Sex;;pooled male and female|source_name;;Mouse P0 cochlear sensory epithelium|strain;;C57BL/6J|tissue;;cochlear sensory epithelium	GEO Accession;;GSM1975057		GSM1975057	WT_P0_Cochlea_SensoryEpithelium_1	5964299066	29526233	2017-04-13 14:09:16	2700402981	5964299066	29526233	2	29526233	index:0,count:29526233,average:101,stdev:0|index:1,count:29526233,average:101,stdev:0	GSM1975057_r1						6.91	3.18	0.02	4570804556	4527780048	4059779094	4045575753	99.06	99.65	28499220	26344235	191.891	661.729	139	225958	83.87	94.75	33530000	23903516	33530000	23903516	90.26	90.82	33530000	25722635	33530000	22912745	152432184	3.33	0.78	0	11.08	0	0.19	0	0.04	0	0.00	0	3.25	0	28499220	0	202	0	200.00	0	1.92	0	0.01	0	2.03	0	0.01	0	278.99	0	0.26	0	229802	0	29526233	0	3271464	0	56887	0	10689	0	0	0	959437	0	8999	0	0	0	90906	0	12877612	0	20625	0	12998142	0	85.44	0	25227756	0	208864	11680700	55.924908074154	29526233.0	28499220.0	229802.0	3271464.0	56887.0	10689.0	0.0	959437.0	25227756.0	96.5	0.8	11.1	0.2	0.0	0.0	3.2	85.4	101	101	101.00	8	2982149533	24.1	24.8	25.1	26.0	0.0	35.8	25.2	bulk
1644654	SRR3032186	SRP067565	SRS1212741	SRX1491266	SRA320716	GEO		Gene expression profiling of sensory epithelium of cochleas and vestibules of the inner ears of wild-type C57Bl/6J mice at post-natal day 0 (P0)	The sensory epithelium of cochleas and vestibules of mice were compared. The two tissues are quite similar in structure, but have distinct roles in hearing and balance. By comparing their gene expression, we hoped to identify key regulators of differentiation. Overall design: Cochlear and vestibular sensory epithelium was dissected from 20 inner ears of 10 P0 C57Bl/6J mice, generating 2.4 and 1.5 µg of total RNA, respectively. 450 ng RNA from each sample was used to create libraries with the TruSeq Stranded mRNA Sample Prep Kit (Illumina), followed by high-throughput sequencing at 100 bp paired end (PE) at the Technion Genome Center, Haifa, Israel. Six samples were generated, 3 cochlear and 3 vestibular, for sequencing in triplicate.		GSM1975058: WT_P0_Cochlea_SensoryEpithelium_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Sensory epithelia from 20 cochlea or 20 vestibule were removed and RNA was harvested using QIAgen’s RNeasy micro kit. Illumina TruSeq® Stranded mRNA Sample Preparation Kit (Cat# RS-122-2101) was used with 450 ng of total RNA for the construction of sequencing libraries.	Illumina HiSeq 2500	age;;newborns (P0)|Sex;;pooled male and female|source_name;;Mouse P0 cochlear sensory epithelium|strain;;C57BL/6J|tissue;;cochlear sensory epithelium	GEO Accession;;GSM1975058		GSM1975058	WT_P0_Cochlea_SensoryEpithelium_2	7106887624	35182612	2017-04-13 14:09:16	3237020147	7106887624	35182612	2	35182612	index:0,count:35182612,average:101,stdev:0|index:1,count:35182612,average:101,stdev:0	GSM1975058_r1						5.4	3.12	0.02	5461454836	5400504155	4881181788	4855202600	98.88	99.47	33870607	31297290	193.008	672.338	148	269677	83.45	93.68	39751625	28265996	39751625	28265996	88.73	89.36	39751625	30052122	39751625	26962934	211765518	3.88	0.69	0	10.51	0	0.25	0	0.04	0	0.00	0	3.44	0	33870607	0	202	0	199.89	0	2.29	0	0.01	0	2.22	0	0.01	0	249.33	0	0.29	0	241389	0	35182612	0	3698402	0	87734	0	13455	0	0	0	1210816	0	9833	0	0	0	113117	0	15898576	0	24003	0	16045529	0	85.76	0	30172205	0	227152	14421487	63.488267767838	35182612.0	33870607.0	241389.0	3698402.0	87734.0	13455.0	0.0	1210816.0	30172205.0	96.3	0.7	10.5	0.2	0.0	0.0	3.4	85.8	101	101	101.00	8	3553443812	23.6	25.4	25.3	25.7	0.0	35.7	25.0	bulk
1644669	SRR3032187	SRP067565	SRS1212739	SRX1491267	SRA320716	GEO		Gene expression profiling of sensory epithelium of cochleas and vestibules of the inner ears of wild-type C57Bl/6J mice at post-natal day 0 (P0)	The sensory epithelium of cochleas and vestibules of mice were compared. The two tissues are quite similar in structure, but have distinct roles in hearing and balance. By comparing their gene expression, we hoped to identify key regulators of differentiation. Overall design: Cochlear and vestibular sensory epithelium was dissected from 20 inner ears of 10 P0 C57Bl/6J mice, generating 2.4 and 1.5 µg of total RNA, respectively. 450 ng RNA from each sample was used to create libraries with the TruSeq Stranded mRNA Sample Prep Kit (Illumina), followed by high-throughput sequencing at 100 bp paired end (PE) at the Technion Genome Center, Haifa, Israel. Six samples were generated, 3 cochlear and 3 vestibular, for sequencing in triplicate.		GSM1975059: WT_P0_Cochlea_SensoryEpithelium_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Sensory epithelia from 20 cochlea or 20 vestibule were removed and RNA was harvested using QIAgen’s RNeasy micro kit. Illumina TruSeq® Stranded mRNA Sample Preparation Kit (Cat# RS-122-2101) was used with 450 ng of total RNA for the construction of sequencing libraries.	Illumina HiSeq 2500	age;;newborns (P0)|Sex;;pooled male and female|source_name;;Mouse P0 cochlear sensory epithelium|strain;;C57BL/6J|tissue;;cochlear sensory epithelium	GEO Accession;;GSM1975059		GSM1975059	WT_P0_Cochlea_SensoryEpithelium_3	7334701002	36310401	2017-04-13 14:09:16	3328273344	7334701002	36310401	2	36310401	index:0,count:36310401,average:101,stdev:0|index:1,count:36310401,average:101,stdev:0	GSM1975059_r1						4.77	3.03	0.02	5608533389	5549849433	5128743648	5101114652	98.95	99.46	35060512	32547814	189.614	635.857	142	292260	83.45	91.52	39927002	29258247	39927002	29258247	86.97	87.43	39927002	30492340	39927002	27952182	347614354	6.20	0.73	0	8.51	0	0.20	0	0.05	0	0.00	0	3.19	0	35060512	0	202	0	200.04	0	2.14	0	0.01	0	2.06	0	0.01	0	312.72	0	0.27	0	264705	0	36310401	0	3089787	0	70974	0	19166	0	0	0	1159749	0	10276	0	0	0	108697	0	16152679	0	24883	0	16296535	0	88.05	0	31970725	0	229084	14409650	62.901162892214	36310401.0	35060512.0	264705.0	3089787.0	70974.0	19166.0	0.0	1159749.0	31970725.0	96.6	0.7	8.5	0.2	0.1	0.0	3.2	88.0	101	101	101.00	8	3667350501	23.9	25.2	25.3	25.5	0.0	35.8	25.1	bulk
1644685	SRR3032188	SRP067565	SRS1212738	SRX1491268	SRA320716	GEO		Gene expression profiling of sensory epithelium of cochleas and vestibules of the inner ears of wild-type C57Bl/6J mice at post-natal day 0 (P0)	The sensory epithelium of cochleas and vestibules of mice were compared. The two tissues are quite similar in structure, but have distinct roles in hearing and balance. By comparing their gene expression, we hoped to identify key regulators of differentiation. Overall design: Cochlear and vestibular sensory epithelium was dissected from 20 inner ears of 10 P0 C57Bl/6J mice, generating 2.4 and 1.5 µg of total RNA, respectively. 450 ng RNA from each sample was used to create libraries with the TruSeq Stranded mRNA Sample Prep Kit (Illumina), followed by high-throughput sequencing at 100 bp paired end (PE) at the Technion Genome Center, Haifa, Israel. Six samples were generated, 3 cochlear and 3 vestibular, for sequencing in triplicate.		GSM1975060: WT_P0_Vestibule_SensoryEpithelium_1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Sensory epithelia from 20 cochlea or 20 vestibule were removed and RNA was harvested using QIAgen’s RNeasy micro kit. Illumina TruSeq® Stranded mRNA Sample Preparation Kit (Cat# RS-122-2101) was used with 450 ng of total RNA for the construction of sequencing libraries.	Illumina HiSeq 2500	age;;newborns (P0)|Sex;;pooled male and female|source_name;;Mouse P0 vestibular sensory epithelium|strain;;C57BL/6J|tissue;;vestibular sensory epithelium	GEO Accession;;GSM1975060		GSM1975060	WT_P0_Vestibule_SensoryEpithelium_1	8310345650	41140325	2017-04-13 14:09:16	3765118951	8310345650	41140325	2	41140325	index:0,count:41140325,average:101,stdev:0|index:1,count:41140325,average:101,stdev:0	GSM1975060_r1						2.99	3.06	0.03	6363688581	6307329540	5946290450	5920375931	99.11	99.56	39763374	36607603	191.020	679.810	142	326394	86.59	92.86	44119846	34429241	44119846	34429241	88.66	89.18	44119846	35253611	44119846	33063934	342845331	5.39	0.78	0	6.53	0	0.20	0	0.06	0	0.00	0	3.09	0	39763374	0	202	0	200.03	0	1.80	0	0.01	0	1.86	0	0.01	0	248.08	0	0.24	0	320079	0	41140325	0	2687674	0	82359	0	24307	0	0	0	1270285	0	13628	0	0	0	135857	0	20241399	0	28708	0	20419592	0	90.12	0	37075700	0	261082	17935808	68.697987605427	41140325.0	39763374.0	320079.0	2687674.0	82359.0	24307.0	0.0	1270285.0	37075700.0	96.7	0.8	6.5	0.2	0.1	0.0	3.1	90.1	101	101	101.00	8	4155172825	23.8	25.4	25.2	25.5	0.0	35.8	25.2	bulk
1644702	SRR3032189	SRP067565	SRS1212737	SRX1491269	SRA320716	GEO		Gene expression profiling of sensory epithelium of cochleas and vestibules of the inner ears of wild-type C57Bl/6J mice at post-natal day 0 (P0)	The sensory epithelium of cochleas and vestibules of mice were compared. The two tissues are quite similar in structure, but have distinct roles in hearing and balance. By comparing their gene expression, we hoped to identify key regulators of differentiation. Overall design: Cochlear and vestibular sensory epithelium was dissected from 20 inner ears of 10 P0 C57Bl/6J mice, generating 2.4 and 1.5 µg of total RNA, respectively. 450 ng RNA from each sample was used to create libraries with the TruSeq Stranded mRNA Sample Prep Kit (Illumina), followed by high-throughput sequencing at 100 bp paired end (PE) at the Technion Genome Center, Haifa, Israel. Six samples were generated, 3 cochlear and 3 vestibular, for sequencing in triplicate.		GSM1975061: WT_P0_Vestibule_SensoryEpithelium_2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Sensory epithelia from 20 cochlea or 20 vestibule were removed and RNA was harvested using QIAgen’s RNeasy micro kit. Illumina TruSeq® Stranded mRNA Sample Preparation Kit (Cat# RS-122-2101) was used with 450 ng of total RNA for the construction of sequencing libraries.	Illumina HiSeq 2500	age;;newborns (P0)|Sex;;pooled male and female|source_name;;Mouse P0 vestibular sensory epithelium|strain;;C57BL/6J|tissue;;vestibular sensory epithelium	GEO Accession;;GSM1975061		GSM1975061	WT_P0_Vestibule_SensoryEpithelium_2	6436964926	31866163	2017-04-13 14:09:16	2922014709	6436964926	31866163	2	31866163	index:0,count:31866163,average:101,stdev:0|index:1,count:31866163,average:101,stdev:0	GSM1975061_r1						5.15	2.98	0.03	4951994132	4891555000	4531646741	4501176293	98.78	99.33	30693186	28549378	191.651	607.423	148	250737	84.05	92.09	34874313	25798757	34874313	25798757	87.68	88.17	34874313	26910995	34874313	24701849	282036831	5.70	0.77	0	8.40	0	0.21	0	0.05	0	0.00	0	3.42	0	30693186	0	202	0	200.01	0	1.92	0	0.01	0	2.02	0	0.01	0	261.91	0	0.26	0	246615	0	31866163	0	2677067	0	66194	0	15501	0	0	0	1091282	0	9800	0	0	0	92160	0	13656731	0	20483	0	13779174	0	87.92	0	28016119	0	228641	12302577	53.807396748615	31866163.0	30693186.0	246615.0	2677067.0	66194.0	15501.0	0.0	1091282.0	28016119.0	96.3	0.8	8.4	0.2	0.0	0.0	3.4	87.9	101	101	101.00	8	3218482463	24.2	25.0	25.2	25.6	0.0	35.8	25.0	bulk
1644814	SRR3032190	SRP067565	SRS1212736	SRX1491270	SRA320716	GEO		Gene expression profiling of sensory epithelium of cochleas and vestibules of the inner ears of wild-type C57Bl/6J mice at post-natal day 0 (P0)	The sensory epithelium of cochleas and vestibules of mice were compared. The two tissues are quite similar in structure, but have distinct roles in hearing and balance. By comparing their gene expression, we hoped to identify key regulators of differentiation. Overall design: Cochlear and vestibular sensory epithelium was dissected from 20 inner ears of 10 P0 C57Bl/6J mice, generating 2.4 and 1.5 µg of total RNA, respectively. 450 ng RNA from each sample was used to create libraries with the TruSeq Stranded mRNA Sample Prep Kit (Illumina), followed by high-throughput sequencing at 100 bp paired end (PE) at the Technion Genome Center, Haifa, Israel. Six samples were generated, 3 cochlear and 3 vestibular, for sequencing in triplicate.		GSM1975062: WT_P0_Vestibule_SensoryEpithelium_3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Sensory epithelia from 20 cochlea or 20 vestibule were removed and RNA was harvested using QIAgen’s RNeasy micro kit. Illumina TruSeq® Stranded mRNA Sample Preparation Kit (Cat# RS-122-2101) was used with 450 ng of total RNA for the construction of sequencing libraries.	Illumina HiSeq 2500	age;;newborns (P0)|Sex;;pooled male and female|source_name;;Mouse P0 vestibular sensory epithelium|strain;;C57BL/6J|tissue;;vestibular sensory epithelium	GEO Accession;;GSM1975062		GSM1975062	WT_P0_Vestibule_SensoryEpithelium_3	6354499032	31457916	2017-04-13 14:09:16	2887062286	6354499032	31457916	2	31457916	index:0,count:31457916,average:101,stdev:0|index:1,count:31457916,average:101,stdev:0	GSM1975062_r1						5.54	3.01	0.03	4826304387	4769973620	4367499433	4342891230	98.83	99.44	30227638	27954022	190.412	651.786	134	243319	83.8	92.88	34857170	25330331	34857170	25330331	88.08	88.69	34857170	26623489	34857170	24189190	228850123	4.74	0.81	0	9.39	0	0.22	0	0.04	0	0.00	0	3.65	0	30227638	0	202	0	199.90	0	2.15	0	0.01	0	2.14	0	0.01	0	267.10	0	0.28	0	255205	0	31457916	0	2955258	0	68869	0	11973	0	0	0	1149436	0	10056	0	0	0	93703	0	13984324	0	22846	0	14110929	0	86.69	0	27272380	0	224526	12509940	55.717110713236	31457916.0	30227638.0	255205.0	2955258.0	68869.0	11973.0	0.0	1149436.0	27272380.0	96.1	0.8	9.4	0.2	0.0	0.0	3.7	86.7	101	101	101.00	8	3177249516	24.0	25.1	25.2	25.6	0.0	35.8	25.0	bulk
1511535	SRR3175106	SRP070433	SRS1305170	SRX1589664	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064357: Wildtype from Notch line; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Wild-type|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064357		GSM2064357	Wildtype from Notch line	2689425000	17929500	2016-02-29 16:27:16	1627136343	2689425000	17929500	2	17929500	index:0,count:17929500,average:75,stdev:0|index:1,count:17929500,average:75,stdev:0	GSM2064357_r1				in_mesa	26940862	36.74	1.97	0.06	1961243068	1955770239	1858073370	1866220873	99.72	100.44	13964283	12876224	282.043	1069.620	281	52621	74.98	79.36	15244206	10470860	15244206	10470860	74.9	75.47	15244206	10458664	15244206	9956954	368343405	18.78	15.58	0	4.30	0	0.13	0	0.13	0	0.00	0	21.85	0	13964283	0	150	0	145.86	0	2.21	0	0.01	0	2.61	0	0.02	0	290.75	0	0.43	0	2793750	0	17929500	0	770309	0	23492	0	24038	0	0	0	3917687	0	987	0	0	0	8514	0	1187394	0	11825	0	1208720	0	73.59	0	13193974	0	116795	1220317	10.448366796524	17929500.0	13964283.0	2793750.0	770309.0	23492.0	24038.0	0.0	3917687.0	13193974.0	77.9	15.6	4.3	0.1	0.1	0.0	21.9	73.6	75	75	75.00	38	1344712500	28.3	21.1	21.7	29.0	0.0	37.5	20.5	bulk
1511550	SRR3175107	SRP070433	SRS1305169	SRX1589665	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064358: Wildtype from Preselin Line; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Wild-type|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064358		GSM2064358	Wildtype from Preselin Line	2913640350	19424269	2016-02-29 16:27:16	1733699125	2913640350	19424269	2	19424269	index:0,count:19424269,average:75,stdev:0|index:1,count:19424269,average:75,stdev:0	GSM2064358_r1				in_mesa	26940862	41.48	2.21	0.03	2116066085	2084663776	2032536561	2012205051	98.52	99.0	15053422	14111344	283.522	1014.347	281	58577	73.52	76.71	16098462	11066864	16098462	11066864	74.28	74.57	16098462	11180986	16098462	10757297	456407429	21.57	18.05	0	3.23	0	0.12	0	0.18	0	0.00	0	22.21	0	15053422	0	150	0	145.85	0	1.87	0	0.01	0	2.32	0	0.01	0	279.71	0	0.37	0	3506850	0	19424269	0	627332	0	22760	0	34887	0	0	0	4313200	0	892	0	0	0	7910	0	1042339	0	11446	0	1062587	0	74.27	0	14426090	0	109920	1068977	9.725045487627	19424269.0	15053422.0	3506850.0	627332.0	22760.0	34887.0	0.0	4313200.0	14426090.0	77.5	18.1	3.2	0.1	0.2	0.0	22.2	74.3	75	75	75.00	38	1456820175	29.1	20.2	20.7	30.0	0.0	37.5	20.2	bulk
1511567	SRR3175108	SRP070433	SRS1305168	SRX1589666	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064359: Wildtype from RBPjk line; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Wild-type|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064359		GSM2064359	Wildtype from RBPjk line	2948894550	19659297	2016-02-29 16:27:16	1801595005	2948894550	19659297	2	19659297	index:0,count:19659297,average:75,stdev:0|index:1,count:19659297,average:75,stdev:0	GSM2064359_r1				in_mesa	26940862	35.75	2.16	0.11	2102703115	2062944824	2010534693	1983639889	98.11	98.66	14992869	13956080	271.858	1086.778	258	58004	71.03	74.46	16195917	10649347	16195917	10649347	71.61	72.05	16195917	10736225	16195917	10305489	493554212	23.47	18.26	0	3.51	0	0.14	0	0.18	0	0.00	0	23.42	0	14992869	0	150	0	145.52	0	1.95	0	0.01	0	2.42	0	0.02	0	279.74	0	0.45	0	3589601	0	19659297	0	689848	0	26790	0	35267	0	0	0	4604371	0	1046	0	0	0	8949	0	1187163	0	13445	0	1210603	0	72.75	0	14303021	0	117319	1218275	10.384294104109	19659297.0	14992869.0	3589601.0	689848.0	26790.0	35267.0	0.0	4604371.0	14303021.0	76.3	18.3	3.5	0.1	0.2	0.0	23.4	72.8	75	75	75.00	38	1474447275	28.5	20.6	21.3	29.6	0.0	37.5	20.3	bulk
1511582	SRR3175109	SRP070433	SRS1305167	SRX1589667	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064360: Mixture of wildtypes from N, PS, and RBPj lines; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Wild-type|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064360		GSM2064360	Mixture of wildtypes from N, PS, and RBPj lines	2979038400	19860256	2016-02-29 16:27:16	1754023801	2979038400	19860256	2	19860256	index:0,count:19860256,average:75,stdev:0|index:1,count:19860256,average:75,stdev:0	GSM2064360_r1				in_mesa	26940862	37.45	2.02	0.06	2181593828	2161804216	2077579605	2071778228	99.09	99.72	15570801	14581073	263.018	953.482	258	64169	72.99	76.84	16891460	11365013	16891460	11365013	72.82	73.37	16891460	11338880	16891460	10851779	457591093	20.98	16.61	0	3.93	0	0.12	0	0.16	0	0.00	0	21.32	0	15570801	0	150	0	145.71	0	2.09	0	0.01	0	2.53	0	0.02	0	308.18	0	0.40	0	3299107	0	19860256	0	781063	0	24618	0	31398	0	0	0	4233439	0	1083	0	0	0	8825	0	1192106	0	13139	0	1215153	0	74.47	0	14789738	0	117117	1221924	10.433361510285	19860256.0	15570801.0	3299107.0	781063.0	24618.0	31398.0	0.0	4233439.0	14789738.0	78.4	16.6	3.9	0.1	0.2	0.0	21.3	74.5	75	75	75.00	38	1489519200	28.4	20.8	21.4	29.3	0.0	37.5	20.4	bulk
1511695	SRR3175110	SRP070433	SRS1305166	SRX1589668	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064361: Notch 1&2 null_sample1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Notch 1&2 deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064361		GSM2064361	Notch 1&2 null_sample1	3355069500	22367130	2016-02-29 16:27:16	2018363136	3355069500	22367130	2	22367130	index:0,count:22367130,average:75,stdev:0|index:1,count:22367130,average:75,stdev:0	GSM2064361_r1				in_mesa	26940862	36.71	1.82	0.05	2324075250	2348299124	2170604736	2218091822	101.04	102.19	17812424	17033882	204.366	677.860	134	84849	74.59	80.31	20024069	13286460	20024069	13286460	72.5	73.76	20024069	12913164	20024069	12202343	394448832	16.97	11.05	0	5.67	0	0.14	0	0.11	0	0.00	0	20.11	0	17812424	0	150	0	145.23	0	2.44	0	0.01	0	2.44	0	0.03	0	294.95	0	0.46	0	2471666	0	22367130	0	1269306	0	31834	0	24835	0	0	0	4498037	0	1116	0	0	0	9177	0	1272659	0	14696	0	1297648	0	73.96	0	16543118	0	120717	1256788	10.411027444353	22367130.0	17812424.0	2471666.0	1269306.0	31834.0	24835.0	0.0	4498037.0	16543118.0	79.6	11.1	5.7	0.1	0.1	0.0	20.1	74.0	75	75	75.00	38	1677534750	27.9	21.8	21.7	28.6	0.0	37.3	20.0	bulk
1511709	SRR3175111	SRP070433	SRS1305165	SRX1589669	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064362: Notch 1&2 null_sample2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Notch 1&2 deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064362		GSM2064362	Notch 1&2 null_sample2	5511001800	36740012	2016-02-29 16:27:16	3263316212	5511001800	36740012	2	36740012	index:0,count:36740012,average:75,stdev:0|index:1,count:36740012,average:75,stdev:0	GSM2064362_r1				in_mesa	26940862	36.5	1.76	0.04	3101656043	3114417437	2860244963	2913713172	100.41	101.87	26997480	26286382	152.302	482.979	80	238228	72.57	79.39	31167193	19592432	31167193	19592432	70.89	72.54	31167193	19138646	31167193	17902255	530401359	17.10	7.07	0	6.31	0	0.15	0	0.09	0	0.00	0	26.27	0	26997480	0	150	0	143.38	0	2.47	0	0.01	0	2.39	0	0.03	0	271.59	0	0.47	0	2597656	0	36740012	0	2317789	0	56757	0	34522	0	0	0	9651253	0	1564	0	0	0	12226	0	1690504	0	21498	0	1725792	0	67.17	0	24679691	0	128334	1549511	12.074048965979	36740012.0	26997480.0	2597656.0	2317789.0	56757.0	34522.0	0.0	9651253.0	24679691.0	73.5	7.1	6.3	0.2	0.1	0.0	26.3	67.2	75	75	75.00	38	2755500900	27.4	22.8	21.1	28.7	0.0	37.3	20.2	bulk
1511742	SRR3175113	SRP070433	SRS1305163	SRX1589671	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064364: Psen 1&2 null_sample1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Psen 1&2 deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064364		GSM2064364	Psen 1&2 null_sample1	3112555950	20750373	2016-02-29 16:27:16	1859396729	3112555950	20750373	2	20750373	index:0,count:20750373,average:75,stdev:0|index:1,count:20750373,average:75,stdev:0	GSM2064364_r1				in_mesa	26940862	33.94	2.08	0.03	2093333277	2141269578	1985911188	2048617104	102.29	103.16	15134452	14209789	277.407	1047.385	281	51260	71.6	75.74	16495141	10836994	16495141	10836994	68.53	69.04	16495141	10372146	16495141	9878078	471705907	22.53	18.85	0	3.99	0	0.11	0	0.16	0	0.00	0	26.80	0	15134452	0	150	0	145.07	0	2.61	0	0.02	0	2.00	0	0.02	0	297.61	0	0.42	0	3911402	0	20750373	0	827135	0	23163	0	32252	0	0	0	5560506	0	893	0	0	0	7365	0	985956	0	14383	0	1008597	0	68.95	0	14307317	0	111584	1005763	9.013505520505	20750373.0	15134452.0	3911402.0	827135.0	23163.0	32252.0	0.0	5560506.0	14307317.0	72.9	18.8	4.0	0.1	0.2	0.0	26.8	68.9	75	75	75.00	38	1556277975	27.8	21.6	21.9	28.7	0.0	37.3	19.9	bulk
1511759	SRR3175114	SRP070433	SRS1305162	SRX1589672	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064365: Psen 1&2 null_sample2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Psen 1&2 deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064365		GSM2064365	Psen 1&2 null_sample2	3195565050	21303767	2016-02-29 16:27:16	1901852721	3195565050	21303767	2	21303767	index:0,count:21303767,average:75,stdev:0|index:1,count:21303767,average:75,stdev:0	GSM2064365_r1				in_mesa	26940862	34.92	2.04	0.03	2216600834	2275138793	2104903479	2178908949	102.64	103.52	15935307	15047476	269.420	971.086	258	60640	71.89	75.94	17322357	11455183	17322357	11455183	68.56	69.01	17322357	10924760	17322357	10409221	496068615	22.38	18.49	0	3.99	0	0.11	0	0.16	0	0.00	0	24.93	0	15935307	0	150	0	145.24	0	2.56	0	0.02	0	1.90	0	0.02	0	299.58	0	0.41	0	3938598	0	21303767	0	850737	0	23093	0	33467	0	0	0	5311900	0	856	0	0	0	7653	0	1000406	0	14383	0	1023298	0	70.81	0	15084570	0	111581	1022501	9.163755478083	21303767.0	15935307.0	3938598.0	850737.0	23093.0	33467.0	0.0	5311900.0	15084570.0	74.8	18.5	4.0	0.1	0.2	0.0	24.9	70.8	75	75	75.00	38	1597782525	28.0	21.4	21.8	28.9	0.0	37.4	20.3	bulk
1511774	SRR3175115	SRP070433	SRS1305161	SRX1589673	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064366: Psen 1&2 null_sample3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Psen 1&2 deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064366		GSM2064366	Psen 1&2 null_sample3	3085503000	20570020	2016-02-29 16:27:16	1843668410	3085503000	20570020	2	20570020	index:0,count:20570020,average:75,stdev:0|index:1,count:20570020,average:75,stdev:0	GSM2064366_r1				in_mesa	26940862	35.19	2.04	0.03	2134102534	2189956755	2027779648	2098341936	102.62	103.48	15361824	14509897	268.144	966.717	258	57828	71.99	76.0	16688226	11058448	16688226	11058448	68.68	69.13	16688226	10550825	16688226	10058551	475899840	22.30	18.60	0	3.95	0	0.11	0	0.16	0	0.00	0	25.06	0	15361824	0	150	0	145.21	0	2.49	0	0.02	0	1.92	0	0.02	0	283.72	0	0.41	0	3826822	0	20570020	0	811810	0	21916	0	32168	0	0	0	5154112	0	873	0	0	0	7372	0	965932	0	14124	0	988301	0	70.73	0	14550014	0	110069	986218	8.959997819550	20570020.0	15361824.0	3826822.0	811810.0	21916.0	32168.0	0.0	5154112.0	14550014.0	74.7	18.6	3.9	0.1	0.2	0.0	25.1	70.7	75	75	75.00	38	1542751500	28.1	21.3	21.7	28.9	0.0	37.3	20.1	bulk
1511790	SRR3175116	SRP070433	SRS1305160	SRX1589674	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064367: RBPjk null_sample1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;RBPjk deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064367		GSM2064367	RBPjk null_sample1	3471790800	23145272	2016-02-29 16:27:16	2104479769	3471790800	23145272	2	23145272	index:0,count:23145272,average:75,stdev:0|index:1,count:23145272,average:75,stdev:0	GSM2064367_r1				in_mesa	26940862	32.47	1.87	0.07	2341327983	2396441959	2210067801	2283111175	102.35	103.31	16898856	15737391	277.572	1109.432	281	56888	72.42	76.99	18563720	12238922	18563720	12238922	68.85	69.56	18563720	11634704	18563720	11057419	486849847	20.79	17.78	0	4.33	0	0.12	0	0.14	0	0.00	0	26.73	0	16898856	0	150	0	145.10	0	2.72	0	0.02	0	2.28	0	0.03	0	320.47	0	0.47	0	4115327	0	23145272	0	1002853	0	27675	0	32675	0	0	0	6186066	0	1058	0	0	0	9016	0	1233202	0	16700	0	1259976	0	68.68	0	15896003	0	122354	1261881	10.313361230528	23145272.0	16898856.0	4115327.0	1002853.0	27675.0	32675.0	0.0	6186066.0	15896003.0	73.0	17.8	4.3	0.1	0.1	0.0	26.7	68.7	75	75	75.00	38	1735895400	27.5	21.9	22.3	28.3	0.0	37.2	19.9	bulk
1511805	SRR3175117	SRP070433	SRS1305159	SRX1589675	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064368: RBPjk null_sample2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;RBPjk deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064368		GSM2064368	RBPjk null_sample2	3043801800	20292012	2016-02-29 16:27:16	1841688832	3043801800	20292012	2	20292012	index:0,count:20292012,average:75,stdev:0|index:1,count:20292012,average:75,stdev:0	GSM2064368_r1				in_mesa	26940862	32.73	1.84	0.07	2075819281	2127908424	1959404527	2027385849	102.51	103.47	14926003	13977183	271.286	1046.050	258	55467	72.28	76.83	16398112	10788715	16398112	10788715	68.39	69.12	16398112	10207402	16398112	9706810	433359036	20.88	17.81	0	4.35	0	0.12	0	0.14	0	0.00	0	26.19	0	14926003	0	150	0	145.07	0	2.70	0	0.02	0	2.31	0	0.03	0	303.12	0	0.47	0	3613455	0	20292012	0	883300	0	23580	0	27517	0	0	0	5314912	0	999	0	0	0	7807	0	1053479	0	15359	0	1077644	0	69.20	0	14042703	0	115773	1079144	9.321206153421	20292012.0	14926003.0	3613455.0	883300.0	23580.0	27517.0	0.0	5314912.0	14042703.0	73.6	17.8	4.4	0.1	0.1	0.0	26.2	69.2	75	75	75.00	38	1521900900	27.5	21.9	22.3	28.3	0.0	37.2	19.8	bulk
3023440	SRR3175112	SRP070433	SRS1305164	SRX1589670	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064363: Notch 1&2 null_sample3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;Notch 1&2 deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064363		GSM2064363	Notch 1&2 null_sample3	3584363250	23895755	2016-02-29 16:27:16	2139889667	3584363250	23895755	2	23895755	index:0,count:23895755,average:75,stdev:0|index:1,count:23895755,average:75,stdev:0	GSM2064363_r1				in_mesa	26940862	37.19	1.75	0.05	2420193413	2436052174	2249110814	2292188161	100.66	101.92	19330370	18717362	176.893	533.611	112	122889	73.8	79.95	21957698	14266507	21957698	14266507	71.78	73.29	21957698	13875811	21957698	13078574	409858511	16.93	9.20	0	6.21	0	0.15	0	0.11	0	0.00	0	18.85	0	19330370	0	150	0	145.07	0	2.40	0	0.01	0	2.48	0	0.03	0	285.80	0	0.47	0	2198323	0	23895755	0	1485108	0	35305	0	25406	0	0	0	4504674	0	1255	0	0	0	9304	0	1287853	0	15629	0	1314041	0	74.68	0	17845262	0	120061	1238437	10.315064842039	23895755.0	19330370.0	2198323.0	1485108.0	35305.0	25406.0	0.0	4504674.0	17845262.0	80.9	9.2	6.2	0.1	0.1	0.0	18.9	74.7	75	75	75.00	38	1792181625	27.8	21.9	21.6	28.6	0.0	37.3	20.2	bulk
3023632	SRR3175118	SRP070433	SRS1305158	SRX1589676	SRA354792	GEO		Quantitative Analysis of Notch mutant (Notch1&2-null, Psen1&2-null, RBPjk-null) and wild-type hair follicle transcriptomes by NGS	The goals of this study is to test whether NICD presence protects the RBPjk-null Hair Follicles by altering gene expression via association with other DNA binding proteins at P3, just before the conversion to TSLP-producing keratin cysts. Overall design: Methods: Skin samples were embedded in OCT. Sectioned at 20µm thickness. Dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure. Laser capture was performed with Arcturus Veritas. Methods: ~100 hair follicles from Notch-null, PS-null, RBPjk-null and wild-type samples were pooled into 3 biological replicates for each genotype and subjected to RNA isolation followed by RNA-Seq. Conclusions: A total of 2047 genes were differentially expressed (=1.5 fold) in three or more biological replicates of Notch mutant hair follicles compared to wild-type controls (p-value<0.05). Unsupervised hierarchical clustering analysis failed to distinguish between the mutants.		GSM2064369: RBPjk null_sample3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Skin samples were embedded in OCT immediately after collecting and snap-frozen in liquid nitrogen before storing at -80°C Sectioned at 20μm thickness, tissue slices were placed on poly-lysine (Sigma-P8920; 1:10 dilution) treated PEN membrane glass slides (Arcturus, LCM0522), dehydrated in EtOH, and equilibrated to Xylene before the LCM procedure Laser capture was performed with Arcturus Veritas and Arcturus CapSure HS LCM Caps (Arcturus Engineering, Inc., Mountain View, CA) within 45 minutes to avoid degradation. 4 membrane with ~25-30 hair follicles each were pooled and stored in QIAzol (Qiagen) at -80°C. RNA extracted as described in methods was QCed for sequencing using an Agilent 2100 Bioanalyzer requiring integrity numbers >8 to pass. Libraries were prepared with the Nextera XT DNA Sample Preparation kit (Illumina Technologies). 1ng of cDNA was tagmented with the Amplicon Tagment Mix at 55°C for 10min. NT Buffer was added to neutralize the samples. Libraries were PCR amplified (Nextera PCR Master Mix) in the following program: one cycle of 72°C for 3min, one cycle of 98°C for 30s, 12 cycles of 95°C for 10s, 55°C for 30s, and 72°C for 1min, and one cycle of 72°C for 5min and (N7XX, and N5XX). The purified cDNA was captured on an Illumina flow cell for cluster generation and sequenced (75bp paired-end, 20 million reads, Illumina HiSeq2500) following the manufacturer's protocol.	Illumina HiSeq 2500	age;;Postnatal day (P) 3|genotype;;RBPjk deficient hair follicle|source_name;;Hair Follicle|strain;;Mixed background	GEO Accession;;GSM2064369		GSM2064369	RBPjk null_sample3	4478839800	29858932	2016-02-29 16:27:16	2698890927	4478839800	29858932	2	29858932	index:0,count:29858932,average:75,stdev:0|index:1,count:29858932,average:75,stdev:0	GSM2064369_r1				in_mesa	26940862	32.22	1.71	0.07	2981962814	3063088107	2781648611	2894272236	102.72	104.05	23342383	22519124	194.471	648.849	98	123407	70.33	75.89	26249115	16416279	26249115	16416279	65.83	66.87	26249115	15366219	26249115	14465277	621338787	20.84	11.68	0	5.73	0	0.13	0	0.13	0	0.00	0	21.57	0	23342383	0	150	0	144.78	0	2.68	0	0.02	0	2.03	0	0.03	0	297.76	0	0.49	0	3486763	0	29858932	0	1709744	0	39269	0	38071	0	0	0	6439209	0	1403	0	0	0	10669	0	1430246	0	22215	0	1464533	0	72.45	0	21632639	0	126524	1395180	11.026998830261	29858932.0	23342383.0	3486763.0	1709744.0	39269.0	38071.0	0.0	6439209.0	21632639.0	78.2	11.7	5.7	0.1	0.1	0.0	21.6	72.4	75	75	75.00	38	2239419900	27.4	22.3	22.1	28.2	0.0	37.2	19.9	bulk
1409871	SRR3212834	SRP071321	SRS1329176	SRX1620347	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083855: cKO3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083855		GSM2083855	cKO3	7013605640	34720820	2016-10-31 08:44:35	5200183642	7013605640	34720820	2	34720820	index:0,count:34720820,average:101,stdev:0|index:1,count:34720820,average:101,stdev:0	GSM2083855_r1				in_mesa	28007900	0.06	2.47	0.03	5363911864	5512064463	5100390481	5285464622	102.76	103.63	30349634	27583815	224.894	1069.560	170	194270	85.73	90.37	32890434	26017998	32890434	26017998	78.61	80.34	32890434	23858887	32890434	23131259	344538566	6.42	7.16	0	4.49	0	0.33	0	0.03	0	0.00	0	12.22	0	30349634	0	202	0	196.48	0	3.76	0	0.03	0	2.56	0	0.03	0	187.68	0	0.53	0	2484476	0	34720820	0	1558358	0	116280	0	10623	0	0	0	4244283	0	11536	0	0	0	69442	0	10681864	0	36298	0	10799140	0	82.92	0	28791276	0	198082	10360970	52.306469038075	34720820.0	30349634.0	2484476.0	1558358.0	116280.0	10623.0	0.0	4244283.0	28791276.0	87.4	7.2	4.5	0.3	0.0	0.0	12.2	82.9	101	101	101.00	38	3506802820	24.4	25.6	25.8	24.3	0.0	33.9	21.3	bulk
1409887	SRR3212835	SRP071321	SRS1329176	SRX1620347	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083855: cKO3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083855		GSM2083855	cKO3	6981358562	34561181	2016-10-31 08:44:35	5191957164	6981358562	34561181	2	34561181	index:0,count:34561181,average:101,stdev:0|index:1,count:34561181,average:101,stdev:0	GSM2083855_r2				in_mesa	28007900	0.06	2.48	0.03	5329261726	5474700208	5067516533	5249675378	102.73	103.59	30178590	27436148	224.485	1068.856	170	193943	85.73	90.36	32702109	25870884	32702109	25870884	78.65	80.37	32702109	23735772	32702109	23010805	343563164	6.45	7.15	0	4.48	0	0.33	0	0.03	0	0.00	0	12.32	0	30178590	0	202	0	196.40	0	3.78	0	0.03	0	2.55	0	0.03	0	242.53	0	0.55	0	2471870	0	34561181	0	1549209	0	114897	0	10419	0	0	0	4257275	0	11401	0	0	0	69143	0	10584162	0	36299	0	10701005	0	82.84	0	28629381	0	198068	10270734	51.854585293939	34561181.0	30178590.0	2471870.0	1549209.0	114897.0	10419.0	0.0	4257275.0	28629381.0	87.3	7.2	4.5	0.3	0.0	0.0	12.3	82.8	101	101	101.00	38	3490679281	24.4	25.6	25.7	24.3	0.0	33.8	21.1	bulk
1409902	SRR3212836	SRP071321	SRS1329176	SRX1620347	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083855: cKO3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083855		GSM2083855	cKO3	7020012070	34752535	2016-10-31 08:44:35	5206774412	7020012070	34752535	2	34752535	index:0,count:34752535,average:101,stdev:0|index:1,count:34752535,average:101,stdev:0	GSM2083855_r3				in_mesa	28007900	0.06	2.47	0.03	5369373354	5518712544	5105926174	5292320671	102.78	103.65	30414427	27667351	224.270	1063.064	169	195419	85.66	90.29	32958444	26052341	32958444	26052341	78.47	80.19	32958444	23866485	32958444	23138183	347344470	6.47	7.24	0	4.49	0	0.33	0	0.03	0	0.00	0	12.12	0	30414427	0	202	0	196.42	0	3.79	0	0.03	0	2.57	0	0.03	0	215.33	0	0.54	0	2515157	0	34752535	0	1559879	0	114573	0	10569	0	0	0	4212966	0	11502	0	0	0	69160	0	10626592	0	36691	0	10743945	0	83.03	0	28854548	0	198014	10302074	52.026998091044	34752535.0	30414427.0	2515157.0	1559879.0	114573.0	10569.0	0.0	4212966.0	28854548.0	87.5	7.2	4.5	0.3	0.0	0.0	12.1	83.0	101	101	101.00	38	3510006035	24.4	25.6	25.7	24.3	0.0	33.9	21.5	bulk
1409918	SRR3212837	SRP071321	SRS1329176	SRX1620347	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083855: cKO3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083855		GSM2083855	cKO3	7029780386	34800893	2016-10-31 08:44:35	5222029321	7029780386	34800893	2	34800893	index:0,count:34800893,average:101,stdev:0|index:1,count:34800893,average:101,stdev:0	GSM2083855_r4				in_mesa	28007900	0.06	2.47	0.03	5379629349	5529735166	5116171389	5303353290	102.79	103.66	30480209	27734362	224.054	1063.356	169	196836	85.61	90.23	33025456	26094923	33025456	26094923	78.37	80.09	33025456	23887685	33025456	23160797	348893655	6.49	7.29	0	4.48	0	0.33	0	0.03	0	0.00	0	12.05	0	30480209	0	202	0	196.41	0	3.84	0	0.03	0	2.57	0	0.03	0	211.99	0	0.52	0	2537202	0	34800893	0	1560526	0	115063	0	10578	0	0	0	4195043	0	11443	0	0	0	69471	0	10645017	0	37205	0	10763136	0	83.10	0	28919683	0	198204	10319595	52.065523400133	34800893.0	30480209.0	2537202.0	1560526.0	115063.0	10578.0	0.0	4195043.0	28919683.0	87.6	7.3	4.5	0.3	0.0	0.0	12.1	83.1	101	101	101.00	38	3514890193	24.4	25.6	25.7	24.3	0.0	33.9	21.6	bulk
1409934	SRR3212838	SRP071321	SRS1329176	SRX1620347	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083855: cKO3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083855		GSM2083855	cKO3	7165443586	35472493	2016-10-31 08:44:35	5309493407	7165443586	35472493	2	35472493	index:0,count:35472493,average:101,stdev:0|index:1,count:35472493,average:101,stdev:0	GSM2083855_r5				in_mesa	28007900	0.06	2.47	0.03	5479953950	5632649340	5210752700	5401178418	102.79	103.65	31047242	28254577	224.003	1053.621	170	199993	85.62	90.25	33642895	26581349	33642895	26581349	78.4	80.13	33642895	24341640	33642895	23599413	355485598	6.49	7.22	0	4.50	0	0.33	0	0.03	0	0.00	0	12.12	0	31047242	0	202	0	196.44	0	3.79	0	0.03	0	2.57	0	0.03	0	205.31	0	0.53	0	2561601	0	35472493	0	1594996	0	117067	0	10583	0	0	0	4297601	0	11511	0	0	0	70791	0	10852594	0	37685	0	10972581	0	83.03	0	29452246	0	199412	10513236	52.721180269994	35472493.0	31047242.0	2561601.0	1594996.0	117067.0	10583.0	0.0	4297601.0	29452246.0	87.5	7.2	4.5	0.3	0.0	0.0	12.1	83.0	101	101	101.00	38	3582721793	24.4	25.6	25.7	24.3	0.0	34.0	21.7	bulk
1409949	SRR3212839	SRP071321	SRS1329176	SRX1620347	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083855: cKO3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083855		GSM2083855	cKO3	7126562020	35280010	2016-10-31 08:44:35	5266622238	7126562020	35280010	2	35280010	index:0,count:35280010,average:101,stdev:0|index:1,count:35280010,average:101,stdev:0	GSM2083855_r6				in_mesa	28007900	0.06	2.47	0.03	5451696167	5602994647	5184447248	5373574902	102.78	103.65	30892140	28120664	223.857	1057.965	169	199319	85.63	90.26	33472135	26454078	33472135	26454078	78.41	80.14	33472135	24223995	33472135	23488178	353595394	6.49	7.25	0	4.49	0	0.33	0	0.03	0	0.00	0	12.08	0	30892140	0	202	0	196.45	0	3.81	0	0.03	0	2.57	0	0.03	0	195.70	0	0.52	0	2556880	0	35280010	0	1583546	0	116202	0	10586	0	0	0	4261082	0	11683	0	0	0	70184	0	10802914	0	37197	0	10921978	0	83.07	0	29308594	0	199051	10466094	52.579961919307	35280010.0	30892140.0	2556880.0	1583546.0	116202.0	10586.0	0.0	4261082.0	29308594.0	87.6	7.2	4.5	0.3	0.0	0.0	12.1	83.1	101	101	101.00	38	3563281010	24.4	25.6	25.7	24.3	0.0	34.1	21.8	bulk
2818195	SRR3212804	SRP071321	SRS1329181	SRX1620342	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083850: Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083850		GSM2083850	Control 1	6092170318	30159259	2016-10-31 08:44:35	4501508052	6092170318	30159259	2	30159259	index:0,count:30159259,average:101,stdev:0|index:1,count:30159259,average:101,stdev:0	GSM2083850_r1				in_mesa	28007900	0.08	2.63	0.03	4704025781	4813173511	4491803718	4631151594	102.32	103.1	26488926	23957760	226.231	1159.611	169	168175	86.94	91.23	28564698	23028431	28564698	23028431	80.64	82.22	28564698	21359365	28564698	20753952	274261378	5.83	7.23	0	4.14	0	0.36	0	0.03	0	0.00	0	11.77	0	26488926	0	202	0	196.70	0	3.50	0	0.02	0	2.49	0	0.02	0	208.79	0	0.50	0	2180137	0	30159259	0	1247634	0	109837	0	10057	0	0	0	3550439	0	8782	0	0	0	62338	0	9556989	0	32341	0	9660450	0	83.69	0	25241292	0	175518	9269627	52.812970749439	30159259.0	26488926.0	2180137.0	1247634.0	109837.0	10057.0	0.0	3550439.0	25241292.0	87.8	7.2	4.1	0.4	0.0	0.0	11.8	83.7	101	101	101.00	38	3046085159	24.8	25.2	25.4	24.6	0.0	34.1	21.5	bulk
2818227	SRR3212805	SRP071321	SRS1329181	SRX1620342	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083850: Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083850		GSM2083850	Control 1	6066532276	30032338	2016-10-31 08:44:35	4496586703	6066532276	30032338	2	30032338	index:0,count:30032338,average:101,stdev:0|index:1,count:30032338,average:101,stdev:0	GSM2083850_r2				in_mesa	28007900	0.08	2.64	0.03	4676244774	4783194983	4465761997	4602960767	102.29	103.07	26350859	23844503	225.866	1154.316	169	167801	86.93	91.22	28410236	22907315	28410236	22907315	80.65	82.23	28410236	21251918	28410236	20650575	273537884	5.85	7.21	0	4.12	0	0.36	0	0.03	0	0.00	0	11.87	0	26350859	0	202	0	196.63	0	3.51	0	0.02	0	2.48	0	0.02	0	218.86	0	0.52	0	2165153	0	30032338	0	1238059	0	108462	0	9643	0	0	0	3563374	0	8771	0	0	0	61627	0	9469260	0	31767	0	9571425	0	83.62	0	25112800	0	175478	9182229	52.326952666431	30032338.0	26350859.0	2165153.0	1238059.0	108462.0	9643.0	0.0	3563374.0	25112800.0	87.7	7.2	4.1	0.4	0.0	0.0	11.9	83.6	101	101	101.00	38	3033266138	24.8	25.2	25.4	24.6	0.0	34.0	21.3	bulk
2818258	SRR3212806	SRP071321	SRS1329181	SRX1620342	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083850: Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083850		GSM2083850	Control 1	6101425150	30205075	2016-10-31 08:44:35	4510719059	6101425150	30205075	2	30205075	index:0,count:30205075,average:101,stdev:0|index:1,count:30205075,average:101,stdev:0	GSM2083850_r3				in_mesa	28007900	0.08	2.63	0.03	4711010421	4820742770	4498299668	4638302141	102.33	103.11	26556866	24036655	225.557	1153.974	170	168355	86.86	91.16	28636398	23067822	28636398	23067822	80.5	82.08	28636398	21379507	28636398	20771165	276589774	5.87	7.30	0	4.15	0	0.36	0	0.03	0	0.00	0	11.69	0	26556866	0	202	0	196.64	0	3.53	0	0.02	0	2.50	0	0.03	0	225.60	0	0.51	0	2205908	0	30205075	0	1252034	0	108583	0	9838	0	0	0	3529788	0	8956	0	0	0	62106	0	9517183	0	32631	0	9620876	0	83.78	0	25304832	0	175225	9227670	52.661834783849	30205075.0	26556866.0	2205908.0	1252034.0	108583.0	9838.0	0.0	3529788.0	25304832.0	87.9	7.3	4.1	0.4	0.0	0.0	11.7	83.8	101	101	101.00	38	3050712575	24.8	25.2	25.4	24.6	0.0	34.1	21.7	bulk
2818291	SRR3212807	SRP071321	SRS1329181	SRX1620342	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083850: Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083850		GSM2083850	Control 1	6094645626	30171513	2016-10-31 08:44:35	4512482804	6094645626	30171513	2	30171513	index:0,count:30171513,average:101,stdev:0|index:1,count:30171513,average:101,stdev:0	GSM2083850_r4				in_mesa	28007900	0.08	2.63	0.03	4708613513	4819416491	4496662439	4637779119	102.35	103.14	26548588	24040167	225.392	1152.875	169	169729	86.84	91.13	28624258	23055294	28624258	23055294	80.43	82.01	28624258	21353243	28624258	20748379	277042802	5.88	7.35	0	4.14	0	0.36	0	0.03	0	0.00	0	11.62	0	26548588	0	202	0	196.63	0	3.57	0	0.02	0	2.50	0	0.03	0	196.06	0	0.49	0	2218901	0	30171513	0	1247927	0	107961	0	9920	0	0	0	3505044	0	8942	0	0	0	62285	0	9506801	0	32896	0	9610924	0	83.86	0	25300661	0	175511	9215074	52.504253294665	30171513.0	26548588.0	2218901.0	1247927.0	107961.0	9920.0	0.0	3505044.0	25300661.0	88.0	7.4	4.1	0.4	0.0	0.0	11.6	83.9	101	101	101.00	38	3047322813	24.8	25.2	25.4	24.7	0.0	34.1	21.8	bulk
2818323	SRR3212808	SRP071321	SRS1329181	SRX1620342	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083850: Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083850		GSM2083850	Control 1	6215821386	30771393	2016-10-31 08:44:35	4589569043	6215821386	30771393	2	30771393	index:0,count:30771393,average:101,stdev:0|index:1,count:30771393,average:101,stdev:0	GSM2083850_r5				in_mesa	28007900	0.08	2.63	0.03	4799270733	4911695196	4582874658	4726165073	102.34	103.13	27060315	24507430	225.317	1149.421	169	172363	86.83	91.12	29177965	23497535	29177965	23497535	80.43	82.01	29177965	21765443	29177965	21148448	282486418	5.89	7.29	0	4.14	0	0.36	0	0.03	0	0.00	0	11.67	0	27060315	0	202	0	196.66	0	3.53	0	0.02	0	2.51	0	0.03	0	198.88	0	0.50	0	2241947	0	30771393	0	1274098	0	110668	0	9872	0	0	0	3590538	0	8993	0	0	0	62593	0	9706892	0	33325	0	9811803	0	83.80	0	25786217	0	175987	9405088	53.441947416571	30771393.0	27060315.0	2241947.0	1274098.0	110668.0	9872.0	0.0	3590538.0	25786217.0	87.9	7.3	4.1	0.4	0.0	0.0	11.7	83.8	101	101	101.00	38	3107910693	24.8	25.2	25.4	24.6	0.0	34.2	21.9	bulk
2818354	SRR3212809	SRP071321	SRS1329181	SRX1620342	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083850: Control 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083850		GSM2083850	Control 1	6175813468	30573334	2016-10-31 08:44:35	4546309071	6175813468	30573334	2	30573334	index:0,count:30573334,average:101,stdev:0|index:1,count:30573334,average:101,stdev:0	GSM2083850_r6				in_mesa	28007900	0.08	2.63	0.03	4769680145	4881164979	4554827787	4697048522	102.34	103.12	26895733	24364464	225.216	1147.422	170	171455	86.85	91.14	29003283	23359022	29003283	23359022	80.45	82.03	29003283	21638205	29003283	21025511	280534854	5.88	7.32	0	4.14	0	0.36	0	0.03	0	0.00	0	11.64	0	26895733	0	202	0	196.68	0	3.55	0	0.02	0	2.50	0	0.03	0	175.54	0	0.49	0	2238166	0	30573334	0	1265189	0	109473	0	10444	0	0	0	3557684	0	9003	0	0	0	63181	0	9648870	0	33281	0	9754335	0	83.83	0	25630544	0	176084	9347022	53.082744599169	30573334.0	26895733.0	2238166.0	1265189.0	109473.0	10444.0	0.0	3557684.0	25630544.0	88.0	7.3	4.1	0.4	0.0	0.0	11.6	83.8	101	101	101.00	38	3087906734	24.8	25.2	25.4	24.6	0.0	34.3	22.0	bulk
2818578	SRR3212810	SRP071321	SRS1329180	SRX1620343	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083851: Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083851		GSM2083851	Control 2	6509761888	32226544	2016-10-31 08:44:35	4824118611	6509761888	32226544	2	32226544	index:0,count:32226544,average:101,stdev:0|index:1,count:32226544,average:101,stdev:0	GSM2083851_r1				in_mesa	28007900	0.09	2.56	0.03	5013205699	5145985245	4777287019	4944720592	102.65	103.5	28237519	25575721	226.821	1141.696	169	178458	86.17	90.62	30524207	24331103	30524207	24331103	79.19	80.92	30524207	22361417	30524207	21725853	313668233	6.26	7.14	0	4.31	0	0.33	0	0.03	0	0.00	0	12.01	0	28237519	0	202	0	196.55	0	3.64	0	0.02	0	2.58	0	0.03	0	203.18	0	0.53	0	2300089	0	32226544	0	1388691	0	107847	0	10689	0	0	0	3870489	0	9106	0	0	0	64581	0	9981248	0	34987	0	10089922	0	83.31	0	26848828	0	180812	9694099	53.614245735902	32226544.0	28237519.0	2300089.0	1388691.0	107847.0	10689.0	0.0	3870489.0	26848828.0	87.6	7.1	4.3	0.3	0.0	0.0	12.0	83.3	101	101	101.00	38	3254880944	24.5	25.5	25.6	24.4	0.0	33.9	21.4	bulk
2818609	SRR3212811	SRP071321	SRS1329180	SRX1620343	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083851: Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083851		GSM2083851	Control 2	6472485212	32042006	2016-10-31 08:44:35	4810186714	6472485212	32042006	2	32042006	index:0,count:32042006,average:101,stdev:0|index:1,count:32042006,average:101,stdev:0	GSM2083851_r2				in_mesa	28007900	0.09	2.57	0.03	4975915139	5105817854	4742264032	4906883288	102.61	103.47	28046975	25407978	226.446	1141.016	170	178220	86.18	90.63	30312328	24171025	30312328	24171025	79.24	80.96	30312328	22223381	30312328	21592116	311857408	6.27	7.12	0	4.30	0	0.33	0	0.03	0	0.00	0	12.10	0	28046975	0	202	0	196.47	0	3.66	0	0.02	0	2.56	0	0.03	0	221.40	0	0.54	0	2281224	0	32042006	0	1376346	0	106496	0	10430	0	0	0	3878105	0	9291	0	0	0	63767	0	9882660	0	34775	0	9990493	0	83.24	0	26670629	0	180182	9591921	53.234623880299	32042006.0	28046975.0	2281224.0	1376346.0	106496.0	10430.0	0.0	3878105.0	26670629.0	87.5	7.1	4.3	0.3	0.0	0.0	12.1	83.2	101	101	101.00	38	3236242606	24.5	25.5	25.6	24.4	0.0	33.8	21.2	bulk
2818641	SRR3212812	SRP071321	SRS1329180	SRX1620343	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083851: Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083851		GSM2083851	Control 2	6543175112	32391956	2016-10-31 08:44:35	4853081635	6543175112	32391956	2	32391956	index:0,count:32391956,average:101,stdev:0|index:1,count:32391956,average:101,stdev:0	GSM2083851_r3				in_mesa	28007900	0.09	2.56	0.03	5037619323	5172297925	4801164858	4970762296	102.67	103.53	28406871	25751254	226.066	1135.778	170	180814	86.1	90.54	30699104	24457873	30699104	24457873	79.05	80.77	30699104	22455692	30699104	21817999	318278558	6.32	7.21	0	4.30	0	0.33	0	0.03	0	0.00	0	11.94	0	28406871	0	202	0	196.49	0	3.68	0	0.02	0	2.58	0	0.03	0	240.93	0	0.54	0	2336783	0	32391956	0	1393522	0	106736	0	10462	0	0	0	3867887	0	9004	0	0	0	64162	0	9966300	0	35603	0	10075069	0	83.40	0	27013349	0	180790	9676338	53.522528900935	32391956.0	28406871.0	2336783.0	1393522.0	106736.0	10462.0	0.0	3867887.0	27013349.0	87.7	7.2	4.3	0.3	0.0	0.0	11.9	83.4	101	101	101.00	38	3271587556	24.5	25.5	25.6	24.4	0.0	34.0	21.6	bulk
2818673	SRR3212813	SRP071321	SRS1329180	SRX1620343	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083851: Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083851		GSM2083851	Control 2	6545452460	32403230	2016-10-31 08:44:35	4863251259	6545452460	32403230	2	32403230	index:0,count:32403230,average:101,stdev:0|index:1,count:32403230,average:101,stdev:0	GSM2083851_r4				in_mesa	28007900	0.09	2.56	0.03	5041890100	5176377991	4805417319	4974994201	102.67	103.53	28438884	25788310	225.885	1136.119	170	180898	86.05	90.48	30734123	24470519	30734123	24470519	78.95	80.66	30734123	22452069	30734123	21815383	318594705	6.32	7.26	0	4.30	0	0.33	0	0.03	0	0.00	0	11.87	0	28438884	0	202	0	196.48	0	3.72	0	0.02	0	2.59	0	0.03	0	208.31	0	0.52	0	2352769	0	32403230	0	1393945	0	107315	0	10595	0	0	0	3846436	0	9290	0	0	0	64315	0	9971822	0	35849	0	10081276	0	83.46	0	27044939	0	180640	9672312	53.544685562445	32403230.0	28438884.0	2352769.0	1393945.0	107315.0	10595.0	0.0	3846436.0	27044939.0	87.8	7.3	4.3	0.3	0.0	0.0	11.9	83.5	101	101	101.00	38	3272726230	24.5	25.5	25.6	24.4	0.0	33.9	21.6	bulk
2818705	SRR3212814	SRP071321	SRS1329180	SRX1620343	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083851: Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083851		GSM2083851	Control 2	6641689098	32879649	2016-10-31 08:44:35	4919685708	6641689098	32879649	2	32879649	index:0,count:32879649,average:101,stdev:0|index:1,count:32879649,average:101,stdev:0	GSM2083851_r5				in_mesa	28007900	0.09	2.56	0.03	5113854012	5250481333	4873477536	5045434828	102.67	103.53	28842874	26158570	225.778	1131.146	170	183995	86.06	90.51	31174681	24822423	31174681	24822423	78.99	80.71	31174681	22783832	31174681	22135384	323396572	6.32	7.20	0	4.31	0	0.33	0	0.03	0	0.00	0	11.92	0	28842874	0	202	0	196.51	0	3.66	0	0.02	0	2.58	0	0.03	0	200.28	0	0.53	0	2366797	0	32879649	0	1416833	0	108364	0	10775	0	0	0	3917636	0	9424	0	0	0	65698	0	10116702	0	36016	0	10227840	0	83.41	0	27426041	0	181166	9819458	54.201439563715	32879649.0	28842874.0	2366797.0	1416833.0	108364.0	10775.0	0.0	3917636.0	27426041.0	87.7	7.2	4.3	0.3	0.0	0.0	11.9	83.4	101	101	101.00	38	3320844549	24.5	25.5	25.6	24.4	0.0	34.0	21.7	bulk
2818737	SRR3212815	SRP071321	SRS1329180	SRX1620343	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083851: Control 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083851		GSM2083851	Control 2	6619386682	32769241	2016-10-31 08:44:35	4890049843	6619386682	32769241	2	32769241	index:0,count:32769241,average:101,stdev:0|index:1,count:32769241,average:101,stdev:0	GSM2083851_r6				in_mesa	28007900	0.09	2.56	0.03	5098308587	5233843000	4859323586	5030482679	102.66	103.52	28759291	26087131	225.710	1127.703	169	183879	86.08	90.52	31080540	24755705	31080540	24755705	79.01	80.73	31080540	22723365	31080540	22078949	322145006	6.32	7.22	0	4.30	0	0.33	0	0.03	0	0.00	0	11.87	0	28759291	0	202	0	196.52	0	3.69	0	0.02	0	2.58	0	0.03	0	182.05	0	0.52	0	2366140	0	32769241	0	1409629	0	108025	0	10584	0	0	0	3891341	0	9202	0	0	0	65585	0	10095932	0	36207	0	10206926	0	83.46	0	27349662	0	180742	9794163	54.188639054564	32769241.0	28759291.0	2366140.0	1409629.0	108025.0	10584.0	0.0	3891341.0	27349662.0	87.8	7.2	4.3	0.3	0.0	0.0	11.9	83.5	101	101	101.00	38	3309693341	24.5	25.5	25.6	24.4	0.0	34.1	21.8	bulk
2818769	SRR3212816	SRP071321	SRS1329179	SRX1620344	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083852: Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083852		GSM2083852	Control 3	6027214794	29837697	2016-10-31 08:44:35	4484178982	6027214794	29837697	2	29837697	index:0,count:29837697,average:101,stdev:0|index:1,count:29837697,average:101,stdev:0	GSM2083852_r1				in_mesa	28007900	0.07	2.68	0.03	4665637298	4774874253	4454837847	4594630897	102.34	103.14	26286197	23756808	227.754	1164.281	169	163917	86.99	91.3	28341789	22867338	28341789	22867338	80.73	82.35	28341789	21220027	28341789	20624716	276218279	5.92	7.20	0	4.16	0	0.35	0	0.03	0	0.00	0	11.52	0	26286197	0	202	0	196.72	0	3.31	0	0.02	0	2.76	0	0.03	0	221.93	0	0.51	0	2147382	0	29837697	0	1240209	0	105182	0	10344	0	0	0	3435974	0	9426	0	0	0	60458	0	9447313	0	32556	0	9549753	0	83.94	0	25045988	0	178488	9154305	51.288069786204	29837697.0	26286197.0	2147382.0	1240209.0	105182.0	10344.0	0.0	3435974.0	25045988.0	88.1	7.2	4.2	0.4	0.0	0.0	11.5	83.9	101	101	101.00	38	3013607397	24.7	25.3	25.5	24.5	0.0	33.9	21.4	bulk
2818801	SRR3212817	SRP071321	SRS1329179	SRX1620344	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083852: Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083852		GSM2083852	Control 3	6003478380	29720190	2016-10-31 08:44:35	4479127946	6003478380	29720190	2	29720190	index:0,count:29720190,average:101,stdev:0|index:1,count:29720190,average:101,stdev:0	GSM2083852_r2				in_mesa	28007900	0.08	2.69	0.03	4639706714	4746509478	4429944835	4567430853	102.3	103.1	26162115	23654981	227.342	1157.808	169	163002	86.98	91.29	28208164	22754897	28208164	22754897	80.74	82.36	28208164	21123315	28208164	20529141	275828551	5.94	7.19	0	4.16	0	0.35	0	0.03	0	0.00	0	11.59	0	26162115	0	202	0	196.65	0	3.33	0	0.02	0	2.76	0	0.03	0	212.29	0	0.53	0	2136546	0	29720190	0	1235315	0	103835	0	10181	0	0	0	3444059	0	9281	0	0	0	59906	0	9371459	0	32143	0	9472789	0	83.87	0	24926800	0	178213	9074026	50.916745691953	29720190.0	26162115.0	2136546.0	1235315.0	103835.0	10181.0	0.0	3444059.0	24926800.0	88.0	7.2	4.2	0.3	0.0	0.0	11.6	83.9	101	101	101.00	38	3001739190	24.7	25.3	25.5	24.6	0.0	33.8	21.2	bulk
2818833	SRR3212818	SRP071321	SRS1329179	SRX1620344	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083852: Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083852		GSM2083852	Control 3	6043465492	29918146	2016-10-31 08:44:35	4497920223	6043465492	29918146	2	29918146	index:0,count:29918146,average:101,stdev:0|index:1,count:29918146,average:101,stdev:0	GSM2083852_r3				in_mesa	28007900	0.08	2.68	0.03	4679151984	4789336495	4467772244	4608890643	102.35	103.16	26392612	23880877	227.042	1154.767	169	165924	86.92	91.23	28453382	22940780	28453382	22940780	80.58	82.2	28453382	21268335	28453382	20670998	279294713	5.97	7.28	0	4.16	0	0.35	0	0.03	0	0.00	0	11.40	0	26392612	0	202	0	196.66	0	3.34	0	0.02	0	2.78	0	0.03	0	213.70	0	0.52	0	2176918	0	29918146	0	1245411	0	103990	0	10373	0	0	0	3411171	0	9177	0	0	0	60371	0	9414937	0	32818	0	9517303	0	84.05	0	25147201	0	178699	9116405	51.015422582107	29918146.0	26392612.0	2176918.0	1245411.0	103990.0	10373.0	0.0	3411171.0	25147201.0	88.2	7.3	4.2	0.3	0.0	0.0	11.4	84.1	101	101	101.00	38	3021732746	24.7	25.3	25.5	24.6	0.0	34.0	21.6	bulk
2818865	SRR3212819	SRP071321	SRS1329179	SRX1620344	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083852: Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083852		GSM2083852	Control 3	6037519218	29888709	2016-10-31 08:44:35	4500658285	6037519218	29888709	2	29888709	index:0,count:29888709,average:101,stdev:0|index:1,count:29888709,average:101,stdev:0	GSM2083852_r4				in_mesa	28007900	0.08	2.67	0.03	4676963298	4787739621	4465800088	4607402553	102.37	103.17	26387494	23878518	226.833	1151.952	170	164938	86.87	91.17	28448512	22923187	28448512	22923187	80.49	82.1	28448512	21238093	28448512	20642472	280225567	5.99	7.32	0	4.16	0	0.35	0	0.03	0	0.00	0	11.33	0	26387494	0	202	0	196.66	0	3.39	0	0.02	0	2.79	0	0.03	0	191.80	0	0.50	0	2188700	0	29888709	0	1244394	0	104064	0	10439	0	0	0	3386712	0	9181	0	0	0	60454	0	9411494	0	32911	0	9514040	0	84.12	0	25143100	0	178508	9112614	51.048770923432	29888709.0	26387494.0	2188700.0	1244394.0	104064.0	10439.0	0.0	3386712.0	25143100.0	88.3	7.3	4.2	0.3	0.0	0.0	11.3	84.1	101	101	101.00	38	3018759609	24.7	25.3	25.4	24.6	0.0	33.9	21.6	bulk
2819090	SRR3212820	SRP071321	SRS1329179	SRX1620344	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083852: Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083852		GSM2083852	Control 3	6146277432	30427116	2016-10-31 08:44:35	4570815129	6146277432	30427116	2	30427116	index:0,count:30427116,average:101,stdev:0|index:1,count:30427116,average:101,stdev:0	GSM2083852_r5				in_mesa	28007900	0.08	2.67	0.03	4758249777	4870772015	4542828454	4686837291	102.36	103.17	26844745	24298727	226.773	1151.253	169	168102	86.89	91.2	28946519	23325010	28946519	23325010	80.53	82.15	28946519	21617367	28946519	21009322	284640369	5.98	7.26	0	4.17	0	0.35	0	0.03	0	0.00	0	11.39	0	26844745	0	202	0	196.68	0	3.35	0	0.02	0	2.78	0	0.03	0	146.05	0	0.51	0	2208351	0	30427116	0	1269687	0	105778	0	10522	0	0	0	3466071	0	9502	0	0	0	61726	0	9585802	0	33447	0	9690477	0	84.05	0	25575058	0	179418	9284612	51.748497921056	30427116.0	26844745.0	2208351.0	1269687.0	105778.0	10522.0	0.0	3466071.0	25575058.0	88.2	7.3	4.2	0.3	0.0	0.0	11.4	84.1	101	101	101.00	38	3073138716	24.7	25.3	25.5	24.6	0.0	34.0	21.7	bulk
2819122	SRR3212821	SRP071321	SRS1329179	SRX1620344	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083852: Control 3; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTrap; Rbm17 f/+|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083852		GSM2083852	Control 3	6120877952	30301376	2016-10-31 08:44:35	4539068363	6120877952	30301376	2	30301376	index:0,count:30301376,average:101,stdev:0|index:1,count:30301376,average:101,stdev:0	GSM2083852_r6				in_mesa	28007900	0.08	2.68	0.03	4739485463	4850603447	4525517390	4668016125	102.34	103.15	26743135	24209238	226.600	1148.790	170	167672	86.88	91.18	28829923	23235359	28829923	23235359	80.53	82.14	28829923	21536525	28829923	20931465	283971771	5.99	7.29	0	4.16	0	0.35	0	0.04	0	0.00	0	11.36	0	26743135	0	202	0	196.70	0	3.37	0	0.02	0	2.78	0	0.03	0	215.16	0	0.50	0	2207567	0	30301376	0	1261442	0	105228	0	10663	0	0	0	3442350	0	9394	0	0	0	60711	0	9555370	0	33034	0	9658509	0	84.09	0	25481693	0	179115	9251123	51.649069033861	30301376.0	26743135.0	2207567.0	1261442.0	105228.0	10663.0	0.0	3442350.0	25481693.0	88.3	7.3	4.2	0.3	0.0	0.0	11.4	84.1	101	101	101.00	38	3060438976	24.7	25.3	25.5	24.6	0.0	34.1	21.9	bulk
2819153	SRR3212822	SRP071321	SRS1329178	SRX1620345	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083853: cKO1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083853		GSM2083853	cKO1	6345857270	31415135	2016-10-31 08:44:35	4689283403	6345857270	31415135	2	31415135	index:0,count:31415135,average:101,stdev:0|index:1,count:31415135,average:101,stdev:0	GSM2083853_r1				in_mesa	28007900	0.11	2.67	0.03	4963936546	5058548306	4733926676	4859839975	101.91	102.66	27740274	24925597	232.327	1152.363	169	169760	86.82	91.21	29965855	24084348	29965855	24084348	81.35	82.83	29965855	22567628	29965855	21869913	299015886	6.02	7.03	0	4.25	0	0.37	0	0.03	0	0.00	0	11.29	0	27740274	0	202	0	196.90	0	3.16	0	0.02	0	2.71	0	0.02	0	220.46	0	0.49	0	2208535	0	31415135	0	1336102	0	117543	0	9764	0	0	0	3547554	0	10008	0	0	0	68479	0	10255895	0	36833	0	10371215	0	84.05	0	26404172	0	205724	10027365	48.741833718963	31415135.0	27740274.0	2208535.0	1336102.0	117543.0	9764.0	0.0	3547554.0	26404172.0	88.3	7.0	4.3	0.4	0.0	0.0	11.3	84.0	101	101	101.00	38	3172928635	24.9	25.1	25.3	24.8	0.0	34.1	21.7	bulk
2819185	SRR3212823	SRP071321	SRS1329178	SRX1620345	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083853: cKO1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083853		GSM2083853	cKO1	6330173990	31337495	2016-10-31 08:44:35	4692893195	6330173990	31337495	2	31337495	index:0,count:31337495,average:101,stdev:0|index:1,count:31337495,average:101,stdev:0	GSM2083853_r2				in_mesa	28007900	0.11	2.67	0.03	4942952882	5036591522	4714117054	4839112055	101.89	102.65	27645322	24849219	231.912	1147.131	170	169897	86.83	91.22	29860124	24003281	29860124	24003281	81.38	82.85	29860124	22497450	29860124	21801183	298816037	6.05	7.03	0	4.25	0	0.37	0	0.03	0	0.00	0	11.38	0	27645322	0	202	0	196.81	0	3.18	0	0.02	0	2.70	0	0.02	0	228.37	0	0.51	0	2202504	0	31337495	0	1330297	0	116096	0	9741	0	0	0	3566336	0	10060	0	0	0	68796	0	10195294	0	36362	0	10310512	0	83.97	0	26315025	0	204839	9965508	48.650442542680	31337495.0	27645322.0	2202504.0	1330297.0	116096.0	9741.0	0.0	3566336.0	26315025.0	88.2	7.0	4.2	0.4	0.0	0.0	11.4	84.0	101	101	101.00	38	3165086995	24.9	25.1	25.2	24.8	0.0	34.0	21.4	bulk
2819217	SRR3212824	SRP071321	SRS1329178	SRX1620345	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083853: cKO1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083853		GSM2083853	cKO1	6347143000	31421500	2016-10-31 08:44:35	4692379951	6347143000	31421500	2	31421500	index:0,count:31421500,average:101,stdev:0|index:1,count:31421500,average:101,stdev:0	GSM2083853_r3				in_mesa	28007900	0.11	2.67	0.03	4963673462	5059133351	4733874739	4860744070	101.92	102.68	27768526	24972389	231.649	1141.677	169	170585	86.76	91.15	29992388	24092050	29992388	24092050	81.24	82.7	29992388	22558456	29992388	21859392	301224841	6.07	7.10	0	4.25	0	0.37	0	0.03	0	0.00	0	11.22	0	27768526	0	202	0	196.84	0	3.19	0	0.02	0	2.72	0	0.02	0	274.56	0	0.50	0	2232072	0	31421500	0	1336120	0	116493	0	9532	0	0	0	3526949	0	10102	0	0	0	68545	0	10211644	0	36841	0	10327132	0	84.12	0	26432406	0	205374	9976775	48.578568854870	31421500.0	27768526.0	2232072.0	1336120.0	116493.0	9532.0	0.0	3526949.0	26432406.0	88.4	7.1	4.3	0.4	0.0	0.0	11.2	84.1	101	101	101.00	38	3173571500	24.9	25.0	25.2	24.8	0.0	34.1	21.8	bulk
2819249	SRR3212825	SRP071321	SRS1329178	SRX1620345	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083853: cKO1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083853		GSM2083853	cKO1	6367704378	31523289	2016-10-31 08:44:35	4718334998	6367704378	31523289	2	31523289	index:0,count:31523289,average:101,stdev:0|index:1,count:31523289,average:101,stdev:0	GSM2083853_r4				in_mesa	28007900	0.11	2.66	0.03	4980837860	5077259472	4750216271	4878119705	101.94	102.69	27874966	25078372	231.351	1144.868	170	171625	86.72	91.11	30107720	24173960	30107720	24173960	81.15	82.62	30107720	22621149	30107720	21921208	302916955	6.08	7.16	0	4.26	0	0.37	0	0.03	0	0.00	0	11.17	0	27874966	0	202	0	196.81	0	3.24	0	0.02	0	2.73	0	0.02	0	233.99	0	0.48	0	2255900	0	31523289	0	1341475	0	116977	0	9529	0	0	0	3521817	0	10013	0	0	0	68859	0	10233620	0	37223	0	10349715	0	84.17	0	26533491	0	205608	9995565	48.614669662659	31523289.0	27874966.0	2255900.0	1341475.0	116977.0	9529.0	0.0	3521817.0	26533491.0	88.4	7.2	4.3	0.4	0.0	0.0	11.2	84.2	101	101	101.00	38	3183852189	24.9	25.0	25.2	24.8	0.0	34.1	21.8	bulk
2819282	SRR3212826	SRP071321	SRS1329178	SRX1620345	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083853: cKO1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083853		GSM2083853	cKO1	6471993746	32039573	2016-10-31 08:44:35	4780480214	6471993746	32039573	2	32039573	index:0,count:32039573,average:101,stdev:0|index:1,count:32039573,average:101,stdev:0	GSM2083853_r5				in_mesa	28007900	0.11	2.66	0.03	5061102668	5158961894	4826648300	4956473029	101.93	102.69	28322679	25484617	231.224	1140.437	169	174783	86.74	91.12	30590659	24566126	30590659	24566126	81.18	82.65	30590659	22993072	30590659	22281719	307750530	6.08	7.09	0	4.26	0	0.37	0	0.03	0	0.00	0	11.20	0	28322679	0	202	0	196.84	0	3.19	0	0.02	0	2.72	0	0.02	0	233.02	0	0.49	0	2270914	0	32039573	0	1363635	0	118415	0	9650	0	0	0	3588829	0	10042	0	0	0	70266	0	10412041	0	37444	0	10529793	0	84.14	0	26959044	0	206312	10173881	49.313084066850	32039573.0	28322679.0	2270914.0	1363635.0	118415.0	9650.0	0.0	3588829.0	26959044.0	88.4	7.1	4.3	0.4	0.0	0.0	11.2	84.1	101	101	101.00	38	3235996873	24.9	25.0	25.3	24.8	0.0	34.2	22.0	bulk
2819314	SRR3212827	SRP071321	SRS1329178	SRX1620345	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083853: cKO1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083853		GSM2083853	cKO1	6433321654	31848127	2016-10-31 08:44:35	4736802572	6433321654	31848127	2	31848127	index:0,count:31848127,average:101,stdev:0|index:1,count:31848127,average:101,stdev:0	GSM2083853_r6				in_mesa	28007900	0.11	2.67	0.03	5032948957	5129517059	4799931622	4928471117	101.92	102.68	28165208	25348646	231.175	1137.687	176	173538	86.74	91.13	30418403	24430433	30418403	24430433	81.2	82.67	30418403	22869611	30418403	22163556	306166652	6.08	7.12	0	4.26	0	0.37	0	0.03	0	0.00	0	11.16	0	28165208	0	202	0	196.87	0	3.22	0	0.02	0	2.72	0	0.02	0	220.49	0	0.48	0	2267864	0	31848127	0	1355758	0	118921	0	9863	0	0	0	3554135	0	9933	0	0	0	69496	0	10360801	0	36941	0	10477171	0	84.18	0	26809450	0	205839	10123045	49.179431497432	31848127.0	28165208.0	2267864.0	1355758.0	118921.0	9863.0	0.0	3554135.0	26809450.0	88.4	7.1	4.3	0.4	0.0	0.0	11.2	84.2	101	101	101.00	38	3216660827	24.9	25.0	25.3	24.8	0.0	34.3	22.1	bulk
2819346	SRR3212828	SRP071321	SRS1329177	SRX1620346	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083854: cKO2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083854		GSM2083854	cKO2	6427444464	31819032	2016-10-31 08:44:35	4785502399	6427444464	31819032	2	31819032	index:0,count:31819032,average:101,stdev:0|index:1,count:31819032,average:101,stdev:0	GSM2083854_r1				in_mesa	28007900	0.07	2.45	0.03	4895822484	5023417828	4653851383	4816988452	102.61	103.51	27701717	25246727	225.418	1062.954	169	176744	85.2	89.84	30015624	23600966	30015624	23600966	77.97	79.75	30015624	21598202	30015624	20951057	332724722	6.80	7.29	0	4.50	0	0.31	0	0.03	0	0.00	0	12.60	0	27701717	0	202	0	196.30	0	3.73	0	0.03	0	2.65	0	0.03	0	237.16	0	0.55	0	2319277	0	31819032	0	1430822	0	97236	0	9836	0	0	0	4010243	0	10101	0	0	0	61511	0	9361889	0	37185	0	9470686	0	82.56	0	26270895	0	194076	9083368	46.803149281725	31819032.0	27701717.0	2319277.0	1430822.0	97236.0	9836.0	0.0	4010243.0	26270895.0	87.1	7.3	4.5	0.3	0.0	0.0	12.6	82.6	101	101	101.00	38	3213722232	24.4	25.6	25.7	24.3	0.0	33.8	21.2	bulk
2819377	SRR3212829	SRP071321	SRS1329177	SRX1620346	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083854: cKO2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083854		GSM2083854	cKO2	6394755006	31657203	2016-10-31 08:44:35	4776211704	6394755006	31657203	2	31657203	index:0,count:31657203,average:101,stdev:0|index:1,count:31657203,average:101,stdev:0	GSM2083854_r2				in_mesa	28007900	0.08	2.45	0.03	4861445272	4987075766	4621549076	4782271073	102.58	103.48	27528141	25092709	225.030	1060.249	169	176152	85.2	89.84	29823392	23454625	29823392	23454625	78.0	79.78	29823392	21472286	29823392	20829107	331632925	6.82	7.27	0	4.49	0	0.30	0	0.03	0	0.00	0	12.71	0	27528141	0	202	0	196.22	0	3.75	0	0.03	0	2.63	0	0.03	0	232.11	0	0.57	0	2300333	0	31657203	0	1419999	0	95736	0	9855	0	0	0	4023471	0	10149	0	0	0	60723	0	9281133	0	36806	0	9388811	0	82.47	0	26108142	0	193487	9000937	46.519595631748	31657203.0	27528141.0	2300333.0	1419999.0	95736.0	9855.0	0.0	4023471.0	26108142.0	87.0	7.3	4.5	0.3	0.0	0.0	12.7	82.5	101	101	101.00	38	3197377503	24.4	25.6	25.7	24.3	0.0	33.7	21.0	bulk
2819601	SRR3212830	SRP071321	SRS1329177	SRX1620346	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083854: cKO2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083854		GSM2083854	cKO2	6430861092	31835946	2016-10-31 08:44:35	4791920453	6430861092	31835946	2	31835946	index:0,count:31835946,average:101,stdev:0|index:1,count:31835946,average:101,stdev:0	GSM2083854_r3				in_mesa	28007900	0.07	2.45	0.03	4898239216	5026536350	4656084451	4819797016	102.62	103.52	27746359	25306476	224.739	1059.206	169	177269	85.11	89.75	30064971	23615753	30064971	23615753	77.82	79.59	30064971	21592114	30064971	20943050	335289138	6.85	7.37	0	4.50	0	0.30	0	0.03	0	0.00	0	12.51	0	27746359	0	202	0	196.24	0	3.76	0	0.03	0	2.65	0	0.03	0	214.62	0	0.57	0	2345178	0	31835946	0	1433563	0	96389	0	9552	0	0	0	3983646	0	9991	0	0	0	61241	0	9318265	0	37159	0	9426656	0	82.65	0	26312796	0	193766	9033997	46.623231113818	31835946.0	27746359.0	2345178.0	1433563.0	96389.0	9552.0	0.0	3983646.0	26312796.0	87.2	7.4	4.5	0.3	0.0	0.0	12.5	82.7	101	101	101.00	38	3215430546	24.4	25.5	25.7	24.3	0.0	33.8	21.4	bulk
2819634	SRR3212831	SRP071321	SRS1329177	SRX1620346	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083854: cKO2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083854		GSM2083854	cKO2	6439436396	31878398	2016-10-31 08:44:35	4806648564	6439436396	31878398	2	31878398	index:0,count:31878398,average:101,stdev:0|index:1,count:31878398,average:101,stdev:0	GSM2083854_r4				in_mesa	28007900	0.07	2.45	0.03	4907110053	5037057255	4665052013	4830406699	102.65	103.54	27805843	25369935	224.517	1059.145	169	177920	85.08	89.71	30128266	23657863	30128266	23657863	77.73	79.5	30128266	21612918	30128266	20965319	336968787	6.87	7.42	0	4.50	0	0.30	0	0.03	0	0.00	0	12.44	0	27805843	0	202	0	196.23	0	3.80	0	0.03	0	2.66	0	0.03	0	233.26	0	0.55	0	2366715	0	31878398	0	1433800	0	96761	0	9881	0	0	0	3965913	0	10068	0	0	0	60884	0	9329477	0	37437	0	9437866	0	82.73	0	26372043	0	194064	9039438	46.579674746475	31878398.0	27805843.0	2366715.0	1433800.0	96761.0	9881.0	0.0	3965913.0	26372043.0	87.2	7.4	4.5	0.3	0.0	0.0	12.4	82.7	101	101	101.00	38	3219718198	24.4	25.5	25.7	24.4	0.0	33.8	21.4	bulk
2819664	SRR3212832	SRP071321	SRS1329177	SRX1620346	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083854: cKO2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083854		GSM2083854	cKO2	6560108570	32475785	2016-10-31 08:44:35	4882444166	6560108570	32475785	2	32475785	index:0,count:32475785,average:101,stdev:0|index:1,count:32475785,average:101,stdev:0	GSM2083854_r5				in_mesa	28007900	0.07	2.45	0.03	4995883328	5127964198	4749469338	4917506654	102.64	103.54	28307379	25830742	224.413	1050.690	169	181320	85.1	89.73	30666390	24090037	30666390	24090037	77.76	79.53	30666390	22010979	30666390	21352311	342174705	6.85	7.36	0	4.50	0	0.30	0	0.03	0	0.00	0	12.50	0	28307379	0	202	0	196.26	0	3.76	0	0.03	0	2.65	0	0.03	0	191.66	0	0.55	0	2388869	0	32475785	0	1459811	0	97959	0	10331	0	0	0	4060116	0	10276	0	0	0	62271	0	9512604	0	38409	0	9623560	0	82.67	0	26847568	0	194588	9218960	47.376816658787	32475785.0	28307379.0	2388869.0	1459811.0	97959.0	10331.0	0.0	4060116.0	26847568.0	87.2	7.4	4.5	0.3	0.0	0.0	12.5	82.7	101	101	101.00	38	3280054285	24.4	25.5	25.7	24.4	0.0	33.9	21.5	bulk
2819696	SRR3212833	SRP071321	SRS1329177	SRX1620346	SRA382274	GEO		Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models	Translating ribosome affinity purification technology was used to isolate mRNAs from cerebellar Purkinje neurons from control (Pcp2-BacTrap; Rbm17 f/+) and mutant (Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-) mice. Overall design: RNA isolation was performed when animals were four-weeks-old (n=3 animals per genotype). Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3' poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer's protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.		GSM2083854: cKO2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			BacTRAP profiling was performed as previously described (Heiman et al. 2014) with the following modifications: One cerebellum was homogenized in 1.5 mL of homogenization buffer and 60 µg each of 19C8 and 19F7 was used for every immunoprecipitation experiment. Using NuGEN Ovation RNA-Seq System v2, purified double-stranded cDNA was generated from 10 ng of total RNA and amplified using both 3’ poly (A) selection and random priming. 2 µg of each sample was sheared using the Covaris S2 focused-ultrasonicator following the manufacturer’s protocol to obtain a final library with insert size of 400 bp. The sheared samples were quantified using the NanoDrop ND-1000 spectrophotometer and Invitrogen Qubit 2.0 DNA quantitation assay. The fragment sizes were confirmed on the Agilent Bioanalyzer to verify proper shearing. A double-stranded DNA library was produced using Illumina TruSeq DNA library preparation system and the sequencing was run on a HiSeq 2500 system.	Illumina HiSeq 2500	age;;4-weeks-old|genotype/variation;;Pcp2-BacTRAP; Pcp2-Cre; Rbm17 f/-|source_name;;Cerebellar Purkinje neurons|strain;;C57BL/6|tissue;;brain	GEO Accession;;GSM2083854		GSM2083854	cKO2	6498540788	32170994	2016-10-31 08:44:35	4822084370	6498540788	32170994	2	32170994	index:0,count:32170994,average:101,stdev:0|index:1,count:32170994,average:101,stdev:0	GSM2083854_r6				in_mesa	28007900	0.07	2.45	0.03	4952527035	5082674477	4708576130	4874488163	102.63	103.52	28061642	25610825	224.396	1053.494	169	180391	85.11	89.73	30399414	23882060	30399414	23882060	77.78	79.55	30399414	21826466	30399414	21172946	339392094	6.85	7.39	0	4.49	0	0.30	0	0.03	0	0.00	0	12.44	0	28061642	0	202	0	196.28	0	3.79	0	0.03	0	2.66	0	0.03	0	208.30	0	0.54	0	2376718	0	32170994	0	1445068	0	96190	0	10186	0	0	0	4002976	0	10429	0	0	0	61640	0	9441229	0	37799	0	9551097	0	82.73	0	26616574	0	194410	9145360	47.041613085747	32170994.0	28061642.0	2376718.0	1445068.0	96190.0	10186.0	0.0	4002976.0	26616574.0	87.2	7.4	4.5	0.3	0.0	0.0	12.4	82.7	101	101	101.00	38	3249270394	24.4	25.5	25.7	24.4	0.0	34.0	21.7	bulk
1347944	SRR3370916	SRP073200	SRS1392418	SRX1700539	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120783: RNA-Seq of N2A cells after knockdown of Mbnl1 and Mbnl2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siMbnl1/Mbnl2|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120783		GSM2120783	RNA-Seq of N2A cells after knockdown of Mbnl1 and Mbnl2	14974898600	74874493	2017-02-06 11:28:10	6309319953	14974898600	74874493	2	74874493	index:0,count:74874493,average:100,stdev:0|index:1,count:74874493,average:100,stdev:0	GSM2120783_r1						2.73	3.62	0.1	10686392267	10445849867	9667985013	9568995048	97.75	98.98	67950774	62648967	187.386	888.813	131	624385	80.29	88.87	80572882	54557802	80572882	54557802	84.33	85.44	80572882	57300916	80572882	52452323	1029246165	9.63	2.62	0	8.76	0	1.16	0	2.75	0	0.00	0	5.33	0	67950774	0	200	0	198.39	0	1.97	0	0.01	0	1.77	0	0.01	0	234.39	0	0.30	0	1961073	0	74874493	0	6558970	0	869252	0	2060681	0	0	0	3993786	0	26037	0	0	0	241577	0	32671599	0	83647	0	33022860	0	81.99	0	61391804	0	287981	28864257	100.229726961154	74874493.0	67950774.0	1961073.0	6558970.0	869252.0	2060681.0	0.0	3993786.0	61391804.0	90.8	2.6	8.8	1.2	2.8	0.0	5.3	82.0	100	100	100.00	23	7487449300	25.3	24.7	24.4	25.6	0.0	36.6	26.3	bulk
1348120	SRR3370921	SRP073200	SRS1392413	SRX1700544	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120788: RNA-Seq of N2A cells after knockdown of Zfp871, replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siZfp871|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120788		GSM2120788	RNA-Seq of N2A cells after knockdown of Zfp871, replicate 1	18003687750	72014751	2017-02-06 11:28:10	8380048588	18003687750	72014751	2	72014751	index:0,count:72014751,average:125,stdev:0|index:1,count:72014751,average:125,stdev:0	GSM2120788_r1						2.83	3.66	0.06	10320477535	10201388124	9249523372	9258853254	98.85	100.1	63234702	55516860	195.303	1204.855	137	505197	85.64	95.74	75800091	54155348	75800091	54155348	89.86	91.36	75800091	56821453	75800091	51678039	347777308	3.37	1.71	0	9.26	0	0.97	0	1.26	0	0.00	0	9.96	0	63234702	0	250	0	243.84	0	2.12	0	0.01	0	2.12	0	0.01	0	171.58	0	0.28	0	1232521	0	72014751	0	6668154	0	699633	0	909783	0	0	0	7170633	0	40475	0	0	0	340823	0	44696635	0	88439	0	45166372	0	78.55	0	56566548	0	259156	33208305	128.140212844773	72014751.0	63234702.0	1232521.0	6668154.0	699633.0	909783.0	0.0	7170633.0	56566548.0	87.8	1.7	9.3	1.0	1.3	0.0	10.0	78.5	125	125	125.00	28	9001843875	23.6	24.9	25.1	26.4	0.0	36.2	28.5	bulk
1348137	SRR3370922	SRP073200	SRS1392412	SRX1700545	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120789: RNA-Seq of N2A cells after knockdown of Zfp871, replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siZfp871|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120789		GSM2120789	RNA-Seq of N2A cells after knockdown of Zfp871, replicate 2	20593527250	82374109	2017-02-06 11:28:10	9640759334	20593527250	82374109	2	82374109	index:0,count:82374109,average:125,stdev:0|index:1,count:82374109,average:125,stdev:0	GSM2120789_r1						3.82	3.58	0.07	12257643427	12084562069	10982619665	10972069109	98.59	99.9	72103953	63753471	202.409	1162.913	137	523872	85.04	95.16	86336057	61319139	86336057	61319139	89.42	90.9	86336057	64474057	86336057	58573280	459027125	3.74	1.97	0	9.31	0	1.02	0	1.46	0	0.00	0	10.00	0	72103953	0	250	0	244.35	0	2.15	0	0.01	0	2.17	0	0.01	0	203.53	0	0.29	0	1623247	0	82374109	0	7665466	0	837493	0	1199056	0	0	0	8233607	0	45892	0	0	0	370739	0	49758174	0	104322	0	50279127	0	78.23	0	64438487	0	269668	38312968	142.074580595399	82374109.0	72103953.0	1623247.0	7665466.0	837493.0	1199056.0	0.0	8233607.0	64438487.0	87.5	2.0	9.3	1.0	1.5	0.0	10.0	78.2	125	125	125.00	28	10296763625	23.6	24.7	25.4	26.3	0.0	36.1	28.3	bulk
1348155	SRR3370923	SRP073200	SRS1392411	SRX1700546	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120790: RNA-Seq of N2A cells after non-targeting knockdown (control for Srrm4 and Zfp871 knockdowns), replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siNT|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120790		GSM2120790	RNA-Seq of N2A cells after non-targeting knockdown (control for Srrm4 and Zfp871 knockdowns), replicate 1	18720842750	74883371	2017-02-06 11:28:10	9010530703	18720842750	74883371	2	74883371	index:0,count:74883371,average:125,stdev:0|index:1,count:74883371,average:125,stdev:0	GSM2120790_r1						3.1	3.61	0.06	10844003757	10744183704	9729647706	9751114028	99.08	100.22	66001365	58116355	196.030	1203.346	137	520026	85.68	95.69	78912389	56547949	78912389	56547949	90.02	91.32	78912389	59413375	78912389	53966004	377164860	3.48	1.73	0	9.22	0	0.87	0	0.91	0	0.00	0	10.09	0	66001365	0	250	0	243.75	0	2.15	0	0.01	0	2.16	0	0.01	0	185.79	0	0.30	0	1294232	0	74883371	0	6907206	0	648671	0	679479	0	0	0	7553856	0	38373	0	0	0	342828	0	45846255	0	87227	0	46314683	0	78.91	0	59094159	0	260366	34311394	131.781392347695	74883371.0	66001365.0	1294232.0	6907206.0	648671.0	679479.0	0.0	7553856.0	59094159.0	88.1	1.7	9.2	0.9	0.9	0.0	10.1	78.9	125	125	125.00	28	9360421375	23.5	24.8	25.6	26.1	0.0	35.7	27.4	bulk
1348170	SRR3370924	SRP073200	SRS1392408	SRX1700547	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120791: RNA-Seq of N2A cells after non-targeting knockdown (control for Srrm4 and Zfp871 knockdowns), replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siNT|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120791		GSM2120791	RNA-Seq of N2A cells after non-targeting knockdown (control for Srrm4 and Zfp871 knockdowns), replicate 2	19736883500	78947534	2017-02-06 11:28:10	9172728772	19736883500	78947534	2	78947534	index:0,count:78947534,average:125,stdev:0|index:1,count:78947534,average:125,stdev:0	GSM2120791_r1						3.84	3.61	0.08	11839485270	11673256988	10670943387	10645068750	98.6	99.76	69948853	61956217	200.725	1153.668	142	522316	84.22	93.66	82930094	58908143	82930094	58908143	88.33	89.55	82930094	61783894	82930094	56327021	612156812	5.17	1.68	0	8.93	0	0.90	0	1.18	0	0.00	0	9.32	0	69948853	0	250	0	244.40	0	2.17	0	0.01	0	2.21	0	0.01	0	178.08	0	0.29	0	1327167	0	78947534	0	7051894	0	711694	0	931066	0	0	0	7355921	0	39018	0	0	0	365229	0	47076819	0	95258	0	47576324	0	79.67	0	62896959	0	266321	36050254	135.363917978680	78947534.0	69948853.0	1327167.0	7051894.0	711694.0	931066.0	0.0	7355921.0	62896959.0	88.6	1.7	8.9	0.9	1.2	0.0	9.3	79.7	125	125	125.00	28	9868441750	23.7	24.8	25.2	26.4	0.0	36.2	28.5	bulk
673981	SRR3370917	SRP073200	SRS1392410	SRX1700540	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120784: RNA-Seq of N2A cells after knockdown of Nacc1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siNacc1|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120784		GSM2120784	RNA-Seq of N2A cells after knockdown of Nacc1	17918767600	89593838	2017-02-06 11:28:10	7386301276	17918767600	89593838	2	89593838	index:0,count:89593838,average:100,stdev:0|index:1,count:89593838,average:100,stdev:0	GSM2120784_r1						3.36	3.55	0.09	13009818386	12795507471	11747796263	11675456109	98.35	99.38	82592476	76269787	187.287	848.155	131	752275	80.21	88.97	97609019	66249427	97609019	66249427	84.8	85.57	97609019	70034926	97609019	63713899	1276398839	9.81	2.63	0	9.08	0	0.93	0	1.84	0	0.00	0	5.05	0	82592476	0	200	0	198.41	0	1.98	0	0.01	0	1.76	0	0.01	0	215.17	0	0.28	0	2358600	0	89593838	0	8132066	0	829885	0	1645271	0	0	0	4526206	0	32750	0	0	0	298982	0	39215329	0	99730	0	39646791	0	83.11	0	74460410	0	294983	34768012	117.864459985830	89593838.0	82592476.0	2358600.0	8132066.0	829885.0	1645271.0	0.0	4526206.0	74460410.0	92.2	2.6	9.1	0.9	1.8	0.0	5.1	83.1	100	100	100.00	23	8959383800	25.4	24.6	24.4	25.7	0.0	36.8	26.7	bulk
673989	SRR3370918	SRP073200	SRS1392414	SRX1700541	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120785: RNA-Seq of N2A cells after non-targeting knockdown (control for Mbnl and Nacc1 knockdowns); Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siNT|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120785		GSM2120785	RNA-Seq of N2A cells after non-targeting knockdown (control for Mbnl and Nacc1 knockdowns)	18853236800	94266184	2017-02-06 11:28:10	7844553457	18853236800	94266184	2	94266184	index:0,count:94266184,average:100,stdev:0|index:1,count:94266184,average:100,stdev:0	GSM2120785_r1						3.13	3.58	0.09	13649436518	13417381332	12324834120	12244996935	98.3	99.35	86729432	79997375	187.829	870.989	131	802015	79.76	88.48	102550483	69176941	102550483	69176941	84.29	85.06	102550483	73105876	102550483	66507152	1400604667	10.26	2.67	0	9.06	0	0.93	0	1.95	0	0.00	0	5.11	0	86729432	0	200	0	198.43	0	2.00	0	0.01	0	1.80	0	0.01	0	254.39	0	0.28	0	2521329	0	94266184	0	8543334	0	876019	0	1840932	0	0	0	4819801	0	33637	0	0	0	304564	0	41044413	0	103957	0	41486571	0	82.94	0	78186098	0	301290	36292344	120.456516976999	94266184.0	86729432.0	2521329.0	8543334.0	876019.0	1840932.0	0.0	4819801.0	78186098.0	92.0	2.7	9.1	0.9	2.0	0.0	5.1	82.9	100	100	100.00	23	9426618400	25.3	24.7	24.5	25.5	0.0	36.7	26.4	bulk
673999	SRR3370919	SRP073200	SRS1392409	SRX1700542	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120786: RNA-Seq of N2A cells after knockdown of Srrm4, replicate 1; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siSrrm4|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120786		GSM2120786	RNA-Seq of N2A cells after knockdown of Srrm4, replicate 1	18026709250	72106837	2017-02-06 11:28:10	8387061626	18026709250	72106837	2	72106837	index:0,count:72106837,average:125,stdev:0|index:1,count:72106837,average:125,stdev:0	GSM2120786_r1						2.74	3.75	0.06	10743375590	10589590889	9617456907	9604359779	98.57	99.86	63176065	55615969	203.866	1228.072	137	449058	84.99	95.22	76122508	53695556	76122508	53695556	89.3	90.87	76122508	56416686	76122508	51243960	392211817	3.65	1.68	0	9.41	0	1.10	0	1.54	0	0.00	0	9.74	0	63176065	0	250	0	244.09	0	2.16	0	0.01	0	2.19	0	0.01	0	183.58	0	0.29	0	1209959	0	72106837	0	6785640	0	794597	0	1113780	0	0	0	7022395	0	38273	0	0	0	348458	0	44298027	0	87724	0	44772482	0	78.20	0	56390425	0	270136	34226878	126.702394349513	72106837.0	63176065.0	1209959.0	6785640.0	794597.0	1113780.0	0.0	7022395.0	56390425.0	87.6	1.7	9.4	1.1	1.5	0.0	9.7	78.2	125	125	125.00	28	9013354625	23.5	25.1	25.3	26.1	0.0	36.2	28.5	bulk
674054	SRR3370920	SRP073200	SRS1392415	SRX1700543	SRA410103	GEO		Multilayered control of alternative splicing regulatory networks by transcription factors (RNA-Seq)	Networks of coordinated alternative splicing (AS) events play critical roles in development and disease. However, a comprehensive knowledge of the factors that regulate these networks is lacking. We describe a high-throughput system for systematically linking trans-acting factors to endogenous RNA regulation events. Using this system, we identify hundreds of factors associated with diverse regulatory layers that positively or negatively control AS events linked to cell fate. Remarkably, more than one third of the new regulators are transcription factors. Further analyses of the zinc finger protein Zfp871 and BTB/POZ domain transcription factor Nacc1, which regulate neural and stem cell AS programs, respectively, reveal roles in controlling the expression of specific splicing regulators. Surprisingly, these proteins also appear to regulate target AS programs via binding RNA. Our results thus uncover a large ‘missing cache’ of splicing regulators among annotated transcription factors, some of which dually regulate AS through direct and indirect mechanisms. Overall design: RNA-Seq of N2A cells upon RNAi-mediated knockdown of Mbnl1/Mbnl2 or Nacc1, or control knockdown (1 replicate each), as well as upon knockdown of Srrm4 or Zfp871, or control knockdown (2 replicates each) vast-tools.AltSplicing_Mbnl.Nacc1.tab: Primary vast-tools output for Mbnl and Nacc1 knockdowns vast-tools.AltSplicing_Srrm4.Zfp871.tab: Primary vast-tools output for Srrm4 and Zfp871 knockdowns AltSplicing_Mbnl.Nacc1.tab: Filtered PSI values and differential AS annotation for Mbnl and Nacc1 knockdowns AltSplicing_Srrm4.Zfp871.tab: Filtered PSI values and differential AS annotation for Srrm4 and Zfp871 knockdowns Expression_Mbnl.Nacc1.tab: Raw and read counts per gene, normalized expression and fold-change for Mbnl and Nacc1 knockdowns Expression_Srrm4.Zfp871.tab: Raw read counts per gene, normalized expression and fold-change (edgeR analysis) for Srrm4 and Zfp871 knockdowns		GSM2120787: RNA-Seq of N2A cells after knockdown of Srrm4, replicate 2; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Total RNA was extracted either with TriZol (ThermoFisher) or the Qiagen RNasy kit. RNA libraries were prepared for sequencing using standard Illumina protocols	Illumina HiSeq 2500	cell line;;N2A|knockdown;;siSrrm4|source_name;;Neuroblastoma cells	GEO Accession;;GSM2120787		GSM2120787	RNA-Seq of N2A cells after knockdown of Srrm4, replicate 2	25037140250	100148561	2017-02-06 11:28:10	11823553182	25037140250	100148561	2	100148561	index:0,count:100148561,average:125,stdev:0|index:1,count:100148561,average:125,stdev:0	GSM2120787_r1						4.19	3.77	0.07	14671017616	14364586419	13048765193	12972392243	97.91	99.41	87276752	77093036	199.484	1234.816	142	655153	83.97	94.6	105722791	73286555	105722791	73286555	88.6	90.34	105722791	77322895	105722791	69981824	580436780	3.96	1.62	0	9.80	0	1.24	0	1.97	0	0.00	0	9.64	0	87276752	0	250	0	244.28	0	2.14	0	0.01	0	2.19	0	0.01	0	170.95	0	0.30	0	1625768	0	100148561	0	9809609	0	1239639	0	1977089	0	0	0	9655081	0	51772	0	0	0	467782	0	59968844	0	118661	0	60607059	0	77.35	0	77467143	0	292860	45721904	156.122051492181	100148561.0	87276752.0	1625768.0	9809609.0	1239639.0	1977089.0	0.0	9655081.0	77467143.0	87.1	1.6	9.8	1.2	2.0	0.0	9.6	77.4	125	125	125.00	28	12518570125	23.6	24.8	25.1	26.5	0.0	36.1	28.3	bulk
1442351	SRR3638022	SRP076212	SRS1488205	SRX1826247	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189049: 1-0-1-0-BTN34-C18-1782070111-8ul-1-IL5413-N707-N502 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189049		GSM2189049	1-0-1-0-BTN34-C18-1782070111-8ul-1-IL5413-N707-N502 BTN34 Mic-scRNA-Seq	62024700	413498	2016-07-18 10:56:32	29310964	62024700	413498	2	413498	index:0,count:413498,average:75,stdev:0|index:1,count:413498,average:75,stdev:0	GSM2189049_r4						2.05	4.13	0.01	50278269	49519520	46980508	46833913	98.49	99.69	368994	334634	207.571	1146.959	165	1730	82.71	88.64	406883	305192	406883	305192	84.89	85.69	406883	313227	406883	295027	4645032	9.24	1.03	0	5.97	0	0.23	0	0.05	0	0.00	0	10.48	0	368994	0	150	0	147.52	0	1.39	0	0.01	0	1.15	0	0.00	0	93.04	0	0.74	0	4257	0	413498	0	24703	0	971	0	187	0	0	0	43346	0	65	0	0	0	326	0	52588	0	404	0	53383	0	83.26	0	344291	0	11433	53266	4.658969649261	413498.0	368994.0	4257.0	24703.0	971.0	187.0	0.0	43346.0	344291.0	89.2	1.0	6.0	0.2	0.0	0.0	10.5	83.3	75	75	75.00	7	31012350	29.3	21.2	21.0	28.5	0.0	33.7	22.3	smartseq
1442367	SRR3638023	SRP076212	SRS1488206	SRX1826248	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189050: 1-0-1-0-BTN34-C21-1782070111-30ul-1-IL5413-N710-N502 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189050		GSM2189050	1-0-1-0-BTN34-C21-1782070111-30ul-1-IL5413-N710-N502 BTN34 Mic-scRNA-Seq	53792400	358616	2016-07-18 10:56:32	25918924	53792400	358616	2	358616	index:0,count:358616,average:75,stdev:0|index:1,count:358616,average:75,stdev:0	GSM2189050_r1						1.35	2.92	0.07	44938052	43322360	43482500	42143488	96.4	96.92	322268	307105	216.562	811.789	181	1583	43.66	45.17	340804	140718	340804	140718	44.37	43.66	340804	142987	340804	136044	22885727	50.93	0.90	0	2.98	0	0.15	0	0.26	0	0.00	0	9.73	0	322268	0	150	0	148.15	0	1.42	0	0.01	0	1.19	0	0.00	0	67.95	0	0.83	0	3240	0	358616	0	10704	0	547	0	917	0	0	0	34884	0	24	0	0	0	158	0	21279	0	241	0	21702	0	86.88	0	311564	0	10286	21602	2.100136107330	358616.0	322268.0	3240.0	10704.0	547.0	917.0	0.0	34884.0	311564.0	89.9	0.9	3.0	0.2	0.3	0.0	9.7	86.9	75	75	75.00	7	26896200	30.1	20.3	20.4	29.2	0.0	33.4	21.7	smartseq
1442383	SRR3638024	SRP076212	SRS1488206	SRX1826248	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189050: 1-0-1-0-BTN34-C21-1782070111-30ul-1-IL5413-N710-N502 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189050		GSM2189050	1-0-1-0-BTN34-C21-1782070111-30ul-1-IL5413-N710-N502 BTN34 Mic-scRNA-Seq	54325800	362172	2016-07-18 10:56:32	26130707	54325800	362172	2	362172	index:0,count:362172,average:75,stdev:0|index:1,count:362172,average:75,stdev:0	GSM2189050_r2						1.34	2.88	0.07	45567111	43961297	44103897	42781898	96.48	97.0	326326	310415	219.629	842.545	195	1539	44.0	45.5	344951	143576	344951	143576	44.64	43.95	344951	145664	344951	138712	23094963	50.68	0.92	0	2.97	0	0.16	0	0.26	0	0.00	0	9.48	0	326326	0	150	0	148.15	0	1.36	0	0.01	0	1.17	0	0.00	0	81.49	0	0.83	0	3342	0	362172	0	10746	0	572	0	928	0	0	0	34346	0	22	0	0	0	152	0	21913	0	248	0	22335	0	87.14	0	315580	0	10387	22139	2.131414267835	362172.0	326326.0	3342.0	10746.0	572.0	928.0	0.0	34346.0	315580.0	90.1	0.9	3.0	0.2	0.3	0.0	9.5	87.1	75	75	75.00	7	27162900	30.0	20.4	20.5	29.1	0.0	33.4	21.9	smartseq
1442399	SRR3638025	SRP076212	SRS1488206	SRX1826248	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189050: 1-0-1-0-BTN34-C21-1782070111-30ul-1-IL5413-N710-N502 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189050		GSM2189050	1-0-1-0-BTN34-C21-1782070111-30ul-1-IL5413-N710-N502 BTN34 Mic-scRNA-Seq	54406500	362710	2016-07-18 10:56:32	26244717	54406500	362710	2	362710	index:0,count:362710,average:75,stdev:0|index:1,count:362710,average:75,stdev:0	GSM2189050_r3						1.36	2.91	0.06	45457593	43834814	43976186	42639875	96.43	96.96	325911	310030	217.659	821.182	193	1573	44.12	45.64	344685	143797	344685	143797	44.84	44.16	344685	146131	344685	139109	22945588	50.48	0.92	0	3.00	0	0.17	0	0.25	0	0.00	0	9.73	0	325911	0	150	0	148.15	0	1.37	0	0.01	0	1.18	0	0.00	0	68.72	0	0.85	0	3336	0	362710	0	10877	0	601	0	911	0	0	0	35287	0	11	0	0	0	158	0	22344	0	257	0	22770	0	86.86	0	315034	0	10562	22704	2.149592880136	362710.0	325911.0	3336.0	10877.0	601.0	911.0	0.0	35287.0	315034.0	89.9	0.9	3.0	0.2	0.3	0.0	9.7	86.9	75	75	75.00	7	27203250	30.1	20.4	20.5	29.1	0.0	33.3	21.7	smartseq
1442431	SRR3638027	SRP076212	SRS1488207	SRX1826249	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189051: 1-0-1-0-BTN34-C23-1782070111-22ul-1-IL5413-N701-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189051		GSM2189051	1-0-1-0-BTN34-C23-1782070111-22ul-1-IL5413-N701-N503 BTN34 Mic-scRNA-Seq	50002650	333351	2016-07-18 10:56:32	24361680	50002650	333351	2	333351	index:0,count:333351,average:75,stdev:0|index:1,count:333351,average:75,stdev:0	GSM2189051_r1						0.88	2.74	0.12	43039238	42268157	41436185	40892431	98.21	98.69	301283	277802	239.789	1133.695	200	1415	55.04	57.22	320880	165833	320880	165833	56.01	55.34	320880	168738	320880	160389	17434790	40.51	0.98	0	3.44	0	0.21	0	0.08	0	0.00	0	9.33	0	301283	0	150	0	148.16	0	1.40	0	0.01	0	1.19	0	0.00	0	70.59	0	0.88	0	3262	0	333351	0	11459	0	690	0	280	0	0	0	31098	0	20	0	0	0	245	0	31673	0	269	0	32207	0	86.94	0	289824	0	12246	32156	2.625837008003	333351.0	301283.0	3262.0	11459.0	690.0	280.0	0.0	31098.0	289824.0	90.4	1.0	3.4	0.2	0.1	0.0	9.3	86.9	75	75	75.00	7	25001325	28.8	21.5	21.8	27.9	0.0	33.1	21.2	smartseq
1442446	SRR3638028	SRP076212	SRS1488207	SRX1826249	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189051: 1-0-1-0-BTN34-C23-1782070111-22ul-1-IL5413-N701-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189051		GSM2189051	1-0-1-0-BTN34-C23-1782070111-22ul-1-IL5413-N701-N503 BTN34 Mic-scRNA-Seq	51857400	345716	2016-07-18 10:56:32	25211393	51857400	345716	2	345716	index:0,count:345716,average:75,stdev:0|index:1,count:345716,average:75,stdev:0	GSM2189051_r2						0.87	2.7	0.11	44803481	43964651	43157751	42567671	98.13	98.63	313167	287957	244.038	1153.981	189	1399	55.27	57.43	333326	173083	333326	173083	56.2	55.57	333326	175997	333326	167468	18059009	40.31	0.96	0	3.41	0	0.21	0	0.10	0	0.00	0	9.11	0	313167	0	150	0	148.19	0	1.42	0	0.01	0	1.15	0	0.00	0	77.79	0	0.87	0	3303	0	345716	0	11781	0	712	0	335	0	0	0	31502	0	17	0	0	0	249	0	33836	0	265	0	34367	0	87.18	0	301386	0	12678	34338	2.708471367724	345716.0	313167.0	3303.0	11781.0	712.0	335.0	0.0	31502.0	301386.0	90.6	1.0	3.4	0.2	0.1	0.0	9.1	87.2	75	75	75.00	7	25928700	28.7	21.5	21.9	27.9	0.0	33.2	21.4	smartseq
1442447	SRR3639028	SRP076212	SRS1488457	SRX1826499	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189301: 1-rr-0-0-BTN24-C24-38ul-IL5195-707-502 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189301		GSM2189301	1-rr-0-0-BTN24-C24-38ul-IL5195-707-502 BTN24 Mic-scRNA-Seq	71630400	477536	2016-07-18 10:56:32	35352487	71630400	477536	2	477536	index:0,count:477536,average:75,stdev:0|index:1,count:477536,average:75,stdev:0	GSM2189301_r2						1.85	3.44	0.06	61169884	59845593	58487881	57499720	97.84	98.31	424196	385042	262.849	1264.003	208	1713	56.69	59.34	455925	240470	455925	240470	57.84	56.95	455925	245351	455925	230799	22919415	37.47	1.23	0	3.96	0	0.24	0	0.16	0	0.00	0	10.76	0	424196	0	150	0	147.86	0	1.57	0	0.01	0	1.13	0	0.00	0	68.77	0	1.04	0	5862	0	477536	0	18933	0	1165	0	773	0	0	0	51402	0	50	0	0	0	359	0	47524	0	732	0	48665	0	84.87	0	405263	0	19433	48468	2.494107960685	477536.0	424196.0	5862.0	18933.0	1165.0	773.0	0.0	51402.0	405263.0	88.8	1.2	4.0	0.2	0.2	0.0	10.8	84.9	75	75	75.00	7	35815200	28.8	21.5	21.9	27.7	0.0	32.7	20.6	smartseq
1442671	SRR3638036	SRP076212	SRS1488209	SRX1826251	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189053: 1-0-1-0-BTN34-C26-1782070111-38ul-1-IL5413-N703-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189053		GSM2189053	1-0-1-0-BTN34-C26-1782070111-38ul-1-IL5413-N703-N503 BTN34 Mic-scRNA-Seq	52693200	351288	2016-07-18 10:56:32	25563013	52693200	351288	2	351288	index:0,count:351288,average:75,stdev:0|index:1,count:351288,average:75,stdev:0	GSM2189053_r2						1.45	3.38	0.13	45152301	43902428	43292991	42303994	97.23	97.72	317382	296465	236.904	940.143	185	1459	54.74	57.13	338533	173741	338533	173741	56.15	55.39	338533	178218	338533	168444	17787579	39.39	0.98	0	3.78	0	0.14	0	0.11	0	0.00	0	9.40	0	317382	0	150	0	148.21	0	1.36	0	0.01	0	1.17	0	0.00	0	70.26	0	0.85	0	3445	0	351288	0	13287	0	488	0	394	0	0	0	33024	0	23	0	0	0	216	0	27711	0	323	0	28273	0	86.57	0	304095	0	12568	28011	2.228755569701	351288.0	317382.0	3445.0	13287.0	488.0	394.0	0.0	33024.0	304095.0	90.3	1.0	3.8	0.1	0.1	0.0	9.4	86.6	75	75	75.00	7	26346600	30.2	20.0	20.4	29.4	0.0	33.2	21.4	smartseq
1442687	SRR3638037	SRP076212	SRS1488209	SRX1826251	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189053: 1-0-1-0-BTN34-C26-1782070111-38ul-1-IL5413-N703-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189053		GSM2189053	1-0-1-0-BTN34-C26-1782070111-38ul-1-IL5413-N703-N503 BTN34 Mic-scRNA-Seq	51900150	346001	2016-07-18 10:56:32	25282361	51900150	346001	2	346001	index:0,count:346001,average:75,stdev:0|index:1,count:346001,average:75,stdev:0	GSM2189053_r3						1.49	3.42	0.14	44255696	43033036	42420419	41456346	97.24	97.73	311404	291216	233.530	932.287	191	1491	54.77	57.18	332412	170545	332412	170545	56.25	55.45	332412	175157	332412	165385	17428761	39.38	1.00	0	3.81	0	0.14	0	0.10	0	0.00	0	9.76	0	311404	0	150	0	148.22	0	1.35	0	0.01	0	1.16	0	0.00	0	77.85	0	0.87	0	3463	0	346001	0	13169	0	496	0	341	0	0	0	33760	0	19	0	0	0	230	0	27152	0	312	0	27713	0	86.19	0	298235	0	12359	27504	2.225422768832	346001.0	311404.0	3463.0	13169.0	496.0	341.0	0.0	33760.0	298235.0	90.0	1.0	3.8	0.1	0.1	0.0	9.8	86.2	75	75	75.00	7	25950075	30.2	20.0	20.4	29.3	0.0	33.1	21.3	smartseq
1442702	SRR3638038	SRP076212	SRS1488209	SRX1826251	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189053: 1-0-1-0-BTN34-C26-1782070111-38ul-1-IL5413-N703-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189053		GSM2189053	1-0-1-0-BTN34-C26-1782070111-38ul-1-IL5413-N703-N503 BTN34 Mic-scRNA-Seq	54831450	365543	2016-07-18 10:56:32	26283376	54831450	365543	2	365543	index:0,count:365543,average:75,stdev:0|index:1,count:365543,average:75,stdev:0	GSM2189053_r4						1.42	3.4	0.13	46801771	45504528	44886372	43875279	97.23	97.75	328995	307442	236.808	966.701	199	1528	54.88	57.27	351526	180563	351526	180563	56.3	55.57	351526	185218	351526	175219	18383544	39.28	0.98	0	3.75	0	0.15	0	0.10	0	0.00	0	9.75	0	328995	0	150	0	148.27	0	1.35	0	0.01	0	1.16	0	0.00	0	82.25	0	0.78	0	3572	0	365543	0	13702	0	533	0	373	0	0	0	35642	0	24	0	0	0	292	0	28967	0	349	0	29632	0	86.25	0	315293	0	12970	29367	2.264225134927	365543.0	328995.0	3572.0	13702.0	533.0	373.0	0.0	35642.0	315293.0	90.0	1.0	3.7	0.1	0.1	0.0	9.8	86.3	75	75	75.00	7	27415725	30.2	20.0	20.4	29.4	0.0	33.5	21.7	smartseq
1442703	SRR3639038	SRP076212	SRS1488459	SRX1826501	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189303: 1-rr-0-0-BTN24-C28-54ul-IL5195-707-503 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189303		GSM2189303	1-rr-0-0-BTN24-C28-54ul-IL5195-707-503 BTN24 Mic-scRNA-Seq	81928650	546191	2016-07-18 10:56:32	40082229	81928650	546191	2	546191	index:0,count:546191,average:75,stdev:0|index:1,count:546191,average:75,stdev:0	GSM2189303_r4						1.26	3.35	0.05	70781986	68747307	67682706	66080080	97.13	97.63	489250	437713	267.072	1342.151	207	1933	59.47	62.24	525727	290972	525727	290972	60.88	60.17	525727	297840	525727	281305	24371898	34.43	1.13	0	3.98	0	0.19	0	0.12	0	0.00	0	10.11	0	489250	0	150	0	148.00	0	1.47	0	0.01	0	1.19	0	0.00	0	103.49	0	0.95	0	6159	0	546191	0	21756	0	1020	0	681	0	0	0	55240	0	46	0	0	0	465	0	61623	0	767	0	62901	0	85.59	0	467494	0	23533	62925	2.673904729529	546191.0	489250.0	6159.0	21756.0	1020.0	681.0	0.0	55240.0	467494.0	89.6	1.1	4.0	0.2	0.1	0.0	10.1	85.6	75	75	75.00	7	40964325	28.7	21.4	22.0	27.9	0.0	32.9	20.8	smartseq
1442717	SRR3638039	SRP076212	SRS1488210	SRX1826252	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189054: 1-0-1-0-BTN34-C36-1782070111-38ul-1-IL5413-N712-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189054		GSM2189054	1-0-1-0-BTN34-C36-1782070111-38ul-1-IL5413-N712-N503 BTN34 Mic-scRNA-Seq	67648050	450987	2016-07-18 10:56:32	32373090	67648050	450987	2	450987	index:0,count:450987,average:75,stdev:0|index:1,count:450987,average:75,stdev:0	GSM2189054_r1						3.32	3.92	0.22	55862947	54908289	52487774	52015359	98.29	99.1	405529	378565	209.893	906.241	182	1966	62.03	66.06	446183	251531	446183	251531	64.21	63.39	446183	260387	446183	241357	17172732	30.74	1.18	0	5.49	0	0.22	0	0.16	0	0.00	0	9.71	0	405529	0	150	0	147.73	0	1.41	0	0.01	0	1.17	0	0.00	0	95.50	0	0.79	0	5310	0	450987	0	24761	0	975	0	703	0	0	0	43780	0	27	0	0	0	255	0	39766	0	368	0	40416	0	84.43	0	380768	0	14967	40516	2.707022115320	450987.0	405529.0	5310.0	24761.0	975.0	703.0	0.0	43780.0	380768.0	89.9	1.2	5.5	0.2	0.2	0.0	9.7	84.4	75	75	75.00	7	33824025	30.4	19.9	20.2	29.5	0.0	33.4	21.6	smartseq
1442718	SRR3639039	SRP076212	SRS1488460	SRX1826502	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189304: 1-rr-0-0-BTN24-C69-46ul-IL5195-706-505 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189304		GSM2189304	1-rr-0-0-BTN24-C69-46ul-IL5195-706-505 BTN24 Mic-scRNA-Seq	67307700	448718	2016-07-18 10:56:32	33627458	67307700	448718	2	448718	index:0,count:448718,average:75,stdev:0|index:1,count:448718,average:75,stdev:0	GSM2189304_r1						0.93	3.43	0.07	58039332	56090091	55927147	54307556	96.64	97.1	402975	371224	253.613	1171.578	200	1738	50.54	52.49	429026	203654	429026	203654	51.56	50.8	429026	207781	429026	197123	25491044	43.92	1.06	0	3.33	0	0.21	0	0.18	0	0.00	0	9.80	0	402975	0	150	0	148.17	0	1.49	0	0.01	0	1.15	0	0.00	0	100.96	0	1.00	0	4756	0	448718	0	14959	0	945	0	814	0	0	0	43984	0	35	0	0	0	285	0	40447	0	537	0	41304	0	86.47	0	388016	0	18828	41220	2.189292543021	448718.0	402975.0	4756.0	14959.0	945.0	814.0	0.0	43984.0	388016.0	89.8	1.1	3.3	0.2	0.2	0.0	9.8	86.5	75	75	75.00	7	33653850	29.0	21.3	21.5	28.2	0.0	32.6	20.8	smartseq
1442719	SRR3640039	SRP076212	SRS1488978	SRX1827020	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189822: C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189822		GSM2189822	C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	964800	6432	2016-07-18 10:56:32	367408	964800	6432	2	6432	index:0,count:6432,average:75,stdev:0|index:1,count:6432,average:75,stdev:0	GSM2189822_r4						0.56	2.36	0.0	570932	624666	533969	590973	109.41	110.68	4980	4734	137.291	588.324	91	57	81.37	87.63	5540	4052	5540	4052	71.73	73.18	5540	3572	5540	3384	57015	9.99	2.08	0	5.53	0	0.39	0	0.12	0	0.00	0	22.06	0	4980	0	150	0	146.34	0	3.71	0	0.04	0	1.13	0	0.02	0	7.72	0	0.25	0	134	0	6432	0	356	0	25	0	8	0	0	0	1419	0	1	0	0	0	12	0	1175	0	3	0	1191	0	71.89	0	4624	0	883	984	1.114382785957	6432.0	4980.0	134.0	356.0	25.0	8.0	0.0	1419.0	4624.0	77.4	2.1	5.5	0.4	0.1	0.0	22.1	71.9	75	75	75.00	6	482400	23.8	26.5	25.0	24.7	0.0	35.2	29.9	smartseq
1442829	SRR3638040	SRP076212	SRS1488210	SRX1826252	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189054: 1-0-1-0-BTN34-C36-1782070111-38ul-1-IL5413-N712-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189054		GSM2189054	1-0-1-0-BTN34-C36-1782070111-38ul-1-IL5413-N712-N503 BTN34 Mic-scRNA-Seq	68408100	456054	2016-07-18 10:56:32	32682445	68408100	456054	2	456054	index:0,count:456054,average:75,stdev:0|index:1,count:456054,average:75,stdev:0	GSM2189054_r2						3.33	3.92	0.19	56805091	55796422	53378335	52861800	98.22	99.03	411262	382709	212.927	958.948	174	1964	61.99	66.02	451995	254946	451995	254946	64.2	63.38	451995	264032	451995	244742	17486229	30.78	1.15	0	5.50	0	0.21	0	0.16	0	0.00	0	9.46	0	411262	0	150	0	147.77	0	1.39	0	0.01	0	1.18	0	0.00	0	91.21	0	0.79	0	5233	0	456054	0	25085	0	957	0	712	0	0	0	43123	0	37	0	0	0	295	0	41005	0	363	0	41700	0	84.68	0	386177	0	15442	41820	2.708198419894	456054.0	411262.0	5233.0	25085.0	957.0	712.0	0.0	43123.0	386177.0	90.2	1.1	5.5	0.2	0.2	0.0	9.5	84.7	75	75	75.00	7	34204050	30.3	20.0	20.3	29.5	0.0	33.4	21.8	smartseq
1442830	SRR3639040	SRP076212	SRS1488460	SRX1826502	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189304: 1-rr-0-0-BTN24-C69-46ul-IL5195-706-505 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189304		GSM2189304	1-rr-0-0-BTN24-C69-46ul-IL5195-706-505 BTN24 Mic-scRNA-Seq	66014400	440096	2016-07-18 10:56:32	32763819	66014400	440096	2	440096	index:0,count:440096,average:75,stdev:0|index:1,count:440096,average:75,stdev:0	GSM2189304_r2						0.91	3.39	0.08	57168291	55273516	55040330	53471787	96.69	97.15	396574	363908	256.884	1228.517	207	1694	50.89	52.9	423046	201824	423046	201824	51.95	51.22	423046	206033	423046	195408	24899232	43.55	1.06	0	3.42	0	0.20	0	0.19	0	0.00	0	9.50	0	396574	0	150	0	148.16	0	1.46	0	0.01	0	1.16	0	0.00	0	105.62	0	0.98	0	4653	0	440096	0	15047	0	902	0	815	0	0	0	41805	0	33	0	0	0	283	0	40381	0	504	0	41201	0	86.69	0	381527	0	18972	41234	2.173413451402	440096.0	396574.0	4653.0	15047.0	902.0	815.0	0.0	41805.0	381527.0	90.1	1.1	3.4	0.2	0.2	0.0	9.5	86.7	75	75	75.00	7	33007200	28.9	21.3	21.6	28.1	0.0	32.7	20.9	smartseq
1442831	SRR3640040	SRP076212	SRS1488978	SRX1827020	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189822: C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189822		GSM2189822	C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	60016800	400112	2016-07-18 10:56:32	22643473	60016800	400112	2	400112	index:0,count:400112,average:75,stdev:0|index:1,count:400112,average:75,stdev:0	GSM2189822_r5						0.77	2.61	0.01	49790457	53857954	47098428	51406528	108.17	109.15	369920	321962	221.765	1580.881	125	1740	83.47	88.52	401520	308763	401520	308763	75.98	76.86	401520	281061	401520	268081	4952525	9.95	1.48	0	5.28	0	0.39	0	0.13	0	0.00	0	7.03	0	369920	0	150	0	147.83	0	4.13	0	0.04	0	1.11	0	0.01	0	84.73	0	0.28	0	5925	0	400112	0	21120	0	1571	0	501	0	0	0	28120	0	70	0	0	0	636	0	90979	0	575	0	92260	0	87.18	0	348800	0	26719	88038	3.294958643662	400112.0	369920.0	5925.0	21120.0	1571.0	501.0	0.0	28120.0	348800.0	92.5	1.5	5.3	0.4	0.1	0.0	7.0	87.2	75	75	75.00	6	30008400	24.2	25.8	25.5	24.5	0.0	34.7	27.9	smartseq
1442844	SRR3638041	SRP076212	SRS1488210	SRX1826252	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189054: 1-0-1-0-BTN34-C36-1782070111-38ul-1-IL5413-N712-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189054		GSM2189054	1-0-1-0-BTN34-C36-1782070111-38ul-1-IL5413-N712-N503 BTN34 Mic-scRNA-Seq	67962750	453085	2016-07-18 10:56:32	32592324	67962750	453085	2	453085	index:0,count:453085,average:75,stdev:0|index:1,count:453085,average:75,stdev:0	GSM2189054_r3						3.32	3.96	0.22	56175231	55156217	52829429	52286374	98.19	98.97	407070	379239	210.980	956.638	172	1962	62.03	66.02	447169	252520	447169	252520	64.23	63.43	447169	261471	447169	242626	17300199	30.80	1.16	0	5.42	0	0.22	0	0.16	0	0.00	0	9.78	0	407070	0	150	0	147.77	0	1.41	0	0.01	0	1.15	0	0.00	0	101.94	0	0.81	0	5264	0	453085	0	24552	0	984	0	736	0	0	0	44295	0	31	0	0	0	270	0	40355	0	357	0	41013	0	84.43	0	382518	0	15232	41081	2.697019432773	453085.0	407070.0	5264.0	24552.0	984.0	736.0	0.0	44295.0	382518.0	89.8	1.2	5.4	0.2	0.2	0.0	9.8	84.4	75	75	75.00	7	33981375	30.3	20.0	20.3	29.4	0.0	33.3	21.6	smartseq
1442845	SRR3639041	SRP076212	SRS1488460	SRX1826502	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189304: 1-rr-0-0-BTN24-C69-46ul-IL5195-706-505 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189304		GSM2189304	1-rr-0-0-BTN24-C69-46ul-IL5195-706-505 BTN24 Mic-scRNA-Seq	71394300	475962	2016-07-18 10:56:32	35366628	71394300	475962	2	475962	index:0,count:475962,average:75,stdev:0|index:1,count:475962,average:75,stdev:0	GSM2189304_r3						0.92	3.41	0.07	61636713	59598491	59369145	57680821	96.69	97.16	427575	392236	256.255	1231.744	198	1782	51.08	53.07	455972	218414	455972	218414	52.13	51.38	455972	222907	455972	211444	26743981	43.39	1.09	0	3.37	0	0.20	0	0.18	0	0.00	0	9.78	0	427575	0	150	0	148.17	0	1.49	0	0.01	0	1.15	0	0.00	0	114.23	0	0.96	0	5165	0	475962	0	16051	0	973	0	870	0	0	0	46544	0	34	0	0	0	359	0	44218	0	570	0	45181	0	86.46	0	411524	0	19932	45078	2.261589403974	475962.0	427575.0	5165.0	16051.0	973.0	870.0	0.0	46544.0	411524.0	89.8	1.1	3.4	0.2	0.2	0.0	9.8	86.5	75	75	75.00	7	35697150	28.9	21.4	21.6	28.1	0.0	32.8	21.0	smartseq
1442846	SRR3640041	SRP076212	SRS1488978	SRX1827020	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189822: C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189822		GSM2189822	C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	57775800	385172	2016-07-18 10:56:32	21820406	57775800	385172	2	385172	index:0,count:385172,average:75,stdev:0|index:1,count:385172,average:75,stdev:0	GSM2189822_r6						0.79	2.62	0.02	47868896	51817004	45262649	49428852	108.25	109.2	355838	309942	220.516	1540.415	125	1751	83.38	88.47	386536	296691	386536	296691	75.89	76.77	386536	270042	386536	257452	4766750	9.96	1.47	0	5.31	0	0.38	0	0.13	0	0.00	0	7.11	0	355838	0	150	0	147.81	0	4.16	0	0.04	0	1.11	0	0.01	0	138.66	0	0.30	0	5676	0	385172	0	20462	0	1448	0	516	0	0	0	27370	0	87	0	0	0	554	0	87204	0	547	0	88392	0	87.07	0	335376	0	26338	84181	3.196180423722	385172.0	355838.0	5676.0	20462.0	1448.0	516.0	0.0	27370.0	335376.0	92.4	1.5	5.3	0.4	0.1	0.0	7.1	87.1	75	75	75.00	6	28887900	24.2	25.8	25.5	24.5	0.0	34.7	28.0	smartseq
1442847	SRR3641041	SRP076212	SRS1489235	SRX1827278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190080: G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190080		GSM2190080	G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	99150	661	2016-07-18 10:56:32	74055	99150	661	2	661	index:0,count:661,average:75,stdev:0|index:1,count:661,average:75,stdev:0	GSM2190080_r1						1.14	1.14	0.0	9405	10476	9056	10055	111.39	111.03	84	81	153.630	368.845	53	3	79.76	83.75	88	67	88	67	69.05	70.0	88	58	88	56	1608	17.10	0.00	0	0.61	0	0.15	0	0.00	0	0.00	0	87.14	0	84	0	150	0	145.22	0	2.00	0	0.02	0	1.00	0	0.02	0	2.38	0	0.18	0	0	0	661	0	4	0	1	0	0	0	0	0	576	0	0	0	0	0	0	0	21	0	0	0	21	0	12.10	0	80	0	16	16	1.000000000000	661.0	84.0	0.0	4.0	1.0	0.0	0.0	576.0	80.0	12.7	0.0	0.6	0.2	0.0	0.0	87.1	12.1	75	75	75.00	6	49575	23.1	28.1	25.2	23.6	0.0	35.2	29.8	smartseq
1442859	SRR3638042	SRP076212	SRS1488210	SRX1826252	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189054: 1-0-1-0-BTN34-C36-1782070111-38ul-1-IL5413-N712-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189054		GSM2189054	1-0-1-0-BTN34-C36-1782070111-38ul-1-IL5413-N712-N503 BTN34 Mic-scRNA-Seq	70299150	468661	2016-07-18 10:56:32	33286265	70299150	468661	2	468661	index:0,count:468661,average:75,stdev:0|index:1,count:468661,average:75,stdev:0	GSM2189054_r4						3.34	4.01	0.22	58002015	56941873	54499392	53933321	98.17	98.96	420569	391949	212.045	933.452	173	2032	61.92	65.94	462404	260412	462404	260412	64.12	63.3	462404	269680	462404	249990	17873650	30.82	1.16	0	5.48	0	0.24	0	0.16	0	0.00	0	9.86	0	420569	0	150	0	147.79	0	1.40	0	0.01	0	1.16	0	0.00	0	99.25	0	0.73	0	5422	0	468661	0	25671	0	1115	0	765	0	0	0	46212	0	36	0	0	0	315	0	41604	0	408	0	42363	0	84.26	0	394898	0	15359	42326	2.755778370988	468661.0	420569.0	5422.0	25671.0	1115.0	765.0	0.0	46212.0	394898.0	89.7	1.2	5.5	0.2	0.2	0.0	9.9	84.3	75	75	75.00	7	35149575	30.4	19.9	20.2	29.5	0.0	33.6	22.0	smartseq
1442860	SRR3639042	SRP076212	SRS1488460	SRX1826502	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189304: 1-rr-0-0-BTN24-C69-46ul-IL5195-706-505 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189304		GSM2189304	1-rr-0-0-BTN24-C69-46ul-IL5195-706-505 BTN24 Mic-scRNA-Seq	67722300	451482	2016-07-18 10:56:32	33524186	67722300	451482	2	451482	index:0,count:451482,average:75,stdev:0|index:1,count:451482,average:75,stdev:0	GSM2189304_r4						0.92	3.46	0.07	58465895	56511764	56324890	54712011	96.66	97.14	405518	372476	256.179	1187.497	203	1712	50.86	52.83	431713	206238	431713	206238	51.86	51.13	431713	210296	431713	199613	25485058	43.59	1.07	0	3.35	0	0.21	0	0.20	0	0.00	0	9.77	0	405518	0	150	0	148.18	0	1.47	0	0.01	0	1.15	0	0.00	0	95.61	0	0.97	0	4844	0	451482	0	15135	0	934	0	906	0	0	0	44124	0	35	0	0	0	302	0	41833	0	532	0	42702	0	86.47	0	390383	0	19304	42571	2.205294239536	451482.0	405518.0	4844.0	15135.0	934.0	906.0	0.0	44124.0	390383.0	89.8	1.1	3.4	0.2	0.2	0.0	9.8	86.5	75	75	75.00	7	33861150	29.0	21.3	21.6	28.2	0.0	32.8	21.0	smartseq
1442861	SRR3640042	SRP076212	SRS1488978	SRX1827020	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189822: C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189822		GSM2189822	C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	58432650	389551	2016-07-18 10:56:32	22220325	58432650	389551	2	389551	index:0,count:389551,average:75,stdev:0|index:1,count:389551,average:75,stdev:0	GSM2189822_r7						0.78	2.61	0.02	48531571	52516540	45896265	50106009	108.21	109.17	360597	314058	221.509	1550.252	130	1723	83.37	88.45	391787	300646	391787	300646	75.89	76.74	391787	273661	391787	260856	4841000	9.97	1.46	0	5.31	0	0.38	0	0.12	0	0.00	0	6.93	0	360597	0	150	0	147.82	0	4.13	0	0.04	0	1.12	0	0.01	0	87.65	0	0.29	0	5698	0	389551	0	20689	0	1494	0	480	0	0	0	26980	0	75	0	0	0	593	0	88249	0	542	0	89459	0	87.26	0	339908	0	26455	85415	3.228690228690	389551.0	360597.0	5698.0	20689.0	1494.0	480.0	0.0	26980.0	339908.0	92.6	1.5	5.3	0.4	0.1	0.0	6.9	87.3	75	75	75.00	6	29216325	24.2	25.8	25.5	24.5	0.0	34.7	27.7	smartseq
1442862	SRR3641042	SRP076212	SRS1489235	SRX1827278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190080: G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190080		GSM2190080	G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	98700	658	2016-07-18 10:56:32	74155	98700	658	2	658	index:0,count:658,average:75,stdev:0|index:1,count:658,average:75,stdev:0	GSM2190080_r2						0.0	3.3	0.0	10212	12274	9796	11708	120.19	119.52	88	84	146.179	427.034	147	4	87.5	90.59	91	77	91	77	69.32	69.41	91	61	91	59	618	6.05	0.15	0	0.46	0	0.00	0	0.00	0	0.00	0	86.63	0	88	0	150	0	147.29	0	0.00	0	0.00	0	1.00	0	0.02	0	2.37	0	0.30	0	1	0	658	0	3	0	0	0	0	0	0	0	570	0	0	0	0	0	0	0	22	0	0	0	22	0	12.92	0	85	0	18	18	1.000000000000	658.0	88.0	1.0	3.0	0.0	0.0	0.0	570.0	85.0	13.4	0.2	0.5	0.0	0.0	0.0	86.6	12.9	75	75	75.00	6	49350	22.8	28.0	24.9	24.2	0.1	35.2	28.6	smartseq
1442875	SRR3638043	SRP076212	SRS1488211	SRX1826253	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189055: 1-0-1-0-BTN34-C42-1782070111-46ul-1-IL5413-N704-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189055		GSM2189055	1-0-1-0-BTN34-C42-1782070111-46ul-1-IL5413-N704-N504 BTN34 Mic-scRNA-Seq	55053150	367021	2016-07-18 10:56:32	26159166	55053150	367021	2	367021	index:0,count:367021,average:75,stdev:0|index:1,count:367021,average:75,stdev:0	GSM2189055_r1						2.71	3.61	0.07	41874160	40932173	39558726	38996159	97.75	98.58	319096	304608	182.789	685.450	154	1659	55.38	58.68	347625	176724	347625	176724	57.13	56.27	347625	182314	347625	169454	15651009	37.38	1.23	0	4.89	0	0.18	0	0.16	0	0.00	0	12.72	0	319096	0	150	0	147.18	0	1.36	0	0.01	0	1.13	0	0.00	0	73.40	0	0.75	0	4532	0	367021	0	17954	0	647	0	577	0	0	0	46701	0	11	0	0	0	146	0	24770	0	328	0	25255	0	82.05	0	301142	0	11744	24483	2.084724114441	367021.0	319096.0	4532.0	17954.0	647.0	577.0	0.0	46701.0	301142.0	86.9	1.2	4.9	0.2	0.2	0.0	12.7	82.1	75	75	75.00	7	27526575	30.8	19.7	19.3	30.2	0.0	33.6	22.0	smartseq
1442876	SRR3639043	SRP076212	SRS1488461	SRX1826503	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189305: 1-rr-0-0-BTN24-C74-70ul-IL5195-705-507 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189305		GSM2189305	1-rr-0-0-BTN24-C74-70ul-IL5195-705-507 BTN24 Mic-scRNA-Seq	54100050	360667	2016-07-18 10:56:32	27674190	54100050	360667	2	360667	index:0,count:360667,average:75,stdev:0|index:1,count:360667,average:75,stdev:0	GSM2189305_r1						1.35	3.49	0.09	46866815	45220570	45084702	43720831	96.49	96.97	325314	299560	252.613	1155.481	189	1409	50.99	53.04	347231	165872	347231	165872	52.03	51.27	347231	169252	347231	160342	20334580	43.39	1.03	0	3.49	0	0.21	0	0.18	0	0.00	0	9.41	0	325314	0	150	0	148.00	0	1.44	0	0.01	0	1.13	0	0.00	0	76.38	0	1.11	0	3729	0	360667	0	12585	0	741	0	660	0	0	0	33952	0	33	0	0	0	234	0	32796	0	412	0	33475	0	86.71	0	312729	0	17326	33147	1.913136326908	360667.0	325314.0	3729.0	12585.0	741.0	660.0	0.0	33952.0	312729.0	90.2	1.0	3.5	0.2	0.2	0.0	9.4	86.7	75	75	75.00	7	27050025	29.4	21.1	21.5	27.9	0.0	32.1	20.0	smartseq
1442877	SRR3640043	SRP076212	SRS1488978	SRX1827020	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189822: C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189822		GSM2189822	C3_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	58055700	387038	2016-07-18 10:56:32	22107745	58055700	387038	2	387038	index:0,count:387038,average:75,stdev:0|index:1,count:387038,average:75,stdev:0	GSM2189822_r8						0.79	2.58	0.02	48215863	52192871	45605019	49809460	108.25	109.22	358092	311870	222.199	1533.071	124	1708	83.46	88.53	388899	298871	388899	298871	75.96	76.79	388899	271995	388899	259251	4779173	9.91	1.47	0	5.30	0	0.39	0	0.13	0	0.00	0	6.96	0	358092	0	150	0	147.81	0	4.08	0	0.04	0	1.11	0	0.01	0	116.11	0	0.30	0	5707	0	387038	0	20494	0	1502	0	511	0	0	0	26933	0	79	0	0	0	607	0	87675	0	521	0	88882	0	87.23	0	337598	0	26327	84863	3.223420822730	387038.0	358092.0	5707.0	20494.0	1502.0	511.0	0.0	26933.0	337598.0	92.5	1.5	5.3	0.4	0.1	0.0	7.0	87.2	75	75	75.00	6	29027850	24.2	25.8	25.5	24.5	0.0	34.7	27.8	smartseq
1442878	SRR3641043	SRP076212	SRS1489235	SRX1827278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190080: G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190080		GSM2190080	G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	95250	635	2016-07-18 10:56:32	72852	95250	635	2	635	index:0,count:635,average:75,stdev:0|index:1,count:635,average:75,stdev:0	GSM2190080_r3						1.92	1.92	0.0	11421	11950	10710	11239	104.63	104.94	97	93	139.140	255.825	93	3	77.32	82.42	104	75	104	75	73.2	73.63	104	71	104	67	1629	14.26	0.47	0	0.94	0	0.00	0	0.31	0	0.00	0	84.41	0	97	0	150	0	145.97	0	6.00	0	0.05	0	1.00	0	0.05	0	1.14	0	0.27	0	3	0	635	0	6	0	0	0	2	0	0	0	536	0	0	0	0	0	0	0	17	0	0	0	17	0	14.33	0	91	0	16	16	1.000000000000	635.0	97.0	3.0	6.0	0.0	2.0	0.0	536.0	91.0	15.3	0.5	0.9	0.0	0.3	0.0	84.4	14.3	75	75	75.00	6	47625	22.8	28.6	25.0	23.6	0.0	35.1	29.6	smartseq
1442891	SRR3638044	SRP076212	SRS1488211	SRX1826253	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189055: 1-0-1-0-BTN34-C42-1782070111-46ul-1-IL5413-N704-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189055		GSM2189055	1-0-1-0-BTN34-C42-1782070111-46ul-1-IL5413-N704-N504 BTN34 Mic-scRNA-Seq	53928000	359520	2016-07-18 10:56:32	25564939	53928000	359520	2	359520	index:0,count:359520,average:75,stdev:0|index:1,count:359520,average:75,stdev:0	GSM2189055_r2						2.71	3.67	0.06	41337562	40392585	39069307	38489982	97.71	98.52	314165	299556	184.908	678.709	130	1576	55.43	58.71	342216	174147	342216	174147	57.13	56.28	342216	179490	342216	166936	15452402	37.38	1.26	0	4.87	0	0.19	0	0.16	0	0.00	0	12.27	0	314165	0	150	0	147.20	0	1.40	0	0.01	0	1.14	0	0.00	0	68.12	0	0.76	0	4533	0	359520	0	17526	0	686	0	565	0	0	0	44104	0	24	0	0	0	147	0	24841	0	356	0	25368	0	82.51	0	296639	0	11823	24733	2.091939440074	359520.0	314165.0	4533.0	17526.0	686.0	565.0	0.0	44104.0	296639.0	87.4	1.3	4.9	0.2	0.2	0.0	12.3	82.5	75	75	75.00	7	26964000	30.7	19.7	19.3	30.3	0.0	33.6	22.2	smartseq
1442892	SRR3639044	SRP076212	SRS1488461	SRX1826503	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189305: 1-rr-0-0-BTN24-C74-70ul-IL5195-705-507 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189305		GSM2189305	1-rr-0-0-BTN24-C74-70ul-IL5195-705-507 BTN24 Mic-scRNA-Seq	52487550	349917	2016-07-18 10:56:32	26651821	52487550	349917	2	349917	index:0,count:349917,average:75,stdev:0|index:1,count:349917,average:75,stdev:0	GSM2189305_r2						1.32	3.46	0.1	45540986	43938486	43794635	42456034	96.48	96.94	315718	289710	254.871	1189.132	208	1374	51.26	53.34	337312	161826	337312	161826	52.28	51.52	337312	165065	337312	156318	19583378	43.00	0.99	0	3.52	0	0.22	0	0.18	0	0.00	0	9.38	0	315718	0	150	0	148.04	0	1.45	0	0.01	0	1.14	0	0.00	0	66.30	0	1.13	0	3449	0	349917	0	12327	0	754	0	631	0	0	0	32814	0	27	0	0	0	220	0	32217	0	369	0	32833	0	86.70	0	303391	0	17216	32655	1.896782063197	349917.0	315718.0	3449.0	12327.0	754.0	631.0	0.0	32814.0	303391.0	90.2	1.0	3.5	0.2	0.2	0.0	9.4	86.7	75	75	75.00	7	26243775	29.3	21.2	21.6	27.9	0.0	32.1	20.0	smartseq
1442893	SRR3640044	SRP076212	SRS1488979	SRX1827021	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189823: C3_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189823		GSM2189823	C3_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq	64164900	427766	2016-07-18 10:56:32	23818282	64164900	427766	2	427766	index:0,count:427766,average:75,stdev:0|index:1,count:427766,average:75,stdev:0	GSM2189823_r1						2.44	2.27	0.05	47696075	54620105	44081493	51336049	114.52	116.46	372262	348825	178.651	866.939	110	2581	77.92	84.76	414072	290056	414072	290056	64.05	64.8	414072	238451	414072	221735	5991643	12.56	2.18	0	7.03	0	0.23	0	0.07	0	0.00	0	12.67	0	372262	0	150	0	147.06	0	4.50	0	0.07	0	1.06	0	0.02	0	118.46	0	0.32	0	9336	0	427766	0	30072	0	990	0	317	0	0	0	54197	0	30	0	0	0	420	0	58724	0	586	0	59760	0	79.99	0	342190	0	11190	55842	4.990348525469	427766.0	372262.0	9336.0	30072.0	990.0	317.0	0.0	54197.0	342190.0	87.0	2.2	7.0	0.2	0.1	0.0	12.7	80.0	75	75	75.00	6	32082450	24.8	25.2	24.8	25.2	0.0	34.7	27.8	smartseq
1442894	SRR3641044	SRP076212	SRS1489235	SRX1827278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190080: G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190080		GSM2190080	G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	93450	623	2016-07-18 10:56:32	72149	93450	623	2	623	index:0,count:623,average:75,stdev:0|index:1,count:623,average:75,stdev:0	GSM2190080_r4						1.01	2.02	0.0	10686	11899	10166	11459	111.35	112.72	95	90	126.078	902.505	87	4	86.32	90.11	99	82	99	82	69.47	71.43	99	66	99	65	605	5.66	0.16	0	0.64	0	0.00	0	0.16	0	0.00	0	84.59	0	95	0	150	0	146.52	0	4.71	0	0.25	0	1.00	0	0.01	0	2.24	0	0.22	0	1	0	623	0	4	0	0	0	1	0	0	0	527	0	0	0	0	0	0	0	15	0	0	0	15	0	14.61	0	91	0	11	11	1.000000000000	623.0	95.0	1.0	4.0	0.0	1.0	0.0	527.0	91.0	15.2	0.2	0.6	0.0	0.2	0.0	84.6	14.6	75	75	75.00	6	46725	22.8	28.9	25.3	23.0	0.0	35.3	30.8	smartseq
1442908	SRR3638045	SRP076212	SRS1488211	SRX1826253	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189055: 1-0-1-0-BTN34-C42-1782070111-46ul-1-IL5413-N704-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189055		GSM2189055	1-0-1-0-BTN34-C42-1782070111-46ul-1-IL5413-N704-N504 BTN34 Mic-scRNA-Seq	53313000	355420	2016-07-18 10:56:32	25390763	53313000	355420	2	355420	index:0,count:355420,average:75,stdev:0|index:1,count:355420,average:75,stdev:0	GSM2189055_r3						2.72	3.62	0.07	40464536	39559365	38241965	37703025	97.76	98.59	308600	294688	181.817	679.557	154	1586	55.46	58.74	336053	171164	336053	171164	57.16	56.34	336053	176392	336053	164154	15104034	37.33	1.24	0	4.84	0	0.19	0	0.15	0	0.00	0	12.84	0	308600	0	150	0	147.18	0	1.39	0	0.01	0	1.16	0	0.01	0	75.27	0	0.77	0	4416	0	355420	0	17220	0	667	0	527	0	0	0	45626	0	17	0	0	0	141	0	23851	0	285	0	24294	0	81.98	0	291380	0	11345	23596	2.079858968709	355420.0	308600.0	4416.0	17220.0	667.0	527.0	0.0	45626.0	291380.0	86.8	1.2	4.8	0.2	0.1	0.0	12.8	82.0	75	75	75.00	7	26656500	30.8	19.8	19.3	30.2	0.0	33.5	22.0	smartseq
1442909	SRR3639045	SRP076212	SRS1488461	SRX1826503	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189305: 1-rr-0-0-BTN24-C74-70ul-IL5195-705-507 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189305		GSM2189305	1-rr-0-0-BTN24-C74-70ul-IL5195-705-507 BTN24 Mic-scRNA-Seq	53241750	354945	2016-07-18 10:56:32	27225829	53241750	354945	2	354945	index:0,count:354945,average:75,stdev:0|index:1,count:354945,average:75,stdev:0	GSM2189305_r3						1.33	3.44	0.09	46090138	44513810	44354727	43041637	96.58	97.04	319853	294070	252.444	1152.888	208	1381	51.42	53.47	341052	164471	341052	164471	52.37	51.63	341052	167517	341052	158815	19815753	42.99	1.03	0	3.45	0	0.22	0	0.19	0	0.00	0	9.48	0	319853	0	150	0	148.04	0	1.45	0	0.01	0	1.15	0	0.00	0	75.16	0	1.09	0	3639	0	354945	0	12249	0	788	0	667	0	0	0	33637	0	24	0	0	0	229	0	32831	0	386	0	33470	0	86.66	0	307604	0	17190	33121	1.926759744037	354945.0	319853.0	3639.0	12249.0	788.0	667.0	0.0	33637.0	307604.0	90.1	1.0	3.5	0.2	0.2	0.0	9.5	86.7	75	75	75.00	7	26620875	29.4	21.2	21.6	27.8	0.0	32.2	20.1	smartseq
1442910	SRR3640045	SRP076212	SRS1488979	SRX1827021	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189823: C3_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189823		GSM2189823	C3_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq	61793400	411956	2016-07-18 10:56:32	22943047	61793400	411956	2	411956	index:0,count:411956,average:75,stdev:0|index:1,count:411956,average:75,stdev:0	GSM2189823_r2						2.44	2.28	0.04	45879893	52512149	42386675	49331558	114.46	116.38	358353	336042	178.324	855.474	110	2394	77.85	84.71	398973	278962	398973	278962	64.04	64.73	398973	229493	398973	213169	5782176	12.60	2.25	0	7.05	0	0.22	0	0.08	0	0.00	0	12.71	0	358353	0	150	0	147.01	0	4.44	0	0.06	0	1.05	0	0.02	0	78.05	0	0.33	0	9285	0	411956	0	29055	0	926	0	316	0	0	0	52361	0	22	0	0	0	391	0	56056	0	536	0	57005	0	79.94	0	329298	0	11074	53386	4.820841610981	411956.0	358353.0	9285.0	29055.0	926.0	316.0	0.0	52361.0	329298.0	87.0	2.3	7.1	0.2	0.1	0.0	12.7	79.9	75	75	75.00	6	30896700	24.8	25.2	24.8	25.2	0.0	34.7	27.8	smartseq
1442911	SRR3641045	SRP076212	SRS1489235	SRX1827278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190080: G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190080		GSM2190080	G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	64239600	428264	2016-07-18 10:56:32	24161807	64239600	428264	2	428264	index:0,count:428264,average:75,stdev:0|index:1,count:428264,average:75,stdev:0	GSM2190080_r5						0.71	2.42	0.03	52634451	57752469	49700193	55044041	109.72	110.75	395426	349478	207.030	1414.218	126	2090	83.98	89.23	429347	332065	429347	332065	74.88	75.8	429347	296079	429347	282059	4767939	9.06	1.58	0	5.44	0	0.25	0	0.15	0	0.00	0	7.27	0	395426	0	150	0	147.73	0	4.28	0	0.05	0	1.09	0	0.01	0	118.60	0	0.28	0	6760	0	428264	0	23301	0	1083	0	630	0	0	0	31125	0	81	0	0	0	624	0	96561	0	612	0	97878	0	86.89	0	372125	0	26552	92482	3.483052124134	428264.0	395426.0	6760.0	23301.0	1083.0	630.0	0.0	31125.0	372125.0	92.3	1.6	5.4	0.3	0.1	0.0	7.3	86.9	75	75	75.00	6	32119800	24.1	25.9	25.6	24.4	0.0	34.8	28.1	smartseq
1442924	SRR3638046	SRP076212	SRS1488211	SRX1826253	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189055: 1-0-1-0-BTN34-C42-1782070111-46ul-1-IL5413-N704-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189055		GSM2189055	1-0-1-0-BTN34-C42-1782070111-46ul-1-IL5413-N704-N504 BTN34 Mic-scRNA-Seq	56369400	375796	2016-07-18 10:56:32	26493180	56369400	375796	2	375796	index:0,count:375796,average:75,stdev:0|index:1,count:375796,average:75,stdev:0	GSM2189055_r4						2.66	3.68	0.08	43098132	42136765	40761878	40191028	97.77	98.6	327159	311601	186.591	686.301	156	1612	55.62	58.87	356202	181968	356202	181968	57.27	56.43	356202	187369	356202	174410	16042720	37.22	1.26	0	4.81	0	0.18	0	0.16	0	0.00	0	12.59	0	327159	0	150	0	147.25	0	1.39	0	0.01	0	1.16	0	0.00	0	75.16	0	0.70	0	4744	0	375796	0	18064	0	689	0	620	0	0	0	47328	0	17	0	0	0	159	0	26087	0	382	0	26645	0	82.25	0	309095	0	12155	25909	2.131550802139	375796.0	327159.0	4744.0	18064.0	689.0	620.0	0.0	47328.0	309095.0	87.1	1.3	4.8	0.2	0.2	0.0	12.6	82.3	75	75	75.00	7	28184700	30.8	19.8	19.3	30.2	0.0	33.9	22.4	smartseq
1442925	SRR3639046	SRP076212	SRS1488461	SRX1826503	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189305: 1-rr-0-0-BTN24-C74-70ul-IL5195-705-507 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189305		GSM2189305	1-rr-0-0-BTN24-C74-70ul-IL5195-705-507 BTN24 Mic-scRNA-Seq	48215100	321434	2016-07-18 10:56:32	24636976	48215100	321434	2	321434	index:0,count:321434,average:75,stdev:0|index:1,count:321434,average:75,stdev:0	GSM2189305_r4						1.39	3.5	0.11	41486482	39998086	39918161	38682388	96.41	96.9	287770	264684	253.913	1163.761	211	1260	50.98	53.01	306874	146694	306874	146694	51.97	51.26	306874	149562	306874	141853	18012834	43.42	1.00	0	3.44	0	0.21	0	0.18	0	0.00	0	10.08	0	287770	0	150	0	148.01	0	1.45	0	0.01	0	1.17	0	0.00	0	68.07	0	1.16	0	3218	0	321434	0	11053	0	674	0	575	0	0	0	32415	0	24	0	0	0	239	0	28659	0	350	0	29272	0	86.09	0	276717	0	15865	29010	1.828553419477	321434.0	287770.0	3218.0	11053.0	674.0	575.0	0.0	32415.0	276717.0	89.5	1.0	3.4	0.2	0.2	0.0	10.1	86.1	75	75	75.00	7	24107550	29.5	21.1	21.5	27.9	0.0	32.1	19.9	smartseq
1442926	SRR3640046	SRP076212	SRS1488979	SRX1827021	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189823: C3_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189823		GSM2189823	C3_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq	62443050	416287	2016-07-18 10:56:32	23331827	62443050	416287	2	416287	index:0,count:416287,average:75,stdev:0|index:1,count:416287,average:75,stdev:0	GSM2189823_r3						2.47	2.26	0.04	46516164	53321140	42963478	50098002	114.63	116.61	362605	339886	179.026	872.655	110	2436	77.85	84.72	403774	282292	403774	282292	63.98	64.67	403774	231993	403774	215464	5870999	12.62	2.22	0	7.07	0	0.22	0	0.08	0	0.00	0	12.60	0	362605	0	150	0	147.06	0	4.44	0	0.06	0	1.06	0	0.02	0	107.05	0	0.32	0	9225	0	416287	0	29412	0	921	0	314	0	0	0	52447	0	28	0	0	0	386	0	57023	0	562	0	57999	0	80.04	0	333193	0	11086	54469	4.913314089843	416287.0	362605.0	9225.0	29412.0	921.0	314.0	0.0	52447.0	333193.0	87.1	2.2	7.1	0.2	0.1	0.0	12.6	80.0	75	75	75.00	6	31221525	24.8	25.2	24.8	25.2	0.0	34.7	27.7	smartseq
1442927	SRR3641046	SRP076212	SRS1489235	SRX1827278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190080: G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190080		GSM2190080	G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	61859550	412397	2016-07-18 10:56:32	23298332	61859550	412397	2	412397	index:0,count:412397,average:75,stdev:0|index:1,count:412397,average:75,stdev:0	GSM2190080_r6						0.73	2.43	0.03	50630649	55554526	47820401	52946758	109.73	110.72	380369	336005	206.433	1389.741	110	1988	83.98	89.23	413420	319440	413420	319440	74.83	75.72	413420	284648	413420	271081	4567125	9.02	1.55	0	5.43	0	0.26	0	0.13	0	0.00	0	7.37	0	380369	0	150	0	147.75	0	4.29	0	0.05	0	1.10	0	0.01	0	114.20	0	0.30	0	6412	0	412397	0	22375	0	1084	0	544	0	0	0	30400	0	74	0	0	0	635	0	93356	0	580	0	94645	0	86.81	0	357994	0	26278	89432	3.403303143314	412397.0	380369.0	6412.0	22375.0	1084.0	544.0	0.0	30400.0	357994.0	92.2	1.6	5.4	0.3	0.1	0.0	7.4	86.8	75	75	75.00	6	30929775	24.1	25.9	25.6	24.3	0.0	34.8	28.2	smartseq
1442941	SRR3638047	SRP076212	SRS1488212	SRX1826254	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189056: 1-0-1-0-BTN34-C49-1782070111-22ul-1-IL5413-N704-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189056		GSM2189056	1-0-1-0-BTN34-C49-1782070111-22ul-1-IL5413-N704-N501 BTN34 Mic-scRNA-Seq	46300650	308671	2016-07-18 10:56:32	22735691	46300650	308671	2	308671	index:0,count:308671,average:75,stdev:0|index:1,count:308671,average:75,stdev:0	GSM2189056_r1						0.71	3.0	0.07	39116764	37704807	38010370	36788687	96.39	96.79	276023	262679	227.653	920.112	206	1351	41.69	42.93	289984	115069	289984	115069	42.23	41.6	289984	116561	289984	111501	20939837	53.53	0.99	0	2.59	0	0.21	0	0.17	0	0.00	0	10.20	0	276023	0	150	0	148.19	0	1.38	0	0.01	0	1.15	0	0.00	0	65.37	0	0.95	0	3062	0	308671	0	7984	0	635	0	538	0	0	0	31475	0	20	0	0	0	156	0	18555	0	277	0	19008	0	86.84	0	268039	0	8761	18820	2.148156603127	308671.0	276023.0	3062.0	7984.0	635.0	538.0	0.0	31475.0	268039.0	89.4	1.0	2.6	0.2	0.2	0.0	10.2	86.8	75	75	75.00	7	23150325	29.3	21.0	21.2	28.5	0.0	33.1	21.4	smartseq
1442942	SRR3639047	SRP076212	SRS1488462	SRX1826504	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189306: 1-rr-0-0-BTN24-C78-46ul-IL5195-710-501 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189306		GSM2189306	1-rr-0-0-BTN24-C78-46ul-IL5195-710-501 BTN24 Mic-scRNA-Seq	58927350	392849	2016-07-18 10:56:32	28977341	58927350	392849	2	392849	index:0,count:392849,average:75,stdev:0|index:1,count:392849,average:75,stdev:0	GSM2189306_r1						0.86	3.44	0.11	50946758	49468325	49036650	47851095	97.1	97.58	353483	316967	264.114	1358.527	201	1426	58.83	61.16	376341	207970	376341	207970	59.71	59.17	376341	211067	376341	201187	18113220	35.55	1.18	0	3.43	0	0.21	0	0.16	0	0.00	0	9.65	0	353483	0	150	0	147.99	0	1.54	0	0.01	0	1.14	0	0.00	0	88.39	0	0.94	0	4648	0	392849	0	13458	0	829	0	626	0	0	0	37911	0	31	0	0	0	287	0	44777	0	505	0	45600	0	86.55	0	340025	0	20599	45233	2.195883295306	392849.0	353483.0	4648.0	13458.0	829.0	626.0	0.0	37911.0	340025.0	90.0	1.2	3.4	0.2	0.2	0.0	9.7	86.6	75	75	75.00	7	29463675	28.4	21.8	22.2	27.6	0.0	32.8	20.8	smartseq
1442943	SRR3640047	SRP076212	SRS1488979	SRX1827021	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189823: C3_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189823		GSM2189823	C3_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq	62181000	414540	2016-07-18 10:56:32	23266825	62181000	414540	2	414540	index:0,count:414540,average:75,stdev:0|index:1,count:414540,average:75,stdev:0	GSM2189823_r4						2.46	2.22	0.05	46331176	53034122	42779716	49812559	114.47	116.44	361371	338721	178.552	866.848	110	2449	77.88	84.78	402869	281426	402869	281426	64.13	64.84	402869	231748	402869	215228	5826701	12.58	2.20	0	7.10	0	0.24	0	0.07	0	0.00	0	12.51	0	361371	0	150	0	147.03	0	4.48	0	0.07	0	1.05	0	0.02	0	87.78	0	0.33	0	9115	0	414540	0	29441	0	998	0	306	0	0	0	51865	0	31	0	0	0	364	0	56321	0	548	0	57264	0	80.07	0	331930	0	11076	53725	4.850577825930	414540.0	361371.0	9115.0	29441.0	998.0	306.0	0.0	51865.0	331930.0	87.2	2.2	7.1	0.2	0.1	0.0	12.5	80.1	75	75	75.00	6	31090500	24.8	25.2	24.8	25.2	0.0	34.7	27.7	smartseq
1442956	SRR3638048	SRP076212	SRS1488212	SRX1826254	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189056: 1-0-1-0-BTN34-C49-1782070111-22ul-1-IL5413-N704-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189056		GSM2189056	1-0-1-0-BTN34-C49-1782070111-22ul-1-IL5413-N704-N501 BTN34 Mic-scRNA-Seq	46535700	310238	2016-07-18 10:56:32	22770038	46535700	310238	2	310238	index:0,count:310238,average:75,stdev:0|index:1,count:310238,average:75,stdev:0	GSM2189056_r2						0.68	2.99	0.08	39499449	38054930	38409588	37153617	96.34	96.73	278438	264616	230.162	930.438	193	1321	41.82	43.04	292553	116430	292553	116430	42.33	41.73	292553	117850	292553	112892	21110156	53.44	1.02	0	2.55	0	0.20	0	0.19	0	0.00	0	9.87	0	278438	0	150	0	148.21	0	1.40	0	0.01	0	1.15	0	0.00	0	93.07	0	0.93	0	3168	0	310238	0	7910	0	607	0	582	0	0	0	30611	0	9	0	0	0	164	0	19069	0	273	0	19515	0	87.20	0	270528	0	8912	19284	2.163824057451	310238.0	278438.0	3168.0	7910.0	607.0	582.0	0.0	30611.0	270528.0	89.7	1.0	2.5	0.2	0.2	0.0	9.9	87.2	75	75	75.00	7	23267850	29.3	21.1	21.2	28.5	0.0	33.2	21.7	smartseq
1442957	SRR3639048	SRP076212	SRS1488462	SRX1826504	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189306: 1-rr-0-0-BTN24-C78-46ul-IL5195-710-501 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189306		GSM2189306	1-rr-0-0-BTN24-C78-46ul-IL5195-710-501 BTN24 Mic-scRNA-Seq	57483150	383221	2016-07-18 10:56:32	28074131	57483150	383221	2	383221	index:0,count:383221,average:75,stdev:0|index:1,count:383221,average:75,stdev:0	GSM2189306_r2						0.83	3.39	0.11	49887066	48462530	48012597	46879193	97.14	97.64	346035	309403	266.089	1398.582	194	1333	59.01	61.36	368542	204212	368542	204212	59.91	59.37	368542	207307	368542	197584	17658515	35.40	1.18	0	3.46	0	0.22	0	0.15	0	0.00	0	9.33	0	346035	0	150	0	148.01	0	1.50	0	0.01	0	1.14	0	0.00	0	76.64	0	0.93	0	4533	0	383221	0	13241	0	829	0	590	0	0	0	35767	0	33	0	0	0	347	0	44452	0	456	0	45288	0	86.84	0	332794	0	20645	45013	2.180334221361	383221.0	346035.0	4533.0	13241.0	829.0	590.0	0.0	35767.0	332794.0	90.3	1.2	3.5	0.2	0.2	0.0	9.3	86.8	75	75	75.00	7	28741575	28.4	21.9	22.2	27.6	0.0	32.9	21.0	smartseq
1442958	SRR3640048	SRP076212	SRS1488980	SRX1827022	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189824: C3_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189824		GSM2189824	C3_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	49533450	330223	2016-07-18 10:56:32	18605258	49533450	330223	2	330223	index:0,count:330223,average:75,stdev:0|index:1,count:330223,average:75,stdev:0	GSM2189824_r1						1.1	2.36	0.04	42753652	47268935	40280771	44967762	110.56	111.64	309428	269018	239.733	1595.555	151	1407	83.06	88.42	335606	256999	335606	256999	73.32	74.27	335606	226879	335606	215857	4145476	9.70	1.55	0	5.69	0	0.27	0	0.11	0	0.00	0	5.92	0	309428	0	150	0	148.03	0	4.44	0	0.06	0	1.07	0	0.02	0	91.45	0	0.28	0	5116	0	330223	0	18779	0	877	0	365	0	0	0	19553	0	60	0	0	0	496	0	68302	0	497	0	69355	0	88.02	0	290649	0	21995	67205	3.055467151625	330223.0	309428.0	5116.0	18779.0	877.0	365.0	0.0	19553.0	290649.0	93.7	1.5	5.7	0.3	0.1	0.0	5.9	88.0	75	75	75.00	6	24766725	24.3	25.5	25.5	24.6	0.0	34.8	28.2	smartseq
1442959	SRR3641048	SRP076212	SRS1489235	SRX1827278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190080: G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190080		GSM2190080	G3_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	61960500	413070	2016-07-18 10:56:32	23514516	61960500	413070	2	413070	index:0,count:413070,average:75,stdev:0|index:1,count:413070,average:75,stdev:0	GSM2190080_r8						0.73	2.4	0.03	50885452	55815737	48059999	53194672	109.69	110.68	382051	337114	207.866	1413.484	110	2052	84.06	89.31	414658	321156	414658	321156	74.88	75.8	414658	286096	414658	272572	4560120	8.96	1.51	0	5.43	0	0.27	0	0.14	0	0.00	0	7.10	0	382051	0	150	0	147.73	0	4.34	0	0.05	0	1.09	0	0.01	0	99.14	0	0.30	0	6234	0	413070	0	22437	0	1102	0	579	0	0	0	29338	0	82	0	0	0	584	0	94301	0	610	0	95577	0	87.06	0	359614	0	26361	90434	3.430598232237	413070.0	382051.0	6234.0	22437.0	1102.0	579.0	0.0	29338.0	359614.0	92.5	1.5	5.4	0.3	0.1	0.0	7.1	87.1	75	75	75.00	6	30980250	24.1	25.9	25.6	24.3	0.0	34.7	28.1	smartseq
1442972	SRR3638049	SRP076212	SRS1488212	SRX1826254	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189056: 1-0-1-0-BTN34-C49-1782070111-22ul-1-IL5413-N704-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189056		GSM2189056	1-0-1-0-BTN34-C49-1782070111-22ul-1-IL5413-N704-N501 BTN34 Mic-scRNA-Seq	46200000	308000	2016-07-18 10:56:32	22705205	46200000	308000	2	308000	index:0,count:308000,average:75,stdev:0|index:1,count:308000,average:75,stdev:0	GSM2189056_r3						0.7	3.08	0.06	39065703	37660550	37983279	36765689	96.4	96.79	275520	261919	228.284	894.564	193	1340	42.01	43.25	289434	115757	289434	115757	42.52	41.91	289434	117157	289434	112170	20788084	53.21	0.97	0	2.55	0	0.19	0	0.18	0	0.00	0	10.17	0	275520	0	150	0	148.20	0	1.38	0	0.01	0	1.18	0	0.00	0	48.21	0	0.96	0	2981	0	308000	0	7855	0	597	0	549	0	0	0	31334	0	15	0	0	0	171	0	18819	0	256	0	19261	0	86.90	0	267665	0	8828	19067	2.159832351609	308000.0	275520.0	2981.0	7855.0	597.0	549.0	0.0	31334.0	267665.0	89.5	1.0	2.6	0.2	0.2	0.0	10.2	86.9	75	75	75.00	7	23100000	29.3	21.1	21.2	28.4	0.0	33.1	21.5	smartseq
1442973	SRR3639049	SRP076212	SRS1488462	SRX1826504	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189306: 1-rr-0-0-BTN24-C78-46ul-IL5195-710-501 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189306		GSM2189306	1-rr-0-0-BTN24-C78-46ul-IL5195-710-501 BTN24 Mic-scRNA-Seq	61914750	412765	2016-07-18 10:56:32	30240356	61914750	412765	2	412765	index:0,count:412765,average:75,stdev:0|index:1,count:412765,average:75,stdev:0	GSM2189306_r3						0.83	3.4	0.11	53523184	52001032	51488359	50284491	97.16	97.66	371228	332194	265.924	1432.888	213	1448	58.9	61.27	395656	218667	395656	218667	59.81	59.29	395656	222024	395656	211592	18993541	35.49	1.19	0	3.47	0	0.22	0	0.15	0	0.00	0	9.69	0	371228	0	150	0	148.01	0	1.52	0	0.01	0	1.14	0	0.00	0	92.87	0	0.92	0	4909	0	412765	0	14343	0	892	0	637	0	0	0	40008	0	40	0	0	0	317	0	48184	0	540	0	49081	0	86.46	0	356885	0	21391	48572	2.270674582768	412765.0	371228.0	4909.0	14343.0	892.0	637.0	0.0	40008.0	356885.0	89.9	1.2	3.5	0.2	0.2	0.0	9.7	86.5	75	75	75.00	7	30957375	28.4	21.9	22.2	27.5	0.0	33.0	21.0	smartseq
1442974	SRR3640049	SRP076212	SRS1488980	SRX1827022	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189824: C3_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189824		GSM2189824	C3_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	49301400	328676	2016-07-18 10:56:32	18560392	49301400	328676	2	328676	index:0,count:328676,average:75,stdev:0|index:1,count:328676,average:75,stdev:0	GSM2189824_r2						1.09	2.25	0.04	42510729	47010854	40019363	44691567	110.59	111.67	307489	267185	240.546	1597.921	143	1342	82.93	88.35	333831	254993	333831	254993	73.25	74.18	333831	225238	333831	214095	4145086	9.75	1.52	0	5.74	0	0.27	0	0.11	0	0.00	0	6.07	0	307489	0	150	0	148.04	0	4.40	0	0.05	0	1.06	0	0.02	0	107.57	0	0.30	0	4984	0	328676	0	18876	0	882	0	355	0	0	0	19950	0	52	0	0	0	506	0	67432	0	487	0	68477	0	87.81	0	288613	0	21984	66416	3.021106259098	328676.0	307489.0	4984.0	18876.0	882.0	355.0	0.0	19950.0	288613.0	93.6	1.5	5.7	0.3	0.1	0.0	6.1	87.8	75	75	75.00	6	24650700	24.4	25.5	25.5	24.6	0.0	34.8	28.1	smartseq
1442975	SRR3641049	SRP076212	SRS1489238	SRX1827279	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190081: G3_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190081		GSM2190081	G3_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq	53438550	356257	2016-07-18 10:56:32	19948068	53438550	356257	2	356257	index:0,count:356257,average:75,stdev:0|index:1,count:356257,average:75,stdev:0	GSM2190081_r1						2.35	2.48	0.06	41191446	46545342	38382571	43969305	113.0	114.56	315990	299318	188.312	847.942	110	1949	65.23	70.31	349112	206111	349112	206111	52.44	52.05	349112	165714	349112	152585	10589810	25.71	2.13	0	6.41	0	0.26	0	0.27	0	0.00	0	10.78	0	315990	0	150	0	147.38	0	4.25	0	0.06	0	1.06	0	0.02	0	98.66	0	0.30	0	7597	0	356257	0	22851	0	910	0	949	0	0	0	38408	0	35	0	0	0	261	0	37540	0	502	0	38338	0	82.28	0	293139	0	9206	36174	3.929393873561	356257.0	315990.0	7597.0	22851.0	910.0	949.0	0.0	38408.0	293139.0	88.7	2.1	6.4	0.3	0.3	0.0	10.8	82.3	75	75	75.00	6	26719275	25.2	24.7	24.4	25.6	0.0	34.7	27.8	smartseq
1443085	SRR3638050	SRP076212	SRS1488212	SRX1826254	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189056: 1-0-1-0-BTN34-C49-1782070111-22ul-1-IL5413-N704-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189056		GSM2189056	1-0-1-0-BTN34-C49-1782070111-22ul-1-IL5413-N704-N501 BTN34 Mic-scRNA-Seq	49585500	330570	2016-07-18 10:56:32	24031457	49585500	330570	2	330570	index:0,count:330570,average:75,stdev:0|index:1,count:330570,average:75,stdev:0	GSM2189056_r4						0.69	3.02	0.09	42033199	40518593	40867841	39570239	96.4	96.82	295729	280979	233.890	910.972	192	1390	41.64	42.87	310390	123152	310390	123152	42.11	41.52	310390	124526	310390	119286	22540368	53.63	0.98	0	2.55	0	0.18	0	0.18	0	0.00	0	10.17	0	295729	0	150	0	148.27	0	1.40	0	0.01	0	1.15	0	0.00	0	74.38	0	0.87	0	3255	0	330570	0	8445	0	611	0	605	0	0	0	33625	0	27	0	0	0	172	0	20139	0	293	0	20631	0	86.91	0	287284	0	9190	20426	2.222633297062	330570.0	295729.0	3255.0	8445.0	611.0	605.0	0.0	33625.0	287284.0	89.5	1.0	2.6	0.2	0.2	0.0	10.2	86.9	75	75	75.00	7	24792750	29.3	21.0	21.2	28.5	0.0	33.5	21.9	smartseq
1443086	SRR3639050	SRP076212	SRS1488462	SRX1826504	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189306: 1-rr-0-0-BTN24-C78-46ul-IL5195-710-501 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189306		GSM2189306	1-rr-0-0-BTN24-C78-46ul-IL5195-710-501 BTN24 Mic-scRNA-Seq	59235450	394903	2016-07-18 10:56:32	28860616	59235450	394903	2	394903	index:0,count:394903,average:75,stdev:0|index:1,count:394903,average:75,stdev:0	GSM2189306_r4						0.85	3.47	0.1	51204813	49722069	49288276	48110223	97.1	97.61	355417	317904	265.679	1398.380	191	1356	58.88	61.22	378421	209274	378421	209274	59.77	59.23	378421	212440	378421	202499	18160439	35.47	1.18	0	3.43	0	0.20	0	0.16	0	0.00	0	9.64	0	355417	0	150	0	147.98	0	1.52	0	0.01	0	1.15	0	0.00	0	78.98	0	0.92	0	4667	0	394903	0	13550	0	808	0	619	0	0	0	38059	0	32	0	0	0	329	0	45401	0	562	0	46324	0	86.57	0	341867	0	20637	45877	2.223045985366	394903.0	355417.0	4667.0	13550.0	808.0	619.0	0.0	38059.0	341867.0	90.0	1.2	3.4	0.2	0.2	0.0	9.6	86.6	75	75	75.00	7	29617725	28.4	21.8	22.2	27.6	0.0	33.0	21.0	smartseq
1443087	SRR3640050	SRP076212	SRS1488980	SRX1827022	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189824: C3_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189824		GSM2189824	C3_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	49052250	327015	2016-07-18 10:56:32	18628799	49052250	327015	2	327015	index:0,count:327015,average:75,stdev:0|index:1,count:327015,average:75,stdev:0	GSM2189824_r3						1.08	2.3	0.05	42399821	46812024	39956618	44548791	110.41	111.49	306676	266034	241.205	1624.652	134	1402	83.18	88.52	332261	255087	332261	255087	73.42	74.41	332261	225155	332261	214412	4052927	9.56	1.59	0	5.66	0	0.27	0	0.12	0	0.00	0	5.82	0	306676	0	150	0	148.00	0	4.41	0	0.05	0	1.06	0	0.02	0	84.09	0	0.30	0	5207	0	327015	0	18509	0	890	0	401	0	0	0	19048	0	51	0	0	0	503	0	68225	0	476	0	69255	0	88.12	0	288167	0	22151	67159	3.031872150242	327015.0	306676.0	5207.0	18509.0	890.0	401.0	0.0	19048.0	288167.0	93.8	1.6	5.7	0.3	0.1	0.0	5.8	88.1	75	75	75.00	6	24526125	24.4	25.5	25.5	24.6	0.0	34.6	27.7	smartseq
1443101	SRR3638051	SRP076212	SRS1488213	SRX1826255	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189057: 1-0-1-0-BTN34-C50-1782070111-22ul-1-IL5413-N705-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189057		GSM2189057	1-0-1-0-BTN34-C50-1782070111-22ul-1-IL5413-N705-N501 BTN34 Mic-scRNA-Seq	46511550	310077	2016-07-18 10:56:32	22773080	46511550	310077	2	310077	index:0,count:310077,average:75,stdev:0|index:1,count:310077,average:75,stdev:0	GSM2189057_r1						0.97	2.84	0.09	39691038	38455762	38463214	37434107	96.89	97.32	279923	260216	232.339	1050.573	205	1329	54.66	56.45	294956	153003	294956	153003	54.98	54.5	294956	153892	294956	147716	15885304	40.02	1.00	0	2.86	0	0.18	0	0.16	0	0.00	0	9.38	0	279923	0	150	0	148.06	0	1.45	0	0.01	0	1.17	0	0.00	0	65.66	0	0.92	0	3103	0	310077	0	8881	0	568	0	491	0	0	0	29095	0	15	0	0	0	172	0	27757	0	290	0	28234	0	87.41	0	271042	0	12218	27788	2.274349320674	310077.0	279923.0	3103.0	8881.0	568.0	491.0	0.0	29095.0	271042.0	90.3	1.0	2.9	0.2	0.2	0.0	9.4	87.4	75	75	75.00	7	23255775	28.9	21.4	21.6	28.1	0.0	33.2	21.6	smartseq
1443102	SRR3639051	SRP076212	SRS1488463	SRX1826505	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189307: 1-rr-0-0-BTN24-C89-38ul-IL5195-711-501 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189307		GSM2189307	1-rr-0-0-BTN24-C89-38ul-IL5195-711-501 BTN24 Mic-scRNA-Seq	65660400	437736	2016-07-18 10:56:32	32447217	65660400	437736	2	437736	index:0,count:437736,average:75,stdev:0|index:1,count:437736,average:75,stdev:0	GSM2189307_r1						1.46	3.39	0.12	56671731	55485875	54350929	53494213	97.91	98.42	393350	354390	260.662	1341.335	201	1581	59.1	61.67	421053	232457	421053	232457	59.83	59.22	421053	235350	421053	223231	20074331	35.42	1.26	0	3.75	0	0.24	0	0.14	0	0.00	0	9.76	0	393350	0	150	0	147.84	0	1.58	0	0.01	0	1.15	0	0.00	0	98.49	0	0.97	0	5521	0	437736	0	16410	0	1072	0	601	0	0	0	42713	0	51	0	0	0	323	0	47867	0	622	0	48863	0	86.11	0	376940	0	18839	48714	2.585806040660	437736.0	393350.0	5521.0	16410.0	1072.0	601.0	0.0	42713.0	376940.0	89.9	1.3	3.7	0.2	0.1	0.0	9.8	86.1	75	75	75.00	7	32830200	28.6	21.6	22.0	27.9	0.0	32.7	20.7	smartseq
1443103	SRR3640051	SRP076212	SRS1488980	SRX1827022	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189824: C3_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189824		GSM2189824	C3_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	49134450	327563	2016-07-18 10:56:32	18677713	49134450	327563	2	327563	index:0,count:327563,average:75,stdev:0|index:1,count:327563,average:75,stdev:0	GSM2189824_r4						1.08	2.31	0.03	42453826	46839931	39982590	44541420	110.33	111.4	306981	266271	241.287	1611.388	146	1352	82.97	88.37	332844	254706	332844	254706	73.43	74.41	332844	225419	332844	214472	4112805	9.69	1.56	0	5.72	0	0.27	0	0.11	0	0.00	0	5.90	0	306981	0	150	0	148.02	0	4.41	0	0.05	0	1.05	0	0.02	0	69.37	0	0.30	0	5098	0	327563	0	18745	0	894	0	362	0	0	0	19326	0	59	0	0	0	490	0	67681	0	503	0	68733	0	87.99	0	288236	0	21978	66510	3.026208026208	327563.0	306981.0	5098.0	18745.0	894.0	362.0	0.0	19326.0	288236.0	93.7	1.6	5.7	0.3	0.1	0.0	5.9	88.0	75	75	75.00	6	24567225	24.4	25.5	25.5	24.6	0.0	34.7	27.8	smartseq
1443119	SRR3638052	SRP076212	SRS1488213	SRX1826255	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189057: 1-0-1-0-BTN34-C50-1782070111-22ul-1-IL5413-N705-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189057		GSM2189057	1-0-1-0-BTN34-C50-1782070111-22ul-1-IL5413-N705-N501 BTN34 Mic-scRNA-Seq	47066250	313775	2016-07-18 10:56:32	22965681	47066250	313775	2	313775	index:0,count:313775,average:75,stdev:0|index:1,count:313775,average:75,stdev:0	GSM2189057_r2						0.98	2.92	0.06	40393743	39179713	39127873	38115772	96.99	97.41	284496	263799	235.134	1074.303	204	1335	54.71	56.53	299944	155638	299944	155638	55.06	54.57	299944	156637	299944	150235	16176020	40.05	1.03	0	2.92	0	0.18	0	0.16	0	0.00	0	8.99	0	284496	0	150	0	148.10	0	1.43	0	0.01	0	1.16	0	0.00	0	62.76	0	0.92	0	3246	0	313775	0	9165	0	571	0	509	0	0	0	28199	0	25	0	0	0	193	0	28493	0	269	0	28980	0	87.75	0	275331	0	12372	28656	2.316197866149	313775.0	284496.0	3246.0	9165.0	571.0	509.0	0.0	28199.0	275331.0	90.7	1.0	2.9	0.2	0.2	0.0	9.0	87.7	75	75	75.00	7	23533125	28.9	21.4	21.6	28.1	0.0	33.3	21.8	smartseq
1443167	SRR3638055	SRP076212	SRS1488214	SRX1826256	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189058: 1-0-1-0-BTN34-C51-1782070111-6ul-1-IL5413-N706-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189058		GSM2189058	1-0-1-0-BTN34-C51-1782070111-6ul-1-IL5413-N706-N501 BTN34 Mic-scRNA-Seq	46918050	312787	2016-07-18 10:56:32	23028783	46918050	312787	2	312787	index:0,count:312787,average:75,stdev:0|index:1,count:312787,average:75,stdev:0	GSM2189058_r1						2.48	2.37	0.23	39030691	38250503	37221439	36673857	98.0	98.53	278180	262577	218.433	911.962	182	1398	56.48	59.27	298623	157104	298623	157104	57.4	56.56	298623	159672	298623	149913	14682399	37.62	1.03	0	4.19	0	0.12	0	0.14	0	0.00	0	10.80	0	278180	0	150	0	147.82	0	1.50	0	0.01	0	1.17	0	0.00	0	66.24	0	0.95	0	3215	0	312787	0	13113	0	379	0	449	0	0	0	33779	0	4	0	0	0	132	0	23025	0	204	0	23365	0	84.74	0	265067	0	6488	23444	3.613440197287	312787.0	278180.0	3215.0	13113.0	379.0	449.0	0.0	33779.0	265067.0	88.9	1.0	4.2	0.1	0.1	0.0	10.8	84.7	75	75	75.00	7	23459025	29.3	21.1	21.3	28.3	0.0	33.1	21.4	smartseq
1443182	SRR3638056	SRP076212	SRS1488214	SRX1826256	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189058: 1-0-1-0-BTN34-C51-1782070111-6ul-1-IL5413-N706-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189058		GSM2189058	1-0-1-0-BTN34-C51-1782070111-6ul-1-IL5413-N706-N501 BTN34 Mic-scRNA-Seq	47031600	313544	2016-07-18 10:56:32	23027116	47031600	313544	2	313544	index:0,count:313544,average:75,stdev:0|index:1,count:313544,average:75,stdev:0	GSM2189058_r2						2.4	2.44	0.28	39362147	38586014	37571017	37040766	98.03	98.59	280088	263871	220.795	950.432	188	1423	56.71	59.47	300749	158831	300749	158831	57.58	56.77	300749	161287	300749	151638	14746592	37.46	1.04	0	4.15	0	0.12	0	0.14	0	0.00	0	10.41	0	280088	0	150	0	147.85	0	1.50	0	0.01	0	1.15	0	0.00	0	70.55	0	0.95	0	3275	0	313544	0	12997	0	361	0	443	0	0	0	32652	0	11	0	0	0	109	0	23043	0	203	0	23366	0	85.18	0	267091	0	6593	23531	3.569088427120	313544.0	280088.0	3275.0	12997.0	361.0	443.0	0.0	32652.0	267091.0	89.3	1.0	4.1	0.1	0.1	0.0	10.4	85.2	75	75	75.00	7	23515800	29.2	21.2	21.3	28.3	0.0	33.2	21.6	smartseq
1443183	SRR3639056	SRP076212	SRS1488464	SRX1826506	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189308: 1-rr-0-d-BTN24-C42-30ul-IL5195-709-504 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189308		GSM2189308	1-rr-0-d-BTN24-C42-30ul-IL5195-709-504 BTN24 Mic-scRNA-Seq	61752750	411685	2016-07-18 10:56:32	30397333	61752750	411685	2	411685	index:0,count:411685,average:75,stdev:0|index:1,count:411685,average:75,stdev:0	GSM2189308_r2						2.5	2.99	0.09	53018006	51781811	50545553	49640130	97.67	98.21	369516	340733	253.632	1050.299	200	1565	54.53	57.24	397508	201483	397508	201483	55.51	54.5	397508	205134	397508	191846	20758386	39.15	1.43	0	4.26	0	0.23	0	0.17	0	0.00	0	9.84	0	369516	0	150	0	147.72	0	1.64	0	0.01	0	1.14	0	0.00	0	87.18	0	0.99	0	5897	0	411685	0	17520	0	935	0	711	0	0	0	40523	0	19	0	0	0	288	0	37204	0	519	0	38030	0	85.50	0	351996	0	15470	37970	2.454427925016	411685.0	369516.0	5897.0	17520.0	935.0	711.0	0.0	40523.0	351996.0	89.8	1.4	4.3	0.2	0.2	0.0	9.8	85.5	75	75	75.00	7	30876375	28.5	21.6	22.0	27.9	0.0	33.0	21.1	smartseq
1443199	SRR3638057	SRP076212	SRS1488214	SRX1826256	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189058: 1-0-1-0-BTN34-C51-1782070111-6ul-1-IL5413-N706-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189058		GSM2189058	1-0-1-0-BTN34-C51-1782070111-6ul-1-IL5413-N706-N501 BTN34 Mic-scRNA-Seq	46815750	312105	2016-07-18 10:56:32	23009681	46815750	312105	2	312105	index:0,count:312105,average:75,stdev:0|index:1,count:312105,average:75,stdev:0	GSM2189058_r3						2.44	2.45	0.27	39003289	38190227	37219742	36646968	97.92	98.46	277863	261884	218.904	954.860	197	1398	56.89	59.68	298214	158087	298214	158087	57.84	57.03	298214	160716	298214	151064	14491014	37.15	1.06	0	4.15	0	0.11	0	0.14	0	0.00	0	10.72	0	277863	0	150	0	147.80	0	1.50	0	0.01	0	1.19	0	0.00	0	53.50	0	0.97	0	3303	0	312105	0	12957	0	354	0	435	0	0	0	33453	0	6	0	0	0	117	0	23061	0	217	0	23401	0	84.88	0	264906	0	6614	23476	3.549440580587	312105.0	277863.0	3303.0	12957.0	354.0	435.0	0.0	33453.0	264906.0	89.0	1.1	4.2	0.1	0.1	0.0	10.7	84.9	75	75	75.00	7	23407875	29.2	21.2	21.4	28.2	0.0	33.1	21.4	smartseq
1443214	SRR3638058	SRP076212	SRS1488214	SRX1826256	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189058: 1-0-1-0-BTN34-C51-1782070111-6ul-1-IL5413-N706-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189058		GSM2189058	1-0-1-0-BTN34-C51-1782070111-6ul-1-IL5413-N706-N501 BTN34 Mic-scRNA-Seq	50010150	333401	2016-07-18 10:56:32	24226536	50010150	333401	2	333401	index:0,count:333401,average:75,stdev:0|index:1,count:333401,average:75,stdev:0	GSM2189058_r4						2.45	2.4	0.25	41829928	40995113	39929852	39347679	98.0	98.54	296952	279373	223.639	974.701	180	1461	56.75	59.5	318865	168506	318865	168506	57.61	56.8	318865	171064	318865	160849	15645709	37.40	1.02	0	4.13	0	0.11	0	0.15	0	0.00	0	10.67	0	296952	0	150	0	147.92	0	1.53	0	0.01	0	1.21	0	0.00	0	70.60	0	0.88	0	3401	0	333401	0	13768	0	375	0	485	0	0	0	35589	0	5	0	0	0	150	0	25330	0	233	0	25718	0	84.94	0	283184	0	6769	25751	3.804254690501	333401.0	296952.0	3401.0	13768.0	375.0	485.0	0.0	35589.0	283184.0	89.1	1.0	4.1	0.1	0.1	0.0	10.7	84.9	75	75	75.00	7	25005075	29.2	21.1	21.3	28.3	0.0	33.4	21.8	smartseq
1443215	SRR3639058	SRP076212	SRS1488464	SRX1826506	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189308: 1-rr-0-d-BTN24-C42-30ul-IL5195-709-504 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189308		GSM2189308	1-rr-0-d-BTN24-C42-30ul-IL5195-709-504 BTN24 Mic-scRNA-Seq	65303100	435354	2016-07-18 10:56:32	32112264	65303100	435354	2	435354	index:0,count:435354,average:75,stdev:0|index:1,count:435354,average:75,stdev:0	GSM2189308_r4						2.47	3.06	0.1	56078102	54730488	53486117	52480987	97.6	98.12	390353	359165	256.616	1076.333	197	1632	54.4	57.08	420259	212362	420259	212362	55.44	54.44	420259	216404	420259	202512	22043391	39.31	1.43	0	4.21	0	0.23	0	0.18	0	0.00	0	9.93	0	390353	0	150	0	147.73	0	1.67	0	0.01	0	1.11	0	0.00	0	87.07	0	0.97	0	6227	0	435354	0	18334	0	1002	0	781	0	0	0	43218	0	21	0	0	0	281	0	39395	0	630	0	40327	0	85.45	0	372019	0	15938	40263	2.526226628184	435354.0	390353.0	6227.0	18334.0	1002.0	781.0	0.0	43218.0	372019.0	89.7	1.4	4.2	0.2	0.2	0.0	9.9	85.5	75	75	75.00	7	32651550	28.5	21.6	22.0	27.9	0.0	33.2	21.2	smartseq
1443230	SRR3638059	SRP076212	SRS1488215	SRX1826257	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189059: 1-0-1-0-BTN34-C52-1782070111-10ul-1-IL5413-N710-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189059		GSM2189059	1-0-1-0-BTN34-C52-1782070111-10ul-1-IL5413-N710-N501 BTN34 Mic-scRNA-Seq	41391750	275945	2016-07-18 10:56:32	20366317	41391750	275945	2	275945	index:0,count:275945,average:75,stdev:0|index:1,count:275945,average:75,stdev:0	GSM2189059_r1						1.48	3.45	0.25	34448133	34278795	32503988	32571362	99.51	100.21	245465	221340	227.383	1207.065	199	1153	73.16	77.64	268833	179592	268833	179592	74.38	74.25	268833	182570	268833	171753	6903132	20.04	1.13	0	5.12	0	0.21	0	0.06	0	0.00	0	10.78	0	245465	0	150	0	147.50	0	1.66	0	0.01	0	1.15	0	0.00	0	55.19	0	0.98	0	3128	0	275945	0	14140	0	586	0	155	0	0	0	29739	0	23	0	0	0	242	0	35803	0	314	0	36382	0	83.83	0	231325	0	11004	36425	3.310159941839	275945.0	245465.0	3128.0	14140.0	586.0	155.0	0.0	29739.0	231325.0	89.0	1.1	5.1	0.2	0.1	0.0	10.8	83.8	75	75	75.00	7	20695875	28.4	22.0	22.2	27.4	0.0	33.1	21.4	smartseq
1443231	SRR3639059	SRP076212	SRS1488465	SRX1826507	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189309: 1-rr-0-d-BTN24-C47-54ul-IL5195-708-505 BTN24 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN24|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189309		GSM2189309	1-rr-0-d-BTN24-C47-54ul-IL5195-708-505 BTN24 Mic-scRNA-Seq	77843250	518955	2016-07-18 10:56:32	38772568	77843250	518955	2	518955	index:0,count:518955,average:75,stdev:0|index:1,count:518955,average:75,stdev:0	GSM2189309_r1						1.55	3.24	0.07	66966623	66182658	63694175	63297550	98.83	99.38	467685	410291	250.655	1438.923	184	1961	70.96	74.67	505896	331887	505896	331887	72.1	71.74	505896	337199	505896	318869	15301626	22.85	1.22	0	4.47	0	0.27	0	0.10	0	0.00	0	9.50	0	467685	0	150	0	147.70	0	1.63	0	0.01	0	1.13	0	0.00	0	116.76	0	0.99	0	6345	0	518955	0	23222	0	1409	0	536	0	0	0	49325	0	60	0	0	0	555	0	77531	0	755	0	78901	0	85.65	0	444463	0	26500	78988	2.980679245283	518955.0	467685.0	6345.0	23222.0	1409.0	536.0	0.0	49325.0	444463.0	90.1	1.2	4.5	0.3	0.1	0.0	9.5	85.6	75	75	75.00	7	38921625	28.1	22.1	22.4	27.4	0.0	32.6	20.8	smartseq
1443343	SRR3638060	SRP076212	SRS1488215	SRX1826257	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189059: 1-0-1-0-BTN34-C52-1782070111-10ul-1-IL5413-N710-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189059		GSM2189059	1-0-1-0-BTN34-C52-1782070111-10ul-1-IL5413-N710-N501 BTN34 Mic-scRNA-Seq	41743200	278288	2016-07-18 10:56:32	20496046	41743200	278288	2	278288	index:0,count:278288,average:75,stdev:0|index:1,count:278288,average:75,stdev:0	GSM2189059_r2						1.5	3.47	0.24	34946965	34757844	32992468	33036181	99.46	100.13	248572	223587	230.331	1258.014	188	1141	73.28	77.73	271992	182163	271992	182163	74.46	74.35	271992	185093	271992	174252	6954796	19.90	1.12	0	5.10	0	0.21	0	0.06	0	0.00	0	10.41	0	248572	0	150	0	147.54	0	1.61	0	0.01	0	1.14	0	0.00	0	50.09	0	0.98	0	3130	0	278288	0	14205	0	573	0	165	0	0	0	28978	0	24	0	0	0	244	0	36675	0	312	0	37255	0	84.22	0	234367	0	11011	37346	3.391699209881	278288.0	248572.0	3130.0	14205.0	573.0	165.0	0.0	28978.0	234367.0	89.3	1.1	5.1	0.2	0.1	0.0	10.4	84.2	75	75	75.00	7	20871600	28.3	22.1	22.2	27.4	0.0	33.2	21.5	smartseq
1443359	SRR3638061	SRP076212	SRS1488215	SRX1826257	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189059: 1-0-1-0-BTN34-C52-1782070111-10ul-1-IL5413-N710-N501 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189059		GSM2189059	1-0-1-0-BTN34-C52-1782070111-10ul-1-IL5413-N710-N501 BTN34 Mic-scRNA-Seq	41750100	278334	2016-07-18 10:56:32	20551553	41750100	278334	2	278334	index:0,count:278334,average:75,stdev:0|index:1,count:278334,average:75,stdev:0	GSM2189059_r3						1.51	3.45	0.22	34804012	34611002	32851468	32907151	99.45	100.17	247826	222989	228.560	1230.340	191	1152	73.36	77.82	271426	181812	271426	181812	74.53	74.46	271426	184709	271426	173962	6916903	19.87	1.12	0	5.10	0	0.22	0	0.05	0	0.00	0	10.70	0	247826	0	150	0	147.51	0	1.67	0	0.01	0	1.17	0	0.00	0	58.94	0	0.99	0	3113	0	278334	0	14192	0	603	0	135	0	0	0	29770	0	30	0	0	0	248	0	36700	0	318	0	37296	0	83.94	0	233634	0	11041	37225	3.371524318449	278334.0	247826.0	3113.0	14192.0	603.0	135.0	0.0	29770.0	233634.0	89.0	1.1	5.1	0.2	0.0	0.0	10.7	83.9	75	75	75.00	7	20875050	28.3	22.1	22.3	27.3	0.0	33.1	21.4	smartseq
1443678	SRR3638075	SRP076212	SRS1488219	SRX1826261	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189063: 1-0-1-0-BTN34-C64-1782070111-30ul-1-IL5413-N709-N502 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189063		GSM2189063	1-0-1-0-BTN34-C64-1782070111-30ul-1-IL5413-N709-N502 BTN34 Mic-scRNA-Seq	51923100	346154	2016-07-18 10:56:32	24642114	51923100	346154	2	346154	index:0,count:346154,average:75,stdev:0|index:1,count:346154,average:75,stdev:0	GSM2189063_r1						1.95	3.41	0.11	42330172	40800313	40642074	39409677	96.39	96.97	311117	299554	197.819	640.823	165	1575	44.14	46.0	330669	137320	330669	137320	45.27	44.26	330669	140855	330669	132117	20866565	49.29	0.97	0	3.64	0	0.14	0	0.15	0	0.00	0	9.84	0	311117	0	150	0	148.00	0	1.33	0	0.01	0	1.15	0	0.00	0	89.01	0	0.74	0	3370	0	346154	0	12616	0	469	0	511	0	0	0	34057	0	16	0	0	0	140	0	18177	0	218	0	18551	0	86.23	0	298501	0	8956	18176	2.029477445288	346154.0	311117.0	3370.0	12616.0	469.0	511.0	0.0	34057.0	298501.0	89.9	1.0	3.6	0.1	0.1	0.0	9.8	86.2	75	75	75.00	7	25961550	30.9	19.6	19.4	30.0	0.0	33.6	22.1	smartseq
1443679	SRR3639075	SRP076212	SRS1488479	SRX1826520	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189322: 1_BTN10_C36_IL4791-708-508_CAGAGAGG-CTAAGCCT BTN10 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN10|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189322		GSM2189322	1_BTN10_C36_IL4791-708-508_CAGAGAGG-CTAAGCCT BTN10 Mic-scRNA-Seq	298203558	987429	2016-07-18 10:56:32	180567369	298203558	987429	2	987429	index:0,count:987429,average:151,stdev:0|index:1,count:987429,average:151,stdev:0	GSM2189322_r1						12.76	3.79	0.01	164515689	159763547	151257845	147432207	97.11	97.47	762586	715104	243.815	733.014	152	3966	57.46	62.57	834082	438159	834082	438159	62.88	60.51	834082	479508	834082	423723	55174201	33.54	1.87	0	6.31	0	0.07	0	0.15	0	0.00	0	22.55	0	762586	0	302	0	289.85	0	1.67	0	0.02	0	1.39	0	0.01	0	104.55	0	0.47	0	18434	0	987429	0	62336	0	713	0	1504	0	0	0	222626	0	82	0	0	0	728	0	182030	0	1955	0	184795	0	70.92	0	700250	0	6873	146490	21.313836752510	987429.0	762586.0	18434.0	62336.0	713.0	1504.0	0.0	222626.0	700250.0	77.2	1.9	6.3	0.1	0.2	0.0	22.5	70.9	151	151	151.00	28	149101779	27.7	22.4	21.1	28.8	0.0	35.7	19.0	smartseq
1443694	SRR3638076	SRP076212	SRS1488219	SRX1826261	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189063: 1-0-1-0-BTN34-C64-1782070111-30ul-1-IL5413-N709-N502 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189063		GSM2189063	1-0-1-0-BTN34-C64-1782070111-30ul-1-IL5413-N709-N502 BTN34 Mic-scRNA-Seq	51857100	345714	2016-07-18 10:56:32	24517803	51857100	345714	2	345714	index:0,count:345714,average:75,stdev:0|index:1,count:345714,average:75,stdev:0	GSM2189063_r2						1.88	3.47	0.13	42622949	41048826	40964099	39683502	96.31	96.87	312557	300249	200.655	683.291	185	1585	44.28	46.1	331814	138410	331814	138410	45.39	44.42	331814	141857	331814	133344	20979747	49.22	0.96	0	3.57	0	0.15	0	0.14	0	0.00	0	9.30	0	312557	0	150	0	148.02	0	1.32	0	0.01	0	1.16	0	0.00	0	59.27	0	0.73	0	3316	0	345714	0	12342	0	524	0	482	0	0	0	32151	0	14	0	0	0	149	0	18598	0	232	0	18993	0	86.84	0	300215	0	9219	18704	2.028853454822	345714.0	312557.0	3316.0	12342.0	524.0	482.0	0.0	32151.0	300215.0	90.4	1.0	3.6	0.2	0.1	0.0	9.3	86.8	75	75	75.00	7	25928550	30.8	19.6	19.5	30.1	0.0	33.7	22.3	smartseq
1443695	SRR3639076	SRP076212	SRS1488478	SRX1826521	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189323: 1_BTN10_C60_IL4791-704-508_TCCTGAGC-CTAAGCCT BTN10 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN10|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189323		GSM2189323	1_BTN10_C60_IL4791-704-508_TCCTGAGC-CTAAGCCT BTN10 Mic-scRNA-Seq	328632474	1088187	2016-07-18 10:56:32	195849307	328632474	1088187	2	1088187	index:0,count:1088187,average:151,stdev:0|index:1,count:1088187,average:151,stdev:0	GSM2189323_r1						3.13	10.47	0.06	197571360	198499872	189073143	190551026	100.47	100.78	884857	782260	262.297	1036.879	153	3789	80.58	84.38	943686	712985	943686	712985	80.05	80.03	943686	708304	943686	676295	29006876	14.68	1.42	0	3.66	0	0.14	0	0.06	0	0.00	0	18.49	0	884857	0	302	0	291.61	0	1.88	0	0.02	0	1.44	0	0.01	0	115.22	0	0.40	0	15435	0	1088187	0	39842	0	1472	0	681	0	0	0	201177	0	312	0	0	0	2624	0	428691	0	2977	0	434604	0	77.65	0	845015	0	19868	361657	18.202989732233	1088187.0	884857.0	15435.0	39842.0	1472.0	681.0	0.0	201177.0	845015.0	81.3	1.4	3.7	0.1	0.1	0.0	18.5	77.7	151	151	151.00	28	164316237	26.5	23.7	22.2	27.6	0.0	35.9	20.4	smartseq
1443710	SRR3638077	SRP076212	SRS1488219	SRX1826261	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189063: 1-0-1-0-BTN34-C64-1782070111-30ul-1-IL5413-N709-N502 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189063		GSM2189063	1-0-1-0-BTN34-C64-1782070111-30ul-1-IL5413-N709-N502 BTN34 Mic-scRNA-Seq	51829500	345530	2016-07-18 10:56:32	24604906	51829500	345530	2	345530	index:0,count:345530,average:75,stdev:0|index:1,count:345530,average:75,stdev:0	GSM2189063_r3						1.96	3.37	0.12	42326577	40779289	40636568	39392040	96.34	96.94	310722	298894	198.890	646.327	165	1596	44.08	45.95	330334	136973	330334	136973	45.19	44.18	330334	140406	330334	131704	20891953	49.36	0.94	0	3.66	0	0.14	0	0.13	0	0.00	0	9.80	0	310722	0	150	0	148.04	0	1.32	0	0.01	0	1.13	0	0.00	0	77.74	0	0.75	0	3255	0	345530	0	12636	0	489	0	441	0	0	0	33878	0	24	0	0	0	133	0	18114	0	227	0	18498	0	86.27	0	298086	0	9011	18035	2.001442681167	345530.0	310722.0	3255.0	12636.0	489.0	441.0	0.0	33878.0	298086.0	89.9	0.9	3.7	0.1	0.1	0.0	9.8	86.3	75	75	75.00	7	25914750	30.9	19.6	19.5	30.0	0.0	33.6	22.1	smartseq
1443711	SRR3639077	SRP076212	SRS1488481	SRX1826522	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189324: 1_BTN10_C70_IL4791-707-508_CTCTCTAC-CTAAGCCT BTN10 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN10|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189324		GSM2189324	1_BTN10_C70_IL4791-707-508_CTCTCTAC-CTAAGCCT BTN10 Mic-scRNA-Seq	365339366	1209733	2016-07-18 10:56:32	216667333	365339366	1209733	2	1209733	index:0,count:1209733,average:151,stdev:0|index:1,count:1209733,average:151,stdev:0	GSM2189324_r1						2.34	7.15	0.08	218091979	219002038	210109662	211754710	100.42	100.78	980200	888358	259.305	999.943	154	4471	72.57	75.48	1037400	711379	1037400	711379	70.95	70.73	1037400	695469	1037400	666623	49933239	22.90	1.47	0	3.12	0	0.14	0	0.10	0	0.00	0	18.74	0	980200	0	302	0	291.62	0	1.79	0	0.02	0	1.51	0	0.01	0	98.98	0	0.39	0	17790	0	1209733	0	37697	0	1709	0	1156	0	0	0	226668	0	340	0	0	0	2239	0	396172	0	3426	0	402177	0	77.91	0	942503	0	22488	334699	14.883448950551	1209733.0	980200.0	17790.0	37697.0	1709.0	1156.0	0.0	226668.0	942503.0	81.0	1.5	3.1	0.1	0.1	0.0	18.7	77.9	151	151	151.00	28	182669683	26.8	23.6	21.8	27.9	0.0	35.8	20.4	smartseq
1443727	SRR3638078	SRP076212	SRS1488219	SRX1826261	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189063: 1-0-1-0-BTN34-C64-1782070111-30ul-1-IL5413-N709-N502 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189063		GSM2189063	1-0-1-0-BTN34-C64-1782070111-30ul-1-IL5413-N709-N502 BTN34 Mic-scRNA-Seq	53733450	358223	2016-07-18 10:56:32	25193863	53733450	358223	2	358223	index:0,count:358223,average:75,stdev:0|index:1,count:358223,average:75,stdev:0	GSM2189063_r4						1.9	3.5	0.12	43943580	42304485	42181113	40872067	96.27	96.9	322463	310171	200.403	666.321	172	1592	44.16	46.04	342977	142414	342977	142414	45.31	44.34	342977	146096	342977	137128	21640169	49.25	0.96	0	3.68	0	0.14	0	0.14	0	0.00	0	9.70	0	322463	0	150	0	148.05	0	1.34	0	0.01	0	1.15	0	0.00	0	92.11	0	0.68	0	3453	0	358223	0	13167	0	487	0	512	0	0	0	34761	0	20	0	0	0	155	0	19169	0	230	0	19574	0	86.34	0	309296	0	9322	19170	2.056425659730	358223.0	322463.0	3453.0	13167.0	487.0	512.0	0.0	34761.0	309296.0	90.0	1.0	3.7	0.1	0.1	0.0	9.7	86.3	75	75	75.00	7	26866725	30.9	19.6	19.5	30.1	0.0	33.9	22.5	smartseq
1443743	SRR3638079	SRP076212	SRS1488220	SRX1826262	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189064: 1-0-1-0-BTN34-C75-1782070111-30ul-1-IL5413-N705-N503 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189064		GSM2189064	1-0-1-0-BTN34-C75-1782070111-30ul-1-IL5413-N705-N503 BTN34 Mic-scRNA-Seq	69095550	460637	2016-07-18 10:56:32	32974549	69095550	460637	2	460637	index:0,count:460637,average:75,stdev:0|index:1,count:460637,average:75,stdev:0	GSM2189064_r1						2.01	4.11	0.07	58007312	56593431	55415538	54399631	97.56	98.17	418003	393707	213.415	878.788	175	2027	52.83	55.35	449829	220836	449829	220836	54.13	53.31	449829	226277	449829	212712	23856066	41.13	1.03	0	4.13	0	0.21	0	0.24	0	0.00	0	8.80	0	418003	0	150	0	148.05	0	1.36	0	0.01	0	1.15	0	0.00	0	97.55	0	0.76	0	4728	0	460637	0	19017	0	977	0	1113	0	0	0	40544	0	21	0	0	0	251	0	34193	0	318	0	34783	0	86.62	0	398986	0	13132	34702	2.642552543405	460637.0	418003.0	4728.0	19017.0	977.0	1113.0	0.0	40544.0	398986.0	90.7	1.0	4.1	0.2	0.2	0.0	8.8	86.6	75	75	75.00	7	34547775	30.5	19.8	20.0	29.7	0.0	33.4	21.8	smartseq
1444174	SRR3638094	SRP076212	SRS1488223	SRX1826265	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189067: 1-0-1-0-BTN34-C94-1782070111-30ul-1-IL5413-N711-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189067		GSM2189067	1-0-1-0-BTN34-C94-1782070111-30ul-1-IL5413-N711-N504 BTN34 Mic-scRNA-Seq	61956000	413040	2016-07-18 10:56:32	29073414	61956000	413040	2	413040	index:0,count:413040,average:75,stdev:0|index:1,count:413040,average:75,stdev:0	GSM2189067_r4						1.9	3.47	0.2	43783805	42115769	41974303	40626375	96.19	96.79	342715	331564	172.131	646.265	100	1793	42.7	44.58	366698	146347	366698	146347	43.7	42.79	366698	149757	366698	140461	22050638	50.36	1.17	0	3.49	0	0.21	0	0.25	0	0.00	0	16.57	0	342715	0	150	0	146.91	0	1.37	0	0.01	0	1.21	0	0.00	0	78.26	0	0.70	0	4852	0	413040	0	14424	0	888	0	1016	0	0	0	68421	0	22	0	0	0	128	0	19825	0	296	0	20271	0	79.48	0	328291	0	9402	19231	2.045415868964	413040.0	342715.0	4852.0	14424.0	888.0	1016.0	0.0	68421.0	328291.0	83.0	1.2	3.5	0.2	0.2	0.0	16.6	79.5	75	75	75.00	7	30978000	30.9	20.0	19.2	29.9	0.0	33.8	22.2	smartseq
1444175	SRR3639094	SRP076212	SRS1488497	SRX1826539	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189341: 1_BTN15_C42_IL4884-712-501_GTAGAGGA-TAGATCGC BTN15 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN15|major cell type;;Ependy-C|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189341		GSM2189341	1_BTN15_C42_IL4884-712-501_GTAGAGGA-TAGATCGC BTN15 Mic-scRNA-Seq	236684006	1171703	2016-07-18 10:56:32	164102568	236684006	1171703	2	1171703	index:0,count:1171703,average:101,stdev:0|index:1,count:1171703,average:101,stdev:0	GSM2189341_r1						9.4	1.67	0.84	175425658	165141970	163095783	154285374	94.14	94.6	1010253	979041	236.286	623.311	166	4887	56.84	61.23	1119063	574215	1119063	574215	60.46	58.9	1119063	610840	1119063	552294	55662411	31.73	1.47	0	6.19	0	0.30	0	0.22	0	0.00	0	13.25	0	1010253	0	202	0	198.43	0	1.62	0	0.01	0	1.28	0	0.01	0	117.17	0	0.37	0	17171	0	1171703	0	72523	0	3534	0	2624	0	0	0	155292	0	9	0	0	0	1108	0	82824	0	2332	0	86273	0	80.03	0	937730	0	3849	83850	21.784879189400	1171703.0	1010253.0	17171.0	72523.0	3534.0	2624.0	0.0	155292.0	937730.0	86.2	1.5	6.2	0.3	0.2	0.0	13.3	80.0	101	101	101.00	38	118342003	28.2	21.0	21.2	29.6	0.0	33.3	15.5	smartseq
1444190	SRR3638095	SRP076212	SRS1488224	SRX1826266	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189068: 1-0-1-0-BTN35-C03-1782070112-18ul-1-IL5413-N712-N504 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189068		GSM2189068	1-0-1-0-BTN35-C03-1782070112-18ul-1-IL5413-N712-N504 BTN35 Mic-scRNA-Seq	64211400	428076	2016-07-18 10:56:32	30407158	64211400	428076	2	428076	index:0,count:428076,average:75,stdev:0|index:1,count:428076,average:75,stdev:0	GSM2189068_r1						1.8	3.53	0.15	44579392	43217250	42219688	41254366	96.94	97.71	350065	329818	173.666	816.535	111	1835	60.0	63.42	381765	210055	381765	210055	61.54	61.1	381765	215442	381765	202371	14214174	31.89	1.30	0	4.40	0	0.24	0	0.16	0	0.00	0	17.82	0	350065	0	150	0	146.52	0	1.39	0	0.01	0	1.14	0	0.00	0	64.21	0	0.75	0	5564	0	428076	0	18847	0	1045	0	673	0	0	0	76293	0	46	0	0	0	233	0	37746	0	319	0	38344	0	77.37	0	331218	0	13565	36859	2.717213416882	428076.0	350065.0	5564.0	18847.0	1045.0	673.0	0.0	76293.0	331218.0	81.8	1.3	4.4	0.2	0.2	0.0	17.8	77.4	75	75	75.00	7	32105700	30.1	20.7	20.0	29.2	0.0	33.5	21.8	smartseq
1444191	SRR3639095	SRP076212	SRS1488498	SRX1826540	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189342: 1_BTN15_C45_IL4884-710-503_CGAGGCTG-TATCCTCT BTN15 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN15|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189342		GSM2189342	1_BTN15_C45_IL4884-710-503_CGAGGCTG-TATCCTCT BTN15 Mic-scRNA-Seq	409995562	2029681	2016-07-18 10:56:32	285867892	409995562	2029681	2	2029681	index:0,count:2029681,average:101,stdev:0|index:1,count:2029681,average:101,stdev:0	GSM2189342_r1						2.57	1.95	0.19	313412640	306822395	300789170	295264232	97.9	98.16	1797090	1667349	242.651	705.573	154	8265	72.18	75.29	1934397	1297152	1934397	1297152	73.03	72.8	1934397	1312357	1934397	1254266	69478373	22.17	1.03	0	3.65	0	0.67	0	0.06	0	0.00	0	10.72	0	1797090	0	202	0	198.64	0	1.66	0	0.01	0	1.17	0	0.01	0	214.91	0	0.42	0	20859	0	2029681	0	74144	0	13655	0	1271	0	0	0	217665	0	139	0	0	0	2235	0	348421	0	4432	0	355227	0	84.89	0	1722946	0	6063	339899	56.061190829622	2029681.0	1797090.0	20859.0	74144.0	13655.0	1271.0	0.0	217665.0	1722946.0	88.5	1.0	3.7	0.7	0.1	0.0	10.7	84.9	101	101	101.00	38	204997781	26.9	22.7	22.5	27.9	0.0	34.4	17.2	smartseq
1445951	SRR3638103	SRP076212	SRS1488226	SRX1826268	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189070: 1-0-1-0-BTN35-C14-1782070112-18ul-1-IL5413-N701-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189070		GSM2189070	1-0-1-0-BTN35-C14-1782070112-18ul-1-IL5413-N701-N506 BTN35 Mic-scRNA-Seq	50341050	335607	2016-07-18 10:56:32	24732024	50341050	335607	2	335607	index:0,count:335607,average:75,stdev:0|index:1,count:335607,average:75,stdev:0	GSM2189070_r1						1.29	3.4	0.06	42934542	42094432	40779799	40231293	98.04	98.65	301532	269157	243.304	1319.632	199	1315	68.81	72.52	326971	207491	326971	207491	70.69	70.34	326971	213157	326971	201245	10570365	24.62	0.98	0	4.60	0	0.26	0	0.09	0	0.00	0	9.80	0	301532	0	150	0	147.87	0	1.49	0	0.01	0	1.15	0	0.00	0	67.12	0	0.92	0	3283	0	335607	0	15422	0	879	0	310	0	0	0	32886	0	28	0	0	0	286	0	43884	0	342	0	44540	0	85.25	0	286110	0	15544	44539	2.865349974267	335607.0	301532.0	3283.0	15422.0	879.0	310.0	0.0	32886.0	286110.0	89.8	1.0	4.6	0.3	0.1	0.0	9.8	85.3	75	75	75.00	7	25170525	28.6	21.8	22.1	27.4	0.0	33.0	21.0	smartseq
1446175	SRR3638111	SRP076212	SRS1488229	SRX1826270	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189072: 1-0-1-0-BTN35-C18-1782070112-22ul-1-IL5413-N704-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189072		GSM2189072	1-0-1-0-BTN35-C18-1782070112-22ul-1-IL5413-N704-N506 BTN35 Mic-scRNA-Seq	69266250	461775	2016-07-18 10:56:32	33188876	69266250	461775	2	461775	index:0,count:461775,average:75,stdev:0|index:1,count:461775,average:75,stdev:0	GSM2189072_r1						1.99	3.4	0.05	54511869	53472702	51703945	51153749	98.09	98.94	405412	379144	200.340	886.368	154	1858	64.14	67.69	441048	260043	441048	260043	65.31	65.0	441048	264759	441048	249731	15731244	28.86	1.12	0	4.59	0	0.23	0	0.16	0	0.00	0	11.82	0	405412	0	150	0	147.37	0	1.42	0	0.01	0	1.16	0	0.00	0	87.49	0	0.80	0	5161	0	461775	0	21217	0	1067	0	728	0	0	0	54568	0	35	0	0	0	371	0	40560	0	478	0	41444	0	83.20	0	384195	0	14478	40706	2.811576184556	461775.0	405412.0	5161.0	21217.0	1067.0	728.0	0.0	54568.0	384195.0	87.8	1.1	4.6	0.2	0.2	0.0	11.8	83.2	75	75	75.00	7	34633125	30.3	20.4	20.1	29.3	0.0	33.3	21.5	smartseq
1446191	SRR3638112	SRP076212	SRS1488229	SRX1826270	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189072: 1-0-1-0-BTN35-C18-1782070112-22ul-1-IL5413-N704-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189072		GSM2189072	1-0-1-0-BTN35-C18-1782070112-22ul-1-IL5413-N704-N506 BTN35 Mic-scRNA-Seq	69368850	462459	2016-07-18 10:56:32	33126019	69368850	462459	2	462459	index:0,count:462459,average:75,stdev:0|index:1,count:462459,average:75,stdev:0	GSM2189072_r2						2.02	3.38	0.05	55059408	53988976	52177124	51592209	98.06	98.88	408226	380615	203.211	889.473	157	1849	64.28	67.89	444402	262394	444402	262394	65.54	65.24	444402	267563	444402	252168	15789552	28.68	1.14	0	4.69	0	0.24	0	0.16	0	0.00	0	11.32	0	408226	0	150	0	147.41	0	1.41	0	0.01	0	1.18	0	0.00	0	87.62	0	0.79	0	5267	0	462459	0	21702	0	1114	0	761	0	0	0	52358	0	44	0	0	0	324	0	41571	0	459	0	42398	0	83.58	0	386524	0	14758	41798	2.832226588969	462459.0	408226.0	5267.0	21702.0	1114.0	761.0	0.0	52358.0	386524.0	88.3	1.1	4.7	0.2	0.2	0.0	11.3	83.6	75	75	75.00	7	34684425	30.2	20.4	20.2	29.3	0.0	33.5	21.7	smartseq
1446207	SRR3638113	SRP076212	SRS1488229	SRX1826270	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189072: 1-0-1-0-BTN35-C18-1782070112-22ul-1-IL5413-N704-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189072		GSM2189072	1-0-1-0-BTN35-C18-1782070112-22ul-1-IL5413-N704-N506 BTN35 Mic-scRNA-Seq	69189900	461266	2016-07-18 10:56:32	33209444	69189900	461266	2	461266	index:0,count:461266,average:75,stdev:0|index:1,count:461266,average:75,stdev:0	GSM2189072_r3						1.97	3.37	0.06	54554046	53492463	51711396	51138930	98.05	98.89	405156	378450	201.312	875.700	161	1901	64.32	67.91	440656	260601	440656	260601	65.59	65.28	440656	265749	440656	250500	15622075	28.64	1.11	0	4.64	0	0.26	0	0.16	0	0.00	0	11.75	0	405156	0	150	0	147.39	0	1.41	0	0.01	0	1.11	0	0.00	0	72.20	0	0.82	0	5141	0	461266	0	21416	0	1184	0	725	0	0	0	54201	0	39	0	0	0	319	0	41066	0	490	0	41914	0	83.19	0	383740	0	14716	41346	2.809594998641	461266.0	405156.0	5141.0	21416.0	1184.0	725.0	0.0	54201.0	383740.0	87.8	1.1	4.6	0.3	0.2	0.0	11.8	83.2	75	75	75.00	7	34594950	30.3	20.4	20.1	29.2	0.0	33.3	21.5	smartseq
1446223	SRR3638114	SRP076212	SRS1488229	SRX1826270	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189072: 1-0-1-0-BTN35-C18-1782070112-22ul-1-IL5413-N704-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189072		GSM2189072	1-0-1-0-BTN35-C18-1782070112-22ul-1-IL5413-N704-N506 BTN35 Mic-scRNA-Seq	71912250	479415	2016-07-18 10:56:32	34052068	71912250	479415	2	479415	index:0,count:479415,average:75,stdev:0|index:1,count:479415,average:75,stdev:0	GSM2189072_r4						1.97	3.35	0.05	56666653	55582291	53728514	53157884	98.09	98.94	420572	392301	202.851	880.316	155	1905	64.17	67.74	457334	269896	457334	269896	65.39	65.11	457334	275004	457334	259446	16375383	28.90	1.18	0	4.62	0	0.25	0	0.16	0	0.00	0	11.86	0	420572	0	150	0	147.43	0	1.42	0	0.01	0	1.15	0	0.00	0	86.29	0	0.75	0	5662	0	479415	0	22127	0	1202	0	761	0	0	0	56880	0	29	0	0	0	333	0	43296	0	527	0	44185	0	83.11	0	398445	0	14991	43553	2.905276499233	479415.0	420572.0	5662.0	22127.0	1202.0	761.0	0.0	56880.0	398445.0	87.7	1.2	4.6	0.3	0.2	0.0	11.9	83.1	75	75	75.00	7	35956125	30.3	20.3	20.1	29.3	0.0	33.6	21.9	smartseq
1446239	SRR3638115	SRP076212	SRS1488228	SRX1826271	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189073: 1-0-1-0-BTN35-C21-1782070112-46ul-1-IL5413-N710-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189073		GSM2189073	1-0-1-0-BTN35-C21-1782070112-46ul-1-IL5413-N710-N506 BTN35 Mic-scRNA-Seq	65582250	437215	2016-07-18 10:56:32	31210700	65582250	437215	2	437215	index:0,count:437215,average:75,stdev:0|index:1,count:437215,average:75,stdev:0	GSM2189073_r1						2.24	3.56	0.13	47680472	45994911	45561386	44298159	96.46	97.23	369214	354929	178.837	668.998	99	1825	45.78	47.95	397448	169010	397448	169010	46.99	46.09	397448	173507	397448	162464	22591369	47.38	1.24	0	3.83	0	0.19	0	0.26	0	0.00	0	15.10	0	369214	0	150	0	146.91	0	1.40	0	0.01	0	1.19	0	0.00	0	87.44	0	0.78	0	5403	0	437215	0	16751	0	832	0	1142	0	0	0	66027	0	17	0	0	0	168	0	24764	0	345	0	25294	0	80.62	0	352463	0	11735	24233	2.065019173413	437215.0	369214.0	5403.0	16751.0	832.0	1142.0	0.0	66027.0	352463.0	84.4	1.2	3.8	0.2	0.3	0.0	15.1	80.6	75	75	75.00	7	32791125	30.5	20.4	19.6	29.4	0.0	33.4	21.6	smartseq
1446271	SRR3638117	SRP076212	SRS1488228	SRX1826271	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189073: 1-0-1-0-BTN35-C21-1782070112-46ul-1-IL5413-N710-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189073		GSM2189073	1-0-1-0-BTN35-C21-1782070112-46ul-1-IL5413-N710-N506 BTN35 Mic-scRNA-Seq	65778150	438521	2016-07-18 10:56:32	31351280	65778150	438521	2	438521	index:0,count:438521,average:75,stdev:0|index:1,count:438521,average:75,stdev:0	GSM2189073_r3						2.2	3.48	0.14	47920307	46267527	45792771	44570790	96.55	97.33	370341	355845	179.978	706.598	154	1892	45.91	48.08	398746	170014	398746	170014	47.1	46.21	398746	174422	398746	163395	22649930	47.27	1.22	0	3.82	0	0.19	0	0.25	0	0.00	0	15.10	0	370341	0	150	0	146.99	0	1.40	0	0.01	0	1.18	0	0.00	0	87.70	0	0.79	0	5339	0	438521	0	16757	0	828	0	1117	0	0	0	66235	0	12	0	0	0	181	0	24921	0	360	0	25474	0	80.63	0	353584	0	11894	24445	2.055237935093	438521.0	370341.0	5339.0	16757.0	828.0	1117.0	0.0	66235.0	353584.0	84.5	1.2	3.8	0.2	0.3	0.0	15.1	80.6	75	75	75.00	7	32889075	30.5	20.5	19.6	29.4	0.0	33.4	21.6	smartseq
1446303	SRR3638119	SRP076212	SRS1488230	SRX1826272	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189074: 1-0-1-0-BTN35-C26-1782070112-10ul-1-IL5413-N707-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189074		GSM2189074	1-0-1-0-BTN35-C26-1782070112-10ul-1-IL5413-N707-N507 BTN35 Mic-scRNA-Seq	56552400	377016	2016-07-18 10:56:32	26661051	56552400	377016	2	377016	index:0,count:377016,average:75,stdev:0|index:1,count:377016,average:75,stdev:0	GSM2189074_r1						1.57	3.88	0.18	38510700	37879003	36298809	36025839	98.36	99.25	305230	282971	176.062	896.388	79	1660	76.18	80.94	336105	232526	336105	232526	77.23	77.78	336105	235741	336105	223432	6145595	15.96	1.40	0	4.76	0	0.23	0	0.20	0	0.00	0	18.61	0	305230	0	150	0	146.09	0	1.44	0	0.01	0	1.17	0	0.01	0	59.01	0	0.72	0	5282	0	377016	0	17957	0	856	0	749	0	0	0	70181	0	52	0	0	0	256	0	39435	0	328	0	40071	0	76.20	0	287273	0	11260	38983	3.462078152753	377016.0	305230.0	5282.0	17957.0	856.0	749.0	0.0	70181.0	287273.0	81.0	1.4	4.8	0.2	0.2	0.0	18.6	76.2	75	75	75.00	7	28276200	29.4	21.5	20.2	28.9	0.0	33.5	21.8	smartseq
1446415	SRR3638120	SRP076212	SRS1488230	SRX1826272	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189074: 1-0-1-0-BTN35-C26-1782070112-10ul-1-IL5413-N707-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189074		GSM2189074	1-0-1-0-BTN35-C26-1782070112-10ul-1-IL5413-N707-N507 BTN35 Mic-scRNA-Seq	55390200	369268	2016-07-18 10:56:32	26027433	55390200	369268	2	369268	index:0,count:369268,average:75,stdev:0|index:1,count:369268,average:75,stdev:0	GSM2189074_r2						1.59	3.81	0.13	38667458	38050105	36462012	36203901	98.4	99.29	305396	282131	178.377	935.958	81	1644	76.3	81.05	336378	233015	336378	233015	77.34	77.88	336378	236194	336378	223892	6134215	15.86	1.40	0	4.85	0	0.24	0	0.19	0	0.00	0	16.86	0	305396	0	150	0	146.14	0	1.46	0	0.01	0	1.16	0	0.01	0	78.20	0	0.72	0	5177	0	369268	0	17900	0	885	0	715	0	0	0	62272	0	44	0	0	0	256	0	40076	0	362	0	40738	0	77.86	0	287496	0	11440	39409	3.444842657343	369268.0	305396.0	5177.0	17900.0	885.0	715.0	0.0	62272.0	287496.0	82.7	1.4	4.8	0.2	0.2	0.0	16.9	77.9	75	75	75.00	7	27695100	29.3	21.4	20.3	29.0	0.0	33.7	22.1	smartseq
1446431	SRR3638121	SRP076212	SRS1488230	SRX1826272	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189074: 1-0-1-0-BTN35-C26-1782070112-10ul-1-IL5413-N707-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189074		GSM2189074	1-0-1-0-BTN35-C26-1782070112-10ul-1-IL5413-N707-N507 BTN35 Mic-scRNA-Seq	56664750	377765	2016-07-18 10:56:32	26722551	56664750	377765	2	377765	index:0,count:377765,average:75,stdev:0|index:1,count:377765,average:75,stdev:0	GSM2189074_r3						1.58	3.88	0.14	38815809	38197190	36625588	36356179	98.41	99.26	307055	284252	177.231	927.688	77	1621	76.39	81.09	337890	234573	337890	234573	77.4	77.91	337890	237664	337890	225362	6138269	15.81	1.40	0	4.71	0	0.24	0	0.20	0	0.00	0	18.28	0	307055	0	150	0	146.12	0	1.44	0	0.01	0	1.13	0	0.00	0	42.50	0	0.72	0	5272	0	377765	0	17797	0	891	0	771	0	0	0	69048	0	43	0	0	0	263	0	40112	0	342	0	40760	0	76.57	0	289258	0	11382	39578	3.477244772448	377765.0	307055.0	5272.0	17797.0	891.0	771.0	0.0	69048.0	289258.0	81.3	1.4	4.7	0.2	0.2	0.0	18.3	76.6	75	75	75.00	7	28332375	29.4	21.5	20.3	28.8	0.0	33.5	21.9	smartseq
1446543	SRR3638128	SRP076212	SRS1488232	SRX1826274	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189076: 1-0-1-0-BTN35-C53-1782070112-30ul-1-IL5413-N705-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189076		GSM2189076	1-0-1-0-BTN35-C53-1782070112-30ul-1-IL5413-N705-N505 BTN35 Mic-scRNA-Seq	71840400	478936	2016-07-18 10:56:32	34409521	71840400	478936	2	478936	index:0,count:478936,average:75,stdev:0|index:1,count:478936,average:75,stdev:0	GSM2189076_r2						1.73	3.51	0.06	58185395	56645916	55279012	54265397	97.35	98.17	430360	405250	199.141	844.153	176	2042	57.15	60.22	467807	245955	467807	245955	58.44	57.9	467807	251510	467807	236462	20855319	35.84	1.08	0	4.58	0	0.24	0	0.15	0	0.00	0	9.75	0	430360	0	150	0	147.68	0	1.39	0	0.01	0	1.15	0	0.00	0	86.21	0	0.77	0	5196	0	478936	0	21948	0	1162	0	700	0	0	0	46714	0	27	0	0	0	232	0	38728	0	367	0	39354	0	85.27	0	408412	0	15468	38940	2.517455391777	478936.0	430360.0	5196.0	21948.0	1162.0	700.0	0.0	46714.0	408412.0	89.9	1.1	4.6	0.2	0.1	0.0	9.8	85.3	75	75	75.00	7	35920200	30.5	19.9	19.7	29.9	0.0	33.5	22.3	smartseq
1446671	SRR3638130	SRP076212	SRS1488232	SRX1826274	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189076: 1-0-1-0-BTN35-C53-1782070112-30ul-1-IL5413-N705-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189076		GSM2189076	1-0-1-0-BTN35-C53-1782070112-30ul-1-IL5413-N705-N505 BTN35 Mic-scRNA-Seq	73806000	492040	2016-07-18 10:56:32	35054319	73806000	492040	2	492040	index:0,count:492040,average:75,stdev:0|index:1,count:492040,average:75,stdev:0	GSM2189076_r4						1.76	3.53	0.07	59410776	57867858	56484106	55463070	97.4	98.19	439744	414159	199.066	828.138	177	2074	57.11	60.13	477495	251120	477495	251120	58.3	57.77	477495	256360	477495	241269	21336326	35.91	1.11	0	4.50	0	0.23	0	0.16	0	0.00	0	10.24	0	439744	0	150	0	147.69	0	1.41	0	0.01	0	1.14	0	0.00	0	118.09	0	0.72	0	5456	0	492040	0	22124	0	1133	0	783	0	0	0	50380	0	28	0	0	0	264	0	40025	0	349	0	40666	0	84.88	0	417620	0	15796	40269	2.549316282603	492040.0	439744.0	5456.0	22124.0	1133.0	783.0	0.0	50380.0	417620.0	89.4	1.1	4.5	0.2	0.2	0.0	10.2	84.9	75	75	75.00	7	36903000	30.5	19.9	19.7	29.9	0.0	33.8	22.5	smartseq
1446687	SRR3638131	SRP076212	SRS1488233	SRX1826275	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189077: 1-0-1-0-BTN35-C54-1782070112-22ul-1-IL5413-N706-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189077		GSM2189077	1-0-1-0-BTN35-C54-1782070112-22ul-1-IL5413-N706-N505 BTN35 Mic-scRNA-Seq	59130600	394204	2016-07-18 10:56:32	28638702	59130600	394204	2	394204	index:0,count:394204,average:75,stdev:0|index:1,count:394204,average:75,stdev:0	GSM2189077_r1						1.14	4.43	0.06	48679486	47592062	46085850	45461244	97.77	98.64	355518	326726	205.290	978.302	174	1771	73.48	77.72	389454	261235	389454	261235	74.8	75.09	389454	265927	389454	252402	9279233	19.06	1.04	0	4.92	0	0.26	0	0.08	0	0.00	0	9.48	0	355518	0	150	0	147.68	0	1.47	0	0.01	0	1.15	0	0.00	0	74.69	0	0.84	0	4104	0	394204	0	19384	0	1025	0	309	0	0	0	37352	0	23	0	0	0	277	0	45489	0	319	0	46108	0	85.27	0	336134	0	16487	45768	2.776005337539	394204.0	355518.0	4104.0	19384.0	1025.0	309.0	0.0	37352.0	336134.0	90.2	1.0	4.9	0.3	0.1	0.0	9.5	85.3	75	75	75.00	7	29565300	30.0	20.4	20.5	29.2	0.0	33.3	21.9	smartseq
1446766	SRR3638136	SRP076212	SRS1488235	SRX1826276	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189078: 1-0-1-0-BTN35-C55-1782070112-8ul-1-IL5413-N708-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189078		GSM2189078	1-0-1-0-BTN35-C55-1782070112-8ul-1-IL5413-N708-N505 BTN35 Mic-scRNA-Seq	58265250	388435	2016-07-18 10:56:32	27835127	58265250	388435	2	388435	index:0,count:388435,average:75,stdev:0|index:1,count:388435,average:75,stdev:0	GSM2189078_r2						7.52	3.69	0.1	38210820	38012599	34713885	34967423	99.48	100.73	308872	293636	164.805	909.197	90	1904	65.57	72.2	351610	202527	351610	202527	68.98	67.95	351610	213066	351610	190588	9257410	24.23	1.52	0	7.31	0	0.28	0	0.37	0	0.00	0	19.83	0	308872	0	150	0	145.81	0	1.59	0	0.01	0	1.13	0	0.00	0	60.80	0	0.76	0	5921	0	388435	0	28383	0	1102	0	1429	0	0	0	77032	0	25	0	0	0	188	0	30002	0	291	0	30506	0	72.21	0	280489	0	9570	29175	3.048589341693	388435.0	308872.0	5921.0	28383.0	1102.0	1429.0	0.0	77032.0	280489.0	79.5	1.5	7.3	0.3	0.4	0.0	19.8	72.2	75	75	75.00	7	29132625	29.9	21.0	20.0	29.1	0.0	33.5	22.1	smartseq
1446767	SRR3639136	SRP076212	SRS1488539	SRX1826581	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189383: 1g_BTN7_C08_IL4709-702-502_CGTACTAG-CTCTCTAT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189383		GSM2189383	1g_BTN7_C08_IL4709-702-502_CGTACTAG-CTCTCTAT BTN07 Mic-scRNA-Seq	443122350	2193675	2016-07-18 10:56:32	301705562	443122350	2193675	2	2193675	index:0,count:2193675,average:101,stdev:0|index:1,count:2193675,average:101,stdev:0	GSM2189383_r1						2.54	3.26	0.93	339548062	319627206	320826649	303577595	94.13	94.62	1893785	1785920	249.253	677.865	188	9627	70.24	74.41	2089503	1330124	2089503	1330124	71.62	71.68	2089503	1356315	2089503	1281350	65023112	19.15	1.14	0	4.85	0	0.49	0	0.08	0	0.00	0	13.10	0	1893785	0	202	0	198.11	0	1.75	0	0.01	0	1.20	0	0.01	0	171.68	0	0.74	0	24947	0	2193675	0	106298	0	10750	0	1839	0	0	0	287301	0	206	0	0	0	1711	0	314266	0	3838	0	320021	0	81.48	0	1787487	0	6802	317617	46.694648632755	2193675.0	1893785.0	24947.0	106298.0	10750.0	1839.0	0.0	287301.0	1787487.0	86.3	1.1	4.8	0.5	0.1	0.0	13.1	81.5	101	101	101.00	38	221561175	26.6	22.9	23.0	27.5	0.0	34.8	17.7	smartseq
1446780	SRR3638137	SRP076212	SRS1488235	SRX1826276	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189078: 1-0-1-0-BTN35-C55-1782070112-8ul-1-IL5413-N708-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189078		GSM2189078	1-0-1-0-BTN35-C55-1782070112-8ul-1-IL5413-N708-N505 BTN35 Mic-scRNA-Seq	59831850	398879	2016-07-18 10:56:32	28659425	59831850	398879	2	398879	index:0,count:398879,average:75,stdev:0|index:1,count:398879,average:75,stdev:0	GSM2189078_r3						7.57	3.62	0.09	38605482	38420789	35055199	35334766	99.52	100.8	312748	297609	163.391	890.404	79	1937	65.56	72.24	355701	205032	355701	205032	69.0	67.93	355701	215782	355701	192803	9345224	24.21	1.49	0	7.26	0	0.28	0	0.33	0	0.00	0	20.97	0	312748	0	150	0	145.80	0	1.54	0	0.01	0	1.16	0	0.00	0	59.83	0	0.78	0	5952	0	398879	0	28942	0	1135	0	1334	0	0	0	83662	0	33	0	0	0	193	0	30475	0	278	0	30979	0	71.15	0	283806	0	9799	29460	3.006429227472	398879.0	312748.0	5952.0	28942.0	1135.0	1334.0	0.0	83662.0	283806.0	78.4	1.5	7.3	0.3	0.3	0.0	21.0	71.2	75	75	75.00	7	29915925	30.0	21.0	20.1	28.9	0.0	33.4	21.8	smartseq
1446781	SRR3639137	SRP076212	SRS1488540	SRX1826582	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189384: 1g_BTN7_C12_IL4709-707-502_CTCTCTAC-CTCTCTAT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189384		GSM2189384	1g_BTN7_C12_IL4709-707-502_CTCTCTAC-CTCTCTAT BTN07 Mic-scRNA-Seq	528054260	2614130	2016-07-18 10:56:32	358507438	528054260	2614130	2	2614130	index:0,count:2614130,average:101,stdev:0|index:1,count:2614130,average:101,stdev:0	GSM2189384_r1						0.68	3.49	1.4	403286121	366588760	390913047	357560914	90.9	91.47	2252105	2169564	244.688	658.581	188	11884	63.3	65.36	2395862	1425627	2395862	1425627	62.83	63.21	2395862	1414885	2395862	1378756	105786987	26.23	1.16	0	2.71	0	0.29	0	0.13	0	0.00	0	13.43	0	2252105	0	202	0	198.20	0	1.56	0	0.01	0	1.25	0	0.01	0	165.10	0	0.74	0	30223	0	2614130	0	70912	0	7485	0	3367	0	0	0	351173	0	63	0	0	0	1933	0	237373	0	3326	0	242695	0	83.44	0	2181193	0	5048	243694	48.275356576862	2614130.0	2252105.0	30223.0	70912.0	7485.0	3367.0	0.0	351173.0	2181193.0	86.2	1.2	2.7	0.3	0.1	0.0	13.4	83.4	101	101	101.00	38	264027130	27.0	22.4	22.5	28.1	0.0	34.9	17.7	smartseq
1446782	SRR3640137	SRP076212	SRS1489003	SRX1827045	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189847: C7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189847		GSM2189847	C7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq	68739150	458261	2016-07-18 10:56:32	25557526	68739150	458261	2	458261	index:0,count:458261,average:75,stdev:0|index:1,count:458261,average:75,stdev:0	GSM2189847_r2						1.85	2.44	0.03	54404062	61961116	50781810	58612749	113.89	115.42	412759	386075	198.031	926.350	110	2484	68.88	74.13	454289	284322	454289	284322	55.48	55.36	454289	229019	454289	212333	12093852	22.23	2.07	0	6.37	0	0.29	0	0.22	0	0.00	0	9.42	0	412759	0	150	0	147.46	0	4.41	0	0.06	0	1.04	0	0.02	0	137.48	0	0.32	0	9464	0	458261	0	29200	0	1321	0	991	0	0	0	43190	0	38	0	0	0	342	0	56201	0	617	0	57198	0	83.70	0	383559	0	11516	54141	4.701372004168	458261.0	412759.0	9464.0	29200.0	1321.0	991.0	0.0	43190.0	383559.0	90.1	2.1	6.4	0.3	0.2	0.0	9.4	83.7	75	75	75.00	6	34369575	25.1	24.8	24.6	25.5	0.0	34.7	27.9	smartseq
1446783	SRR3641137	SRP076212	SRS1489260	SRX1827301	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190103: G7_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190103		GSM2190103	G7_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	83534700	556898	2016-07-18 10:56:32	35008968	83534700	556898	2	556898	index:0,count:556898,average:75,stdev:0|index:1,count:556898,average:75,stdev:0	GSM2190103_r1						1.84	2.39	0.05	68597472	77077796	63871445	72776154	112.36	113.94	499207	451722	226.598	1237.162	174	2474	77.26	83.3	549064	385689	549064	385689	65.17	66.0	549064	325324	549064	305570	9376143	13.67	2.02	0	6.50	0	0.22	0	0.12	0	0.00	0	10.02	0	499207	0	150	0	147.54	0	4.82	0	0.09	0	1.08	0	0.02	0	143.20	0	0.48	0	11274	0	556898	0	36218	0	1233	0	683	0	0	0	55775	0	58	0	0	0	506	0	83885	0	769	0	85218	0	83.14	0	462989	0	24832	82472	3.321198453608	556898.0	499207.0	11274.0	36218.0	1233.0	683.0	0.0	55775.0	462989.0	89.6	2.0	6.5	0.2	0.1	0.0	10.0	83.1	75	75	75.00	6	41767350	24.9	24.8	25.0	25.3	0.0	33.8	25.4	smartseq
1446795	SRR3638138	SRP076212	SRS1488235	SRX1826276	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189078: 1-0-1-0-BTN35-C55-1782070112-8ul-1-IL5413-N708-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189078		GSM2189078	1-0-1-0-BTN35-C55-1782070112-8ul-1-IL5413-N708-N505 BTN35 Mic-scRNA-Seq	60488550	403257	2016-07-18 10:56:32	28590961	60488550	403257	2	403257	index:0,count:403257,average:75,stdev:0|index:1,count:403257,average:75,stdev:0	GSM2189078_r4						7.47	3.61	0.09	39423849	39229360	35850128	36133831	99.51	100.79	318793	303110	164.533	873.619	100	1943	65.53	72.13	362700	208913	362700	208913	68.91	67.86	362700	219677	362700	196540	9585111	24.31	1.51	0	7.23	0	0.29	0	0.35	0	0.00	0	20.30	0	318793	0	150	0	145.87	0	1.56	0	0.01	0	1.17	0	0.00	0	69.13	0	0.71	0	6076	0	403257	0	29152	0	1169	0	1422	0	0	0	81873	0	38	0	0	0	174	0	31169	0	314	0	31695	0	71.83	0	289641	0	9903	30229	3.052509340604	403257.0	318793.0	6076.0	29152.0	1169.0	1422.0	0.0	81873.0	289641.0	79.1	1.5	7.2	0.3	0.4	0.0	20.3	71.8	75	75	75.00	7	30244275	30.0	21.0	20.0	29.0	0.0	33.7	22.1	smartseq
1446796	SRR3639138	SRP076212	SRS1488541	SRX1826583	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189385: 1g_BTN7_C14_IL4709-702-503_CGTACTAG-TATCCTCT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189385		GSM2189385	1g_BTN7_C14_IL4709-702-503_CGTACTAG-TATCCTCT BTN07 Mic-scRNA-Seq	458867846	2271623	2016-07-18 10:56:32	313033884	458867846	2271623	2	2271623	index:0,count:2271623,average:101,stdev:0|index:1,count:2271623,average:101,stdev:0	GSM2189385_r1						2.33	3.56	1.16	354608389	328940049	335175804	312597193	92.76	93.26	1982615	1890053	244.676	627.306	188	10402	69.21	73.36	2202905	1372218	2202905	1372218	70.4	70.76	2202905	1395788	2202905	1323739	67259152	18.97	1.07	0	4.93	0	0.60	0	0.09	0	0.00	0	12.03	0	1982615	0	202	0	198.22	0	1.57	0	0.01	0	1.22	0	0.01	0	146.03	0	0.73	0	24375	0	2271623	0	111988	0	13567	0	2071	0	0	0	273370	0	9	0	0	0	1480	0	271465	0	4945	0	277899	0	82.35	0	1870627	0	5918	279580	47.242311591754	2271623.0	1982615.0	24375.0	111988.0	13567.0	2071.0	0.0	273370.0	1870627.0	87.3	1.1	4.9	0.6	0.1	0.0	12.0	82.3	101	101	101.00	38	229433923	26.7	22.7	22.9	27.7	0.0	34.8	17.7	smartseq
1446797	SRR3640138	SRP076212	SRS1489003	SRX1827045	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189847: C7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189847		GSM2189847	C7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq	69529800	463532	2016-07-18 10:56:32	26056869	69529800	463532	2	463532	index:0,count:463532,average:75,stdev:0|index:1,count:463532,average:75,stdev:0	GSM2189847_r3						1.93	2.43	0.03	55153983	62755001	51509472	59390697	113.78	115.3	418273	391107	198.949	937.350	110	2471	68.9	74.09	459907	288184	459907	288184	55.55	55.44	459907	232367	459907	215634	12262479	22.23	2.06	0	6.32	0	0.29	0	0.23	0	0.00	0	9.25	0	418273	0	150	0	147.46	0	4.40	0	0.07	0	1.04	0	0.02	0	139.06	0	0.31	0	9568	0	463532	0	29303	0	1332	0	1062	0	0	0	42865	0	36	0	0	0	359	0	56889	0	633	0	57917	0	83.91	0	388970	0	11589	54771	4.726119596169	463532.0	418273.0	9568.0	29303.0	1332.0	1062.0	0.0	42865.0	388970.0	90.2	2.1	6.3	0.3	0.2	0.0	9.2	83.9	75	75	75.00	6	34764900	25.1	24.8	24.6	25.4	0.0	34.7	27.8	smartseq
1446798	SRR3641138	SRP076212	SRS1489260	SRX1827301	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190103: G7_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190103		GSM2190103	G7_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	81171150	541141	2016-07-18 10:56:32	34090354	81171150	541141	2	541141	index:0,count:541141,average:75,stdev:0|index:1,count:541141,average:75,stdev:0	GSM2190103_r2						1.88	2.43	0.06	66517746	74747366	61893413	70551709	112.37	113.99	484055	437527	227.018	1254.619	174	2418	77.18	83.27	533016	373583	533016	373583	65.15	65.99	533016	315381	533016	296037	9136836	13.74	1.98	0	6.55	0	0.22	0	0.12	0	0.00	0	10.21	0	484055	0	150	0	147.49	0	4.85	0	0.09	0	1.09	0	0.02	0	139.15	0	0.51	0	10741	0	541141	0	35420	0	1187	0	628	0	0	0	55271	0	66	0	0	0	488	0	80281	0	758	0	81593	0	82.91	0	448635	0	24554	78860	3.211696668567	541141.0	484055.0	10741.0	35420.0	1187.0	628.0	0.0	55271.0	448635.0	89.5	2.0	6.5	0.2	0.1	0.0	10.2	82.9	75	75	75.00	6	40585575	24.9	24.8	25.0	25.3	0.0	33.8	25.4	smartseq
1446811	SRR3638139	SRP076212	SRS1488234	SRX1826277	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189079: 1-0-1-0-BTN35-C56-1782070112-10ul-1-IL5413-N709-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189079		GSM2189079	1-0-1-0-BTN35-C56-1782070112-10ul-1-IL5413-N709-N505 BTN35 Mic-scRNA-Seq	50883600	339224	2016-07-18 10:56:32	24225065	50883600	339224	2	339224	index:0,count:339224,average:75,stdev:0|index:1,count:339224,average:75,stdev:0	GSM2189079_r1						3.38	4.24	0.1	35359836	34700866	33019070	32778797	98.14	99.27	280499	264637	168.568	764.288	122	1582	72.53	77.76	311792	203434	311792	203434	74.61	74.91	311792	209284	311792	195961	6842584	19.35	1.27	0	5.57	0	0.21	0	0.24	0	0.00	0	16.86	0	280499	0	150	0	146.50	0	1.41	0	0.01	0	1.19	0	0.00	0	53.10	0	0.73	0	4292	0	339224	0	18892	0	718	0	822	0	0	0	57185	0	42	0	0	0	239	0	32629	0	245	0	33155	0	77.12	0	261607	0	11487	31618	2.752502829285	339224.0	280499.0	4292.0	18892.0	718.0	822.0	0.0	57185.0	261607.0	82.7	1.3	5.6	0.2	0.2	0.0	16.9	77.1	75	75	75.00	7	25441800	29.9	20.8	19.9	29.3	0.0	33.5	22.1	smartseq
1446812	SRR3639139	SRP076212	SRS1488542	SRX1826584	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189386: 1g_BTN7_C15_IL4709-701-503_TAAGGCGA-TATCCTCT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189386		GSM2189386	1g_BTN7_C15_IL4709-701-503_TAAGGCGA-TATCCTCT BTN07 Mic-scRNA-Seq	465788972	2305886	2016-07-18 10:56:32	318455930	465788972	2305886	2	2305886	index:0,count:2305886,average:101,stdev:0|index:1,count:2305886,average:101,stdev:0	GSM2189386_r1						1.42	2.32	0.41	371455135	356395542	357821539	344187049	95.95	96.19	2050382	1943232	256.162	631.996	188	10035	63.03	65.49	2187916	1292362	2187916	1292362	63.83	63.58	2187916	1308803	2187916	1254695	113565973	30.57	0.97	0	3.34	0	0.30	0	0.09	0	0.00	0	10.69	0	2050382	0	202	0	198.63	0	1.57	0	0.01	0	1.28	0	0.01	0	202.47	0	0.72	0	22301	0	2305886	0	76909	0	6886	0	2076	0	0	0	246542	0	225	0	0	0	2056	0	291653	0	2898	0	296832	0	85.58	0	1973473	0	6865	295259	43.009322651129	2305886.0	2050382.0	22301.0	76909.0	6886.0	2076.0	0.0	246542.0	1973473.0	88.9	1.0	3.3	0.3	0.1	0.0	10.7	85.6	101	101	101.00	38	232894486	27.0	22.5	22.7	27.8	0.0	35.0	18.2	smartseq
1446813	SRR3640139	SRP076212	SRS1489003	SRX1827045	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189847: C7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189847		GSM2189847	C7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq	69512700	463418	2016-07-18 10:56:32	26067314	69512700	463418	2	463418	index:0,count:463418,average:75,stdev:0|index:1,count:463418,average:75,stdev:0	GSM2189847_r4						1.91	2.44	0.04	55202261	62846047	51555583	59481896	113.85	115.37	418187	390741	199.642	929.647	110	2413	68.91	74.1	460045	288182	460045	288182	55.58	55.4	460045	232410	460045	215439	12286056	22.26	2.03	0	6.32	0	0.30	0	0.22	0	0.00	0	9.24	0	418187	0	150	0	147.47	0	4.47	0	0.07	0	1.05	0	0.02	0	128.33	0	0.32	0	9419	0	463418	0	29287	0	1385	0	1027	0	0	0	42819	0	39	0	0	0	379	0	56770	0	629	0	57817	0	83.92	0	388900	0	11594	54868	4.732447817837	463418.0	418187.0	9419.0	29287.0	1385.0	1027.0	0.0	42819.0	388900.0	90.2	2.0	6.3	0.3	0.2	0.0	9.2	83.9	75	75	75.00	6	34756350	25.1	24.8	24.6	25.5	0.0	34.7	27.8	smartseq
1446814	SRR3641139	SRP076212	SRS1489260	SRX1827301	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190103: G7_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190103		GSM2190103	G7_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	82072350	547149	2016-07-18 10:56:32	34876984	82072350	547149	2	547149	index:0,count:547149,average:75,stdev:0|index:1,count:547149,average:75,stdev:0	GSM2190103_r3						1.8	2.38	0.07	67260777	75482149	62639885	71274392	112.22	113.78	489716	442705	225.781	1272.417	174	2437	77.3	83.32	538804	378573	538804	378573	65.37	66.19	538804	320131	538804	300737	9218316	13.71	1.96	0	6.46	0	0.22	0	0.12	0	0.00	0	10.15	0	489716	0	150	0	147.48	0	4.86	0	0.09	0	1.09	0	0.02	0	140.70	0	0.54	0	10709	0	547149	0	35357	0	1213	0	665	0	0	0	55555	0	44	0	0	0	509	0	82386	0	781	0	83720	0	83.04	0	454359	0	24728	81033	3.276973471368	547149.0	489716.0	10709.0	35357.0	1213.0	665.0	0.0	55555.0	454359.0	89.5	2.0	6.5	0.2	0.1	0.0	10.2	83.0	75	75	75.00	6	41036175	24.9	24.8	25.0	25.3	0.0	33.5	24.9	smartseq
1446924	SRR3638140	SRP076212	SRS1488234	SRX1826277	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189079: 1-0-1-0-BTN35-C56-1782070112-10ul-1-IL5413-N709-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189079		GSM2189079	1-0-1-0-BTN35-C56-1782070112-10ul-1-IL5413-N709-N505 BTN35 Mic-scRNA-Seq	49291650	328611	2016-07-18 10:56:32	23369009	49291650	328611	2	328611	index:0,count:328611,average:75,stdev:0|index:1,count:328611,average:75,stdev:0	GSM2189079_r2						3.31	4.24	0.11	35232076	34619374	32981068	32763842	98.26	99.34	278551	262230	170.346	780.794	120	1545	72.69	77.77	308421	202492	308421	202492	74.62	74.9	308421	207856	308421	195019	6830371	19.39	1.32	0	5.53	0	0.22	0	0.23	0	0.00	0	14.79	0	278551	0	150	0	146.54	0	1.45	0	0.01	0	1.16	0	0.00	0	78.87	0	0.72	0	4348	0	328611	0	18168	0	707	0	767	0	0	0	48586	0	50	0	0	0	250	0	32789	0	248	0	33337	0	79.24	0	260383	0	11540	31764	2.752512998267	328611.0	278551.0	4348.0	18168.0	707.0	767.0	0.0	48586.0	260383.0	84.8	1.3	5.5	0.2	0.2	0.0	14.8	79.2	75	75	75.00	7	24645825	29.8	20.8	19.9	29.5	0.0	33.7	22.5	smartseq
1446925	SRR3639140	SRP076212	SRS1488543	SRX1826585	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189387: 1g_BTN7_C16_IL4709-709-503_GCTACGCT-TATCCTCT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189387		GSM2189387	1g_BTN7_C16_IL4709-709-503_GCTACGCT-TATCCTCT BTN07 Mic-scRNA-Seq	497441968	2462584	2016-07-18 10:56:32	339017706	497441968	2462584	2	2462584	index:0,count:2462584,average:101,stdev:0|index:1,count:2462584,average:101,stdev:0	GSM2189387_r1						6.65	3.14	0.1	389961860	385756316	362205424	360033017	98.92	99.4	2186600	1811775	233.990	1081.072	167	12260	77.2	83.19	2392229	1688019	2392229	1688019	81.62	81.08	2392229	1784769	2392229	1645220	58515109	15.01	1.16	0	6.39	0	0.13	0	0.04	0	0.00	0	11.04	0	2186600	0	202	0	198.06	0	1.52	0	0.01	0	1.26	0	0.00	0	170.49	0	0.69	0	28489	0	2462584	0	157464	0	3198	0	996	0	0	0	271790	0	167	0	0	0	3377	0	950985	0	3622	0	958151	0	82.40	0	2029136	0	16930	903971	53.394624926167	2462584.0	2186600.0	28489.0	157464.0	3198.0	996.0	0.0	271790.0	2029136.0	88.8	1.2	6.4	0.1	0.0	0.0	11.0	82.4	101	101	101.00	38	248720984	26.1	23.1	23.5	27.3	0.0	35.1	18.4	smartseq
1446926	SRR3640140	SRP076212	SRS1489004	SRX1827046	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189848: C7_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189848		GSM2189848	C7_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	45707700	304718	2016-07-18 10:56:32	17198062	45707700	304718	2	304718	index:0,count:304718,average:75,stdev:0|index:1,count:304718,average:75,stdev:0	GSM2189848_r1						0.88	2.36	0.02	39595667	44388211	37262208	42222313	112.1	113.31	286066	249354	244.063	1652.155	146	1331	83.59	89.1	310735	239112	310735	239112	72.25	73.26	310735	206694	310735	196606	3522097	8.90	1.58	0	5.81	0	0.22	0	0.10	0	0.00	0	5.80	0	286066	0	150	0	148.06	0	4.56	0	0.06	0	1.06	0	0.02	0	91.42	0	0.29	0	4828	0	304718	0	17714	0	671	0	296	0	0	0	17685	0	62	0	0	0	402	0	60442	0	418	0	61324	0	88.07	0	268352	0	21229	59348	2.795609779076	304718.0	286066.0	4828.0	17714.0	671.0	296.0	0.0	17685.0	268352.0	93.9	1.6	5.8	0.2	0.1	0.0	5.8	88.1	75	75	75.00	6	22853850	24.2	25.7	25.6	24.5	0.0	34.8	28.2	smartseq
1446927	SRR3641140	SRP076212	SRS1489260	SRX1827301	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190103: G7_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190103		GSM2190103	G7_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	80999400	539996	2016-07-18 10:56:32	34268822	80999400	539996	2	539996	index:0,count:539996,average:75,stdev:0|index:1,count:539996,average:75,stdev:0	GSM2190103_r4						1.8	2.38	0.06	66569955	74802984	61929582	70593279	112.37	113.99	484167	437294	227.382	1271.184	174	2424	77.19	83.29	533135	373739	533135	373739	65.23	66.05	533135	315846	533135	296389	9146362	13.74	1.96	0	6.56	0	0.22	0	0.11	0	0.00	0	10.01	0	484167	0	150	0	147.52	0	4.83	0	0.09	0	1.09	0	0.02	0	138.86	0	0.51	0	10560	0	539996	0	35445	0	1185	0	607	0	0	0	54037	0	54	0	0	0	558	0	80828	0	717	0	82157	0	83.10	0	448722	0	24483	79457	3.245394763714	539996.0	484167.0	10560.0	35445.0	1185.0	607.0	0.0	54037.0	448722.0	89.7	2.0	6.6	0.2	0.1	0.0	10.0	83.1	75	75	75.00	6	40499700	24.9	24.9	25.0	25.3	0.0	33.7	25.2	smartseq
1446941	SRR3638141	SRP076212	SRS1488234	SRX1826277	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189079: 1-0-1-0-BTN35-C56-1782070112-10ul-1-IL5413-N709-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189079		GSM2189079	1-0-1-0-BTN35-C56-1782070112-10ul-1-IL5413-N709-N505 BTN35 Mic-scRNA-Seq	50764200	338428	2016-07-18 10:56:32	24132571	50764200	338428	2	338428	index:0,count:338428,average:75,stdev:0|index:1,count:338428,average:75,stdev:0	GSM2189079_r3						3.43	4.25	0.12	35514800	34844457	33201254	32935137	98.11	99.2	281238	264902	169.220	775.165	100	1588	72.65	77.82	311887	204333	311887	204333	74.75	75.04	311887	210221	311887	197022	6847050	19.28	1.25	0	5.52	0	0.20	0	0.23	0	0.00	0	16.46	0	281238	0	150	0	146.54	0	1.43	0	0.01	0	1.21	0	0.00	0	58.02	0	0.73	0	4236	0	338428	0	18672	0	691	0	792	0	0	0	55707	0	30	0	0	0	234	0	33273	0	261	0	33798	0	77.58	0	262566	0	11608	32172	2.771536871123	338428.0	281238.0	4236.0	18672.0	691.0	792.0	0.0	55707.0	262566.0	83.1	1.3	5.5	0.2	0.2	0.0	16.5	77.6	75	75	75.00	7	25382100	29.9	20.9	19.9	29.3	0.0	33.6	22.3	smartseq
1446942	SRR3639141	SRP076212	SRS1488544	SRX1826586	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189388: 1g_BTN7_C18_IL4709-707-503_CTCTCTAC-TATCCTCT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189388		GSM2189388	1g_BTN7_C18_IL4709-707-503_CTCTCTAC-TATCCTCT BTN07 Mic-scRNA-Seq	544415452	2695126	2016-07-18 10:56:32	370002738	544415452	2695126	2	2695126	index:0,count:2695126,average:101,stdev:0|index:1,count:2695126,average:101,stdev:0	GSM2189388_r1						2.88	3.88	2.01	414496276	372511540	391172512	353936282	89.87	90.48	2320564	2209682	244.064	715.622	174	11810	61.25	64.99	2566601	1421404	2566601	1421404	62.41	62.4	2566601	1448226	2566601	1364682	103027308	24.86	1.31	0	4.95	0	0.56	0	0.19	0	0.00	0	13.15	0	2320564	0	202	0	198.18	0	1.66	0	0.01	0	1.25	0	0.01	0	164.45	0	0.72	0	35257	0	2695126	0	133413	0	14966	0	5194	0	0	0	354402	0	120	0	0	0	2289	0	319015	0	4497	0	325921	0	81.15	0	2187151	0	9084	331650	36.509247027741	2695126.0	2320564.0	35257.0	133413.0	14966.0	5194.0	0.0	354402.0	2187151.0	86.1	1.3	5.0	0.6	0.2	0.0	13.1	81.2	101	101	101.00	38	272207726	27.2	22.1	22.3	28.4	0.0	34.9	17.5	smartseq
1446943	SRR3640141	SRP076212	SRS1489004	SRX1827046	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189848: C7_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189848		GSM2189848	C7_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	45363600	302424	2016-07-18 10:56:32	17166993	45363600	302424	2	302424	index:0,count:302424,average:75,stdev:0|index:1,count:302424,average:75,stdev:0	GSM2189848_r2						0.92	2.32	0.03	39249183	43956792	36934427	41793716	111.99	113.16	283346	246342	244.759	1652.060	146	1340	83.55	89.07	307284	236739	307284	236739	72.33	73.3	307284	204938	307284	194828	3468676	8.84	1.56	0	5.80	0	0.21	0	0.09	0	0.00	0	6.01	0	283346	0	150	0	148.05	0	4.46	0	0.06	0	1.08	0	0.02	0	68.05	0	0.31	0	4716	0	302424	0	17550	0	632	0	281	0	0	0	18165	0	55	0	0	0	387	0	60229	0	496	0	61167	0	87.89	0	265796	0	21171	59109	2.791979594729	302424.0	283346.0	4716.0	17550.0	632.0	281.0	0.0	18165.0	265796.0	93.7	1.6	5.8	0.2	0.1	0.0	6.0	87.9	75	75	75.00	6	22681800	24.2	25.7	25.6	24.5	0.0	34.7	28.1	smartseq
1446959	SRR3638142	SRP076212	SRS1488234	SRX1826277	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189079: 1-0-1-0-BTN35-C56-1782070112-10ul-1-IL5413-N709-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189079		GSM2189079	1-0-1-0-BTN35-C56-1782070112-10ul-1-IL5413-N709-N505 BTN35 Mic-scRNA-Seq	51052350	340349	2016-07-18 10:56:32	23965307	51052350	340349	2	340349	index:0,count:340349,average:75,stdev:0|index:1,count:340349,average:75,stdev:0	GSM2189079_r4						3.4	4.2	0.11	36195561	35524181	33863558	33609195	98.15	99.25	286395	269627	170.338	779.204	93	1602	72.66	77.77	316915	208097	316915	208097	74.62	74.94	316915	213719	316915	200544	6995946	19.33	1.29	0	5.53	0	0.20	0	0.25	0	0.00	0	15.41	0	286395	0	150	0	146.53	0	1.46	0	0.01	0	1.18	0	0.00	0	68.07	0	0.67	0	4387	0	340349	0	18805	0	668	0	838	0	0	0	52448	0	44	0	0	0	278	0	34190	0	304	0	34816	0	78.62	0	267590	0	11824	33203	2.808102165088	340349.0	286395.0	4387.0	18805.0	668.0	838.0	0.0	52448.0	267590.0	84.1	1.3	5.5	0.2	0.2	0.0	15.4	78.6	75	75	75.00	7	25526175	29.9	20.8	19.9	29.4	0.0	33.9	22.7	smartseq
1446975	SRR3638143	SRP076212	SRS1488236	SRX1826278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189080: 1-0-1-0-BTN35-C57-1782070112-22ul-1-IL5413-N710-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189080		GSM2189080	1-0-1-0-BTN35-C57-1782070112-22ul-1-IL5413-N710-N505 BTN35 Mic-scRNA-Seq	61785600	411904	2016-07-18 10:56:32	29580544	61785600	411904	2	411904	index:0,count:411904,average:75,stdev:0|index:1,count:411904,average:75,stdev:0	GSM2189080_r1						2.87	3.48	0.06	41416063	40439516	39079739	38496872	97.64	98.51	333820	318454	163.741	725.525	79	2016	57.98	61.53	365831	193544	365831	193544	59.36	58.76	365831	198145	365831	184851	14212870	34.32	1.35	0	4.68	0	0.19	0	0.24	0	0.00	0	18.53	0	333820	0	150	0	146.16	0	1.46	0	0.01	0	1.16	0	0.00	0	74.14	0	0.78	0	5549	0	411904	0	19257	0	766	0	1004	0	0	0	76314	0	12	0	0	0	212	0	31490	0	323	0	32037	0	76.37	0	314563	0	11611	30305	2.610024976316	411904.0	333820.0	5549.0	19257.0	766.0	1004.0	0.0	76314.0	314563.0	81.0	1.3	4.7	0.2	0.2	0.0	18.5	76.4	75	75	75.00	7	30892800	29.7	21.1	20.1	29.0	0.0	33.5	22.1	smartseq
1446991	SRR3638144	SRP076212	SRS1488236	SRX1826278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189080: 1-0-1-0-BTN35-C57-1782070112-22ul-1-IL5413-N710-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189080		GSM2189080	1-0-1-0-BTN35-C57-1782070112-22ul-1-IL5413-N710-N505 BTN35 Mic-scRNA-Seq	60246450	401643	2016-07-18 10:56:32	28781586	60246450	401643	2	401643	index:0,count:401643,average:75,stdev:0|index:1,count:401643,average:75,stdev:0	GSM2189080_r2						2.86	3.45	0.06	41096268	40119383	38803046	38210056	97.62	98.47	329750	314247	166.037	765.061	90	1893	58.12	61.62	360826	191648	360826	191648	59.56	58.95	360826	196388	360826	183328	14091637	34.29	1.37	0	4.67	0	0.19	0	0.26	0	0.00	0	17.45	0	329750	0	150	0	146.25	0	1.47	0	0.01	0	1.17	0	0.00	0	65.72	0	0.77	0	5498	0	401643	0	18755	0	759	0	1051	0	0	0	70083	0	13	0	0	0	195	0	31923	0	380	0	32511	0	77.43	0	310995	0	11701	30760	2.628835142296	401643.0	329750.0	5498.0	18755.0	759.0	1051.0	0.0	70083.0	310995.0	82.1	1.4	4.7	0.2	0.3	0.0	17.4	77.4	75	75	75.00	7	30123225	29.6	21.1	20.1	29.1	0.0	33.6	22.3	smartseq
1447007	SRR3638145	SRP076212	SRS1488236	SRX1826278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189080: 1-0-1-0-BTN35-C57-1782070112-22ul-1-IL5413-N710-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189080		GSM2189080	1-0-1-0-BTN35-C57-1782070112-22ul-1-IL5413-N710-N505 BTN35 Mic-scRNA-Seq	61583250	410555	2016-07-18 10:56:32	29471740	61583250	410555	2	410555	index:0,count:410555,average:75,stdev:0|index:1,count:410555,average:75,stdev:0	GSM2189080_r3						2.89	3.44	0.07	41546810	40566246	39217935	38628221	97.64	98.5	334054	318440	164.595	733.166	79	2033	57.97	61.48	365739	193656	365739	193656	59.34	58.76	365739	198222	365739	185113	14319074	34.46	1.39	0	4.64	0	0.22	0	0.24	0	0.00	0	18.18	0	334054	0	150	0	146.26	0	1.45	0	0.01	0	1.15	0	0.00	0	54.74	0	0.78	0	5696	0	410555	0	19048	0	889	0	990	0	0	0	74622	0	11	0	0	0	216	0	31838	0	315	0	32380	0	76.73	0	315006	0	11736	30699	2.615797546012	410555.0	334054.0	5696.0	19048.0	889.0	990.0	0.0	74622.0	315006.0	81.4	1.4	4.6	0.2	0.2	0.0	18.2	76.7	75	75	75.00	7	30791625	29.6	21.2	20.2	29.0	0.0	33.5	22.2	smartseq
1447023	SRR3638146	SRP076212	SRS1488236	SRX1826278	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189080: 1-0-1-0-BTN35-C57-1782070112-22ul-1-IL5413-N710-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189080		GSM2189080	1-0-1-0-BTN35-C57-1782070112-22ul-1-IL5413-N710-N505 BTN35 Mic-scRNA-Seq	62612850	417419	2016-07-18 10:56:32	29566970	62612850	417419	2	417419	index:0,count:417419,average:75,stdev:0|index:1,count:417419,average:75,stdev:0	GSM2189080_r4						2.85	3.41	0.06	42440224	41447796	40082425	39478969	97.66	98.49	340869	324939	165.894	739.787	80	2007	58.03	61.51	373280	197815	373280	197815	59.4	58.78	373280	202471	373280	189015	14595844	34.39	1.43	0	4.62	0	0.19	0	0.25	0	0.00	0	17.90	0	340869	0	150	0	146.25	0	1.44	0	0.01	0	1.18	0	0.00	0	60.11	0	0.72	0	5980	0	417419	0	19296	0	777	0	1060	0	0	0	74713	0	13	0	0	0	197	0	32475	0	349	0	33034	0	77.04	0	321573	0	11783	31306	2.656878553849	417419.0	340869.0	5980.0	19296.0	777.0	1060.0	0.0	74713.0	321573.0	81.7	1.4	4.6	0.2	0.3	0.0	17.9	77.0	75	75	75.00	7	31306425	29.7	21.1	20.1	29.1	0.0	33.8	22.6	smartseq
1447038	SRR3638147	SRP076212	SRS1488237	SRX1826279	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189081: 1-0-1-0-BTN35-C58-1782070112-22ul-1-IL5413-N712-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189081		GSM2189081	1-0-1-0-BTN35-C58-1782070112-22ul-1-IL5413-N712-N505 BTN35 Mic-scRNA-Seq	73010400	486736	2016-07-18 10:56:32	35060886	73010400	486736	2	486736	index:0,count:486736,average:75,stdev:0|index:1,count:486736,average:75,stdev:0	GSM2189081_r1						1.4	3.74	0.31	56604653	54192410	54072356	52204575	95.74	96.55	425272	403354	191.799	804.716	162	2041	52.78	55.33	461884	224449	461884	224449	53.59	53.32	461884	227894	461884	216316	22503940	39.76	1.13	0	4.03	0	0.22	0	0.30	0	0.00	0	12.11	0	425272	0	150	0	147.39	0	1.55	0	0.01	0	1.11	0	0.00	0	87.61	0	0.80	0	5510	0	486736	0	19606	0	1072	0	1457	0	0	0	58935	0	38	0	0	0	231	0	34576	0	452	0	35297	0	83.34	0	405666	0	13159	34388	2.613268485447	486736.0	425272.0	5510.0	19606.0	1072.0	1457.0	0.0	58935.0	405666.0	87.4	1.1	4.0	0.2	0.3	0.0	12.1	83.3	75	75	75.00	7	36505200	30.3	20.3	20.1	29.4	0.0	33.4	22.0	smartseq
1447039	SRR3639147	SRP076212	SRS1488550	SRX1826592	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189394: 1g_BTN7_C27_IL4709-703-505_AGGCAGAA-GTAAGGAG BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189394		GSM2189394	1g_BTN7_C27_IL4709-703-505_AGGCAGAA-GTAAGGAG BTN07 Mic-scRNA-Seq	579116022	2866911	2016-07-18 10:56:32	397177950	579116022	2866911	2	2866911	index:0,count:2866911,average:101,stdev:0|index:1,count:2866911,average:101,stdev:0	GSM2189394_r1						4.14	3.03	0.24	464817455	458483777	433884310	429939578	98.64	99.09	2594926	2194721	244.567	1108.463	167	13292	82.3	88.28	2876487	2135636	2876487	2135636	85.6	85.66	2876487	2221238	2876487	2072345	44866950	9.65	1.08	0	6.13	0	0.41	0	0.04	0	0.00	0	9.04	0	2594926	0	202	0	198.28	0	1.60	0	0.01	0	1.23	0	0.00	0	206.42	0	0.70	0	30890	0	2866911	0	175787	0	11768	0	1183	0	0	0	259034	0	458	0	0	0	4580	0	1068363	0	5022	0	1078423	0	84.38	0	2419139	0	21858	1042286	47.684417604538	2866911.0	2594926.0	30890.0	175787.0	11768.0	1183.0	0.0	259034.0	2419139.0	90.5	1.1	6.1	0.4	0.0	0.0	9.0	84.4	101	101	101.00	38	289558011	26.1	23.3	23.7	26.8	0.0	35.2	18.8	smartseq
1447053	SRR3638148	SRP076212	SRS1488237	SRX1826279	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189081: 1-0-1-0-BTN35-C58-1782070112-22ul-1-IL5413-N712-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189081		GSM2189081	1-0-1-0-BTN35-C58-1782070112-22ul-1-IL5413-N712-N505 BTN35 Mic-scRNA-Seq	72994800	486632	2016-07-18 10:56:32	34943135	72994800	486632	2	486632	index:0,count:486632,average:75,stdev:0|index:1,count:486632,average:75,stdev:0	GSM2189081_r2						1.39	3.76	0.27	57061379	54667217	54540489	52668496	95.8	96.57	427631	404933	194.473	788.514	142	2036	53.02	55.55	464277	226744	464277	226744	53.84	53.53	464277	230223	464277	218520	22556075	39.53	1.16	0	3.99	0	0.21	0	0.33	0	0.00	0	11.58	0	427631	0	150	0	147.44	0	1.52	0	0.01	0	1.12	0	0.00	0	109.49	0	0.79	0	5668	0	486632	0	19433	0	1043	0	1590	0	0	0	56368	0	49	0	0	0	293	0	35350	0	463	0	36155	0	83.88	0	408198	0	13434	35397	2.634881643591	486632.0	427631.0	5668.0	19433.0	1043.0	1590.0	0.0	56368.0	408198.0	87.9	1.2	4.0	0.2	0.3	0.0	11.6	83.9	75	75	75.00	7	36497400	30.1	20.3	20.1	29.4	0.0	33.5	22.2	smartseq
1447054	SRR3639148	SRP076212	SRS1488551	SRX1826593	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189395: 1g_BTN7_C28_IL4709-707-505_CTCTCTAC-GTAAGGAG BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189395		GSM2189395	1g_BTN7_C28_IL4709-707-505_CTCTCTAC-GTAAGGAG BTN07 Mic-scRNA-Seq	583399432	2888116	2016-07-18 10:56:32	400454512	583399432	2888116	2	2888116	index:0,count:2888116,average:101,stdev:0|index:1,count:2888116,average:101,stdev:0	GSM2189395_r1						1.09	2.83	1.14	462961294	416536347	444196134	400387599	89.97	90.14	2574426	2440862	248.214	666.351	188	13193	64.98	67.76	2796262	1672934	2796262	1672934	66.1	65.91	2796262	1701647	2796262	1627326	103282619	22.31	1.04	0	3.65	0	0.83	0	0.10	0	0.00	0	9.93	0	2574426	0	202	0	198.56	0	1.57	0	0.01	0	1.25	0	0.01	0	203.87	0	0.71	0	29901	0	2888116	0	105483	0	23880	0	2919	0	0	0	286891	0	227	0	0	0	2515	0	401708	0	4331	0	408781	0	85.49	0	2468943	0	7335	410669	55.987593728698	2888116.0	2574426.0	29901.0	105483.0	23880.0	2919.0	0.0	286891.0	2468943.0	89.1	1.0	3.7	0.8	0.1	0.0	9.9	85.5	101	101	101.00	38	291699716	26.9	22.6	22.8	27.7	0.0	35.0	18.2	smartseq
1447055	SRR3640148	SRP076212	SRS1489005	SRX1827048	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189850: C7_1000701204-OGC16-sal_1_2ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189850		GSM2189850	C7_1000701204-OGC16-sal_1_2ul_1 OGC16-sal FACS-scRNA-Seq	118342200	788948	2016-07-18 10:56:32	41005704	118342200	788948	2	788948	index:0,count:788948,average:75,stdev:0|index:1,count:788948,average:75,stdev:0	GSM2189850_r1						1.05	2.13	0.05	102375114	119705970	96518417	114367097	116.93	118.49	738717	668312	261.839	1365.869	125	3066	75.26	80.13	799082	555983	799082	555983	58.65	59.29	799082	433268	799082	411406	17104113	16.71	1.74	0	5.68	0	0.25	0	0.26	0	0.00	0	5.86	0	738717	0	150	0	148.20	0	4.69	0	0.08	0	1.06	0	0.02	0	189.35	0	0.26	0	13738	0	788948	0	44849	0	1947	0	2037	0	0	0	46247	0	77	0	0	0	841	0	109601	0	1202	0	111721	0	87.95	0	693868	0	20238	108279	5.350281648384	788948.0	738717.0	13738.0	44849.0	1947.0	2037.0	0.0	46247.0	693868.0	93.6	1.7	5.7	0.2	0.3	0.0	5.9	87.9	75	75	75.00	6	59171100	24.5	25.3	25.3	24.9	0.0	35.2	30.1	smartseq
1447069	SRR3638149	SRP076212	SRS1488237	SRX1826279	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189081: 1-0-1-0-BTN35-C58-1782070112-22ul-1-IL5413-N712-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189081		GSM2189081	1-0-1-0-BTN35-C58-1782070112-22ul-1-IL5413-N712-N505 BTN35 Mic-scRNA-Seq	73337550	488917	2016-07-18 10:56:32	35232722	73337550	488917	2	488917	index:0,count:488917,average:75,stdev:0|index:1,count:488917,average:75,stdev:0	GSM2189081_r3						1.37	3.72	0.25	56954089	54558694	54440727	52559925	95.79	96.55	427561	404877	192.759	828.445	162	2080	53.07	55.6	463992	226897	463992	226897	53.86	53.57	463992	230265	463992	218628	22496093	39.50	1.17	0	3.98	0	0.22	0	0.30	0	0.00	0	12.03	0	427561	0	150	0	147.39	0	1.51	0	0.01	0	1.12	0	0.00	0	76.53	0	0.82	0	5708	0	488917	0	19470	0	1078	0	1472	0	0	0	58806	0	41	0	0	0	273	0	35687	0	467	0	36468	0	83.47	0	408091	0	13340	35547	2.664692653673	488917.0	427561.0	5708.0	19470.0	1078.0	1472.0	0.0	58806.0	408091.0	87.5	1.2	4.0	0.2	0.3	0.0	12.0	83.5	75	75	75.00	7	36668775	30.2	20.3	20.1	29.3	0.0	33.4	22.1	smartseq
1447070	SRR3639149	SRP076212	SRS1488552	SRX1826594	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189396: 1g_BTN7_C30_IL4709-709-505_GCTACGCT-GTAAGGAG BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189396		GSM2189396	1g_BTN7_C30_IL4709-709-505_GCTACGCT-GTAAGGAG BTN07 Mic-scRNA-Seq	561098632	2777716	2016-07-18 10:56:32	384166633	561098632	2777716	2	2777716	index:0,count:2777716,average:101,stdev:0|index:1,count:2777716,average:101,stdev:0	GSM2189396_r1						2.21	3.1	1.62	446996369	401813118	425071539	383400462	89.89	90.2	2496974	2358202	244.021	670.989	188	12788	62.31	65.58	2728904	1555857	2728904	1555857	63.58	63.29	2728904	1587661	2728904	1501417	109341006	24.46	1.08	0	4.49	0	0.60	0	0.08	0	0.00	0	9.42	0	2496974	0	202	0	198.60	0	1.60	0	0.01	0	1.25	0	0.01	0	181.81	0	0.70	0	29944	0	2777716	0	124650	0	16756	0	2329	0	0	0	261657	0	373	0	0	0	3851	0	406461	0	5456	0	416141	0	85.41	0	2372324	0	9254	417111	45.073589799006	2777716.0	2496974.0	29944.0	124650.0	16756.0	2329.0	0.0	261657.0	2372324.0	89.9	1.1	4.5	0.6	0.1	0.0	9.4	85.4	101	101	101.00	38	280549316	27.1	22.6	22.7	27.7	0.0	35.2	18.7	smartseq
1447071	SRR3640149	SRP076212	SRS1489007	SRX1827049	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189851: C8_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189851		GSM2189851	C8_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	38462100	256414	2016-07-18 10:56:32	12774199	38462100	256414	2	256414	index:0,count:256414,average:75,stdev:0|index:1,count:256414,average:75,stdev:0	GSM2189851_r1						1.68	2.45	0.09	30080823	31928078	28429610	30442611	106.14	107.08	233020	219799	179.864	768.539	110	1528	69.21	73.45	252810	161273	252810	161273	61.91	62.21	252810	144262	252810	136585	6880198	22.87	2.00	0	5.25	0	0.24	0	0.29	0	0.00	0	8.59	0	233020	0	150	0	147.37	0	3.69	0	0.04	0	1.14	0	0.01	0	61.54	0	0.22	0	5125	0	256414	0	13466	0	614	0	749	0	0	0	22031	0	22	0	0	0	242	0	35405	0	336	0	36005	0	85.62	0	219554	0	13308	33186	2.493688007214	256414.0	233020.0	5125.0	13466.0	614.0	749.0	0.0	22031.0	219554.0	90.9	2.0	5.3	0.2	0.3	0.0	8.6	85.6	75	75	75.00	6	19231050	25.4	24.5	24.2	25.9	0.0	35.2	30.1	smartseq
1447179	SRR3638150	SRP076212	SRS1488237	SRX1826279	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189081: 1-0-1-0-BTN35-C58-1782070112-22ul-1-IL5413-N712-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189081		GSM2189081	1-0-1-0-BTN35-C58-1782070112-22ul-1-IL5413-N712-N505 BTN35 Mic-scRNA-Seq	75352200	502348	2016-07-18 10:56:32	35716628	75352200	502348	2	502348	index:0,count:502348,average:75,stdev:0|index:1,count:502348,average:75,stdev:0	GSM2189081_r4						1.35	3.72	0.28	58829619	56343098	56221919	54275742	95.77	96.54	440463	416954	195.191	827.865	157	2186	52.76	55.29	477999	232397	477999	232397	53.53	53.27	477999	235772	477999	223917	23411700	39.80	1.18	0	4.01	0	0.22	0	0.34	0	0.00	0	11.76	0	440463	0	150	0	147.45	0	1.48	0	0.01	0	1.14	0	0.00	0	90.42	0	0.74	0	5904	0	502348	0	20150	0	1103	0	1686	0	0	0	59096	0	47	0	0	0	301	0	36793	0	482	0	37623	0	83.67	0	420313	0	13660	36904	2.701610541728	502348.0	440463.0	5904.0	20150.0	1103.0	1686.0	0.0	59096.0	420313.0	87.7	1.2	4.0	0.2	0.3	0.0	11.8	83.7	75	75	75.00	7	37676100	30.2	20.3	20.1	29.4	0.0	33.8	22.5	smartseq
1447180	SRR3639150	SRP076212	SRS1488553	SRX1826595	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189397: 1g_BTN7_C31_IL4709-701-506_TAAGGCGA-ACTGCATA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189397		GSM2189397	1g_BTN7_C31_IL4709-701-506_TAAGGCGA-ACTGCATA BTN07 Mic-scRNA-Seq	507978086	2514743	2016-07-18 10:56:32	346817157	507978086	2514743	2	2514743	index:0,count:2514743,average:101,stdev:0|index:1,count:2514743,average:101,stdev:0	GSM2189397_r1						6.19	2.68	0.06	396228343	389997694	375020026	370423786	98.43	98.77	2200232	1871007	243.338	1025.831	167	11666	69.03	73.0	2357304	1518884	2357304	1518884	72.22	71.42	2357304	1589015	2357304	1485866	100593191	25.39	1.11	0	4.76	0	0.13	0	0.06	0	0.00	0	12.31	0	2200232	0	202	0	198.35	0	1.57	0	0.01	0	1.20	0	0.00	0	188.61	0	0.71	0	27986	0	2514743	0	119669	0	3361	0	1489	0	0	0	309661	0	261	0	0	0	2367	0	807884	0	3698	0	814210	0	82.73	0	2080563	0	19597	767550	39.166709190182	2514743.0	2200232.0	27986.0	119669.0	3361.0	1489.0	0.0	309661.0	2080563.0	87.5	1.1	4.8	0.1	0.1	0.0	12.3	82.7	101	101	101.00	38	253989043	26.5	22.7	23.1	27.7	0.0	35.0	18.2	smartseq
1447181	SRR3640150	SRP076212	SRS1489007	SRX1827049	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189851: C8_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189851		GSM2189851	C8_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	38558250	257055	2016-07-18 10:56:32	12877222	38558250	257055	2	257055	index:0,count:257055,average:75,stdev:0|index:1,count:257055,average:75,stdev:0	GSM2189851_r2						1.6	2.44	0.08	30047214	31849709	28388329	30345653	106.0	106.89	233064	219785	179.139	750.887	110	1495	69.12	73.4	252843	161103	252843	161103	61.94	62.31	252843	144360	252843	136755	6872695	22.87	1.94	0	5.29	0	0.26	0	0.28	0	0.00	0	8.80	0	233064	0	150	0	147.38	0	3.64	0	0.04	0	1.10	0	0.01	0	77.12	0	0.23	0	4986	0	257055	0	13590	0	658	0	709	0	0	0	22624	0	11	0	0	0	219	0	35604	0	333	0	36167	0	85.38	0	219474	0	13379	33378	2.494805291875	257055.0	233064.0	4986.0	13590.0	658.0	709.0	0.0	22624.0	219474.0	90.7	1.9	5.3	0.3	0.3	0.0	8.8	85.4	75	75	75.00	6	19279125	25.4	24.5	24.2	25.9	0.0	35.2	30.0	smartseq
1447182	SRR3641150	SRP076212	SRS1489262	SRX1827303	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190105: G7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190105		GSM2190105	G7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq	47650950	317673	2016-07-18 10:56:32	17998708	47650950	317673	2	317673	index:0,count:317673,average:75,stdev:0|index:1,count:317673,average:75,stdev:0	GSM2190105_r2						1.39	2.69	0.02	38466388	41557510	36253834	39543100	108.04	109.07	288919	256314	209.195	1369.279	125	1491	81.92	87.21	314882	236677	314882	236677	74.4	75.14	314882	214969	314882	203929	4074036	10.59	1.68	0	5.52	0	0.37	0	0.09	0	0.00	0	8.59	0	288919	0	150	0	147.57	0	4.11	0	0.04	0	1.17	0	0.02	0	114.36	0	0.31	0	5327	0	317673	0	17531	0	1180	0	301	0	0	0	27273	0	67	0	0	0	405	0	67445	0	348	0	68265	0	85.43	0	271388	0	19710	64662	3.280669710807	317673.0	288919.0	5327.0	17531.0	1180.0	301.0	0.0	27273.0	271388.0	90.9	1.7	5.5	0.4	0.1	0.0	8.6	85.4	75	75	75.00	6	23825475	24.5	25.6	25.3	24.7	0.0	34.7	27.8	smartseq
1447195	SRR3638151	SRP076212	SRS1488238	SRX1826280	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189082: 1-0-1-0-BTN35-C64-1782070112-14ul-1-IL5413-N707-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189082		GSM2189082	1-0-1-0-BTN35-C64-1782070112-14ul-1-IL5413-N707-N506 BTN35 Mic-scRNA-Seq	61435950	409573	2016-07-18 10:56:32	29135795	61435950	409573	2	409573	index:0,count:409573,average:75,stdev:0|index:1,count:409573,average:75,stdev:0	GSM2189082_r1						3.12	3.53	0.09	41622344	40500994	39358409	38589383	97.31	98.05	330572	316987	170.122	760.146	90	1856	50.8	53.77	360289	167946	360289	167946	52.06	50.96	360289	172111	360289	159179	17224309	41.38	1.27	0	4.45	0	0.19	0	0.28	0	0.00	0	18.82	0	330572	0	150	0	146.37	0	1.34	0	0.01	0	1.15	0	0.00	0	64.11	0	0.73	0	5210	0	409573	0	18231	0	794	0	1135	0	0	0	77072	0	23	0	0	0	139	0	24153	0	326	0	24641	0	76.26	0	312341	0	9372	23596	2.517712334614	409573.0	330572.0	5210.0	18231.0	794.0	1135.0	0.0	77072.0	312341.0	80.7	1.3	4.5	0.2	0.3	0.0	18.8	76.3	75	75	75.00	7	30717975	30.5	20.6	19.3	29.6	0.0	33.3	21.4	smartseq
1447196	SRR3639151	SRP076212	SRS1488554	SRX1826596	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189398: 1g_BTN7_C33_IL4709-703-506_AGGCAGAA-ACTGCATA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189398		GSM2189398	1g_BTN7_C33_IL4709-703-506_AGGCAGAA-ACTGCATA BTN07 Mic-scRNA-Seq	553817744	2741672	2016-07-18 10:56:32	376038214	553817744	2741672	2	2741672	index:0,count:2741672,average:101,stdev:0|index:1,count:2741672,average:101,stdev:0	GSM2189398_r1						4.74	3.76	0.25	428706174	421486726	408296361	402898503	98.32	98.68	2387371	2102750	241.945	881.299	167	12530	64.76	68.06	2551784	1546094	2551784	1546094	66.88	66.07	2551784	1596749	2551784	1500815	128957380	30.08	1.08	0	4.22	0	0.13	0	0.08	0	0.00	0	12.72	0	2387371	0	202	0	198.43	0	1.56	0	0.01	0	1.24	0	0.00	0	173.16	0	0.71	0	29537	0	2741672	0	115833	0	3511	0	2130	0	0	0	348660	0	177	0	0	0	2570	0	725328	0	3581	0	731656	0	82.85	0	2271538	0	17515	693365	39.586925492435	2741672.0	2387371.0	29537.0	115833.0	3511.0	2130.0	0.0	348660.0	2271538.0	87.1	1.1	4.2	0.1	0.1	0.0	12.7	82.9	101	101	101.00	38	276908872	26.9	22.4	22.7	28.0	0.0	35.1	18.1	smartseq
1447197	SRR3640151	SRP076212	SRS1489007	SRX1827049	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189851: C8_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189851		GSM2189851	C8_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	37903800	252692	2016-07-18 10:56:32	12710580	37903800	252692	2	252692	index:0,count:252692,average:75,stdev:0|index:1,count:252692,average:75,stdev:0	GSM2189851_r3						1.61	2.41	0.1	29723620	31462679	28102805	30020633	105.85	106.82	230078	216894	180.363	761.166	125	1508	69.28	73.5	249451	159393	249451	159393	62.01	62.37	249451	142669	249451	135254	6767506	22.77	1.95	0	5.23	0	0.25	0	0.29	0	0.00	0	8.41	0	230078	0	150	0	147.40	0	3.72	0	0.04	0	1.09	0	0.01	0	82.70	0	0.23	0	4919	0	252692	0	13226	0	622	0	734	0	0	0	21258	0	23	0	0	0	215	0	35123	0	305	0	35666	0	85.82	0	216852	0	13311	32974	2.477199308842	252692.0	230078.0	4919.0	13226.0	622.0	734.0	0.0	21258.0	216852.0	91.1	1.9	5.2	0.2	0.3	0.0	8.4	85.8	75	75	75.00	6	18951900	25.4	24.5	24.2	25.8	0.0	35.2	30.1	smartseq
1447198	SRR3641151	SRP076212	SRS1489262	SRX1827303	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190105: G7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190105		GSM2190105	G7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq	48347250	322315	2016-07-18 10:56:32	18407399	48347250	322315	2	322315	index:0,count:322315,average:75,stdev:0|index:1,count:322315,average:75,stdev:0	GSM2190105_r3						1.36	2.59	0.02	39167447	42309906	36942772	40279259	108.02	109.03	294002	260863	210.763	1385.086	125	1488	81.89	87.09	320335	240747	320335	240747	74.23	74.97	320335	218243	320335	207239	4184417	10.68	1.66	0	5.45	0	0.36	0	0.09	0	0.00	0	8.34	0	294002	0	150	0	147.57	0	4.10	0	0.04	0	1.15	0	0.01	0	82.88	0	0.30	0	5353	0	322315	0	17581	0	1150	0	288	0	0	0	26875	0	60	0	0	0	423	0	69002	0	410	0	69895	0	85.76	0	276421	0	19767	66082	3.343046491627	322315.0	294002.0	5353.0	17581.0	1150.0	288.0	0.0	26875.0	276421.0	91.2	1.7	5.5	0.4	0.1	0.0	8.3	85.8	75	75	75.00	6	24173625	24.5	25.6	25.3	24.7	0.0	34.6	27.6	smartseq
1447210	SRR3638152	SRP076212	SRS1488238	SRX1826280	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189082: 1-0-1-0-BTN35-C64-1782070112-14ul-1-IL5413-N707-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189082		GSM2189082	1-0-1-0-BTN35-C64-1782070112-14ul-1-IL5413-N707-N506 BTN35 Mic-scRNA-Seq	60736050	404907	2016-07-18 10:56:32	28687309	60736050	404907	2	404907	index:0,count:404907,average:75,stdev:0|index:1,count:404907,average:75,stdev:0	GSM2189082_r2						3.04	3.49	0.09	41918754	40824406	39655262	38911799	97.39	98.13	331878	317565	172.342	793.878	79	1836	51.08	54.03	361437	169512	361437	169512	52.28	51.2	361437	173498	361437	160654	17265506	41.19	1.32	0	4.48	0	0.19	0	0.27	0	0.00	0	17.58	0	331878	0	150	0	146.39	0	1.42	0	0.01	0	1.15	0	0.00	0	80.98	0	0.73	0	5360	0	404907	0	18122	0	775	0	1086	0	0	0	71168	0	20	0	0	0	170	0	25072	0	312	0	25574	0	77.49	0	313756	0	9639	24614	2.553584396722	404907.0	331878.0	5360.0	18122.0	775.0	1086.0	0.0	71168.0	313756.0	82.0	1.3	4.5	0.2	0.3	0.0	17.6	77.5	75	75	75.00	7	30368025	30.4	20.6	19.3	29.7	0.0	33.5	21.7	smartseq
1447211	SRR3639152	SRP076212	SRS1488555	SRX1826597	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189399: 1g_BTN7_C34_IL4709-707-506_CTCTCTAC-ACTGCATA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189399		GSM2189399	1g_BTN7_C34_IL4709-707-506_CTCTCTAC-ACTGCATA BTN07 Mic-scRNA-Seq	579511336	2868868	2016-07-18 10:56:32	394376119	579511336	2868868	2	2868868	index:0,count:2868868,average:101,stdev:0|index:1,count:2868868,average:101,stdev:0	GSM2189399_r1						8.21	2.63	0.06	443516363	435845944	411620967	406172106	98.27	98.68	2483075	2166490	234.553	896.820	167	13689	67.68	72.99	2700022	1680499	2700022	1680499	72.47	71.14	2700022	1799558	2700022	1637957	109154776	24.61	1.23	0	6.30	0	0.14	0	0.11	0	0.00	0	13.20	0	2483075	0	202	0	198.19	0	1.63	0	0.01	0	1.17	0	0.00	0	229.51	0	0.70	0	35346	0	2868868	0	180762	0	4038	0	3025	0	0	0	378730	0	299	0	0	0	2110	0	783685	0	3863	0	789957	0	80.25	0	2302313	0	11405	737756	64.687067075844	2868868.0	2483075.0	35346.0	180762.0	4038.0	3025.0	0.0	378730.0	2302313.0	86.6	1.2	6.3	0.1	0.1	0.0	13.2	80.3	101	101	101.00	38	289755668	26.8	22.4	22.8	28.0	0.0	35.0	18.0	smartseq
1447212	SRR3640152	SRP076212	SRS1489007	SRX1827049	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189851: C8_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189851		GSM2189851	C8_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	37612350	250749	2016-07-18 10:56:32	12696214	37612350	250749	2	250749	index:0,count:250749,average:75,stdev:0|index:1,count:250749,average:75,stdev:0	GSM2189851_r4						1.67	2.49	0.07	29419520	31218534	27823431	29792543	106.12	107.08	227933	215121	179.782	737.943	125	1449	69.38	73.59	247024	158144	247024	158144	62.04	62.36	247024	141407	247024	134018	6680357	22.71	2.01	0	5.20	0	0.26	0	0.26	0	0.00	0	8.58	0	227933	0	150	0	147.35	0	3.67	0	0.04	0	1.13	0	0.01	0	75.22	0	0.23	0	5048	0	250749	0	13030	0	649	0	664	0	0	0	21503	0	12	0	0	0	220	0	34017	0	295	0	34544	0	85.70	0	214903	0	13024	31799	2.441569410319	250749.0	227933.0	5048.0	13030.0	649.0	664.0	0.0	21503.0	214903.0	90.9	2.0	5.2	0.3	0.3	0.0	8.6	85.7	75	75	75.00	6	18806175	25.4	24.6	24.2	25.8	0.0	35.2	30.0	smartseq
1447213	SRR3641152	SRP076212	SRS1489262	SRX1827303	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190105: G7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190105		GSM2190105	G7_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq	47488350	316589	2016-07-18 10:56:32	18077193	47488350	316589	2	316589	index:0,count:316589,average:75,stdev:0|index:1,count:316589,average:75,stdev:0	GSM2190105_r4						1.38	2.65	0.02	38469726	41569502	36263259	39565625	108.06	109.11	288446	255539	211.104	1377.305	121	1485	81.91	87.17	314248	236264	314248	236264	74.22	74.95	314248	214072	314248	203141	4053716	10.54	1.69	0	5.49	0	0.37	0	0.10	0	0.00	0	8.42	0	288446	0	150	0	147.58	0	4.08	0	0.04	0	1.16	0	0.01	0	94.98	0	0.30	0	5345	0	316589	0	17394	0	1161	0	322	0	0	0	26660	0	75	0	0	0	372	0	67366	0	409	0	68222	0	85.62	0	271052	0	19713	64646	3.279358798762	316589.0	288446.0	5345.0	17394.0	1161.0	322.0	0.0	26660.0	271052.0	91.1	1.7	5.5	0.4	0.1	0.0	8.4	85.6	75	75	75.00	6	23744175	24.5	25.5	25.3	24.7	0.0	34.7	27.7	smartseq
1447229	SRR3638153	SRP076212	SRS1488238	SRX1826280	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189082: 1-0-1-0-BTN35-C64-1782070112-14ul-1-IL5413-N707-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189082		GSM2189082	1-0-1-0-BTN35-C64-1782070112-14ul-1-IL5413-N707-N506 BTN35 Mic-scRNA-Seq	61215450	408103	2016-07-18 10:56:32	29063726	61215450	408103	2	408103	index:0,count:408103,average:75,stdev:0|index:1,count:408103,average:75,stdev:0	GSM2189082_r3						3.09	3.54	0.09	41674896	40582678	39384446	38647437	97.38	98.13	330363	316360	171.169	763.397	110	1841	51.15	54.16	360737	168987	360737	168987	52.42	51.34	360737	173176	360737	160172	17120099	41.08	1.28	0	4.50	0	0.19	0	0.26	0	0.00	0	18.60	0	330363	0	150	0	146.37	0	1.39	0	0.01	0	1.17	0	0.00	0	73.46	0	0.75	0	5243	0	408103	0	18369	0	779	0	1064	0	0	0	75897	0	27	0	0	0	151	0	24562	0	299	0	25039	0	76.45	0	311994	0	9599	24141	2.514949473904	408103.0	330363.0	5243.0	18369.0	779.0	1064.0	0.0	75897.0	311994.0	81.0	1.3	4.5	0.2	0.3	0.0	18.6	76.4	75	75	75.00	7	30607725	30.5	20.6	19.4	29.5	0.0	33.3	21.4	smartseq
1447230	SRR3639153	SRP076212	SRS1488556	SRX1826598	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189400: 1g_BTN7_C35_IL4709-708-506_CAGAGAGG-ACTGCATA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189400		GSM2189400	1g_BTN7_C35_IL4709-708-506_CAGAGAGG-ACTGCATA BTN07 Mic-scRNA-Seq	606643168	3003184	2016-07-18 10:56:32	414227646	606643168	3003184	2	3003184	index:0,count:3003184,average:101,stdev:0|index:1,count:3003184,average:101,stdev:0	GSM2189400_r1						4.78	2.65	0.14	473356744	467677921	450545885	446374010	98.8	99.07	2644640	2303975	236.380	941.322	178	14121	66.51	69.94	2821575	1758941	2821575	1758941	68.87	68.11	2821575	1821390	2821575	1712907	135745557	28.68	1.08	0	4.32	0	0.11	0	0.06	0	0.00	0	11.77	0	2644640	0	202	0	198.37	0	1.61	0	0.01	0	1.22	0	0.00	0	193.06	0	0.71	0	32509	0	3003184	0	129816	0	3261	0	1833	0	0	0	353450	0	223	0	0	0	2636	0	863874	0	4700	0	871433	0	83.74	0	2514824	0	16312	821204	50.343550760177	3003184.0	2644640.0	32509.0	129816.0	3261.0	1833.0	0.0	353450.0	2514824.0	88.1	1.1	4.3	0.1	0.1	0.0	11.8	83.7	101	101	101.00	38	303321584	26.6	22.7	23.1	27.6	0.0	35.1	18.4	smartseq
1447231	SRR3640153	SRP076212	SRS1489008	SRX1827050	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189852: C8_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189852		GSM2189852	C8_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq	56124000	374160	2016-07-18 10:56:32	18864298	56124000	374160	2	374160	index:0,count:374160,average:75,stdev:0|index:1,count:374160,average:75,stdev:0	GSM2189852_r1						1.02	2.77	0.03	46310966	50262309	43729224	47930918	108.53	109.61	346934	305219	209.192	1470.791	134	1812	85.26	90.6	376270	295792	376270	295792	77.39	78.45	376270	268486	376270	256103	3704604	8.00	1.57	0	5.47	0	0.31	0	0.07	0	0.00	0	6.90	0	346934	0	150	0	147.77	0	4.02	0	0.04	0	1.12	0	0.01	0	112.25	0	0.23	0	5875	0	374160	0	20460	0	1142	0	254	0	0	0	25830	0	68	0	0	0	634	0	89038	0	553	0	90293	0	87.26	0	326474	0	26607	85385	3.209117901304	374160.0	346934.0	5875.0	20460.0	1142.0	254.0	0.0	25830.0	326474.0	92.7	1.6	5.5	0.3	0.1	0.0	6.9	87.3	75	75	75.00	6	28062000	24.4	25.5	25.3	24.7	0.0	35.2	30.1	smartseq
1447245	SRR3638154	SRP076212	SRS1488238	SRX1826280	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189082: 1-0-1-0-BTN35-C64-1782070112-14ul-1-IL5413-N707-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189082		GSM2189082	1-0-1-0-BTN35-C64-1782070112-14ul-1-IL5413-N707-N506 BTN35 Mic-scRNA-Seq	63156900	421046	2016-07-18 10:56:32	29586277	63156900	421046	2	421046	index:0,count:421046,average:75,stdev:0|index:1,count:421046,average:75,stdev:0	GSM2189082_r4						3.06	3.52	0.09	43116154	41972374	40797151	40018776	97.35	98.09	342254	327737	171.803	772.363	79	1913	51.06	54.01	373387	174747	373387	174747	52.22	51.2	373387	178708	373387	165648	17777551	41.23	1.33	0	4.44	0	0.21	0	0.28	0	0.00	0	18.23	0	342254	0	150	0	146.38	0	1.38	0	0.01	0	1.13	0	0.00	0	56.14	0	0.69	0	5599	0	421046	0	18697	0	866	0	1175	0	0	0	76751	0	22	0	0	0	155	0	25486	0	295	0	25958	0	76.85	0	323557	0	9729	24868	2.556069482989	421046.0	342254.0	5599.0	18697.0	866.0	1175.0	0.0	76751.0	323557.0	81.3	1.3	4.4	0.2	0.3	0.0	18.2	76.8	75	75	75.00	7	31578450	30.5	20.5	19.3	29.7	0.0	33.6	21.8	smartseq
1447246	SRR3639154	SRP076212	SRS1488557	SRX1826599	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189401: 1g_BTN7_C36_IL4709-709-506_GCTACGCT-ACTGCATA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189401		GSM2189401	1g_BTN7_C36_IL4709-709-506_GCTACGCT-ACTGCATA BTN07 Mic-scRNA-Seq	526379276	2605838	2016-07-18 10:56:32	357494370	526379276	2605838	2	2605838	index:0,count:2605838,average:101,stdev:0|index:1,count:2605838,average:101,stdev:0	GSM2189401_r1						3.26	2.66	0.49	403328803	378221782	384778306	361670011	93.78	93.99	2259240	2124894	242.778	694.255	188	11842	69.87	73.31	2427681	1578431	2427681	1578431	71.43	71.27	2427681	1613743	2427681	1534456	80963967	20.07	1.03	0	4.07	0	0.21	0	0.11	0	0.00	0	12.98	0	2259240	0	202	0	198.22	0	1.70	0	0.01	0	1.20	0	0.01	0	167.52	0	0.72	0	26917	0	2605838	0	106180	0	5403	0	2859	0	0	0	338336	0	620	0	0	0	3166	0	400720	0	4381	0	408887	0	82.62	0	2153060	0	7702	402177	52.217216307453	2605838.0	2259240.0	26917.0	106180.0	5403.0	2859.0	0.0	338336.0	2153060.0	86.7	1.0	4.1	0.2	0.1	0.0	13.0	82.6	101	101	101.00	38	263189638	27.0	22.5	22.6	27.8	0.0	35.0	18.1	smartseq
1447247	SRR3640154	SRP076212	SRS1489013	SRX1827055	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189857: C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189857		GSM2189857	C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	125700	838	2016-07-18 10:56:32	83219	125700	838	2	838	index:0,count:838,average:75,stdev:0|index:1,count:838,average:75,stdev:0	GSM2189857_r2						1.82	2.55	0.0	30218	32177	28403	30235	106.48	106.45	253	239	150.937	497.383	106	7	79.45	84.81	275	201	275	201	73.91	74.68	275	187	275	177	3578	11.84	1.31	0	1.91	0	0.12	0	0.00	0	0.00	0	69.69	0	253	0	150	0	146.03	0	1.00	0	0.01	0	1.00	0	0.01	0	1.51	0	0.26	0	11	0	838	0	16	0	1	0	0	0	0	0	584	0	0	0	0	0	0	0	67	0	0	0	67	0	28.28	0	237	0	58	59	1.017241379310	838.0	253.0	11.0	16.0	1.0	0.0	0.0	584.0	237.0	30.2	1.3	1.9	0.1	0.0	0.0	69.7	28.3	75	75	75.00	6	62850	22.1	29.1	27.3	21.5	0.0	35.2	30.0	smartseq
1447262	SRR3638155	SRP076212	SRS1488239	SRX1826281	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189083: 1-0-1-0-BTN35-C65-1782070112-14ul-1-IL5413-N708-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189083		GSM2189083	1-0-1-0-BTN35-C65-1782070112-14ul-1-IL5413-N708-N506 BTN35 Mic-scRNA-Seq	58212000	388080	2016-07-18 10:56:32	27727460	58212000	388080	2	388080	index:0,count:388080,average:75,stdev:0|index:1,count:388080,average:75,stdev:0	GSM2189083_r1						0.82	3.88	0.26	40376546	39369268	38385926	37730058	97.51	98.29	317339	299756	176.099	829.739	90	1671	63.68	67.07	345900	202084	345900	202084	64.39	64.36	345900	204321	345900	193901	11705117	28.99	1.24	0	4.14	0	0.19	0	0.18	0	0.00	0	17.86	0	317339	0	150	0	146.47	0	1.40	0	0.01	0	1.24	0	0.00	0	49.90	0	0.77	0	4818	0	388080	0	16052	0	726	0	695	0	0	0	69320	0	22	0	0	0	228	0	32334	0	375	0	32959	0	77.64	0	301287	0	11857	31667	2.670743021000	388080.0	317339.0	4818.0	16052.0	726.0	695.0	0.0	69320.0	301287.0	81.8	1.2	4.1	0.2	0.2	0.0	17.9	77.6	75	75	75.00	7	29106000	30.5	20.6	19.8	29.1	0.0	33.3	21.3	smartseq
1447263	SRR3639155	SRP076212	SRS1488558	SRX1826600	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189402: 1g_BTN7_C40_IL4709-707-507_CTCTCTAC-AAGGAGTA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189402		GSM2189402	1g_BTN7_C40_IL4709-707-507_CTCTCTAC-AAGGAGTA BTN07 Mic-scRNA-Seq	495512868	2453034	2016-07-18 10:56:32	338514322	495512868	2453034	2	2453034	index:0,count:2453034,average:101,stdev:0|index:1,count:2453034,average:101,stdev:0	GSM2189402_r1						1.96	1.9	0.66	386290501	340780131	366802043	324165293	88.22	88.38	2154642	2056581	246.880	622.453	188	11202	64.14	67.67	2360308	1382041	2360308	1382041	65.5	65.59	2360308	1411262	2360308	1339623	78381379	20.29	1.20	0	4.58	0	0.34	0	0.09	0	0.00	0	11.74	0	2154642	0	202	0	198.27	0	1.83	0	0.02	0	1.27	0	0.01	0	215.39	0	0.69	0	29558	0	2453034	0	112256	0	8223	0	2237	0	0	0	287932	0	185	0	0	0	1926	0	297009	0	3561	0	302681	0	83.26	0	2042386	0	6854	306081	44.657280420193	2453034.0	2154642.0	29558.0	112256.0	8223.0	2237.0	0.0	287932.0	2042386.0	87.8	1.2	4.6	0.3	0.1	0.0	11.7	83.3	101	101	101.00	38	247756434	26.7	22.7	22.9	27.8	0.0	34.8	17.5	smartseq
1447277	SRR3638156	SRP076212	SRS1488239	SRX1826281	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189083: 1-0-1-0-BTN35-C65-1782070112-14ul-1-IL5413-N708-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189083		GSM2189083	1-0-1-0-BTN35-C65-1782070112-14ul-1-IL5413-N708-N506 BTN35 Mic-scRNA-Seq	57460950	383073	2016-07-18 10:56:32	27286917	57460950	383073	2	383073	index:0,count:383073,average:75,stdev:0|index:1,count:383073,average:75,stdev:0	GSM2189083_r2						0.8	3.88	0.26	40319122	39352871	38355594	37727703	97.6	98.36	316396	298060	177.525	848.787	134	1645	63.91	67.27	344520	202216	344520	202216	64.52	64.51	344520	204135	344520	193915	11625775	28.83	1.28	0	4.12	0	0.21	0	0.18	0	0.00	0	17.01	0	316396	0	150	0	146.53	0	1.40	0	0.01	0	1.20	0	0.00	0	68.95	0	0.77	0	4896	0	383073	0	15784	0	818	0	682	0	0	0	65177	0	23	0	0	0	227	0	32901	0	335	0	33486	0	78.47	0	300612	0	11874	31983	2.693532086913	383073.0	316396.0	4896.0	15784.0	818.0	682.0	0.0	65177.0	300612.0	82.6	1.3	4.1	0.2	0.2	0.0	17.0	78.5	75	75	75.00	7	28730475	30.4	20.6	19.8	29.2	0.0	33.4	21.6	smartseq
1447278	SRR3639156	SRP076212	SRS1488560	SRX1826601	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189403: 1g_BTN7_C42_IL4709-709-507_GCTACGCT-AAGGAGTA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189403		GSM2189403	1g_BTN7_C42_IL4709-709-507_GCTACGCT-AAGGAGTA BTN07 Mic-scRNA-Seq	458299822	2268811	2016-07-18 10:56:32	310330899	458299822	2268811	2	2268811	index:0,count:2268811,average:101,stdev:0|index:1,count:2268811,average:101,stdev:0	GSM2189403_r1						7.82	2.55	2.52	348587427	330585607	328045265	313388142	94.84	95.53	1968644	1897740	233.588	610.716	188	11229	69.29	73.67	2147683	1364136	2147683	1364136	72.02	71.92	2147683	1417720	2147683	1331665	73435701	21.07	1.23	0	5.16	0	0.47	0	0.15	0	0.00	0	12.61	0	1968644	0	202	0	197.96	0	1.69	0	0.01	0	1.26	0	0.01	0	194.47	0	0.67	0	27844	0	2268811	0	117064	0	10735	0	3337	0	0	0	286095	0	52	0	0	0	574	0	187074	0	3402	0	191102	0	81.61	0	1851580	0	2854	186507	65.349334267694	2268811.0	1968644.0	27844.0	117064.0	10735.0	3337.0	0.0	286095.0	1851580.0	86.8	1.2	5.2	0.5	0.1	0.0	12.6	81.6	101	101	101.00	38	229149911	27.2	22.0	22.2	28.5	0.0	34.9	17.5	smartseq
1447279	SRR3640156	SRP076212	SRS1489008	SRX1827050	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189852: C8_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189852		GSM2189852	C8_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq	55560000	370400	2016-07-18 10:56:32	18871521	55560000	370400	2	370400	index:0,count:370400,average:75,stdev:0|index:1,count:370400,average:75,stdev:0	GSM2189852_r3						1.01	2.75	0.03	45946305	49900685	43392004	47588408	108.61	109.67	344017	302642	208.997	1452.787	126	1851	85.27	90.6	373610	293348	373610	293348	77.34	78.35	373610	266058	373610	253688	3677646	8.00	1.59	0	5.47	0	0.30	0	0.06	0	0.00	0	6.76	0	344017	0	150	0	147.78	0	4.06	0	0.04	0	1.14	0	0.01	0	111.12	0	0.23	0	5878	0	370400	0	20244	0	1095	0	233	0	0	0	25055	0	62	0	0	0	587	0	86957	0	507	0	88113	0	87.41	0	323773	0	26394	83728	3.172236114268	370400.0	344017.0	5878.0	20244.0	1095.0	233.0	0.0	25055.0	323773.0	92.9	1.6	5.5	0.3	0.1	0.0	6.8	87.4	75	75	75.00	6	27780000	24.4	25.6	25.3	24.7	0.0	35.2	30.1	smartseq
1447291	SRR3638157	SRP076212	SRS1488239	SRX1826281	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189083: 1-0-1-0-BTN35-C65-1782070112-14ul-1-IL5413-N708-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189083		GSM2189083	1-0-1-0-BTN35-C65-1782070112-14ul-1-IL5413-N708-N506 BTN35 Mic-scRNA-Seq	58445250	389635	2016-07-18 10:56:32	27879470	58445250	389635	2	389635	index:0,count:389635,average:75,stdev:0|index:1,count:389635,average:75,stdev:0	GSM2189083_r3						0.8	3.83	0.23	40656636	39651728	38655078	37992212	97.53	98.29	319055	300612	176.734	828.173	105	1663	63.97	67.38	347554	204114	347554	204114	64.64	64.6	347554	206250	347554	195694	11655960	28.67	1.22	0	4.14	0	0.21	0	0.19	0	0.00	0	17.72	0	319055	0	150	0	146.53	0	1.37	0	0.01	0	1.21	0	0.00	0	48.37	0	0.79	0	4754	0	389635	0	16135	0	807	0	721	0	0	0	69052	0	35	0	0	0	233	0	33428	0	316	0	34012	0	77.74	0	302920	0	12104	32774	2.707699933906	389635.0	319055.0	4754.0	16135.0	807.0	721.0	0.0	69052.0	302920.0	81.9	1.2	4.1	0.2	0.2	0.0	17.7	77.7	75	75	75.00	7	29222625	30.5	20.7	19.9	29.0	0.0	33.3	21.4	smartseq
1447292	SRR3639157	SRP076212	SRS1488559	SRX1826602	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189404: 1g_BTN7_C43_IL4709-701-508_TAAGGCGA-CTAAGCCT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189404		GSM2189404	1g_BTN7_C43_IL4709-701-508_TAAGGCGA-CTAAGCCT BTN07 Mic-scRNA-Seq	416961128	2064164	2016-07-18 10:56:32	285940231	416961128	2064164	2	2064164	index:0,count:2064164,average:101,stdev:0|index:1,count:2064164,average:101,stdev:0	GSM2189404_r1						7.75	2.68	0.19	323463027	320736948	302967482	301611446	99.16	99.55	1791713	1527293	246.756	1093.059	167	9117	75.23	80.4	1941507	1347865	1941507	1347865	78.5	77.88	1941507	1406503	1941507	1305611	57653671	17.82	1.10	0	5.59	0	0.12	0	0.04	0	0.00	0	13.04	0	1791713	0	202	0	198.24	0	1.88	0	0.01	0	1.21	0	0.00	0	140.21	0	0.71	0	22715	0	2064164	0	115309	0	2471	0	761	0	0	0	269219	0	190	0	0	0	2099	0	645039	0	2857	0	650185	0	81.21	0	1676404	0	16415	618929	37.705086810844	2064164.0	1791713.0	22715.0	115309.0	2471.0	761.0	0.0	269219.0	1676404.0	86.8	1.1	5.6	0.1	0.0	0.0	13.0	81.2	101	101	101.00	38	208480564	26.4	22.8	23.2	27.6	0.0	34.7	17.7	smartseq
1447293	SRR3640157	SRP076212	SRS1489008	SRX1827050	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189852: C8_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189852		GSM2189852	C8_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq	54873600	365824	2016-07-18 10:56:32	18788709	54873600	365824	2	365824	index:0,count:365824,average:75,stdev:0|index:1,count:365824,average:75,stdev:0	GSM2189852_r4						0.97	2.73	0.03	45301443	49190223	42808752	46917304	108.58	109.6	339247	298598	209.105	1458.242	125	1824	85.29	90.56	368122	289327	368122	289327	77.38	78.38	368122	262505	368122	250399	3638410	8.03	1.56	0	5.40	0	0.31	0	0.07	0	0.00	0	6.89	0	339247	0	150	0	147.76	0	4.05	0	0.04	0	1.12	0	0.01	0	109.75	0	0.24	0	5701	0	365824	0	19759	0	1120	0	267	0	0	0	25190	0	63	0	0	0	564	0	85979	0	552	0	87158	0	87.33	0	319488	0	26445	82503	3.119795802609	365824.0	339247.0	5701.0	19759.0	1120.0	267.0	0.0	25190.0	319488.0	92.7	1.6	5.4	0.3	0.1	0.0	6.9	87.3	75	75	75.00	6	27436800	24.4	25.6	25.3	24.7	0.0	35.2	29.9	smartseq
1447294	SRR3641157	SRP076212	SRS1489263	SRX1827305	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190107: G8_1000700102-OGC9-sal_1_8ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190107		GSM2190107	G8_1000700102-OGC9-sal_1_8ul_1 OGC09-sal FACS-scRNA-Seq	77146650	514311	2016-07-18 10:56:32	32443304	77146650	514311	2	514311	index:0,count:514311,average:75,stdev:0|index:1,count:514311,average:75,stdev:0	GSM2190107_r1						1.74	2.42	0.05	62263913	69156351	58003182	65304433	111.07	112.59	455127	420684	220.194	1111.747	174	2480	72.18	77.83	500565	328532	500565	328532	60.64	61.4	500565	276000	500565	259198	11617907	18.66	2.27	0	6.42	0	0.27	0	0.21	0	0.00	0	11.04	0	455127	0	150	0	147.37	0	4.97	0	0.10	0	1.10	0	0.03	0	142.42	0	0.49	0	11671	0	514311	0	33005	0	1365	0	1059	0	0	0	56760	0	65	0	0	0	378	0	61948	0	766	0	63157	0	82.08	0	422122	0	20466	60704	2.966090100655	514311.0	455127.0	11671.0	33005.0	1365.0	1059.0	0.0	56760.0	422122.0	88.5	2.3	6.4	0.3	0.2	0.0	11.0	82.1	75	75	75.00	6	38573325	25.0	24.6	24.8	25.5	0.0	33.7	25.3	smartseq
1447309	SRR3638158	SRP076212	SRS1488239	SRX1826281	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189083: 1-0-1-0-BTN35-C65-1782070112-14ul-1-IL5413-N708-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189083		GSM2189083	1-0-1-0-BTN35-C65-1782070112-14ul-1-IL5413-N708-N506 BTN35 Mic-scRNA-Seq	60150000	401000	2016-07-18 10:56:32	28308559	60150000	401000	2	401000	index:0,count:401000,average:75,stdev:0|index:1,count:401000,average:75,stdev:0	GSM2189083_r4						0.8	3.78	0.22	41935275	40880311	39911771	39205915	97.48	98.23	329499	310668	177.121	816.835	90	1751	63.98	67.31	358433	210807	358433	210807	64.6	64.58	358433	212851	358433	202256	12036934	28.70	1.26	0	4.07	0	0.20	0	0.19	0	0.00	0	17.44	0	329499	0	150	0	146.52	0	1.42	0	0.01	0	1.22	0	0.00	0	60.15	0	0.72	0	5036	0	401000	0	16304	0	794	0	758	0	0	0	69949	0	36	0	0	0	219	0	34437	0	368	0	35060	0	78.10	0	313195	0	12252	33638	2.745510936990	401000.0	329499.0	5036.0	16304.0	794.0	758.0	0.0	69949.0	313195.0	82.2	1.3	4.1	0.2	0.2	0.0	17.4	78.1	75	75	75.00	7	30075000	30.4	20.6	19.8	29.2	0.0	33.6	21.7	smartseq
1447310	SRR3639158	SRP076212	SRS1488561	SRX1826603	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189405: 1g_BTN7_C59_IL4709-711-502_AAGAGGCA-CTCTCTAT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189405		GSM2189405	1g_BTN7_C59_IL4709-711-502_AAGAGGCA-CTCTCTAT BTN07 Mic-scRNA-Seq	600445606	2972503	2016-07-18 10:56:32	410312923	600445606	2972503	2	2972503	index:0,count:2972503,average:101,stdev:0|index:1,count:2972503,average:101,stdev:0	GSM2189405_r1						1.34	4.06	0.55	469161530	449816177	447452733	430721161	95.88	96.26	2594927	2417359	257.250	764.928	182	12382	69.21	72.62	2835882	1795947	2835882	1795947	70.57	70.55	2835882	1831181	2835882	1744850	109265166	23.29	1.01	0	4.10	0	0.73	0	0.07	0	0.00	0	11.90	0	2594927	0	202	0	198.44	0	1.56	0	0.01	0	1.29	0	0.01	0	152.87	0	0.72	0	30026	0	2972503	0	121843	0	21687	0	2204	0	0	0	353685	0	145	0	0	0	2512	0	498617	0	5594	0	506868	0	83.20	0	2473084	0	9391	511085	54.422851666489	2972503.0	2594927.0	30026.0	121843.0	21687.0	2204.0	0.0	353685.0	2473084.0	87.3	1.0	4.1	0.7	0.1	0.0	11.9	83.2	101	101	101.00	38	300222803	26.8	22.7	22.9	27.5	0.0	34.9	18.2	smartseq
1447311	SRR3640158	SRP076212	SRS1489009	SRX1827051	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189853: C8_1000700602-OGC11-sal_1_10ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189853		GSM2189853	C8_1000700602-OGC11-sal_1_10ul_1 OGC11-sal FACS-scRNA-Seq	65883300	439222	2016-07-18 10:56:32	24621852	65883300	439222	2	439222	index:0,count:439222,average:75,stdev:0|index:1,count:439222,average:75,stdev:0	GSM2189853_r1						2.16	2.14	0.04	52188906	59591334	48509969	56188890	114.18	115.83	395076	362363	201.735	1093.972	110	2353	76.13	82.28	437103	300777	437103	300777	62.88	63.15	437103	248410	437103	230851	7630400	14.62	2.05	0	6.72	0	0.33	0	0.16	0	0.00	0	9.56	0	395076	0	150	0	147.41	0	4.47	0	0.06	0	1.05	0	0.02	0	121.63	0	0.31	0	9008	0	439222	0	29528	0	1453	0	695	0	0	0	41998	0	45	0	0	0	388	0	68017	0	598	0	69048	0	83.23	0	365548	0	13579	65767	4.843287429118	439222.0	395076.0	9008.0	29528.0	1453.0	695.0	0.0	41998.0	365548.0	89.9	2.1	6.7	0.3	0.2	0.0	9.6	83.2	75	75	75.00	6	32941650	24.6	25.3	25.1	24.9	0.0	34.7	27.8	smartseq
1447324	SRR3638159	SRP076212	SRS1488240	SRX1826282	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189084: 1-0-1-0-BTN35-C66-1782070112-8ul-1-IL5413-N709-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189084		GSM2189084	1-0-1-0-BTN35-C66-1782070112-8ul-1-IL5413-N709-N506 BTN35 Mic-scRNA-Seq	44907750	299385	2016-07-18 10:56:32	21193240	44907750	299385	2	299385	index:0,count:299385,average:75,stdev:0|index:1,count:299385,average:75,stdev:0	GSM2189084_r1						7.78	3.49	0.15	29507876	29526775	26559082	26880808	100.06	101.21	238740	225633	163.922	710.498	100	1464	74.84	83.18	272779	178679	272779	178679	79.46	79.22	272779	189711	272779	170179	4325835	14.66	1.49	0	7.99	0	0.17	0	0.18	0	0.00	0	19.90	0	238740	0	150	0	145.76	0	1.41	0	0.01	0	1.16	0	0.00	0	46.86	0	0.73	0	4467	0	299385	0	23918	0	520	0	537	0	0	0	59588	0	31	0	0	0	188	0	28246	0	218	0	28683	0	71.75	0	214822	0	9172	27274	2.973615351068	299385.0	238740.0	4467.0	23918.0	520.0	537.0	0.0	59588.0	214822.0	79.7	1.5	8.0	0.2	0.2	0.0	19.9	71.8	75	75	75.00	7	22453875	29.9	21.3	19.9	28.9	0.0	33.4	21.5	smartseq
1447325	SRR3639159	SRP076212	SRS1488562	SRX1826604	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189406: 1g_BTN7_C63_IL4709-706-503_TAGGCATG-TATCCTCT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189406		GSM2189406	1g_BTN7_C63_IL4709-706-503_TAGGCATG-TATCCTCT BTN07 Mic-scRNA-Seq	631331608	3125404	2016-07-18 10:56:32	431362281	631331608	3125404	2	3125404	index:0,count:3125404,average:101,stdev:0|index:1,count:3125404,average:101,stdev:0	GSM2189406_r1						1.94	2.92	1.84	500879393	429533798	476208424	410332379	85.76	86.17	2774561	2649042	251.592	690.223	182	13714	56.17	59.13	3063365	1558499	3063365	1558499	57.67	57.44	3063365	1600051	3063365	1514048	134819399	26.92	1.00	0	4.44	0	0.74	0	0.12	0	0.00	0	10.36	0	2774561	0	202	0	198.66	0	1.55	0	0.01	0	1.24	0	0.01	0	138.91	0	0.71	0	31134	0	3125404	0	138863	0	23268	0	3819	0	0	0	323756	0	50	0	0	0	2531	0	360351	0	4908	0	367840	0	84.33	0	2635698	0	7444	368673	49.526195593767	3125404.0	2774561.0	31134.0	138863.0	23268.0	3819.0	0.0	323756.0	2635698.0	88.8	1.0	4.4	0.7	0.1	0.0	10.4	84.3	101	101	101.00	38	315665804	27.2	22.3	22.5	27.9	0.0	35.1	18.4	smartseq
1447326	SRR3640159	SRP076212	SRS1489009	SRX1827051	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189853: C8_1000700602-OGC11-sal_1_10ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189853		GSM2189853	C8_1000700602-OGC11-sal_1_10ul_1 OGC11-sal FACS-scRNA-Seq	63552900	423686	2016-07-18 10:56:32	23741202	63552900	423686	2	423686	index:0,count:423686,average:75,stdev:0|index:1,count:423686,average:75,stdev:0	GSM2189853_r2						2.13	2.16	0.05	50387837	57478127	46841104	54203980	114.07	115.72	381024	349492	202.005	1086.114	110	2263	76.05	82.16	421043	289751	421043	289751	62.82	63.12	421043	239357	421043	222592	7428233	14.74	2.03	0	6.69	0	0.35	0	0.16	0	0.00	0	9.56	0	381024	0	150	0	147.42	0	4.49	0	0.06	0	1.04	0	0.02	0	127.11	0	0.33	0	8622	0	423686	0	28355	0	1477	0	678	0	0	0	40507	0	43	0	0	0	423	0	66093	0	554	0	67113	0	83.24	0	352669	0	13487	63972	4.743234225551	423686.0	381024.0	8622.0	28355.0	1477.0	678.0	0.0	40507.0	352669.0	89.9	2.0	6.7	0.3	0.2	0.0	9.6	83.2	75	75	75.00	6	31776450	24.6	25.3	25.1	24.9	0.0	34.7	27.8	smartseq
1447327	SRR3641159	SRP076212	SRS1489263	SRX1827305	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190107: G8_1000700102-OGC9-sal_1_8ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190107		GSM2190107	G8_1000700102-OGC9-sal_1_8ul_1 OGC09-sal FACS-scRNA-Seq	75164700	501098	2016-07-18 10:56:32	32051931	75164700	501098	2	501098	index:0,count:501098,average:75,stdev:0|index:1,count:501098,average:75,stdev:0	GSM2190107_r3						1.73	2.41	0.04	60485409	67174582	56278925	63389708	111.06	112.63	442234	409101	219.802	1087.588	174	2373	72.21	77.94	486767	319335	486767	319335	60.69	61.46	486767	268405	486767	251817	11221488	18.55	2.23	0	6.49	0	0.26	0	0.20	0	0.00	0	11.29	0	442234	0	150	0	147.32	0	4.92	0	0.10	0	1.09	0	0.03	0	106.11	0	0.56	0	11164	0	501098	0	32517	0	1278	0	994	0	0	0	56592	0	62	0	0	0	378	0	59842	0	696	0	60978	0	81.76	0	409717	0	20047	58647	2.925475133436	501098.0	442234.0	11164.0	32517.0	1278.0	994.0	0.0	56592.0	409717.0	88.3	2.2	6.5	0.3	0.2	0.0	11.3	81.8	75	75	75.00	6	37582350	25.1	24.6	24.8	25.5	0.0	33.5	24.8	smartseq
1447438	SRR3638160	SRP076212	SRS1488240	SRX1826282	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189084: 1-0-1-0-BTN35-C66-1782070112-8ul-1-IL5413-N709-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189084		GSM2189084	1-0-1-0-BTN35-C66-1782070112-8ul-1-IL5413-N709-N506 BTN35 Mic-scRNA-Seq	43478850	289859	2016-07-18 10:56:32	20410853	43478850	289859	2	289859	index:0,count:289859,average:75,stdev:0|index:1,count:289859,average:75,stdev:0	GSM2189084_r2						7.76	3.45	0.12	29521171	29543957	26587075	26903242	100.08	101.19	238244	224852	165.841	720.318	77	1455	74.92	83.2	271638	178491	271638	178491	79.58	79.3	271638	189587	271638	170115	4307447	14.59	1.50	0	8.18	0	0.18	0	0.18	0	0.00	0	17.45	0	238244	0	150	0	145.81	0	1.48	0	0.01	0	1.19	0	0.01	0	61.38	0	0.71	0	4339	0	289859	0	23716	0	524	0	517	0	0	0	50574	0	31	0	0	0	160	0	28525	0	188	0	28904	0	74.01	0	214528	0	9114	27507	3.018104015800	289859.0	238244.0	4339.0	23716.0	524.0	517.0	0.0	50574.0	214528.0	82.2	1.5	8.2	0.2	0.2	0.0	17.4	74.0	75	75	75.00	7	21739425	29.8	21.1	19.9	29.1	0.0	33.6	21.9	smartseq
1447439	SRR3639160	SRP076212	SRS1488563	SRX1826605	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189407: 1g_BTN7_C69_IL4709-706-504_TAGGCATG-AGAGTAGA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189407		GSM2189407	1g_BTN7_C69_IL4709-706-504_TAGGCATG-AGAGTAGA BTN07 Mic-scRNA-Seq	545708252	2701526	2016-07-18 10:56:32	373827272	545708252	2701526	2	2701526	index:0,count:2701526,average:101,stdev:0|index:1,count:2701526,average:101,stdev:0	GSM2189407_r1						2.39	3.6	2.03	428389284	396946148	410938796	383714649	92.66	93.38	2419121	2334980	231.137	609.807	188	13663	68.77	71.74	2610108	1663551	2610108	1663551	69.83	70.34	2610108	1689282	2610108	1631003	93747330	21.88	0.94	0	3.71	0	0.43	0	0.12	0	0.00	0	9.90	0	2419121	0	202	0	198.50	0	1.52	0	0.01	0	1.29	0	0.01	0	202.61	0	0.68	0	25310	0	2701526	0	100232	0	11576	0	3307	0	0	0	267522	0	33	0	0	0	1731	0	245065	0	4998	0	251827	0	85.84	0	2318889	0	3672	249345	67.904411764706	2701526.0	2419121.0	25310.0	100232.0	11576.0	3307.0	0.0	267522.0	2318889.0	89.5	0.9	3.7	0.4	0.1	0.0	9.9	85.8	101	101	101.00	38	272854126	27.3	22.3	22.4	28.0	0.0	35.1	18.6	smartseq
1447454	SRR3638161	SRP076212	SRS1488240	SRX1826282	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189084: 1-0-1-0-BTN35-C66-1782070112-8ul-1-IL5413-N709-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189084		GSM2189084	1-0-1-0-BTN35-C66-1782070112-8ul-1-IL5413-N709-N506 BTN35 Mic-scRNA-Seq	44565900	297106	2016-07-18 10:56:32	21044953	44565900	297106	2	297106	index:0,count:297106,average:75,stdev:0|index:1,count:297106,average:75,stdev:0	GSM2189084_r3						7.72	3.46	0.11	29438534	29483998	26507656	26840375	100.15	101.26	237906	224736	165.050	717.089	102	1425	74.85	83.15	271336	178079	271336	178079	79.48	79.21	271336	189081	271336	169628	4325602	14.69	1.53	0	7.99	0	0.18	0	0.18	0	0.00	0	19.57	0	237906	0	150	0	145.77	0	1.44	0	0.01	0	1.14	0	0.00	0	42.78	0	0.74	0	4557	0	297106	0	23750	0	522	0	544	0	0	0	58134	0	34	0	0	0	164	0	28263	0	247	0	28708	0	72.08	0	214156	0	9080	27269	3.003193832599	297106.0	237906.0	4557.0	23750.0	522.0	544.0	0.0	58134.0	214156.0	80.1	1.5	8.0	0.2	0.2	0.0	19.6	72.1	75	75	75.00	7	22282950	29.9	21.3	20.0	28.9	0.0	33.4	21.6	smartseq
1447455	SRR3639161	SRP076212	SRS1488564	SRX1826606	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189408: 1g_BTN7_C70_IL4709-710-504_CGAGGCTG-AGAGTAGA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189408		GSM2189408	1g_BTN7_C70_IL4709-710-504_CGAGGCTG-AGAGTAGA BTN07 Mic-scRNA-Seq	596585588	2953394	2016-07-18 10:56:32	410685620	596585588	2953394	2	2953394	index:0,count:2953394,average:101,stdev:0|index:1,count:2953394,average:101,stdev:0	GSM2189408_r1						1.19	3.04	1.26	479776648	447337596	463204570	433688190	93.24	93.63	2674490	2558953	243.949	624.019	174	13767	62.1	64.36	2858232	1660776	2858232	1660776	62.66	62.56	2858232	1675719	2858232	1614277	142058302	29.61	0.88	0	3.19	0	0.48	0	0.08	0	0.00	0	8.89	0	2674490	0	202	0	198.85	0	1.50	0	0.01	0	1.24	0	0.01	0	193.31	0	0.70	0	26011	0	2953394	0	94115	0	14127	0	2228	0	0	0	262549	0	17	0	0	0	2011	0	334714	0	3968	0	340710	0	87.37	0	2580375	0	6240	340288	54.533333333333	2953394.0	2674490.0	26011.0	94115.0	14127.0	2228.0	0.0	262549.0	2580375.0	90.6	0.9	3.2	0.5	0.1	0.0	8.9	87.4	101	101	101.00	38	298292794	27.2	22.5	22.6	27.7	0.0	35.2	19.1	smartseq
1447470	SRR3638162	SRP076212	SRS1488240	SRX1826282	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189084: 1-0-1-0-BTN35-C66-1782070112-8ul-1-IL5413-N709-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189084		GSM2189084	1-0-1-0-BTN35-C66-1782070112-8ul-1-IL5413-N709-N506 BTN35 Mic-scRNA-Seq	45222600	301484	2016-07-18 10:56:32	21055554	45222600	301484	2	301484	index:0,count:301484,average:75,stdev:0|index:1,count:301484,average:75,stdev:0	GSM2189084_r4						7.77	3.46	0.12	30328296	30360588	27360332	27687905	100.11	101.2	245218	231297	165.120	683.757	88	1495	74.99	83.17	279090	183900	279090	183900	79.52	79.24	279090	195005	279090	175201	4436133	14.63	1.52	0	8.00	0	0.19	0	0.20	0	0.00	0	18.28	0	245218	0	150	0	145.79	0	1.39	0	0.01	0	1.17	0	0.00	0	49.33	0	0.66	0	4592	0	301484	0	24107	0	563	0	600	0	0	0	55103	0	18	0	0	0	190	0	29425	0	223	0	29856	0	73.34	0	221111	0	9283	28345	3.053431002909	301484.0	245218.0	4592.0	24107.0	563.0	600.0	0.0	55103.0	221111.0	81.3	1.5	8.0	0.2	0.2	0.0	18.3	73.3	75	75	75.00	7	22611300	29.9	21.2	19.8	29.1	0.0	33.7	22.0	smartseq
1447471	SRR3639162	SRP076212	SRS1488565	SRX1826607	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189409: 1g_BTN7_C73_IL4709-706-505_TAGGCATG-GTAAGGAG BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189409		GSM2189409	1g_BTN7_C73_IL4709-706-505_TAGGCATG-GTAAGGAG BTN07 Mic-scRNA-Seq	610949202	3024501	2016-07-18 10:56:32	419301715	610949202	3024501	2	3024501	index:0,count:3024501,average:101,stdev:0|index:1,count:3024501,average:101,stdev:0	GSM2189409_r1						2.19	3.54	1.93	487312417	433060600	459527806	411568639	88.87	89.56	2712918	2584892	244.357	704.673	180	13968	62.33	66.16	3035629	1690946	3035629	1690946	63.63	63.78	3035629	1726215	3035629	1630040	112777060	23.14	1.02	0	5.20	0	0.69	0	0.10	0	0.00	0	9.51	0	2712918	0	202	0	198.64	0	1.55	0	0.01	0	1.30	0	0.01	0	151.23	0	0.71	0	30821	0	3024501	0	157241	0	20760	0	3165	0	0	0	287658	0	181	0	0	0	1980	0	373534	0	5534	0	381229	0	84.50	0	2555677	0	6885	384366	55.826579520697	3024501.0	2712918.0	30821.0	157241.0	20760.0	3165.0	0.0	287658.0	2555677.0	89.7	1.0	5.2	0.7	0.1	0.0	9.5	84.5	101	101	101.00	38	305474601	27.1	22.4	22.6	27.9	0.0	35.1	18.3	smartseq
1447487	SRR3638163	SRP076212	SRS1488241	SRX1826283	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189085: 1-0-1-0-BTN35-C68-1782070112-12ul-1-IL5413-N701-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189085		GSM2189085	1-0-1-0-BTN35-C68-1782070112-12ul-1-IL5413-N701-N507 BTN35 Mic-scRNA-Seq	47399850	315999	2016-07-18 10:56:32	23099424	47399850	315999	2	315999	index:0,count:315999,average:75,stdev:0|index:1,count:315999,average:75,stdev:0	GSM2189085_r1						1.88	3.56	0.05	40721678	40200150	38573217	38329461	98.72	99.37	285883	253221	244.205	1329.091	199	1233	74.89	79.16	311442	214105	311442	214105	76.64	76.52	311442	219107	311442	206982	7591552	18.64	0.99	0	4.87	0	0.28	0	0.07	0	0.00	0	9.18	0	285883	0	150	0	147.86	0	1.51	0	0.01	0	1.19	0	0.00	0	63.20	0	0.87	0	3129	0	315999	0	15395	0	869	0	223	0	0	0	29024	0	29	0	0	0	334	0	44715	0	300	0	45378	0	85.60	0	270488	0	13959	45409	3.253026721112	315999.0	285883.0	3129.0	15395.0	869.0	223.0	0.0	29024.0	270488.0	90.5	1.0	4.9	0.3	0.1	0.0	9.2	85.6	75	75	75.00	7	23699925	28.1	22.1	22.3	27.4	0.0	33.3	21.4	smartseq
1447500	SRR3638164	SRP076212	SRS1488241	SRX1826283	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189085: 1-0-1-0-BTN35-C68-1782070112-12ul-1-IL5413-N701-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189085		GSM2189085	1-0-1-0-BTN35-C68-1782070112-12ul-1-IL5413-N701-N507 BTN35 Mic-scRNA-Seq	48271950	321813	2016-07-18 10:56:32	23488842	48271950	321813	2	321813	index:0,count:321813,average:75,stdev:0|index:1,count:321813,average:75,stdev:0	GSM2189085_r2						1.87	3.54	0.04	41614292	41036275	39390213	39092876	98.61	99.25	291645	257045	248.353	1374.429	196	1212	74.94	79.26	318211	218558	318211	218558	76.8	76.68	318211	223986	318211	211467	7689021	18.48	1.02	0	4.94	0	0.27	0	0.06	0	0.00	0	9.04	0	291645	0	150	0	147.87	0	1.49	0	0.01	0	1.16	0	0.00	0	68.15	0	0.87	0	3274	0	321813	0	15884	0	865	0	201	0	0	0	29102	0	27	0	0	0	349	0	46554	0	295	0	47225	0	85.69	0	275761	0	14259	47336	3.319727891156	321813.0	291645.0	3274.0	15884.0	865.0	201.0	0.0	29102.0	275761.0	90.6	1.0	4.9	0.3	0.1	0.0	9.0	85.7	75	75	75.00	7	24135975	28.0	22.1	22.4	27.5	0.0	33.3	21.6	smartseq
1447501	SRR3639164	SRP076212	SRS1488567	SRX1826609	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189411: 1gch_BTN5_C44_IL4690-706-501_TAGGCATG-TAGATCGC BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189411		GSM2189411	1gch_BTN5_C44_IL4690-706-501_TAGGCATG-TAGATCGC BTN05 Mic-scRNA-Seq	542840862	2687331	2016-07-18 10:56:32	375872889	542840862	2687331	2	2687331	index:0,count:2687331,average:101,stdev:0|index:1,count:2687331,average:101,stdev:0	GSM2189411_r1						1.41	4.37	0.83	431929569	408429081	416545347	395601024	94.56	94.97	2388409	2249502	253.306	701.863	188	12102	72.4	75.15	2545736	1729269	2545736	1729269	72.15	72.59	2545736	1723215	2545736	1670290	82116213	19.01	1.08	0	3.25	0	0.30	0	0.10	0	0.00	0	10.72	0	2388409	0	202	0	198.57	0	1.95	0	0.01	0	1.22	0	0.01	0	186.05	0	0.84	0	28993	0	2687331	0	87468	0	8033	0	2806	0	0	0	288083	0	50	0	0	0	2410	0	382176	0	4613	0	389249	0	85.62	0	2300941	0	5924	383724	64.774476704929	2687331.0	2388409.0	28993.0	87468.0	8033.0	2806.0	0.0	288083.0	2300941.0	88.9	1.1	3.3	0.3	0.1	0.0	10.7	85.6	101	101	101.00	38	271420431	26.6	23.0	23.2	27.2	0.0	34.5	17.7	smartseq
1447502	SRR3640164	SRP076212	SRS1489010	SRX1827052	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189854: C8_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189854		GSM2189854	C8_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	43066650	287111	2016-07-18 10:56:32	16390043	43066650	287111	2	287111	index:0,count:287111,average:75,stdev:0|index:1,count:287111,average:75,stdev:0	GSM2189854_r3						1.13	1.93	0.05	36901898	44336679	34431301	42035028	120.15	122.08	267477	241719	239.069	1139.439	174	1245	81.8	88.04	292537	218805	292537	218805	62.6	63.46	292537	167438	292537	157718	3361647	9.11	1.79	0	6.60	0	0.26	0	0.10	0	0.00	0	6.48	0	267477	0	150	0	148.00	0	4.82	0	0.08	0	1.04	0	0.02	0	68.91	0	0.36	0	5135	0	287111	0	18956	0	745	0	287	0	0	0	18602	0	17	0	0	0	322	0	43264	0	392	0	43995	0	86.56	0	248521	0	15974	42411	2.655001878052	287111.0	267477.0	5135.0	18956.0	745.0	287.0	0.0	18602.0	248521.0	93.2	1.8	6.6	0.3	0.1	0.0	6.5	86.6	75	75	75.00	6	21533325	24.1	25.7	25.7	24.5	0.0	34.6	27.5	smartseq
1447503	SRR3641164	SRP076212	SRS1489264	SRX1827306	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190108: G8_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190108		GSM2190108	G8_1000700602-OGC11-sal_1_14ul_1 OGC11-sal FACS-scRNA-Seq	59606400	397376	2016-07-18 10:56:32	22873261	59606400	397376	2	397376	index:0,count:397376,average:75,stdev:0|index:1,count:397376,average:75,stdev:0	GSM2190108_r4						1.4	2.42	0.01	47862288	53743940	44746778	50872868	112.29	113.69	361742	326478	200.626	1202.753	110	2058	82.2	88.27	397708	297364	397708	297364	70.35	71.23	397708	254485	397708	239971	4437079	9.27	1.79	0	6.26	0	0.32	0	0.12	0	0.00	0	8.52	0	361742	0	150	0	147.53	0	4.44	0	0.06	0	1.17	0	0.02	0	89.41	0	0.32	0	7109	0	397376	0	24869	0	1276	0	488	0	0	0	33870	0	78	0	0	0	512	0	78182	0	520	0	79292	0	84.77	0	336873	0	19404	74806	3.855184498042	397376.0	361742.0	7109.0	24869.0	1276.0	488.0	0.0	33870.0	336873.0	91.0	1.8	6.3	0.3	0.1	0.0	8.5	84.8	75	75	75.00	6	29803200	24.4	25.6	25.4	24.6	0.0	34.6	27.6	smartseq
1447516	SRR3638165	SRP076212	SRS1488241	SRX1826283	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189085: 1-0-1-0-BTN35-C68-1782070112-12ul-1-IL5413-N701-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189085		GSM2189085	1-0-1-0-BTN35-C68-1782070112-12ul-1-IL5413-N701-N507 BTN35 Mic-scRNA-Seq	48021600	320144	2016-07-18 10:56:32	23449729	48021600	320144	2	320144	index:0,count:320144,average:75,stdev:0|index:1,count:320144,average:75,stdev:0	GSM2189085_r3						1.85	3.51	0.04	41255420	40727798	39086979	38824174	98.72	99.33	289393	255251	246.350	1351.425	197	1248	75.05	79.29	315216	217197	315216	217197	76.87	76.75	315216	222457	315216	210228	7646799	18.54	0.96	0	4.83	0	0.26	0	0.06	0	0.00	0	9.28	0	289393	0	150	0	147.86	0	1.50	0	0.01	0	1.16	0	0.00	0	72.03	0	0.89	0	3088	0	320144	0	15464	0	842	0	192	0	0	0	29717	0	24	0	0	0	332	0	46198	0	327	0	46881	0	85.56	0	273929	0	14087	46881	3.327961950735	320144.0	289393.0	3088.0	15464.0	842.0	192.0	0.0	29717.0	273929.0	90.4	1.0	4.8	0.3	0.1	0.0	9.3	85.6	75	75	75.00	7	24010800	28.1	22.1	22.4	27.4	0.0	33.2	21.5	smartseq
1447517	SRR3639165	SRP076212	SRS1488568	SRX1826610	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189412: 1gg_BTN3_C01_IL3971-701-501_TAAGGCGA-TAGATCGC BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189412		GSM2189412	1gg_BTN3_C01_IL3971-701-501_TAAGGCGA-TAGATCGC BTN03 Mic-scRNA-Seq	487060582	2411191	2016-07-18 10:56:32	352428105	487060582	2411191	2	2411191	index:0,count:2411191,average:101,stdev:0|index:1,count:2411191,average:101,stdev:0	GSM2189412_r1						5.57	0.53	0.02	361204302	364070982	348131997	351866556	100.79	101.07	2174321	2145865	204.738	377.784	148	14571	79.88	82.94	2270573	1736832	2270573	1736832	81.04	80.73	2270573	1762054	2270573	1690455	58840062	16.29	1.23	0	3.33	0	0.13	0	0.03	0	0.00	0	9.66	0	2174321	0	202	0	197.50	0	1.77	0	0.01	0	1.17	0	0.01	0	211.71	0	0.65	0	29680	0	2411191	0	80312	0	3021	0	815	0	0	0	233034	0	6	0	0	0	104	0	87694	0	1995	0	89799	0	86.85	0	2094009	0	1609	81357	50.563704164077	2411191.0	2174321.0	29680.0	80312.0	3021.0	815.0	0.0	233034.0	2094009.0	90.2	1.2	3.3	0.1	0.0	0.0	9.7	86.8	101	101	101.00	38	243530291	26.8	22.9	22.8	27.5	0.0	34.5	17.6	smartseq
1447518	SRR3640165	SRP076212	SRS1489010	SRX1827052	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189854: C8_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189854		GSM2189854	C8_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	43181550	287877	2016-07-18 10:56:32	16475886	43181550	287877	2	287877	index:0,count:287877,average:75,stdev:0|index:1,count:287877,average:75,stdev:0	GSM2189854_r4						1.15	1.92	0.05	36956450	44372030	34457327	42056577	120.07	122.05	267865	241927	239.617	1155.130	174	1303	81.93	88.23	293199	219461	293199	219461	62.79	63.69	293199	168189	293199	158425	3331380	9.01	1.78	0	6.64	0	0.26	0	0.09	0	0.00	0	6.60	0	267865	0	150	0	147.98	0	4.85	0	0.08	0	1.04	0	0.02	0	94.21	0	0.36	0	5121	0	287877	0	19119	0	749	0	249	0	0	0	19014	0	36	0	0	0	289	0	43045	0	438	0	43808	0	86.41	0	248746	0	16039	42124	2.626348276077	287877.0	267865.0	5121.0	19119.0	749.0	249.0	0.0	19014.0	248746.0	93.0	1.8	6.6	0.3	0.1	0.0	6.6	86.4	75	75	75.00	6	21590775	24.1	25.7	25.7	24.5	0.0	34.6	27.7	smartseq
1447519	SRR3641165	SRP076212	SRS1489265	SRX1827307	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190109: G8_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190109		GSM2190109	G8_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	40949250	272995	2016-07-18 10:56:32	15268835	40949250	272995	2	272995	index:0,count:272995,average:75,stdev:0|index:1,count:272995,average:75,stdev:0	GSM2190109_r1						1.38	2.27	0.03	35252955	39330028	33062453	37333782	111.57	112.92	255324	224281	241.052	1504.056	146	1127	81.62	87.31	278328	208397	278328	208397	70.76	71.69	278328	180665	278328	171118	3571068	10.13	1.77	0	6.09	0	0.25	0	0.09	0	0.00	0	6.13	0	255324	0	150	0	147.97	0	4.47	0	0.06	0	1.07	0	0.02	0	81.90	0	0.28	0	4823	0	272995	0	16631	0	694	0	234	0	0	0	16743	0	24	0	0	0	352	0	51222	0	379	0	51977	0	87.43	0	238693	0	18479	50108	2.711618594080	272995.0	255324.0	4823.0	16631.0	694.0	234.0	0.0	16743.0	238693.0	93.5	1.8	6.1	0.3	0.1	0.0	6.1	87.4	75	75	75.00	6	20474625	24.5	25.4	25.4	24.7	0.0	34.8	28.3	smartseq
1447532	SRR3638166	SRP076212	SRS1488241	SRX1826283	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189085: 1-0-1-0-BTN35-C68-1782070112-12ul-1-IL5413-N701-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189085		GSM2189085	1-0-1-0-BTN35-C68-1782070112-12ul-1-IL5413-N701-N507 BTN35 Mic-scRNA-Seq	49763700	331758	2016-07-18 10:56:32	23985258	49763700	331758	2	331758	index:0,count:331758,average:75,stdev:0|index:1,count:331758,average:75,stdev:0	GSM2189085_r4						1.88	3.55	0.04	42673920	42076034	40432697	40116005	98.6	99.22	299173	263831	248.600	1378.515	198	1247	74.89	79.13	325928	224059	325928	224059	76.73	76.6	325928	229552	325928	216896	7950034	18.63	1.01	0	4.83	0	0.27	0	0.06	0	0.00	0	9.49	0	299173	0	150	0	147.91	0	1.50	0	0.01	0	1.13	0	0.00	0	74.65	0	0.82	0	3344	0	331758	0	16008	0	900	0	213	0	0	0	31472	0	24	0	0	0	351	0	47627	0	328	0	48330	0	85.35	0	283165	0	14295	48440	3.388597411682	331758.0	299173.0	3344.0	16008.0	900.0	213.0	0.0	31472.0	283165.0	90.2	1.0	4.8	0.3	0.1	0.0	9.5	85.4	75	75	75.00	7	24881850	28.1	22.1	22.3	27.5	0.0	33.5	21.8	smartseq
1447533	SRR3639166	SRP076212	SRS1488569	SRX1826611	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189413: 1gg_BTN3_C10_IL3971-709-501_GCTACGCT-TAGATCGC BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189413		GSM2189413	1gg_BTN3_C10_IL3971-709-501_GCTACGCT-TAGATCGC BTN03 Mic-scRNA-Seq	454671296	2250848	2016-07-18 10:56:32	325707134	454671296	2250848	2	2250848	index:0,count:2250848,average:101,stdev:0|index:1,count:2250848,average:101,stdev:0	GSM2189413_r1						3.2	0.9	0.03	333761796	337374729	323218298	327701070	101.08	101.39	2015126	1973414	202.652	455.450	148	13535	86.9	89.8	2106266	1751079	2106266	1751079	86.84	86.99	2106266	1749932	2106266	1696345	32357321	9.69	1.13	0	2.90	0	0.08	0	0.03	0	0.00	0	10.36	0	2015126	0	202	0	197.57	0	1.49	0	0.01	0	1.26	0	0.01	0	192.93	0	0.58	0	25484	0	2250848	0	65179	0	1812	0	613	0	0	0	233297	0	1	0	0	0	996	0	135650	0	2028	0	138675	0	86.63	0	1949947	0	2152	130785	60.773698884758	2250848.0	2015126.0	25484.0	65179.0	1812.0	613.0	0.0	233297.0	1949947.0	89.5	1.1	2.9	0.1	0.0	0.0	10.4	86.6	101	101	101.00	38	227335648	26.9	22.8	22.5	27.8	0.0	34.7	17.5	smartseq
1447534	SRR3640166	SRP076212	SRS1489011	SRX1827053	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189855: C8_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189855		GSM2189855	C8_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	44928600	299524	2016-07-18 10:56:32	16842758	44928600	299524	2	299524	index:0,count:299524,average:75,stdev:0|index:1,count:299524,average:75,stdev:0	GSM2189855_r1						1.31	2.23	0.04	38579562	43114158	36303626	40999659	111.75	112.94	278979	248144	241.928	1430.853	146	1278	77.15	82.23	302651	215228	302651	215228	65.63	66.37	302651	183081	302651	173719	5702684	14.78	1.76	0	5.76	0	0.23	0	0.19	0	0.00	0	6.44	0	278979	0	150	0	147.97	0	4.51	0	0.06	0	1.07	0	0.02	0	98.03	0	0.29	0	5271	0	299524	0	17249	0	690	0	574	0	0	0	19281	0	41	0	0	0	352	0	49430	0	466	0	50289	0	87.38	0	261730	0	18239	48425	2.655024946543	299524.0	278979.0	5271.0	17249.0	690.0	574.0	0.0	19281.0	261730.0	93.1	1.8	5.8	0.2	0.2	0.0	6.4	87.4	75	75	75.00	6	22464300	24.7	25.1	25.1	25.1	0.0	34.8	28.2	smartseq
1447535	SRR3641166	SRP076212	SRS1489265	SRX1827307	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190109: G8_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190109		GSM2190109	G8_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	40694400	271296	2016-07-18 10:56:32	15253860	40694400	271296	2	271296	index:0,count:271296,average:75,stdev:0|index:1,count:271296,average:75,stdev:0	GSM2190109_r2						1.38	2.34	0.03	34942251	39011284	32770788	37005749	111.65	112.92	252885	221944	242.036	1513.252	146	1174	81.53	87.2	275088	206184	275088	206184	70.68	71.58	275088	178746	275088	169264	3568434	10.21	1.69	0	6.06	0	0.25	0	0.10	0	0.00	0	6.44	0	252885	0	150	0	147.96	0	4.47	0	0.06	0	1.09	0	0.02	0	69.76	0	0.31	0	4573	0	271296	0	16427	0	671	0	268	0	0	0	17472	0	46	0	0	0	393	0	50563	0	395	0	51397	0	87.16	0	236458	0	18388	49547	2.694529040679	271296.0	252885.0	4573.0	16427.0	671.0	268.0	0.0	17472.0	236458.0	93.2	1.7	6.1	0.2	0.1	0.0	6.4	87.2	75	75	75.00	6	20347200	24.4	25.4	25.4	24.8	0.0	34.8	28.2	smartseq
1447549	SRR3638167	SRP076212	SRS1488242	SRX1826284	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189086: 1-0-1-0-BTN35-C71-1782070112-2ul-1-IL5413-N704-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189086		GSM2189086	1-0-1-0-BTN35-C71-1782070112-2ul-1-IL5413-N704-N507 BTN35 Mic-scRNA-Seq	36092250	240615	2016-07-18 10:56:32	18041882	36092250	240615	2	240615	index:0,count:240615,average:75,stdev:0|index:1,count:240615,average:75,stdev:0	GSM2189086_r1						12.0	3.55	0.56	28975750	27814956	25402108	24658832	95.99	97.07	213418	202202	197.072	747.062	164	1183	73.52	83.81	249275	156900	249275	156900	79.9	79.22	249275	170514	249275	148316	2673732	9.23	1.40	0	10.89	0	0.43	0	0.12	0	0.00	0	10.75	0	213418	0	150	0	147.00	0	2.05	0	0.01	0	1.11	0	0.01	0	54.14	0	0.92	0	3368	0	240615	0	26201	0	1031	0	293	0	0	0	25873	0	5	0	0	0	116	0	20447	0	156	0	20724	0	77.81	0	187217	0	5143	20521	3.990083608789	240615.0	213418.0	3368.0	26201.0	1031.0	293.0	0.0	25873.0	187217.0	88.7	1.4	10.9	0.4	0.1	0.0	10.8	77.8	75	75	75.00	7	18046125	29.8	20.8	20.9	28.5	0.0	32.7	20.8	smartseq
1447550	SRR3639167	SRP076212	SRS1488570	SRX1826612	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189414: 1gg_BTN3_C20_IL3971-704-502_TCCTGAGC-CTCTCTAT BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189414		GSM2189414	1gg_BTN3_C20_IL3971-704-502_TCCTGAGC-CTCTCTAT BTN03 Mic-scRNA-Seq	566175094	2802847	2016-07-18 10:56:32	406237533	566175094	2802847	2	2802847	index:0,count:2802847,average:101,stdev:0|index:1,count:2802847,average:101,stdev:0	GSM2189414_r1						1.88	1.77	0.0	409614690	411531018	393721696	396970493	100.47	100.83	2459767	2320057	209.613	616.612	148	15503	93.17	97.02	2642993	2291818	2642993	2291818	94.37	94.82	2642993	2321380	2642993	2239953	10689977	2.61	0.94	0	3.48	0	0.30	0	0.02	0	0.00	0	11.92	0	2459767	0	202	0	196.59	0	1.63	0	0.01	0	1.20	0	0.01	0	168.17	0	1.02	0	26273	0	2802847	0	97527	0	8409	0	511	0	0	0	334160	0	105	0	0	0	2300	0	455224	0	3702	0	461331	0	84.28	0	2362240	0	6121	441576	72.141153406306	2802847.0	2459767.0	26273.0	97527.0	8409.0	511.0	0.0	334160.0	2362240.0	87.8	0.9	3.5	0.3	0.0	0.0	11.9	84.3	101	101	101.00	38	283087547	26.3	23.4	23.2	27.0	0.0	34.6	17.6	smartseq
1447551	SRR3640167	SRP076212	SRS1489011	SRX1827053	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189855: C8_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189855		GSM2189855	C8_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	44513850	296759	2016-07-18 10:56:32	16762952	44513850	296759	2	296759	index:0,count:296759,average:75,stdev:0|index:1,count:296759,average:75,stdev:0	GSM2189855_r2						1.34	2.15	0.04	38088411	42486384	35802341	40379168	111.55	112.78	275360	245376	241.937	1415.838	174	1261	77.0	82.17	299096	212036	299096	212036	65.7	66.46	299096	180917	299096	171476	5638496	14.80	1.75	0	5.84	0	0.24	0	0.21	0	0.00	0	6.76	0	275360	0	150	0	147.97	0	4.50	0	0.06	0	1.06	0	0.02	0	89.03	0	0.31	0	5180	0	296759	0	17327	0	707	0	621	0	0	0	20071	0	42	0	0	0	372	0	48190	0	446	0	49050	0	86.95	0	258033	0	18180	47295	2.601485148515	296759.0	275360.0	5180.0	17327.0	707.0	621.0	0.0	20071.0	258033.0	92.8	1.7	5.8	0.2	0.2	0.0	6.8	87.0	75	75	75.00	6	22256925	24.7	25.1	25.1	25.1	0.0	34.7	28.0	smartseq
1447566	SRR3638168	SRP076212	SRS1488242	SRX1826284	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189086: 1-0-1-0-BTN35-C71-1782070112-2ul-1-IL5413-N704-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189086		GSM2189086	1-0-1-0-BTN35-C71-1782070112-2ul-1-IL5413-N704-N507 BTN35 Mic-scRNA-Seq	30862350	205749	2016-07-18 10:56:32	15563018	30862350	205749	2	205749	index:0,count:205749,average:75,stdev:0|index:1,count:205749,average:75,stdev:0	GSM2189086_r2						12.17	3.64	0.61	24845846	23746475	21728347	21009704	95.58	96.69	182466	172864	199.467	730.834	137	997	73.2	83.62	213462	133559	213462	133559	79.83	79.17	213462	145659	213462	126451	2291295	9.22	1.37	0	11.06	0	0.42	0	0.13	0	0.00	0	10.76	0	182466	0	150	0	147.01	0	2.03	0	0.01	0	1.11	0	0.01	0	43.57	0	1.00	0	2821	0	205749	0	22754	0	870	0	272	0	0	0	22141	0	0	0	0	0	88	0	17061	0	114	0	17263	0	77.62	0	159712	0	4794	17175	3.582603254068	205749.0	182466.0	2821.0	22754.0	870.0	272.0	0.0	22141.0	159712.0	88.7	1.4	11.1	0.4	0.1	0.0	10.8	77.6	75	75	75.00	7	15431175	29.9	20.6	20.9	28.5	0.0	32.5	20.5	smartseq
1447567	SRR3639168	SRP076212	SRS1488571	SRX1826613	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189415: 1gg_BTN3_C26_IL3971-711-502_AAGAGGCA-CTCTCTAT BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189415		GSM2189415	1gg_BTN3_C26_IL3971-711-502_AAGAGGCA-CTCTCTAT BTN03 Mic-scRNA-Seq	398527416	1972908	2016-07-18 10:56:32	284829514	398527416	1972908	2	1972908	index:0,count:1972908,average:101,stdev:0|index:1,count:1972908,average:101,stdev:0	GSM2189415_r1						3.14	0.89	0.01	284444842	286692013	277141014	279989963	100.79	101.03	1704543	1653083	208.861	524.453	148	10794	87.73	90.11	1767040	1495433	1767040	1495433	87.25	87.27	1767040	1487213	1767040	1448275	25519092	8.97	0.91	0	2.28	0	0.09	0	0.01	0	0.00	0	13.50	0	1704543	0	202	0	196.72	0	1.50	0	0.01	0	1.22	0	0.01	0	142.05	0	1.12	0	17880	0	1972908	0	45071	0	1805	0	275	0	0	0	266285	0	132	0	0	0	1115	0	163643	0	2006	0	166896	0	84.11	0	1659472	0	3504	155211	44.295376712329	1972908.0	1704543.0	17880.0	45071.0	1805.0	275.0	0.0	266285.0	1659472.0	86.4	0.9	2.3	0.1	0.0	0.0	13.5	84.1	101	101	101.00	38	199263708	26.8	22.8	22.7	27.6	0.0	34.6	17.4	smartseq
1447581	SRR3638169	SRP076212	SRS1488242	SRX1826284	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189086: 1-0-1-0-BTN35-C71-1782070112-2ul-1-IL5413-N704-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189086		GSM2189086	1-0-1-0-BTN35-C71-1782070112-2ul-1-IL5413-N704-N507 BTN35 Mic-scRNA-Seq	33889200	225928	2016-07-18 10:56:32	17117211	33889200	225928	2	225928	index:0,count:225928,average:75,stdev:0|index:1,count:225928,average:75,stdev:0	GSM2189086_r3						11.93	3.55	0.54	27280742	26127551	23909164	23165890	95.77	96.89	200764	190075	197.169	711.407	162	1071	73.49	83.77	234354	147547	234354	147547	79.82	79.15	234354	160243	234354	139411	2489064	9.12	1.38	0	10.90	0	0.40	0	0.12	0	0.00	0	10.61	0	200764	0	150	0	147.00	0	2.05	0	0.01	0	1.13	0	0.01	0	40.67	0	0.97	0	3119	0	225928	0	24629	0	911	0	273	0	0	0	23980	0	3	0	0	0	95	0	18904	0	153	0	19155	0	77.96	0	176135	0	4989	19074	3.823211064342	225928.0	200764.0	3119.0	24629.0	911.0	273.0	0.0	23980.0	176135.0	88.9	1.4	10.9	0.4	0.1	0.0	10.6	78.0	75	75	75.00	7	16944600	29.9	20.8	21.0	28.4	0.0	32.6	20.6	smartseq
1447582	SRR3639169	SRP076212	SRS1488574	SRX1826614	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189416: 1gg_BTN3_C47_IL3971-702-504_CGTACTAG-AGAGTAGA BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Ependy-Sec|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189416		GSM2189416	1gg_BTN3_C47_IL3971-702-504_CGTACTAG-AGAGTAGA BTN03 Mic-scRNA-Seq	391410148	1937674	2016-07-18 10:56:32	287492982	391410148	1937674	2	1937674	index:0,count:1937674,average:101,stdev:0|index:1,count:1937674,average:101,stdev:0	GSM2189416_r1						3.28	2.72	0.0	298066195	298684591	275828633	277880561	100.21	100.74	1761438	1541779	222.527	1029.857	148	9352	87.06	94.24	1964335	1533574	1964335	1533574	90.77	91.25	1964335	1598822	1964335	1484984	16114871	5.41	1.15	0	6.92	0	0.28	0	0.04	0	0.00	0	8.77	0	1761438	0	202	0	197.30	0	2.00	0	0.01	0	1.38	0	0.00	0	199.30	0	0.71	0	22277	0	1937674	0	134057	0	5457	0	870	0	0	0	169909	0	360	0	0	0	3203	0	673496	0	4047	0	681106	0	83.99	0	1627381	0	13930	641089	46.022182340273	1937674.0	1761438.0	22277.0	134057.0	5457.0	870.0	0.0	169909.0	1627381.0	90.9	1.1	6.9	0.3	0.0	0.0	8.8	84.0	101	101	101.00	38	195705074	25.6	24.1	24.2	26.1	0.0	34.7	18.0	smartseq
1447583	SRR3640169	SRP076212	SRS1489011	SRX1827053	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189855: C8_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189855		GSM2189855	C8_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	44602500	297350	2016-07-18 10:56:32	16964063	44602500	297350	2	297350	index:0,count:297350,average:75,stdev:0|index:1,count:297350,average:75,stdev:0	GSM2189855_r4						1.36	2.19	0.05	38330667	42785994	36057019	40686865	111.62	112.84	276919	246268	243.550	1417.607	146	1233	77.06	82.17	300860	213388	300860	213388	65.63	66.33	300860	181735	300860	172257	5648900	14.74	1.75	0	5.79	0	0.21	0	0.20	0	0.00	0	6.46	0	276919	0	150	0	147.98	0	4.50	0	0.06	0	1.06	0	0.02	0	97.31	0	0.32	0	5198	0	297350	0	17224	0	620	0	595	0	0	0	19216	0	42	0	0	0	382	0	48324	0	423	0	49171	0	87.34	0	259695	0	18230	47590	2.610532089962	297350.0	276919.0	5198.0	17224.0	620.0	595.0	0.0	19216.0	259695.0	93.1	1.7	5.8	0.2	0.2	0.0	6.5	87.3	75	75	75.00	6	22301250	24.7	25.1	25.1	25.1	0.0	34.7	27.7	smartseq
1447694	SRR3638170	SRP076212	SRS1488242	SRX1826284	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189086: 1-0-1-0-BTN35-C71-1782070112-2ul-1-IL5413-N704-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189086		GSM2189086	1-0-1-0-BTN35-C71-1782070112-2ul-1-IL5413-N704-N507 BTN35 Mic-scRNA-Seq	25666650	171111	2016-07-18 10:56:32	13107529	25666650	171111	2	171111	index:0,count:171111,average:75,stdev:0|index:1,count:171111,average:75,stdev:0	GSM2189086_r4						12.55	3.7	0.63	20551884	19605728	17926974	17300711	95.4	96.51	151098	143696	197.628	705.184	169	839	72.81	83.36	177198	110011	177198	110011	79.77	79.05	177198	120532	177198	104314	1925062	9.37	1.37	0	11.18	0	0.41	0	0.12	0	0.00	0	11.17	0	151098	0	150	0	147.02	0	2.01	0	0.01	0	1.14	0	0.01	0	36.24	0	0.97	0	2342	0	171111	0	19131	0	704	0	201	0	0	0	19108	0	1	0	0	0	72	0	13619	0	99	0	13791	0	77.12	0	131967	0	4377	13653	3.119259766964	171111.0	151098.0	2342.0	19131.0	704.0	201.0	0.0	19108.0	131967.0	88.3	1.4	11.2	0.4	0.1	0.0	11.2	77.1	75	75	75.00	7	12833325	30.3	20.4	20.7	28.6	0.0	32.6	20.5	smartseq
1447695	SRR3639170	SRP076212	SRS1488572	SRX1826615	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189417: 1gg_BTN3_C69_IL3971-706-502_TAGGCATG-CTCTCTAT BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189417		GSM2189417	1gg_BTN3_C69_IL3971-706-502_TAGGCATG-CTCTCTAT BTN03 Mic-scRNA-Seq	432509472	2141136	2016-07-18 10:56:32	311101324	432509472	2141136	2	2141136	index:0,count:2141136,average:101,stdev:0|index:1,count:2141136,average:101,stdev:0	GSM2189417_r1						1.22	1.62	0.0	312989908	313087725	306204939	306828998	100.03	100.2	1891104	1817433	204.094	513.812	137	12676	90.28	92.33	1957649	1707260	1957649	1707260	90.38	90.61	1957649	1709258	1957649	1675331	22275737	7.12	0.97	0	1.97	0	0.11	0	0.02	0	0.00	0	11.55	0	1891104	0	202	0	196.77	0	1.58	0	0.01	0	1.25	0	0.01	0	233.58	0	0.96	0	20869	0	2141136	0	42098	0	2400	0	360	0	0	0	247272	0	282	0	0	0	1496	0	235684	0	2455	0	239917	0	86.36	0	1849006	0	4214	223465	53.029188419554	2141136.0	1891104.0	20869.0	42098.0	2400.0	360.0	0.0	247272.0	1849006.0	88.3	1.0	2.0	0.1	0.0	0.0	11.5	86.4	101	101	101.00	38	216254736	26.7	23.0	22.9	27.4	0.0	34.7	17.8	smartseq
1447709	SRR3638171	SRP076212	SRS1488243	SRX1826285	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189087: 1-0-1-0-BTN35-C75-1782070112-18ul-1-IL5413-N708-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189087		GSM2189087	1-0-1-0-BTN35-C75-1782070112-18ul-1-IL5413-N708-N507 BTN35 Mic-scRNA-Seq	65595450	437303	2016-07-18 10:56:32	30982291	65595450	437303	2	437303	index:0,count:437303,average:75,stdev:0|index:1,count:437303,average:75,stdev:0	GSM2189087_r1						2.11	3.74	0.26	47339033	46112851	44737639	43963885	97.41	98.27	366711	345898	182.201	952.974	109	1759	59.19	62.71	399753	217061	399753	217061	60.81	60.32	399753	222984	399753	208789	15604615	32.96	1.23	0	4.70	0	0.21	0	0.17	0	0.00	0	15.76	0	366711	0	150	0	146.79	0	1.37	0	0.01	0	1.16	0	0.00	0	78.71	0	0.72	0	5364	0	437303	0	20565	0	931	0	727	0	0	0	68934	0	30	0	0	0	242	0	34012	0	317	0	34601	0	79.15	0	346146	0	12200	33362	2.734590163934	437303.0	366711.0	5364.0	20565.0	931.0	727.0	0.0	68934.0	346146.0	83.9	1.2	4.7	0.2	0.2	0.0	15.8	79.2	75	75	75.00	7	32797725	30.2	20.5	19.9	29.3	0.0	33.6	21.9	smartseq
1447710	SRR3639171	SRP076212	SRS1488573	SRX1826616	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189418: 1gg_BTN3_C71_IL3971-709-502_GCTACGCT-CTCTCTAT BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Ependy-C|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189418		GSM2189418	1gg_BTN3_C71_IL3971-709-502_GCTACGCT-CTCTCTAT BTN03 Mic-scRNA-Seq	449026406	2222903	2016-07-18 10:56:32	323225717	449026406	2222903	2	2222903	index:0,count:2222903,average:101,stdev:0|index:1,count:2222903,average:101,stdev:0	GSM2189418_r1						2.48	2.25	0.01	328086299	320699728	315858764	309836812	97.75	98.09	1966746	1857817	210.654	693.040	148	12070	78.81	81.97	2086650	1550019	2086650	1550019	79.4	79.42	2086650	1561681	2086650	1501750	49203384	15.00	1.05	0	3.41	0	0.08	0	0.02	0	0.00	0	11.42	0	1966746	0	202	0	197.00	0	1.54	0	0.01	0	1.26	0	0.01	0	186.10	0	0.91	0	23276	0	2222903	0	75800	0	1767	0	481	0	0	0	253909	0	310	0	0	0	2655	0	329778	0	2269	0	335012	0	85.07	0	1890946	0	6545	318304	48.633155080214	2222903.0	1966746.0	23276.0	75800.0	1767.0	481.0	0.0	253909.0	1890946.0	88.5	1.0	3.4	0.1	0.0	0.0	11.4	85.1	101	101	101.00	38	224513203	26.9	22.8	22.7	27.6	0.0	34.9	17.9	smartseq
1447711	SRR3640171	SRP076212	SRS1489013	SRX1827055	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189857: C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189857		GSM2189857	C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	131550	877	2016-07-18 10:56:32	85218	131550	877	2	877	index:0,count:877,average:75,stdev:0|index:1,count:877,average:75,stdev:0	GSM2189857_r1						1.74	3.77	0.29	33948	34899	31255	32792	102.8	104.92	296	284	135.504	367.368	133	5	81.76	90.3	345	242	345	242	80.74	82.09	345	239	345	220	2508	7.39	0.80	0	3.19	0	0.11	0	0.11	0	0.00	0	66.02	0	296	0	150	0	145.87	0	6.00	0	0.03	0	1.29	0	0.02	0	3.16	0	0.25	0	7	0	877	0	28	0	1	0	1	0	0	0	579	0	0	0	0	0	0	0	61	0	0	0	61	0	30.56	0	268	0	56	57	1.017857142857	877.0	296.0	7.0	28.0	1.0	1.0	0.0	579.0	268.0	33.8	0.8	3.2	0.1	0.1	0.0	66.0	30.6	75	75	75.00	6	65775	22.1	28.9	26.8	22.2	0.0	35.2	29.0	smartseq
1447725	SRR3638172	SRP076212	SRS1488243	SRX1826285	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189087: 1-0-1-0-BTN35-C75-1782070112-18ul-1-IL5413-N708-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189087		GSM2189087	1-0-1-0-BTN35-C75-1782070112-18ul-1-IL5413-N708-N507 BTN35 Mic-scRNA-Seq	64688250	431255	2016-07-18 10:56:32	30495675	64688250	431255	2	431255	index:0,count:431255,average:75,stdev:0|index:1,count:431255,average:75,stdev:0	GSM2189087_r2						2.09	3.75	0.28	47313737	46096754	44723152	43968937	97.43	98.31	365114	343432	184.713	999.883	123	1752	59.4	62.91	397783	216874	397783	216874	61.05	60.58	397783	222910	397783	208850	15531688	32.83	1.24	0	4.73	0	0.22	0	0.17	0	0.00	0	14.95	0	365114	0	150	0	146.86	0	1.40	0	0.01	0	1.18	0	0.00	0	91.32	0	0.72	0	5328	0	431255	0	20382	0	932	0	724	0	0	0	64485	0	27	0	0	0	205	0	34930	0	317	0	35479	0	79.94	0	344732	0	12262	34192	2.788452128527	431255.0	365114.0	5328.0	20382.0	932.0	724.0	0.0	64485.0	344732.0	84.7	1.2	4.7	0.2	0.2	0.0	15.0	79.9	75	75	75.00	7	32344125	30.1	20.6	19.9	29.4	0.0	33.7	22.2	smartseq
1447726	SRR3639172	SRP076212	SRS1488575	SRX1826617	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189419: 1gg_BTN3_C87_IL3971-708-503_CAGAGAGG-TATCCTCT BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189419		GSM2189419	1gg_BTN3_C87_IL3971-708-503_CAGAGAGG-TATCCTCT BTN03 Mic-scRNA-Seq	514563488	2547344	2016-07-18 10:56:32	366492914	514563488	2547344	2	2547344	index:0,count:2547344,average:101,stdev:0|index:1,count:2547344,average:101,stdev:0	GSM2189419_r1						3.37	1.5	0.0	362711790	364931665	350557930	354064169	100.61	101.0	2184558	2124577	205.985	463.155	137	14303	82.62	85.52	2281686	1804792	2281686	1804792	83.06	82.98	2281686	1814538	2281686	1751137	50151855	13.83	0.82	0	2.91	0	0.07	0	0.02	0	0.00	0	14.15	0	2184558	0	202	0	196.43	0	1.60	0	0.01	0	1.27	0	0.01	0	179.81	0	1.34	0	20866	0	2547344	0	74122	0	1712	0	613	0	0	0	360461	0	286	0	0	0	1460	0	167461	0	3230	0	172437	0	82.85	0	2110436	0	2912	163752	56.233516483516	2547344.0	2184558.0	20866.0	74122.0	1712.0	613.0	0.0	360461.0	2110436.0	85.8	0.8	2.9	0.1	0.0	0.0	14.2	82.8	101	101	101.00	38	257281744	27.2	22.5	22.3	28.0	0.0	34.8	17.6	smartseq
1447727	SRR3640172	SRP076212	SRS1489013	SRX1827055	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189857: C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189857		GSM2189857	C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	131700	878	2016-07-18 10:56:32	84258	131700	878	2	878	index:0,count:878,average:75,stdev:0|index:1,count:878,average:75,stdev:0	GSM2189857_r3						2.73	5.86	0.0	26470	28525	24980	27205	107.76	108.91	236	226	139.487	303.669	95	5	85.17	90.95	256	201	256	201	77.54	78.28	256	183	256	173	2506	9.47	0.80	0	1.71	0	0.11	0	0.00	0	0.00	0	73.01	0	236	0	150	0	145.21	0	1.00	0	0.01	0	1.00	0	0.02	0	3.16	0	0.20	0	7	0	878	0	15	0	1	0	0	0	0	0	641	0	0	0	0	0	0	0	49	0	0	0	49	0	25.17	0	221	0	41	42	1.024390243902	878.0	236.0	7.0	15.0	1.0	0.0	0.0	641.0	221.0	26.9	0.8	1.7	0.1	0.0	0.0	73.0	25.2	75	75	75.00	5	65850	21.7	29.6	27.1	21.5	0.0	35.2	30.3	smartseq
1447741	SRR3638173	SRP076212	SRS1488243	SRX1826285	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189087: 1-0-1-0-BTN35-C75-1782070112-18ul-1-IL5413-N708-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189087		GSM2189087	1-0-1-0-BTN35-C75-1782070112-18ul-1-IL5413-N708-N507 BTN35 Mic-scRNA-Seq	65857050	439047	2016-07-18 10:56:32	31145954	65857050	439047	2	439047	index:0,count:439047,average:75,stdev:0|index:1,count:439047,average:75,stdev:0	GSM2189087_r3						2.09	3.7	0.3	47737496	46518576	45127444	44360170	97.45	98.3	368973	347353	183.456	984.812	98	1791	59.21	62.71	402339	218463	402339	218463	60.87	60.4	402339	224595	402339	210414	15775961	33.05	1.21	0	4.69	0	0.23	0	0.17	0	0.00	0	15.57	0	368973	0	150	0	146.83	0	1.37	0	0.01	0	1.18	0	0.00	0	68.72	0	0.73	0	5329	0	439047	0	20583	0	991	0	737	0	0	0	68346	0	41	0	0	0	234	0	34536	0	327	0	35138	0	79.35	0	348390	0	12337	33972	2.753667828483	439047.0	368973.0	5329.0	20583.0	991.0	737.0	0.0	68346.0	348390.0	84.0	1.2	4.7	0.2	0.2	0.0	15.6	79.4	75	75	75.00	7	32928525	30.2	20.6	20.0	29.3	0.0	33.6	22.0	smartseq
1447742	SRR3639173	SRP076212	SRS1488576	SRX1826618	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189420: 1gg_BTN3_C93_IL3971-701-504_TAAGGCGA-AGAGTAGA BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189420		GSM2189420	1gg_BTN3_C93_IL3971-701-504_TAAGGCGA-AGAGTAGA BTN03 Mic-scRNA-Seq	408823154	2023877	2016-07-18 10:56:32	300534390	408823154	2023877	2	2023877	index:0,count:2023877,average:101,stdev:0|index:1,count:2023877,average:101,stdev:0	GSM2189420_r1						1.01	2.65	0.04	304970749	306237833	292428047	294805549	100.42	100.81	1836582	1693236	208.321	838.811	139	10993	86.98	90.83	1971309	1597503	1971309	1597503	87.74	88.09	1971309	1611326	1971309	1549419	25329189	8.31	1.17	0	3.84	0	0.22	0	0.04	0	0.00	0	8.99	0	1836582	0	202	0	197.32	0	1.81	0	0.01	0	1.36	0	0.01	0	196.92	0	0.76	0	23722	0	2023877	0	77771	0	4498	0	837	0	0	0	181960	0	247	0	0	0	3144	0	489175	0	4453	0	497019	0	86.90	0	1758811	0	9868	467604	47.385893798135	2023877.0	1836582.0	23722.0	77771.0	4498.0	837.0	0.0	181960.0	1758811.0	90.7	1.2	3.8	0.2	0.0	0.0	9.0	86.9	101	101	101.00	38	204411577	25.8	24.0	23.9	26.2	0.0	34.8	18.3	smartseq
1447743	SRR3640173	SRP076212	SRS1489013	SRX1827055	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189857: C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189857		GSM2189857	C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	116100	774	2016-07-18 10:56:32	79954	116100	774	2	774	index:0,count:774,average:75,stdev:0|index:1,count:774,average:75,stdev:0	GSM2189857_r4						1.14	2.65	0.0	28244	29580	26421	28327	104.73	107.21	243	230	142.374	2274.062	157	6	80.25	85.9	264	195	264	195	72.84	74.01	264	177	264	168	2904	10.28	0.39	0	2.07	0	0.13	0	0.00	0	0.00	0	68.48	0	243	0	150	0	145.00	0	3.00	0	0.06	0	1.00	0	0.02	0	1.39	0	0.15	0	3	0	774	0	16	0	1	0	0	0	0	0	530	0	0	0	0	0	1	0	69	0	0	0	70	0	29.33	0	227	0	56	57	1.017857142857	774.0	243.0	3.0	16.0	1.0	0.0	0.0	530.0	227.0	31.4	0.4	2.1	0.1	0.0	0.0	68.5	29.3	75	75	75.00	6	58050	22.2	28.8	26.8	22.2	0.0	35.2	30.1	smartseq
1447756	SRR3638174	SRP076212	SRS1488243	SRX1826285	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189087: 1-0-1-0-BTN35-C75-1782070112-18ul-1-IL5413-N708-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189087		GSM2189087	1-0-1-0-BTN35-C75-1782070112-18ul-1-IL5413-N708-N507 BTN35 Mic-scRNA-Seq	66745200	444968	2016-07-18 10:56:32	31162505	66745200	444968	2	444968	index:0,count:444968,average:75,stdev:0|index:1,count:444968,average:75,stdev:0	GSM2189087_r4						2.06	3.73	0.26	48469476	47228529	45828454	45044251	97.44	98.29	374782	352723	184.232	952.256	101	1823	59.18	62.66	408181	221805	408181	221805	60.81	60.33	408181	227898	408181	213527	16024833	33.06	1.23	0	4.68	0	0.22	0	0.18	0	0.00	0	15.37	0	374782	0	150	0	146.85	0	1.39	0	0.01	0	1.20	0	0.00	0	72.81	0	0.67	0	5495	0	444968	0	20824	0	962	0	815	0	0	0	68409	0	37	0	0	0	286	0	35585	0	341	0	36249	0	79.55	0	353958	0	12479	35014	2.805833800785	444968.0	374782.0	5495.0	20824.0	962.0	815.0	0.0	68409.0	353958.0	84.2	1.2	4.7	0.2	0.2	0.0	15.4	79.5	75	75	75.00	7	33372600	30.2	20.5	19.9	29.4	0.0	33.9	22.3	smartseq
1447757	SRR3639174	SRP076212	SRS1488577	SRX1826619	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189421: 1gg_BTN5_C04_IL4690-711-502_AAGAGGCA-CTCTCTAT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189421		GSM2189421	1gg_BTN5_C04_IL4690-711-502_AAGAGGCA-CTCTCTAT BTN05 Mic-scRNA-Seq	615077678	3044939	2016-07-18 10:56:32	419237409	615077678	3044939	2	3044939	index:0,count:3044939,average:101,stdev:0|index:1,count:3044939,average:101,stdev:0	GSM2189421_r1						1.21	2.74	0.75	463967227	443292485	449143230	431107075	95.54	95.98	2582272	2474007	247.888	615.807	188	13229	61.35	63.43	2747097	1584179	2747097	1584179	60.94	60.94	2747097	1573643	2747097	1521936	149594461	32.24	0.92	0	2.78	0	0.30	0	0.08	0	0.00	0	14.82	0	2582272	0	202	0	198.25	0	1.71	0	0.01	0	1.26	0	0.01	0	142.36	0	0.92	0	28122	0	3044939	0	84682	0	9124	0	2424	0	0	0	451119	0	205	0	0	0	2081	0	300784	0	5902	0	308972	0	82.02	0	2497590	0	5075	308306	60.749950738916	3044939.0	2582272.0	28122.0	84682.0	9124.0	2424.0	0.0	451119.0	2497590.0	84.8	0.9	2.8	0.3	0.1	0.0	14.8	82.0	101	101	101.00	38	307538839	27.1	22.5	22.6	27.8	0.0	34.8	18.0	smartseq
1447758	SRR3640174	SRP076212	SRS1489013	SRX1827055	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189857: C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189857		GSM2189857	C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	71626950	477513	2016-07-18 10:56:32	26461558	71626950	477513	2	477513	index:0,count:477513,average:75,stdev:0|index:1,count:477513,average:75,stdev:0	GSM2189857_r5						1.2	2.65	0.01	57916406	62111561	54629643	59110463	107.24	108.2	441412	391086	196.981	1315.453	134	2524	85.42	90.86	480383	377061	480383	377061	79.25	80.14	480383	349809	480383	332574	4515226	7.80	1.55	0	5.53	0	0.28	0	0.05	0	0.00	0	7.23	0	441412	0	150	0	147.59	0	3.80	0	0.04	0	1.08	0	0.01	0	143.25	0	0.26	0	7411	0	477513	0	26398	0	1338	0	241	0	0	0	34522	0	97	0	0	0	828	0	117248	0	708	0	118881	0	86.91	0	415014	0	26137	111742	4.275241994108	477513.0	441412.0	7411.0	26398.0	1338.0	241.0	0.0	34522.0	415014.0	92.4	1.6	5.5	0.3	0.1	0.0	7.2	86.9	75	75	75.00	6	35813475	24.3	25.7	25.4	24.6	0.0	34.8	28.3	smartseq
1447759	SRR3641174	SRP076212	SRS1489268	SRX1827310	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190112: G9_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190112		GSM2190112	G9_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	44885250	299235	2016-07-18 10:56:32	15008868	44885250	299235	2	299235	index:0,count:299235,average:75,stdev:0|index:1,count:299235,average:75,stdev:0	GSM2190112_r1						1.2	2.88	0.04	37064883	38369697	35165242	36662256	103.52	104.26	277875	244322	208.963	1469.433	122	1511	78.18	82.63	300839	217231	300839	217231	74.79	75.18	300839	207825	300839	197642	5776298	15.58	1.47	0	5.00	0	0.25	0	0.14	0	0.00	0	6.75	0	277875	0	150	0	147.75	0	3.29	0	0.02	0	1.17	0	0.01	0	119.69	0	0.21	0	4409	0	299235	0	14970	0	750	0	415	0	0	0	20195	0	64	0	0	0	528	0	70242	0	445	0	71279	0	87.86	0	262905	0	24737	67216	2.717225209201	299235.0	277875.0	4409.0	14970.0	750.0	415.0	0.0	20195.0	262905.0	92.9	1.5	5.0	0.3	0.1	0.0	6.7	87.9	75	75	75.00	6	22442625	25.0	24.9	24.8	25.2	0.0	35.2	30.1	smartseq
1447772	SRR3638175	SRP076212	SRS1488244	SRX1826286	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189088: 1-0-1-0-BTN35-C76-1782070112-18ul-1-IL5413-N709-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189088		GSM2189088	1-0-1-0-BTN35-C76-1782070112-18ul-1-IL5413-N709-N507 BTN35 Mic-scRNA-Seq	49073850	327159	2016-07-18 10:56:32	22963929	49073850	327159	2	327159	index:0,count:327159,average:75,stdev:0|index:1,count:327159,average:75,stdev:0	GSM2189088_r1						2.82	3.36	0.14	33999659	33065099	32092042	31513580	97.25	98.2	270098	256365	169.378	793.563	110	1495	58.05	61.58	296443	156794	296443	156794	59.44	58.94	296443	160553	296443	150072	11650234	34.27	1.34	0	4.73	0	0.23	0	0.27	0	0.00	0	16.94	0	270098	0	150	0	146.48	0	1.43	0	0.01	0	1.17	0	0.00	0	58.89	0	0.67	0	4369	0	327159	0	15488	0	761	0	885	0	0	0	55415	0	21	0	0	0	156	0	26408	0	283	0	26868	0	77.82	0	254610	0	10814	25716	2.378028481598	327159.0	270098.0	4369.0	15488.0	761.0	885.0	0.0	55415.0	254610.0	82.6	1.3	4.7	0.2	0.3	0.0	16.9	77.8	75	75	75.00	7	24536925	29.7	21.1	20.0	29.2	0.0	33.7	22.2	smartseq
1447773	SRR3639175	SRP076212	SRS1488578	SRX1826620	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189422: 1gg_BTN5_C07_IL4690-707-501_CTCTCTAC-TAGATCGC BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189422		GSM2189422	1gg_BTN5_C07_IL4690-707-501_CTCTCTAC-TAGATCGC BTN05 Mic-scRNA-Seq	503957680	2494840	2016-07-18 10:56:32	350451446	503957680	2494840	2	2494840	index:0,count:2494840,average:101,stdev:0|index:1,count:2494840,average:101,stdev:0	GSM2189422_r1						1.24	2.91	0.71	404023459	374240629	388220416	361136127	92.63	93.02	2226155	2096682	255.426	730.042	174	10898	58.78	61.23	2399496	1308590	2399496	1308590	59.52	59.4	2399496	1324936	2399496	1269569	128822672	31.88	0.97	0	3.56	0	0.49	0	0.09	0	0.00	0	10.19	0	2226155	0	202	0	198.95	0	1.68	0	0.01	0	1.21	0	0.01	0	183.29	0	0.81	0	24211	0	2494840	0	88844	0	12300	0	2218	0	0	0	254167	0	166	0	0	0	2764	0	348661	0	3520	0	355111	0	85.67	0	2137311	0	7366	354868	48.176486559870	2494840.0	2226155.0	24211.0	88844.0	12300.0	2218.0	0.0	254167.0	2137311.0	89.2	1.0	3.6	0.5	0.1	0.0	10.2	85.7	101	101	101.00	38	251978840	27.0	22.7	22.9	27.5	0.0	34.5	17.7	smartseq
1447774	SRR3640175	SRP076212	SRS1489013	SRX1827055	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189857: C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189857		GSM2189857	C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	69398400	462656	2016-07-18 10:56:32	25613147	69398400	462656	2	462656	index:0,count:462656,average:75,stdev:0|index:1,count:462656,average:75,stdev:0	GSM2189857_r6						1.21	2.63	0.02	56043676	60058612	52783118	57050422	107.16	108.08	427060	378840	196.574	1294.545	110	2407	85.3	90.85	465782	364269	465782	364269	79.31	80.2	465782	338708	465782	321581	4357944	7.78	1.55	0	5.64	0	0.30	0	0.05	0	0.00	0	7.34	0	427060	0	150	0	147.57	0	3.85	0	0.04	0	1.09	0	0.01	0	128.12	0	0.27	0	7192	0	462656	0	26093	0	1392	0	239	0	0	0	33965	0	95	0	0	0	846	0	112680	0	709	0	114330	0	86.67	0	400967	0	25799	107535	4.168184813365	462656.0	427060.0	7192.0	26093.0	1392.0	239.0	0.0	33965.0	400967.0	92.3	1.6	5.6	0.3	0.1	0.0	7.3	86.7	75	75	75.00	6	34699200	24.3	25.7	25.4	24.6	0.0	34.8	28.4	smartseq
1447775	SRR3641175	SRP076212	SRS1489268	SRX1827310	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190112: G9_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190112		GSM2190112	G9_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	44833200	298888	2016-07-18 10:56:32	15074541	44833200	298888	2	298888	index:0,count:298888,average:75,stdev:0|index:1,count:298888,average:75,stdev:0	GSM2190112_r2						1.18	2.82	0.03	36933185	38227797	35052885	36533433	103.51	104.22	276939	243313	209.612	1486.143	123	1471	78.37	82.79	299439	217034	299439	217034	75.03	75.4	299439	207793	299439	197653	5703039	15.44	1.55	0	4.95	0	0.24	0	0.15	0	0.00	0	6.95	0	276939	0	150	0	147.74	0	3.30	0	0.02	0	1.13	0	0.01	0	82.77	0	0.21	0	4620	0	298888	0	14800	0	723	0	442	0	0	0	20784	0	68	0	0	0	529	0	70045	0	391	0	71033	0	87.70	0	262139	0	24662	66992	2.716405806504	298888.0	276939.0	4620.0	14800.0	723.0	442.0	0.0	20784.0	262139.0	92.7	1.5	5.0	0.2	0.1	0.0	7.0	87.7	75	75	75.00	6	22416600	25.0	24.9	24.8	25.3	0.0	35.2	30.0	smartseq
1447788	SRR3638176	SRP076212	SRS1488244	SRX1826286	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189088: 1-0-1-0-BTN35-C76-1782070112-18ul-1-IL5413-N709-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189088		GSM2189088	1-0-1-0-BTN35-C76-1782070112-18ul-1-IL5413-N709-N507 BTN35 Mic-scRNA-Seq	47536650	316911	2016-07-18 10:56:32	22158762	47536650	316911	2	316911	index:0,count:316911,average:75,stdev:0|index:1,count:316911,average:75,stdev:0	GSM2189088_r2						2.86	3.31	0.14	33738073	32830160	31844325	31292070	97.31	98.27	267334	253361	171.465	795.008	91	1477	58.14	61.67	293072	155430	293072	155430	59.51	59.02	293072	159091	293072	148737	11539904	34.20	1.31	0	4.83	0	0.23	0	0.28	0	0.00	0	15.13	0	267334	0	150	0	146.53	0	1.47	0	0.01	0	1.19	0	0.00	0	51.86	0	0.66	0	4142	0	316911	0	15314	0	740	0	895	0	0	0	47942	0	17	0	0	0	165	0	26520	0	247	0	26949	0	79.52	0	252020	0	10770	25712	2.387372330548	316911.0	267334.0	4142.0	15314.0	740.0	895.0	0.0	47942.0	252020.0	84.4	1.3	4.8	0.2	0.3	0.0	15.1	79.5	75	75	75.00	7	23768325	29.6	21.1	20.0	29.3	0.0	33.8	22.5	smartseq
1447789	SRR3639176	SRP076212	SRS1488579	SRX1826621	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189423: 1gg_BTN5_C24_IL4690-706-502_TAGGCATG-CTCTCTAT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189423		GSM2189423	1gg_BTN5_C24_IL4690-706-502_TAGGCATG-CTCTCTAT BTN05 Mic-scRNA-Seq	620426840	3071420	2016-07-18 10:56:32	421380480	620426840	3071420	2	3071420	index:0,count:3071420,average:101,stdev:0|index:1,count:3071420,average:101,stdev:0	GSM2189423_r1						3.2	1.85	1.1	458446158	414450080	437187347	396081397	90.4	90.6	2585490	2491284	234.940	585.065	169	14105	63.01	66.14	2785996	1629121	2785996	1629121	64.6	64.28	2785996	1670112	2785996	1583177	111637963	24.35	1.12	0	3.99	0	0.20	0	0.12	0	0.00	0	15.50	0	2585490	0	202	0	197.95	0	1.67	0	0.01	0	1.24	0	0.01	0	184.29	0	0.92	0	34481	0	3071420	0	122429	0	6031	0	3677	0	0	0	476222	0	18	0	0	0	2108	0	278983	0	4103	0	285212	0	80.19	0	2463061	0	4751	283416	59.653967585771	3071420.0	2585490.0	34481.0	122429.0	6031.0	3677.0	0.0	476222.0	2463061.0	84.2	1.1	4.0	0.2	0.1	0.0	15.5	80.2	101	101	101.00	38	310213420	27.3	22.3	22.4	28.1	0.0	34.9	18.1	smartseq
1447790	SRR3640176	SRP076212	SRS1489013	SRX1827055	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189857: C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189857		GSM2189857	C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	69909300	466062	2016-07-18 10:56:32	25976241	69909300	466062	2	466062	index:0,count:466062,average:75,stdev:0|index:1,count:466062,average:75,stdev:0	GSM2189857_r7						1.19	2.61	0.02	56696721	60835185	53494230	57901351	107.3	108.24	431465	382496	197.695	1300.755	126	2449	85.48	90.87	469218	368829	469218	368829	79.23	80.08	469218	341854	469218	325020	4394199	7.75	1.55	0	5.49	0	0.29	0	0.05	0	0.00	0	7.08	0	431465	0	150	0	147.59	0	3.81	0	0.03	0	1.11	0	0.01	0	98.70	0	0.26	0	7241	0	466062	0	25589	0	1352	0	225	0	0	0	33020	0	94	0	0	0	816	0	114060	0	682	0	115652	0	87.09	0	405876	0	25902	108732	4.197822561964	466062.0	431465.0	7241.0	25589.0	1352.0	225.0	0.0	33020.0	405876.0	92.6	1.6	5.5	0.3	0.0	0.0	7.1	87.1	75	75	75.00	6	34954650	24.3	25.7	25.3	24.6	0.0	34.8	28.2	smartseq
1447791	SRR3641176	SRP076212	SRS1489268	SRX1827310	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190112: G9_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190112		GSM2190112	G9_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	44412450	296083	2016-07-18 10:56:32	15003928	44412450	296083	2	296083	index:0,count:296083,average:75,stdev:0|index:1,count:296083,average:75,stdev:0	GSM2190112_r3						1.18	2.85	0.03	36768214	38088064	34881120	36373945	103.59	104.28	275514	242066	209.568	1496.397	124	1482	78.32	82.77	297803	215770	297803	215770	74.97	75.34	297803	206560	297803	196393	5698416	15.50	1.46	0	5.01	0	0.25	0	0.15	0	0.00	0	6.55	0	275514	0	150	0	147.78	0	3.32	0	0.02	0	1.16	0	0.01	0	96.90	0	0.21	0	4333	0	296083	0	14824	0	739	0	431	0	0	0	19399	0	52	0	0	0	508	0	69546	0	384	0	70490	0	88.05	0	260690	0	24481	66424	2.713287855888	296083.0	275514.0	4333.0	14824.0	739.0	431.0	0.0	19399.0	260690.0	93.1	1.5	5.0	0.2	0.1	0.0	6.6	88.0	75	75	75.00	6	22206225	25.0	25.0	24.8	25.2	0.0	35.2	30.1	smartseq
1447803	SRR3638177	SRP076212	SRS1488244	SRX1826286	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189088: 1-0-1-0-BTN35-C76-1782070112-18ul-1-IL5413-N709-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189088		GSM2189088	1-0-1-0-BTN35-C76-1782070112-18ul-1-IL5413-N709-N507 BTN35 Mic-scRNA-Seq	48639450	324263	2016-07-18 10:56:32	22756168	48639450	324263	2	324263	index:0,count:324263,average:75,stdev:0|index:1,count:324263,average:75,stdev:0	GSM2189088_r3						2.77	3.34	0.14	33890293	32961890	31971193	31393210	97.26	98.19	268755	254851	170.439	804.895	105	1514	58.36	61.94	295056	156849	295056	156849	59.75	59.28	295056	160593	295056	150105	11479694	33.87	1.33	0	4.79	0	0.22	0	0.30	0	0.00	0	16.60	0	268755	0	150	0	146.52	0	1.47	0	0.01	0	1.19	0	0.00	0	40.25	0	0.68	0	4311	0	324263	0	15541	0	728	0	965	0	0	0	53815	0	27	0	0	0	148	0	26357	0	250	0	26782	0	78.09	0	253214	0	10878	25670	2.359808788380	324263.0	268755.0	4311.0	15541.0	728.0	965.0	0.0	53815.0	253214.0	82.9	1.3	4.8	0.2	0.3	0.0	16.6	78.1	75	75	75.00	7	24319725	29.6	21.1	20.1	29.2	0.0	33.7	22.3	smartseq
1447804	SRR3639177	SRP076212	SRS1488580	SRX1826622	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189424: 1gg_BTN5_C30_IL4690-702-503_CGTACTAG-TATCCTCT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189424		GSM2189424	1gg_BTN5_C30_IL4690-702-503_CGTACTAG-TATCCTCT BTN05 Mic-scRNA-Seq	671322154	3323377	2016-07-18 10:56:32	461471833	671322154	3323377	2	3323377	index:0,count:3323377,average:101,stdev:0|index:1,count:3323377,average:101,stdev:0	GSM2189424_r1						0.96	3.47	0.11	530514790	524956060	514985518	510868015	98.95	99.2	2958763	2769467	248.027	638.887	175	15003	70.87	73.05	3097281	2096822	3097281	2096822	70.73	70.72	3097281	2092734	3097281	2029907	137071791	25.84	0.95	0	2.66	0	0.19	0	0.03	0	0.00	0	10.75	0	2958763	0	202	0	198.36	0	1.60	0	0.01	0	1.18	0	0.00	0	221.56	0	0.91	0	31434	0	3323377	0	88521	0	6473	0	1020	0	0	0	357121	0	112	0	0	0	3392	0	566186	0	6119	0	575809	0	86.37	0	2870242	0	7545	564446	74.810603048376	3323377.0	2958763.0	31434.0	88521.0	6473.0	1020.0	0.0	357121.0	2870242.0	89.0	0.9	2.7	0.2	0.0	0.0	10.7	86.4	101	101	101.00	38	335661077	26.7	23.0	23.1	27.2	0.0	35.0	18.6	smartseq
1447805	SRR3640177	SRP076212	SRS1489013	SRX1827055	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189857: C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189857		GSM2189857	C9_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	69544800	463632	2016-07-18 10:56:32	25888917	69544800	463632	2	463632	index:0,count:463632,average:75,stdev:0|index:1,count:463632,average:75,stdev:0	GSM2189857_r8						1.2	2.64	0.02	56304953	60373525	53117321	57463521	107.23	108.18	428542	380087	197.922	1296.282	130	2404	85.48	90.9	466139	366328	466139	366328	79.3	80.17	466139	339825	466139	323082	4339221	7.71	1.57	0	5.51	0	0.29	0	0.05	0	0.00	0	7.23	0	428542	0	150	0	147.58	0	3.80	0	0.04	0	1.10	0	0.01	0	128.39	0	0.27	0	7265	0	463632	0	25534	0	1354	0	213	0	0	0	33523	0	83	0	0	0	880	0	113418	0	671	0	115052	0	86.92	0	403008	0	25921	108232	4.175456193820	463632.0	428542.0	7265.0	25534.0	1354.0	213.0	0.0	33523.0	403008.0	92.4	1.6	5.5	0.3	0.0	0.0	7.2	86.9	75	75	75.00	6	34772400	24.3	25.7	25.3	24.6	0.0	34.8	28.2	smartseq
1447806	SRR3641177	SRP076212	SRS1489268	SRX1827310	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190112: G9_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190112		GSM2190112	G9_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	44180550	294537	2016-07-18 10:56:32	15027591	44180550	294537	2	294537	index:0,count:294537,average:75,stdev:0|index:1,count:294537,average:75,stdev:0	GSM2190112_r4						1.19	2.84	0.03	36518926	37797258	34593506	36061707	103.5	104.24	273684	240234	209.100	1501.547	121	1423	78.19	82.75	296643	213997	296643	213997	75.03	75.39	296643	205352	296643	194958	5672509	15.53	1.44	0	5.12	0	0.26	0	0.16	0	0.00	0	6.66	0	273684	0	150	0	147.75	0	3.20	0	0.02	0	1.13	0	0.01	0	81.56	0	0.21	0	4241	0	294537	0	15088	0	752	0	474	0	0	0	19627	0	53	0	0	0	522	0	69195	0	402	0	70172	0	87.80	0	258596	0	24536	66209	2.698443104010	294537.0	273684.0	4241.0	15088.0	752.0	474.0	0.0	19627.0	258596.0	92.9	1.4	5.1	0.3	0.2	0.0	6.7	87.8	75	75	75.00	6	22090275	25.0	24.9	24.8	25.2	0.0	35.2	30.0	smartseq
1447819	SRR3638178	SRP076212	SRS1488244	SRX1826286	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189088: 1-0-1-0-BTN35-C76-1782070112-18ul-1-IL5413-N709-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189088		GSM2189088	1-0-1-0-BTN35-C76-1782070112-18ul-1-IL5413-N709-N507 BTN35 Mic-scRNA-Seq	49239000	328260	2016-07-18 10:56:32	22746970	49239000	328260	2	328260	index:0,count:328260,average:75,stdev:0|index:1,count:328260,average:75,stdev:0	GSM2189088_r4						2.82	3.33	0.16	34589964	33632749	32623146	32025869	97.23	98.17	274616	260534	170.604	763.647	100	1569	58.08	61.65	301849	159510	301849	159510	59.47	59.03	301849	163323	301849	152728	11819098	34.17	1.32	0	4.84	0	0.23	0	0.32	0	0.00	0	15.80	0	274616	0	150	0	146.52	0	1.43	0	0.01	0	1.19	0	0.00	0	73.86	0	0.62	0	4335	0	328260	0	15875	0	750	0	1039	0	0	0	51855	0	21	0	0	0	183	0	26876	0	237	0	27317	0	78.82	0	258741	0	10909	26268	2.407920066001	328260.0	274616.0	4335.0	15875.0	750.0	1039.0	0.0	51855.0	258741.0	83.7	1.3	4.8	0.2	0.3	0.0	15.8	78.8	75	75	75.00	7	24619500	29.7	21.1	20.0	29.3	0.0	34.0	22.7	smartseq
1447820	SRR3639178	SRP076212	SRS1488581	SRX1826623	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189425: 1gg_BTN5_C32_IL4690-704-501_TCCTGAGC-TAGATCGC BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189425		GSM2189425	1gg_BTN5_C32_IL4690-704-501_TCCTGAGC-TAGATCGC BTN05 Mic-scRNA-Seq	378866352	1875576	2016-07-18 10:56:32	263482365	378866352	1875576	2	1875576	index:0,count:1875576,average:101,stdev:0|index:1,count:1875576,average:101,stdev:0	GSM2189425_r1						2.47	2.22	0.63	285144790	270407671	274232509	261492565	94.83	95.35	1611837	1568262	229.696	503.309	188	9373	67.85	70.6	1725826	1093559	1725826	1093559	68.32	68.63	1725826	1101152	1725826	1063140	69470109	24.36	1.27	0	3.35	0	0.23	0	0.11	0	0.00	0	13.72	0	1611837	0	202	0	198.24	0	1.62	0	0.01	0	1.19	0	0.01	0	153.46	0	0.75	0	23762	0	1875576	0	62852	0	4324	0	2066	0	0	0	257349	0	196	0	0	0	733	0	140910	0	2172	0	144011	0	82.59	0	1548985	0	2921	140639	48.147552208148	1875576.0	1611837.0	23762.0	62852.0	4324.0	2066.0	0.0	257349.0	1548985.0	85.9	1.3	3.4	0.2	0.1	0.0	13.7	82.6	101	101	101.00	38	189433176	27.2	22.1	22.6	28.1	0.0	33.8	16.4	smartseq
1447821	SRR3640178	SRP076212	SRS1489014	SRX1827056	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189858: C9_1000700401-OGC7-coc_1_12ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189858		GSM2189858	C9_1000700401-OGC7-coc_1_12ul_1 OGC07-sal FACS-scRNA-Seq	58573800	390492	2016-07-18 10:56:32	19632170	58573800	390492	2	390492	index:0,count:390492,average:75,stdev:0|index:1,count:390492,average:75,stdev:0	GSM2189858_r1						1.41	2.69	0.08	48509207	51718209	45815589	49244625	106.62	107.48	362402	315600	212.817	1503.444	125	1856	84.48	89.74	393241	306168	393241	306168	78.71	79.51	393241	285264	393241	271266	4296983	8.86	1.56	0	5.43	0	0.30	0	0.08	0	0.00	0	6.82	0	362402	0	150	0	147.78	0	3.89	0	0.04	0	1.13	0	0.01	0	117.15	0	0.22	0	6075	0	390492	0	21213	0	1173	0	299	0	0	0	26618	0	63	0	0	0	662	0	94819	0	562	0	96106	0	87.37	0	341189	0	26742	91546	3.423304165732	390492.0	362402.0	6075.0	21213.0	1173.0	299.0	0.0	26618.0	341189.0	92.8	1.6	5.4	0.3	0.1	0.0	6.8	87.4	75	75	75.00	6	29286900	24.5	25.4	25.2	24.8	0.0	35.2	30.2	smartseq
1447822	SRR3641178	SRP076212	SRS1489269	SRX1827311	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190113: G9_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190113		GSM2190113	G9_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	45831600	305544	2016-07-18 10:56:32	15519185	45831600	305544	2	305544	index:0,count:305544,average:75,stdev:0|index:1,count:305544,average:75,stdev:0	GSM2190113_r1						1.47	2.44	0.02	37947641	41247009	35776892	39274378	108.69	109.78	282652	249495	215.175	1481.556	125	1471	81.35	86.57	307289	229941	307289	229941	73.55	74.23	307289	207886	307289	197170	4425238	11.66	1.66	0	5.57	0	0.39	0	0.10	0	0.00	0	7.01	0	282652	0	150	0	147.73	0	4.09	0	0.04	0	1.11	0	0.01	0	91.66	0	0.24	0	5087	0	305544	0	17027	0	1183	0	305	0	0	0	21404	0	58	0	0	0	416	0	66243	0	437	0	67154	0	86.94	0	265625	0	21581	63796	2.956118808211	305544.0	282652.0	5087.0	17027.0	1183.0	305.0	0.0	21404.0	265625.0	92.5	1.7	5.6	0.4	0.1	0.0	7.0	86.9	75	75	75.00	6	22915800	24.6	25.3	25.2	24.9	0.0	35.2	30.0	smartseq
1447836	SRR3638179	SRP076212	SRS1488245	SRX1826287	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189089: 1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189089		GSM2189089	1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq	29810700	198738	2016-07-18 10:56:32	15064135	29810700	198738	2	198738	index:0,count:198738,average:75,stdev:0|index:1,count:198738,average:75,stdev:0	GSM2189089_r1						3.86	2.93	0.1	25506703	25341963	24589417	24557440	99.35	99.87	176438	170801	235.541	582.139	188	1015	50.9	52.81	185524	89805	185524	89805	51.22	50.42	185524	90363	185524	85737	11511002	45.13	1.12	0	3.22	0	0.07	0	0.18	0	0.00	0	10.97	0	176438	0	150	0	148.12	0	1.44	0	0.01	0	1.29	0	0.01	0	44.72	0	0.71	0	2227	0	198738	0	6397	0	145	0	349	0	0	0	21806	0	7	0	0	0	65	0	8319	0	142	0	8533	0	85.56	0	170041	0	2803	8511	3.036389582590	198738.0	176438.0	2227.0	6397.0	145.0	349.0	0.0	21806.0	170041.0	88.8	1.1	3.2	0.1	0.2	0.0	11.0	85.6	75	75	75.00	7	14905350	31.1	18.9	19.4	30.5	0.0	32.7	20.5	smartseq
1447837	SRR3639179	SRP076212	SRS1488582	SRX1826624	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189426: 1gg_BTN5_C37_IL4690-702-501_CGTACTAG-TAGATCGC BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189426		GSM2189426	1gg_BTN5_C37_IL4690-702-501_CGTACTAG-TAGATCGC BTN05 Mic-scRNA-Seq	501718510	2483755	2016-07-18 10:56:32	346239578	501718510	2483755	2	2483755	index:0,count:2483755,average:101,stdev:0|index:1,count:2483755,average:101,stdev:0	GSM2189426_r1						1.67	2.34	0.96	394649057	371789925	378106080	357582958	94.21	94.57	2190757	2071940	252.165	755.956	174	11115	69.97	73.09	2361196	1532816	2361196	1532816	70.08	70.31	2361196	1535338	2361196	1474497	82481098	20.90	1.14	0	3.77	0	0.34	0	0.12	0	0.00	0	11.33	0	2190757	0	202	0	198.49	0	1.75	0	0.01	0	1.22	0	0.01	0	182.48	0	0.86	0	28359	0	2483755	0	93618	0	8555	0	3008	0	0	0	281435	0	377	0	0	0	2604	0	358417	0	4664	0	366062	0	84.43	0	2097139	0	6652	363024	54.573662056524	2483755.0	2190757.0	28359.0	93618.0	8555.0	3008.0	0.0	281435.0	2097139.0	88.2	1.1	3.8	0.3	0.1	0.0	11.3	84.4	101	101	101.00	38	250859255	26.5	23.1	23.3	27.1	0.0	34.6	17.8	smartseq
1447838	SRR3640179	SRP076212	SRS1489014	SRX1827056	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189858: C9_1000700401-OGC7-coc_1_12ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189858		GSM2189858	C9_1000700401-OGC7-coc_1_12ul_1 OGC07-sal FACS-scRNA-Seq	58114350	387429	2016-07-18 10:56:32	19555034	58114350	387429	2	387429	index:0,count:387429,average:75,stdev:0|index:1,count:387429,average:75,stdev:0	GSM2189858_r2						1.41	2.69	0.06	48050739	51193585	45356771	48772356	106.54	107.53	358878	312426	213.134	1516.937	123	1826	84.46	89.75	389476	303099	389476	303099	78.63	79.45	389476	282191	389476	268318	4238151	8.82	1.53	0	5.47	0	0.28	0	0.07	0	0.00	0	7.02	0	358878	0	150	0	147.76	0	3.84	0	0.03	0	1.13	0	0.01	0	116.23	0	0.23	0	5937	0	387429	0	21179	0	1088	0	281	0	0	0	27182	0	64	0	0	0	649	0	93337	0	584	0	94634	0	87.16	0	337699	0	26705	90030	3.371278786744	387429.0	358878.0	5937.0	21179.0	1088.0	281.0	0.0	27182.0	337699.0	92.6	1.5	5.5	0.3	0.1	0.0	7.0	87.2	75	75	75.00	6	29057175	24.5	25.4	25.2	24.8	0.0	35.2	30.1	smartseq
1447839	SRR3641179	SRP076212	SRS1489269	SRX1827311	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190113: G9_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190113		GSM2190113	G9_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	45483000	303220	2016-07-18 10:56:32	15481247	45483000	303220	2	303220	index:0,count:303220,average:75,stdev:0|index:1,count:303220,average:75,stdev:0	GSM2190113_r2						1.45	2.41	0.02	37577198	40795578	35420904	38822106	108.56	109.6	279889	246531	215.707	1457.391	125	1433	81.36	86.6	304404	227731	304404	227731	73.77	74.43	304404	206486	304404	195742	4393453	11.69	1.65	0	5.58	0	0.38	0	0.09	0	0.00	0	7.23	0	279889	0	150	0	147.74	0	4.01	0	0.04	0	1.14	0	0.02	0	90.97	0	0.24	0	4996	0	303220	0	16905	0	1142	0	267	0	0	0	21922	0	35	0	0	0	461	0	65556	0	441	0	66493	0	86.73	0	262984	0	21554	63118	2.928365964554	303220.0	279889.0	4996.0	16905.0	1142.0	267.0	0.0	21922.0	262984.0	92.3	1.6	5.6	0.4	0.1	0.0	7.2	86.7	75	75	75.00	6	22741500	24.6	25.3	25.2	24.9	0.0	35.2	29.9	smartseq
1447949	SRR3638180	SRP076212	SRS1488245	SRX1826287	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189089: 1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189089		GSM2189089	1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq	28629900	190866	2016-07-18 10:56:32	14429609	28629900	190866	2	190866	index:0,count:190866,average:75,stdev:0|index:1,count:190866,average:75,stdev:0	GSM2189089_r2						3.79	3.02	0.1	24588043	24440786	23731703	23699250	99.4	99.86	169944	164442	236.756	580.464	183	940	50.83	52.68	178292	86389	178292	86389	51.05	50.31	178292	86761	178292	82495	11145140	45.33	1.13	0	3.12	0	0.07	0	0.17	0	0.00	0	10.71	0	169944	0	150	0	148.17	0	1.45	0	0.01	0	1.31	0	0.01	0	45.81	0	0.71	0	2155	0	190866	0	5959	0	142	0	331	0	0	0	20449	0	0	0	0	0	51	0	7949	0	142	0	8142	0	85.92	0	163985	0	2719	8045	2.958808385436	190866.0	169944.0	2155.0	5959.0	142.0	331.0	0.0	20449.0	163985.0	89.0	1.1	3.1	0.1	0.2	0.0	10.7	85.9	75	75	75.00	7	14314950	31.1	18.9	19.4	30.6	0.0	32.7	20.5	smartseq
1447950	SRR3639180	SRP076212	SRS1488583	SRX1826625	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189427: 1gg_BTN5_C41_IL4690-709-502_GCTACGCT-CTCTCTAT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189427		GSM2189427	1gg_BTN5_C41_IL4690-709-502_GCTACGCT-CTCTCTAT BTN05 Mic-scRNA-Seq	759261036	3758718	2016-07-18 10:56:32	516197832	759261036	3758718	2	3758718	index:0,count:3758718,average:101,stdev:0|index:1,count:3758718,average:101,stdev:0	GSM2189427_r1						1.02	2.6	0.85	573800655	554196579	548800914	532437036	96.58	97.02	3215952	2982808	244.180	809.792	174	16995	78.35	82.01	3498848	2519737	3498848	2519737	78.99	79.49	3498848	2540202	3498848	2442499	80700561	14.06	0.94	0	3.81	0	0.57	0	0.03	0	0.00	0	13.84	0	3215952	0	202	0	197.92	0	1.88	0	0.01	0	1.21	0	0.01	0	135.31	0	0.93	0	35304	0	3758718	0	143306	0	21440	0	1079	0	0	0	520247	0	214	0	0	0	5632	0	652712	0	6413	0	664971	0	81.75	0	3072646	0	6762	655932	97.002661934339	3758718.0	3215952.0	35304.0	143306.0	21440.0	1079.0	0.0	520247.0	3072646.0	85.6	0.9	3.8	0.6	0.0	0.0	13.8	81.7	101	101	101.00	38	379630518	26.4	23.3	23.4	26.9	0.0	34.9	18.4	smartseq
1447951	SRR3640180	SRP076212	SRS1489014	SRX1827056	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189858: C9_1000700401-OGC7-coc_1_12ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189858		GSM2189858	C9_1000700401-OGC7-coc_1_12ul_1 OGC07-sal FACS-scRNA-Seq	57926250	386175	2016-07-18 10:56:32	19641326	57926250	386175	2	386175	index:0,count:386175,average:75,stdev:0|index:1,count:386175,average:75,stdev:0	GSM2189858_r3						1.4	2.73	0.07	48069630	51251066	45383135	48818541	106.62	107.57	358957	312441	213.387	1535.406	125	1873	84.58	89.87	390073	303618	390073	303618	78.76	79.55	390073	282724	390073	268764	4196179	8.73	1.52	0	5.46	0	0.30	0	0.07	0	0.00	0	6.68	0	358957	0	150	0	147.76	0	3.86	0	0.03	0	1.12	0	0.01	0	115.85	0	0.22	0	5871	0	386175	0	21102	0	1140	0	283	0	0	0	25795	0	69	0	0	0	619	0	93572	0	585	0	94845	0	87.49	0	337855	0	26743	90385	3.379762928617	386175.0	358957.0	5871.0	21102.0	1140.0	283.0	0.0	25795.0	337855.0	93.0	1.5	5.5	0.3	0.1	0.0	6.7	87.5	75	75	75.00	6	28963125	24.5	25.4	25.2	24.8	0.0	35.2	30.1	smartseq
1447965	SRR3638181	SRP076212	SRS1488245	SRX1826287	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189089: 1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189089		GSM2189089	1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq	28007400	186716	2016-07-18 10:56:32	14319357	28007400	186716	2	186716	index:0,count:186716,average:75,stdev:0|index:1,count:186716,average:75,stdev:0	GSM2189089_r3						3.8	2.96	0.08	23897823	23754704	23073214	23043051	99.4	99.87	165361	160090	234.760	552.821	188	951	50.93	52.77	173401	84219	173401	84219	51.12	50.35	173401	84535	173401	80363	10811533	45.24	1.16	0	3.08	0	0.08	0	0.18	0	0.00	0	11.18	0	165361	0	150	0	148.10	0	1.43	0	0.01	0	1.31	0	0.01	0	42.01	0	0.72	0	2165	0	186716	0	5759	0	142	0	341	0	0	0	20872	0	8	0	0	0	72	0	7944	0	167	0	8191	0	85.48	0	159602	0	2757	8081	2.931084512151	186716.0	165361.0	2165.0	5759.0	142.0	341.0	0.0	20872.0	159602.0	88.6	1.2	3.1	0.1	0.2	0.0	11.2	85.5	75	75	75.00	7	14003700	31.3	18.8	19.4	30.5	0.0	32.5	20.3	smartseq
1447966	SRR3639181	SRP076212	SRS1488585	SRX1826626	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189428: 1gg_BTN5_C47_IL4690-710-502_CGAGGCTG-CTCTCTAT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189428		GSM2189428	1gg_BTN5_C47_IL4690-710-502_CGAGGCTG-CTCTCTAT BTN05 Mic-scRNA-Seq	672375988	3328594	2016-07-18 10:56:32	460880885	672375988	3328594	2	3328594	index:0,count:3328594,average:101,stdev:0|index:1,count:3328594,average:101,stdev:0	GSM2189428_r1						0.96	2.32	0.27	516093981	505356077	495950761	487594156	97.92	98.32	2866142	2672429	249.584	741.397	188	14443	67.58	70.39	3074996	1937064	3074996	1937064	67.51	67.66	3074996	1935003	3074996	1861932	139323218	27.00	0.93	0	3.43	0	0.24	0	0.09	0	0.00	0	13.57	0	2866142	0	202	0	198.20	0	1.85	0	0.01	0	1.20	0	0.01	0	190.21	0	0.92	0	30986	0	3328594	0	114203	0	7977	0	2888	0	0	0	451587	0	47	0	0	0	3707	0	549692	0	5224	0	558670	0	82.68	0	2751939	0	8248	555771	67.382516973812	3328594.0	2866142.0	30986.0	114203.0	7977.0	2888.0	0.0	451587.0	2751939.0	86.1	0.9	3.4	0.2	0.1	0.0	13.6	82.7	101	101	101.00	38	336187994	26.5	23.2	23.3	27.0	0.0	34.7	18.2	smartseq
1447967	SRR3640181	SRP076212	SRS1489014	SRX1827056	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189858: C9_1000700401-OGC7-coc_1_12ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189858		GSM2189858	C9_1000700401-OGC7-coc_1_12ul_1 OGC07-sal FACS-scRNA-Seq	57336750	382245	2016-07-18 10:56:32	19552683	57336750	382245	2	382245	index:0,count:382245,average:75,stdev:0|index:1,count:382245,average:75,stdev:0	GSM2189858_r4						1.41	2.7	0.06	47477342	50647052	44799173	48214940	106.68	107.62	354822	308991	212.791	1535.606	134	1858	84.49	89.82	385682	299801	385682	299801	78.72	79.5	385682	279329	385682	265356	4170656	8.78	1.57	0	5.51	0	0.30	0	0.07	0	0.00	0	6.81	0	354822	0	150	0	147.72	0	3.82	0	0.03	0	1.10	0	0.01	0	98.29	0	0.23	0	5996	0	382245	0	21051	0	1134	0	267	0	0	0	26022	0	75	0	0	0	672	0	92255	0	546	0	93548	0	87.32	0	333771	0	26477	89170	3.367828681497	382245.0	354822.0	5996.0	21051.0	1134.0	267.0	0.0	26022.0	333771.0	92.8	1.6	5.5	0.3	0.1	0.0	6.8	87.3	75	75	75.00	6	28668375	24.5	25.4	25.2	24.8	0.0	35.2	30.0	smartseq
1447981	SRR3638182	SRP076212	SRS1488245	SRX1826287	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189089: 1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189089		GSM2189089	1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq	25235700	168238	2016-07-18 10:56:32	13009984	25235700	168238	2	168238	index:0,count:168238,average:75,stdev:0|index:1,count:168238,average:75,stdev:0	GSM2189089_r4						3.8	2.93	0.1	21519302	21402486	20751878	20739053	99.46	99.94	148790	144150	234.396	578.727	195	865	50.85	52.75	156332	75659	156332	75659	51.15	50.35	156332	76104	156332	72220	9733165	45.23	1.13	0	3.18	0	0.08	0	0.16	0	0.00	0	11.31	0	148790	0	150	0	148.10	0	1.46	0	0.01	0	1.26	0	0.01	0	35.63	0	0.77	0	1900	0	168238	0	5357	0	142	0	274	0	0	0	19032	0	9	0	0	0	51	0	6882	0	137	0	7079	0	85.26	0	143433	0	2545	6966	2.737131630648	168238.0	148790.0	1900.0	5357.0	142.0	274.0	0.0	19032.0	143433.0	88.4	1.1	3.2	0.1	0.2	0.0	11.3	85.3	75	75	75.00	7	12617850	31.3	18.7	19.4	30.6	0.0	32.3	20.0	smartseq
1447982	SRR3639182	SRP076212	SRS1488584	SRX1826627	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189429: 1gg_BTN5_C49_IL4690-711-501_AAGAGGCA-TAGATCGC BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189429		GSM2189429	1gg_BTN5_C49_IL4690-711-501_AAGAGGCA-TAGATCGC BTN05 Mic-scRNA-Seq	471863314	2335957	2016-07-18 10:56:32	325992045	471863314	2335957	2	2335957	index:0,count:2335957,average:101,stdev:0|index:1,count:2335957,average:101,stdev:0	GSM2189429_r1						1.82	2.95	0.69	370035688	341303360	349125319	324115811	92.24	92.84	2058341	1937175	249.888	712.753	182	10408	68.87	73.06	2289640	1417614	2289640	1417614	70.41	70.6	2289640	1449329	2289640	1369830	69342266	18.74	1.10	0	5.05	0	0.62	0	0.09	0	0.00	0	11.17	0	2058341	0	202	0	198.38	0	1.71	0	0.01	0	1.31	0	0.01	0	168.19	0	0.82	0	25785	0	2335957	0	117939	0	14570	0	2185	0	0	0	260861	0	142	0	0	0	2436	0	350695	0	3581	0	356854	0	83.07	0	1940402	0	7976	366916	46.002507522568	2335957.0	2058341.0	25785.0	117939.0	14570.0	2185.0	0.0	260861.0	1940402.0	88.1	1.1	5.0	0.6	0.1	0.0	11.2	83.1	101	101	101.00	38	235931657	26.7	22.9	23.1	27.4	0.0	34.6	17.6	smartseq
1447983	SRR3640182	SRP076212	SRS1489015	SRX1827057	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189859: C9_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189859		GSM2189859	C9_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq	64109550	427397	2016-07-18 10:56:32	23996529	64109550	427397	2	427397	index:0,count:427397,average:75,stdev:0|index:1,count:427397,average:75,stdev:0	GSM2189859_r1						0.91	2.36	0.05	52598170	57774969	49787062	55212659	109.84	110.9	392855	348677	215.243	1417.259	125	2044	77.76	82.45	425380	305503	425380	305503	67.89	68.62	425380	266715	425380	254263	7969073	15.15	1.73	0	5.22	0	0.29	0	0.16	0	0.00	0	7.63	0	392855	0	150	0	147.69	0	4.29	0	0.05	0	1.15	0	0.02	0	118.36	0	0.30	0	7393	0	427397	0	22316	0	1246	0	691	0	0	0	32605	0	80	0	0	0	588	0	85046	0	656	0	86370	0	86.70	0	370539	0	25348	81874	3.229998421966	427397.0	392855.0	7393.0	22316.0	1246.0	691.0	0.0	32605.0	370539.0	91.9	1.7	5.2	0.3	0.2	0.0	7.6	86.7	75	75	75.00	6	32054775	24.3	25.7	25.4	24.6	0.0	34.7	27.9	smartseq
1447997	SRR3638183	SRP076212	SRS1488245	SRX1826287	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189089: 1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189089		GSM2189089	1-0-1-1-BTN27-C03-1771026164-IL5326-704-501 BTN27 Mic-scRNA-Seq	111683700	744558	2016-07-18 10:56:32	56730582	111683700	744558	2	744558	index:0,count:744558,average:75,stdev:0|index:1,count:744558,average:75,stdev:0	GSM2189089_r5						3.82	2.96	0.09	95511871	94939939	92146212	92038794	99.4	99.88	660533	639483	235.400	573.600	188	3723	50.88	52.75	693549	336072	693549	336072	51.13	50.36	693549	337763	693549	320815	43200840	45.23	1.13	0	3.15	0	0.08	0	0.17	0	0.00	0	11.03	0	660533	0	150	0	148.12	0	1.44	0	0.01	0	1.29	0	0.01	0	148.91	0	0.73	0	8447	0	744558	0	23472	0	571	0	1295	0	0	0	82159	0	24	0	0	0	239	0	31094	0	588	0	31945	0	85.56	0	637061	0	4477	31987	7.144739781103	744558.0	660533.0	8447.0	23472.0	571.0	1295.0	0.0	82159.0	637061.0	88.7	1.1	3.2	0.1	0.2	0.0	11.0	85.6	75	75	75.00	7	55841850	31.2	18.8	19.4	30.5	0.0	32.6	20.3	smartseq
1447998	SRR3639183	SRP076212	SRS1488586	SRX1826628	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189430: 1gg_BTN5_C54_IL4690-707-503_CTCTCTAC-TATCCTCT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189430		GSM2189430	1gg_BTN5_C54_IL4690-707-503_CTCTCTAC-TATCCTCT BTN05 Mic-scRNA-Seq	58733722	290761	2016-07-18 10:56:32	40654047	58733722	290761	2	290761	index:0,count:290761,average:101,stdev:0|index:1,count:290761,average:101,stdev:0	GSM2189430_r1						0.31	1.28	0.09	40365410	40126866	38294076	38094087	99.41	99.48	245482	231455	200.779	613.297	173	1845	85.92	90.63	272549	210909	272549	210909	86.29	86.54	272549	211820	272549	201401	2692084	6.67	1.64	0	4.39	0	1.14	0	0.01	0	0.00	0	14.42	0	245482	0	202	0	197.24	0	1.82	0	0.01	0	1.20	0	0.00	0	61.57	0	0.97	0	4782	0	290761	0	12755	0	3324	0	31	0	0	0	41924	0	18	0	0	0	294	0	74851	0	683	0	75846	0	80.04	0	232727	0	4833	71216	14.735361059383	290761.0	245482.0	4782.0	12755.0	3324.0	31.0	0.0	41924.0	232727.0	84.4	1.6	4.4	1.1	0.0	0.0	14.4	80.0	101	101	101.00	38	29366861	23.4	26.5	26.4	23.7	0.0	34.5	19.1	smartseq
1447999	SRR3640183	SRP076212	SRS1489015	SRX1827057	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189859: C9_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189859		GSM2189859	C9_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq	61695300	411302	2016-07-18 10:56:32	23057692	61695300	411302	2	411302	index:0,count:411302,average:75,stdev:0|index:1,count:411302,average:75,stdev:0	GSM2189859_r2						0.91	2.37	0.05	50624023	55514402	47910434	53043729	109.66	110.71	377988	335876	215.084	1446.959	125	1982	77.61	82.27	409598	293356	409598	293356	67.9	68.58	409598	256661	409598	244531	7728126	15.27	1.76	0	5.21	0	0.28	0	0.16	0	0.00	0	7.66	0	377988	0	150	0	147.68	0	4.28	0	0.05	0	1.16	0	0.02	0	92.54	0	0.31	0	7226	0	411302	0	21427	0	1145	0	674	0	0	0	31495	0	89	0	0	0	558	0	81431	0	590	0	82668	0	86.69	0	356561	0	24800	78208	3.153548387097	411302.0	377988.0	7226.0	21427.0	1145.0	674.0	0.0	31495.0	356561.0	91.9	1.8	5.2	0.3	0.2	0.0	7.7	86.7	75	75	75.00	6	30847650	24.3	25.7	25.4	24.6	0.0	34.8	28.1	smartseq
1448012	SRR3638184	SRP076212	SRS1488246	SRX1826288	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189090: 1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189090		GSM2189090	1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq	37644000	250960	2016-07-18 10:56:32	17791219	37644000	250960	2	250960	index:0,count:250960,average:75,stdev:0|index:1,count:250960,average:75,stdev:0	GSM2189090_r1						2.72	3.27	0.12	33067665	32175611	32231485	31481592	97.3	97.67	228119	221140	242.303	576.769	193	1258	39.32	40.36	237131	89700	237131	89700	39.5	38.79	237131	90110	237131	86213	18830239	56.94	1.25	0	2.34	0	0.15	0	0.22	0	0.00	0	8.73	0	228119	0	150	0	148.37	0	1.52	0	0.01	0	1.25	0	0.01	0	60.23	0	0.67	0	3144	0	250960	0	5862	0	382	0	552	0	0	0	21907	0	5	0	0	0	119	0	9847	0	337	0	10308	0	88.56	0	222257	0	3539	10126	2.861260243006	250960.0	228119.0	3144.0	5862.0	382.0	552.0	0.0	21907.0	222257.0	90.9	1.3	2.3	0.2	0.2	0.0	8.7	88.6	75	75	75.00	7	18822000	30.1	19.8	20.0	30.1	0.0	33.6	21.9	smartseq
1448013	SRR3639184	SRP076212	SRS1488587	SRX1826629	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189431: 1gg_BTN5_C57_IL4690-702-502_CGTACTAG-CTCTCTAT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189431		GSM2189431	1gg_BTN5_C57_IL4690-702-502_CGTACTAG-CTCTCTAT BTN05 Mic-scRNA-Seq	674193786	3337593	2016-07-18 10:56:32	459737756	674193786	3337593	2	3337593	index:0,count:3337593,average:101,stdev:0|index:1,count:3337593,average:101,stdev:0	GSM2189431_r1						1.83	3.67	0.7	507836749	477803403	489553131	462133328	94.09	94.4	2843137	2664622	243.807	694.272	188	15007	69.72	72.39	3022339	1982235	3022339	1982235	69.99	70.1	3022339	1989964	3022339	1919498	108956686	21.46	0.99	0	3.14	0	0.20	0	0.06	0	0.00	0	14.56	0	2843137	0	202	0	198.13	0	1.63	0	0.01	0	1.25	0	0.00	0	174.14	0	0.92	0	32983	0	3337593	0	104906	0	6532	0	1979	0	0	0	485945	0	227	0	0	0	2772	0	525734	0	5751	0	534484	0	82.04	0	2738231	0	7484	525902	70.270176376269	3337593.0	2843137.0	32983.0	104906.0	6532.0	1979.0	0.0	485945.0	2738231.0	85.2	1.0	3.1	0.2	0.1	0.0	14.6	82.0	101	101	101.00	38	337096893	26.9	22.8	22.9	27.4	0.0	35.0	18.7	smartseq
1448014	SRR3640184	SRP076212	SRS1489015	SRX1827057	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189859: C9_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189859		GSM2189859	C9_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq	62512950	416753	2016-07-18 10:56:32	23537447	62512950	416753	2	416753	index:0,count:416753,average:75,stdev:0|index:1,count:416753,average:75,stdev:0	GSM2189859_r3						0.92	2.33	0.05	51430941	56426765	48664551	53911400	109.71	110.78	383602	340642	215.905	1406.878	110	1952	77.73	82.44	415662	298165	415662	298165	67.86	68.62	415662	260324	415662	248203	7774434	15.12	1.69	0	5.26	0	0.28	0	0.17	0	0.00	0	7.50	0	383602	0	150	0	147.72	0	4.33	0	0.05	0	1.16	0	0.02	0	115.41	0	0.30	0	7054	0	416753	0	21908	0	1171	0	714	0	0	0	31266	0	77	0	0	0	531	0	83002	0	580	0	84190	0	86.79	0	361694	0	24983	79784	3.193531601489	416753.0	383602.0	7054.0	21908.0	1171.0	714.0	0.0	31266.0	361694.0	92.0	1.7	5.3	0.3	0.2	0.0	7.5	86.8	75	75	75.00	6	31256475	24.3	25.7	25.4	24.6	0.0	34.7	27.8	smartseq
1448015	SRR3641184	SRP076212	SRS1489270	SRX1827312	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190114: G9_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190114		GSM2190114	G9_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq	56297850	375319	2016-07-18 10:56:32	21196741	56297850	375319	2	375319	index:0,count:375319,average:75,stdev:0|index:1,count:375319,average:75,stdev:0	GSM2190114_r2						2.09	2.1	0.05	45309733	51514127	42583999	49004844	113.69	115.08	340725	317119	207.407	926.711	110	1876	78.83	84.21	369183	268605	369183	268605	65.03	65.81	369183	221581	369183	209914	5765421	12.72	2.38	0	5.80	0	0.22	0	0.15	0	0.00	0	8.85	0	340725	0	150	0	147.53	0	4.40	0	0.06	0	1.11	0	0.02	0	122.83	0	0.33	0	8920	0	375319	0	21773	0	825	0	557	0	0	0	33212	0	56	0	0	0	336	0	49483	0	870	0	50745	0	84.98	0	318952	0	15137	47316	3.125850564841	375319.0	340725.0	8920.0	21773.0	825.0	557.0	0.0	33212.0	318952.0	90.8	2.4	5.8	0.2	0.1	0.0	8.8	85.0	75	75	75.00	6	28148925	24.4	25.6	25.3	24.7	0.0	34.7	27.9	smartseq
1448028	SRR3638185	SRP076212	SRS1488246	SRX1826288	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189090: 1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189090		GSM2189090	1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq	36736500	244910	2016-07-18 10:56:32	17211612	36736500	244910	2	244910	index:0,count:244910,average:75,stdev:0|index:1,count:244910,average:75,stdev:0	GSM2189090_r2						2.79	3.39	0.1	32338200	31433265	31492452	30733398	97.2	97.59	222952	215980	244.147	579.082	194	1151	39.56	40.64	231973	88209	231973	88209	39.83	39.09	231973	88804	231973	84835	18289435	56.56	1.26	0	2.42	0	0.13	0	0.22	0	0.00	0	8.61	0	222952	0	150	0	148.37	0	1.48	0	0.01	0	1.28	0	0.01	0	55.10	0	0.66	0	3096	0	244910	0	5920	0	329	0	540	0	0	0	21089	0	5	0	0	0	120	0	9463	0	289	0	9877	0	88.62	0	217032	0	3465	9658	2.787301587302	244910.0	222952.0	3096.0	5920.0	329.0	540.0	0.0	21089.0	217032.0	91.0	1.3	2.4	0.1	0.2	0.0	8.6	88.6	75	75	75.00	7	18368250	30.1	19.7	20.0	30.1	0.0	33.7	21.9	smartseq
1448029	SRR3639185	SRP076212	SRS1488588	SRX1826630	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189432: 1gg_BTN5_C61_IL4690-712-501_GTAGAGGA-TAGATCGC BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189432		GSM2189432	1gg_BTN5_C61_IL4690-712-501_GTAGAGGA-TAGATCGC BTN05 Mic-scRNA-Seq	438139414	2169007	2016-07-18 10:56:32	305054745	438139414	2169007	2	2169007	index:0,count:2169007,average:101,stdev:0|index:1,count:2169007,average:101,stdev:0	GSM2189432_r1						2.76	2.73	0.84	347585497	324920903	332464881	312082838	93.48	93.87	1925510	1848994	247.256	666.053	188	10174	62.59	65.49	2074607	1205147	2074607	1205147	63.97	63.78	2074607	1231809	2074607	1173731	99256348	28.56	1.01	0	3.93	0	0.25	0	0.20	0	0.00	0	10.78	0	1925510	0	202	0	198.82	0	1.48	0	0.01	0	1.23	0	0.01	0	162.68	0	0.75	0	21841	0	2169007	0	85256	0	5318	0	4439	0	0	0	233740	0	62	0	0	0	1976	0	221307	0	2711	0	226056	0	84.84	0	1840254	0	4710	224992	47.769002123142	2169007.0	1925510.0	21841.0	85256.0	5318.0	4439.0	0.0	233740.0	1840254.0	88.8	1.0	3.9	0.2	0.2	0.0	10.8	84.8	101	101	101.00	38	219069707	27.4	22.1	22.4	28.1	0.0	34.2	17.2	smartseq
1448030	SRR3640185	SRP076212	SRS1489015	SRX1827057	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189859: C9_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189859		GSM2189859	C9_1000700602-OGC11-sal_1_12ul_1 OGC11-sal FACS-scRNA-Seq	62124750	414165	2016-07-18 10:56:32	23444435	62124750	414165	2	414165	index:0,count:414165,average:75,stdev:0|index:1,count:414165,average:75,stdev:0	GSM2189859_r4						0.96	2.31	0.05	51145653	56218053	48432173	53724435	109.92	110.93	381497	338701	216.672	1410.873	110	1899	77.81	82.46	412852	296842	412852	296842	67.89	68.57	412852	258998	412852	246821	7763148	15.18	1.77	0	5.20	0	0.30	0	0.16	0	0.00	0	7.43	0	381497	0	150	0	147.71	0	4.30	0	0.05	0	1.15	0	0.02	0	124.25	0	0.31	0	7315	0	414165	0	21521	0	1231	0	652	0	0	0	30785	0	83	0	0	0	553	0	82531	0	563	0	83730	0	86.92	0	359976	0	24830	79105	3.185863874346	414165.0	381497.0	7315.0	21521.0	1231.0	652.0	0.0	30785.0	359976.0	92.1	1.8	5.2	0.3	0.2	0.0	7.4	86.9	75	75	75.00	6	31062375	24.3	25.7	25.4	24.6	0.0	34.7	27.9	smartseq
1448031	SRR3641185	SRP076212	SRS1489270	SRX1827312	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190114: G9_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190114		GSM2190114	G9_1000700602-OGC11-sal_1_8ul_1 OGC11-sal FACS-scRNA-Seq	57193650	381291	2016-07-18 10:56:32	21706652	57193650	381291	2	381291	index:0,count:381291,average:75,stdev:0|index:1,count:381291,average:75,stdev:0	GSM2190114_r3						2.08	2.04	0.04	46186227	52502771	43386685	49957780	113.68	115.15	346964	322772	207.823	936.277	125	1861	78.87	84.32	376199	273665	376199	273665	65.05	65.87	376199	225714	376199	213770	5858243	12.68	2.36	0	5.88	0	0.22	0	0.15	0	0.00	0	8.64	0	346964	0	150	0	147.55	0	4.37	0	0.06	0	1.11	0	0.02	0	105.59	0	0.32	0	9005	0	381291	0	22410	0	821	0	577	0	0	0	32929	0	44	0	0	0	329	0	50132	0	939	0	51444	0	85.12	0	324554	0	15127	48073	3.177959939182	381291.0	346964.0	9005.0	22410.0	821.0	577.0	0.0	32929.0	324554.0	91.0	2.4	5.9	0.2	0.2	0.0	8.6	85.1	75	75	75.00	6	28596825	24.4	25.6	25.3	24.7	0.0	34.6	27.6	smartseq
1448046	SRR3638186	SRP076212	SRS1488246	SRX1826288	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189090: 1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189090		GSM2189090	1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq	35686500	237910	2016-07-18 10:56:32	16922307	35686500	237910	2	237910	index:0,count:237910,average:75,stdev:0|index:1,count:237910,average:75,stdev:0	GSM2189090_r3						2.72	3.32	0.09	31360894	30461985	30558513	29794782	97.13	97.5	216449	209771	239.593	574.480	194	1168	39.52	40.58	225041	85548	225041	85548	39.73	39.04	225041	85993	225041	82303	17730488	56.54	1.25	0	2.37	0	0.14	0	0.23	0	0.00	0	8.65	0	216449	0	150	0	148.36	0	1.50	0	0.01	0	1.32	0	0.01	0	45.08	0	0.68	0	2981	0	237910	0	5634	0	325	0	550	0	0	0	20586	0	3	0	0	0	91	0	9115	0	282	0	9491	0	88.61	0	210815	0	3434	9346	2.721607454863	237910.0	216449.0	2981.0	5634.0	325.0	550.0	0.0	20586.0	210815.0	91.0	1.3	2.4	0.1	0.2	0.0	8.7	88.6	75	75	75.00	7	17843250	30.2	19.8	20.0	30.0	0.0	33.5	21.8	smartseq
1448047	SRR3639186	SRP076212	SRS1488589	SRX1826631	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189433: 1gg_BTN5_C65_IL4690-706-503_TAGGCATG-TATCCTCT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189433		GSM2189433	1gg_BTN5_C65_IL4690-706-503_TAGGCATG-TATCCTCT BTN05 Mic-scRNA-Seq	613439054	3036827	2016-07-18 10:56:32	420441513	613439054	3036827	2	3036827	index:0,count:3036827,average:101,stdev:0|index:1,count:3036827,average:101,stdev:0	GSM2189433_r1						1.49	2.61	0.35	480513114	457767727	462757819	441808104	95.27	95.47	2672308	2529259	249.206	686.601	188	13331	65.25	67.81	2862961	1743594	2862961	1743594	65.85	65.63	2862961	1759840	2862961	1687592	131885607	27.45	0.99	0	3.32	0	0.48	0	0.08	0	0.00	0	11.45	0	2672308	0	202	0	198.37	0	1.55	0	0.01	0	1.22	0	0.01	0	168.19	0	0.89	0	30120	0	3036827	0	100827	0	14627	0	2314	0	0	0	347578	0	150	0	0	0	2161	0	401101	0	4107	0	407519	0	84.68	0	2571481	0	6778	403751	59.567866627324	3036827.0	2672308.0	30120.0	100827.0	14627.0	2314.0	0.0	347578.0	2571481.0	88.0	1.0	3.3	0.5	0.1	0.0	11.4	84.7	101	101	101.00	38	306719527	27.2	22.4	22.6	27.8	0.0	35.0	18.4	smartseq
1448062	SRR3638187	SRP076212	SRS1488246	SRX1826288	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189090: 1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189090		GSM2189090	1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq	35688300	237922	2016-07-18 10:56:32	16868172	35688300	237922	2	237922	index:0,count:237922,average:75,stdev:0|index:1,count:237922,average:75,stdev:0	GSM2189090_r4						2.7	3.33	0.12	31328126	30488830	30541319	29829831	97.32	97.67	216084	209361	242.368	581.337	182	1155	39.44	40.47	224577	85217	224577	85217	39.63	38.92	224577	85641	224577	81958	17819975	56.88	1.21	0	2.32	0	0.14	0	0.23	0	0.00	0	8.81	0	216084	0	150	0	148.37	0	1.48	0	0.01	0	1.28	0	0.01	0	57.10	0	0.69	0	2880	0	237922	0	5517	0	331	0	557	0	0	0	20950	0	5	0	0	0	93	0	9190	0	332	0	9620	0	88.50	0	210567	0	3444	9363	2.718641114983	237922.0	216084.0	2880.0	5517.0	331.0	557.0	0.0	20950.0	210567.0	90.8	1.2	2.3	0.1	0.2	0.0	8.8	88.5	75	75	75.00	7	17844150	30.1	19.7	20.0	30.1	0.0	33.6	21.7	smartseq
1448063	SRR3639187	SRP076212	SRS1488590	SRX1826632	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189434: 1gg_BTN5_C69_IL4690-703-502_AGGCAGAA-CTCTCTAT BTN05 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN05|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189434		GSM2189434	1gg_BTN5_C69_IL4690-703-502_AGGCAGAA-CTCTCTAT BTN05 Mic-scRNA-Seq	655224168	3243684	2016-07-18 10:56:32	444314482	655224168	3243684	2	3243684	index:0,count:3243684,average:101,stdev:0|index:1,count:3243684,average:101,stdev:0	GSM2189434_r1						2.49	3.74	0.85	487879673	445273153	463306913	425306445	91.27	91.8	2757978	2619412	235.499	622.579	169	14953	69.02	72.78	3012896	1903627	3012896	1903627	69.94	69.98	3012896	1928931	3012896	1830465	86318059	17.69	1.09	0	4.39	0	0.27	0	0.06	0	0.00	0	14.64	0	2757978	0	202	0	197.89	0	1.67	0	0.01	0	1.26	0	0.01	0	191.43	0	0.93	0	35241	0	3243684	0	142251	0	8673	0	2001	0	0	0	475032	0	451	0	0	0	2563	0	427841	0	4010	0	434865	0	80.64	0	2615727	0	5885	431901	73.390144435004	3243684.0	2757978.0	35241.0	142251.0	8673.0	2001.0	0.0	475032.0	2615727.0	85.0	1.1	4.4	0.3	0.1	0.0	14.6	80.6	101	101	101.00	38	327612084	26.9	22.7	22.8	27.5	0.0	35.0	18.6	smartseq
1448079	SRR3638188	SRP076212	SRS1488246	SRX1826288	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189090: 1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189090		GSM2189090	1-0-1-1-BTN27-C36-1771026164-IL5326-710-504 BTN27 Mic-scRNA-Seq	145755300	971702	2016-07-18 10:56:32	68700407	145755300	971702	2	971702	index:0,count:971702,average:75,stdev:0|index:1,count:971702,average:75,stdev:0	GSM2189090_r5						2.73	3.33	0.11	128094885	124559691	124823769	121839603	97.24	97.61	883604	856252	242.120	577.909	193	4603	39.46	40.51	918722	348674	918722	348674	39.67	38.96	918722	350548	918722	335309	72670137	56.73	1.25	0	2.36	0	0.14	0	0.23	0	0.00	0	8.70	0	883604	0	150	0	148.37	0	1.49	0	0.01	0	1.28	0	0.01	0	218.63	0	0.67	0	12101	0	971702	0	22933	0	1367	0	2199	0	0	0	84532	0	18	0	0	0	423	0	37615	0	1240	0	39296	0	88.57	0	860671	0	5996	39143	6.528185456971	971702.0	883604.0	12101.0	22933.0	1367.0	2199.0	0.0	84532.0	860671.0	90.9	1.2	2.4	0.1	0.2	0.0	8.7	88.6	75	75	75.00	7	72877650	30.1	19.7	20.0	30.1	0.0	33.6	21.8	smartseq
1448095	SRR3638189	SRP076212	SRS1488247	SRX1826289	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189091: 1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189091		GSM2189091	1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq	55384050	369227	2016-07-18 10:56:32	26013613	55384050	369227	2	369227	index:0,count:369227,average:75,stdev:0|index:1,count:369227,average:75,stdev:0	GSM2189091_r1						4.64	3.52	0.08	48883773	47683475	46891024	46021067	97.54	98.14	335909	321109	259.218	705.394	198	1631	48.91	51.01	356209	164305	356209	164305	50.29	49.35	356209	168941	356209	158961	22458438	45.94	1.30	0	3.74	0	0.13	0	0.29	0	0.00	0	8.60	0	335909	0	150	0	148.31	0	1.42	0	0.01	0	1.24	0	0.01	0	78.19	0	0.65	0	4801	0	369227	0	13794	0	483	0	1065	0	0	0	31770	0	21	0	0	0	178	0	18570	0	378	0	19147	0	87.24	0	322115	0	6052	19168	3.167217448777	369227.0	335909.0	4801.0	13794.0	483.0	1065.0	0.0	31770.0	322115.0	91.0	1.3	3.7	0.1	0.3	0.0	8.6	87.2	75	75	75.00	7	27692025	30.6	19.5	19.7	30.1	0.0	33.6	21.8	smartseq
1448207	SRR3638190	SRP076212	SRS1488247	SRX1826289	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189091: 1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189091		GSM2189091	1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq	53974350	359829	2016-07-18 10:56:32	25141231	53974350	359829	2	359829	index:0,count:359829,average:75,stdev:0|index:1,count:359829,average:75,stdev:0	GSM2189091_r2						4.63	3.6	0.08	47665141	46535540	45698705	44905477	97.63	98.26	327430	313055	260.110	702.615	209	1537	48.96	51.08	347363	160300	347363	160300	50.33	49.38	347363	164782	347363	154952	21893640	45.93	1.30	0	3.78	0	0.15	0	0.29	0	0.00	0	8.57	0	327430	0	150	0	148.35	0	1.39	0	0.01	0	1.28	0	0.01	0	86.36	0	0.63	0	4678	0	359829	0	13615	0	532	0	1046	0	0	0	30821	0	19	0	0	0	179	0	18337	0	403	0	18938	0	87.21	0	313815	0	6036	18831	3.119781312127	359829.0	327430.0	4678.0	13615.0	532.0	1046.0	0.0	30821.0	313815.0	91.0	1.3	3.8	0.1	0.3	0.0	8.6	87.2	75	75	75.00	7	26987175	30.6	19.5	19.7	30.2	0.0	33.6	21.8	smartseq
1448221	SRR3638191	SRP076212	SRS1488247	SRX1826289	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189091: 1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189091		GSM2189091	1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq	54851400	365676	2016-07-18 10:56:32	25787130	54851400	365676	2	365676	index:0,count:365676,average:75,stdev:0|index:1,count:365676,average:75,stdev:0	GSM2189091_r3						4.62	3.55	0.08	48446446	47252781	46481717	45624342	97.54	98.16	332787	318151	260.247	723.628	188	1615	48.94	51.03	352820	162880	352820	162880	50.32	49.39	352820	167466	352820	157644	22268492	45.97	1.27	0	3.72	0	0.14	0	0.29	0	0.00	0	8.56	0	332787	0	150	0	148.33	0	1.40	0	0.01	0	1.24	0	0.01	0	73.14	0	0.64	0	4651	0	365676	0	13604	0	521	0	1077	0	0	0	31291	0	24	0	0	0	211	0	18418	0	445	0	19098	0	87.29	0	319183	0	6122	19041	3.110258085593	365676.0	332787.0	4651.0	13604.0	521.0	1077.0	0.0	31291.0	319183.0	91.0	1.3	3.7	0.1	0.3	0.0	8.6	87.3	75	75	75.00	7	27425700	30.6	19.5	19.7	30.1	0.0	33.6	21.8	smartseq
1448222	SRR3639191	SRP076212	SRS1488593	SRX1826636	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189438: 1gg_BTN6_C31_IL4690-703-505_AGGCAGAA-GTAAGGAG BTN06 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN06|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189438		GSM2189438	1gg_BTN6_C31_IL4690-703-505_AGGCAGAA-GTAAGGAG BTN06 Mic-scRNA-Seq	716156660	3545330	2016-07-18 10:56:32	487885987	716156660	3545330	2	3545330	index:0,count:3545330,average:101,stdev:0|index:1,count:3545330,average:101,stdev:0	GSM2189438_r1						2.56	2.53	0.02	546192399	537137603	531362774	524609839	98.34	98.73	3069411	2974522	235.892	595.251	188	16728	61.24	63.0	3206289	1879812	3206289	1879812	60.88	60.59	3206289	1868761	3206289	1808038	189935255	34.77	0.92	0	2.41	0	0.18	0	0.15	0	0.00	0	13.09	0	3069411	0	202	0	198.38	0	1.63	0	0.01	0	1.29	0	0.01	0	220.05	0	0.91	0	32440	0	3545330	0	85444	0	6452	0	5393	0	0	0	464074	0	46	0	0	0	2291	0	271414	0	4215	0	277966	0	84.17	0	2983967	0	4674	269800	57.723577235772	3545330.0	3069411.0	32440.0	85444.0	6452.0	5393.0	0.0	464074.0	2983967.0	86.6	0.9	2.4	0.2	0.2	0.0	13.1	84.2	101	101	101.00	38	358078330	27.5	22.1	22.2	28.1	0.0	35.2	18.9	smartseq
1448223	SRR3640191	SRP076212	SRS1489017	SRX1827059	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189861: C9_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189861		GSM2189861	C9_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	49267350	328449	2016-07-18 10:56:32	18449773	49267350	328449	2	328449	index:0,count:328449,average:75,stdev:0|index:1,count:328449,average:75,stdev:0	GSM2189861_r2						1.54	2.44	0.02	42265962	46531973	39551400	44050795	110.09	111.38	305877	266640	240.852	1596.112	144	1407	80.08	85.85	335228	244949	335228	244949	70.54	71.38	335228	215773	335228	203676	4817748	11.40	1.58	0	6.26	0	0.34	0	0.15	0	0.00	0	6.38	0	305877	0	150	0	148.02	0	4.47	0	0.06	0	1.08	0	0.02	0	98.53	0	0.30	0	5184	0	328449	0	20554	0	1106	0	504	0	0	0	20962	0	57	0	0	0	415	0	64928	0	455	0	65855	0	86.87	0	285323	0	22210	63528	2.860333183251	328449.0	305877.0	5184.0	20554.0	1106.0	504.0	0.0	20962.0	285323.0	93.1	1.6	6.3	0.3	0.2	0.0	6.4	86.9	75	75	75.00	6	24633675	24.6	25.2	25.2	24.9	0.0	34.8	28.2	smartseq
1448238	SRR3638192	SRP076212	SRS1488247	SRX1826289	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189091: 1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189091		GSM2189091	1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq	52184700	347898	2016-07-18 10:56:32	24518161	52184700	347898	2	347898	index:0,count:347898,average:75,stdev:0|index:1,count:347898,average:75,stdev:0	GSM2189091_r4						4.6	3.6	0.08	45954630	44847029	44088812	43300284	97.59	98.21	315808	301858	259.322	689.056	188	1493	49.12	51.21	334343	155121	334343	155121	50.48	49.54	334343	159405	334343	150063	21062254	45.83	1.27	0	3.71	0	0.14	0	0.29	0	0.00	0	8.79	0	315808	0	150	0	148.30	0	1.41	0	0.01	0	1.24	0	0.01	0	83.50	0	0.66	0	4426	0	347898	0	12897	0	492	0	1003	0	0	0	30595	0	17	0	0	0	181	0	17380	0	387	0	17965	0	87.07	0	302911	0	5797	17875	3.083491461101	347898.0	315808.0	4426.0	12897.0	492.0	1003.0	0.0	30595.0	302911.0	90.8	1.3	3.7	0.1	0.3	0.0	8.8	87.1	75	75	75.00	7	26092350	30.7	19.5	19.7	30.1	0.0	33.5	21.7	smartseq
1448239	SRR3639192	SRP076212	SRS1488595	SRX1826637	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189439: 1gg_BTN6_C36_IL4690-707-506_CTCTCTAC-ACTGCATA BTN06 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN06|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189439		GSM2189439	1gg_BTN6_C36_IL4690-707-506_CTCTCTAC-ACTGCATA BTN06 Mic-scRNA-Seq	741491096	3670748	2016-07-18 10:56:32	505705584	741491096	3670748	2	3670748	index:0,count:3670748,average:101,stdev:0|index:1,count:3670748,average:101,stdev:0	GSM2189439_r1						0.64	3.45	0.01	554327740	533578982	536650367	519028932	96.26	96.72	3137419	2899477	231.120	860.812	174	17326	79.94	82.64	3322379	2508126	3322379	2508126	79.64	80.02	3322379	2498597	3322379	2428738	71453851	12.89	0.92	0	2.79	0	0.19	0	0.02	0	0.00	0	14.31	0	3137419	0	202	0	197.99	0	1.74	0	0.01	0	1.26	0	0.01	0	181.02	0	0.91	0	33647	0	3670748	0	102372	0	7154	0	767	0	0	0	525408	0	335	0	0	0	5238	0	686343	0	5576	0	697492	0	82.68	0	3035047	0	10245	680769	66.448901903367	3670748.0	3137419.0	33647.0	102372.0	7154.0	767.0	0.0	525408.0	3035047.0	85.5	0.9	2.8	0.2	0.0	0.0	14.3	82.7	101	101	101.00	38	370745548	27.0	22.7	22.7	27.6	0.0	34.9	18.4	smartseq
1448254	SRR3638193	SRP076212	SRS1488247	SRX1826289	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189091: 1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN27|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189091		GSM2189091	1-0-1-1-BTN27-C71-1771026164-IL5326-709-508 BTN27 Mic-scRNA-Seq	216394500	1442630	2016-07-18 10:56:32	101366166	216394500	1442630	2	1442630	index:0,count:1442630,average:75,stdev:0|index:1,count:1442630,average:75,stdev:0	GSM2189091_r5						4.62	3.56	0.08	190949990	186318825	183160258	179851170	97.57	98.19	1311934	1254173	259.727	705.393	188	6133	48.98	51.08	1390735	642606	1390735	642606	50.35	49.41	1390735	660594	1390735	621620	87682824	45.92	1.29	0	3.74	0	0.14	0	0.29	0	0.00	0	8.63	0	1311934	0	150	0	148.32	0	1.41	0	0.01	0	1.25	0	0.01	0	185.48	0	0.65	0	18556	0	1442630	0	53910	0	2028	0	4191	0	0	0	124477	0	81	0	0	0	749	0	72705	0	1613	0	75148	0	87.20	0	1258024	0	10252	75816	7.395239953180	1442630.0	1311934.0	18556.0	53910.0	2028.0	4191.0	0.0	124477.0	1258024.0	90.9	1.3	3.7	0.1	0.3	0.0	8.6	87.2	75	75	75.00	7	108197250	30.6	19.5	19.7	30.1	0.0	33.6	21.8	smartseq
1448255	SRR3639193	SRP076212	SRS1488596	SRX1826638	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189440: 1gg_BTN6_C39_IL4690-706-505_TAGGCATG-GTAAGGAG BTN06 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN06|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189440		GSM2189440	1gg_BTN6_C39_IL4690-706-505_TAGGCATG-GTAAGGAG BTN06 Mic-scRNA-Seq	653277494	3234047	2016-07-18 10:56:32	445611041	653277494	3234047	2	3234047	index:0,count:3234047,average:101,stdev:0|index:1,count:3234047,average:101,stdev:0	GSM2189440_r1						1.12	3.09	0.02	493986895	462486764	484269384	455282840	93.62	94.01	2753398	2671212	242.916	647.378	188	14344	53.6	54.71	2855365	1475945	2855365	1475945	52.82	52.82	2855365	1454225	2855365	1425055	194717525	39.42	0.95	0	1.72	0	0.15	0	0.13	0	0.00	0	14.58	0	2753398	0	202	0	198.49	0	1.68	0	0.01	0	1.36	0	0.01	0	173.77	0	0.93	0	30746	0	3234047	0	55628	0	4811	0	4177	0	0	0	471661	0	197	0	0	0	1777	0	209316	0	4534	0	215824	0	83.42	0	2697770	0	5013	211283	42.147017753840	3234047.0	2753398.0	30746.0	55628.0	4811.0	4177.0	0.0	471661.0	2697770.0	85.1	1.0	1.7	0.1	0.1	0.0	14.6	83.4	101	101	101.00	38	326638747	27.8	21.8	21.9	28.6	0.0	35.0	18.1	smartseq
1448270	SRR3638194	SRP076212	SRS1488248	SRX1826290	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189092: 1-0-1-1-BTN34-C38-1782070111-46ul-1-IL5413-N701-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189092		GSM2189092	1-0-1-1-BTN34-C38-1782070111-46ul-1-IL5413-N701-N504 BTN34 Mic-scRNA-Seq	40706400	271376	2016-07-18 10:56:32	19896064	40706400	271376	2	271376	index:0,count:271376,average:75,stdev:0|index:1,count:271376,average:75,stdev:0	GSM2189092_r1						2.09	3.38	0.06	34559444	33644354	32889197	32205005	97.35	97.92	244309	224029	229.486	1129.185	182	1164	61.67	64.85	263612	150654	263612	150654	63.28	62.66	263612	154589	263612	145567	10960604	31.72	1.03	0	4.43	0	0.22	0	0.15	0	0.00	0	9.60	0	244309	0	150	0	147.97	0	1.47	0	0.01	0	1.16	0	0.00	0	51.42	0	0.90	0	2797	0	271376	0	12013	0	610	0	418	0	0	0	26039	0	17	0	0	0	211	0	30002	0	234	0	30464	0	85.60	0	232296	0	14233	30139	2.117543736387	271376.0	244309.0	2797.0	12013.0	610.0	418.0	0.0	26039.0	232296.0	90.0	1.0	4.4	0.2	0.2	0.0	9.6	85.6	75	75	75.00	7	20353200	28.8	21.4	21.7	28.0	0.0	33.2	21.4	smartseq
1448271	SRR3639194	SRP076212	SRS1488597	SRX1826639	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189441: 1gg_BTN6_C41_IL4690-704-506_TCCTGAGC-ACTGCATA BTN06 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN06|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189441		GSM2189441	1gg_BTN6_C41_IL4690-704-506_TCCTGAGC-ACTGCATA BTN06 Mic-scRNA-Seq	679545776	3364088	2016-07-18 10:56:32	463021413	679545776	3364088	2	3364088	index:0,count:3364088,average:101,stdev:0|index:1,count:3364088,average:101,stdev:0	GSM2189441_r1						2.56	2.74	0.02	509245096	505585612	494474050	492993870	99.28	99.7	2854998	2746088	239.177	648.522	180	15045	65.03	67.02	2973467	1856588	2973467	1856588	64.61	64.32	2973467	1844497	2973467	1781975	158487086	31.12	0.91	0	2.52	0	0.10	0	0.13	0	0.00	0	14.90	0	2854998	0	202	0	198.33	0	1.66	0	0.01	0	1.51	0	0.01	0	186.32	0	0.90	0	30458	0	3364088	0	84607	0	3293	0	4474	0	0	0	501323	0	6	0	0	0	2575	0	302350	0	3682	0	308613	0	82.35	0	2770391	0	5464	298770	54.679721815520	3364088.0	2854998.0	30458.0	84607.0	3293.0	4474.0	0.0	501323.0	2770391.0	84.9	0.9	2.5	0.1	0.1	0.0	14.9	82.4	101	101	101.00	38	339772888	27.5	22.2	22.3	28.1	0.0	35.0	18.4	smartseq
1448285	SRR3638195	SRP076212	SRS1488248	SRX1826290	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189092: 1-0-1-1-BTN34-C38-1782070111-46ul-1-IL5413-N701-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189092		GSM2189092	1-0-1-1-BTN34-C38-1782070111-46ul-1-IL5413-N701-N504 BTN34 Mic-scRNA-Seq	40533600	270224	2016-07-18 10:56:32	19777565	40533600	270224	2	270224	index:0,count:270224,average:75,stdev:0|index:1,count:270224,average:75,stdev:0	GSM2189092_r2						2.1	3.29	0.06	34506485	33582728	32854104	32155649	97.32	97.87	243714	222819	231.566	1112.448	198	1147	61.89	65.07	263199	150830	263199	150830	63.52	62.91	263199	154796	263199	145839	10891780	31.56	1.01	0	4.41	0	0.24	0	0.16	0	0.00	0	9.41	0	243714	0	150	0	147.99	0	1.44	0	0.01	0	1.16	0	0.00	0	48.64	0	0.91	0	2739	0	270224	0	11910	0	661	0	431	0	0	0	25418	0	25	0	0	0	221	0	30174	0	260	0	30680	0	85.78	0	231804	0	14450	30402	2.103944636678	270224.0	243714.0	2739.0	11910.0	661.0	431.0	0.0	25418.0	231804.0	90.2	1.0	4.4	0.2	0.2	0.0	9.4	85.8	75	75	75.00	7	20266800	28.8	21.5	21.7	28.0	0.0	33.3	21.5	smartseq
1448286	SRR3639195	SRP076212	SRS1488598	SRX1826640	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189442: 1gg_BTN6_C46_IL4690-703-506_AGGCAGAA-ACTGCATA BTN06 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN06|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189442		GSM2189442	1gg_BTN6_C46_IL4690-703-506_AGGCAGAA-ACTGCATA BTN06 Mic-scRNA-Seq	668080660	3307330	2016-07-18 10:56:32	452225847	668080660	3307330	2	3307330	index:0,count:3307330,average:101,stdev:0|index:1,count:3307330,average:101,stdev:0	GSM2189442_r1						2.55	4.03	0.03	498642058	478373973	484804158	467850337	95.94	96.5	2796051	2742485	238.282	558.333	174	14783	45.67	47.0	2931465	1277056	2931465	1277056	45.33	44.92	2931465	1267411	2931465	1220608	244488848	49.03	1.17	0	2.38	0	0.15	0	0.15	0	0.00	0	15.15	0	2796051	0	202	0	198.38	0	1.70	0	0.01	0	1.47	0	0.01	0	170.09	0	0.91	0	38791	0	3307330	0	78869	0	5088	0	5003	0	0	0	501188	0	158	0	0	0	1321	0	139236	0	4559	0	145274	0	82.16	0	2717182	0	4930	139118	28.218661257606	3307330.0	2796051.0	38791.0	78869.0	5088.0	5003.0	0.0	501188.0	2717182.0	84.5	1.2	2.4	0.2	0.2	0.0	15.2	82.2	101	101	101.00	38	334040330	28.0	21.5	21.7	28.8	0.0	35.2	18.2	smartseq
1448287	SRR3640195	SRP076212	SRS1489019	SRX1827061	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189863: D10_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189863		GSM2189863	D10_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	54830850	365539	2016-07-18 10:56:32	23162918	54830850	365539	2	365539	index:0,count:365539,average:75,stdev:0|index:1,count:365539,average:75,stdev:0	GSM2189863_r1						2.35	2.26	0.05	43771833	48911314	40564126	46022768	111.74	113.46	320599	293655	221.687	1261.017	174	1611	74.61	80.86	355452	239192	355452	239192	63.12	63.87	355452	202372	355452	188929	6943888	15.86	2.35	0	6.78	0	0.21	0	0.16	0	0.00	0	11.92	0	320599	0	150	0	147.21	0	4.88	0	0.10	0	1.09	0	0.03	0	94.00	0	0.50	0	8572	0	365539	0	24789	0	761	0	598	0	0	0	43581	0	28	0	0	0	285	0	46528	0	490	0	47331	0	80.92	0	295810	0	17163	45447	2.647963642720	365539.0	320599.0	8572.0	24789.0	761.0	598.0	0.0	43581.0	295810.0	87.7	2.3	6.8	0.2	0.2	0.0	11.9	80.9	75	75	75.00	6	27415425	25.0	24.7	24.8	25.5	0.0	33.7	25.2	smartseq
1448302	SRR3638196	SRP076212	SRS1488248	SRX1826290	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189092: 1-0-1-1-BTN34-C38-1782070111-46ul-1-IL5413-N701-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189092		GSM2189092	1-0-1-1-BTN34-C38-1782070111-46ul-1-IL5413-N701-N504 BTN34 Mic-scRNA-Seq	39132000	260880	2016-07-18 10:56:32	19177466	39132000	260880	2	260880	index:0,count:260880,average:75,stdev:0|index:1,count:260880,average:75,stdev:0	GSM2189092_r3						2.03	3.38	0.07	33122491	32251311	31523848	30870974	97.37	97.93	234491	215276	227.159	1115.897	207	1116	61.75	64.94	253100	144789	253100	144789	63.35	62.74	253100	148550	253100	139878	10494966	31.69	1.01	0	4.43	0	0.25	0	0.15	0	0.00	0	9.72	0	234491	0	150	0	147.97	0	1.46	0	0.01	0	1.17	0	0.00	0	44.72	0	0.92	0	2641	0	260880	0	11547	0	665	0	379	0	0	0	25345	0	16	0	0	0	213	0	28737	0	212	0	29178	0	85.46	0	222944	0	13831	28895	2.089147567060	260880.0	234491.0	2641.0	11547.0	665.0	379.0	0.0	25345.0	222944.0	89.9	1.0	4.4	0.3	0.1	0.0	9.7	85.5	75	75	75.00	7	19566000	28.8	21.5	21.7	28.0	0.0	33.2	21.4	smartseq
1448303	SRR3639196	SRP076212	SRS1488599	SRX1826641	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189443: 1gg_BTN6_C59_IL4690-712-506_GTAGAGGA-ACTGCATA BTN06 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN06|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189443		GSM2189443	1gg_BTN6_C59_IL4690-712-506_GTAGAGGA-ACTGCATA BTN06 Mic-scRNA-Seq	582408420	2883210	2016-07-18 10:56:32	396681809	582408420	2883210	2	2883210	index:0,count:2883210,average:101,stdev:0|index:1,count:2883210,average:101,stdev:0	GSM2189443_r1						2.98	4.29	0.01	440856593	401414751	422522673	386483760	91.05	91.47	2447555	2296361	251.804	862.357	188	12515	67.27	70.23	2625269	1646400	2625269	1646400	68.49	68.25	2625269	1676222	2625269	1599793	90935031	20.63	0.89	0	3.59	0	0.35	0	0.05	0	0.00	0	14.71	0	2447555	0	202	0	198.20	0	1.60	0	0.01	0	1.36	0	0.01	0	199.61	0	0.93	0	25723	0	2883210	0	103381	0	9962	0	1580	0	0	0	424113	0	208	0	0	0	2401	0	381162	0	3347	0	387118	0	81.30	0	2344174	0	6910	382280	55.322720694645	2883210.0	2447555.0	25723.0	103381.0	9962.0	1580.0	0.0	424113.0	2344174.0	84.9	0.9	3.6	0.3	0.1	0.0	14.7	81.3	101	101	101.00	38	291204210	27.2	22.4	22.5	27.9	0.0	34.9	18.3	smartseq
1448351	SRR3638199	SRP076212	SRS1488249	SRX1826291	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189093: 1-0-1-1-BTN34-C39-1782070111-30ul-1-IL5413-N702-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189093		GSM2189093	1-0-1-1-BTN34-C39-1782070111-30ul-1-IL5413-N702-N504 BTN34 Mic-scRNA-Seq	37717050	251447	2016-07-18 10:56:32	18226472	37717050	251447	2	251447	index:0,count:251447,average:75,stdev:0|index:1,count:251447,average:75,stdev:0	GSM2189093_r2						2.48	3.63	0.08	31457284	30308947	29872011	28957297	96.35	96.94	225861	211236	218.816	956.694	176	1086	58.1	61.24	245050	131230	245050	131230	60.12	59.33	245050	135778	245050	127146	10824176	34.41	1.06	0	4.60	0	0.25	0	0.18	0	0.00	0	9.74	0	225861	0	150	0	147.92	0	1.40	0	0.01	0	1.13	0	0.00	0	56.58	0	0.85	0	2661	0	251447	0	11564	0	640	0	457	0	0	0	24489	0	19	0	0	0	157	0	21709	0	216	0	22101	0	85.23	0	214297	0	11476	21762	1.896305332869	251447.0	225861.0	2661.0	11564.0	640.0	457.0	0.0	24489.0	214297.0	89.8	1.1	4.6	0.3	0.2	0.0	9.7	85.2	75	75	75.00	7	18858525	29.6	20.6	20.8	29.0	0.0	33.4	21.7	smartseq
1449999	SRR3638200	SRP076212	SRS1488249	SRX1826291	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189093: 1-0-1-1-BTN34-C39-1782070111-30ul-1-IL5413-N702-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189093		GSM2189093	1-0-1-1-BTN34-C39-1782070111-30ul-1-IL5413-N702-N504 BTN34 Mic-scRNA-Seq	36863250	245755	2016-07-18 10:56:32	17888623	36863250	245755	2	245755	index:0,count:245755,average:75,stdev:0|index:1,count:245755,average:75,stdev:0	GSM2189093_r3						2.55	3.56	0.11	30563734	29444015	29003633	28116677	96.34	96.94	219947	206016	215.667	967.901	179	1075	58.1	61.28	238645	127800	238645	127800	60.16	59.38	238645	132331	238645	123829	10489168	34.32	1.08	0	4.64	0	0.24	0	0.17	0	0.00	0	10.09	0	219947	0	150	0	147.90	0	1.44	0	0.01	0	1.13	0	0.00	0	42.13	0	0.87	0	2646	0	245755	0	11412	0	601	0	420	0	0	0	24787	0	22	0	0	0	156	0	21095	0	225	0	21498	0	84.85	0	208535	0	11259	21031	1.867927879918	245755.0	219947.0	2646.0	11412.0	601.0	420.0	0.0	24787.0	208535.0	89.5	1.1	4.6	0.2	0.2	0.0	10.1	84.9	75	75	75.00	7	18431625	29.6	20.7	20.7	28.9	0.0	33.3	21.6	smartseq
1450014	SRR3638201	SRP076212	SRS1488249	SRX1826291	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189093: 1-0-1-1-BTN34-C39-1782070111-30ul-1-IL5413-N702-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189093		GSM2189093	1-0-1-1-BTN34-C39-1782070111-30ul-1-IL5413-N702-N504 BTN34 Mic-scRNA-Seq	39928050	266187	2016-07-18 10:56:32	19134005	39928050	266187	2	266187	index:0,count:266187,average:75,stdev:0|index:1,count:266187,average:75,stdev:0	GSM2189093_r4						2.51	3.58	0.07	33268238	32080781	31632677	30685123	96.43	97.0	238374	222383	222.758	984.984	193	1095	58.27	61.34	258186	138900	258186	138900	60.22	59.45	258186	143556	258186	134618	11457128	34.44	1.07	0	4.49	0	0.26	0	0.21	0	0.00	0	9.98	0	238374	0	150	0	147.95	0	1.33	0	0.01	0	1.13	0	0.00	0	50.44	0	0.79	0	2842	0	266187	0	11943	0	686	0	567	0	0	0	26560	0	27	0	0	0	178	0	23489	0	217	0	23911	0	85.06	0	226431	0	12111	23526	1.942531582859	266187.0	238374.0	2842.0	11943.0	686.0	567.0	0.0	26560.0	226431.0	89.6	1.1	4.5	0.3	0.2	0.0	10.0	85.1	75	75	75.00	7	19964025	29.6	20.7	20.8	28.9	0.0	33.7	22.0	smartseq
1450015	SRR3639201	SRP076212	SRS1488604	SRX1826646	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189448: 1gg_BTN6_C82_IL4690-701-507_TAAGGCGA-AAGGAGTA BTN06 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN06|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189448		GSM2189448	1gg_BTN6_C82_IL4690-701-507_TAAGGCGA-AAGGAGTA BTN06 Mic-scRNA-Seq	595601444	2948522	2016-07-18 10:56:32	408707281	595601444	2948522	2	2948522	index:0,count:2948522,average:101,stdev:0|index:1,count:2948522,average:101,stdev:0	GSM2189448_r1						1.66	3.09	0.02	478050779	458332329	466535638	449040775	95.88	96.25	2654208	2562070	246.070	656.687	188	13505	49.77	51.03	2764280	1321036	2764280	1321036	48.87	48.59	2764280	1297200	2764280	1257981	213929898	44.75	0.94	0	2.21	0	0.17	0	0.17	0	0.00	0	9.64	0	2654208	0	202	0	199.20	0	1.61	0	0.01	0	1.38	0	0.01	0	163.30	0	0.78	0	27759	0	2948522	0	65303	0	4897	0	5073	0	0	0	284344	0	18	0	0	0	1810	0	238111	0	4216	0	244155	0	87.80	0	2588905	0	7148	237671	33.250000000000	2948522.0	2654208.0	27759.0	65303.0	4897.0	5073.0	0.0	284344.0	2588905.0	90.0	0.9	2.2	0.2	0.2	0.0	9.6	87.8	101	101	101.00	38	297800722	27.9	21.7	21.9	28.5	0.0	35.4	19.1	smartseq
1450031	SRR3638202	SRP076212	SRS1488250	SRX1826292	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189094: 1-0-1-1-BTN34-C41-1782070111-30ul-1-IL5413-N703-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189094		GSM2189094	1-0-1-1-BTN34-C41-1782070111-30ul-1-IL5413-N703-N504 BTN34 Mic-scRNA-Seq	46180050	307867	2016-07-18 10:56:32	22226365	46180050	307867	2	307867	index:0,count:307867,average:75,stdev:0|index:1,count:307867,average:75,stdev:0	GSM2189094_r1						10.06	2.96	0.11	36131025	34532217	32670340	31473473	95.57	96.34	268343	259170	191.763	651.954	156	1412	49.9	55.16	301725	133907	301725	133907	56.3	53.33	301725	151078	301725	129471	13480238	37.31	1.37	0	8.30	0	0.17	0	0.24	0	0.00	0	12.43	0	268343	0	150	0	147.33	0	1.40	0	0.01	0	1.17	0	0.01	0	65.20	0	0.80	0	4230	0	307867	0	25560	0	516	0	739	0	0	0	38269	0	20	0	0	0	88	0	14611	0	234	0	14953	0	78.86	0	242783	0	8371	14460	1.727392187313	307867.0	268343.0	4230.0	25560.0	516.0	739.0	0.0	38269.0	242783.0	87.2	1.4	8.3	0.2	0.2	0.0	12.4	78.9	75	75	75.00	7	23090025	31.5	19.0	18.9	30.6	0.0	33.3	21.5	smartseq
1450047	SRR3638203	SRP076212	SRS1488250	SRX1826292	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189094: 1-0-1-1-BTN34-C41-1782070111-30ul-1-IL5413-N703-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189094		GSM2189094	1-0-1-1-BTN34-C41-1782070111-30ul-1-IL5413-N703-N504 BTN34 Mic-scRNA-Seq	45298200	301988	2016-07-18 10:56:32	21738928	45298200	301988	2	301988	index:0,count:301988,average:75,stdev:0|index:1,count:301988,average:75,stdev:0	GSM2189094_r2						10.03	2.88	0.12	35682332	34117435	32273827	31100506	95.61	96.36	264552	254965	193.917	695.174	151	1334	50.1	55.37	297583	132532	297583	132532	56.5	53.59	297583	149476	297583	128269	13255144	37.15	1.43	0	8.34	0	0.16	0	0.24	0	0.00	0	12.00	0	264552	0	150	0	147.37	0	1.37	0	0.01	0	1.14	0	0.00	0	51.77	0	0.79	0	4307	0	301988	0	25183	0	492	0	717	0	0	0	36227	0	17	0	0	0	88	0	14827	0	268	0	15200	0	79.26	0	239369	0	8400	14629	1.741547619048	301988.0	264552.0	4307.0	25183.0	492.0	717.0	0.0	36227.0	239369.0	87.6	1.4	8.3	0.2	0.2	0.0	12.0	79.3	75	75	75.00	7	22649100	31.4	19.0	19.0	30.6	0.0	33.4	21.7	smartseq
1450062	SRR3638204	SRP076212	SRS1488250	SRX1826292	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189094: 1-0-1-1-BTN34-C41-1782070111-30ul-1-IL5413-N703-N504 BTN34 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN34|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189094		GSM2189094	1-0-1-1-BTN34-C41-1782070111-30ul-1-IL5413-N703-N504 BTN34 Mic-scRNA-Seq	44812650	298751	2016-07-18 10:56:32	21632838	44812650	298751	2	298751	index:0,count:298751,average:75,stdev:0|index:1,count:298751,average:75,stdev:0	GSM2189094_r3						10.07	2.92	0.12	35014132	33474934	31670758	30516975	95.6	96.36	260281	251252	190.931	675.134	174	1376	49.92	55.16	292380	129922	292380	129922	56.28	53.34	292380	146497	292380	125639	13058686	37.30	1.38	0	8.28	0	0.16	0	0.24	0	0.00	0	12.48	0	260281	0	150	0	147.34	0	1.39	0	0.01	0	1.17	0	0.00	0	56.61	0	0.82	0	4129	0	298751	0	24725	0	481	0	703	0	0	0	37286	0	11	0	0	0	89	0	14154	0	279	0	14533	0	78.85	0	235556	0	8136	13987	1.719149459194	298751.0	260281.0	4129.0	24725.0	481.0	703.0	0.0	37286.0	235556.0	87.1	1.4	8.3	0.2	0.2	0.0	12.5	78.8	75	75	75.00	7	22406325	31.5	19.0	18.9	30.5	0.0	33.3	21.5	smartseq
1450063	SRR3639204	SRP076212	SRS1488607	SRX1826649	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189451: 1gg_BTN7_C32_IL4709-702-506_CGTACTAG-ACTGCATA BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189451		GSM2189451	1gg_BTN7_C32_IL4709-702-506_CGTACTAG-ACTGCATA BTN07 Mic-scRNA-Seq	475091274	2351937	2016-07-18 10:56:32	323571441	475091274	2351937	2	2351937	index:0,count:2351937,average:101,stdev:0|index:1,count:2351937,average:101,stdev:0	GSM2189451_r1						1.92	2.44	0.67	361321426	339996002	340376158	321300354	94.1	94.4	2019964	1878439	245.455	758.144	174	10152	70.87	75.31	2230115	1431484	2230115	1431484	72.5	72.39	2230115	1464562	2230115	1375948	64555321	17.87	1.17	0	5.07	0	0.55	0	0.09	0	0.00	0	13.48	0	2019964	0	202	0	198.04	0	1.62	0	0.01	0	1.20	0	0.01	0	180.15	0	0.74	0	27529	0	2351937	0	119298	0	12954	0	2005	0	0	0	317014	0	152	0	0	0	2092	0	409749	0	4133	0	416126	0	80.81	0	1900666	0	9501	421374	44.350489422166	2351937.0	2019964.0	27529.0	119298.0	12954.0	2005.0	0.0	317014.0	1900666.0	85.9	1.2	5.1	0.6	0.1	0.0	13.5	80.8	101	101	101.00	38	237545637	26.6	22.8	23.0	27.6	0.0	34.8	17.6	smartseq
1450095	SRR3638206	SRP076212	SRS1488251	SRX1826293	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189095: 1-0-1-1-BTN35-C05-1782070112-12ul-1-IL5413-N704-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189095		GSM2189095	1-0-1-1-BTN35-C05-1782070112-12ul-1-IL5413-N704-N505 BTN35 Mic-scRNA-Seq	67800900	452006	2016-07-18 10:56:32	32631805	67800900	452006	2	452006	index:0,count:452006,average:75,stdev:0|index:1,count:452006,average:75,stdev:0	GSM2189095_r1						7.86	2.98	0.12	49107954	48844783	44416569	44673915	99.46	100.58	382240	361903	175.976	788.082	143	2004	65.06	71.93	433277	248672	433277	248672	69.06	67.65	433277	263994	433277	233882	11711317	23.85	1.65	0	8.08	0	0.23	0	0.22	0	0.00	0	14.98	0	382240	0	150	0	146.34	0	1.62	0	0.01	0	1.12	0	0.00	0	90.40	0	0.80	0	7469	0	452006	0	36532	0	1057	0	988	0	0	0	67721	0	27	0	0	0	260	0	38257	0	405	0	38949	0	76.48	0	345708	0	11721	37824	3.227028410545	452006.0	382240.0	7469.0	36532.0	1057.0	988.0	0.0	67721.0	345708.0	84.6	1.7	8.1	0.2	0.2	0.0	15.0	76.5	75	75	75.00	7	33900450	29.9	20.7	20.2	29.2	0.0	33.3	21.8	smartseq
1450109	SRR3638207	SRP076212	SRS1488251	SRX1826293	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189095: 1-0-1-1-BTN35-C05-1782070112-12ul-1-IL5413-N704-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189095		GSM2189095	1-0-1-1-BTN35-C05-1782070112-12ul-1-IL5413-N704-N505 BTN35 Mic-scRNA-Seq	65672100	437814	2016-07-18 10:56:32	31633260	65672100	437814	2	437814	index:0,count:437814,average:75,stdev:0|index:1,count:437814,average:75,stdev:0	GSM2189095_r2						7.85	2.98	0.08	48188457	47930479	43577376	43837509	99.46	100.6	373889	353521	177.545	788.177	105	1911	65.13	72.03	424651	243509	424651	243509	69.09	67.72	424651	258312	424651	228929	11445564	23.75	1.66	0	8.18	0	0.23	0	0.20	0	0.00	0	14.17	0	373889	0	150	0	146.40	0	1.62	0	0.01	0	1.13	0	0.00	0	75.05	0	0.81	0	7266	0	437814	0	35819	0	1015	0	875	0	0	0	62035	0	17	0	0	0	209	0	37701	0	379	0	38306	0	77.22	0	338070	0	11749	37457	3.188101114989	437814.0	373889.0	7266.0	35819.0	1015.0	875.0	0.0	62035.0	338070.0	85.4	1.7	8.2	0.2	0.2	0.0	14.2	77.2	75	75	75.00	7	32836050	29.9	20.7	20.2	29.3	0.0	33.4	22.0	smartseq
1450110	SRR3639207	SRP076212	SRS1488610	SRX1826652	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189454: 1gg_BTN7_C45_IL4709-703-508_AGGCAGAA-CTAAGCCT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189454		GSM2189454	1gg_BTN7_C45_IL4709-703-508_AGGCAGAA-CTAAGCCT BTN07 Mic-scRNA-Seq	530301106	2625253	2016-07-18 10:56:32	360696841	530301106	2625253	2	2625253	index:0,count:2625253,average:101,stdev:0|index:1,count:2625253,average:101,stdev:0	GSM2189454_r1						1.71	3.41	0.31	409577139	401253647	392503795	385968724	97.97	98.34	2269971	2123015	254.041	705.995	174	11213	66.69	69.66	2434776	1513822	2434776	1513822	66.96	66.87	2434776	1519986	2434776	1453338	113985331	27.83	1.02	0	3.68	0	0.26	0	0.09	0	0.00	0	13.18	0	2269971	0	202	0	198.39	0	1.81	0	0.01	0	1.20	0	0.01	0	162.95	0	0.76	0	26896	0	2625253	0	96664	0	6737	0	2417	0	0	0	346128	0	253	0	0	0	2488	0	425713	0	4613	0	433067	0	82.78	0	2173307	0	11612	433184	37.304857044437	2625253.0	2269971.0	26896.0	96664.0	6737.0	2417.0	0.0	346128.0	2173307.0	86.5	1.0	3.7	0.3	0.1	0.0	13.2	82.8	101	101	101.00	38	265150553	26.6	22.8	23.0	27.5	0.0	34.9	17.7	smartseq
1450111	SRR3640207	SRP076212	SRS1489022	SRX1827064	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189866: D10_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189866		GSM2189866	D10_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	60716250	404775	2016-07-18 10:56:32	22624295	60716250	404775	2	404775	index:0,count:404775,average:75,stdev:0|index:1,count:404775,average:75,stdev:0	GSM2189866_r1						1.67	2.91	0.01	51834674	56136571	49138217	53668245	108.3	109.22	376713	334565	234.727	1516.903	134	1696	76.51	80.92	403818	288205	403818	288205	67.72	68.34	403818	255111	403818	243403	8353855	16.12	1.54	0	5.08	0	0.18	0	0.16	0	0.00	0	6.60	0	376713	0	150	0	148.04	0	4.10	0	0.05	0	1.10	0	0.02	0	121.43	0	0.27	0	6231	0	404775	0	20550	0	711	0	655	0	0	0	26696	0	59	0	0	0	611	0	72927	0	591	0	74188	0	87.99	0	356163	0	21095	71530	3.390850912539	404775.0	376713.0	6231.0	20550.0	711.0	655.0	0.0	26696.0	356163.0	93.1	1.5	5.1	0.2	0.2	0.0	6.6	88.0	75	75	75.00	6	30358125	25.0	24.8	24.8	25.4	0.0	34.8	28.3	smartseq
1450125	SRR3638208	SRP076212	SRS1488251	SRX1826293	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189095: 1-0-1-1-BTN35-C05-1782070112-12ul-1-IL5413-N704-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189095		GSM2189095	1-0-1-1-BTN35-C05-1782070112-12ul-1-IL5413-N704-N505 BTN35 Mic-scRNA-Seq	67275300	448502	2016-07-18 10:56:32	32445972	67275300	448502	2	448502	index:0,count:448502,average:75,stdev:0|index:1,count:448502,average:75,stdev:0	GSM2189095_r3						7.8	2.94	0.09	49027083	48788416	44311114	44605904	99.51	100.67	380848	360019	176.769	783.131	143	2020	65.06	71.98	432490	247773	432490	247773	69.05	67.64	432490	262994	432490	232822	11660306	23.78	1.66	0	8.17	0	0.24	0	0.22	0	0.00	0	14.62	0	380848	0	150	0	146.36	0	1.66	0	0.01	0	1.12	0	0.00	0	76.89	0	0.82	0	7427	0	448502	0	36628	0	1085	0	987	0	0	0	65582	0	27	0	0	0	245	0	38412	0	395	0	39079	0	76.75	0	344220	0	11897	38236	3.213919475498	448502.0	380848.0	7427.0	36628.0	1085.0	987.0	0.0	65582.0	344220.0	84.9	1.7	8.2	0.2	0.2	0.0	14.6	76.7	75	75	75.00	7	33637650	29.9	20.8	20.2	29.1	0.0	33.3	21.9	smartseq
1450126	SRR3639208	SRP076212	SRS1488611	SRX1826653	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189455: 1gg_BTN7_C49_IL4709-704-501_TCCTGAGC-TAGATCGC BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189455		GSM2189455	1gg_BTN7_C49_IL4709-704-501_TCCTGAGC-TAGATCGC BTN07 Mic-scRNA-Seq	414612878	2052539	2016-07-18 10:56:32	288945469	414612878	2052539	2	2052539	index:0,count:2052539,average:101,stdev:0|index:1,count:2052539,average:101,stdev:0	GSM2189455_r1						1.49	2.74	1.37	336195168	306553443	320315785	293446761	91.18	91.61	1858771	1760573	250.708	656.950	188	9443	67.37	70.79	2033641	1252298	2033641	1252298	68.38	68.6	2033641	1270940	2033641	1213542	69049945	20.54	1.03	0	4.37	0	0.57	0	0.27	0	0.00	0	8.60	0	1858771	0	202	0	198.81	0	1.56	0	0.01	0	1.19	0	0.01	0	171.84	0	0.61	0	21118	0	2052539	0	89729	0	11757	0	5562	0	0	0	176449	0	455	0	0	0	1898	0	280077	0	2595	0	285025	0	86.19	0	1769042	0	6970	285160	40.912482065997	2052539.0	1858771.0	21118.0	89729.0	11757.0	5562.0	0.0	176449.0	1769042.0	90.6	1.0	4.4	0.6	0.3	0.0	8.6	86.2	101	101	101.00	38	207306439	27.0	22.5	22.9	27.7	0.0	34.2	17.2	smartseq
1450127	SRR3640208	SRP076212	SRS1489022	SRX1827064	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189866: D10_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189866		GSM2189866	D10_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	60485100	403234	2016-07-18 10:56:32	22619541	60485100	403234	2	403234	index:0,count:403234,average:75,stdev:0|index:1,count:403234,average:75,stdev:0	GSM2189866_r2						1.63	2.93	0.02	51439484	55763221	48789513	53330328	108.41	109.31	373808	331626	235.421	1487.557	153	1658	76.64	81.02	400672	286482	400672	286482	67.67	68.34	400672	252954	400672	241630	8280510	16.10	1.52	0	5.02	0	0.17	0	0.18	0	0.00	0	6.95	0	373808	0	150	0	148.02	0	4.18	0	0.05	0	1.09	0	0.02	0	111.66	0	0.28	0	6136	0	403234	0	20234	0	700	0	712	0	0	0	28014	0	52	0	0	0	593	0	72532	0	593	0	73770	0	87.68	0	353574	0	20966	71075	3.390012401030	403234.0	373808.0	6136.0	20234.0	700.0	712.0	0.0	28014.0	353574.0	92.7	1.5	5.0	0.2	0.2	0.0	6.9	87.7	75	75	75.00	6	30242550	25.0	24.8	24.8	25.4	0.0	34.8	28.2	smartseq
1450142	SRR3638209	SRP076212	SRS1488251	SRX1826293	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189095: 1-0-1-1-BTN35-C05-1782070112-12ul-1-IL5413-N704-N505 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189095		GSM2189095	1-0-1-1-BTN35-C05-1782070112-12ul-1-IL5413-N704-N505 BTN35 Mic-scRNA-Seq	65624550	437497	2016-07-18 10:56:32	31520796	65624550	437497	2	437497	index:0,count:437497,average:75,stdev:0|index:1,count:437497,average:75,stdev:0	GSM2189095_r4						7.96	2.97	0.09	47749923	47443134	43194967	43412897	99.36	100.5	371547	351747	176.333	746.154	118	1942	64.87	71.72	421659	241025	421659	241025	68.84	67.43	421659	255778	421659	226620	11456720	23.99	1.67	0	8.11	0	0.22	0	0.22	0	0.00	0	14.63	0	371547	0	150	0	146.39	0	1.65	0	0.01	0	1.15	0	0.00	0	87.50	0	0.77	0	7308	0	437497	0	35488	0	973	0	979	0	0	0	63998	0	23	0	0	0	250	0	36995	0	399	0	37667	0	76.81	0	336059	0	11514	36759	3.192548202189	437497.0	371547.0	7308.0	35488.0	973.0	979.0	0.0	63998.0	336059.0	84.9	1.7	8.1	0.2	0.2	0.0	14.6	76.8	75	75	75.00	7	32812275	30.0	20.6	20.1	29.3	0.0	33.5	22.0	smartseq
1450143	SRR3639209	SRP076212	SRS1488612	SRX1826654	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189456: 1gg_BTN7_C53_IL4709-711-501_AAGAGGCA-TAGATCGC BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189456		GSM2189456	1gg_BTN7_C53_IL4709-711-501_AAGAGGCA-TAGATCGC BTN07 Mic-scRNA-Seq	529745606	2622503	2016-07-18 10:56:32	364729054	529745606	2622503	2	2622503	index:0,count:2622503,average:101,stdev:0|index:1,count:2622503,average:101,stdev:0	GSM2189456_r1						2.17	3.03	0.98	422892662	394782827	402438102	377672939	93.35	93.85	2345635	2225448	250.453	653.066	188	11863	65.23	68.61	2563457	1530013	2563457	1530013	66.59	66.44	2563457	1562014	2563457	1481667	104643729	24.74	1.13	0	4.41	0	0.56	0	0.20	0	0.00	0	9.80	0	2345635	0	202	0	198.63	0	1.60	0	0.01	0	1.24	0	0.01	0	188.82	0	0.66	0	29524	0	2622503	0	115535	0	14639	0	5252	0	0	0	256977	0	93	0	0	0	2041	0	358277	0	3616	0	364027	0	85.04	0	2230100	0	7961	363668	45.681195829670	2622503.0	2345635.0	29524.0	115535.0	14639.0	5252.0	0.0	256977.0	2230100.0	89.4	1.1	4.4	0.6	0.2	0.0	9.8	85.0	101	101	101.00	38	264872803	26.9	22.6	22.8	27.6	0.0	34.8	17.9	smartseq
1450254	SRR3638210	SRP076212	SRS1488252	SRX1826294	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189096: 1-0-1-1-BTN35-C16-1782070112-22ul-1-IL5413-N706-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189096		GSM2189096	1-0-1-1-BTN35-C16-1782070112-22ul-1-IL5413-N706-N506 BTN35 Mic-scRNA-Seq	67208850	448059	2016-07-18 10:56:32	32039634	67208850	448059	2	448059	index:0,count:448059,average:75,stdev:0|index:1,count:448059,average:75,stdev:0	GSM2189096_r1						3.4	3.91	0.1	47470071	45659879	44587951	43227129	96.19	96.95	370204	354161	176.929	743.652	141	1885	51.11	54.45	407371	189215	407371	189215	53.67	52.48	407371	198670	407371	182348	18747084	39.49	1.38	0	5.07	0	0.41	0	0.23	0	0.00	0	16.74	0	370204	0	150	0	146.55	0	1.36	0	0.01	0	1.18	0	0.00	0	84.90	0	0.78	0	6184	0	448059	0	22723	0	1838	0	1026	0	0	0	74991	0	13	0	0	0	191	0	26423	0	362	0	26989	0	77.55	0	347481	0	11178	26087	2.333780640544	448059.0	370204.0	6184.0	22723.0	1838.0	1026.0	0.0	74991.0	347481.0	82.6	1.4	5.1	0.4	0.2	0.0	16.7	77.6	75	75	75.00	7	33604425	31.0	19.9	19.3	29.8	0.0	33.3	21.4	smartseq
1450255	SRR3639210	SRP076212	SRS1488613	SRX1826655	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189457: 1gg_BTN7_C54_IL4709-712-501_GTAGAGGA-TAGATCGC BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189457		GSM2189457	1gg_BTN7_C54_IL4709-712-501_GTAGAGGA-TAGATCGC BTN07 Mic-scRNA-Seq	498862432	2469616	2016-07-18 10:56:32	347389716	498862432	2469616	2	2469616	index:0,count:2469616,average:101,stdev:0|index:1,count:2469616,average:101,stdev:0	GSM2189457_r1						1.09	2.15	0.11	406004131	402049085	385418394	382227369	99.03	99.17	2232941	2029502	257.335	780.872	188	10884	81.65	86.07	2476287	1823291	2476287	1823291	83.23	83.46	2476287	1858471	2476287	1767966	50143069	12.35	0.90	0	4.64	0	0.95	0	0.11	0	0.00	0	8.52	0	2232941	0	202	0	198.73	0	1.46	0	0.01	0	1.23	0	0.00	0	197.57	0	0.63	0	22256	0	2469616	0	114509	0	23459	0	2835	0	0	0	210381	0	270	0	0	0	3817	0	534151	0	4024	0	542262	0	85.78	0	2118432	0	8084	547303	67.702003958436	2469616.0	2232941.0	22256.0	114509.0	23459.0	2835.0	0.0	210381.0	2118432.0	90.4	0.9	4.6	0.9	0.1	0.0	8.5	85.8	101	101	101.00	38	249431216	26.5	23.0	23.3	27.2	0.0	34.2	17.4	smartseq
1450269	SRR3638211	SRP076212	SRS1488252	SRX1826294	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189096: 1-0-1-1-BTN35-C16-1782070112-22ul-1-IL5413-N706-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189096		GSM2189096	1-0-1-1-BTN35-C16-1782070112-22ul-1-IL5413-N706-N506 BTN35 Mic-scRNA-Seq	67320750	448805	2016-07-18 10:56:32	31975250	67320750	448805	2	448805	index:0,count:448805,average:75,stdev:0|index:1,count:448805,average:75,stdev:0	GSM2189096_r2						3.37	3.96	0.1	48092372	46323957	45168205	43846357	96.32	97.07	374207	357196	179.180	744.507	122	1857	51.44	54.82	412762	192494	412762	192494	53.96	52.83	412762	201922	412762	185516	18907084	39.31	1.36	0	5.13	0	0.40	0	0.22	0	0.00	0	16.00	0	374207	0	150	0	146.60	0	1.35	0	0.01	0	1.17	0	0.00	0	95.04	0	0.77	0	6117	0	448805	0	23039	0	1802	0	1009	0	0	0	71787	0	13	0	0	0	198	0	27699	0	375	0	28285	0	78.25	0	351168	0	11659	27415	2.351402350116	448805.0	374207.0	6117.0	23039.0	1802.0	1009.0	0.0	71787.0	351168.0	83.4	1.4	5.1	0.4	0.2	0.0	16.0	78.2	75	75	75.00	7	33660375	30.9	20.0	19.3	29.8	0.0	33.4	21.6	smartseq
1450270	SRR3639211	SRP076212	SRS1488614	SRX1826656	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189458: 1gg_BTN7_C61_IL4709-704-503_TCCTGAGC-TATCCTCT BTN07 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN07|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189458		GSM2189458	1gg_BTN7_C61_IL4709-704-503_TCCTGAGC-TATCCTCT BTN07 Mic-scRNA-Seq	562876232	2786516	2016-07-18 10:56:32	383742114	562876232	2786516	2	2786516	index:0,count:2786516,average:101,stdev:0|index:1,count:2786516,average:101,stdev:0	GSM2189458_r1						1.53	3.3	1.14	438294708	373082048	421047281	360180447	85.12	85.54	2451500	2335066	242.257	689.767	188	12939	60.07	62.58	2641300	1472533	2641300	1472533	60.72	60.7	2641300	1488470	2641300	1428256	99915066	22.80	1.06	0	3.53	0	0.44	0	0.15	0	0.00	0	11.44	0	2451500	0	202	0	198.37	0	1.61	0	0.01	0	1.20	0	0.01	0	151.99	0	0.71	0	29654	0	2786516	0	98387	0	12136	0	4097	0	0	0	318783	0	295	0	0	0	2348	0	332815	0	3449	0	338907	0	84.45	0	2353113	0	6743	334012	49.534628503633	2786516.0	2451500.0	29654.0	98387.0	12136.0	4097.0	0.0	318783.0	2353113.0	88.0	1.1	3.5	0.4	0.1	0.0	11.4	84.4	101	101	101.00	38	281438116	27.3	22.2	22.3	28.2	0.0	35.0	18.1	smartseq
1450271	SRR3640211	SRP076212	SRS1489023	SRX1827065	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189867: D10_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189867		GSM2189867	D10_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	49296000	328640	2016-07-18 10:56:32	18447911	49296000	328640	2	328640	index:0,count:328640,average:75,stdev:0|index:1,count:328640,average:75,stdev:0	GSM2189867_r1						1.99	2.6	0.06	41747583	45253037	39165253	42862127	108.4	109.44	303996	267675	233.064	1425.666	146	1398	77.71	83.06	330815	236240	330815	236240	70.37	71.04	330815	213917	330815	202043	5997940	14.37	1.55	0	5.96	0	0.30	0	0.21	0	0.00	0	6.99	0	303996	0	150	0	147.98	0	4.37	0	0.05	0	1.07	0	0.02	0	98.59	0	0.27	0	5101	0	328640	0	19579	0	983	0	698	0	0	0	22963	0	47	0	0	0	425	0	63483	0	436	0	64391	0	86.54	0	284417	0	19652	62096	3.159780175046	328640.0	303996.0	5101.0	19579.0	983.0	698.0	0.0	22963.0	284417.0	92.5	1.6	6.0	0.3	0.2	0.0	7.0	86.5	75	75	75.00	6	24648000	24.9	24.9	24.9	25.3	0.0	34.8	28.2	smartseq
1450287	SRR3638212	SRP076212	SRS1488252	SRX1826294	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189096: 1-0-1-1-BTN35-C16-1782070112-22ul-1-IL5413-N706-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189096		GSM2189096	1-0-1-1-BTN35-C16-1782070112-22ul-1-IL5413-N706-N506 BTN35 Mic-scRNA-Seq	67211850	448079	2016-07-18 10:56:32	32090177	67211850	448079	2	448079	index:0,count:448079,average:75,stdev:0|index:1,count:448079,average:75,stdev:0	GSM2189096_r3						3.37	3.92	0.1	47684558	45891068	44820043	43480786	96.24	97.01	371526	354793	177.699	793.116	91	1902	51.53	54.86	408876	191445	408876	191445	54.04	52.94	408876	200761	408876	184752	18739586	39.30	1.41	0	5.03	0	0.39	0	0.22	0	0.00	0	16.48	0	371526	0	150	0	146.55	0	1.38	0	0.01	0	1.18	0	0.00	0	70.13	0	0.80	0	6310	0	448079	0	22541	0	1732	0	985	0	0	0	73836	0	17	0	0	0	204	0	27243	0	358	0	27822	0	77.88	0	348985	0	11618	26854	2.311413324152	448079.0	371526.0	6310.0	22541.0	1732.0	985.0	0.0	73836.0	348985.0	82.9	1.4	5.0	0.4	0.2	0.0	16.5	77.9	75	75	75.00	7	33605925	31.0	20.0	19.3	29.7	0.0	33.3	21.4	smartseq
1450298	SRR3638213	SRP076212	SRS1488252	SRX1826294	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189096: 1-0-1-1-BTN35-C16-1782070112-22ul-1-IL5413-N706-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189096		GSM2189096	1-0-1-1-BTN35-C16-1782070112-22ul-1-IL5413-N706-N506 BTN35 Mic-scRNA-Seq	70370400	469136	2016-07-18 10:56:32	33144489	70370400	469136	2	469136	index:0,count:469136,average:75,stdev:0|index:1,count:469136,average:75,stdev:0	GSM2189096_r4						3.42	3.91	0.09	49955482	48083921	46927292	45515010	96.25	96.99	388966	371020	178.941	777.473	133	1988	51.25	54.6	428700	199353	428700	199353	53.82	52.67	428700	209327	428700	192286	19728768	39.49	1.39	0	5.09	0	0.41	0	0.22	0	0.00	0	16.45	0	388966	0	150	0	146.58	0	1.33	0	0.01	0	1.16	0	0.00	0	99.35	0	0.72	0	6519	0	469136	0	23870	0	1939	0	1049	0	0	0	77182	0	11	0	0	0	251	0	28541	0	341	0	29144	0	77.82	0	365096	0	11876	28352	2.387335803301	469136.0	388966.0	6519.0	23870.0	1939.0	1049.0	0.0	77182.0	365096.0	82.9	1.4	5.1	0.4	0.2	0.0	16.5	77.8	75	75	75.00	7	35185200	31.0	20.0	19.3	29.8	0.0	33.6	21.8	smartseq
1450299	SRR3639213	SRP076212	SRS1488616	SRX1826658	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189460: 1ggs_BTN3_C33_IL3971-703-503_AGGCAGAA-TATCCTCT BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189460		GSM2189460	1ggs_BTN3_C33_IL3971-703-503_AGGCAGAA-TATCCTCT BTN03 Mic-scRNA-Seq	556423948	2754574	2016-07-18 10:56:32	397444060	556423948	2754574	2	2754574	index:0,count:2754574,average:101,stdev:0|index:1,count:2754574,average:101,stdev:0	GSM2189460_r1						1.72	2.43	0.01	402173976	404277469	393219119	396690117	100.52	100.88	2402467	2331469	211.104	580.276	137	14540	61.95	63.4	2487916	1488312	2487916	1488312	60.17	59.84	2487916	1445484	2487916	1404689	141011695	35.06	0.97	0	2.00	0	0.17	0	0.04	0	0.00	0	12.58	0	2402467	0	202	0	197.27	0	1.64	0	0.01	0	1.38	0	0.01	0	141.66	0	1.09	0	26720	0	2754574	0	55033	0	4656	0	980	0	0	0	346471	0	2	0	0	0	1021	0	191145	0	3181	0	195349	0	85.22	0	2347434	0	3982	180554	45.342541436464	2754574.0	2402467.0	26720.0	55033.0	4656.0	980.0	0.0	346471.0	2347434.0	87.2	1.0	2.0	0.2	0.0	0.0	12.6	85.2	101	101	101.00	38	278211974	27.7	22.0	21.9	28.4	0.0	35.1	18.2	smartseq
1450300	SRR3640213	SRP076212	SRS1489023	SRX1827065	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189867: D10_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189867		GSM2189867	D10_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	48365100	322434	2016-07-18 10:56:32	18310123	48365100	322434	2	322434	index:0,count:322434,average:75,stdev:0|index:1,count:322434,average:75,stdev:0	GSM2189867_r3						2.0	2.65	0.05	41040164	44438847	38519428	42098644	108.28	109.29	298600	262427	234.045	1430.075	141	1354	77.72	83.02	325121	232058	325121	232058	70.52	71.11	325121	210571	325121	198766	5918365	14.42	1.50	0	5.92	0	0.28	0	0.18	0	0.00	0	6.93	0	298600	0	150	0	147.98	0	4.33	0	0.05	0	1.08	0	0.02	0	105.52	0	0.28	0	4839	0	322434	0	19076	0	908	0	591	0	0	0	22335	0	59	0	0	0	449	0	62433	0	462	0	63403	0	86.69	0	279524	0	19596	61247	3.125484792815	322434.0	298600.0	4839.0	19076.0	908.0	591.0	0.0	22335.0	279524.0	92.6	1.5	5.9	0.3	0.2	0.0	6.9	86.7	75	75	75.00	6	24182550	24.9	24.9	24.9	25.3	0.0	34.7	27.7	smartseq
1450301	SRR3641213	SRP076212	SRS1489281	SRX1827321	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190123: H11_1000700102-OGC9-sal_1_2ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190123		GSM2190123	H11_1000700102-OGC9-sal_1_2ul_1 OGC09-sal FACS-scRNA-Seq	73828500	492190	2016-07-18 10:56:32	31120463	73828500	492190	2	492190	index:0,count:492190,average:75,stdev:0|index:1,count:492190,average:75,stdev:0	GSM2190123_r2						2.11	2.04	0.04	60551956	68714736	56233575	64769666	113.48	115.18	441014	403523	225.817	1089.721	146	2140	77.25	83.46	486262	340664	486262	340664	64.94	65.59	486262	286413	486262	267736	8322588	13.74	1.92	0	6.67	0	0.22	0	0.13	0	0.00	0	10.05	0	441014	0	150	0	147.63	0	4.67	0	0.07	0	1.07	0	0.02	0	98.44	0	0.51	0	9466	0	492190	0	32837	0	1073	0	631	0	0	0	49472	0	56	0	0	0	449	0	66306	0	645	0	67456	0	82.93	0	408177	0	15831	65997	4.168845935190	492190.0	441014.0	9466.0	32837.0	1073.0	631.0	0.0	49472.0	408177.0	89.6	1.9	6.7	0.2	0.1	0.0	10.1	82.9	75	75	75.00	6	36914250	25.1	24.6	24.8	25.5	0.0	33.8	25.4	smartseq
1450313	SRR3638214	SRP076212	SRS1488253	SRX1826295	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189097: 1-0-1-1-BTN35-C20-1782070112-18ul-1-IL5413-N711-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189097		GSM2189097	1-0-1-1-BTN35-C20-1782070112-18ul-1-IL5413-N711-N506 BTN35 Mic-scRNA-Seq	71944200	479628	2016-07-18 10:56:32	34365786	71944200	479628	2	479628	index:0,count:479628,average:75,stdev:0|index:1,count:479628,average:75,stdev:0	GSM2189097_r1						3.68	3.59	0.04	49998018	49282806	46789547	46524473	98.57	99.43	391259	370038	178.564	775.271	113	1975	61.27	65.51	430486	239718	430486	239718	63.61	62.87	430486	248879	430486	230048	15523047	31.05	1.39	0	5.29	0	0.22	0	0.15	0	0.00	0	18.06	0	391259	0	150	0	146.38	0	1.44	0	0.01	0	1.14	0	0.00	0	90.88	0	0.79	0	6645	0	479628	0	25356	0	1051	0	709	0	0	0	86609	0	27	0	0	0	240	0	36490	0	527	0	37284	0	76.29	0	365903	0	12653	36109	2.853789615111	479628.0	391259.0	6645.0	25356.0	1051.0	709.0	0.0	86609.0	365903.0	81.6	1.4	5.3	0.2	0.1	0.0	18.1	76.3	75	75	75.00	7	35972100	30.6	20.5	19.7	29.1	0.0	33.2	21.3	smartseq
1450314	SRR3639214	SRP076212	SRS1488618	SRX1826659	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189461: 1ggs_BTN3_C61_IL3971-701-502_TAAGGCGA-CTCTCTAT BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189461		GSM2189461	1ggs_BTN3_C61_IL3971-701-502_TAAGGCGA-CTCTCTAT BTN03 Mic-scRNA-Seq	511668828	2533014	2016-07-18 10:56:32	366317437	511668828	2533014	2	2533014	index:0,count:2533014,average:101,stdev:0|index:1,count:2533014,average:101,stdev:0	GSM2189461_r1						3.89	1.95	0.01	372742294	372738328	358087586	359320133	100.0	100.34	2209841	2078983	217.049	752.714	152	12639	77.4	80.64	2334082	1710407	2334082	1710407	78.27	78.04	2334082	1729693	2334082	1655352	67351404	18.07	0.91	0	3.50	0	0.13	0	0.05	0	0.00	0	12.58	0	2209841	0	202	0	196.86	0	1.57	0	0.01	0	1.35	0	0.01	0	178.80	0	1.12	0	23043	0	2533014	0	88750	0	3205	0	1272	0	0	0	318696	0	36	0	0	0	2404	0	365837	0	3820	0	372097	0	83.74	0	2121091	0	6719	350243	52.127251079030	2533014.0	2209841.0	23043.0	88750.0	3205.0	1272.0	0.0	318696.0	2121091.0	87.2	0.9	3.5	0.1	0.1	0.0	12.6	83.7	101	101	101.00	38	255834414	27.0	22.8	22.7	27.6	0.0	34.8	17.8	smartseq
1450315	SRR3640214	SRP076212	SRS1489023	SRX1827065	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189867: D10_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189867		GSM2189867	D10_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	48597300	323982	2016-07-18 10:56:32	18466938	48597300	323982	2	323982	index:0,count:323982,average:75,stdev:0|index:1,count:323982,average:75,stdev:0	GSM2189867_r4						2.0	2.63	0.05	41206657	44596630	38671846	42265058	108.23	109.29	299713	263254	233.686	1496.854	146	1398	77.73	83.05	326555	232956	326555	232956	70.48	71.09	326555	211240	326555	199405	5934403	14.40	1.54	0	5.93	0	0.31	0	0.21	0	0.00	0	6.97	0	299713	0	150	0	147.96	0	4.34	0	0.05	0	1.07	0	0.02	0	89.72	0	0.30	0	4992	0	323982	0	19217	0	992	0	688	0	0	0	22589	0	60	0	0	0	391	0	62393	0	454	0	63298	0	86.58	0	280496	0	19580	61181	3.124668028601	323982.0	299713.0	4992.0	19217.0	992.0	688.0	0.0	22589.0	280496.0	92.5	1.5	5.9	0.3	0.2	0.0	7.0	86.6	75	75	75.00	6	24298650	24.9	24.9	24.9	25.3	0.0	34.7	27.7	smartseq
1450316	SRR3641214	SRP076212	SRS1489281	SRX1827321	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190123: H11_1000700102-OGC9-sal_1_2ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190123		GSM2190123	H11_1000700102-OGC9-sal_1_2ul_1 OGC09-sal FACS-scRNA-Seq	74230950	494873	2016-07-18 10:56:32	31641394	74230950	494873	2	494873	index:0,count:494873,average:75,stdev:0|index:1,count:494873,average:75,stdev:0	GSM2190123_r3						2.12	2.07	0.06	60929157	68970952	56555994	64956986	113.2	114.85	444092	405943	224.558	1075.913	174	2140	77.1	83.33	489683	342378	489683	342378	65.0	65.66	489683	288640	489683	269771	8392051	13.77	1.92	0	6.71	0	0.21	0	0.14	0	0.00	0	9.91	0	444092	0	150	0	147.59	0	4.69	0	0.07	0	1.07	0	0.02	0	111.35	0	0.54	0	9515	0	494873	0	33228	0	1053	0	680	0	0	0	49048	0	61	0	0	0	427	0	67413	0	695	0	68596	0	83.02	0	410864	0	15818	67133	4.244089012517	494873.0	444092.0	9515.0	33228.0	1053.0	680.0	0.0	49048.0	410864.0	89.7	1.9	6.7	0.2	0.1	0.0	9.9	83.0	75	75	75.00	6	37115475	25.1	24.6	24.7	25.5	0.0	33.5	24.9	smartseq
1450331	SRR3638215	SRP076212	SRS1488253	SRX1826295	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189097: 1-0-1-1-BTN35-C20-1782070112-18ul-1-IL5413-N711-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189097		GSM2189097	1-0-1-1-BTN35-C20-1782070112-18ul-1-IL5413-N711-N506 BTN35 Mic-scRNA-Seq	71613150	477421	2016-07-18 10:56:32	34078152	71613150	477421	2	477421	index:0,count:477421,average:75,stdev:0|index:1,count:477421,average:75,stdev:0	GSM2189097_r2						3.68	3.64	0.04	50634244	49905158	47419378	47119465	98.56	99.37	394570	372099	181.335	811.949	89	1960	61.52	65.73	433692	242736	433692	242736	63.88	63.14	433692	252068	433692	233187	15623811	30.86	1.39	0	5.29	0	0.22	0	0.17	0	0.00	0	16.96	0	394570	0	150	0	146.43	0	1.42	0	0.01	0	1.16	0	0.00	0	81.84	0	0.78	0	6623	0	477421	0	25277	0	1060	0	809	0	0	0	80982	0	20	0	0	0	250	0	37921	0	532	0	38723	0	77.35	0	369293	0	13016	37633	2.891287645974	477421.0	394570.0	6623.0	25277.0	1060.0	809.0	0.0	80982.0	369293.0	82.6	1.4	5.3	0.2	0.2	0.0	17.0	77.4	75	75	75.00	7	35806575	30.5	20.6	19.8	29.2	0.0	33.4	21.5	smartseq
1450332	SRR3639215	SRP076212	SRS1488617	SRX1826660	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189462: 1gs_BTN3_C05_IL3971-703-501_AGGCAGAA-TAGATCGC BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189462		GSM2189462	1gs_BTN3_C05_IL3971-703-501_AGGCAGAA-TAGATCGC BTN03 Mic-scRNA-Seq	609652160	3018080	2016-07-18 10:56:32	438854864	609652160	3018080	2	3018080	index:0,count:3018080,average:101,stdev:0|index:1,count:3018080,average:101,stdev:0	GSM2189462_r1						5.14	0.28	0.0	449103917	449620827	433064967	433833552	100.12	100.18	2735941	2710038	199.233	278.134	148	19834	96.01	99.64	2861830	2626673	2861830	2626673	98.87	99.13	2861830	2705102	2861830	2613384	1583445	0.35	1.08	0	3.30	0	0.03	0	0.02	0	0.00	0	9.29	0	2735941	0	202	0	197.33	0	1.38	0	0.01	0	1.22	0	0.01	0	241.45	0	0.66	0	32598	0	3018080	0	99706	0	1017	0	685	0	0	0	280437	0	0	0	0	0	903	0	98074	0	1192	0	100169	0	87.35	0	2636235	0	1441	98911	68.640527411520	3018080.0	2735941.0	32598.0	99706.0	1017.0	685.0	0.0	280437.0	2636235.0	90.7	1.1	3.3	0.0	0.0	0.0	9.3	87.3	101	101	101.00	38	304826080	26.3	23.6	23.3	26.8	0.0	34.6	18.0	smartseq
1450333	SRR3640215	SRP076212	SRS1489024	SRX1827066	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189868: D10_1000701204-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189868		GSM2189868	D10_1000701204-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	85374450	569163	2016-07-18 10:56:32	29648283	85374450	569163	2	569163	index:0,count:569163,average:75,stdev:0|index:1,count:569163,average:75,stdev:0	GSM2189868_r1						1.08	1.97	0.02	72830165	84543305	68348109	80394741	116.08	117.63	527732	466200	261.833	1574.086	125	2165	81.75	87.46	573561	431409	573561	431409	66.81	67.8	573561	352556	573561	334436	7222321	9.92	1.83	0	6.06	0	0.22	0	0.09	0	0.00	0	6.96	0	527732	0	150	0	147.99	0	4.74	0	0.07	0	1.10	0	0.02	0	157.61	0	0.27	0	10436	0	569163	0	34473	0	1258	0	533	0	0	0	39640	0	108	0	0	0	698	0	92009	0	888	0	93703	0	86.66	0	493259	0	23900	90374	3.781338912134	569163.0	527732.0	10436.0	34473.0	1258.0	533.0	0.0	39640.0	493259.0	92.7	1.8	6.1	0.2	0.1	0.0	7.0	86.7	75	75	75.00	6	42687225	24.2	25.5	25.6	24.7	0.0	35.2	30.0	smartseq
1450334	SRR3641215	SRP076212	SRS1489281	SRX1827321	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190123: H11_1000700102-OGC9-sal_1_2ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190123		GSM2190123	H11_1000700102-OGC9-sal_1_2ul_1 OGC09-sal FACS-scRNA-Seq	73725000	491500	2016-07-18 10:56:32	31295435	73725000	491500	2	491500	index:0,count:491500,average:75,stdev:0|index:1,count:491500,average:75,stdev:0	GSM2190123_r4						2.1	2.1	0.06	60654672	68772591	56318205	64817522	113.38	115.09	441441	403564	226.701	1104.776	174	2168	77.21	83.43	486177	340817	486177	340817	64.97	65.61	486177	286786	486177	268006	8316413	13.71	1.91	0	6.70	0	0.21	0	0.13	0	0.00	0	9.84	0	441441	0	150	0	147.66	0	4.72	0	0.07	0	1.07	0	0.02	0	117.96	0	0.51	0	9375	0	491500	0	32943	0	1041	0	640	0	0	0	48378	0	45	0	0	0	397	0	66738	0	687	0	67867	0	83.11	0	408498	0	15788	66426	4.207372688118	491500.0	441441.0	9375.0	32943.0	1041.0	640.0	0.0	48378.0	408498.0	89.8	1.9	6.7	0.2	0.1	0.0	9.8	83.1	75	75	75.00	6	36862500	25.1	24.6	24.8	25.5	0.0	33.7	25.2	smartseq
1450347	SRR3638216	SRP076212	SRS1488253	SRX1826295	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189097: 1-0-1-1-BTN35-C20-1782070112-18ul-1-IL5413-N711-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189097		GSM2189097	1-0-1-1-BTN35-C20-1782070112-18ul-1-IL5413-N711-N506 BTN35 Mic-scRNA-Seq	71966250	479775	2016-07-18 10:56:32	34445050	71966250	479775	2	479775	index:0,count:479775,average:75,stdev:0|index:1,count:479775,average:75,stdev:0	GSM2189097_r3						3.65	3.66	0.04	50278324	49538946	47051521	46762527	98.53	99.39	392398	370594	179.946	808.661	100	1973	61.41	65.68	432099	240985	432099	240985	63.78	63.06	432099	250269	432099	231386	15518434	30.87	1.33	0	5.31	0	0.22	0	0.14	0	0.00	0	17.85	0	392398	0	150	0	146.42	0	1.43	0	0.01	0	1.17	0	0.00	0	69.09	0	0.81	0	6384	0	479775	0	25465	0	1045	0	679	0	0	0	85653	0	18	0	0	0	265	0	37362	0	549	0	38194	0	76.48	0	366933	0	12840	37040	2.884735202492	479775.0	392398.0	6384.0	25465.0	1045.0	679.0	0.0	85653.0	366933.0	81.8	1.3	5.3	0.2	0.1	0.0	17.9	76.5	75	75	75.00	7	35983125	30.6	20.6	19.8	29.0	0.0	33.2	21.3	smartseq
1450348	SRR3639216	SRP076212	SRS1488619	SRX1826661	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189463: 1gs_BTN3_C57_IL3971-707-501_CTCTCTAC-TAGATCGC BTN03 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN03|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189463		GSM2189463	1gs_BTN3_C57_IL3971-707-501_CTCTCTAC-TAGATCGC BTN03 Mic-scRNA-Seq	478117032	2366916	2016-07-18 10:56:32	345653257	478117032	2366916	2	2366916	index:0,count:2366916,average:101,stdev:0|index:1,count:2366916,average:101,stdev:0	GSM2189463_r1						3.35	1.47	0.0	359446625	358284124	345328094	345407582	99.68	100.02	2137504	2049070	212.469	579.639	148	13453	88.95	92.67	2251807	1901304	2251807	1901304	90.58	90.79	2251807	1936099	2251807	1862765	23227233	6.46	1.00	0	3.62	0	0.11	0	0.08	0	0.00	0	9.50	0	2137504	0	202	0	197.74	0	1.56	0	0.01	0	1.27	0	0.01	0	236.69	0	0.62	0	23597	0	2366916	0	85714	0	2649	0	1964	0	0	0	224799	0	492	0	0	0	2050	0	297360	0	3065	0	302967	0	86.69	0	2051790	0	4045	283902	70.185908529048	2366916.0	2137504.0	23597.0	85714.0	2649.0	1964.0	0.0	224799.0	2051790.0	90.3	1.0	3.6	0.1	0.1	0.0	9.5	86.7	101	101	101.00	38	239058516	26.7	23.0	22.8	27.5	0.0	34.4	17.3	smartseq
1450349	SRR3640216	SRP076212	SRS1489025	SRX1827067	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189869: D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189869		GSM2189869	D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	296100	1974	2016-07-18 10:56:32	140507	296100	1974	2	1974	index:0,count:1974,average:75,stdev:0|index:1,count:1974,average:75,stdev:0	GSM2189869_r1						1.45	1.45	0.0	132778	145490	124844	137937	109.57	110.49	1131	1072	142.282	362.093	80	14	81.96	87.78	1244	927	1244	927	73.12	74.05	1244	827	1244	782	13599	10.24	1.67	0	3.80	0	0.15	0	0.10	0	0.00	0	42.45	0	1131	0	150	0	146.47	0	3.81	0	0.04	0	1.00	0	0.01	0	3.55	0	0.23	0	33	0	1974	0	75	0	3	0	2	0	0	0	838	0	0	0	0	0	1	0	253	0	2	0	256	0	53.50	0	1056	0	203	211	1.039408866995	1974.0	1131.0	33.0	75.0	3.0	2.0	0.0	838.0	1056.0	57.3	1.7	3.8	0.2	0.1	0.0	42.5	53.5	75	75	75.00	6	148050	22.7	27.6	26.1	23.6	0.0	35.2	30.1	smartseq
1450350	SRR3641216	SRP076212	SRS1489279	SRX1827322	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190124: H11_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190124		GSM2190124	H11_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq	39023850	260159	2016-07-18 10:56:32	13250789	39023850	260159	2	260159	index:0,count:260159,average:75,stdev:0|index:1,count:260159,average:75,stdev:0	GSM2190124_r1						1.31	2.37	0.02	32448169	36056966	30510428	34294667	111.12	112.4	241424	212740	219.119	1444.496	123	1227	83.26	88.9	262797	201009	262797	201009	72.98	73.95	262797	176196	262797	167205	3039126	9.37	1.75	0	5.89	0	0.25	0	0.09	0	0.00	0	6.86	0	241424	0	150	0	147.78	0	4.22	0	0.05	0	1.10	0	0.02	0	85.14	0	0.25	0	4543	0	260159	0	15324	0	654	0	229	0	0	0	17852	0	32	0	0	0	403	0	55563	0	380	0	56378	0	86.91	0	226100	0	20889	53442	2.558380008617	260159.0	241424.0	4543.0	15324.0	654.0	229.0	0.0	17852.0	226100.0	92.8	1.7	5.9	0.3	0.1	0.0	6.9	86.9	75	75	75.00	6	19511925	24.3	25.5	25.4	24.7	0.0	35.2	30.0	smartseq
1450362	SRR3638217	SRP076212	SRS1488253	SRX1826295	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189097: 1-0-1-1-BTN35-C20-1782070112-18ul-1-IL5413-N711-N506 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189097		GSM2189097	1-0-1-1-BTN35-C20-1782070112-18ul-1-IL5413-N711-N506 BTN35 Mic-scRNA-Seq	74225400	494836	2016-07-18 10:56:32	35004022	74225400	494836	2	494836	index:0,count:494836,average:75,stdev:0|index:1,count:494836,average:75,stdev:0	GSM2189097_r4						3.66	3.67	0.05	52146858	51383349	48837567	48519040	98.54	99.35	406717	383586	180.863	801.286	79	2026	61.43	65.64	447160	249852	447160	249852	63.77	63.02	447160	259368	447160	239881	16112295	30.90	1.37	0	5.27	0	0.22	0	0.16	0	0.00	0	17.43	0	406717	0	150	0	146.46	0	1.41	0	0.01	0	1.14	0	0.00	0	74.23	0	0.73	0	6789	0	494836	0	26064	0	1080	0	784	0	0	0	86255	0	24	0	0	0	261	0	39468	0	546	0	40299	0	76.93	0	380653	0	13298	39182	2.946458114002	494836.0	406717.0	6789.0	26064.0	1080.0	784.0	0.0	86255.0	380653.0	82.2	1.4	5.3	0.2	0.2	0.0	17.4	76.9	75	75	75.00	7	37112700	30.5	20.5	19.7	29.2	0.0	33.6	21.7	smartseq
1450363	SRR3639217	SRP076212	SRS1488620	SRX1826662	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189464: 1ld-BTN17-C03 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189464		GSM2189464	1ld-BTN17-C03 BTN17 Mic-scRNA-Seq	1041044434	3447167	2016-07-18 10:56:32	543828770	1041044434	3447167	2	3447167	index:0,count:3447167,average:151,stdev:0|index:1,count:3447167,average:151,stdev:0	GSM2189464_r1						3.41	8.07	0.03	695412028	698477912	666564389	671524287	100.44	100.74	2851975	2647063	280.434	738.916	233	13070	66.28	69.24	3019962	1890194	3019962	1890194	66.36	65.66	3019962	1892527	3019962	1792306	207054668	29.77	0.84	0	3.54	0	0.13	0	0.07	0	0.00	0	17.07	0	2851975	0	302	0	293.45	0	1.73	0	0.02	0	1.19	0	0.00	0	105.17	0	1.11	0	29055	0	3447167	0	122137	0	4602	0	2254	0	0	0	588336	0	335	0	0	0	4483	0	961957	0	5781	0	972556	0	79.19	0	2729838	0	17237	875624	50.799094970122	3447167.0	2851975.0	29055.0	122137.0	4602.0	2254.0	0.0	588336.0	2729838.0	82.7	0.8	3.5	0.1	0.1	0.0	17.1	79.2	151	151	151.00	7	520522217	29.0	21.7	22.1	27.3	0.0	30.1	19.4	smartseq
1450364	SRR3640217	SRP076212	SRS1489025	SRX1827067	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189869: D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189869		GSM2189869	D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	289200	1928	2016-07-18 10:56:32	139158	289200	1928	2	1928	index:0,count:1928,average:75,stdev:0|index:1,count:1928,average:75,stdev:0	GSM2189869_r2						2.0	2.5	0.0	125597	136346	115545	127750	108.56	110.56	1071	1028	146.554	650.035	82	14	79.08	86.43	1198	847	1198	847	69.93	72.24	1198	749	1198	708	15612	12.43	1.30	0	4.72	0	0.05	0	0.05	0	0.00	0	44.35	0	1071	0	150	0	146.34	0	4.37	0	0.06	0	1.05	0	0.01	0	6.94	0	0.23	0	25	0	1928	0	91	0	1	0	1	0	0	0	855	0	0	0	0	0	2	0	229	0	4	0	235	0	50.83	0	980	0	185	189	1.021621621622	1928.0	1071.0	25.0	91.0	1.0	1.0	0.0	855.0	980.0	55.5	1.3	4.7	0.1	0.1	0.0	44.3	50.8	75	75	75.00	6	144600	23.1	27.4	26.1	23.4	0.0	35.1	29.3	smartseq
1450365	SRR3641217	SRP076212	SRS1489279	SRX1827322	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190124: H11_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190124		GSM2190124	H11_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq	38742150	258281	2016-07-18 10:56:32	13243462	38742150	258281	2	258281	index:0,count:258281,average:75,stdev:0|index:1,count:258281,average:75,stdev:0	GSM2190124_r2						1.27	2.35	0.02	32160436	35760125	30246881	34021665	111.19	112.48	239120	210578	218.864	1509.145	125	1201	83.28	88.88	259963	199142	259963	199142	72.97	73.9	259963	174478	259963	165576	3039489	9.45	1.72	0	5.84	0	0.23	0	0.08	0	0.00	0	7.11	0	239120	0	150	0	147.77	0	4.28	0	0.05	0	1.10	0	0.02	0	66.42	0	0.26	0	4447	0	258281	0	15071	0	588	0	219	0	0	0	18354	0	48	0	0	0	379	0	54332	0	402	0	55161	0	86.75	0	224049	0	20548	52326	2.546525209266	258281.0	239120.0	4447.0	15071.0	588.0	219.0	0.0	18354.0	224049.0	92.6	1.7	5.8	0.2	0.1	0.0	7.1	86.7	75	75	75.00	6	19371075	24.4	25.6	25.4	24.7	0.0	35.2	29.9	smartseq
1450378	SRR3638218	SRP076212	SRS1488254	SRX1826296	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189098: 1-0-1-1-BTN35-C22-1782070112-22ul-1-IL5413-N702-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189098		GSM2189098	1-0-1-1-BTN35-C22-1782070112-22ul-1-IL5413-N702-N507 BTN35 Mic-scRNA-Seq	41240550	274937	2016-07-18 10:56:32	19956677	41240550	274937	2	274937	index:0,count:274937,average:75,stdev:0|index:1,count:274937,average:75,stdev:0	GSM2189098_r1						2.47	3.16	0.1	34529773	32150919	32969006	30838272	93.11	93.54	245050	229589	236.249	974.482	206	1062	49.52	51.92	263937	121341	263937	121341	51.27	50.3	263937	125643	263937	117558	14192424	41.10	1.19	0	4.12	0	0.26	0	0.20	0	0.00	0	10.41	0	245050	0	150	0	147.97	0	1.44	0	0.01	0	1.16	0	0.00	0	47.13	0	0.83	0	3268	0	274937	0	11339	0	716	0	546	0	0	0	28625	0	15	0	0	0	172	0	21451	0	219	0	21857	0	85.01	0	233711	0	10619	21554	2.029757980977	274937.0	245050.0	3268.0	11339.0	716.0	546.0	0.0	28625.0	233711.0	89.1	1.2	4.1	0.3	0.2	0.0	10.4	85.0	75	75	75.00	7	20620275	28.7	21.4	21.6	28.3	0.0	33.4	21.6	smartseq
1450379	SRR3639218	SRP076212	SRS1488621	SRX1826663	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189465: 1ld-BTN17-C04 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;NSC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189465		GSM2189465	1ld-BTN17-C04 BTN17 Mic-scRNA-Seq	640201344	2119872	2016-07-18 10:56:32	327978077	640201344	2119872	2	2119872	index:0,count:2119872,average:151,stdev:0|index:1,count:2119872,average:151,stdev:0	GSM2189465_r1						8.24	2.05	0.11	427533331	429362439	396312904	400611062	100.43	101.08	1759156	1658845	280.909	805.262	230	8731	74.04	79.94	1918104	1302442	1918104	1302442	76.93	76.1	1918104	1353282	1918104	1239964	77302951	18.08	1.01	0	6.12	0	0.15	0	0.15	0	0.00	0	16.72	0	1759156	0	302	0	293.22	0	1.92	0	0.02	0	1.15	0	0.01	0	97.84	0	1.04	0	21510	0	2119872	0	129803	0	3190	0	3093	0	0	0	354433	0	684	0	0	0	3407	0	476409	0	4021	0	484521	0	76.86	0	1629353	0	6995	437825	62.591136526090	2119872.0	1759156.0	21510.0	129803.0	3190.0	3093.0	0.0	354433.0	1629353.0	83.0	1.0	6.1	0.2	0.1	0.0	16.7	76.9	151	151	151.00	7	320100672	28.4	21.9	22.2	27.5	0.0	30.6	19.9	smartseq
1450380	SRR3640218	SRP076212	SRS1489025	SRX1827067	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189869: D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189869		GSM2189869	D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	289800	1932	2016-07-18 10:56:32	140127	289800	1932	2	1932	index:0,count:1932,average:75,stdev:0|index:1,count:1932,average:75,stdev:0	GSM2189869_r3						1.38	2.52	0.0	130543	139252	122282	132288	106.67	108.18	1118	1056	146.208	1064.394	119	18	81.22	87.56	1231	908	1231	908	74.87	75.8	1231	837	1231	786	13028	9.98	1.40	0	4.19	0	0.16	0	0.16	0	0.00	0	41.82	0	1118	0	150	0	146.11	0	3.76	0	0.04	0	1.06	0	0.01	0	6.96	0	0.22	0	27	0	1932	0	81	0	3	0	3	0	0	0	808	0	0	0	0	0	1	0	278	0	2	0	281	0	53.67	0	1037	0	225	237	1.053333333333	1932.0	1118.0	27.0	81.0	3.0	3.0	0.0	808.0	1037.0	57.9	1.4	4.2	0.2	0.2	0.0	41.8	53.7	75	75	75.00	5	144900	23.1	27.5	25.7	23.7	0.0	35.1	29.5	smartseq
1450381	SRR3641218	SRP076212	SRS1489279	SRX1827322	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190124: H11_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190124		GSM2190124	H11_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq	38499150	256661	2016-07-18 10:56:32	13224457	38499150	256661	2	256661	index:0,count:256661,average:75,stdev:0|index:1,count:256661,average:75,stdev:0	GSM2190124_r3						1.25	2.46	0.02	32106588	35719403	30214196	34002879	111.25	112.54	238471	209786	219.353	1521.999	134	1195	83.42	88.98	259543	198931	259543	198931	73.01	73.95	259543	174096	259543	165313	2967733	9.24	1.72	0	5.81	0	0.25	0	0.09	0	0.00	0	6.75	0	238471	0	150	0	147.79	0	4.26	0	0.05	0	1.10	0	0.02	0	84.00	0	0.25	0	4410	0	256661	0	14909	0	642	0	229	0	0	0	17319	0	33	0	0	0	366	0	54533	0	405	0	55337	0	87.10	0	223562	0	20818	52445	2.519214141608	256661.0	238471.0	4410.0	14909.0	642.0	229.0	0.0	17319.0	223562.0	92.9	1.7	5.8	0.3	0.1	0.0	6.7	87.1	75	75	75.00	6	19249575	24.4	25.6	25.4	24.7	0.0	35.2	29.9	smartseq
1450394	SRR3638219	SRP076212	SRS1488254	SRX1826296	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189098: 1-0-1-1-BTN35-C22-1782070112-22ul-1-IL5413-N702-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189098		GSM2189098	1-0-1-1-BTN35-C22-1782070112-22ul-1-IL5413-N702-N507 BTN35 Mic-scRNA-Seq	41842950	278953	2016-07-18 10:56:32	20212415	41842950	278953	2	278953	index:0,count:278953,average:75,stdev:0|index:1,count:278953,average:75,stdev:0	GSM2189098_r2						2.44	3.17	0.1	35235650	32789202	33619011	31437896	93.06	93.51	249678	233379	239.294	1002.082	208	1079	49.76	52.2	268989	124228	268989	124228	51.55	50.58	268989	128708	268989	120373	14379518	40.81	1.17	0	4.20	0	0.27	0	0.22	0	0.00	0	10.00	0	249678	0	150	0	147.97	0	1.43	0	0.01	0	1.15	0	0.00	0	77.25	0	0.83	0	3251	0	278953	0	11710	0	763	0	608	0	0	0	27904	0	11	0	0	0	180	0	22192	0	221	0	22604	0	85.31	0	237968	0	10816	22425	2.073317307692	278953.0	249678.0	3251.0	11710.0	763.0	608.0	0.0	27904.0	237968.0	89.5	1.2	4.2	0.3	0.2	0.0	10.0	85.3	75	75	75.00	7	20921475	28.6	21.4	21.6	28.3	0.0	33.4	21.7	smartseq
1450395	SRR3639219	SRP076212	SRS1488624	SRX1826664	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189466: 1ld-BTN17-C10 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Vascular|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189466		GSM2189466	1ld-BTN17-C10 BTN17 Mic-scRNA-Seq	1144194648	3788724	2016-07-18 10:56:32	587218272	1144194648	3788724	2	3788724	index:0,count:3788724,average:151,stdev:0|index:1,count:3788724,average:151,stdev:0	GSM2189466_r1						9.89	1.34	0.02	758438473	739270378	713803294	697004881	97.47	97.65	3152697	3046571	272.933	586.258	233	16046	59.9	63.73	3365156	1888491	3365156	1888491	63.25	61.37	3365156	1994221	3365156	1818555	248792005	32.80	0.86	0	5.00	0	0.02	0	0.03	0	0.00	0	16.74	0	3152697	0	302	0	293.69	0	1.47	0	0.01	0	1.15	0	0.00	0	117.58	0	1.03	0	32673	0	3788724	0	189525	0	809	0	1072	0	0	0	634146	0	195	0	0	0	3275	0	504526	0	5471	0	513467	0	78.21	0	2963172	0	5826	462461	79.378819086852	3788724.0	3152697.0	32673.0	189525.0	809.0	1072.0	0.0	634146.0	2963172.0	83.2	0.9	5.0	0.0	0.0	0.0	16.7	78.2	151	151	151.00	7	572097324	28.9	21.7	21.7	27.7	0.0	30.6	20.0	smartseq
1450396	SRR3640219	SRP076212	SRS1489025	SRX1827067	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189869: D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189869		GSM2189869	D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	301650	2011	2016-07-18 10:56:32	144491	301650	2011	2	2011	index:0,count:2011,average:75,stdev:0|index:1,count:2011,average:75,stdev:0	GSM2189869_r4						1.3	3.14	0.46	141107	152141	131487	144512	107.82	109.91	1191	1132	143.272	1320.116	121	17	81.95	87.85	1305	976	1305	976	73.38	74.71	1305	874	1305	830	13625	9.66	1.39	0	3.98	0	0.00	0	0.05	0	0.00	0	40.73	0	1191	0	150	0	146.02	0	4.36	0	0.04	0	1.15	0	0.01	0	7.24	0	0.26	0	28	0	2011	0	80	0	0	0	1	0	0	0	819	0	2	0	0	0	0	0	251	0	2	0	255	0	55.25	0	1111	0	214	222	1.037383177570	2011.0	1191.0	28.0	80.0	0.0	1.0	0.0	819.0	1111.0	59.2	1.4	4.0	0.0	0.0	0.0	40.7	55.2	75	75	75.00	6	150825	23.3	27.3	26.0	23.3	0.0	35.1	29.5	smartseq
1450397	SRR3641219	SRP076212	SRS1489279	SRX1827322	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190124: H11_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190124		GSM2190124	H11_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq	38280300	255202	2016-07-18 10:56:32	13240187	38280300	255202	2	255202	index:0,count:255202,average:75,stdev:0|index:1,count:255202,average:75,stdev:0	GSM2190124_r4						1.25	2.35	0.02	31831082	35383624	29975905	33711388	111.16	112.46	236731	208568	219.224	1457.242	144	1213	83.47	88.96	257130	197604	257130	197604	73.07	74.02	257130	172976	257130	164430	2962478	9.31	1.68	0	5.72	0	0.22	0	0.10	0	0.00	0	6.92	0	236731	0	150	0	147.73	0	4.28	0	0.05	0	1.10	0	0.02	0	57.42	0	0.26	0	4281	0	255202	0	14592	0	565	0	247	0	0	0	17659	0	29	0	0	0	368	0	54333	0	372	0	55102	0	87.04	0	222139	0	20725	52230	2.520144752714	255202.0	236731.0	4281.0	14592.0	565.0	247.0	0.0	17659.0	222139.0	92.8	1.7	5.7	0.2	0.1	0.0	6.9	87.0	75	75	75.00	6	19140150	24.3	25.6	25.4	24.7	0.0	35.2	29.9	smartseq
1450507	SRR3638220	SRP076212	SRS1488254	SRX1826296	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189098: 1-0-1-1-BTN35-C22-1782070112-22ul-1-IL5413-N702-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189098		GSM2189098	1-0-1-1-BTN35-C22-1782070112-22ul-1-IL5413-N702-N507 BTN35 Mic-scRNA-Seq	41625750	277505	2016-07-18 10:56:32	20167229	41625750	277505	2	277505	index:0,count:277505,average:75,stdev:0|index:1,count:277505,average:75,stdev:0	GSM2189098_r3						2.42	3.21	0.11	34929446	32477247	33333102	31150521	92.98	93.45	247782	231736	236.788	993.644	188	1073	49.69	52.12	266965	123132	266965	123132	51.47	50.52	266965	127537	266965	119352	14234397	40.75	1.18	0	4.16	0	0.28	0	0.21	0	0.00	0	10.22	0	247782	0	150	0	147.97	0	1.41	0	0.01	0	1.14	0	0.00	0	62.44	0	0.84	0	3279	0	277505	0	11541	0	781	0	577	0	0	0	28365	0	16	0	0	0	145	0	21931	0	229	0	22321	0	85.13	0	236241	0	10782	22053	2.045353366722	277505.0	247782.0	3279.0	11541.0	781.0	577.0	0.0	28365.0	236241.0	89.3	1.2	4.2	0.3	0.2	0.0	10.2	85.1	75	75	75.00	7	20812875	28.7	21.5	21.6	28.2	0.0	33.4	21.7	smartseq
1450508	SRR3639220	SRP076212	SRS1488622	SRX1826665	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189467: 1ld-BTN17-C17 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Vascular|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189467		GSM2189467	1ld-BTN17-C17 BTN17 Mic-scRNA-Seq	1383545956	4581278	2016-07-18 10:56:32	709442921	1383545956	4581278	2	4581278	index:0,count:4581278,average:151,stdev:0|index:1,count:4581278,average:151,stdev:0	GSM2189467_r1						5.91	2.13	0.12	934096089	926452784	885616572	882053829	99.18	99.6	3821623	3640697	282.124	706.878	233	17606	55.37	58.47	4078867	2115917	4078867	2115917	56.9	55.29	4078867	2174375	4078867	2000794	372053936	39.83	0.89	0	4.43	0	0.11	0	0.07	0	0.00	0	16.40	0	3821623	0	302	0	293.75	0	1.68	0	0.02	0	1.19	0	0.00	0	93.18	0	1.05	0	40998	0	4581278	0	202770	0	4888	0	3319	0	0	0	751448	0	1151	0	0	0	5564	0	838161	0	8036	0	852912	0	78.99	0	3618853	0	10702	771357	72.075967108952	4581278.0	3821623.0	40998.0	202770.0	4888.0	3319.0	0.0	751448.0	3618853.0	83.4	0.9	4.4	0.1	0.1	0.0	16.4	79.0	151	151	151.00	7	691772978	28.8	21.6	22.0	27.6	0.0	30.7	20.0	smartseq
1450509	SRR3640220	SRP076212	SRS1489025	SRX1827067	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189869: D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189869		GSM2189869	D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	62344650	415631	2016-07-18 10:56:32	23277417	62344650	415631	2	415631	index:0,count:415631,average:75,stdev:0|index:1,count:415631,average:75,stdev:0	GSM2189869_r5						1.14	2.76	0.04	49135067	52234914	46374418	49726005	106.31	107.23	375731	334293	200.287	1303.581	126	2048	82.05	87.23	408173	308288	408173	308288	76.11	76.91	408173	285964	408173	271820	5368913	10.93	1.60	0	5.37	0	0.27	0	0.10	0	0.00	0	9.23	0	375731	0	150	0	147.46	0	3.77	0	0.04	0	1.13	0	0.01	0	106.88	0	0.26	0	6659	0	415631	0	22307	0	1135	0	406	0	0	0	38359	0	54	0	0	0	626	0	90747	0	485	0	91912	0	85.03	0	353424	0	25184	86050	3.416851969504	415631.0	375731.0	6659.0	22307.0	1135.0	406.0	0.0	38359.0	353424.0	90.4	1.6	5.4	0.3	0.1	0.0	9.2	85.0	75	75	75.00	6	31172325	24.7	25.3	24.9	25.1	0.0	34.7	28.0	smartseq
1450510	SRR3641220	SRP076212	SRS1489280	SRX1827323	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190125: H11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190125		GSM2190125	H11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	46764450	311763	2016-07-18 10:56:32	17512234	46764450	311763	2	311763	index:0,count:311763,average:75,stdev:0|index:1,count:311763,average:75,stdev:0	GSM2190125_r1						1.03	2.65	0.01	39385756	43252473	37053774	41090451	109.82	110.89	285155	249346	242.865	1576.028	144	1289	80.71	86.05	309948	230145	309948	230145	71.22	72.16	309948	203085	309948	193006	4508048	11.45	1.58	0	5.67	0	0.34	0	0.15	0	0.00	0	8.04	0	285155	0	150	0	147.98	0	4.35	0	0.06	0	1.11	0	0.02	0	93.53	0	0.28	0	4930	0	311763	0	17690	0	1065	0	477	0	0	0	25066	0	40	0	0	0	449	0	60420	0	432	0	61341	0	85.79	0	267465	0	22238	59330	2.667955751416	311763.0	285155.0	4930.0	17690.0	1065.0	477.0	0.0	25066.0	267465.0	91.5	1.6	5.7	0.3	0.2	0.0	8.0	85.8	75	75	75.00	6	23382225	24.4	25.4	25.4	24.7	0.0	34.8	28.1	smartseq
1450522	SRR3638221	SRP076212	SRS1488254	SRX1826296	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189098: 1-0-1-1-BTN35-C22-1782070112-22ul-1-IL5413-N702-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189098		GSM2189098	1-0-1-1-BTN35-C22-1782070112-22ul-1-IL5413-N702-N507 BTN35 Mic-scRNA-Seq	43506000	290040	2016-07-18 10:56:32	20815486	43506000	290040	2	290040	index:0,count:290040,average:75,stdev:0|index:1,count:290040,average:75,stdev:0	GSM2189098_r4						2.5	3.27	0.11	36464704	33888385	34788891	32483923	92.93	93.37	258392	241508	240.389	1030.313	187	1114	49.55	51.99	278601	128043	278601	128043	51.36	50.38	278601	132699	278601	124082	14917096	40.91	1.16	0	4.17	0	0.26	0	0.23	0	0.00	0	10.42	0	258392	0	150	0	148.01	0	1.38	0	0.01	0	1.16	0	0.00	0	65.26	0	0.77	0	3374	0	290040	0	12108	0	767	0	660	0	0	0	30221	0	14	0	0	0	176	0	23200	0	263	0	23653	0	84.91	0	246284	0	11101	23266	2.095847220971	290040.0	258392.0	3374.0	12108.0	767.0	660.0	0.0	30221.0	246284.0	89.1	1.2	4.2	0.3	0.2	0.0	10.4	84.9	75	75	75.00	7	21753000	28.8	21.4	21.6	28.3	0.0	33.7	22.0	smartseq
1450523	SRR3639221	SRP076212	SRS1488623	SRX1826666	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189468: 1ld-BTN17-C18 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189468		GSM2189468	1ld-BTN17-C18 BTN17 Mic-scRNA-Seq	1659355610	5494555	2016-07-18 10:56:32	850681054	1659355610	5494555	2	5494555	index:0,count:5494555,average:151,stdev:0|index:1,count:5494555,average:151,stdev:0	GSM2189468_r1						4.82	8.83	0.19	1135019046	1149315703	1080842253	1098798106	101.26	101.66	4640290	4261672	281.781	859.148	225	21032	71.7	75.4	4936517	3327268	4936517	3327268	71.09	70.35	4936517	3298752	4936517	3104237	262439079	23.12	0.87	0	4.14	0	0.12	0	0.05	0	0.00	0	15.38	0	4640290	0	302	0	293.67	0	1.73	0	0.02	0	1.19	0	0.00	0	112.39	0	1.06	0	47751	0	5494555	0	227591	0	6392	0	2667	0	0	0	845206	0	783	0	0	0	7429	0	1696012	0	12562	0	1716786	0	80.31	0	4412699	0	18841	1547811	82.151212780638	5494555.0	4640290.0	47751.0	227591.0	6392.0	2667.0	0.0	845206.0	4412699.0	84.5	0.9	4.1	0.1	0.0	0.0	15.4	80.3	151	151	151.00	7	829677805	28.6	21.8	22.2	27.4	0.0	30.7	20.0	smartseq
1450524	SRR3640221	SRP076212	SRS1489025	SRX1827067	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189869: D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189869		GSM2189869	D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	60316950	402113	2016-07-18 10:56:32	22487409	60316950	402113	2	402113	index:0,count:402113,average:75,stdev:0|index:1,count:402113,average:75,stdev:0	GSM2189869_r6						1.14	2.69	0.04	47578242	50595870	44931571	48196340	106.34	107.27	363861	324156	199.873	1292.369	121	1980	82.12	87.26	395362	298805	395362	298805	76.18	77.0	395362	277178	395362	263653	5207286	10.94	1.59	0	5.33	0	0.28	0	0.09	0	0.00	0	9.14	0	363861	0	150	0	147.49	0	3.78	0	0.03	0	1.10	0	0.01	0	120.63	0	0.27	0	6392	0	402113	0	21447	0	1115	0	378	0	0	0	36759	0	69	0	0	0	593	0	87886	0	514	0	89062	0	85.15	0	342414	0	24872	83278	3.348263107108	402113.0	363861.0	6392.0	21447.0	1115.0	378.0	0.0	36759.0	342414.0	90.5	1.6	5.3	0.3	0.1	0.0	9.1	85.2	75	75	75.00	6	30158475	24.6	25.3	24.9	25.1	0.0	34.8	28.0	smartseq
1450525	SRR3641221	SRP076212	SRS1489280	SRX1827323	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190125: H11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190125		GSM2190125	H11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	46228650	308191	2016-07-18 10:56:32	17389455	46228650	308191	2	308191	index:0,count:308191,average:75,stdev:0|index:1,count:308191,average:75,stdev:0	GSM2190125_r2						1.03	2.69	0.02	38852635	42684519	36535652	40522808	109.86	110.91	281111	245677	242.910	1593.314	153	1280	80.55	85.91	305832	226437	305832	226437	71.15	72.08	305832	199999	305832	189979	4500769	11.58	1.55	0	5.69	0	0.34	0	0.15	0	0.00	0	8.30	0	281111	0	150	0	147.98	0	4.40	0	0.06	0	1.11	0	0.02	0	65.26	0	0.30	0	4782	0	308191	0	17550	0	1047	0	453	0	0	0	25580	0	39	0	0	0	409	0	58927	0	447	0	59822	0	85.52	0	263561	0	21944	57862	2.636802770689	308191.0	281111.0	4782.0	17550.0	1047.0	453.0	0.0	25580.0	263561.0	91.2	1.6	5.7	0.3	0.1	0.0	8.3	85.5	75	75	75.00	6	23114325	24.4	25.4	25.4	24.8	0.0	34.7	28.0	smartseq
1450538	SRR3638222	SRP076212	SRS1488255	SRX1826297	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189099: 1-0-1-1-BTN35-C25-1782070112-12ul-1-IL5413-N706-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189099		GSM2189099	1-0-1-1-BTN35-C25-1782070112-12ul-1-IL5413-N706-N507 BTN35 Mic-scRNA-Seq	67196550	447977	2016-07-18 10:56:32	31763263	67196550	447977	2	447977	index:0,count:447977,average:75,stdev:0|index:1,count:447977,average:75,stdev:0	GSM2189099_r1						6.9	3.43	0.22	49033013	48322155	45379041	45110585	98.55	99.41	378898	364846	179.478	761.409	132	1846	48.83	52.77	419744	185013	419744	185013	52.22	49.98	419744	197844	419744	175257	20855321	42.53	1.33	0	6.31	0	0.21	0	0.30	0	0.00	0	14.91	0	378898	0	150	0	146.79	0	1.39	0	0.01	0	1.12	0	0.00	0	89.60	0	0.73	0	5953	0	447977	0	28266	0	932	0	1332	0	0	0	66815	0	21	0	0	0	184	0	22799	0	467	0	23471	0	78.27	0	350632	0	8241	22641	2.747360757190	447977.0	378898.0	5953.0	28266.0	932.0	1332.0	0.0	66815.0	350632.0	84.6	1.3	6.3	0.2	0.3	0.0	14.9	78.3	75	75	75.00	7	33598275	30.3	20.4	19.8	29.5	0.0	33.6	22.0	smartseq
1450539	SRR3639222	SRP076212	SRS1488625	SRX1826667	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189469: 1ld-BTN17-C24 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;NSC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189469		GSM2189469	1ld-BTN17-C24 BTN17 Mic-scRNA-Seq	923724380	3058690	2016-07-18 10:56:32	477549766	923724380	3058690	2	3058690	index:0,count:3058690,average:151,stdev:0|index:1,count:3058690,average:151,stdev:0	GSM2189469_r1						11.08	1.91	0.07	598039479	600362878	546949441	551215308	100.39	100.78	2518348	2374436	267.480	775.620	233	13182	72.6	79.52	2778754	1828407	2778754	1828407	77.58	76.07	2778754	1953647	2778754	1749224	109119393	18.25	0.88	0	7.16	0	0.17	0	0.12	0	0.00	0	17.38	0	2518348	0	302	0	292.68	0	1.69	0	0.02	0	1.20	0	0.00	0	78.09	0	1.13	0	26781	0	3058690	0	218975	0	5168	0	3552	0	0	0	531622	0	1019	0	0	0	4706	0	714611	0	5465	0	725801	0	75.18	0	2299373	0	7582	648928	85.587971511475	3058690.0	2518348.0	26781.0	218975.0	5168.0	3552.0	0.0	531622.0	2299373.0	82.3	0.9	7.2	0.2	0.1	0.0	17.4	75.2	151	151	151.00	7	461862190	28.6	21.8	22.1	27.4	0.0	30.7	19.9	smartseq
1450540	SRR3640222	SRP076212	SRS1489025	SRX1827067	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189869: D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189869		GSM2189869	D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	60993600	406624	2016-07-18 10:56:32	22912982	60993600	406624	2	406624	index:0,count:406624,average:75,stdev:0|index:1,count:406624,average:75,stdev:0	GSM2189869_r7						1.16	2.68	0.04	48217967	51272272	45536963	48847284	106.33	107.27	368499	328468	200.113	1286.086	122	2016	82.17	87.32	400736	302784	400736	302784	76.23	77.05	400736	280925	400736	267192	5253522	10.90	1.57	0	5.35	0	0.27	0	0.10	0	0.00	0	9.01	0	368499	0	150	0	147.52	0	3.82	0	0.03	0	1.11	0	0.01	0	112.60	0	0.27	0	6377	0	406624	0	21743	0	1083	0	395	0	0	0	36647	0	60	0	0	0	612	0	88810	0	507	0	89989	0	85.28	0	346756	0	24799	84364	3.401911367394	406624.0	368499.0	6377.0	21743.0	1083.0	395.0	0.0	36647.0	346756.0	90.6	1.6	5.3	0.3	0.1	0.0	9.0	85.3	75	75	75.00	6	30496800	24.7	25.3	24.9	25.1	0.0	34.7	27.9	smartseq
1450541	SRR3641222	SRP076212	SRS1489280	SRX1827323	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190125: H11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190125		GSM2190125	H11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	46102200	307348	2016-07-18 10:56:32	17472662	46102200	307348	2	307348	index:0,count:307348,average:75,stdev:0|index:1,count:307348,average:75,stdev:0	GSM2190125_r3						0.98	2.63	0.02	38852974	42701413	36539069	40552939	109.91	110.99	281080	244998	243.394	1547.795	146	1242	80.65	86.0	305519	226678	305519	226678	71.17	72.12	305519	200037	305519	190079	4475425	11.52	1.55	0	5.70	0	0.34	0	0.16	0	0.00	0	8.04	0	281080	0	150	0	147.98	0	4.41	0	0.06	0	1.13	0	0.02	0	92.20	0	0.30	0	4754	0	307348	0	17511	0	1060	0	506	0	0	0	24702	0	41	0	0	0	433	0	59967	0	435	0	60876	0	85.76	0	263569	0	22042	58847	2.669766808820	307348.0	281080.0	4754.0	17511.0	1060.0	506.0	0.0	24702.0	263569.0	91.5	1.5	5.7	0.3	0.2	0.0	8.0	85.8	75	75	75.00	6	23051100	24.4	25.4	25.4	24.8	0.0	34.6	27.6	smartseq
1450556	SRR3638223	SRP076212	SRS1488255	SRX1826297	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189099: 1-0-1-1-BTN35-C25-1782070112-12ul-1-IL5413-N706-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189099		GSM2189099	1-0-1-1-BTN35-C25-1782070112-12ul-1-IL5413-N706-N507 BTN35 Mic-scRNA-Seq	66477600	443184	2016-07-18 10:56:32	31348726	66477600	443184	2	443184	index:0,count:443184,average:75,stdev:0|index:1,count:443184,average:75,stdev:0	GSM2189099_r2						6.98	3.4	0.24	49056607	48388933	45408433	45169154	98.64	99.47	377891	363559	181.829	751.840	143	1862	49.09	53.05	418083	185519	418083	185519	52.53	50.27	418083	198525	418083	175776	20770108	42.34	1.36	0	6.37	0	0.21	0	0.31	0	0.00	0	14.21	0	377891	0	150	0	146.85	0	1.41	0	0.01	0	1.13	0	0.00	0	83.97	0	0.73	0	6014	0	443184	0	28216	0	926	0	1370	0	0	0	62997	0	14	0	0	0	155	0	22742	0	487	0	23398	0	78.90	0	349675	0	8332	22670	2.720835333653	443184.0	377891.0	6014.0	28216.0	926.0	1370.0	0.0	62997.0	349675.0	85.3	1.4	6.4	0.2	0.3	0.0	14.2	78.9	75	75	75.00	7	33238800	30.2	20.4	19.8	29.6	0.0	33.7	22.2	smartseq
1450557	SRR3639223	SRP076212	SRS1488626	SRX1826668	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189470: 1ld-BTN17-C26 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;OPC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189470		GSM2189470	1ld-BTN17-C26 BTN17 Mic-scRNA-Seq	1408056578	4662439	2016-07-18 10:56:32	727443054	1408056578	4662439	2	4662439	index:0,count:4662439,average:151,stdev:0|index:1,count:4662439,average:151,stdev:0	GSM2189470_r1						4.87	2.98	0.12	944572948	935000708	881792082	875920993	98.99	99.33	3909810	3636859	277.213	696.132	216	18092	66.14	71.01	4288080	2586114	4288080	2586114	68.74	67.71	4288080	2687461	4288080	2465971	255600092	27.06	0.80	0	5.74	0	0.16	0	0.12	0	0.00	0	15.87	0	3909810	0	302	0	293.29	0	1.54	0	0.01	0	1.20	0	0.00	0	94.83	0	1.08	0	37497	0	4662439	0	267735	0	7441	0	5422	0	0	0	739766	0	1062	0	0	0	9148	0	1362609	0	10537	0	1383356	0	78.12	0	3642075	0	18691	1268831	67.884596864801	4662439.0	3909810.0	37497.0	267735.0	7441.0	5422.0	0.0	739766.0	3642075.0	83.9	0.8	5.7	0.2	0.1	0.0	15.9	78.1	151	151	151.00	7	704028289	28.8	21.8	22.0	27.4	0.0	30.6	20.2	smartseq
1450558	SRR3640223	SRP076212	SRS1489025	SRX1827067	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189869: D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189869		GSM2189869	D11_1000700401-OGC7-coc_1_18ul_1 OGC07-sal FACS-scRNA-Seq	60799500	405330	2016-07-18 10:56:32	22844102	60799500	405330	2	405330	index:0,count:405330,average:75,stdev:0|index:1,count:405330,average:75,stdev:0	GSM2189869_r8						1.12	2.7	0.05	48077664	51113306	45406077	48688312	106.31	107.23	367301	326969	200.665	1312.953	134	2049	82.23	87.37	399162	302027	399162	302027	76.24	77.07	399162	280046	399162	266422	5202727	10.82	1.56	0	5.33	0	0.26	0	0.10	0	0.00	0	9.02	0	367301	0	150	0	147.50	0	3.78	0	0.04	0	1.11	0	0.01	0	104.23	0	0.27	0	6319	0	405330	0	21601	0	1066	0	387	0	0	0	36576	0	69	0	0	0	610	0	88991	0	445	0	90115	0	85.29	0	345700	0	24835	84300	3.394403060197	405330.0	367301.0	6319.0	21601.0	1066.0	387.0	0.0	36576.0	345700.0	90.6	1.6	5.3	0.3	0.1	0.0	9.0	85.3	75	75	75.00	6	30399750	24.7	25.3	24.9	25.1	0.0	34.7	27.9	smartseq
1450559	SRR3641223	SRP076212	SRS1489280	SRX1827323	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190125: H11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190125		GSM2190125	H11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	45949350	306329	2016-07-18 10:56:32	17426833	45949350	306329	2	306329	index:0,count:306329,average:75,stdev:0|index:1,count:306329,average:75,stdev:0	GSM2190125_r4						1.06	2.68	0.02	38683449	42502934	36378279	40370857	109.87	110.98	279731	244249	244.139	1592.832	146	1248	80.69	86.06	304257	225725	304257	225725	71.23	72.16	304257	199239	304257	189275	4431193	11.46	1.59	0	5.70	0	0.34	0	0.17	0	0.00	0	8.18	0	279731	0	150	0	148.01	0	4.41	0	0.06	0	1.10	0	0.02	0	84.83	0	0.31	0	4867	0	306329	0	17448	0	1029	0	511	0	0	0	25058	0	37	0	0	0	431	0	58763	0	406	0	59637	0	85.62	0	262283	0	21914	57730	2.634388975084	306329.0	279731.0	4867.0	17448.0	1029.0	511.0	0.0	25058.0	262283.0	91.3	1.6	5.7	0.3	0.2	0.0	8.2	85.6	75	75	75.00	6	22974675	24.4	25.4	25.4	24.8	0.0	34.7	27.7	smartseq
1450571	SRR3638224	SRP076212	SRS1488255	SRX1826297	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189099: 1-0-1-1-BTN35-C25-1782070112-12ul-1-IL5413-N706-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189099		GSM2189099	1-0-1-1-BTN35-C25-1782070112-12ul-1-IL5413-N706-N507 BTN35 Mic-scRNA-Seq	67026150	446841	2016-07-18 10:56:32	31718312	67026150	446841	2	446841	index:0,count:446841,average:75,stdev:0|index:1,count:446841,average:75,stdev:0	GSM2189099_r3						6.9	3.4	0.22	49078016	48397282	45443866	45189864	98.61	99.44	378819	364622	180.184	739.416	133	1923	49.09	53.04	419453	185977	419453	185977	52.41	50.18	419453	198533	419453	175935	20755764	42.29	1.37	0	6.31	0	0.20	0	0.29	0	0.00	0	14.73	0	378819	0	150	0	146.84	0	1.39	0	0.01	0	1.10	0	0.00	0	76.60	0	0.75	0	6110	0	446841	0	28200	0	916	0	1276	0	0	0	65830	0	19	0	0	0	162	0	22885	0	463	0	23529	0	78.47	0	350619	0	8318	22805	2.741644626112	446841.0	378819.0	6110.0	28200.0	916.0	1276.0	0.0	65830.0	350619.0	84.8	1.4	6.3	0.2	0.3	0.0	14.7	78.5	75	75	75.00	7	33513075	30.2	20.4	19.9	29.5	0.0	33.6	22.0	smartseq
1450572	SRR3639224	SRP076212	SRS1488627	SRX1826669	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189471: 1ld-BTN17-C28 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Vascular|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189471		GSM2189471	1ld-BTN17-C28 BTN17 Mic-scRNA-Seq	1527727098	5058699	2016-07-18 10:56:32	792597817	1527727098	5058699	2	5058699	index:0,count:5058699,average:151,stdev:0|index:1,count:5058699,average:151,stdev:0	GSM2189471_r1						4.65	2.67	0.08	1005382349	1004512264	963648889	966170949	99.91	100.26	4211274	4047453	266.572	619.166	230	21233	52.05	54.37	4437732	2191970	4437732	2191970	52.08	50.7	4437732	2193244	4437732	2043799	444400986	44.20	0.80	0	3.56	0	0.09	0	0.05	0	0.00	0	16.61	0	4211274	0	302	0	293.69	0	1.53	0	0.01	0	1.16	0	0.00	0	123.89	0	1.07	0	40679	0	5058699	0	179839	0	4543	0	2636	0	0	0	840246	0	387	0	0	0	6512	0	835009	0	6691	0	848599	0	79.69	0	4031435	0	9900	751601	75.919292929293	5058699.0	4211274.0	40679.0	179839.0	4543.0	2636.0	0.0	840246.0	4031435.0	83.2	0.8	3.6	0.1	0.1	0.0	16.6	79.7	151	151	151.00	7	763863549	29.2	21.5	21.6	27.7	0.0	30.3	19.9	smartseq
1450573	SRR3640224	SRP076212	SRS1489026	SRX1827068	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189870: D11_1000700602-OGC11-sal_1_6ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189870		GSM2189870	D11_1000700602-OGC11-sal_1_6ul_1 OGC11-sal FACS-scRNA-Seq	38136600	254244	2016-07-18 10:56:32	14127702	38136600	254244	2	254244	index:0,count:254244,average:75,stdev:0|index:1,count:254244,average:75,stdev:0	GSM2189870_r1						1.15	2.27	0.02	26144711	30733910	24140056	28938001	117.55	119.88	216801	207031	149.387	623.037	110	1937	80.7	88.02	240786	174964	240786	174964	62.82	64.33	240786	136194	240786	127870	2337446	8.94	2.26	0	7.09	0	0.21	0	0.10	0	0.00	0	14.42	0	216801	0	150	0	146.72	0	4.52	0	0.07	0	1.08	0	0.02	0	76.27	0	0.32	0	5748	0	254244	0	18028	0	529	0	261	0	0	0	36653	0	20	0	0	0	227	0	36336	0	294	0	36877	0	78.18	0	198773	0	12213	32476	2.659133709981	254244.0	216801.0	5748.0	18028.0	529.0	261.0	0.0	36653.0	198773.0	85.3	2.3	7.1	0.2	0.1	0.0	14.4	78.2	75	75	75.00	6	19068300	24.0	26.1	25.2	24.7	0.0	34.8	28.1	smartseq
1450574	SRR3641224	SRP076212	SRS1489282	SRX1827324	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190126: H11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190126		GSM2190126	H11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	57802200	385348	2016-07-18 10:56:32	21258885	57802200	385348	2	385348	index:0,count:385348,average:75,stdev:0|index:1,count:385348,average:75,stdev:0	GSM2190126_r1						1.03	2.36	0.03	47533385	53033201	44377554	50127003	111.57	112.96	355090	321184	200.383	1209.507	146	2025	80.81	86.89	389006	286942	389006	286942	69.29	70.66	389006	246042	389006	233351	4965316	10.45	1.69	0	6.45	0	0.29	0	0.16	0	0.00	0	7.40	0	355090	0	150	0	147.80	0	4.62	0	0.07	0	1.09	0	0.02	0	115.60	0	0.27	0	6525	0	385348	0	24846	0	1128	0	603	0	0	0	28527	0	52	0	0	0	518	0	74742	0	605	0	75917	0	85.70	0	330244	0	23437	71827	3.064684046593	385348.0	355090.0	6525.0	24846.0	1128.0	603.0	0.0	28527.0	330244.0	92.1	1.7	6.4	0.3	0.2	0.0	7.4	85.7	75	75	75.00	6	28901100	24.5	25.3	25.2	25.0	0.0	34.8	28.4	smartseq
1450587	SRR3638225	SRP076212	SRS1488255	SRX1826297	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189099: 1-0-1-1-BTN35-C25-1782070112-12ul-1-IL5413-N706-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189099		GSM2189099	1-0-1-1-BTN35-C25-1782070112-12ul-1-IL5413-N706-N507 BTN35 Mic-scRNA-Seq	69249000	461660	2016-07-18 10:56:32	32365895	69249000	461660	2	461660	index:0,count:461660,average:75,stdev:0|index:1,count:461660,average:75,stdev:0	GSM2189099_r4						6.88	3.4	0.23	50789220	50124028	47036821	46808107	98.69	99.51	391430	376404	181.617	757.848	134	1938	48.92	52.83	433126	191495	433126	191495	52.26	50.01	433126	204577	433126	181264	21630573	42.59	1.34	0	6.28	0	0.20	0	0.31	0	0.00	0	14.70	0	391430	0	150	0	146.87	0	1.42	0	0.01	0	1.12	0	0.00	0	79.14	0	0.68	0	6201	0	461660	0	28986	0	941	0	1444	0	0	0	67845	0	18	0	0	0	160	0	24052	0	459	0	24689	0	78.51	0	362444	0	8472	23892	2.820113314448	461660.0	391430.0	6201.0	28986.0	941.0	1444.0	0.0	67845.0	362444.0	84.8	1.3	6.3	0.2	0.3	0.0	14.7	78.5	75	75	75.00	7	34624500	30.2	20.4	19.8	29.6	0.0	33.9	22.4	smartseq
1450588	SRR3639225	SRP076212	SRS1488628	SRX1826670	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189472: 1ld-BTN17-C44 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189472		GSM2189472	1ld-BTN17-C44 BTN17 Mic-scRNA-Seq	1385194876	4586738	2016-07-18 10:56:32	710909964	1385194876	4586738	2	4586738	index:0,count:4586738,average:151,stdev:0|index:1,count:4586738,average:151,stdev:0	GSM2189472_r1						6.3	2.11	1.41	945451909	912697814	893626683	867091152	96.54	97.03	3847363	3636167	284.771	746.803	233	17850	59.1	62.61	4149256	2273808	4149256	2273808	61.02	59.9	4149256	2347786	4149256	2175480	313551446	33.16	0.83	0	4.70	0	0.19	0	0.08	0	0.00	0	15.85	0	3847363	0	302	0	293.82	0	1.64	0	0.02	0	1.16	0	0.01	0	121.41	0	1.06	0	37906	0	4586738	0	215429	0	8703	0	3538	0	0	0	727134	0	117	0	0	0	8006	0	979551	0	9068	0	996742	0	79.18	0	3631934	0	11187	904176	80.823813354787	4586738.0	3847363.0	37906.0	215429.0	8703.0	3538.0	0.0	727134.0	3631934.0	83.9	0.8	4.7	0.2	0.1	0.0	15.9	79.2	151	151	151.00	7	692597438	28.5	22.0	22.2	27.3	0.0	30.7	20.0	smartseq
1450589	SRR3640225	SRP076212	SRS1489026	SRX1827068	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189870: D11_1000700602-OGC11-sal_1_6ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189870		GSM2189870	D11_1000700602-OGC11-sal_1_6ul_1 OGC11-sal FACS-scRNA-Seq	36868950	245793	2016-07-18 10:56:32	13643173	36868950	245793	2	245793	index:0,count:245793,average:75,stdev:0|index:1,count:245793,average:75,stdev:0	GSM2189870_r2						1.11	2.28	0.01	25269277	29722880	23355624	28003042	117.62	119.9	209329	200097	150.510	597.298	110	1861	80.92	88.17	231940	169398	231940	169398	63.02	64.55	231940	131910	231940	124011	2231744	8.83	2.17	0	7.00	0	0.23	0	0.10	0	0.00	0	14.50	0	209329	0	150	0	146.78	0	4.54	0	0.08	0	1.08	0	0.02	0	63.20	0	0.33	0	5328	0	245793	0	17198	0	568	0	257	0	0	0	35639	0	23	0	0	0	227	0	35418	0	318	0	35986	0	78.17	0	192131	0	12062	31579	2.618056707014	245793.0	209329.0	5328.0	17198.0	568.0	257.0	0.0	35639.0	192131.0	85.2	2.2	7.0	0.2	0.1	0.0	14.5	78.2	75	75	75.00	6	18434475	24.0	26.1	25.2	24.7	0.0	34.8	28.2	smartseq
1450590	SRR3641225	SRP076212	SRS1489282	SRX1827324	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190126: H11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190126		GSM2190126	H11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	57360900	382406	2016-07-18 10:56:32	21167137	57360900	382406	2	382406	index:0,count:382406,average:75,stdev:0|index:1,count:382406,average:75,stdev:0	GSM2190126_r2						1.03	2.43	0.04	47065043	52456976	43924640	49549968	111.46	112.81	351341	317857	201.008	1188.483	125	1968	80.72	86.82	385363	283602	385363	283602	69.36	70.69	385363	243680	385363	230885	4904474	10.42	1.69	0	6.46	0	0.27	0	0.15	0	0.00	0	7.71	0	351341	0	150	0	147.78	0	4.56	0	0.06	0	1.07	0	0.02	0	114.72	0	0.29	0	6477	0	382406	0	24702	0	1023	0	560	0	0	0	29482	0	50	0	0	0	564	0	73796	0	541	0	74951	0	85.42	0	326639	0	23431	70928	3.027100849302	382406.0	351341.0	6477.0	24702.0	1023.0	560.0	0.0	29482.0	326639.0	91.9	1.7	6.5	0.3	0.1	0.0	7.7	85.4	75	75	75.00	6	28680450	24.6	25.3	25.2	25.0	0.0	34.8	28.3	smartseq
1450605	SRR3638226	SRP076212	SRS1488256	SRX1826298	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189100: 1-0-1-1-BTN35-C36-1782070112-18ul-1-IL5413-N711-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189100		GSM2189100	1-0-1-1-BTN35-C36-1782070112-18ul-1-IL5413-N711-N507 BTN35 Mic-scRNA-Seq	75233100	501554	2016-07-18 10:56:32	35622017	75233100	501554	2	501554	index:0,count:501554,average:75,stdev:0|index:1,count:501554,average:75,stdev:0	GSM2189100_r1						5.11	3.38	0.05	54773478	53704142	50850826	50245675	98.05	98.81	422048	397301	183.903	913.602	103	2042	56.61	61.01	467802	238933	467802	238933	59.88	58.46	467802	252727	467802	228940	19009731	34.71	1.30	0	6.07	0	0.19	0	0.25	0	0.00	0	15.41	0	422048	0	150	0	146.78	0	1.43	0	0.01	0	1.20	0	0.00	0	64.49	0	0.75	0	6505	0	501554	0	30448	0	940	0	1275	0	0	0	77291	0	41	0	0	0	299	0	41780	0	398	0	42518	0	78.08	0	391600	0	13744	41303	3.005165890570	501554.0	422048.0	6505.0	30448.0	940.0	1275.0	0.0	77291.0	391600.0	84.1	1.3	6.1	0.2	0.3	0.0	15.4	78.1	75	75	75.00	7	37616550	29.6	21.2	20.6	28.6	0.0	33.5	21.9	smartseq
1450606	SRR3639226	SRP076212	SRS1488629	SRX1826671	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189473: 1ld-BTN17-C58 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Vascular|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189473		GSM2189473	1ld-BTN17-C58 BTN17 Mic-scRNA-Seq	1024622580	3392790	2016-07-18 10:56:32	527395794	1024622580	3392790	2	3392790	index:0,count:3392790,average:151,stdev:0|index:1,count:3392790,average:151,stdev:0	GSM2189473_r1						8.34	1.67	0.09	678410525	674566332	635552208	635422085	99.43	99.98	2800618	2680191	277.619	609.880	230	14547	68.95	73.68	3012177	1931068	3012177	1931068	71.38	70.32	3012177	1999175	3012177	1842918	165904070	24.45	0.86	0	5.30	0	0.10	0	0.08	0	0.00	0	17.27	0	2800618	0	302	0	293.31	0	1.61	0	0.01	0	1.16	0	0.00	0	95.42	0	1.07	0	29108	0	3392790	0	179687	0	3371	0	2705	0	0	0	586096	0	359	0	0	0	2964	0	581635	0	4443	0	589401	0	77.25	0	2620931	0	6939	528586	76.176106067157	3392790.0	2800618.0	29108.0	179687.0	3371.0	2705.0	0.0	586096.0	2620931.0	82.5	0.9	5.3	0.1	0.1	0.0	17.3	77.3	151	151	151.00	7	512311290	28.8	21.6	21.9	27.6	0.0	30.6	19.9	smartseq
1450607	SRR3640226	SRP076212	SRS1489026	SRX1827068	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189870: D11_1000700602-OGC11-sal_1_6ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189870		GSM2189870	D11_1000700602-OGC11-sal_1_6ul_1 OGC11-sal FACS-scRNA-Seq	37028400	246856	2016-07-18 10:56:32	13813249	37028400	246856	2	246856	index:0,count:246856,average:75,stdev:0|index:1,count:246856,average:75,stdev:0	GSM2189870_r3						1.1	2.33	0.02	25480431	29983668	23580346	28270545	117.67	119.89	210932	201665	150.185	623.514	110	1812	80.93	88.05	233167	170712	233167	170712	63.06	64.55	233167	133017	233167	125158	2281806	8.96	2.16	0	6.91	0	0.23	0	0.10	0	0.00	0	14.23	0	210932	0	150	0	146.78	0	4.52	0	0.07	0	1.09	0	0.02	0	74.06	0	0.32	0	5330	0	246856	0	17046	0	557	0	246	0	0	0	35121	0	22	0	0	0	275	0	35879	0	332	0	36508	0	78.54	0	193886	0	12182	32141	2.638400919389	246856.0	210932.0	5330.0	17046.0	557.0	246.0	0.0	35121.0	193886.0	85.4	2.2	6.9	0.2	0.1	0.0	14.2	78.5	75	75	75.00	6	18514200	24.0	26.1	25.2	24.7	0.0	34.7	28.0	smartseq
1450621	SRR3638227	SRP076212	SRS1488256	SRX1826298	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189100: 1-0-1-1-BTN35-C36-1782070112-18ul-1-IL5413-N711-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189100		GSM2189100	1-0-1-1-BTN35-C36-1782070112-18ul-1-IL5413-N711-N507 BTN35 Mic-scRNA-Seq	74352900	495686	2016-07-18 10:56:32	35091855	74352900	495686	2	495686	index:0,count:495686,average:75,stdev:0|index:1,count:495686,average:75,stdev:0	GSM2189100_r2						5.05	3.38	0.06	54809975	53751681	50904139	50313180	98.07	98.84	421343	395588	186.086	933.991	143	2027	56.97	61.41	467387	240054	467387	240054	60.29	58.87	467387	254019	467387	230093	18836318	34.37	1.33	0	6.15	0	0.20	0	0.27	0	0.00	0	14.53	0	421343	0	150	0	146.80	0	1.49	0	0.01	0	1.23	0	0.00	0	104.97	0	0.73	0	6593	0	495686	0	30463	0	1003	0	1327	0	0	0	72013	0	40	0	0	0	323	0	42466	0	404	0	43233	0	78.86	0	390880	0	14081	42058	2.986861728570	495686.0	421343.0	6593.0	30463.0	1003.0	1327.0	0.0	72013.0	390880.0	85.0	1.3	6.1	0.2	0.3	0.0	14.5	78.9	75	75	75.00	7	37176450	29.5	21.2	20.6	28.7	0.0	33.6	22.1	smartseq
1450622	SRR3639227	SRP076212	SRS1488630	SRX1826672	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189474: 1ld-BTN17-C86 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Vascular|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189474		GSM2189474	1ld-BTN17-C86 BTN17 Mic-scRNA-Seq	1352551394	4478647	2016-07-18 10:56:32	690758088	1352551394	4478647	2	4478647	index:0,count:4478647,average:151,stdev:0|index:1,count:4478647,average:151,stdev:0	GSM2189474_r1						6.11	2.09	0.02	916691281	935452713	868186352	888981320	102.05	102.4	3763899	3548165	283.229	722.948	230	19441	80.28	84.9	4012486	3021749	4012486	3021749	80.38	79.73	4012486	3025280	4012486	2837785	130165912	14.20	0.91	0	4.57	0	0.06	0	0.06	0	0.00	0	15.84	0	3763899	0	302	0	293.87	0	1.48	0	0.01	0	1.23	0	0.00	0	102.70	0	1.02	0	40589	0	4478647	0	204687	0	2702	0	2575	0	0	0	709471	0	363	0	0	0	5264	0	1122075	0	5305	0	1133007	0	79.47	0	3559212	0	6723	1037500	154.320987654321	4478647.0	3763899.0	40589.0	204687.0	2702.0	2575.0	0.0	709471.0	3559212.0	84.0	0.9	4.6	0.1	0.1	0.0	15.8	79.5	151	151	151.00	7	676275697	28.1	22.3	22.8	26.8	0.0	30.7	19.8	smartseq
1450623	SRR3640227	SRP076212	SRS1489026	SRX1827068	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189870: D11_1000700602-OGC11-sal_1_6ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189870		GSM2189870	D11_1000700602-OGC11-sal_1_6ul_1 OGC11-sal FACS-scRNA-Seq	36952200	246348	2016-07-18 10:56:32	13780625	36952200	246348	2	246348	index:0,count:246348,average:75,stdev:0|index:1,count:246348,average:75,stdev:0	GSM2189870_r4						1.1	2.37	0.01	25468952	29949518	23532567	28192895	117.59	119.8	210642	201283	150.539	605.589	110	1824	80.75	88.01	233551	170086	233551	170086	62.93	64.47	233551	132565	233551	124591	2284029	8.97	2.10	0	7.05	0	0.24	0	0.10	0	0.00	0	14.15	0	210642	0	150	0	146.80	0	4.54	0	0.07	0	1.07	0	0.02	0	63.35	0	0.33	0	5174	0	246348	0	17375	0	584	0	255	0	0	0	34867	0	36	0	0	0	241	0	35071	0	310	0	35658	0	78.45	0	193267	0	12059	31442	2.607347209553	246348.0	210642.0	5174.0	17375.0	584.0	255.0	0.0	34867.0	193267.0	85.5	2.1	7.1	0.2	0.1	0.0	14.2	78.5	75	75	75.00	6	18476100	24.0	26.1	25.2	24.7	0.0	34.7	28.0	smartseq
1450636	SRR3638228	SRP076212	SRS1488256	SRX1826298	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189100: 1-0-1-1-BTN35-C36-1782070112-18ul-1-IL5413-N711-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189100		GSM2189100	1-0-1-1-BTN35-C36-1782070112-18ul-1-IL5413-N711-N507 BTN35 Mic-scRNA-Seq	74958900	499726	2016-07-18 10:56:32	35539878	74958900	499726	2	499726	index:0,count:499726,average:75,stdev:0|index:1,count:499726,average:75,stdev:0	GSM2189100_r3						5.06	3.37	0.05	54695694	53622029	50814259	50202837	98.04	98.8	420855	395543	184.777	893.434	143	2017	56.99	61.4	466581	239861	466581	239861	60.21	58.85	466581	253378	466581	229884	18806393	34.38	1.29	0	6.04	0	0.20	0	0.26	0	0.00	0	15.32	0	420855	0	150	0	146.79	0	1.42	0	0.01	0	1.24	0	0.00	0	78.22	0	0.76	0	6467	0	499726	0	30196	0	1016	0	1306	0	0	0	76549	0	47	0	0	0	316	0	42344	0	418	0	43125	0	78.17	0	390659	0	13875	41949	3.023351351351	499726.0	420855.0	6467.0	30196.0	1016.0	1306.0	0.0	76549.0	390659.0	84.2	1.3	6.0	0.2	0.3	0.0	15.3	78.2	75	75	75.00	7	37479450	29.6	21.2	20.6	28.6	0.0	33.5	21.9	smartseq
1450637	SRR3639228	SRP076212	SRS1488631	SRX1826673	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189475: 1ll-BTN17-C02 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189475		GSM2189475	1ll-BTN17-C02 BTN17 Mic-scRNA-Seq	1179633744	3906072	2016-07-18 10:56:32	606576762	1179633744	3906072	2	3906072	index:0,count:3906072,average:151,stdev:0|index:1,count:3906072,average:151,stdev:0	GSM2189475_r1						2.66	9.18	0.03	806099935	814833408	770573763	781623959	101.08	101.43	3283548	2969249	285.739	940.318	225	14749	79.05	82.8	3491845	2595489	3491845	2595489	78.37	78.16	3491845	2573153	3491845	2450103	127694123	15.84	0.92	0	3.81	0	0.14	0	0.05	0	0.00	0	15.75	0	3283548	0	302	0	293.35	0	1.80	0	0.02	0	1.16	0	0.00	0	112.49	0	1.08	0	36059	0	3906072	0	148941	0	5428	0	1987	0	0	0	615109	0	860	0	0	0	6656	0	1430700	0	10598	0	1448814	0	80.25	0	3134607	0	20748	1305628	62.927896664739	3906072.0	3283548.0	36059.0	148941.0	5428.0	1987.0	0.0	615109.0	3134607.0	84.1	0.9	3.8	0.1	0.1	0.0	15.7	80.2	151	151	151.00	7	589816872	28.0	22.4	22.8	26.8	0.0	30.6	20.0	smartseq
1450638	SRR3640228	SRP076212	SRS1489027	SRX1827069	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189871: D11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189871		GSM2189871	D11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	49670700	331138	2016-07-18 10:56:32	18578907	49670700	331138	2	331138	index:0,count:331138,average:75,stdev:0|index:1,count:331138,average:75,stdev:0	GSM2189871_r1						1.2	2.35	0.03	42818665	46478829	40304859	44155885	108.55	109.55	310298	269629	238.779	1618.093	148	1387	82.45	87.85	336487	255835	336487	255835	74.27	75.24	336487	230447	336487	219123	4217961	9.85	1.53	0	5.76	0	0.27	0	0.11	0	0.00	0	5.91	0	310298	0	150	0	148.05	0	4.34	0	0.05	0	1.08	0	0.02	0	91.70	0	0.27	0	5058	0	331138	0	19073	0	909	0	373	0	0	0	19558	0	47	0	0	0	475	0	69558	0	484	0	70564	0	87.95	0	291225	0	23531	67924	2.886575156177	331138.0	310298.0	5058.0	19073.0	909.0	373.0	0.0	19558.0	291225.0	93.7	1.5	5.8	0.3	0.1	0.0	5.9	87.9	75	75	75.00	6	24835350	24.4	25.4	25.4	24.8	0.0	34.8	28.3	smartseq
1450639	SRR3641228	SRP076212	SRS1489283	SRX1827325	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190127: H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190127		GSM2190127	H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	5640600	37604	2016-07-18 10:56:32	1903108	5640600	37604	2	37604	index:0,count:37604,average:75,stdev:0|index:1,count:37604,average:75,stdev:0	GSM2190127_r1						0.95	2.4	0.03	3740280	4142903	3499172	3924607	110.76	112.16	31691	30027	143.048	631.493	100	306	83.08	89.25	34780	26328	34780	26328	71.85	73.51	34780	22771	34780	21685	320650	8.57	2.09	0	5.83	0	0.27	0	0.12	0	0.00	0	15.33	0	31691	0	150	0	146.61	0	3.86	0	0.04	0	1.13	0	0.02	0	19.34	0	0.23	0	786	0	37604	0	2193	0	102	0	45	0	0	0	5766	0	4	0	0	0	49	0	7474	0	52	0	7579	0	78.44	0	29498	0	4762	6388	1.341453170937	37604.0	31691.0	786.0	2193.0	102.0	45.0	0.0	5766.0	29498.0	84.3	2.1	5.8	0.3	0.1	0.0	15.3	78.4	75	75	75.00	6	2820300	24.2	25.9	24.9	24.9	0.0	35.3	30.4	smartseq
1450652	SRR3638229	SRP076212	SRS1488256	SRX1826298	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189100: 1-0-1-1-BTN35-C36-1782070112-18ul-1-IL5413-N711-N507 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189100		GSM2189100	1-0-1-1-BTN35-C36-1782070112-18ul-1-IL5413-N711-N507 BTN35 Mic-scRNA-Seq	76601850	510679	2016-07-18 10:56:32	35842268	76601850	510679	2	510679	index:0,count:510679,average:75,stdev:0|index:1,count:510679,average:75,stdev:0	GSM2189100_r4						5.1	3.42	0.05	56153931	55092039	52178696	51587445	98.11	98.87	431488	405267	186.207	919.112	143	2025	56.83	61.21	478655	245206	478655	245206	60.1	58.7	478655	259345	478655	235146	19434344	34.61	1.35	0	6.05	0	0.18	0	0.28	0	0.00	0	15.05	0	431488	0	150	0	146.83	0	1.48	0	0.01	0	1.27	0	0.00	0	76.60	0	0.69	0	6882	0	510679	0	30885	0	939	0	1416	0	0	0	76836	0	38	0	0	0	306	0	43196	0	396	0	43936	0	78.45	0	400603	0	13912	42684	3.068142610696	510679.0	431488.0	6882.0	30885.0	939.0	1416.0	0.0	76836.0	400603.0	84.5	1.3	6.0	0.2	0.3	0.0	15.0	78.4	75	75	75.00	7	38300925	29.6	21.2	20.5	28.7	0.0	33.8	22.3	smartseq
1450653	SRR3639229	SRP076212	SRS1488632	SRX1826674	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189476: 1ll-BTN17-C07 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;NSC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189476		GSM2189476	1ll-BTN17-C07 BTN17 Mic-scRNA-Seq	1281792794	4244347	2016-07-18 10:56:32	662083398	1281792794	4244347	2	4244347	index:0,count:4244347,average:151,stdev:0|index:1,count:4244347,average:151,stdev:0	GSM2189476_r1						2.0	2.3	0.17	839584129	830555934	817360050	812765226	98.92	99.44	3463920	3371701	274.493	618.677	233	18936	53.73	55.23	3599055	1861076	3599055	1861076	52.76	52.35	3599055	1827725	3599055	1764116	360994933	43.00	0.87	0	2.22	0	0.05	0	0.06	0	0.00	0	18.28	0	3463920	0	302	0	293.57	0	1.63	0	0.02	0	1.19	0	0.01	0	90.95	0	1.08	0	36826	0	4244347	0	94270	0	2064	0	2494	0	0	0	775869	0	140	0	0	0	2445	0	421214	0	8418	0	432217	0	79.39	0	3369650	0	4860	386751	79.578395061728	4244347.0	3463920.0	36826.0	94270.0	2064.0	2494.0	0.0	775869.0	3369650.0	81.6	0.9	2.2	0.0	0.1	0.0	18.3	79.4	151	151	151.00	7	640896397	29.2	21.3	21.6	27.8	0.0	30.4	19.7	smartseq
1450654	SRR3640229	SRP076212	SRS1489027	SRX1827069	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189871: D11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189871		GSM2189871	D11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	49501350	330009	2016-07-18 10:56:32	18621657	49501350	330009	2	330009	index:0,count:330009,average:75,stdev:0|index:1,count:330009,average:75,stdev:0	GSM2189871_r2						1.16	2.36	0.03	42539438	46195241	40014088	43868905	108.59	109.63	308402	267835	239.146	1588.490	146	1401	82.4	87.87	335025	254127	335025	254127	74.27	75.24	335025	229043	335025	217610	4215503	9.91	1.54	0	5.81	0	0.30	0	0.10	0	0.00	0	6.15	0	308402	0	150	0	148.02	0	4.37	0	0.05	0	1.08	0	0.02	0	108.00	0	0.29	0	5093	0	330009	0	19188	0	977	0	338	0	0	0	20292	0	53	0	0	0	494	0	68871	0	513	0	69931	0	87.64	0	289214	0	23823	67295	2.824791168199	330009.0	308402.0	5093.0	19188.0	977.0	338.0	0.0	20292.0	289214.0	93.5	1.5	5.8	0.3	0.1	0.0	6.1	87.6	75	75	75.00	6	24750675	24.5	25.4	25.3	24.8	0.0	34.8	28.1	smartseq
1450655	SRR3641229	SRP076212	SRS1489283	SRX1827325	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190127: H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190127		GSM2190127	H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	5575050	37167	2016-07-18 10:56:32	1900212	5575050	37167	2	37167	index:0,count:37167,average:75,stdev:0|index:1,count:37167,average:75,stdev:0	GSM2190127_r2						0.92	2.3	0.04	3699111	4098397	3456672	3881235	110.79	112.28	31325	29656	142.319	695.357	111	282	82.84	89.15	34403	25951	34403	25951	71.35	73.01	34403	22351	34403	21252	318345	8.61	2.14	0	5.96	0	0.29	0	0.09	0	0.00	0	15.34	0	31325	0	150	0	146.49	0	4.23	0	0.05	0	1.13	0	0.02	0	22.30	0	0.24	0	795	0	37167	0	2216	0	109	0	33	0	0	0	5700	0	5	0	0	0	50	0	7107	0	37	0	7199	0	78.32	0	29109	0	4593	6127	1.333986501197	37167.0	31325.0	795.0	2216.0	109.0	33.0	0.0	5700.0	29109.0	84.3	2.1	6.0	0.3	0.1	0.0	15.3	78.3	75	75	75.00	6	2787525	24.1	26.0	25.0	24.9	0.0	35.3	30.2	smartseq
1450764	SRR3638230	SRP076212	SRS1488257	SRX1826299	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189101: 1-0-1-1-BTN35-C39-1782070112-30ul-1-IL5413-N703-N508 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189101		GSM2189101	1-0-1-1-BTN35-C39-1782070112-30ul-1-IL5413-N703-N508 BTN35 Mic-scRNA-Seq	44720100	298134	2016-07-18 10:56:32	21893227	44720100	298134	2	298134	index:0,count:298134,average:75,stdev:0|index:1,count:298134,average:75,stdev:0	GSM2189101_r1						2.7	3.49	0.04	37862639	37140601	35772192	35283015	98.09	98.63	266207	238051	242.497	1301.269	189	1189	74.81	79.26	290417	199142	290417	199142	76.97	76.83	290417	204892	290417	193035	6805733	17.97	1.11	0	5.02	0	0.30	0	0.11	0	0.00	0	10.30	0	266207	0	150	0	147.78	0	1.46	0	0.01	0	1.15	0	0.00	0	48.79	0	0.91	0	3306	0	298134	0	14963	0	901	0	330	0	0	0	30696	0	35	0	0	0	274	0	39569	0	279	0	40157	0	84.27	0	251244	0	15934	40037	2.512677293837	298134.0	266207.0	3306.0	14963.0	901.0	330.0	0.0	30696.0	251244.0	89.3	1.1	5.0	0.3	0.1	0.0	10.3	84.3	75	75	75.00	7	22360050	28.4	21.8	22.1	27.6	0.0	33.1	21.1	smartseq
1450765	SRR3639230	SRP076212	SRS1488633	SRX1826675	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189477: 1ll-BTN17-C09 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189477		GSM2189477	1ll-BTN17-C09 BTN17 Mic-scRNA-Seq	1314584558	4352929	2016-07-18 10:56:32	677880743	1314584558	4352929	2	4352929	index:0,count:4352929,average:151,stdev:0|index:1,count:4352929,average:151,stdev:0	GSM2189477_r1						1.4	2.98	0.08	871790094	851514916	846722018	829895623	97.67	98.01	3571958	3381548	281.251	837.397	225	16091	51.0	52.57	3728473	1821607	3728473	1821607	50.51	49.9	3728473	1804294	3728473	1729057	389549005	44.68	0.88	0	2.46	0	0.10	0	0.10	0	0.00	0	17.74	0	3571958	0	302	0	293.67	0	1.62	0	0.02	0	1.20	0	0.00	0	111.93	0	1.08	0	38200	0	4352929	0	106986	0	4468	0	4477	0	0	0	772026	0	834	0	0	0	5793	0	885874	0	9347	0	901848	0	79.60	0	3464972	0	32516	810970	24.940644605733	4352929.0	3571958.0	38200.0	106986.0	4468.0	4477.0	0.0	772026.0	3464972.0	82.1	0.9	2.5	0.1	0.1	0.0	17.7	79.6	151	151	151.00	7	657292279	29.4	21.2	21.5	27.9	0.0	30.5	19.8	smartseq
1450766	SRR3640230	SRP076212	SRS1489027	SRX1827069	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189871: D11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189871		GSM2189871	D11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	48784200	325228	2016-07-18 10:56:32	18465012	48784200	325228	2	325228	index:0,count:325228,average:75,stdev:0|index:1,count:325228,average:75,stdev:0	GSM2189871_r3						1.12	2.34	0.03	42170021	45847835	39729314	43621520	108.72	109.8	305283	264652	240.418	1576.812	146	1366	82.61	87.94	331406	252204	331406	252204	74.25	75.19	331406	226673	331406	215645	4134383	9.80	1.51	0	5.69	0	0.31	0	0.11	0	0.00	0	5.72	0	305283	0	150	0	148.05	0	4.33	0	0.05	0	1.08	0	0.02	0	97.57	0	0.29	0	4912	0	325228	0	18501	0	997	0	345	0	0	0	18603	0	41	0	0	0	509	0	68248	0	490	0	69288	0	88.18	0	286782	0	23458	66863	2.850328246227	325228.0	305283.0	4912.0	18501.0	997.0	345.0	0.0	18603.0	286782.0	93.9	1.5	5.7	0.3	0.1	0.0	5.7	88.2	75	75	75.00	6	24392100	24.5	25.4	25.4	24.8	0.0	34.7	27.8	smartseq
1450767	SRR3641230	SRP076212	SRS1489283	SRX1827325	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190127: H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190127		GSM2190127	H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	5524200	36828	2016-07-18 10:56:32	1884260	5524200	36828	2	36828	index:0,count:36828,average:75,stdev:0|index:1,count:36828,average:75,stdev:0	GSM2190127_r3						0.92	2.41	0.03	3662320	4061436	3413958	3840111	110.9	112.48	31004	29416	143.061	688.837	107	288	82.32	88.88	34148	25524	34148	25524	70.66	72.46	34148	21908	34148	20807	314163	8.58	2.08	0	6.21	0	0.26	0	0.09	0	0.00	0	15.47	0	31004	0	150	0	146.67	0	4.13	0	0.05	0	1.11	0	0.02	0	22.10	0	0.23	0	766	0	36828	0	2287	0	94	0	32	0	0	0	5698	0	9	0	0	0	48	0	7073	0	46	0	7176	0	77.98	0	28717	0	4627	6097	1.317700453858	36828.0	31004.0	766.0	2287.0	94.0	32.0	0.0	5698.0	28717.0	84.2	2.1	6.2	0.3	0.1	0.0	15.5	78.0	75	75	75.00	6	2762100	24.1	26.0	24.9	25.0	0.0	35.2	30.2	smartseq
1450780	SRR3638231	SRP076212	SRS1488257	SRX1826299	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189101: 1-0-1-1-BTN35-C39-1782070112-30ul-1-IL5413-N703-N508 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189101		GSM2189101	1-0-1-1-BTN35-C39-1782070112-30ul-1-IL5413-N703-N508 BTN35 Mic-scRNA-Seq	45976350	306509	2016-07-18 10:56:32	22464856	45976350	306509	2	306509	index:0,count:306509,average:75,stdev:0|index:1,count:306509,average:75,stdev:0	GSM2189101_r2						2.66	3.42	0.04	39133441	38420759	36976468	36498250	98.18	98.71	274621	244085	246.158	1370.023	209	1170	75.0	79.45	299557	205964	299557	205964	77.16	77.0	299557	211890	299557	199600	7003288	17.90	1.13	0	5.02	0	0.31	0	0.10	0	0.00	0	10.00	0	274621	0	150	0	147.77	0	1.45	0	0.01	0	1.20	0	0.00	0	64.91	0	0.91	0	3462	0	306509	0	15393	0	940	0	312	0	0	0	30636	0	31	0	0	0	276	0	41435	0	304	0	42046	0	84.57	0	259228	0	16307	41993	2.575151775311	306509.0	274621.0	3462.0	15393.0	940.0	312.0	0.0	30636.0	259228.0	89.6	1.1	5.0	0.3	0.1	0.0	10.0	84.6	75	75	75.00	7	22988175	28.4	21.9	22.1	27.6	0.0	33.1	21.3	smartseq
1450781	SRR3639231	SRP076212	SRS1488634	SRX1826676	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189478: 1ll-BTN17-C14 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189478		GSM2189478	1ll-BTN17-C14 BTN17 Mic-scRNA-Seq	1120887194	3711547	2016-07-18 10:56:32	574983989	1120887194	3711547	2	3711547	index:0,count:3711547,average:151,stdev:0|index:1,count:3711547,average:151,stdev:0	GSM2189478_r1						4.32	2.96	0.03	746979011	730180978	702837531	689192427	97.75	98.06	3075109	2893689	281.806	753.492	230	15678	76.95	81.92	3336762	2366374	3336762	2366374	78.33	78.19	3336762	2408768	3336762	2258657	108181880	14.48	0.93	0	5.03	0	0.20	0	0.07	0	0.00	0	16.88	0	3075109	0	302	0	293.09	0	2.01	0	0.03	0	1.14	0	0.01	0	78.14	0	1.08	0	34600	0	3711547	0	186595	0	7333	0	2772	0	0	0	626333	0	44	0	0	0	5112	0	902510	0	10599	0	918265	0	77.83	0	2888514	0	6461	842051	130.328277356446	3711547.0	3075109.0	34600.0	186595.0	7333.0	2772.0	0.0	626333.0	2888514.0	82.9	0.9	5.0	0.2	0.1	0.0	16.9	77.8	151	151	151.00	7	560443597	27.9	22.5	22.9	26.8	0.0	30.6	19.8	smartseq
1450782	SRR3640231	SRP076212	SRS1489027	SRX1827069	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189871: D11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189871		GSM2189871	D11_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	49101150	327341	2016-07-18 10:56:32	18634152	49101150	327341	2	327341	index:0,count:327341,average:75,stdev:0|index:1,count:327341,average:75,stdev:0	GSM2189871_r4						1.18	2.37	0.02	42383729	46040068	39898025	43770447	108.63	109.71	306773	266005	240.735	1618.392	146	1391	82.54	87.95	333100	253217	333100	253217	74.25	75.2	333100	227777	333100	216524	4165103	9.83	1.51	0	5.76	0	0.28	0	0.10	0	0.00	0	5.91	0	306773	0	150	0	148.04	0	4.36	0	0.05	0	1.08	0	0.02	0	107.13	0	0.30	0	4956	0	327341	0	18852	0	915	0	319	0	0	0	19334	0	46	0	0	0	472	0	68491	0	523	0	69532	0	87.96	0	287921	0	23596	67048	2.841498559078	327341.0	306773.0	4956.0	18852.0	915.0	319.0	0.0	19334.0	287921.0	93.7	1.5	5.8	0.3	0.1	0.0	5.9	88.0	75	75	75.00	6	24550575	24.5	25.4	25.4	24.8	0.0	34.7	27.9	smartseq
1450783	SRR3641231	SRP076212	SRS1489283	SRX1827325	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190127: H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190127		GSM2190127	H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	5564550	37097	2016-07-18 10:56:32	1910091	5564550	37097	2	37097	index:0,count:37097,average:75,stdev:0|index:1,count:37097,average:75,stdev:0	GSM2190127_r4						1.13	2.32	0.04	3692005	4080810	3459827	3872485	110.53	111.93	31274	29580	142.951	753.573	106	293	82.85	88.95	34263	25910	34263	25910	71.73	73.29	34263	22432	34263	21347	327826	8.88	2.07	0	5.78	0	0.25	0	0.07	0	0.00	0	15.37	0	31274	0	150	0	146.65	0	3.99	0	0.04	0	1.16	0	0.02	0	26.71	0	0.23	0	768	0	37097	0	2146	0	94	0	27	0	0	0	5702	0	8	0	0	0	64	0	7328	0	61	0	7461	0	78.52	0	29128	0	4811	6298	1.309083350655	37097.0	31274.0	768.0	2146.0	94.0	27.0	0.0	5702.0	29128.0	84.3	2.1	5.8	0.3	0.1	0.0	15.4	78.5	75	75	75.00	6	2782275	24.3	25.8	24.9	25.0	0.0	35.2	30.2	smartseq
1450795	SRR3638232	SRP076212	SRS1488257	SRX1826299	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189101: 1-0-1-1-BTN35-C39-1782070112-30ul-1-IL5413-N703-N508 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189101		GSM2189101	1-0-1-1-BTN35-C39-1782070112-30ul-1-IL5413-N703-N508 BTN35 Mic-scRNA-Seq	45441900	302946	2016-07-18 10:56:32	22293007	45441900	302946	2	302946	index:0,count:302946,average:75,stdev:0|index:1,count:302946,average:75,stdev:0	GSM2189101_r3						2.68	3.44	0.04	38531384	37814170	36410247	35917606	98.14	98.65	270697	241244	243.918	1336.302	199	1231	75.16	79.62	295134	203448	295134	203448	77.31	77.17	295134	209277	295134	197169	6788043	17.62	1.11	0	5.01	0	0.29	0	0.10	0	0.00	0	10.25	0	270697	0	150	0	147.79	0	1.49	0	0.01	0	1.19	0	0.00	0	57.40	0	0.93	0	3373	0	302946	0	15185	0	893	0	295	0	0	0	31061	0	20	0	0	0	286	0	40702	0	316	0	41324	0	84.34	0	255512	0	16155	41128	2.545837202105	302946.0	270697.0	3373.0	15185.0	893.0	295.0	0.0	31061.0	255512.0	89.4	1.1	5.0	0.3	0.1	0.0	10.3	84.3	75	75	75.00	7	22720950	28.4	21.9	22.2	27.5	0.0	33.0	21.2	smartseq
1450796	SRR3639232	SRP076212	SRS1488635	SRX1826677	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189479: 1ll-BTN17-C19 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189479		GSM2189479	1ll-BTN17-C19 BTN17 Mic-scRNA-Seq	1218284610	4034055	2016-07-18 10:56:32	630027397	1218284610	4034055	2	4034055	index:0,count:4034055,average:151,stdev:0|index:1,count:4034055,average:151,stdev:0	GSM2189479_r1						3.52	8.85	0.03	800833580	802838134	763353237	768276595	100.25	100.64	3384573	3128797	265.552	759.341	225	16461	69.59	73.12	3610834	2355350	3610834	2355350	69.43	68.87	3610834	2350021	3610834	2218262	201932306	25.22	0.81	0	4.05	0	0.10	0	0.06	0	0.00	0	15.94	0	3384573	0	302	0	292.73	0	1.69	0	0.02	0	1.16	0	0.00	0	108.38	0	1.16	0	32742	0	4034055	0	163547	0	4081	0	2385	0	0	0	643016	0	473	0	0	0	4642	0	1200154	0	7759	0	1213028	0	79.85	0	3221026	0	16088	1072106	66.640104425659	4034055.0	3384573.0	32742.0	163547.0	4081.0	2385.0	0.0	643016.0	3221026.0	83.9	0.8	4.1	0.1	0.1	0.0	15.9	79.8	151	151	151.00	7	609142305	28.4	22.0	22.3	27.3	0.0	30.8	20.3	smartseq
1450797	SRR3640232	SRP076212	SRS1489028	SRX1827070	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189872: D11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189872		GSM2189872	D11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	47859450	319063	2016-07-18 10:56:32	17906265	47859450	319063	2	319063	index:0,count:319063,average:75,stdev:0|index:1,count:319063,average:75,stdev:0	GSM2189872_r1						5.13	2.32	0.12	39818814	45784044	36612356	42829580	114.98	116.98	291083	266732	231.104	1193.129	146	1419	74.93	81.82	322811	218111	322811	218111	61.08	61.24	322811	177794	322811	163261	5546409	13.93	1.98	0	7.68	0	0.25	0	0.20	0	0.00	0	8.32	0	291083	0	150	0	147.79	0	4.62	0	0.07	0	1.08	0	0.02	0	104.42	0	0.32	0	6304	0	319063	0	24507	0	813	0	629	0	0	0	26538	0	15	0	0	0	248	0	41598	0	434	0	42295	0	83.55	0	266576	0	16386	40492	2.471133894788	319063.0	291083.0	6304.0	24507.0	813.0	629.0	0.0	26538.0	266576.0	91.2	2.0	7.7	0.3	0.2	0.0	8.3	83.5	75	75	75.00	6	23929725	24.9	24.9	24.9	25.3	0.0	34.7	27.9	smartseq
1450798	SRR3641232	SRP076212	SRS1489283	SRX1827325	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190127: H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190127		GSM2190127	H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	65101350	434009	2016-07-18 10:56:32	24639869	65101350	434009	2	434009	index:0,count:434009,average:75,stdev:0|index:1,count:434009,average:75,stdev:0	GSM2190127_r5						0.95	2.24	0.03	54933855	60498911	52062064	57850093	110.13	111.12	404946	349814	227.670	1635.738	110	1856	85.33	90.32	437183	345538	437183	345538	75.87	76.75	437183	307244	437183	293602	4429472	8.06	1.55	0	5.16	0	0.31	0	0.10	0	0.00	0	6.29	0	404946	0	150	0	147.85	0	4.21	0	0.05	0	1.10	0	0.01	0	120.19	0	0.29	0	6734	0	434009	0	22384	0	1328	0	432	0	0	0	27303	0	100	0	0	0	779	0	101306	0	672	0	102857	0	88.15	0	382562	0	27191	98293	3.614909345004	434009.0	404946.0	6734.0	22384.0	1328.0	432.0	0.0	27303.0	382562.0	93.3	1.6	5.2	0.3	0.1	0.0	6.3	88.1	75	75	75.00	6	32550675	24.0	26.0	25.8	24.2	0.0	34.7	28.0	smartseq
1450811	SRR3638233	SRP076212	SRS1488257	SRX1826299	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189101: 1-0-1-1-BTN35-C39-1782070112-30ul-1-IL5413-N703-N508 BTN35 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN35|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189101		GSM2189101	1-0-1-1-BTN35-C39-1782070112-30ul-1-IL5413-N703-N508 BTN35 Mic-scRNA-Seq	47485800	316572	2016-07-18 10:56:32	22935217	47485800	316572	2	316572	index:0,count:316572,average:75,stdev:0|index:1,count:316572,average:75,stdev:0	GSM2189101_r4						2.73	3.48	0.05	40260587	39492839	38009892	37495069	98.09	98.65	282560	251501	246.343	1395.861	198	1205	74.93	79.45	308609	211726	308609	211726	77.12	76.96	308609	217916	308609	205093	7152377	17.77	1.07	0	5.08	0	0.30	0	0.11	0	0.00	0	10.33	0	282560	0	150	0	147.85	0	1.50	0	0.01	0	1.17	0	0.00	0	71.23	0	0.84	0	3379	0	316572	0	16072	0	945	0	361	0	0	0	32706	0	29	0	0	0	316	0	43037	0	340	0	43722	0	84.18	0	266488	0	16714	43684	2.613617326792	316572.0	282560.0	3379.0	16072.0	945.0	361.0	0.0	32706.0	266488.0	89.3	1.1	5.1	0.3	0.1	0.0	10.3	84.2	75	75	75.00	7	23742900	28.5	21.8	22.1	27.6	0.0	33.4	21.5	smartseq
1450812	SRR3639233	SRP076212	SRS1488636	SRX1826678	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189480: 1ll-BTN17-C25 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189480		GSM2189480	1ll-BTN17-C25 BTN17 Mic-scRNA-Seq	1107297496	3666548	2016-07-18 10:56:32	575033862	1107297496	3666548	2	3666548	index:0,count:3666548,average:151,stdev:0|index:1,count:3666548,average:151,stdev:0	GSM2189480_r1						2.39	7.72	0.14	736909267	727158208	707921431	700747129	98.68	98.99	3036528	2818470	279.034	763.406	225	13679	65.29	68.07	3224043	1982660	3224043	1982660	65.01	64.63	3224043	1974000	3224043	1882434	218824259	29.69	0.84	0	3.38	0	0.13	0	0.08	0	0.00	0	16.97	0	3036528	0	302	0	293.24	0	1.67	0	0.02	0	1.18	0	0.00	0	107.31	0	1.12	0	30922	0	3666548	0	123955	0	4835	0	3008	0	0	0	622177	0	458	0	0	0	4957	0	1038482	0	7791	0	1051688	0	79.44	0	2912573	0	24478	942826	38.517280823597	3666548.0	3036528.0	30922.0	123955.0	4835.0	3008.0	0.0	622177.0	2912573.0	82.8	0.8	3.4	0.1	0.1	0.0	17.0	79.4	151	151	151.00	7	553648748	28.8	21.8	22.1	27.3	0.0	30.3	19.9	smartseq
1450813	SRR3640233	SRP076212	SRS1489028	SRX1827070	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189872: D11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189872		GSM2189872	D11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	47293650	315291	2016-07-18 10:56:32	17769137	47293650	315291	2	315291	index:0,count:315291,average:75,stdev:0|index:1,count:315291,average:75,stdev:0	GSM2189872_r2						5.23	2.3	0.11	39265622	45064958	36103846	42159414	114.77	116.77	287002	262748	230.815	1213.077	125	1420	74.93	81.79	318008	215038	318008	215038	61.31	61.43	318008	175974	318008	161488	5498211	14.00	1.98	0	7.64	0	0.26	0	0.16	0	0.00	0	8.55	0	287002	0	150	0	147.80	0	4.63	0	0.07	0	1.09	0	0.02	0	87.31	0	0.34	0	6232	0	315291	0	24101	0	825	0	517	0	0	0	26947	0	44	0	0	0	278	0	40766	0	457	0	41545	0	83.38	0	262901	0	16308	39805	2.440826588178	315291.0	287002.0	6232.0	24101.0	825.0	517.0	0.0	26947.0	262901.0	91.0	2.0	7.6	0.3	0.2	0.0	8.5	83.4	75	75	75.00	6	23646825	24.9	24.9	24.9	25.3	0.0	34.7	27.8	smartseq
1450814	SRR3641233	SRP076212	SRS1489283	SRX1827325	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190127: H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190127		GSM2190127	H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	62924100	419494	2016-07-18 10:56:32	23821347	62924100	419494	2	419494	index:0,count:419494,average:75,stdev:0|index:1,count:419494,average:75,stdev:0	GSM2190127_r6						0.96	2.3	0.03	52965627	58341323	50178635	55769683	110.15	111.14	390590	337643	226.957	1630.532	126	1781	85.34	90.37	421827	333342	421827	333342	75.91	76.78	421827	296515	421827	283214	4238539	8.00	1.55	0	5.18	0	0.31	0	0.09	0	0.00	0	6.50	0	390590	0	150	0	147.83	0	4.26	0	0.05	0	1.12	0	0.02	0	125.85	0	0.31	0	6486	0	419494	0	21739	0	1281	0	371	0	0	0	27252	0	83	0	0	0	717	0	97179	0	658	0	98637	0	87.93	0	368851	0	26789	94080	3.511889208257	419494.0	390590.0	6486.0	21739.0	1281.0	371.0	0.0	27252.0	368851.0	93.1	1.5	5.2	0.3	0.1	0.0	6.5	87.9	75	75	75.00	6	31462050	24.0	26.1	25.8	24.2	0.0	34.7	28.0	smartseq
1450827	SRR3638234	SRP076212	SRS1488258	SRX1826300	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189102: 1-0-g-0-BTN22-C02-6ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189102		GSM2189102	1-0-g-0-BTN22-C02-6ul-1 BTN22 Mic-scRNA-Seq	35388300	235922	2016-07-18 10:56:32	16846976	35388300	235922	2	235922	index:0,count:235922,average:75,stdev:0|index:1,count:235922,average:75,stdev:0	GSM2189102_r1						1.75	3.34	0.08	30986585	30333658	29665584	29235026	97.89	98.55	216461	201057	244.335	958.000	201	942	59.92	62.61	230898	129696	230898	129696	61.28	60.88	230898	132639	230898	126111	10858927	35.04	0.85	0	3.95	0	0.12	0	0.16	0	0.00	0	7.97	0	216461	0	150	0	148.35	0	1.31	0	0.01	0	1.18	0	0.00	0	53.08	0	0.71	0	2007	0	235922	0	9328	0	286	0	366	0	0	0	18809	0	20	0	0	0	138	0	21942	0	188	0	22288	0	87.80	0	207133	0	8186	22102	2.699975568043	235922.0	216461.0	2007.0	9328.0	286.0	366.0	0.0	18809.0	207133.0	91.8	0.9	4.0	0.1	0.2	0.0	8.0	87.8	75	75	75.00	7	17694150	30.2	20.1	20.2	29.6	0.0	33.3	21.5	smartseq
1450828	SRR3639234	SRP076212	SRS1488637	SRX1826679	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189481: 1ll-BTN17-C29 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189481		GSM2189481	1ll-BTN17-C29 BTN17 Mic-scRNA-Seq	1464641714	4849807	2016-07-18 10:56:32	758599492	1464641714	4849807	2	4849807	index:0,count:4849807,average:151,stdev:0|index:1,count:4849807,average:151,stdev:0	GSM2189481_r1						3.19	6.73	0.05	979174224	983289266	938436511	945792506	100.42	100.78	4043957	3705178	277.643	878.830	225	18569	68.14	71.21	4291886	2755714	4291886	2755714	66.99	66.4	4291886	2708988	4291886	2569697	264650924	27.03	0.83	0	3.59	0	0.14	0	0.09	0	0.00	0	16.38	0	4043957	0	302	0	293.21	0	1.70	0	0.02	0	1.16	0	0.00	0	102.10	0	1.11	0	40257	0	4849807	0	174016	0	6944	0	4352	0	0	0	794554	0	571	0	0	0	8599	0	1605361	0	11021	0	1625552	0	79.80	0	3869941	0	31345	1452299	46.332716541713	4849807.0	4043957.0	40257.0	174016.0	6944.0	4352.0	0.0	794554.0	3869941.0	83.4	0.8	3.6	0.1	0.1	0.0	16.4	79.8	151	151	151.00	7	732320857	28.4	22.2	22.5	26.9	0.0	30.5	20.1	smartseq
1450829	SRR3640234	SRP076212	SRS1489028	SRX1827070	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189872: D11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189872		GSM2189872	D11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	47017350	313449	2016-07-18 10:56:32	17803952	47017350	313449	2	313449	index:0,count:313449,average:75,stdev:0|index:1,count:313449,average:75,stdev:0	GSM2189872_r3						5.17	2.3	0.1	39314760	45230057	36146662	42325018	115.05	117.09	286927	262744	232.501	1210.436	134	1382	74.96	81.84	318191	215075	318191	215075	61.15	61.32	318191	175457	318191	161150	5519920	14.04	1.91	0	7.70	0	0.28	0	0.18	0	0.00	0	8.01	0	286927	0	150	0	147.81	0	4.60	0	0.07	0	1.08	0	0.02	0	70.53	0	0.34	0	5983	0	313449	0	24120	0	864	0	557	0	0	0	25101	0	27	0	0	0	293	0	40775	0	448	0	41543	0	83.84	0	262807	0	16345	39720	2.430100948302	313449.0	286927.0	5983.0	24120.0	864.0	557.0	0.0	25101.0	262807.0	91.5	1.9	7.7	0.3	0.2	0.0	8.0	83.8	75	75	75.00	6	23508675	24.9	24.9	24.9	25.4	0.0	34.6	27.4	smartseq
1450830	SRR3641234	SRP076212	SRS1489283	SRX1827325	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190127: H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190127		GSM2190127	H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	63695700	424638	2016-07-18 10:56:32	24317710	63695700	424638	2	424638	index:0,count:424638,average:75,stdev:0|index:1,count:424638,average:75,stdev:0	GSM2190127_r7						0.96	2.27	0.04	53820297	59270077	51022546	56673370	110.13	111.08	396531	342302	227.782	1669.672	125	1890	85.42	90.38	428054	338711	428054	338711	75.99	76.87	428054	301320	428054	288082	4297772	7.99	1.54	0	5.13	0	0.30	0	0.10	0	0.00	0	6.22	0	396531	0	150	0	147.85	0	4.25	0	0.05	0	1.10	0	0.02	0	117.59	0	0.30	0	6540	0	424638	0	21782	0	1293	0	410	0	0	0	26404	0	77	0	0	0	723	0	99672	0	689	0	101161	0	88.25	0	374749	0	26933	96623	3.587532023911	424638.0	396531.0	6540.0	21782.0	1293.0	410.0	0.0	26404.0	374749.0	93.4	1.5	5.1	0.3	0.1	0.0	6.2	88.3	75	75	75.00	6	31847850	24.0	26.0	25.8	24.2	0.0	34.7	27.8	smartseq
1450842	SRR3638235	SRP076212	SRS1488258	SRX1826300	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189102: 1-0-g-0-BTN22-C02-6ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189102		GSM2189102	1-0-g-0-BTN22-C02-6ul-1 BTN22 Mic-scRNA-Seq	35324250	235495	2016-07-18 10:56:32	16636017	35324250	235495	2	235495	index:0,count:235495,average:75,stdev:0|index:1,count:235495,average:75,stdev:0	GSM2189102_r2						1.73	3.35	0.06	30951124	30281936	29634217	29197604	97.84	98.53	216089	200611	246.792	966.224	188	948	59.89	62.59	230987	129423	230987	129423	61.27	60.93	230987	132395	230987	125989	10860393	35.09	0.89	0	3.95	0	0.11	0	0.17	0	0.00	0	7.96	0	216089	0	150	0	148.37	0	1.36	0	0.01	0	1.18	0	0.00	0	42.39	0	0.69	0	2097	0	235495	0	9301	0	260	0	397	0	0	0	18749	0	23	0	0	0	150	0	21954	0	169	0	22296	0	87.81	0	206788	0	8381	22277	2.658036033886	235495.0	216089.0	2097.0	9301.0	260.0	397.0	0.0	18749.0	206788.0	91.8	0.9	3.9	0.1	0.2	0.0	8.0	87.8	75	75	75.00	7	17662125	30.2	20.1	20.2	29.6	0.0	33.5	21.7	smartseq
1450843	SRR3639235	SRP076212	SRS1488638	SRX1826680	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189482: 1ll-BTN17-C30 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189482		GSM2189482	1ll-BTN17-C30 BTN17 Mic-scRNA-Seq	1216378386	4027743	2016-07-18 10:56:32	627692001	1216378386	4027743	2	4027743	index:0,count:4027743,average:151,stdev:0|index:1,count:4027743,average:151,stdev:0	GSM2189482_r1						2.34	7.53	0.07	797848654	803882997	763694677	772369110	100.76	101.14	3365519	3054275	267.652	911.624	225	15799	78.73	82.38	3583025	2649740	3583025	2649740	78.16	77.97	3583025	2630484	3583025	2507720	129413919	16.22	0.85	0	3.70	0	0.14	0	0.06	0	0.00	0	16.24	0	3365519	0	302	0	292.92	0	1.68	0	0.02	0	1.17	0	0.00	0	111.54	0	1.06	0	34089	0	4027743	0	149103	0	5657	0	2282	0	0	0	654285	0	892	0	0	0	8505	0	1503322	0	9689	0	1522408	0	79.86	0	3216416	0	29652	1346847	45.421792796439	4027743.0	3365519.0	34089.0	149103.0	5657.0	2282.0	0.0	654285.0	3216416.0	83.6	0.8	3.7	0.1	0.1	0.0	16.2	79.9	151	151	151.00	7	608189193	28.1	22.5	22.6	26.8	0.0	30.5	20.2	smartseq
1450844	SRR3640235	SRP076212	SRS1489028	SRX1827070	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189872: D11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189872		GSM2189872	D11_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	47311200	315408	2016-07-18 10:56:32	17949318	47311200	315408	2	315408	index:0,count:315408,average:75,stdev:0|index:1,count:315408,average:75,stdev:0	GSM2189872_r4						5.22	2.32	0.11	39443917	45349020	36224466	42381963	114.97	117.0	287919	263630	232.765	1180.460	125	1394	74.78	81.72	319495	215303	319495	215303	61.05	61.17	319495	175763	319495	161159	5526720	14.01	1.93	0	7.75	0	0.27	0	0.17	0	0.00	0	8.28	0	287919	0	150	0	147.81	0	4.65	0	0.07	0	1.07	0	0.02	0	94.62	0	0.35	0	6081	0	315408	0	24456	0	845	0	522	0	0	0	26122	0	25	0	0	0	309	0	40858	0	434	0	41626	0	83.53	0	263463	0	16292	39950	2.452123741714	315408.0	287919.0	6081.0	24456.0	845.0	522.0	0.0	26122.0	263463.0	91.3	1.9	7.8	0.3	0.2	0.0	8.3	83.5	75	75	75.00	6	23655600	24.9	24.8	24.9	25.4	0.0	34.6	27.5	smartseq
1450845	SRR3641235	SRP076212	SRS1489283	SRX1827325	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190127: H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190127		GSM2190127	H12_1000700401-OGC7-coc_1_8ul_1 OGC07-sal FACS-scRNA-Seq	63109050	420727	2016-07-18 10:56:32	24085848	63109050	420727	2	420727	index:0,count:420727,average:75,stdev:0|index:1,count:420727,average:75,stdev:0	GSM2190127_r8						0.94	2.27	0.03	53347490	58786665	50595899	56243313	110.2	111.16	392684	338295	228.677	1663.100	134	1851	85.49	90.42	423352	335720	423352	335720	75.96	76.84	423352	298288	423352	285283	4240308	7.95	1.55	0	5.09	0	0.31	0	0.09	0	0.00	0	6.26	0	392684	0	150	0	147.86	0	4.26	0	0.04	0	1.11	0	0.02	0	126.22	0	0.31	0	6507	0	420727	0	21402	0	1325	0	379	0	0	0	26339	0	75	0	0	0	690	0	98987	0	635	0	100387	0	88.25	0	371282	0	27061	95779	3.539374006873	420727.0	392684.0	6507.0	21402.0	1325.0	379.0	0.0	26339.0	371282.0	93.3	1.5	5.1	0.3	0.1	0.0	6.3	88.2	75	75	75.00	6	31554525	23.9	26.1	25.8	24.2	0.0	34.7	27.9	smartseq
1450858	SRR3638236	SRP076212	SRS1488258	SRX1826300	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189102: 1-0-g-0-BTN22-C02-6ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189102		GSM2189102	1-0-g-0-BTN22-C02-6ul-1 BTN22 Mic-scRNA-Seq	34633650	230891	2016-07-18 10:56:32	16571073	34633650	230891	2	230891	index:0,count:230891,average:75,stdev:0|index:1,count:230891,average:75,stdev:0	GSM2189102_r3						1.74	3.44	0.06	30278192	29611837	28980202	28535113	97.8	98.46	211700	196799	243.510	950.141	216	937	59.9	62.61	226542	126798	226542	126798	61.32	60.93	226542	129820	226542	123383	10592311	34.98	0.88	0	3.98	0	0.11	0	0.17	0	0.00	0	8.04	0	211700	0	150	0	148.34	0	1.33	0	0.01	0	1.18	0	0.00	0	51.95	0	0.75	0	2030	0	230891	0	9194	0	244	0	389	0	0	0	18558	0	16	0	0	0	129	0	21507	0	172	0	21824	0	87.71	0	202506	0	8231	21666	2.632243955777	230891.0	211700.0	2030.0	9194.0	244.0	389.0	0.0	18558.0	202506.0	91.7	0.9	4.0	0.1	0.2	0.0	8.0	87.7	75	75	75.00	7	17316825	30.2	20.1	20.2	29.5	0.0	33.2	21.4	smartseq
1450859	SRR3639236	SRP076212	SRS1488639	SRX1826681	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189483: 1ll-BTN17-C31 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Vascular|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189483		GSM2189483	1ll-BTN17-C31 BTN17 Mic-scRNA-Seq	1012088372	3351286	2016-07-18 10:56:32	520832262	1012088372	3351286	2	3351286	index:0,count:3351286,average:151,stdev:0|index:1,count:3351286,average:151,stdev:0	GSM2189483_r1						4.48	1.82	0.02	661344831	665652307	628948898	635927915	100.65	101.11	2739955	2595939	276.587	735.950	230	13262	65.21	68.63	2920562	1786798	2920562	1786798	65.14	64.17	2920562	1784709	2920562	1670687	192626368	29.13	1.29	0	4.07	0	0.12	0	0.08	0	0.00	0	18.04	0	2739955	0	302	0	292.97	0	1.56	0	0.01	0	1.18	0	0.00	0	107.72	0	1.08	0	43267	0	3351286	0	136336	0	4072	0	2673	0	0	0	604586	0	488	0	0	0	3772	0	686811	0	6723	0	697794	0	77.69	0	2603619	0	8853	636727	71.922173274596	3351286.0	2739955.0	43267.0	136336.0	4072.0	2673.0	0.0	604586.0	2603619.0	81.8	1.3	4.1	0.1	0.1	0.0	18.0	77.7	151	151	151.00	7	506044186	28.5	21.9	22.4	27.2	0.0	30.5	19.5	smartseq
1450860	SRR3640236	SRP076212	SRS1489029	SRX1827071	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189873: D11_1000701204-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189873		GSM2189873	D11_1000701204-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	90348000	602320	2016-07-18 10:56:32	31300728	90348000	602320	2	602320	index:0,count:602320,average:75,stdev:0|index:1,count:602320,average:75,stdev:0	GSM2189873_r1						1.63	2.05	0.04	75692463	87006236	71002456	82690068	114.95	116.46	550314	496701	255.236	1390.574	146	2300	76.15	81.49	598728	419072	598728	419072	61.86	62.53	598728	340420	598728	321545	11714857	15.48	1.96	0	5.99	0	0.19	0	0.24	0	0.00	0	8.21	0	550314	0	150	0	147.88	0	4.77	0	0.08	0	1.09	0	0.02	0	135.52	0	0.26	0	11782	0	602320	0	36057	0	1134	0	1430	0	0	0	49442	0	67	0	0	0	569	0	82517	0	912	0	84065	0	85.38	0	514257	0	19845	81204	4.091912320484	602320.0	550314.0	11782.0	36057.0	1134.0	1430.0	0.0	49442.0	514257.0	91.4	2.0	6.0	0.2	0.2	0.0	8.2	85.4	75	75	75.00	6	45174000	24.6	25.0	25.2	25.2	0.0	35.2	29.8	smartseq
1450861	SRR3641236	SRP076212	SRS1489284	SRX1827326	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190128: H1_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190128		GSM2190128	H1_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	39731100	264874	2016-07-18 10:56:32	13295460	39731100	264874	2	264874	index:0,count:264874,average:75,stdev:0|index:1,count:264874,average:75,stdev:0	GSM2190128_r1						1.5	2.78	0.04	32877968	35254764	30947617	33490161	107.23	108.22	246106	213960	212.652	1521.696	134	1301	84.48	90.05	268380	207922	268380	207922	78.26	79.06	268380	192608	268380	182554	2754372	8.38	1.64	0	5.74	0	0.31	0	0.11	0	0.00	0	6.67	0	246106	0	150	0	147.67	0	3.89	0	0.03	0	1.11	0	0.01	0	86.69	0	0.22	0	4356	0	264874	0	15198	0	813	0	279	0	0	0	17676	0	46	0	0	0	472	0	65429	0	381	0	66328	0	87.18	0	230908	0	22944	62526	2.725156903766	264874.0	246106.0	4356.0	15198.0	813.0	279.0	0.0	17676.0	230908.0	92.9	1.6	5.7	0.3	0.1	0.0	6.7	87.2	75	75	75.00	6	19865550	24.7	25.2	25.1	25.1	0.0	35.2	30.1	smartseq
1450874	SRR3638237	SRP076212	SRS1488258	SRX1826300	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189102: 1-0-g-0-BTN22-C02-6ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189102		GSM2189102	1-0-g-0-BTN22-C02-6ul-1 BTN22 Mic-scRNA-Seq	34037550	226917	2016-07-18 10:56:32	16177833	34037550	226917	2	226917	index:0,count:226917,average:75,stdev:0|index:1,count:226917,average:75,stdev:0	GSM2189102_r4						1.75	3.38	0.07	29655046	29023039	28397583	27980412	97.87	98.53	207315	192888	243.001	956.068	209	901	59.65	62.33	221367	123661	221367	123661	61.04	60.64	221367	126550	221367	120324	10481324	35.34	0.87	0	3.92	0	0.12	0	0.16	0	0.00	0	8.36	0	207315	0	150	0	148.33	0	1.31	0	0.01	0	1.18	0	0.00	0	54.46	0	0.73	0	1979	0	226917	0	8904	0	265	0	372	0	0	0	18965	0	26	0	0	0	136	0	20762	0	168	0	21092	0	87.44	0	198411	0	8065	20882	2.589212647241	226917.0	207315.0	1979.0	8904.0	265.0	372.0	0.0	18965.0	198411.0	91.4	0.9	3.9	0.1	0.2	0.0	8.4	87.4	75	75	75.00	7	17018775	30.2	20.0	20.1	29.6	0.0	33.3	21.4	smartseq
1450875	SRR3639237	SRP076212	SRS1488640	SRX1826682	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189484: 1ll-BTN17-C34 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189484		GSM2189484	1ll-BTN17-C34 BTN17 Mic-scRNA-Seq	1818676616	6022108	2016-07-18 10:56:32	929414834	1818676616	6022108	2	6022108	index:0,count:6022108,average:151,stdev:0|index:1,count:6022108,average:151,stdev:0	GSM2189484_r1						3.46	9.43	0.05	1232174955	1238601284	1178824091	1188826575	100.52	100.85	5101290	4642865	275.254	870.023	225	23468	72.29	75.68	5409155	3687946	5409155	3687946	72.13	71.61	5409155	3679538	5409155	3489466	284631793	23.10	0.82	0	3.79	0	0.10	0	0.07	0	0.00	0	15.12	0	5101290	0	302	0	293.51	0	1.66	0	0.01	0	1.17	0	0.00	0	97.22	0	1.05	0	49245	0	6022108	0	228351	0	5904	0	4275	0	0	0	910639	0	1618	0	0	0	10705	0	2091731	0	13059	0	2117113	0	80.92	0	4872939	0	23897	1887662	78.991588902373	6022108.0	5101290.0	49245.0	228351.0	5904.0	4275.0	0.0	910639.0	4872939.0	84.7	0.8	3.8	0.1	0.1	0.0	15.1	80.9	151	151	151.00	7	909338308	28.3	22.2	22.4	27.1	0.0	30.8	20.1	smartseq
1450876	SRR3640237	SRP076212	SRS1489030	SRX1827072	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189874: D12_1000700602-OGC11-sal_1_30ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189874		GSM2189874	D12_1000700602-OGC11-sal_1_30ul_1 OGC11-sal FACS-scRNA-Seq	53637000	357580	2016-07-18 10:56:32	19819683	53637000	357580	2	357580	index:0,count:357580,average:75,stdev:0|index:1,count:357580,average:75,stdev:0	GSM2189874_r1						2.41	2.18	0.06	37835862	43423565	34935187	40785360	114.77	116.75	305997	291703	159.335	668.886	110	2422	73.95	80.51	340240	226270	340240	226270	59.59	59.95	340240	182334	340240	168465	5954432	15.74	2.22	0	6.98	0	0.19	0	0.17	0	0.00	0	14.07	0	305997	0	150	0	146.82	0	4.29	0	0.06	0	1.05	0	0.02	0	80.46	0	0.30	0	7924	0	357580	0	24968	0	689	0	600	0	0	0	50294	0	22	0	0	0	287	0	44593	0	420	0	45322	0	78.59	0	281029	0	9371	41346	4.412122505602	357580.0	305997.0	7924.0	24968.0	689.0	600.0	0.0	50294.0	281029.0	85.6	2.2	7.0	0.2	0.2	0.0	14.1	78.6	75	75	75.00	6	26818500	24.9	25.1	24.5	25.5	0.0	34.7	28.0	smartseq
1450877	SRR3641237	SRP076212	SRS1489284	SRX1827326	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190128: H1_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190128		GSM2190128	H1_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	39435300	262902	2016-07-18 10:56:32	13251068	39435300	262902	2	262902	index:0,count:262902,average:75,stdev:0|index:1,count:262902,average:75,stdev:0	GSM2190128_r2						1.49	2.74	0.04	32598109	34962437	30711304	33260162	107.25	108.3	243881	211920	212.803	1584.790	134	1286	84.56	90.06	265778	206237	265778	206237	78.25	79.07	265778	190844	265778	181073	2731773	8.38	1.61	0	5.66	0	0.33	0	0.10	0	0.00	0	6.80	0	243881	0	150	0	147.66	0	3.83	0	0.03	0	1.09	0	0.01	0	78.87	0	0.23	0	4243	0	262902	0	14880	0	859	0	273	0	0	0	17889	0	44	0	0	0	441	0	64478	0	404	0	65367	0	87.11	0	229001	0	22782	61630	2.705205864279	262902.0	243881.0	4243.0	14880.0	859.0	273.0	0.0	17889.0	229001.0	92.8	1.6	5.7	0.3	0.1	0.0	6.8	87.1	75	75	75.00	6	19717650	24.7	25.2	25.0	25.1	0.0	35.2	30.1	smartseq
1450890	SRR3638238	SRP076212	SRS1488259	SRX1826301	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189103: 1-0-g-0-BTN22-C10-14ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189103		GSM2189103	1-0-g-0-BTN22-C10-14ul-1 BTN22 Mic-scRNA-Seq	73789800	491932	2016-07-18 10:56:32	34663100	73789800	491932	2	491932	index:0,count:491932,average:75,stdev:0|index:1,count:491932,average:75,stdev:0	GSM2189103_r1						1.59	3.62	0.13	65429020	63661962	62597083	61362555	97.3	98.03	456934	419100	247.369	1111.697	202	1869	67.06	70.14	488180	306426	488180	306426	68.47	68.35	488180	312864	488180	298603	17666527	27.00	0.97	0	4.07	0	0.10	0	0.12	0	0.00	0	6.89	0	456934	0	150	0	148.38	0	1.33	0	0.01	0	1.17	0	0.00	0	93.21	0	0.64	0	4768	0	491932	0	20031	0	503	0	612	0	0	0	33883	0	53	0	0	0	440	0	55312	0	514	0	56319	0	88.81	0	436903	0	15041	56241	3.739179575826	491932.0	456934.0	4768.0	20031.0	503.0	612.0	0.0	33883.0	436903.0	92.9	1.0	4.1	0.1	0.1	0.0	6.9	88.8	75	75	75.00	7	36894900	29.5	20.4	20.5	29.5	0.0	33.7	22.1	smartseq
1450891	SRR3639238	SRP076212	SRS1488641	SRX1826683	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189485: 1ll-BTN17-C38 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189485		GSM2189485	1ll-BTN17-C38 BTN17 Mic-scRNA-Seq	1527065416	5056508	2016-07-18 10:56:32	777001315	1527065416	5056508	2	5056508	index:0,count:5056508,average:151,stdev:0|index:1,count:5056508,average:151,stdev:0	GSM2189485_r1						2.0	2.95	0.06	1053062083	1028346095	1023663842	1002516167	97.65	97.93	4313534	4092772	281.033	845.584	230	19440	48.76	50.21	4496789	2103129	4496789	2103129	48.71	48.03	4496789	2100997	4496789	2011748	495405258	47.04	1.03	0	2.46	0	0.12	0	0.11	0	0.00	0	14.47	0	4313534	0	302	0	294.12	0	1.56	0	0.01	0	1.21	0	0.00	0	118.20	0	1.01	0	51996	0	5056508	0	124620	0	5986	0	5355	0	0	0	731633	0	858	0	0	0	7591	0	1010288	0	11961	0	1030698	0	82.84	0	4188914	0	25822	932929	36.129230888390	5056508.0	4313534.0	51996.0	124620.0	5986.0	5355.0	0.0	731633.0	4188914.0	85.3	1.0	2.5	0.1	0.1	0.0	14.5	82.8	151	151	151.00	7	763532708	28.9	21.5	21.7	27.8	0.0	31.0	20.4	smartseq
1450892	SRR3640238	SRP076212	SRS1489030	SRX1827072	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189874: D12_1000700602-OGC11-sal_1_30ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189874		GSM2189874	D12_1000700602-OGC11-sal_1_30ul_1 OGC11-sal FACS-scRNA-Seq	51838500	345590	2016-07-18 10:56:32	19107192	51838500	345590	2	345590	index:0,count:345590,average:75,stdev:0|index:1,count:345590,average:75,stdev:0	GSM2189874_r2						2.37	2.15	0.05	36579103	42033684	33792332	39505726	114.91	116.91	295734	281783	159.760	694.533	110	2314	74.13	80.69	329075	219229	329075	219229	59.53	59.95	329075	176065	329075	162886	5720458	15.64	2.24	0	6.96	0	0.18	0	0.18	0	0.00	0	14.07	0	295734	0	150	0	146.80	0	4.29	0	0.06	0	1.05	0	0.02	0	95.70	0	0.30	0	7724	0	345590	0	24041	0	631	0	605	0	0	0	48620	0	28	0	0	0	222	0	43164	0	390	0	43804	0	78.62	0	271693	0	9267	39964	4.312506744362	345590.0	295734.0	7724.0	24041.0	631.0	605.0	0.0	48620.0	271693.0	85.6	2.2	7.0	0.2	0.2	0.0	14.1	78.6	75	75	75.00	6	25919250	24.8	25.2	24.5	25.5	0.0	34.8	28.1	smartseq
1450893	SRR3641238	SRP076212	SRS1489284	SRX1827326	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190128: H1_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190128		GSM2190128	H1_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	39243000	261620	2016-07-18 10:56:32	13265820	39243000	261620	2	261620	index:0,count:261620,average:75,stdev:0|index:1,count:261620,average:75,stdev:0	GSM2190128_r3						1.48	2.73	0.04	32531919	34884890	30636000	33175285	107.23	108.29	243429	211340	213.122	1586.607	122	1288	84.55	90.07	265179	205825	265179	205825	78.31	79.1	265179	190640	265179	180773	2717719	8.35	1.64	0	5.70	0	0.32	0	0.10	0	0.00	0	6.53	0	243429	0	150	0	147.65	0	3.77	0	0.03	0	1.10	0	0.01	0	72.45	0	0.22	0	4300	0	261620	0	14903	0	839	0	267	0	0	0	17085	0	41	0	0	0	447	0	64761	0	372	0	65621	0	87.35	0	228526	0	22974	61985	2.698049969531	261620.0	243429.0	4300.0	14903.0	839.0	267.0	0.0	17085.0	228526.0	93.0	1.6	5.7	0.3	0.1	0.0	6.5	87.4	75	75	75.00	6	19621500	24.7	25.2	25.1	25.0	0.0	35.2	30.2	smartseq
1450906	SRR3638239	SRP076212	SRS1488259	SRX1826301	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189103: 1-0-g-0-BTN22-C10-14ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189103		GSM2189103	1-0-g-0-BTN22-C10-14ul-1 BTN22 Mic-scRNA-Seq	73056450	487043	2016-07-18 10:56:32	33941693	73056450	487043	2	487043	index:0,count:487043,average:75,stdev:0|index:1,count:487043,average:75,stdev:0	GSM2189103_r2						1.59	3.6	0.13	64867809	63136515	62107027	60897189	97.33	98.05	452662	414290	249.999	1129.985	195	1882	66.83	69.84	483220	302508	483220	302508	68.15	68.0	483220	308467	483220	294515	17686866	27.27	0.97	0	4.01	0	0.10	0	0.13	0	0.00	0	6.83	0	452662	0	150	0	148.41	0	1.37	0	0.01	0	1.16	0	0.00	0	109.58	0	0.62	0	4704	0	487043	0	19523	0	494	0	622	0	0	0	33265	0	59	0	0	0	454	0	55215	0	558	0	56286	0	88.93	0	433139	0	14953	55990	3.744399117234	487043.0	452662.0	4704.0	19523.0	494.0	622.0	0.0	33265.0	433139.0	92.9	1.0	4.0	0.1	0.1	0.0	6.8	88.9	75	75	75.00	7	36528225	29.5	20.4	20.5	29.5	0.0	33.8	22.4	smartseq
1450907	SRR3639239	SRP076212	SRS1488642	SRX1826684	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189486: 1ll-BTN17-C39 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189486		GSM2189486	1ll-BTN17-C39 BTN17 Mic-scRNA-Seq	1768475760	5855880	2016-07-18 10:56:32	906329520	1768475760	5855880	2	5855880	index:0,count:5855880,average:151,stdev:0|index:1,count:5855880,average:151,stdev:0	GSM2189486_r1						3.01	5.45	0.04	1200378877	1214247987	1153999265	1171807234	101.16	101.54	4934378	4593732	280.387	823.673	225	22377	63.18	65.8	5204942	3117514	5204942	3117514	62.14	61.44	5204942	3066036	5204942	2911275	400330911	33.35	1.09	0	3.35	0	0.12	0	0.08	0	0.00	0	15.54	0	4934378	0	302	0	293.46	0	1.83	0	0.02	0	1.16	0	0.00	0	95.39	0	1.08	0	64024	0	5855880	0	196216	0	7032	0	4659	0	0	0	909811	0	783	0	0	0	8779	0	1544123	0	13440	0	1567125	0	80.91	0	4738162	0	25486	1409125	55.290159303147	5855880.0	4934378.0	64024.0	196216.0	7032.0	4659.0	0.0	909811.0	4738162.0	84.3	1.1	3.4	0.1	0.1	0.0	15.5	80.9	151	151	151.00	7	884237880	28.3	22.2	22.5	27.0	0.0	30.8	20.1	smartseq
1450908	SRR3640239	SRP076212	SRS1489030	SRX1827072	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189874: D12_1000700602-OGC11-sal_1_30ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189874		GSM2189874	D12_1000700602-OGC11-sal_1_30ul_1 OGC11-sal FACS-scRNA-Seq	52235700	348238	2016-07-18 10:56:32	19421601	52235700	348238	2	348238	index:0,count:348238,average:75,stdev:0|index:1,count:348238,average:75,stdev:0	GSM2189874_r3						2.44	2.19	0.06	36967558	42449227	34111216	39857510	114.83	116.85	298499	284323	159.807	688.356	110	2412	73.85	80.46	332599	220438	332599	220438	59.49	59.81	332599	177586	332599	163843	5849622	15.82	2.22	0	7.05	0	0.17	0	0.18	0	0.00	0	13.93	0	298499	0	150	0	146.83	0	4.28	0	0.06	0	1.05	0	0.02	0	104.47	0	0.30	0	7731	0	348238	0	24540	0	609	0	634	0	0	0	48496	0	20	0	0	0	252	0	43482	0	414	0	44168	0	78.67	0	273959	0	9372	40365	4.306978233035	348238.0	298499.0	7731.0	24540.0	609.0	634.0	0.0	48496.0	273959.0	85.7	2.2	7.0	0.2	0.2	0.0	13.9	78.7	75	75	75.00	6	26117850	24.9	25.1	24.5	25.5	0.0	34.7	27.9	smartseq
1450909	SRR3641239	SRP076212	SRS1489284	SRX1827326	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190128: H1_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190128		GSM2190128	H1_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	38713050	258087	2016-07-18 10:56:32	13165744	38713050	258087	2	258087	index:0,count:258087,average:75,stdev:0|index:1,count:258087,average:75,stdev:0	GSM2190128_r4						1.46	2.78	0.05	32042696	34340645	30174386	32644652	107.17	108.19	239908	208459	212.492	1556.025	125	1298	84.46	89.98	261638	202634	261638	202634	78.31	79.08	261638	187864	261638	178090	2702655	8.43	1.62	0	5.70	0	0.32	0	0.10	0	0.00	0	6.63	0	239908	0	150	0	147.64	0	3.86	0	0.03	0	1.12	0	0.01	0	58.07	0	0.23	0	4175	0	258087	0	14718	0	826	0	251	0	0	0	17102	0	58	0	0	0	425	0	63574	0	362	0	64419	0	87.25	0	225190	0	22807	60779	2.664927434560	258087.0	239908.0	4175.0	14718.0	826.0	251.0	0.0	17102.0	225190.0	93.0	1.6	5.7	0.3	0.1	0.0	6.6	87.3	75	75	75.00	6	19356525	24.7	25.2	25.1	25.0	0.0	35.2	30.1	smartseq
1451016	SRR3638240	SRP076212	SRS1488259	SRX1826301	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189103: 1-0-g-0-BTN22-C10-14ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189103		GSM2189103	1-0-g-0-BTN22-C10-14ul-1 BTN22 Mic-scRNA-Seq	71358150	475721	2016-07-18 10:56:32	33697232	71358150	475721	2	475721	index:0,count:475721,average:75,stdev:0|index:1,count:475721,average:75,stdev:0	GSM2189103_r3						1.58	3.6	0.13	63244124	61560795	60524611	59355841	97.34	98.07	441930	405043	246.185	1093.747	193	1839	66.95	69.99	471829	295865	471829	295865	68.27	68.16	471829	301725	471829	288103	17185361	27.17	0.95	0	4.04	0	0.10	0	0.12	0	0.00	0	6.88	0	441930	0	150	0	148.35	0	1.35	0	0.01	0	1.15	0	0.00	0	114.17	0	0.68	0	4516	0	475721	0	19233	0	478	0	576	0	0	0	32737	0	53	0	0	0	471	0	53678	0	541	0	54743	0	88.85	0	422697	0	14869	54526	3.667092608783	475721.0	441930.0	4516.0	19233.0	478.0	576.0	0.0	32737.0	422697.0	92.9	0.9	4.0	0.1	0.1	0.0	6.9	88.9	75	75	75.00	7	35679075	29.5	20.4	20.6	29.5	0.0	33.6	22.1	smartseq
1451017	SRR3639240	SRP076212	SRS1488643	SRX1826685	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189487: 1ll-BTN17-C40 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;OPC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189487		GSM2189487	1ll-BTN17-C40 BTN17 Mic-scRNA-Seq	1798281348	5954574	2016-07-18 10:56:32	917314763	1798281348	5954574	2	5954574	index:0,count:5954574,average:151,stdev:0|index:1,count:5954574,average:151,stdev:0	GSM2189487_r1						3.55	2.79	0.1	1245026087	1220482894	1185418102	1165264660	98.03	98.3	5086789	4852888	282.988	626.163	230	23386	54.21	57.03	5429203	2757415	5429203	2757415	55.59	54.5	5429203	2827925	5429203	2634990	507290749	40.75	0.73	0	4.23	0	0.10	0	0.03	0	0.00	0	14.44	0	5086789	0	302	0	294.26	0	1.58	0	0.01	0	1.18	0	0.00	0	123.20	0	1.02	0	43301	0	5954574	0	251843	0	6239	0	1988	0	0	0	859558	0	757	0	0	0	8504	0	1085510	0	9356	0	1104127	0	81.20	0	4834946	0	12483	1014409	81.263238003685	5954574.0	5086789.0	43301.0	251843.0	6239.0	1988.0	0.0	859558.0	4834946.0	85.4	0.7	4.2	0.1	0.0	0.0	14.4	81.2	151	151	151.00	7	899140674	29.1	21.4	21.5	28.0	0.0	30.9	20.2	smartseq
1451018	SRR3640240	SRP076212	SRS1489030	SRX1827072	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189874: D12_1000700602-OGC11-sal_1_30ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189874		GSM2189874	D12_1000700602-OGC11-sal_1_30ul_1 OGC11-sal FACS-scRNA-Seq	51837150	345581	2016-07-18 10:56:32	19251718	51837150	345581	2	345581	index:0,count:345581,average:75,stdev:0|index:1,count:345581,average:75,stdev:0	GSM2189874_r4						2.43	2.15	0.07	36679038	42063338	33887638	39528524	114.68	116.65	296100	282274	159.739	678.150	110	2224	73.89	80.41	329442	218774	329442	218774	59.61	59.94	329442	176501	329442	163073	5810590	15.84	2.25	0	6.95	0	0.17	0	0.18	0	0.00	0	13.97	0	296100	0	150	0	146.82	0	4.37	0	0.06	0	1.05	0	0.02	0	95.70	0	0.31	0	7775	0	345581	0	24021	0	586	0	607	0	0	0	48288	0	13	0	0	0	267	0	43458	0	402	0	44140	0	78.73	0	272079	0	9344	40411	4.324807363014	345581.0	296100.0	7775.0	24021.0	586.0	607.0	0.0	48288.0	272079.0	85.7	2.2	7.0	0.2	0.2	0.0	14.0	78.7	75	75	75.00	6	25918575	24.9	25.1	24.5	25.5	0.0	34.7	27.9	smartseq
1451019	SRR3641240	SRP076212	SRS1489285	SRX1827327	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190129: H1_1000700102-OGC9-sal_1_0ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190129		GSM2190129	H1_1000700102-OGC9-sal_1_0ul_1 OGC09-sal FACS-scRNA-Seq	41459400	276396	2016-07-18 10:56:32	17598474	41459400	276396	2	276396	index:0,count:276396,average:75,stdev:0|index:1,count:276396,average:75,stdev:0	GSM2190129_r1						1.87	2.23	0.04	34859779	38379595	32580722	36277330	110.1	111.35	251061	227242	239.779	1349.271	174	1199	74.6	80.04	275212	187295	275212	187295	64.65	65.18	275212	162303	275212	152522	5787567	16.60	2.10	0	6.17	0	0.26	0	0.17	0	0.00	0	8.74	0	251061	0	150	0	147.61	0	4.58	0	0.07	0	1.12	0	0.02	0	71.07	0	0.49	0	5793	0	276396	0	17058	0	710	0	472	0	0	0	24153	0	32	0	0	0	253	0	38817	0	448	0	39550	0	84.66	0	234003	0	16293	38142	2.341005339716	276396.0	251061.0	5793.0	17058.0	710.0	472.0	0.0	24153.0	234003.0	90.8	2.1	6.2	0.3	0.2	0.0	8.7	84.7	75	75	75.00	6	20729700	25.1	24.6	24.7	25.5	0.0	33.7	25.3	smartseq
1451032	SRR3638241	SRP076212	SRS1488259	SRX1826301	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189103: 1-0-g-0-BTN22-C10-14ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189103		GSM2189103	1-0-g-0-BTN22-C10-14ul-1 BTN22 Mic-scRNA-Seq	71332350	475549	2016-07-18 10:56:32	33372882	71332350	475549	2	475549	index:0,count:475549,average:75,stdev:0|index:1,count:475549,average:75,stdev:0	GSM2189103_r4						1.62	3.56	0.14	63118830	61409431	60442461	59234204	97.29	98.0	440918	404303	246.141	1102.249	197	1848	66.98	69.98	470410	295305	470410	295305	68.34	68.2	470410	301317	470410	287769	17114486	27.11	0.98	0	3.99	0	0.11	0	0.12	0	0.00	0	7.05	0	440918	0	150	0	148.38	0	1.38	0	0.01	0	1.14	0	0.00	0	100.70	0	0.65	0	4669	0	475549	0	18952	0	506	0	578	0	0	0	33547	0	54	0	0	0	489	0	53703	0	487	0	54733	0	88.73	0	421966	0	14843	54346	3.661389207034	475549.0	440918.0	4669.0	18952.0	506.0	578.0	0.0	33547.0	421966.0	92.7	1.0	4.0	0.1	0.1	0.0	7.1	88.7	75	75	75.00	7	35666175	29.5	20.4	20.5	29.6	0.0	33.7	22.1	smartseq
1451033	SRR3639241	SRP076212	SRS1488644	SRX1826686	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189488: 1ll-BTN17-C46 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189488		GSM2189488	1ll-BTN17-C46 BTN17 Mic-scRNA-Seq	1807342556	5984578	2016-07-18 10:56:32	927809842	1807342556	5984578	2	5984578	index:0,count:5984578,average:151,stdev:0|index:1,count:5984578,average:151,stdev:0	GSM2189488_r1						4.38	7.64	0.07	1220169234	1226351459	1161469020	1172023162	100.51	100.91	5030377	4583317	277.911	927.376	225	22939	72.17	75.94	5376194	3630460	5376194	3630460	72.32	71.67	5376194	3637778	5376194	3426308	272463606	22.33	1.01	0	4.18	0	0.17	0	0.07	0	0.00	0	15.71	0	5030377	0	302	0	293.31	0	1.77	0	0.02	0	1.17	0	0.00	0	115.21	0	1.07	0	60585	0	5984578	0	249941	0	9923	0	3890	0	0	0	940388	0	929	0	0	0	10254	0	2054871	0	13595	0	2079649	0	79.88	0	4780436	0	28526	1862963	65.307543994952	5984578.0	5030377.0	60585.0	249941.0	9923.0	3890.0	0.0	940388.0	4780436.0	84.1	1.0	4.2	0.2	0.1	0.0	15.7	79.9	151	151	151.00	7	903671278	28.1	22.5	22.7	26.8	0.0	30.6	20.0	smartseq
1451034	SRR3640241	SRP076212	SRS1489031	SRX1827073	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189875: D12_1000701001-OGC14-sal_1_2ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189875		GSM2189875	D12_1000701001-OGC14-sal_1_2ul_1 OGC14-sal FACS-scRNA-Seq	48268650	321791	2016-07-18 10:56:32	17960168	48268650	321791	2	321791	index:0,count:321791,average:75,stdev:0|index:1,count:321791,average:75,stdev:0	GSM2189875_r1						1.48	2.25	0.02	40561095	44467804	38074419	42210051	109.63	110.86	296253	269638	228.605	1124.651	125	1412	74.62	79.73	321765	221051	321765	221051	65.03	65.55	321765	192654	321765	181749	6991840	17.24	1.73	0	5.90	0	0.23	0	0.21	0	0.00	0	7.50	0	296253	0	150	0	147.96	0	4.27	0	0.05	0	1.09	0	0.02	0	96.54	0	0.27	0	5568	0	321791	0	18990	0	742	0	662	0	0	0	24134	0	40	0	0	0	373	0	47344	0	460	0	48217	0	86.16	0	277263	0	14390	46350	3.220986796386	321791.0	296253.0	5568.0	18990.0	742.0	662.0	0.0	24134.0	277263.0	92.1	1.7	5.9	0.2	0.2	0.0	7.5	86.2	75	75	75.00	6	24134325	25.1	24.7	24.6	25.6	0.0	34.8	28.2	smartseq
1451035	SRR3641241	SRP076212	SRS1489285	SRX1827327	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190129: H1_1000700102-OGC9-sal_1_0ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190129		GSM2190129	H1_1000700102-OGC9-sal_1_0ul_1 OGC09-sal FACS-scRNA-Seq	40254300	268362	2016-07-18 10:56:32	17135437	40254300	268362	2	268362	index:0,count:268362,average:75,stdev:0|index:1,count:268362,average:75,stdev:0	GSM2190129_r2						1.88	2.19	0.05	33703976	37137368	31520248	35099977	110.19	111.36	242547	219397	240.310	1323.968	174	1096	74.63	80.03	265324	181019	265324	181019	64.64	65.15	265324	156782	265324	147361	5590651	16.59	2.07	0	6.09	0	0.25	0	0.16	0	0.00	0	9.21	0	242547	0	150	0	147.57	0	4.61	0	0.07	0	1.11	0	0.02	0	69.01	0	0.52	0	5546	0	268362	0	16354	0	660	0	432	0	0	0	24723	0	39	0	0	0	261	0	37300	0	369	0	37969	0	84.29	0	226193	0	16043	36891	2.299507573396	268362.0	242547.0	5546.0	16354.0	660.0	432.0	0.0	24723.0	226193.0	90.4	2.1	6.1	0.2	0.2	0.0	9.2	84.3	75	75	75.00	6	20127150	25.1	24.5	24.8	25.5	0.0	33.7	25.3	smartseq
1451050	SRR3638242	SRP076212	SRS1488260	SRX1826302	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189104: 1-0-g-0-BTN22-C13-8ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189104		GSM2189104	1-0-g-0-BTN22-C13-8ul-1 BTN22 Mic-scRNA-Seq	37009950	246733	2016-07-18 10:56:32	17612151	37009950	246733	2	246733	index:0,count:246733,average:75,stdev:0|index:1,count:246733,average:75,stdev:0	GSM2189104_r1						1.17	3.19	0.09	32679864	31352210	31904603	30725660	95.94	96.3	227035	218690	252.140	753.287	208	973	37.1	38.02	235972	84221	235972	84221	37.59	37.04	235972	85340	235972	82062	19177611	58.68	0.87	0	2.23	0	0.11	0	0.19	0	0.00	0	7.68	0	227035	0	150	0	148.65	0	1.37	0	0.01	0	1.18	0	0.00	0	49.35	0	0.73	0	2143	0	246733	0	5509	0	262	0	480	0	0	0	18956	0	22	0	0	0	116	0	11697	0	188	0	12023	0	89.78	0	221526	0	6255	11674	1.866346922462	246733.0	227035.0	2143.0	5509.0	262.0	480.0	0.0	18956.0	221526.0	92.0	0.9	2.2	0.1	0.2	0.0	7.7	89.8	75	75	75.00	7	18504975	30.2	20.1	20.1	29.5	0.0	33.4	21.6	smartseq
1451051	SRR3639242	SRP076212	SRS1488645	SRX1826687	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189489: 1ll-BTN17-C47 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;NSC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189489		GSM2189489	1ll-BTN17-C47 BTN17 Mic-scRNA-Seq	1676416194	5551047	2016-07-18 10:56:32	857896986	1676416194	5551047	2	5551047	index:0,count:5551047,average:151,stdev:0|index:1,count:5551047,average:151,stdev:0	GSM2189489_r1						2.46	1.92	0.07	1112817818	1104778284	1082010526	1076784803	99.28	99.52	4631763	4444735	270.215	675.774	230	24374	58.01	59.71	4800800	2686954	4800800	2686954	57.63	57.07	4800800	2669137	4800800	2567766	432992091	38.91	0.82	0	2.38	0	0.03	0	0.06	0	0.00	0	16.47	0	4631763	0	302	0	293.80	0	1.58	0	0.02	0	1.16	0	0.00	0	116.86	0	1.03	0	45400	0	5551047	0	132090	0	1601	0	3341	0	0	0	914342	0	934	0	0	0	4165	0	930705	0	9261	0	945065	0	81.06	0	4499673	0	7908	843685	106.687531613556	5551047.0	4631763.0	45400.0	132090.0	1601.0	3341.0	0.0	914342.0	4499673.0	83.4	0.8	2.4	0.0	0.1	0.0	16.5	81.1	151	151	151.00	7	838208097	28.8	21.8	22.1	27.3	0.0	30.7	20.0	smartseq
1451052	SRR3640242	SRP076212	SRS1489031	SRX1827073	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189875: D12_1000701001-OGC14-sal_1_2ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189875		GSM2189875	D12_1000701001-OGC14-sal_1_2ul_1 OGC14-sal FACS-scRNA-Seq	47964750	319765	2016-07-18 10:56:32	17917751	47964750	319765	2	319765	index:0,count:319765,average:75,stdev:0|index:1,count:319765,average:75,stdev:0	GSM2189875_r2						1.49	2.28	0.02	40202602	44022188	37762976	41815937	109.5	110.73	293541	266832	228.921	1165.178	141	1393	74.45	79.5	318741	218555	318741	218555	64.95	65.43	318741	190643	318741	179875	7011087	17.44	1.69	0	5.83	0	0.21	0	0.21	0	0.00	0	7.77	0	293541	0	150	0	147.94	0	4.24	0	0.05	0	1.09	0	0.02	0	95.93	0	0.29	0	5389	0	319765	0	18635	0	687	0	687	0	0	0	24850	0	33	0	0	0	339	0	47111	0	395	0	47878	0	85.97	0	274906	0	14309	46080	3.220350828150	319765.0	293541.0	5389.0	18635.0	687.0	687.0	0.0	24850.0	274906.0	91.8	1.7	5.8	0.2	0.2	0.0	7.8	86.0	75	75	75.00	6	23982375	25.2	24.6	24.6	25.6	0.0	34.8	28.2	smartseq
1451053	SRR3641242	SRP076212	SRS1489285	SRX1827327	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190129: H1_1000700102-OGC9-sal_1_0ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190129		GSM2190129	H1_1000700102-OGC9-sal_1_0ul_1 OGC09-sal FACS-scRNA-Seq	40652850	271019	2016-07-18 10:56:32	17497707	40652850	271019	2	271019	index:0,count:271019,average:75,stdev:0|index:1,count:271019,average:75,stdev:0	GSM2190129_r3						1.84	2.21	0.05	34140668	37558319	31899416	35481283	110.01	111.23	245858	222687	239.076	1301.273	174	1193	74.45	79.89	269213	183036	269213	183036	64.6	65.15	269213	158826	269213	149256	5730250	16.78	2.07	0	6.18	0	0.23	0	0.16	0	0.00	0	8.89	0	245858	0	150	0	147.55	0	4.60	0	0.06	0	1.11	0	0.02	0	65.04	0	0.55	0	5619	0	271019	0	16762	0	630	0	433	0	0	0	24098	0	41	0	0	0	241	0	37868	0	404	0	38554	0	84.53	0	229096	0	16040	37316	2.326433915212	271019.0	245858.0	5619.0	16762.0	630.0	433.0	0.0	24098.0	229096.0	90.7	2.1	6.2	0.2	0.2	0.0	8.9	84.5	75	75	75.00	6	20326425	25.1	24.6	24.8	25.5	0.0	33.5	24.8	smartseq
1451065	SRR3638243	SRP076212	SRS1488260	SRX1826302	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189104: 1-0-g-0-BTN22-C13-8ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189104		GSM2189104	1-0-g-0-BTN22-C13-8ul-1 BTN22 Mic-scRNA-Seq	36981450	246543	2016-07-18 10:56:32	17401336	36981450	246543	2	246543	index:0,count:246543,average:75,stdev:0|index:1,count:246543,average:75,stdev:0	GSM2189104_r2						1.12	3.14	0.1	32662276	31358349	31903526	30742763	96.01	96.36	226749	218269	255.782	767.988	218	971	37.04	37.94	235394	83997	235394	83997	37.54	36.97	235394	85123	235394	81848	19192075	58.76	0.88	0	2.18	0	0.09	0	0.22	0	0.00	0	7.72	0	226749	0	150	0	148.65	0	1.37	0	0.01	0	1.22	0	0.00	0	52.21	0	0.70	0	2180	0	246543	0	5372	0	222	0	540	0	0	0	19032	0	15	0	0	0	99	0	11690	0	225	0	12029	0	89.79	0	221377	0	6329	11678	1.845157212830	246543.0	226749.0	2180.0	5372.0	222.0	540.0	0.0	19032.0	221377.0	92.0	0.9	2.2	0.1	0.2	0.0	7.7	89.8	75	75	75.00	7	18490725	30.2	20.1	20.1	29.5	0.0	33.6	21.9	smartseq
1451066	SRR3639243	SRP076212	SRS1488646	SRX1826688	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189490: 1ll-BTN17-C50 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189490		GSM2189490	1ll-BTN17-C50 BTN17 Mic-scRNA-Seq	1261097338	4175819	2016-07-18 10:56:32	656758935	1261097338	4175819	2	4175819	index:0,count:4175819,average:151,stdev:0|index:1,count:4175819,average:151,stdev:0	GSM2189490_r1						2.75	8.8	0.06	807137850	814401347	774067958	783308086	100.9	101.19	3303884	2996745	283.369	876.687	233	14974	80.12	83.66	3515362	2647034	3515362	2647034	79.21	79.08	3515362	2617079	3515362	2501988	123502028	15.30	0.80	0	3.35	0	0.17	0	0.05	0	0.00	0	20.66	0	3303884	0	302	0	293.47	0	1.65	0	0.02	0	1.21	0	0.00	0	85.41	0	1.07	0	33511	0	4175819	0	139915	0	7066	0	2267	0	0	0	862602	0	1354	0	0	0	6798	0	1427296	0	7244	0	1442692	0	75.77	0	3163969	0	16422	1304029	79.407441237365	4175819.0	3303884.0	33511.0	139915.0	7066.0	2267.0	0.0	862602.0	3163969.0	79.1	0.8	3.4	0.2	0.1	0.0	20.7	75.8	151	151	151.00	7	630548669	28.9	21.8	22.9	26.4	0.0	29.9	18.8	smartseq
1451067	SRR3640243	SRP076212	SRS1489031	SRX1827073	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189875: D12_1000701001-OGC14-sal_1_2ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189875		GSM2189875	D12_1000701001-OGC14-sal_1_2ul_1 OGC14-sal FACS-scRNA-Seq	47344800	315632	2016-07-18 10:56:32	17804425	47344800	315632	2	315632	index:0,count:315632,average:75,stdev:0|index:1,count:315632,average:75,stdev:0	GSM2189875_r3						1.48	2.3	0.04	39832417	43613972	37413623	41422411	109.49	110.71	290650	263962	230.009	1157.232	141	1400	74.54	79.59	315583	216648	315583	216648	65.04	65.51	315583	189027	315583	178332	6898734	17.32	1.75	0	5.84	0	0.22	0	0.20	0	0.00	0	7.49	0	290650	0	150	0	147.94	0	4.26	0	0.05	0	1.10	0	0.02	0	94.69	0	0.29	0	5509	0	315632	0	18439	0	692	0	644	0	0	0	23646	0	50	0	0	0	368	0	46490	0	428	0	47336	0	86.24	0	272211	0	14224	45449	3.195233408324	315632.0	290650.0	5509.0	18439.0	692.0	644.0	0.0	23646.0	272211.0	92.1	1.7	5.8	0.2	0.2	0.0	7.5	86.2	75	75	75.00	6	23672400	25.2	24.6	24.7	25.5	0.0	34.7	27.8	smartseq
1451068	SRR3641243	SRP076212	SRS1489285	SRX1827327	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190129: H1_1000700102-OGC9-sal_1_0ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190129		GSM2190129	H1_1000700102-OGC9-sal_1_0ul_1 OGC09-sal FACS-scRNA-Seq	40068450	267123	2016-07-18 10:56:32	17172200	40068450	267123	2	267123	index:0,count:267123,average:75,stdev:0|index:1,count:267123,average:75,stdev:0	GSM2190129_r4						1.86	2.23	0.05	33673561	37081712	31456602	35027889	110.12	111.35	242294	219175	240.002	1292.424	153	1070	74.41	79.87	265409	180285	265409	180285	64.46	64.97	265409	156183	265409	146656	5611525	16.66	2.09	0	6.20	0	0.25	0	0.17	0	0.00	0	8.88	0	242294	0	150	0	147.58	0	4.57	0	0.07	0	1.10	0	0.02	0	80.14	0	0.53	0	5580	0	267123	0	16573	0	671	0	447	0	0	0	23711	0	39	0	0	0	250	0	37586	0	378	0	38253	0	84.50	0	225721	0	15990	37039	2.316385240775	267123.0	242294.0	5580.0	16573.0	671.0	447.0	0.0	23711.0	225721.0	90.7	2.1	6.2	0.3	0.2	0.0	8.9	84.5	75	75	75.00	6	20034225	25.1	24.6	24.8	25.5	0.0	33.6	25.0	smartseq
1451081	SRR3638244	SRP076212	SRS1488260	SRX1826302	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189104: 1-0-g-0-BTN22-C13-8ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189104		GSM2189104	1-0-g-0-BTN22-C13-8ul-1 BTN22 Mic-scRNA-Seq	35944800	239632	2016-07-18 10:56:32	17182603	35944800	239632	2	239632	index:0,count:239632,average:75,stdev:0|index:1,count:239632,average:75,stdev:0	GSM2189104_r3						1.1	3.19	0.1	31715935	30431264	30987455	29846226	95.95	96.32	220388	212168	251.236	752.792	203	965	37.12	38.01	228682	81812	228682	81812	37.59	37.05	228682	82837	228682	79743	18629660	58.74	0.86	0	2.15	0	0.08	0	0.20	0	0.00	0	7.75	0	220388	0	150	0	148.62	0	1.40	0	0.01	0	1.23	0	0.00	0	53.92	0	0.76	0	2051	0	239632	0	5160	0	198	0	481	0	0	0	18565	0	11	0	0	0	94	0	11451	0	170	0	11726	0	89.82	0	215228	0	6124	11382	1.858589157413	239632.0	220388.0	2051.0	5160.0	198.0	481.0	0.0	18565.0	215228.0	92.0	0.9	2.2	0.1	0.2	0.0	7.7	89.8	75	75	75.00	7	17972400	30.2	20.1	20.1	29.5	0.0	33.3	21.5	smartseq
1451082	SRR3639244	SRP076212	SRS1488647	SRX1826689	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189491: 1ll-BTN17-C55 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189491		GSM2189491	1ll-BTN17-C55 BTN17 Mic-scRNA-Seq	1439484510	4766505	2016-07-18 10:56:32	740122470	1439484510	4766505	2	4766505	index:0,count:4766505,average:151,stdev:0|index:1,count:4766505,average:151,stdev:0	GSM2189491_r1						1.03	3.39	0.02	976707141	956818575	948235534	931911808	97.96	98.28	4002058	3771809	280.537	837.810	233	17936	55.13	56.85	4182248	2206412	4182248	2206412	54.75	54.22	4182248	2191045	4182248	2104239	396246350	40.57	0.81	0	2.54	0	0.10	0	0.09	0	0.00	0	15.84	0	4002058	0	302	0	293.83	0	1.56	0	0.01	0	1.20	0	0.00	0	108.60	0	1.07	0	38524	0	4766505	0	121100	0	4766	0	4438	0	0	0	755243	0	1132	0	0	0	7260	0	1106284	0	11184	0	1125860	0	81.42	0	3880958	0	31322	1016515	32.453706659856	4766505.0	4002058.0	38524.0	121100.0	4766.0	4438.0	0.0	755243.0	3880958.0	84.0	0.8	2.5	0.1	0.1	0.0	15.8	81.4	151	151	151.00	7	719742255	29.1	21.4	21.7	27.8	0.0	30.6	20.0	smartseq
1451083	SRR3640244	SRP076212	SRS1489031	SRX1827073	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189875: D12_1000701001-OGC14-sal_1_2ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189875		GSM2189875	D12_1000701001-OGC14-sal_1_2ul_1 OGC14-sal FACS-scRNA-Seq	47677050	317847	2016-07-18 10:56:32	17974034	47677050	317847	2	317847	index:0,count:317847,average:75,stdev:0|index:1,count:317847,average:75,stdev:0	GSM2189875_r4						1.51	2.27	0.02	40069542	43868265	37665132	41690099	109.48	110.69	292531	265510	230.175	1170.351	146	1407	74.56	79.55	317433	218113	317433	218113	65.0	65.47	317433	190142	317433	179504	6950888	17.35	1.71	0	5.77	0	0.23	0	0.19	0	0.00	0	7.55	0	292531	0	150	0	147.93	0	4.27	0	0.05	0	1.09	0	0.02	0	95.35	0	0.30	0	5446	0	317847	0	18346	0	728	0	599	0	0	0	23989	0	35	0	0	0	351	0	46907	0	418	0	47711	0	86.26	0	274185	0	14346	45930	3.201589293183	317847.0	292531.0	5446.0	18346.0	728.0	599.0	0.0	23989.0	274185.0	92.0	1.7	5.8	0.2	0.2	0.0	7.5	86.3	75	75	75.00	6	23838525	25.1	24.7	24.6	25.6	0.0	34.7	27.9	smartseq
1451084	SRR3641244	SRP076212	SRS1489286	SRX1827328	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190130: H1_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190130		GSM2190130	H1_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	49450200	329668	2016-07-18 10:56:32	18477557	49450200	329668	2	329668	index:0,count:329668,average:75,stdev:0|index:1,count:329668,average:75,stdev:0	GSM2190130_r1						1.21	2.19	0.01	42840393	48610074	40359960	46311770	113.47	114.75	309428	272464	243.060	1519.653	144	1391	81.04	86.29	335514	250770	335514	250770	68.35	68.97	335514	211491	335514	200427	4873256	11.38	1.65	0	5.71	0	0.23	0	0.10	0	0.00	0	5.81	0	309428	0	150	0	148.08	0	4.33	0	0.06	0	1.06	0	0.02	0	98.90	0	0.29	0	5428	0	329668	0	18809	0	766	0	315	0	0	0	19159	0	49	0	0	0	431	0	60485	0	699	0	61664	0	88.16	0	290619	0	19123	59901	3.132406003242	329668.0	309428.0	5428.0	18809.0	766.0	315.0	0.0	19159.0	290619.0	93.9	1.6	5.7	0.2	0.1	0.0	5.8	88.2	75	75	75.00	6	24725100	24.5	25.4	25.4	24.8	0.0	34.8	28.3	smartseq
1451098	SRR3638245	SRP076212	SRS1488260	SRX1826302	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189104: 1-0-g-0-BTN22-C13-8ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189104		GSM2189104	1-0-g-0-BTN22-C13-8ul-1 BTN22 Mic-scRNA-Seq	35857200	239048	2016-07-18 10:56:32	17007831	35857200	239048	2	239048	index:0,count:239048,average:75,stdev:0|index:1,count:239048,average:75,stdev:0	GSM2189104_r4						1.15	3.18	0.09	31585295	30299558	30844170	29704917	95.93	96.31	219514	211451	251.194	775.731	221	978	37.14	38.05	228020	81531	228020	81531	37.62	37.08	228020	82587	228020	79459	18531479	58.67	0.84	0	2.20	0	0.09	0	0.20	0	0.00	0	7.88	0	219514	0	150	0	148.63	0	1.38	0	0.01	0	1.23	0	0.00	0	50.62	0	0.74	0	2007	0	239048	0	5252	0	214	0	474	0	0	0	18846	0	15	0	0	0	94	0	11441	0	199	0	11749	0	89.63	0	214262	0	6208	11408	1.837628865979	239048.0	219514.0	2007.0	5252.0	214.0	474.0	0.0	18846.0	214262.0	91.8	0.8	2.2	0.1	0.2	0.0	7.9	89.6	75	75	75.00	7	17928600	30.2	20.1	20.1	29.5	0.0	33.4	21.6	smartseq
1451099	SRR3639245	SRP076212	SRS1488648	SRX1826690	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189492: 1ll-BTN17-C57 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189492		GSM2189492	1ll-BTN17-C57 BTN17 Mic-scRNA-Seq	1563182200	5176100	2016-07-18 10:56:32	806957617	1563182200	5176100	2	5176100	index:0,count:5176100,average:151,stdev:0|index:1,count:5176100,average:151,stdev:0	GSM2189492_r1						2.66	7.5	0.04	1043141281	1047052444	995706023	1003098500	100.37	100.74	4298406	3891377	279.519	900.677	225	19287	79.15	83.06	4592439	3402338	4592439	3402338	78.83	78.69	4592439	3388306	4592439	3223488	163268480	15.65	0.80	0	3.91	0	0.17	0	0.08	0	0.00	0	16.71	0	4298406	0	302	0	293.03	0	1.70	0	0.02	0	1.18	0	0.00	0	114.32	0	1.12	0	41592	0	5176100	0	202146	0	9047	0	3951	0	0	0	864696	0	861	0	0	0	9831	0	1958903	0	13209	0	1982804	0	79.14	0	4096260	0	36656	1785993	48.723073985159	5176100.0	4298406.0	41592.0	202146.0	9047.0	3951.0	0.0	864696.0	4096260.0	83.0	0.8	3.9	0.2	0.1	0.0	16.7	79.1	151	151	151.00	7	781591100	28.1	22.4	22.8	26.7	0.0	30.6	19.9	smartseq
1451100	SRR3640245	SRP076212	SRS1489032	SRX1827074	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189876: D12_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189876		GSM2189876	D12_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	55101150	367341	2016-07-18 10:56:32	20558865	55101150	367341	2	367341	index:0,count:367341,average:75,stdev:0|index:1,count:367341,average:75,stdev:0	GSM2189876_r1						2.05	2.62	0.03	46421201	51912540	43114613	48860689	111.83	113.33	338791	303047	230.355	1341.790	136	1584	79.16	85.54	373534	268198	373534	268198	68.28	69.13	373534	231332	373534	216724	5303037	11.42	1.68	0	6.88	0	0.34	0	0.14	0	0.00	0	7.29	0	338791	0	150	0	147.91	0	4.65	0	0.06	0	1.08	0	0.02	0	120.22	0	0.29	0	6188	0	367341	0	25270	0	1239	0	521	0	0	0	26790	0	49	0	0	0	475	0	63250	0	517	0	64291	0	85.35	0	313521	0	19534	61953	3.171547046176	367341.0	338791.0	6188.0	25270.0	1239.0	521.0	0.0	26790.0	313521.0	92.2	1.7	6.9	0.3	0.1	0.0	7.3	85.3	75	75	75.00	6	27550575	24.6	25.1	25.1	25.1	0.0	34.8	28.2	smartseq
1451101	SRR3641245	SRP076212	SRS1489286	SRX1827328	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190130: H1_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190130		GSM2190130	H1_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	49116450	327443	2016-07-18 10:56:32	18441791	49116450	327443	2	327443	index:0,count:327443,average:75,stdev:0|index:1,count:327443,average:75,stdev:0	GSM2190130_r2						1.21	2.2	0.01	42404630	48092017	39914051	45789367	113.41	114.72	306253	269306	243.327	1533.296	143	1336	80.91	86.21	332093	247798	332093	247798	68.26	68.97	332093	209035	332093	198239	4882209	11.51	1.60	0	5.75	0	0.22	0	0.10	0	0.00	0	6.15	0	306253	0	150	0	148.04	0	4.42	0	0.06	0	1.05	0	0.02	0	98.23	0	0.31	0	5242	0	327443	0	18815	0	722	0	321	0	0	0	20147	0	54	0	0	0	391	0	60102	0	649	0	61196	0	87.78	0	287438	0	19124	59277	3.099613051663	327443.0	306253.0	5242.0	18815.0	722.0	321.0	0.0	20147.0	287438.0	93.5	1.6	5.7	0.2	0.1	0.0	6.2	87.8	75	75	75.00	6	24558225	24.5	25.3	25.3	24.8	0.0	34.8	28.2	smartseq
1451115	SRR3638246	SRP076212	SRS1488261	SRX1826303	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189105: 1-0-g-0-BTN22-C15-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189105		GSM2189105	1-0-g-0-BTN22-C15-10ul-1 BTN22 Mic-scRNA-Seq	44623500	297490	2016-07-18 10:56:32	21292894	44623500	297490	2	297490	index:0,count:297490,average:75,stdev:0|index:1,count:297490,average:75,stdev:0	GSM2189105_r1						1.14	3.19	0.09	39040222	37405868	38030822	36604524	95.81	96.25	271651	260221	246.327	787.413	185	1193	37.92	38.94	283448	102998	283448	102998	38.54	37.9	283448	104687	283448	100243	22453880	57.51	0.93	0	2.41	0	0.09	0	0.23	0	0.00	0	8.36	0	271651	0	150	0	148.54	0	1.41	0	0.01	0	1.18	0	0.00	0	63.00	0	0.75	0	2760	0	297490	0	7173	0	280	0	698	0	0	0	24861	0	14	0	0	0	135	0	16108	0	261	0	16518	0	88.90	0	264478	0	7920	16169	2.041540404040	297490.0	271651.0	2760.0	7173.0	280.0	698.0	0.0	24861.0	264478.0	91.3	0.9	2.4	0.1	0.2	0.0	8.4	88.9	75	75	75.00	7	22311750	30.1	20.2	20.3	29.4	0.0	33.3	21.5	smartseq
1451116	SRR3639246	SRP076212	SRS1488649	SRX1826691	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189493: 1ll-BTN17-C63 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;OPC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189493		GSM2189493	1ll-BTN17-C63 BTN17 Mic-scRNA-Seq	1593863286	5277693	2016-07-18 10:56:32	818657860	1593863286	5277693	2	5277693	index:0,count:5277693,average:151,stdev:0|index:1,count:5277693,average:151,stdev:0	GSM2189493_r1						1.84	3.3	0.03	1081772542	1073126971	1012609883	1009060627	99.2	99.65	4436274	4063804	282.881	740.820	230	20211	73.84	79.07	4888688	3275818	4888688	3275818	75.75	75.57	4888688	3360432	4888688	3130733	210593650	19.47	0.73	0	5.56	0	0.19	0	0.04	0	0.00	0	15.72	0	4436274	0	302	0	293.51	0	1.52	0	0.01	0	1.19	0	0.00	0	118.01	0	1.07	0	38749	0	5277693	0	293572	0	9818	0	2162	0	0	0	829439	0	1774	0	0	0	12689	0	1857053	0	11957	0	1883473	0	78.49	0	4142702	0	20768	1745432	84.044298921418	5277693.0	4436274.0	38749.0	293572.0	9818.0	2162.0	0.0	829439.0	4142702.0	84.1	0.7	5.6	0.2	0.0	0.0	15.7	78.5	151	151	151.00	7	796931643	28.6	21.8	22.2	27.3	0.0	30.6	19.9	smartseq
1451117	SRR3640246	SRP076212	SRS1489032	SRX1827074	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189876: D12_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189876		GSM2189876	D12_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	54483900	363226	2016-07-18 10:56:32	20442134	54483900	363226	2	363226	index:0,count:363226,average:75,stdev:0|index:1,count:363226,average:75,stdev:0	GSM2189876_r2						2.05	2.6	0.02	45838432	51231638	42558520	48199021	111.77	113.25	334159	298389	231.131	1338.063	146	1656	79.29	85.7	368583	264963	368583	264963	68.53	69.38	368583	228992	368583	214511	5195010	11.33	1.67	0	6.88	0	0.34	0	0.13	0	0.00	0	7.53	0	334159	0	150	0	147.92	0	4.62	0	0.06	0	1.07	0	0.02	0	108.97	0	0.31	0	6078	0	363226	0	24990	0	1217	0	482	0	0	0	27368	0	38	0	0	0	472	0	63181	0	525	0	64216	0	85.12	0	309169	0	19372	61973	3.199101796407	363226.0	334159.0	6078.0	24990.0	1217.0	482.0	0.0	27368.0	309169.0	92.0	1.7	6.9	0.3	0.1	0.0	7.5	85.1	75	75	75.00	6	27241950	24.7	25.1	25.1	25.1	0.0	34.7	28.0	smartseq
1451118	SRR3641246	SRP076212	SRS1489286	SRX1827328	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190130: H1_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190130		GSM2190130	H1_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	48835350	325569	2016-07-18 10:56:32	18471791	48835350	325569	2	325569	index:0,count:325569,average:75,stdev:0|index:1,count:325569,average:75,stdev:0	GSM2190130_r3						1.22	2.19	0.01	42322578	48033369	39824808	45718295	113.49	114.8	305590	268680	244.731	1523.057	125	1376	81.05	86.39	331738	247668	331738	247668	68.52	69.22	331738	209387	331738	198444	4834134	11.42	1.64	0	5.80	0	0.24	0	0.10	0	0.00	0	5.80	0	305590	0	150	0	148.06	0	4.40	0	0.06	0	1.05	0	0.02	0	106.55	0	0.31	0	5350	0	325569	0	18895	0	773	0	336	0	0	0	18870	0	55	0	0	0	393	0	60044	0	620	0	61112	0	88.06	0	286695	0	19210	59300	3.086933888600	325569.0	305590.0	5350.0	18895.0	773.0	336.0	0.0	18870.0	286695.0	93.9	1.6	5.8	0.2	0.1	0.0	5.8	88.1	75	75	75.00	6	24417675	24.5	25.3	25.3	24.8	0.0	34.7	27.8	smartseq
1451131	SRR3638247	SRP076212	SRS1488261	SRX1826303	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189105: 1-0-g-0-BTN22-C15-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189105		GSM2189105	1-0-g-0-BTN22-C15-10ul-1 BTN22 Mic-scRNA-Seq	44745150	298301	2016-07-18 10:56:32	21118165	44745150	298301	2	298301	index:0,count:298301,average:75,stdev:0|index:1,count:298301,average:75,stdev:0	GSM2189105_r2						1.18	3.19	0.11	39258832	37620500	38247836	36809298	95.83	96.24	272931	261196	249.723	807.912	196	1199	37.98	39.01	284805	103660	284805	103660	38.6	37.96	284805	105342	284805	100865	22546129	57.43	0.95	0	2.41	0	0.09	0	0.24	0	0.00	0	8.17	0	272931	0	150	0	148.56	0	1.40	0	0.01	0	1.16	0	0.00	0	56.52	0	0.72	0	2823	0	298301	0	7186	0	270	0	717	0	0	0	24383	0	19	0	0	0	128	0	16283	0	236	0	16666	0	89.09	0	265745	0	7962	16219	2.037050992213	298301.0	272931.0	2823.0	7186.0	270.0	717.0	0.0	24383.0	265745.0	91.5	0.9	2.4	0.1	0.2	0.0	8.2	89.1	75	75	75.00	7	22372575	30.1	20.2	20.3	29.4	0.0	33.5	21.7	smartseq
1451132	SRR3639247	SRP076212	SRS1488650	SRX1826692	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189494: 1ll-BTN17-C65 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189494		GSM2189494	1ll-BTN17-C65 BTN17 Mic-scRNA-Seq	1503687596	4979098	2016-07-18 10:56:32	774068345	1503687596	4979098	2	4979098	index:0,count:4979098,average:151,stdev:0|index:1,count:4979098,average:151,stdev:0	GSM2189494_r1						0.47	2.76	0.13	1004646930	993506043	971373064	963123723	98.89	99.15	4112051	3810968	283.657	738.387	233	20672	80.28	83.12	4371124	3301100	4371124	3301100	79.52	79.74	4371124	3269753	4371124	3167007	151401717	15.07	0.71	0	2.82	0	0.32	0	0.13	0	0.00	0	16.96	0	4112051	0	302	0	293.55	0	1.46	0	0.01	0	1.17	0	0.00	0	114.17	0	1.08	0	35239	0	4979098	0	140627	0	16031	0	6518	0	0	0	844498	0	927	0	0	0	9001	0	1441756	0	11961	0	1463645	0	79.76	0	3971424	0	9081	1346239	148.247880189406	4979098.0	4112051.0	35239.0	140627.0	16031.0	6518.0	0.0	844498.0	3971424.0	82.6	0.7	2.8	0.3	0.1	0.0	17.0	79.8	151	151	151.00	7	751843798	28.1	22.4	22.8	26.7	0.0	30.5	19.7	smartseq
1451133	SRR3640247	SRP076212	SRS1489032	SRX1827074	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189876: D12_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189876		GSM2189876	D12_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	54023400	360156	2016-07-18 10:56:32	20374788	54023400	360156	2	360156	index:0,count:360156,average:75,stdev:0|index:1,count:360156,average:75,stdev:0	GSM2189876_r3						2.07	2.55	0.01	45646510	51034783	42381301	48030528	111.8	113.33	332604	297009	231.669	1330.950	146	1577	79.36	85.78	366888	263964	366888	263964	68.55	69.41	366888	228000	366888	213600	5143155	11.27	1.68	0	6.91	0	0.35	0	0.16	0	0.00	0	7.15	0	332604	0	150	0	147.93	0	4.67	0	0.06	0	1.08	0	0.02	0	86.44	0	0.31	0	6052	0	360156	0	24873	0	1243	0	562	0	0	0	25747	0	41	0	0	0	439	0	63060	0	478	0	64018	0	85.44	0	307731	0	19445	61978	3.187348932888	360156.0	332604.0	6052.0	24873.0	1243.0	562.0	0.0	25747.0	307731.0	92.3	1.7	6.9	0.3	0.2	0.0	7.1	85.4	75	75	75.00	6	27011700	24.7	25.1	25.2	25.1	0.0	34.6	27.7	smartseq
1451134	SRR3641247	SRP076212	SRS1489286	SRX1827328	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190130: H1_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190130		GSM2190130	H1_1000701001-OGC14-sal_1_4ul_1 OGC14-sal FACS-scRNA-Seq	48822600	325484	2016-07-18 10:56:32	18500913	48822600	325484	2	325484	index:0,count:325484,average:75,stdev:0|index:1,count:325484,average:75,stdev:0	GSM2190130_r4						1.21	2.17	0.02	42236785	47961559	39751561	45640990	113.55	114.82	304743	267624	245.051	1529.098	153	1335	81.01	86.32	330629	246869	330629	246869	68.3	69.0	330629	208142	330629	197342	4828460	11.43	1.66	0	5.76	0	0.23	0	0.10	0	0.00	0	6.04	0	304743	0	150	0	148.06	0	4.38	0	0.06	0	1.06	0	0.02	0	97.65	0	0.31	0	5388	0	325484	0	18753	0	756	0	324	0	0	0	19661	0	36	0	0	0	378	0	60192	0	635	0	61241	0	87.87	0	285990	0	19144	59269	3.095956957794	325484.0	304743.0	5388.0	18753.0	756.0	324.0	0.0	19661.0	285990.0	93.6	1.7	5.8	0.2	0.1	0.0	6.0	87.9	75	75	75.00	6	24411300	24.5	25.3	25.3	24.8	0.0	34.7	27.9	smartseq
1451146	SRR3638248	SRP076212	SRS1488261	SRX1826303	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189105: 1-0-g-0-BTN22-C15-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189105		GSM2189105	1-0-g-0-BTN22-C15-10ul-1 BTN22 Mic-scRNA-Seq	43219200	288128	2016-07-18 10:56:32	20740027	43219200	288128	2	288128	index:0,count:288128,average:75,stdev:0|index:1,count:288128,average:75,stdev:0	GSM2189105_r3						1.16	3.16	0.11	37817160	36255951	36832623	35474664	95.87	96.31	263039	251918	246.179	795.850	199	1189	38.03	39.07	274603	100031	274603	100031	38.62	37.97	274603	101579	274603	97218	21717247	57.43	0.92	0	2.43	0	0.08	0	0.22	0	0.00	0	8.41	0	263039	0	150	0	148.55	0	1.37	0	0.01	0	1.13	0	0.00	0	69.15	0	0.78	0	2640	0	288128	0	6996	0	223	0	623	0	0	0	24243	0	25	0	0	0	140	0	15447	0	271	0	15883	0	88.86	0	256043	0	7690	15446	2.008582574772	288128.0	263039.0	2640.0	6996.0	223.0	623.0	0.0	24243.0	256043.0	91.3	0.9	2.4	0.1	0.2	0.0	8.4	88.9	75	75	75.00	7	21609600	30.1	20.2	20.3	29.4	0.0	33.3	21.4	smartseq
1451147	SRR3639248	SRP076212	SRS1488651	SRX1826693	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189495: 1ll-BTN17-C66 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189495		GSM2189495	1ll-BTN17-C66 BTN17 Mic-scRNA-Seq	1357200382	4494041	2016-07-18 10:56:32	696539300	1357200382	4494041	2	4494041	index:0,count:4494041,average:151,stdev:0|index:1,count:4494041,average:151,stdev:0	GSM2189495_r1						7.26	2.54	0.1	916431592	894041264	854995426	836059224	97.56	97.79	3739809	3489167	287.303	689.090	230	18542	79.35	85.19	4104538	2967706	4104538	2967706	81.96	81.69	4104538	3065155	4104538	2845831	107222420	11.70	0.85	0	5.70	0	0.28	0	0.14	0	0.00	0	16.36	0	3739809	0	302	0	293.38	0	1.64	0	0.02	0	1.22	0	0.01	0	95.17	0	1.08	0	38358	0	4494041	0	256016	0	12382	0	6418	0	0	0	735432	0	62	0	0	0	8794	0	1230423	0	12655	0	1251934	0	77.52	0	3483793	0	9061	1146545	126.536254276570	4494041.0	3739809.0	38358.0	256016.0	12382.0	6418.0	0.0	735432.0	3483793.0	83.2	0.9	5.7	0.3	0.1	0.0	16.4	77.5	151	151	151.00	7	678600191	28.1	22.2	22.7	27.0	0.0	30.6	19.8	smartseq
1451148	SRR3640248	SRP076212	SRS1489032	SRX1827074	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189876: D12_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189876		GSM2189876	D12_1000701201-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	54326250	362175	2016-07-18 10:56:32	20561856	54326250	362175	2	362175	index:0,count:362175,average:75,stdev:0|index:1,count:362175,average:75,stdev:0	GSM2189876_r4						2.06	2.61	0.02	45813305	51212888	42556990	48209154	111.79	113.28	333845	297581	231.646	1365.418	134	1573	79.33	85.7	368201	264827	368201	264827	68.49	69.33	368201	228658	368201	214235	5196310	11.34	1.68	0	6.86	0	0.35	0	0.15	0	0.00	0	7.33	0	333845	0	150	0	147.89	0	4.70	0	0.07	0	1.08	0	0.02	0	108.65	0	0.31	0	6078	0	362175	0	24828	0	1258	0	540	0	0	0	26532	0	55	0	0	0	409	0	62931	0	499	0	63894	0	85.32	0	309017	0	19463	61828	3.176694240353	362175.0	333845.0	6078.0	24828.0	1258.0	540.0	0.0	26532.0	309017.0	92.2	1.7	6.9	0.3	0.1	0.0	7.3	85.3	75	75	75.00	6	27163125	24.7	25.1	25.1	25.1	0.0	34.7	27.8	smartseq
1451149	SRR3641248	SRP076212	SRS1489287	SRX1827329	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190131: H2_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190131		GSM2190131	H2_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	43272600	288484	2016-07-18 10:56:32	14435187	43272600	288484	2	288484	index:0,count:288484,average:75,stdev:0|index:1,count:288484,average:75,stdev:0	GSM2190131_r1						1.45	2.41	0.04	35274700	38193322	33155079	36269224	108.27	109.39	266231	238629	202.762	1187.501	123	1508	80.7	86.17	290881	214845	290881	214845	73.31	73.97	290881	195174	290881	184431	4236298	12.01	1.69	0	5.85	0	0.33	0	0.11	0	0.00	0	7.27	0	266231	0	150	0	147.63	0	3.93	0	0.04	0	1.14	0	0.01	0	103.85	0	0.23	0	4861	0	288484	0	16890	0	961	0	314	0	0	0	20978	0	51	0	0	0	397	0	60558	0	426	0	61432	0	86.43	0	249341	0	20397	57866	2.836985831250	288484.0	266231.0	4861.0	16890.0	961.0	314.0	0.0	20978.0	249341.0	92.3	1.7	5.9	0.3	0.1	0.0	7.3	86.4	75	75	75.00	6	21636300	24.8	25.1	25.0	25.1	0.0	35.2	30.1	smartseq
1451163	SRR3638249	SRP076212	SRS1488261	SRX1826303	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189105: 1-0-g-0-BTN22-C15-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189105		GSM2189105	1-0-g-0-BTN22-C15-10ul-1 BTN22 Mic-scRNA-Seq	43333050	288887	2016-07-18 10:56:32	20610895	43333050	288887	2	288887	index:0,count:288887,average:75,stdev:0|index:1,count:288887,average:75,stdev:0	GSM2189105_r4						1.17	3.16	0.08	37833844	36246855	36843064	35458519	95.81	96.24	263414	252248	245.292	812.666	216	1198	38.03	39.08	275173	100186	275173	100186	38.67	38.01	275173	101865	275173	97455	21678823	57.30	0.94	0	2.44	0	0.08	0	0.24	0	0.00	0	8.49	0	263414	0	150	0	148.53	0	1.38	0	0.01	0	1.17	0	0.00	0	52.00	0	0.76	0	2708	0	288887	0	7046	0	237	0	696	0	0	0	24540	0	28	0	0	0	120	0	15724	0	274	0	16146	0	88.74	0	256368	0	7765	15687	2.020218931101	288887.0	263414.0	2708.0	7046.0	237.0	696.0	0.0	24540.0	256368.0	91.2	0.9	2.4	0.1	0.2	0.0	8.5	88.7	75	75	75.00	7	21666525	30.2	20.2	20.3	29.4	0.0	33.3	21.5	smartseq
1451164	SRR3639249	SRP076212	SRS1488652	SRX1826694	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189496: 1ll-BTN17-C69 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189496		GSM2189496	1ll-BTN17-C69 BTN17 Mic-scRNA-Seq	986690172	3267186	2016-07-18 10:56:32	512793845	986690172	3267186	2	3267186	index:0,count:3267186,average:151,stdev:0|index:1,count:3267186,average:151,stdev:0	GSM2189496_r1						3.7	11.58	0.05	639565038	647493661	604027061	614405003	101.24	101.72	2684639	2418754	270.840	860.142	225	12883	84.82	89.95	2895824	2277106	2895824	2277106	85.11	85.2	2895824	2284956	2895824	2156849	59917604	9.37	0.84	0	4.69	0	0.12	0	0.07	0	0.00	0	17.63	0	2684639	0	302	0	292.34	0	1.77	0	0.02	0	1.15	0	0.00	0	79.47	0	1.19	0	27416	0	3267186	0	153132	0	3999	0	2431	0	0	0	576117	0	637	0	0	0	5012	0	1291896	0	7034	0	1304579	0	77.48	0	2531507	0	22516	1155756	51.330431693018	3267186.0	2684639.0	27416.0	153132.0	3999.0	2431.0	0.0	576117.0	2531507.0	82.2	0.8	4.7	0.1	0.1	0.0	17.6	77.5	151	151	151.00	7	493345086	28.1	22.3	23.0	26.6	0.0	30.6	19.8	smartseq
1451165	SRR3640249	SRP076212	SRS1489033	SRX1827075	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189877: D12_1000701204-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189877		GSM2189877	D12_1000701204-OGC16-sal_1_4ul_1 OGC16-sal FACS-scRNA-Seq	126751050	845007	2016-07-18 10:56:32	43821581	126751050	845007	2	845007	index:0,count:845007,average:75,stdev:0|index:1,count:845007,average:75,stdev:0	GSM2189877_r1						1.62	2.14	0.03	106492309	119518431	99976510	113557651	112.23	113.58	772374	672475	258.933	1674.723	125	3133	79.45	84.91	842045	613637	842045	613637	68.24	68.92	842045	527076	842045	498064	13285711	12.48	1.77	0	5.88	0	0.26	0	0.13	0	0.00	0	8.20	0	772374	0	150	0	147.92	0	4.53	0	0.06	0	1.10	0	0.02	0	217.29	0	0.24	0	14951	0	845007	0	49707	0	2231	0	1095	0	0	0	69307	0	132	0	0	0	1068	0	148750	0	1340	0	151290	0	85.52	0	722667	0	26781	146580	5.473283297860	845007.0	772374.0	14951.0	49707.0	2231.0	1095.0	0.0	69307.0	722667.0	91.4	1.8	5.9	0.3	0.1	0.0	8.2	85.5	75	75	75.00	6	63375525	24.7	25.0	25.1	25.2	0.0	35.2	29.9	smartseq
1451166	SRR3641249	SRP076212	SRS1489287	SRX1827329	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190131: H2_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190131		GSM2190131	H2_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	43111950	287413	2016-07-18 10:56:32	14483307	43111950	287413	2	287413	index:0,count:287413,average:75,stdev:0|index:1,count:287413,average:75,stdev:0	GSM2190131_r2						1.45	2.41	0.03	35016795	37905987	32901355	36001001	108.25	109.42	264165	236987	203.396	1224.975	125	1484	80.68	86.18	288811	213126	288811	213126	73.32	73.99	288811	193678	288811	182978	4215397	12.04	1.67	0	5.86	0	0.32	0	0.11	0	0.00	0	7.65	0	264165	0	150	0	147.64	0	3.91	0	0.04	0	1.11	0	0.01	0	86.22	0	0.24	0	4786	0	287413	0	16856	0	933	0	318	0	0	0	21997	0	65	0	0	0	383	0	60365	0	384	0	61197	0	86.05	0	247309	0	20432	57818	2.829776820673	287413.0	264165.0	4786.0	16856.0	933.0	318.0	0.0	21997.0	247309.0	91.9	1.7	5.9	0.3	0.1	0.0	7.7	86.0	75	75	75.00	6	21555975	24.8	25.1	24.9	25.2	0.0	35.2	30.0	smartseq
1451278	SRR3638250	SRP076212	SRS1488262	SRX1826304	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189106: 1-0-g-0-BTN22-C22-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189106		GSM2189106	1-0-g-0-BTN22-C22-10ul-1 BTN22 Mic-scRNA-Seq	73117950	487453	2016-07-18 10:56:32	34530624	73117950	487453	2	487453	index:0,count:487453,average:75,stdev:0|index:1,count:487453,average:75,stdev:0	GSM2189106_r1						1.2	3.79	0.09	63813632	61871112	61272597	59844726	96.96	97.67	446385	411837	243.893	1035.588	196	1961	67.92	70.77	474390	303200	474390	303200	68.92	68.88	474390	307665	474390	295096	16602653	26.02	0.98	0	3.69	0	0.07	0	0.11	0	0.00	0	8.24	0	446385	0	150	0	148.31	0	1.34	0	0.01	0	1.16	0	0.00	0	97.49	0	0.68	0	4780	0	487453	0	17980	0	355	0	531	0	0	0	40182	0	46	0	0	0	340	0	49493	0	526	0	50405	0	87.89	0	428405	0	13228	50361	3.807151496825	487453.0	446385.0	4780.0	17980.0	355.0	531.0	0.0	40182.0	428405.0	91.6	1.0	3.7	0.1	0.1	0.0	8.2	87.9	75	75	75.00	7	36558975	30.0	20.0	20.2	29.8	0.0	33.4	21.8	smartseq
1451279	SRR3639250	SRP076212	SRS1488653	SRX1826695	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189497: 1ll-BTN17-C70 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;OPC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189497		GSM2189497	1ll-BTN17-C70 BTN17 Mic-scRNA-Seq	1201965134	3980017	2016-07-18 10:56:32	619894562	1201965134	3980017	2	3980017	index:0,count:3980017,average:151,stdev:0|index:1,count:3980017,average:151,stdev:0	GSM2189497_r1						3.19	2.98	0.11	790574858	795473988	732531302	741199077	100.62	101.18	3360096	3052286	268.184	811.985	230	16484	84.9	91.87	3749693	2852712	3749693	2852712	86.63	87.22	3749693	2911006	3749693	2708249	60980872	7.71	0.74	0	6.41	0	0.19	0	0.04	0	0.00	0	15.34	0	3360096	0	302	0	292.40	0	1.56	0	0.01	0	1.20	0	0.00	0	97.47	0	1.14	0	29327	0	3980017	0	255070	0	7560	0	1682	0	0	0	610679	0	706	0	0	0	13264	0	1685215	0	9077	0	1708262	0	78.02	0	3105026	0	19436	1538098	79.136550730603	3980017.0	3360096.0	29327.0	255070.0	7560.0	1682.0	0.0	610679.0	3105026.0	84.4	0.7	6.4	0.2	0.0	0.0	15.3	78.0	151	151	151.00	7	600982567	27.7	22.7	22.8	26.8	0.0	30.9	20.4	smartseq
1451292	SRR3638251	SRP076212	SRS1488262	SRX1826304	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189106: 1-0-g-0-BTN22-C22-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189106		GSM2189106	1-0-g-0-BTN22-C22-10ul-1 BTN22 Mic-scRNA-Seq	72396600	482644	2016-07-18 10:56:32	33779515	72396600	482644	2	482644	index:0,count:482644,average:75,stdev:0|index:1,count:482644,average:75,stdev:0	GSM2189106_r2						1.17	3.74	0.09	63445947	61482297	60934845	59486022	96.91	97.62	443268	408567	246.998	1032.513	212	1863	67.9	70.73	470552	300986	470552	300986	68.92	68.89	470552	305488	470552	293162	16554368	26.09	1.00	0	3.67	0	0.08	0	0.10	0	0.00	0	7.97	0	443268	0	150	0	148.35	0	1.35	0	0.01	0	1.18	0	0.00	0	91.45	0	0.65	0	4827	0	482644	0	17724	0	393	0	505	0	0	0	38478	0	57	0	0	0	341	0	49202	0	536	0	50136	0	88.17	0	425544	0	13201	50220	3.804257253238	482644.0	443268.0	4827.0	17724.0	393.0	505.0	0.0	38478.0	425544.0	91.8	1.0	3.7	0.1	0.1	0.0	8.0	88.2	75	75	75.00	7	36198300	30.0	20.0	20.2	29.7	0.0	33.7	22.1	smartseq
1451293	SRR3639251	SRP076212	SRS1488654	SRX1826696	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189498: 1ll-BTN17-C72 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;OPC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189498		GSM2189498	1ll-BTN17-C72 BTN17 Mic-scRNA-Seq	1308347050	4332275	2016-07-18 10:56:32	674327927	1308347050	4332275	2	4332275	index:0,count:4332275,average:151,stdev:0|index:1,count:4332275,average:151,stdev:0	GSM2189498_r1						1.08	2.99	0.14	888564840	876009470	852762787	844006449	98.59	98.97	3684252	3463967	274.889	713.800	230	17312	56.3	58.76	3922531	2074276	3922531	2074276	56.83	56.17	3922531	2093930	3922531	1982846	352031909	39.62	0.72	0	3.55	0	0.11	0	0.07	0	0.00	0	14.78	0	3684252	0	302	0	293.49	0	1.50	0	0.01	0	1.19	0	0.00	0	113.02	0	1.12	0	31077	0	4332275	0	153914	0	4674	0	2855	0	0	0	640494	0	764	0	0	0	8099	0	1103836	0	8495	0	1121194	0	81.49	0	3530338	0	23327	1020942	43.766536631371	4332275.0	3684252.0	31077.0	153914.0	4674.0	2855.0	0.0	640494.0	3530338.0	85.0	0.7	3.6	0.1	0.1	0.0	14.8	81.5	151	151	151.00	7	654173525	28.6	21.8	22.1	27.5	0.0	30.9	20.4	smartseq
1451294	SRR3640251	SRP076212	SRS1489034	SRX1827076	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189878: D1_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189878		GSM2189878	D1_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	53008650	353391	2016-07-18 10:56:32	17756507	53008650	353391	2	353391	index:0,count:353391,average:75,stdev:0|index:1,count:353391,average:75,stdev:0	GSM2189878_r2						1.23	2.67	0.07	43123537	46046180	40727488	43874602	106.78	107.73	326006	290454	199.363	1308.459	124	1843	82.67	87.79	354358	269514	354358	269514	76.51	77.25	354358	249411	354358	237152	4437224	10.29	1.60	0	5.38	0	0.36	0	0.09	0	0.00	0	7.31	0	326006	0	150	0	147.65	0	3.75	0	0.03	0	1.09	0	0.01	0	106.02	0	0.22	0	5639	0	353391	0	19014	0	1268	0	301	0	0	0	25816	0	73	0	0	0	645	0	78261	0	439	0	79418	0	86.87	0	306992	0	22748	74786	3.287585721822	353391.0	326006.0	5639.0	19014.0	1268.0	301.0	0.0	25816.0	306992.0	92.3	1.6	5.4	0.4	0.1	0.0	7.3	86.9	75	75	75.00	6	26504325	24.8	25.1	24.9	25.2	0.0	35.2	30.2	smartseq
1451295	SRR3641251	SRP076212	SRS1489287	SRX1827329	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190131: H2_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190131		GSM2190131	H2_1000700101-OGC9-sal_1_38ul_1 OGC09-sal FACS-scRNA-Seq	42418500	282790	2016-07-18 10:56:32	14410870	42418500	282790	2	282790	index:0,count:282790,average:75,stdev:0|index:1,count:282790,average:75,stdev:0	GSM2190131_r4						1.44	2.39	0.03	34584685	37428627	32495909	35548962	108.22	109.4	261069	234103	202.874	1202.206	125	1454	80.84	86.35	285182	211054	285182	211054	73.54	74.21	285182	191993	285182	181367	4082423	11.80	1.70	0	5.89	0	0.32	0	0.12	0	0.00	0	7.24	0	261069	0	150	0	147.60	0	3.87	0	0.04	0	1.14	0	0.01	0	113.12	0	0.24	0	4798	0	282790	0	16660	0	909	0	344	0	0	0	20468	0	29	0	0	0	411	0	59650	0	348	0	60438	0	86.43	0	244409	0	20329	57008	2.804269762408	282790.0	261069.0	4798.0	16660.0	909.0	344.0	0.0	20468.0	244409.0	92.3	1.7	5.9	0.3	0.1	0.0	7.2	86.4	75	75	75.00	6	21209250	24.8	25.1	25.0	25.1	0.0	35.2	30.0	smartseq
1451311	SRR3638252	SRP076212	SRS1488262	SRX1826304	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189106: 1-0-g-0-BTN22-C22-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189106		GSM2189106	1-0-g-0-BTN22-C22-10ul-1 BTN22 Mic-scRNA-Seq	70381950	469213	2016-07-18 10:56:32	33425182	70381950	469213	2	469213	index:0,count:469213,average:75,stdev:0|index:1,count:469213,average:75,stdev:0	GSM2189106_r3						1.2	3.78	0.08	61354862	59560024	58923216	57616010	97.07	97.78	429297	396405	243.031	1003.615	188	1831	68.03	70.88	455766	292058	455766	292058	68.97	68.95	455766	296071	455766	284109	15970050	26.03	0.97	0	3.68	0	0.08	0	0.09	0	0.00	0	8.33	0	429297	0	150	0	148.29	0	1.36	0	0.01	0	1.17	0	0.00	0	112.61	0	0.71	0	4573	0	469213	0	17248	0	391	0	442	0	0	0	39083	0	43	0	0	0	347	0	47515	0	516	0	48421	0	87.82	0	412049	0	13036	48402	3.712948757288	469213.0	429297.0	4573.0	17248.0	391.0	442.0	0.0	39083.0	412049.0	91.5	1.0	3.7	0.1	0.1	0.0	8.3	87.8	75	75	75.00	7	35190975	30.1	20.0	20.2	29.7	0.0	33.4	21.7	smartseq
1451326	SRR3638253	SRP076212	SRS1488262	SRX1826304	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189106: 1-0-g-0-BTN22-C22-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189106		GSM2189106	1-0-g-0-BTN22-C22-10ul-1 BTN22 Mic-scRNA-Seq	70471950	469813	2016-07-18 10:56:32	33160806	70471950	469813	2	469813	index:0,count:469813,average:75,stdev:0|index:1,count:469813,average:75,stdev:0	GSM2189106_r4						1.19	3.78	0.08	61383472	59509256	58945089	57552830	96.95	97.64	429478	396469	243.094	1012.050	212	1822	67.98	70.82	456163	291947	456163	291947	68.95	68.92	456163	296137	456163	284116	15961596	26.00	0.98	0	3.67	0	0.09	0	0.10	0	0.00	0	8.40	0	429478	0	150	0	148.29	0	1.33	0	0.01	0	1.17	0	0.00	0	89.02	0	0.69	0	4587	0	469813	0	17246	0	408	0	480	0	0	0	39447	0	59	0	0	0	306	0	47875	0	467	0	48707	0	87.74	0	412232	0	13038	48781	3.741448074858	469813.0	429478.0	4587.0	17246.0	408.0	480.0	0.0	39447.0	412232.0	91.4	1.0	3.7	0.1	0.1	0.0	8.4	87.7	75	75	75.00	7	35235975	30.0	20.0	20.2	29.8	0.0	33.5	21.7	smartseq
1451327	SRR3639253	SRP076212	SRS1488656	SRX1826698	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189500: 1ll-BTN17-C79 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189500		GSM2189500	1ll-BTN17-C79 BTN17 Mic-scRNA-Seq	1297074296	4294948	2016-07-18 10:56:32	667294859	1297074296	4294948	2	4294948	index:0,count:4294948,average:151,stdev:0|index:1,count:4294948,average:151,stdev:0	GSM2189500_r1						1.38	4.6	0.06	882092232	887579556	859094476	867408396	100.62	100.97	3590518	3348339	285.065	851.450	233	16188	66.76	68.61	3726433	2397028	3726433	2397028	65.22	64.98	3726433	2341897	3726433	2270042	272338106	30.87	0.84	0	2.26	0	0.07	0	0.06	0	0.00	0	16.26	0	3590518	0	302	0	293.53	0	1.62	0	0.02	0	1.16	0	0.00	0	90.42	0	1.09	0	36269	0	4294948	0	97067	0	3218	0	2780	0	0	0	698432	0	378	0	0	0	6580	0	1080094	0	10600	0	1097652	0	81.34	0	3493451	0	13049	983020	75.332975706951	4294948.0	3590518.0	36269.0	97067.0	3218.0	2780.0	0.0	698432.0	3493451.0	83.6	0.8	2.3	0.1	0.1	0.0	16.3	81.3	151	151	151.00	7	648537148	28.9	21.5	21.9	27.6	0.0	30.6	19.9	smartseq
1451342	SRR3638254	SRP076212	SRS1488263	SRX1826305	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189107: 1-0-g-0-BTN22-C27-14ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189107		GSM2189107	1-0-g-0-BTN22-C27-14ul-1 BTN22 Mic-scRNA-Seq	45043350	300289	2016-07-18 10:56:32	21536230	45043350	300289	2	300289	index:0,count:300289,average:75,stdev:0|index:1,count:300289,average:75,stdev:0	GSM2189107_r1						1.16	3.57	0.04	39439057	38163917	38370090	37313957	96.77	97.25	274902	261746	243.685	835.912	199	1239	42.84	44.06	287194	117762	287194	117762	43.42	42.85	287194	119359	287194	114538	20858761	52.89	0.88	0	2.54	0	0.08	0	0.21	0	0.00	0	8.16	0	274902	0	150	0	148.55	0	1.38	0	0.01	0	1.17	0	0.00	0	60.06	0	0.76	0	2653	0	300289	0	7622	0	243	0	635	0	0	0	24509	0	22	0	0	0	182	0	19116	0	278	0	19598	0	89.01	0	267280	0	8891	19242	2.164210999888	300289.0	274902.0	2653.0	7622.0	243.0	635.0	0.0	24509.0	267280.0	91.5	0.9	2.5	0.1	0.2	0.0	8.2	89.0	75	75	75.00	7	22521675	30.2	20.2	20.3	29.4	0.0	33.3	21.5	smartseq
1451343	SRR3639254	SRP076212	SRS1488657	SRX1826699	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189501: 1ll-BTN17-C81 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189501		GSM2189501	1ll-BTN17-C81 BTN17 Mic-scRNA-Seq	1278976946	4235023	2016-07-18 10:56:32	656303647	1278976946	4235023	2	4235023	index:0,count:4235023,average:151,stdev:0|index:1,count:4235023,average:151,stdev:0	GSM2189501_r1						1.96	9.1	0.08	881939910	884497555	848812903	854505321	100.29	100.67	3584511	3261273	287.012	883.952	225	15470	70.44	73.29	3790809	2524922	3790809	2524922	69.68	69.33	3790809	2497613	3790809	2388642	226227816	25.65	0.81	0	3.29	0	0.15	0	0.06	0	0.00	0	15.15	0	3584511	0	302	0	293.54	0	1.67	0	0.01	0	1.21	0	0.00	0	104.43	0	1.09	0	34503	0	4235023	0	139423	0	6334	0	2428	0	0	0	641750	0	695	0	0	0	6987	0	1430308	0	9092	0	1447082	0	81.35	0	3445088	0	26397	1315316	49.828238057355	4235023.0	3584511.0	34503.0	139423.0	6334.0	2428.0	0.0	641750.0	3445088.0	84.6	0.8	3.3	0.1	0.1	0.0	15.2	81.3	151	151	151.00	7	639488473	28.3	22.1	22.5	27.1	0.0	30.7	20.0	smartseq
1451357	SRR3638255	SRP076212	SRS1488263	SRX1826305	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189107: 1-0-g-0-BTN22-C27-14ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189107		GSM2189107	1-0-g-0-BTN22-C27-14ul-1 BTN22 Mic-scRNA-Seq	45136650	300911	2016-07-18 10:56:32	21312094	45136650	300911	2	300911	index:0,count:300911,average:75,stdev:0|index:1,count:300911,average:75,stdev:0	GSM2189107_r2						1.17	3.5	0.03	39625247	38355305	38540207	37483711	96.8	97.26	276002	262407	246.458	891.303	210	1206	42.58	43.8	288366	117518	288366	117518	43.21	42.61	288366	119247	288366	114331	21068719	53.17	0.89	0	2.56	0	0.08	0	0.23	0	0.00	0	7.96	0	276002	0	150	0	148.57	0	1.34	0	0.01	0	1.20	0	0.00	0	60.18	0	0.72	0	2665	0	300911	0	7710	0	250	0	704	0	0	0	23955	0	21	0	0	0	185	0	19036	0	222	0	19464	0	89.16	0	268292	0	8956	19282	2.152970075927	300911.0	276002.0	2665.0	7710.0	250.0	704.0	0.0	23955.0	268292.0	91.7	0.9	2.6	0.1	0.2	0.0	8.0	89.2	75	75	75.00	7	22568325	30.2	20.2	20.3	29.4	0.0	33.5	21.7	smartseq
1451358	SRR3639255	SRP076212	SRS1488658	SRX1826700	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189502: 1ll-BTN17-C83 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;OPC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189502		GSM2189502	1ll-BTN17-C83 BTN17 Mic-scRNA-Seq	1879594546	6223823	2016-07-18 10:56:32	966945730	1879594546	6223823	2	6223823	index:0,count:6223823,average:151,stdev:0|index:1,count:6223823,average:151,stdev:0	GSM2189502_r1						2.03	2.91	0.05	1285713771	1276913238	1213025122	1209453963	99.32	99.71	5225937	4771042	289.386	822.565	230	22480	69.81	74.17	5692458	3648363	5692458	3648363	71.53	71.05	5692458	3738054	5692458	3494731	320399777	24.92	0.70	0	4.93	0	0.13	0	0.06	0	0.00	0	15.85	0	5225937	0	302	0	293.48	0	1.53	0	0.01	0	1.20	0	0.00	0	113.16	0	1.10	0	43698	0	6223823	0	307047	0	7912	0	3766	0	0	0	986208	0	1507	0	0	0	14548	0	2204331	0	14565	0	2234951	0	79.03	0	4918890	0	27585	2067136	74.936958491934	6223823.0	5225937.0	43698.0	307047.0	7912.0	3766.0	0.0	986208.0	4918890.0	84.0	0.7	4.9	0.1	0.1	0.0	15.8	79.0	151	151	151.00	7	939797273	28.5	22.1	22.4	27.0	0.0	30.6	19.9	smartseq
1451359	SRR3640255	SRP076212	SRS1489036	SRX1827077	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189879: D1_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189879		GSM2189879	D1_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	55155150	367701	2016-07-18 10:56:32	23418839	55155150	367701	2	367701	index:0,count:367701,average:75,stdev:0|index:1,count:367701,average:75,stdev:0	GSM2189879_r2						2.3	2.25	0.05	43482085	48110936	40635692	45532621	110.65	112.05	317397	292895	221.900	1155.717	174	1722	71.95	77.31	348272	228367	348272	228367	61.61	62.17	348272	195559	348272	183657	8749039	20.12	2.19	0	5.98	0	0.20	0	0.18	0	0.00	0	13.30	0	317397	0	150	0	147.31	0	4.95	0	0.10	0	1.05	0	0.03	0	88.25	0	0.52	0	8035	0	367701	0	22003	0	745	0	664	0	0	0	48895	0	29	0	0	0	287	0	42252	0	520	0	43088	0	80.34	0	295394	0	14217	41343	2.907997467820	367701.0	317397.0	8035.0	22003.0	745.0	664.0	0.0	48895.0	295394.0	86.3	2.2	6.0	0.2	0.2	0.0	13.3	80.3	75	75	75.00	6	27577575	25.3	24.4	24.6	25.7	0.0	33.7	25.1	smartseq
1451369	SRR3638256	SRP076212	SRS1488263	SRX1826305	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189107: 1-0-g-0-BTN22-C27-14ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189107		GSM2189107	1-0-g-0-BTN22-C27-14ul-1 BTN22 Mic-scRNA-Seq	43552500	290350	2016-07-18 10:56:32	20961826	43552500	290350	2	290350	index:0,count:290350,average:75,stdev:0|index:1,count:290350,average:75,stdev:0	GSM2189107_r3						1.13	3.55	0.04	38039108	36810045	37006473	35990337	96.77	97.25	265159	252205	243.309	877.746	188	1172	42.86	44.09	277051	113659	277051	113659	43.47	42.94	277051	115274	277051	110703	20132635	52.93	0.86	0	2.53	0	0.09	0	0.21	0	0.00	0	8.38	0	265159	0	150	0	148.53	0	1.34	0	0.01	0	1.17	0	0.00	0	49.77	0	0.79	0	2496	0	290350	0	7350	0	247	0	612	0	0	0	24332	0	24	0	0	0	170	0	18310	0	234	0	18738	0	88.79	0	257809	0	8653	18310	2.116029122848	290350.0	265159.0	2496.0	7350.0	247.0	612.0	0.0	24332.0	257809.0	91.3	0.9	2.5	0.1	0.2	0.0	8.4	88.8	75	75	75.00	7	21776250	30.2	20.2	20.3	29.3	0.0	33.2	21.4	smartseq
1451370	SRR3639256	SRP076212	SRS1488659	SRX1826701	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189503: 1ll-BTN17-C85 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Vascular|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189503		GSM2189503	1ll-BTN17-C85 BTN17 Mic-scRNA-Seq	1703724242	5641471	2016-07-18 10:56:32	871986541	1703724242	5641471	2	5641471	index:0,count:5641471,average:151,stdev:0|index:1,count:5641471,average:151,stdev:0	GSM2189503_r1						1.74	3.07	0.03	1169782029	1161196273	1139024585	1133489337	99.27	99.51	4783269	4586685	280.936	645.340	230	22703	53.12	54.61	4972434	2540851	4972434	2540851	51.61	50.98	4972434	2468872	4972434	2371882	516876358	44.19	0.79	0	2.31	0	0.11	0	0.09	0	0.00	0	15.01	0	4783269	0	302	0	294.22	0	1.56	0	0.01	0	1.20	0	0.00	0	99.56	0	1.05	0	44402	0	5641471	0	130520	0	6172	0	5340	0	0	0	846690	0	147	0	0	0	5152	0	929616	0	10843	0	945758	0	82.47	0	4652749	0	9643	850090	88.156175464067	5641471.0	4783269.0	44402.0	130520.0	6172.0	5340.0	0.0	846690.0	4652749.0	84.8	0.8	2.3	0.1	0.1	0.0	15.0	82.5	151	151	151.00	7	851862121	28.7	21.7	22.0	27.5	0.0	30.8	20.2	smartseq
1451371	SRR3640256	SRP076212	SRS1489036	SRX1827077	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189879: D1_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189879		GSM2189879	D1_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	55572900	370486	2016-07-18 10:56:32	23858042	55572900	370486	2	370486	index:0,count:370486,average:75,stdev:0|index:1,count:370486,average:75,stdev:0	GSM2189879_r3						2.33	2.25	0.05	43839732	48451241	40887846	45773627	110.52	111.95	320414	295772	220.968	1124.236	174	1748	71.85	77.37	352341	230223	352341	230223	61.79	62.37	352341	197998	352341	185601	8776826	20.02	2.26	0	6.16	0	0.21	0	0.17	0	0.00	0	13.14	0	320414	0	150	0	147.27	0	5.01	0	0.10	0	1.05	0	0.03	0	102.60	0	0.55	0	8355	0	370486	0	22837	0	779	0	629	0	0	0	48664	0	49	0	0	0	285	0	43327	0	516	0	44177	0	80.32	0	297577	0	14418	42481	2.946386461368	370486.0	320414.0	8355.0	22837.0	779.0	629.0	0.0	48664.0	297577.0	86.5	2.3	6.2	0.2	0.2	0.0	13.1	80.3	75	75	75.00	6	27786450	25.2	24.4	24.6	25.7	0.0	33.4	24.6	smartseq
1451372	SRR3641256	SRP076212	SRS1489289	SRX1827331	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190133: H2_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190133		GSM2190133	H2_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	45494400	303296	2016-07-18 10:56:32	16995245	45494400	303296	2	303296	index:0,count:303296,average:75,stdev:0|index:1,count:303296,average:75,stdev:0	GSM2190133_r1						0.97	2.17	0.02	39446039	44500907	37014503	42253193	112.81	114.15	285373	248894	241.942	1534.107	146	1284	83.21	88.97	309981	237453	309981	237453	71.1	72.08	309981	202910	309981	192381	3397019	8.61	1.60	0	6.09	0	0.22	0	0.10	0	0.00	0	5.59	0	285373	0	150	0	148.05	0	4.62	0	0.07	0	1.06	0	0.02	0	99.26	0	0.29	0	4843	0	303296	0	18468	0	670	0	303	0	0	0	16950	0	45	0	0	0	408	0	60787	0	429	0	61669	0	88.00	0	266905	0	21770	59692	2.741938447405	303296.0	285373.0	4843.0	18468.0	670.0	303.0	0.0	16950.0	266905.0	94.1	1.6	6.1	0.2	0.1	0.0	5.6	88.0	75	75	75.00	6	22747200	24.2	25.7	25.6	24.5	0.0	34.8	28.4	smartseq
1451387	SRR3638257	SRP076212	SRS1488263	SRX1826305	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189107: 1-0-g-0-BTN22-C27-14ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189107		GSM2189107	1-0-g-0-BTN22-C27-14ul-1 BTN22 Mic-scRNA-Seq	43625400	290836	2016-07-18 10:56:32	20783992	43625400	290836	2	290836	index:0,count:290836,average:75,stdev:0|index:1,count:290836,average:75,stdev:0	GSM2189107_r4						1.15	3.58	0.04	38064096	36844577	37005015	35999571	96.8	97.28	265453	252582	242.698	913.287	201	1187	42.98	44.23	277365	114087	277365	114087	43.59	43.02	277365	115704	277365	110966	20080661	52.75	0.88	0	2.59	0	0.08	0	0.22	0	0.00	0	8.42	0	265453	0	150	0	148.52	0	1.38	0	0.01	0	1.18	0	0.00	0	55.11	0	0.77	0	2567	0	290836	0	7528	0	237	0	646	0	0	0	24500	0	15	0	0	0	157	0	18101	0	237	0	18510	0	88.68	0	257925	0	8774	18086	2.061317529063	290836.0	265453.0	2567.0	7528.0	237.0	646.0	0.0	24500.0	257925.0	91.3	0.9	2.6	0.1	0.2	0.0	8.4	88.7	75	75	75.00	7	21812700	30.2	20.2	20.2	29.3	0.0	33.3	21.4	smartseq
1451388	SRR3639257	SRP076212	SRS1488660	SRX1826702	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189504: 1ll-BTN17-C88 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189504		GSM2189504	1ll-BTN17-C88 BTN17 Mic-scRNA-Seq	1800983040	5963520	2016-07-18 10:56:32	921010523	1800983040	5963520	2	5963520	index:0,count:5963520,average:151,stdev:0|index:1,count:5963520,average:151,stdev:0	GSM2189504_r1						1.67	2.08	0.29	1236028729	1204129830	1200235433	1171236216	97.42	97.58	5025628	4754563	287.127	644.002	233	24439	63.63	65.62	5269505	3197987	5269505	3197987	63.41	63.23	5269505	3186899	5269505	3081515	403890689	32.68	0.76	0	2.55	0	0.15	0	0.07	0	0.00	0	15.51	0	5025628	0	302	0	293.86	0	1.59	0	0.02	0	1.19	0	0.00	0	108.98	0	1.05	0	45562	0	5963520	0	151942	0	8687	0	4093	0	0	0	925112	0	111	0	0	0	6051	0	1251257	0	11681	0	1269100	0	81.72	0	4873686	0	7777	1150824	147.977883502636	5963520.0	5025628.0	45562.0	151942.0	8687.0	4093.0	0.0	925112.0	4873686.0	84.3	0.8	2.5	0.1	0.1	0.0	15.5	81.7	151	151	151.00	7	900491520	28.2	22.1	22.5	27.2	0.0	30.8	20.1	smartseq
1451389	SRR3640257	SRP076212	SRS1489036	SRX1827077	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189879: D1_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189879		GSM2189879	D1_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	54774450	365163	2016-07-18 10:56:32	23429969	54774450	365163	2	365163	index:0,count:365163,average:75,stdev:0|index:1,count:365163,average:75,stdev:0	GSM2189879_r4						2.37	2.27	0.05	43279915	47860267	40382481	45222060	110.58	111.98	316028	291797	221.787	1147.403	174	1691	71.96	77.43	347133	227398	347133	227398	61.8	62.41	347133	195300	347133	183279	8660703	20.01	2.18	0	6.12	0	0.22	0	0.18	0	0.00	0	13.05	0	316028	0	150	0	147.30	0	4.98	0	0.10	0	1.05	0	0.03	0	93.90	0	0.52	0	7976	0	365163	0	22340	0	821	0	673	0	0	0	47641	0	20	0	0	0	267	0	42708	0	500	0	43495	0	80.43	0	293688	0	14317	41924	2.928267095062	365163.0	316028.0	7976.0	22340.0	821.0	673.0	0.0	47641.0	293688.0	86.5	2.2	6.1	0.2	0.2	0.0	13.0	80.4	75	75	75.00	6	27387225	25.3	24.4	24.6	25.7	0.0	33.5	24.9	smartseq
1451390	SRR3641257	SRP076212	SRS1489289	SRX1827331	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190133: H2_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190133		GSM2190133	H2_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	45240750	301605	2016-07-18 10:56:32	17000886	45240750	301605	2	301605	index:0,count:301605,average:75,stdev:0|index:1,count:301605,average:75,stdev:0	GSM2190133_r2						0.9	2.14	0.02	39100221	44056334	36691484	41824912	112.68	113.99	282895	246219	242.185	1590.636	141	1254	83.3	89.07	307722	235646	307722	235646	71.29	72.33	307722	201670	307722	191372	3338895	8.54	1.59	0	6.08	0	0.22	0	0.11	0	0.00	0	5.87	0	282895	0	150	0	148.00	0	4.70	0	0.07	0	1.06	0	0.02	0	90.48	0	0.32	0	4805	0	301605	0	18329	0	669	0	322	0	0	0	17719	0	50	0	0	0	448	0	59859	0	421	0	60778	0	87.72	0	264566	0	21611	58774	2.719633519967	301605.0	282895.0	4805.0	18329.0	669.0	322.0	0.0	17719.0	264566.0	93.8	1.6	6.1	0.2	0.1	0.0	5.9	87.7	75	75	75.00	6	22620375	24.2	25.6	25.6	24.6	0.0	34.8	28.2	smartseq
1451403	SRR3638258	SRP076212	SRS1488264	SRX1826306	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189108: 1-0-g-0-BTN22-C28-8ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189108		GSM2189108	1-0-g-0-BTN22-C28-8ul-1 BTN22 Mic-scRNA-Seq	51878250	345855	2016-07-18 10:56:32	24506228	51878250	345855	2	345855	index:0,count:345855,average:75,stdev:0|index:1,count:345855,average:75,stdev:0	GSM2189108_r1						1.0	3.7	0.18	45455768	44208783	43681678	42759037	97.26	97.89	318204	295892	241.553	933.175	190	1418	66.91	69.66	337514	212908	337514	212908	67.92	67.87	337514	216110	337514	207451	12475504	27.45	0.88	0	3.63	0	0.10	0	0.08	0	0.00	0	7.82	0	318204	0	150	0	148.37	0	1.35	0	0.01	0	1.14	0	0.00	0	65.53	0	0.67	0	3044	0	345855	0	12554	0	331	0	289	0	0	0	27031	0	36	0	0	0	242	0	33203	0	302	0	33783	0	88.38	0	305650	0	10807	33402	3.090774498011	345855.0	318204.0	3044.0	12554.0	331.0	289.0	0.0	27031.0	305650.0	92.0	0.9	3.6	0.1	0.1	0.0	7.8	88.4	75	75	75.00	7	25939125	30.1	19.8	20.2	29.9	0.0	33.5	21.7	smartseq
1451404	SRR3639258	SRP076212	SRS1488661	SRX1826703	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189505: 1ll-BTN17-C91 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189505		GSM2189505	1ll-BTN17-C91 BTN17 Mic-scRNA-Seq	1376038538	4556419	2016-07-18 10:56:32	708313589	1376038538	4556419	2	4556419	index:0,count:4556419,average:151,stdev:0|index:1,count:4556419,average:151,stdev:0	GSM2189505_r1						0.91	2.13	0.1	905600611	901489595	868848476	866578051	99.55	99.74	3753516	3489889	275.551	820.244	230	20204	83.45	87.11	4023349	3132213	4023349	3132213	82.81	83.15	4023349	3108225	4023349	2989972	99794202	11.02	0.80	0	3.46	0	0.18	0	0.08	0	0.00	0	17.36	0	3753516	0	302	0	293.03	0	1.88	0	0.02	0	1.19	0	0.01	0	79.63	0	1.09	0	36593	0	4556419	0	157634	0	7979	0	3783	0	0	0	791141	0	474	0	0	0	7218	0	1281535	0	10373	0	1299600	0	78.92	0	3595882	0	7881	1186544	150.557543458952	4556419.0	3753516.0	36593.0	157634.0	7979.0	3783.0	0.0	791141.0	3595882.0	82.4	0.8	3.5	0.2	0.1	0.0	17.4	78.9	151	151	151.00	7	688019269	27.8	22.7	23.1	26.4	0.0	30.6	19.8	smartseq
1451405	SRR3640258	SRP076212	SRS1489035	SRX1827078	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189880: D1_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189880		GSM2189880	D1_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq	24044550	160297	2016-07-18 10:56:32	7980081	24044550	160297	2	160297	index:0,count:160297,average:75,stdev:0|index:1,count:160297,average:75,stdev:0	GSM2189880_r1						1.31	3.0	0.02	17541265	19003887	16353972	17937364	108.34	109.68	140918	130771	164.094	833.124	117	1028	81.56	87.9	156067	114933	156067	114933	73.94	75.05	156067	104199	156067	98135	1794556	10.23	1.90	0	6.34	0	0.28	0	0.10	0	0.00	0	11.71	0	140918	0	150	0	147.00	0	3.83	0	0.04	0	1.11	0	0.01	0	44.39	0	0.22	0	3042	0	160297	0	10164	0	453	0	161	0	0	0	18765	0	29	0	0	0	219	0	33429	0	207	0	33884	0	81.57	0	130754	0	14995	30356	2.024408136045	160297.0	140918.0	3042.0	10164.0	453.0	161.0	0.0	18765.0	130754.0	87.9	1.9	6.3	0.3	0.1	0.0	11.7	81.6	75	75	75.00	6	12022275	24.5	25.5	24.9	25.2	0.0	35.2	30.1	smartseq
1451406	SRR3641258	SRP076212	SRS1489289	SRX1827331	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190133: H2_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190133		GSM2190133	H2_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	44727000	298180	2016-07-18 10:56:32	16932017	44727000	298180	2	298180	index:0,count:298180,average:75,stdev:0|index:1,count:298180,average:75,stdev:0	GSM2190133_r3						0.98	2.15	0.02	38838681	43754430	36406314	41483774	112.66	113.95	280717	244112	243.179	1605.832	153	1239	83.16	89.02	305762	233446	305762	233446	71.29	72.34	305762	200116	305762	189722	3339288	8.60	1.61	0	6.19	0	0.25	0	0.10	0	0.00	0	5.51	0	280717	0	150	0	148.02	0	4.65	0	0.07	0	1.06	0	0.02	0	89.45	0	0.31	0	4803	0	298180	0	18467	0	734	0	308	0	0	0	16421	0	45	0	0	0	430	0	59905	0	405	0	60785	0	87.95	0	262250	0	21659	59038	2.725795281407	298180.0	280717.0	4803.0	18467.0	734.0	308.0	0.0	16421.0	262250.0	94.1	1.6	6.2	0.2	0.1	0.0	5.5	88.0	75	75	75.00	6	22363500	24.2	25.6	25.6	24.5	0.0	34.7	27.8	smartseq
1451419	SRR3638259	SRP076212	SRS1488264	SRX1826306	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189108: 1-0-g-0-BTN22-C28-8ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189108		GSM2189108	1-0-g-0-BTN22-C28-8ul-1 BTN22 Mic-scRNA-Seq	51462750	343085	2016-07-18 10:56:32	24035287	51462750	343085	2	343085	index:0,count:343085,average:75,stdev:0|index:1,count:343085,average:75,stdev:0	GSM2189108_r2						0.98	3.7	0.16	45205047	43951926	43410818	42480403	97.23	97.86	316228	293094	244.066	991.419	188	1373	66.85	69.65	335810	211395	335810	211395	67.93	67.84	335810	214798	335810	205917	12392835	27.41	0.84	0	3.71	0	0.09	0	0.10	0	0.00	0	7.64	0	316228	0	150	0	148.38	0	1.38	0	0.01	0	1.18	0	0.00	0	88.22	0	0.65	0	2889	0	343085	0	12716	0	295	0	336	0	0	0	26226	0	38	0	0	0	219	0	33499	0	287	0	34043	0	88.47	0	303512	0	10837	33715	3.111100858171	343085.0	316228.0	2889.0	12716.0	295.0	336.0	0.0	26226.0	303512.0	92.2	0.8	3.7	0.1	0.1	0.0	7.6	88.5	75	75	75.00	7	25731375	30.1	19.9	20.2	29.8	0.0	33.7	22.0	smartseq
1451420	SRR3639259	SRP076212	SRS1488662	SRX1826704	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189506: 1ll-BTN17-C92 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;NSC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189506		GSM2189506	1ll-BTN17-C92 BTN17 Mic-scRNA-Seq	1708751636	5658118	2016-07-18 10:56:32	873916430	1708751636	5658118	2	5658118	index:0,count:5658118,average:151,stdev:0|index:1,count:5658118,average:151,stdev:0	GSM2189506_r1						3.03	2.8	0.01	1165674102	1173185570	1117560280	1127077570	100.64	100.85	4804117	4470575	278.309	950.552	230	23918	75.31	78.64	5064718	3617754	5064718	3617754	75.7	75.19	5064718	3636622	5064718	3459224	236210004	20.26	0.84	0	3.60	0	0.06	0	0.04	0	0.00	0	15.00	0	4804117	0	302	0	293.57	0	1.72	0	0.02	0	1.18	0	0.00	0	113.16	0	1.05	0	47485	0	5658118	0	203687	0	3170	0	2020	0	0	0	848811	0	1384	0	0	0	6466	0	1587799	0	12858	0	1608507	0	81.31	0	4600430	0	10373	1451435	139.924322761014	5658118.0	4804117.0	47485.0	203687.0	3170.0	2020.0	0.0	848811.0	4600430.0	84.9	0.8	3.6	0.1	0.0	0.0	15.0	81.3	151	151	151.00	7	854375818	28.0	22.5	22.7	26.8	0.0	30.7	20.1	smartseq
1451421	SRR3640259	SRP076212	SRS1489035	SRX1827078	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189880: D1_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189880		GSM2189880	D1_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq	24046350	160309	2016-07-18 10:56:32	8002238	24046350	160309	2	160309	index:0,count:160309,average:75,stdev:0|index:1,count:160309,average:75,stdev:0	GSM2189880_r2						1.35	3.09	0.02	17459647	18882981	16269161	17806241	108.15	109.45	140574	130918	162.989	798.823	111	1018	81.6	87.97	155671	114711	155671	114711	74.18	75.3	155671	104278	155671	98183	1758028	10.07	1.85	0	6.35	0	0.29	0	0.09	0	0.00	0	11.93	0	140574	0	150	0	146.97	0	3.87	0	0.04	0	1.13	0	0.01	0	44.39	0	0.23	0	2969	0	160309	0	10177	0	466	0	138	0	0	0	19131	0	32	0	0	0	247	0	32758	0	210	0	33247	0	81.34	0	130397	0	14701	29955	2.037616488674	160309.0	140574.0	2969.0	10177.0	466.0	138.0	0.0	19131.0	130397.0	87.7	1.9	6.3	0.3	0.1	0.0	11.9	81.3	75	75	75.00	6	12023175	24.5	25.5	24.9	25.2	0.0	35.2	30.1	smartseq
1451422	SRR3641259	SRP076212	SRS1489289	SRX1827331	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190133: H2_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC14-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190133		GSM2190133	H2_1000701001-OGC14-sal_1_6ul_1 OGC14-sal FACS-scRNA-Seq	44915250	299435	2016-07-18 10:56:32	17027789	44915250	299435	2	299435	index:0,count:299435,average:75,stdev:0|index:1,count:299435,average:75,stdev:0	GSM2190133_r4						0.94	2.15	0.02	38923419	43855263	36498776	41595401	112.67	113.96	281419	244676	243.085	1577.048	146	1231	83.16	88.98	306585	234016	306585	234016	71.19	72.23	306585	200334	306585	189985	3342678	8.59	1.60	0	6.15	0	0.26	0	0.10	0	0.00	0	5.67	0	281419	0	150	0	148.03	0	4.66	0	0.06	0	1.05	0	0.02	0	71.86	0	0.32	0	4795	0	299435	0	18406	0	765	0	287	0	0	0	16964	0	35	0	0	0	429	0	59729	0	469	0	60662	0	87.84	0	263013	0	21630	58664	2.712159038373	299435.0	281419.0	4795.0	18406.0	765.0	287.0	0.0	16964.0	263013.0	94.0	1.6	6.1	0.3	0.1	0.0	5.7	87.8	75	75	75.00	6	22457625	24.2	25.6	25.6	24.6	0.0	34.7	27.9	smartseq
1451531	SRR3638260	SRP076212	SRS1488264	SRX1826306	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189108: 1-0-g-0-BTN22-C28-8ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189108		GSM2189108	1-0-g-0-BTN22-C28-8ul-1 BTN22 Mic-scRNA-Seq	50389800	335932	2016-07-18 10:56:32	23954111	50389800	335932	2	335932	index:0,count:335932,average:75,stdev:0|index:1,count:335932,average:75,stdev:0	GSM2189108_r3						0.98	3.65	0.16	44102024	42904250	42369314	41478031	97.28	97.9	308822	286710	240.851	942.029	199	1386	67.01	69.79	327608	206943	327608	206943	68.02	67.94	327608	210072	327608	201466	12024175	27.26	0.85	0	3.66	0	0.10	0	0.09	0	0.00	0	7.88	0	308822	0	150	0	148.33	0	1.36	0	0.01	0	1.16	0	0.00	0	71.14	0	0.71	0	2844	0	335932	0	12281	0	331	0	293	0	0	0	26486	0	34	0	0	0	204	0	32747	0	264	0	33249	0	88.27	0	296541	0	10683	32964	3.085650098287	335932.0	308822.0	2844.0	12281.0	331.0	293.0	0.0	26486.0	296541.0	91.9	0.8	3.7	0.1	0.1	0.0	7.9	88.3	75	75	75.00	7	25194900	30.1	19.9	20.2	29.8	0.0	33.4	21.6	smartseq
1451532	SRR3639260	SRP076212	SRS1488663	SRX1826705	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189507: 1ll-BTN17-C96 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189507		GSM2189507	1ll-BTN17-C96 BTN17 Mic-scRNA-Seq	1201892956	3979778	2016-07-18 10:56:32	618402276	1201892956	3979778	2	3979778	index:0,count:3979778,average:151,stdev:0|index:1,count:3979778,average:151,stdev:0	GSM2189507_r1						3.86	2.66	0.07	814459002	809677032	788481607	785777200	99.41	99.66	3316118	3163084	285.286	708.872	230	16711	62.66	64.78	3458959	2077779	3458959	2077779	62.04	61.4	3458959	2057208	3458959	1969460	274970781	33.76	0.96	0	2.73	0	0.12	0	0.10	0	0.00	0	16.46	0	3316118	0	302	0	293.64	0	1.60	0	0.01	0	1.17	0	0.00	0	112.81	0	1.07	0	38257	0	3979778	0	108501	0	4677	0	3884	0	0	0	655099	0	159	0	0	0	4509	0	714598	0	7792	0	727058	0	80.60	0	3207617	0	6962	649885	93.347457627119	3979778.0	3316118.0	38257.0	108501.0	4677.0	3884.0	0.0	655099.0	3207617.0	83.3	1.0	2.7	0.1	0.1	0.0	16.5	80.6	151	151	151.00	7	600946478	28.6	21.8	22.1	27.4	0.0	30.6	19.9	smartseq
1451533	SRR3640260	SRP076212	SRS1489035	SRX1827078	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189880: D1_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189880		GSM2189880	D1_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq	23867850	159119	2016-07-18 10:56:32	7997281	23867850	159119	2	159119	index:0,count:159119,average:75,stdev:0|index:1,count:159119,average:75,stdev:0	GSM2189880_r3						1.31	3.01	0.02	17438837	18887585	16250312	17834823	108.31	109.75	140208	130313	163.256	779.075	123	1011	81.54	87.89	155090	114325	155090	114325	73.77	74.94	155090	103428	155090	97482	1768212	10.14	1.90	0	6.36	0	0.28	0	0.10	0	0.00	0	11.50	0	140208	0	150	0	146.99	0	3.87	0	0.04	0	1.11	0	0.01	0	47.74	0	0.23	0	3024	0	159119	0	10125	0	445	0	164	0	0	0	18302	0	39	0	0	0	220	0	33244	0	239	0	33742	0	81.75	0	130083	0	14853	30273	2.038174106241	159119.0	140208.0	3024.0	10125.0	445.0	164.0	0.0	18302.0	130083.0	88.1	1.9	6.4	0.3	0.1	0.0	11.5	81.8	75	75	75.00	6	11933925	24.5	25.5	24.9	25.1	0.0	35.2	30.1	smartseq
1451534	SRR3641260	SRP076212	SRS1489290	SRX1827332	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190134: H2_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190134		GSM2190134	H2_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	55748550	371657	2016-07-18 10:56:32	20890929	55748550	371657	2	371657	index:0,count:371657,average:75,stdev:0|index:1,count:371657,average:75,stdev:0	GSM2190134_r1						1.24	2.02	0.02	47338767	54215795	44104187	51227396	114.53	116.15	345343	311255	226.920	1318.480	174	1688	80.27	86.5	377925	277211	377925	277211	66.18	67.39	377925	228565	377925	215991	4985624	10.53	1.91	0	6.69	0	0.23	0	0.15	0	0.00	0	6.70	0	345343	0	150	0	147.92	0	4.75	0	0.08	0	1.08	0	0.02	0	95.57	0	0.31	0	7081	0	371657	0	24857	0	848	0	563	0	0	0	24903	0	44	0	0	0	424	0	61458	0	542	0	62468	0	86.23	0	320486	0	19791	59921	3.027689353747	371657.0	345343.0	7081.0	24857.0	848.0	563.0	0.0	24903.0	320486.0	92.9	1.9	6.7	0.2	0.2	0.0	6.7	86.2	75	75	75.00	6	27874275	24.3	25.5	25.5	24.7	0.0	34.8	28.1	smartseq
1451544	SRR3638261	SRP076212	SRS1488264	SRX1826306	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189108: 1-0-g-0-BTN22-C28-8ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189108		GSM2189108	1-0-g-0-BTN22-C28-8ul-1 BTN22 Mic-scRNA-Seq	50550900	337006	2016-07-18 10:56:32	23804478	50550900	337006	2	337006	index:0,count:337006,average:75,stdev:0|index:1,count:337006,average:75,stdev:0	GSM2189108_r4						0.97	3.65	0.18	44205428	42969136	42487640	41571216	97.2	97.84	309542	287462	240.778	940.040	182	1336	66.86	69.61	328280	206974	328280	206974	67.85	67.82	328280	210015	328280	201637	12126136	27.43	0.84	0	3.63	0	0.09	0	0.09	0	0.00	0	7.97	0	309542	0	150	0	148.36	0	1.38	0	0.01	0	1.16	0	0.00	0	67.40	0	0.68	0	2820	0	337006	0	12224	0	290	0	305	0	0	0	26869	0	38	0	0	0	232	0	32605	0	255	0	33130	0	88.22	0	297318	0	10726	32798	3.057803468208	337006.0	309542.0	2820.0	12224.0	290.0	305.0	0.0	26869.0	297318.0	91.9	0.8	3.6	0.1	0.1	0.0	8.0	88.2	75	75	75.00	7	25275450	30.1	19.8	20.2	29.9	0.0	33.5	21.7	smartseq
1451545	SRR3639261	SRP076212	SRS1488664	SRX1826706	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189508: 1lld-BTN17-C05 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;NSC|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189508		GSM2189508	1lld-BTN17-C05 BTN17 Mic-scRNA-Seq	1011688222	3349961	2016-07-18 10:56:32	520013916	1011688222	3349961	2	3349961	index:0,count:3349961,average:151,stdev:0|index:1,count:3349961,average:151,stdev:0	GSM2189508_r1						9.55	2.67	0.04	673857069	674022932	628141351	631487965	100.02	100.53	2766991	2612228	281.013	753.839	230	13736	72.24	77.59	2991198	1998937	2991198	1998937	74.91	73.88	2991198	2072811	2991198	1903532	136682539	20.28	0.92	0	5.69	0	0.07	0	0.09	0	0.00	0	17.24	0	2766991	0	302	0	293.39	0	1.86	0	0.02	0	1.14	0	0.00	0	78.31	0	1.06	0	30782	0	3349961	0	190616	0	2253	0	3025	0	0	0	577692	0	475	0	0	0	3405	0	714765	0	9491	0	728136	0	76.91	0	2576375	0	7728	651182	84.262681159420	3349961.0	2766991.0	30782.0	190616.0	2253.0	3025.0	0.0	577692.0	2576375.0	82.6	0.9	5.7	0.1	0.1	0.0	17.2	76.9	151	151	151.00	7	505844111	28.8	21.6	21.9	27.7	0.0	30.6	19.8	smartseq
1451546	SRR3640261	SRP076212	SRS1489035	SRX1827078	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189880: D1_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189880		GSM2189880	D1_1000700401-OGC7-coc_1_22ul_1 OGC07-sal FACS-scRNA-Seq	23621550	157477	2016-07-18 10:56:32	7957293	23621550	157477	2	157477	index:0,count:157477,average:75,stdev:0|index:1,count:157477,average:75,stdev:0	GSM2189880_r4						1.32	3.11	0.02	17214015	18697561	16039358	17643872	108.62	110.0	138539	128922	163.049	793.459	122	1037	81.62	87.99	153454	113076	153454	113076	73.82	74.94	153454	102271	153454	96305	1748891	10.16	1.89	0	6.37	0	0.27	0	0.08	0	0.00	0	11.67	0	138539	0	150	0	146.97	0	3.95	0	0.04	0	1.12	0	0.01	0	51.54	0	0.23	0	2980	0	157477	0	10025	0	427	0	130	0	0	0	18381	0	31	0	0	0	231	0	32498	0	241	0	33001	0	81.61	0	128514	0	14618	29616	2.025995348201	157477.0	138539.0	2980.0	10025.0	427.0	130.0	0.0	18381.0	128514.0	88.0	1.9	6.4	0.3	0.1	0.0	11.7	81.6	75	75	75.00	6	11810775	24.5	25.5	24.9	25.1	0.0	35.2	30.1	smartseq
1451547	SRR3641261	SRP076212	SRS1489290	SRX1827332	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190134: H2_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190134		GSM2190134	H2_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	55368450	369123	2016-07-18 10:56:32	20856565	55368450	369123	2	369123	index:0,count:369123,average:75,stdev:0|index:1,count:369123,average:75,stdev:0	GSM2190134_r2						1.21	2.0	0.02	46913011	53670531	43714098	50695272	114.4	115.97	342088	307786	227.505	1322.902	153	1702	80.2	86.4	374490	274358	374490	274358	66.19	67.42	374490	226433	374490	214078	4962708	10.58	1.83	0	6.65	0	0.24	0	0.15	0	0.00	0	6.94	0	342088	0	150	0	147.90	0	4.76	0	0.08	0	1.07	0	0.02	0	102.22	0	0.33	0	6743	0	369123	0	24537	0	883	0	546	0	0	0	25606	0	58	0	0	0	406	0	61204	0	486	0	62154	0	86.03	0	317551	0	19795	59518	3.006718868401	369123.0	342088.0	6743.0	24537.0	883.0	546.0	0.0	25606.0	317551.0	92.7	1.8	6.6	0.2	0.1	0.0	6.9	86.0	75	75	75.00	6	27684225	24.3	25.5	25.5	24.7	0.0	34.7	28.0	smartseq
1451563	SRR3638262	SRP076212	SRS1488265	SRX1826307	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189109: 1-0-g-0-BTN22-C32-26ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189109		GSM2189109	1-0-g-0-BTN22-C32-26ul-1 BTN22 Mic-scRNA-Seq	40547250	270315	2016-07-18 10:56:32	19399986	40547250	270315	2	270315	index:0,count:270315,average:75,stdev:0|index:1,count:270315,average:75,stdev:0	GSM2189109_r1						1.1	3.04	0.09	35559850	34552742	34386012	33608572	97.17	97.74	248406	234514	243.592	869.032	176	1083	50.78	52.55	261959	126135	261959	126135	51.55	51.1	261959	128059	261959	122664	15880813	44.66	0.93	0	3.09	0	0.10	0	0.21	0	0.00	0	7.79	0	248406	0	150	0	148.54	0	1.36	0	0.01	0	1.19	0	0.00	0	69.51	0	0.72	0	2524	0	270315	0	8366	0	266	0	578	0	0	0	21065	0	24	0	0	0	175	0	20386	0	202	0	20787	0	88.80	0	240040	0	10118	20389	2.015121565527	270315.0	248406.0	2524.0	8366.0	266.0	578.0	0.0	21065.0	240040.0	91.9	0.9	3.1	0.1	0.2	0.0	7.8	88.8	75	75	75.00	7	20273625	30.0	20.1	20.1	29.8	0.0	33.4	21.9	smartseq
1451564	SRR3639262	SRP076212	SRS1488665	SRX1826707	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189509: 1lld-BTN17-C21 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Vascular|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189509		GSM2189509	1lld-BTN17-C21 BTN17 Mic-scRNA-Seq	813653232	2694216	2016-07-18 10:56:32	420918359	813653232	2694216	2	2694216	index:0,count:2694216,average:151,stdev:0|index:1,count:2694216,average:151,stdev:0	GSM2189509_r1						4.8	2.46	0.02	537202875	533798532	514812427	512872125	99.37	99.62	2253589	2172171	266.341	634.205	230	11692	54.6	57.03	2372451	1230420	2372451	1230420	54.52	53.18	2372451	1228747	2372451	1147382	220232265	41.00	0.85	0	3.57	0	0.03	0	0.05	0	0.00	0	16.27	0	2253589	0	302	0	293.30	0	1.54	0	0.01	0	1.19	0	0.00	0	93.26	0	1.14	0	22896	0	2694216	0	96060	0	905	0	1313	0	0	0	438409	0	211	0	0	0	2155	0	401284	0	4573	0	408223	0	80.08	0	2157529	0	7382	359543	48.705364399892	2694216.0	2253589.0	22896.0	96060.0	905.0	1313.0	0.0	438409.0	2157529.0	83.6	0.8	3.6	0.0	0.0	0.0	16.3	80.1	151	151	151.00	7	406826616	28.9	21.5	21.7	27.9	0.0	30.8	20.2	smartseq
1451565	SRR3640262	SRP076212	SRS1489037	SRX1827079	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189881: D2_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189881		GSM2189881	D2_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	47060850	313739	2016-07-18 10:56:32	15787169	47060850	313739	2	313739	index:0,count:313739,average:75,stdev:0|index:1,count:313739,average:75,stdev:0	GSM2189881_r1						1.08	2.54	0.03	39229065	42321360	37266972	40546557	107.88	108.8	292881	258878	210.674	1481.153	130	1534	83.09	87.73	314935	243355	314935	243355	75.64	76.48	314935	221535	314935	212142	4219430	10.76	1.51	0	4.94	0	0.26	0	0.11	0	0.00	0	6.27	0	292881	0	150	0	147.86	0	4.00	0	0.04	0	1.11	0	0.01	0	94.12	0	0.23	0	4724	0	313739	0	15501	0	831	0	347	0	0	0	19680	0	52	0	0	0	470	0	69999	0	402	0	70923	0	88.41	0	277380	0	22632	67158	2.967391304348	313739.0	292881.0	4724.0	15501.0	831.0	347.0	0.0	19680.0	277380.0	93.4	1.5	4.9	0.3	0.1	0.0	6.3	88.4	75	75	75.00	6	23530425	24.6	25.3	25.2	24.9	0.0	35.2	30.2	smartseq
1451566	SRR3641262	SRP076212	SRS1489290	SRX1827332	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190134: H2_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190134		GSM2190134	H2_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	54549450	363663	2016-07-18 10:56:32	20689233	54549450	363663	2	363663	index:0,count:363663,average:75,stdev:0|index:1,count:363663,average:75,stdev:0	GSM2190134_r3						1.21	2.0	0.03	46489078	53184396	43315522	50243420	114.4	115.99	338724	304887	228.486	1318.570	146	1722	80.2	86.42	370762	271673	370762	271673	66.19	67.42	370762	224191	370762	211930	4920135	10.58	1.85	0	6.70	0	0.23	0	0.15	0	0.00	0	6.48	0	338724	0	150	0	147.91	0	4.76	0	0.08	0	1.08	0	0.02	0	119.02	0	0.33	0	6728	0	363663	0	24367	0	823	0	540	0	0	0	23576	0	41	0	0	0	444	0	60570	0	536	0	61591	0	86.44	0	314357	0	19803	58999	2.979296066253	363663.0	338724.0	6728.0	24367.0	823.0	540.0	0.0	23576.0	314357.0	93.1	1.9	6.7	0.2	0.1	0.0	6.5	86.4	75	75	75.00	6	27274725	24.3	25.5	25.5	24.7	0.0	34.6	27.6	smartseq
1451577	SRR3638263	SRP076212	SRS1488265	SRX1826307	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189109: 1-0-g-0-BTN22-C32-26ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189109		GSM2189109	1-0-g-0-BTN22-C32-26ul-1 BTN22 Mic-scRNA-Seq	40369950	269133	2016-07-18 10:56:32	19077020	40369950	269133	2	269133	index:0,count:269133,average:75,stdev:0|index:1,count:269133,average:75,stdev:0	GSM2189109_r2						1.1	3.03	0.06	35545885	34540969	34345779	33583799	97.17	97.78	248034	234066	247.470	866.225	199	1063	50.83	52.64	261941	126076	261941	126076	51.62	51.15	261941	128034	261941	122506	15859145	44.62	0.92	0	3.17	0	0.10	0	0.20	0	0.00	0	7.54	0	248034	0	150	0	148.58	0	1.35	0	0.01	0	1.21	0	0.00	0	69.21	0	0.69	0	2470	0	269133	0	8530	0	267	0	542	0	0	0	20290	0	19	0	0	0	154	0	20402	0	209	0	20784	0	88.99	0	239504	0	10094	20453	2.026253219734	269133.0	248034.0	2470.0	8530.0	267.0	542.0	0.0	20290.0	239504.0	92.2	0.9	3.2	0.1	0.2	0.0	7.5	89.0	75	75	75.00	7	20184975	30.1	20.1	20.1	29.7	0.0	33.6	22.3	smartseq
1451578	SRR3639263	SRP076212	SRS1488666	SRX1826708	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189510: 1lld-BTN17-C33 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189510		GSM2189510	1lld-BTN17-C33 BTN17 Mic-scRNA-Seq	1506421602	4988151	2016-07-18 10:56:32	776392113	1506421602	4988151	2	4988151	index:0,count:4988151,average:151,stdev:0|index:1,count:4988151,average:151,stdev:0	GSM2189510_r1						3.9	9.01	0.04	1026777622	1043997466	980526723	1000833693	101.68	102.07	4186166	3735427	286.323	1015.497	225	18192	81.63	85.62	4451025	3417296	4451025	3417296	80.77	80.57	4451025	3381128	4451025	3215902	136962904	13.34	0.83	0	3.90	0	0.10	0	0.05	0	0.00	0	15.93	0	4186166	0	302	0	293.11	0	1.74	0	0.02	0	1.18	0	0.00	0	84.70	0	1.13	0	41376	0	4988151	0	194780	0	5183	0	2381	0	0	0	794421	0	799	0	0	0	9339	0	1985564	0	11154	0	2006856	0	80.02	0	3991386	0	25528	1811870	70.975791287997	4988151.0	4186166.0	41376.0	194780.0	5183.0	2381.0	0.0	794421.0	3991386.0	83.9	0.8	3.9	0.1	0.0	0.0	15.9	80.0	151	151	151.00	7	753210801	27.8	22.7	23.1	26.4	0.0	30.6	19.9	smartseq
1451579	SRR3640263	SRP076212	SRS1489037	SRX1827079	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189881: D2_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189881		GSM2189881	D2_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	47138700	314258	2016-07-18 10:56:32	15891649	47138700	314258	2	314258	index:0,count:314258,average:75,stdev:0|index:1,count:314258,average:75,stdev:0	GSM2189881_r2						1.09	2.48	0.04	39219067	42340957	37280516	40602276	107.96	108.91	292741	258588	210.073	1477.774	123	1518	83.15	87.74	314586	243409	314586	243409	75.61	76.43	314586	221342	314586	212028	4234647	10.80	1.57	0	4.87	0	0.24	0	0.09	0	0.00	0	6.51	0	292741	0	150	0	147.84	0	3.92	0	0.04	0	1.10	0	0.01	0	102.85	0	0.23	0	4924	0	314258	0	15310	0	764	0	296	0	0	0	20457	0	47	0	0	0	454	0	70294	0	403	0	71198	0	88.28	0	277431	0	22531	67492	2.995517287293	314258.0	292741.0	4924.0	15310.0	764.0	296.0	0.0	20457.0	277431.0	93.2	1.6	4.9	0.2	0.1	0.0	6.5	88.3	75	75	75.00	6	23569350	24.6	25.3	25.1	24.9	0.0	35.2	30.2	smartseq
1451580	SRR3641263	SRP076212	SRS1489290	SRX1827332	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190134: H2_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190134		GSM2190134	H2_1000701201-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	54811350	365409	2016-07-18 10:56:32	20865966	54811350	365409	2	365409	index:0,count:365409,average:75,stdev:0|index:1,count:365409,average:75,stdev:0	GSM2190134_r4						1.25	2.02	0.02	46661433	53456016	43464204	50499509	114.56	116.19	339813	305809	228.329	1325.201	141	1718	80.16	86.41	371952	272386	371952	272386	66.07	67.29	371952	224527	371952	212132	4957483	10.62	1.86	0	6.72	0	0.24	0	0.14	0	0.00	0	6.63	0	339813	0	150	0	147.91	0	4.79	0	0.08	0	1.08	0	0.02	0	87.70	0	0.34	0	6798	0	365409	0	24572	0	863	0	524	0	0	0	24209	0	47	0	0	0	368	0	59727	0	513	0	60655	0	86.27	0	315241	0	19613	58394	2.977310967216	365409.0	339813.0	6798.0	24572.0	863.0	524.0	0.0	24209.0	315241.0	93.0	1.9	6.7	0.2	0.1	0.0	6.6	86.3	75	75	75.00	6	27405675	24.3	25.5	25.5	24.7	0.0	34.6	27.6	smartseq
1451595	SRR3638264	SRP076212	SRS1488265	SRX1826307	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189109: 1-0-g-0-BTN22-C32-26ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189109		GSM2189109	1-0-g-0-BTN22-C32-26ul-1 BTN22 Mic-scRNA-Seq	39240600	261604	2016-07-18 10:56:32	18846804	39240600	261604	2	261604	index:0,count:261604,average:75,stdev:0|index:1,count:261604,average:75,stdev:0	GSM2189109_r3						1.08	3.03	0.09	34380187	33417678	33219595	32490911	97.2	97.81	240316	227235	242.836	857.844	188	1060	50.76	52.57	253724	121991	253724	121991	51.51	51.09	253724	123795	253724	118551	15348543	44.64	0.92	0	3.16	0	0.09	0	0.20	0	0.00	0	7.84	0	240316	0	150	0	148.53	0	1.34	0	0.01	0	1.16	0	0.00	0	62.78	0	0.75	0	2394	0	261604	0	8272	0	248	0	531	0	0	0	20509	0	21	0	0	0	153	0	19220	0	208	0	19602	0	88.70	0	232044	0	9734	19303	1.983049106226	261604.0	240316.0	2394.0	8272.0	248.0	531.0	0.0	20509.0	232044.0	91.9	0.9	3.2	0.1	0.2	0.0	7.8	88.7	75	75	75.00	7	19620300	30.1	20.1	20.1	29.7	0.0	33.4	21.9	smartseq
1451596	SRR3639264	SRP076212	SRS1488667	SRX1826709	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189511: 1lld-BTN17-C51 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189511		GSM2189511	1lld-BTN17-C51 BTN17 Mic-scRNA-Seq	909524340	3011670	2016-07-18 10:56:32	474122605	909524340	3011670	2	3011670	index:0,count:3011670,average:151,stdev:0|index:1,count:3011670,average:151,stdev:0	GSM2189511_r1						6.44	2.13	0.27	580899156	571085106	543282122	535722524	98.31	98.61	2395538	2240369	279.643	644.087	230	12068	79.6	85.25	2612607	1906931	2612607	1906931	81.67	81.3	2612607	1956456	2612607	1818501	67900697	11.69	0.88	0	5.27	0	0.24	0	0.13	0	0.00	0	20.08	0	2395538	0	302	0	293.07	0	1.70	0	0.02	0	1.20	0	0.00	0	88.87	0	1.11	0	26595	0	3011670	0	158762	0	7329	0	3946	0	0	0	604857	0	893	0	0	0	4120	0	795777	0	6766	0	807556	0	74.27	0	2236776	0	9039	738297	81.679057417856	3011670.0	2395538.0	26595.0	158762.0	7329.0	3946.0	0.0	604857.0	2236776.0	79.5	0.9	5.3	0.2	0.1	0.0	20.1	74.3	151	151	151.00	7	454762170	28.5	22.0	22.7	26.7	0.0	30.0	19.0	smartseq
1451597	SRR3640264	SRP076212	SRS1489037	SRX1827079	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189881: D2_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189881		GSM2189881	D2_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	46705050	311367	2016-07-18 10:56:32	15835933	46705050	311367	2	311367	index:0,count:311367,average:75,stdev:0|index:1,count:311367,average:75,stdev:0	GSM2189881_r3						1.12	2.56	0.04	39037066	42107175	37075760	40334214	107.86	108.79	291156	256955	210.766	1474.944	135	1509	83.0	87.68	313559	241674	313559	241674	75.62	76.45	313559	220160	313559	210717	4218350	10.81	1.51	0	4.98	0	0.27	0	0.11	0	0.00	0	6.12	0	291156	0	150	0	147.86	0	3.92	0	0.04	0	1.08	0	0.01	0	93.41	0	0.23	0	4708	0	311367	0	15520	0	834	0	327	0	0	0	19050	0	52	0	0	0	482	0	70135	0	406	0	71075	0	88.52	0	275636	0	22748	67454	2.965271672235	311367.0	291156.0	4708.0	15520.0	834.0	327.0	0.0	19050.0	275636.0	93.5	1.5	5.0	0.3	0.1	0.0	6.1	88.5	75	75	75.00	6	23352525	24.6	25.3	25.1	24.9	0.0	35.2	30.1	smartseq
1451598	SRR3641264	SRP076212	SRS1489291	SRX1827333	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190135: H2_1000701204-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC16-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190135		GSM2190135	H2_1000701204-OGC16-sal_1_6ul_1 OGC16-sal FACS-scRNA-Seq	69265500	461770	2016-07-18 10:56:32	24092861	69265500	461770	2	461770	index:0,count:461770,average:75,stdev:0|index:1,count:461770,average:75,stdev:0	GSM2190135_r1						1.45	2.01	0.01	58462333	69122887	54662332	65641294	118.23	120.09	426667	380153	248.106	1491.347	146	1830	81.63	87.67	465443	348289	465443	348289	64.37	65.18	465443	274661	465443	258930	5600871	9.58	1.88	0	6.37	0	0.19	0	0.15	0	0.00	0	7.26	0	426667	0	150	0	147.94	0	4.74	0	0.08	0	1.07	0	0.02	0	118.74	0	0.27	0	8670	0	461770	0	29409	0	864	0	702	0	0	0	33537	0	52	0	0	0	513	0	74026	0	715	0	75306	0	86.03	0	397258	0	22128	71930	3.250632682574	461770.0	426667.0	8670.0	29409.0	864.0	702.0	0.0	33537.0	397258.0	92.4	1.9	6.4	0.2	0.2	0.0	7.3	86.0	75	75	75.00	6	34632750	24.2	25.5	25.6	24.7	0.0	35.2	29.9	smartseq
1451609	SRR3638265	SRP076212	SRS1488265	SRX1826307	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189109: 1-0-g-0-BTN22-C32-26ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189109		GSM2189109	1-0-g-0-BTN22-C32-26ul-1 BTN22 Mic-scRNA-Seq	39265500	261770	2016-07-18 10:56:32	18683203	39265500	261770	2	261770	index:0,count:261770,average:75,stdev:0|index:1,count:261770,average:75,stdev:0	GSM2189109_r4						1.09	3.07	0.09	34390076	33418332	33216042	32483627	97.17	97.79	240382	227579	242.589	823.015	208	1042	50.79	52.63	254131	122101	254131	122101	51.59	51.15	254131	124004	254131	118683	15340282	44.61	0.92	0	3.20	0	0.10	0	0.20	0	0.00	0	7.88	0	240382	0	150	0	148.54	0	1.38	0	0.01	0	1.18	0	0.00	0	58.90	0	0.72	0	2413	0	261770	0	8366	0	254	0	519	0	0	0	20615	0	17	0	0	0	166	0	19406	0	216	0	19805	0	88.63	0	232016	0	9804	19420	1.980824153407	261770.0	240382.0	2413.0	8366.0	254.0	519.0	0.0	20615.0	232016.0	91.8	0.9	3.2	0.1	0.2	0.0	7.9	88.6	75	75	75.00	7	19632750	30.0	20.1	20.1	29.7	0.0	33.5	22.0	smartseq
1451610	SRR3639265	SRP076212	SRS1488668	SRX1826710	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189512: 1lld-BTN17-C53 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189512		GSM2189512	1lld-BTN17-C53 BTN17 Mic-scRNA-Seq	1440269408	4769104	2016-07-18 10:56:32	746434798	1440269408	4769104	2	4769104	index:0,count:4769104,average:151,stdev:0|index:1,count:4769104,average:151,stdev:0	GSM2189512_r1						3.21	10.68	0.05	967148676	977165828	918659563	931617609	101.04	101.41	3969595	3558144	281.118	900.889	225	17860	83.0	87.52	4262821	3294854	4262821	3294854	82.96	83.03	4262821	3293288	4262821	3125719	113928056	11.78	0.82	0	4.29	0	0.14	0	0.05	0	0.00	0	16.58	0	3969595	0	302	0	293.24	0	1.73	0	0.02	0	1.19	0	0.00	0	107.98	0	1.10	0	39010	0	4769104	0	204833	0	6582	0	2194	0	0	0	790733	0	1079	0	0	0	8295	0	1918877	0	12324	0	1940575	0	78.94	0	3764762	0	28431	1741578	61.256304737786	4769104.0	3969595.0	39010.0	204833.0	6582.0	2194.0	0.0	790733.0	3764762.0	83.2	0.8	4.3	0.1	0.0	0.0	16.6	78.9	151	151	151.00	7	720134704	28.4	22.2	22.6	26.8	0.0	30.3	19.6	smartseq
1451611	SRR3640265	SRP076212	SRS1489037	SRX1827079	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189881: D2_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189881		GSM2189881	D2_1000700101-OGC9-sal_1_30ul_1 OGC09-sal FACS-scRNA-Seq	46239750	308265	2016-07-18 10:56:32	15781063	46239750	308265	2	308265	index:0,count:308265,average:75,stdev:0|index:1,count:308265,average:75,stdev:0	GSM2189881_r4						1.06	2.56	0.04	38549937	41579381	36618633	39846525	107.86	108.81	287975	254373	209.780	1460.284	134	1538	82.97	87.64	309990	238938	309990	238938	75.53	76.4	309990	217496	309990	208291	4186324	10.86	1.51	0	4.97	0	0.25	0	0.09	0	0.00	0	6.24	0	287975	0	150	0	147.84	0	3.92	0	0.04	0	1.09	0	0.01	0	100.89	0	0.24	0	4653	0	308265	0	15326	0	780	0	286	0	0	0	19224	0	58	0	0	0	472	0	69006	0	413	0	69949	0	88.45	0	272649	0	22271	66391	2.981051591756	308265.0	287975.0	4653.0	15326.0	780.0	286.0	0.0	19224.0	272649.0	93.4	1.5	5.0	0.3	0.1	0.0	6.2	88.4	75	75	75.00	6	23119875	24.6	25.3	25.2	24.9	0.0	35.2	30.1	smartseq
1451612	SRR3641265	SRP076212	SRS1489292	SRX1827334	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190136: H3_1000700101-OGC9-sal_1_22ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190136		GSM2190136	H3_1000700101-OGC9-sal_1_22ul_1 OGC09-sal FACS-scRNA-Seq	47934900	319566	2016-07-18 10:56:32	15935787	47934900	319566	2	319566	index:0,count:319566,average:75,stdev:0|index:1,count:319566,average:75,stdev:0	GSM2190136_r1						1.11	2.48	0.03	39199200	43041024	36993550	41072790	109.8	111.03	295715	262231	201.607	1290.922	134	1699	85.64	91.09	320405	253242	320405	253242	76.5	77.55	320405	226214	320405	215607	2871046	7.32	1.65	0	5.54	0	0.19	0	0.08	0	0.00	0	7.19	0	295715	0	150	0	147.71	0	4.06	0	0.04	0	1.08	0	0.01	0	88.50	0	0.22	0	5280	0	319566	0	17696	0	599	0	269	0	0	0	22983	0	57	0	0	0	506	0	72676	0	398	0	73637	0	87.00	0	278019	0	21596	69528	3.219485089831	319566.0	295715.0	5280.0	17696.0	599.0	269.0	0.0	22983.0	278019.0	92.5	1.7	5.5	0.2	0.1	0.0	7.2	87.0	75	75	75.00	6	23967450	24.6	25.3	25.2	24.9	0.0	35.3	30.3	smartseq
1451626	SRR3638266	SRP076212	SRS1488266	SRX1826308	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189110: 1-0-g-0-BTN22-C46-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189110		GSM2189110	1-0-g-0-BTN22-C46-10ul-1 BTN22 Mic-scRNA-Seq	73082250	487215	2016-07-18 10:56:32	34509283	73082250	487215	2	487215	index:0,count:487215,average:75,stdev:0|index:1,count:487215,average:75,stdev:0	GSM2189110_r1						1.01	3.27	0.05	63245361	61811647	61030501	59998776	97.73	98.31	449911	414551	221.514	956.839	193	2128	67.65	70.15	474759	304350	474759	304350	68.41	68.41	474759	307790	474759	296826	17336432	27.41	0.87	0	3.29	0	0.07	0	0.11	0	0.00	0	7.47	0	449911	0	150	0	148.09	0	1.40	0	0.01	0	1.22	0	0.00	0	92.31	0	0.70	0	4216	0	487215	0	16039	0	348	0	557	0	0	0	36399	0	45	0	0	0	525	0	57472	0	491	0	58533	0	89.05	0	433872	0	13849	57211	4.131056393963	487215.0	449911.0	4216.0	16039.0	348.0	557.0	0.0	36399.0	433872.0	92.3	0.9	3.3	0.1	0.1	0.0	7.5	89.1	75	75	75.00	7	36541125	29.7	20.7	20.7	28.9	0.0	33.4	21.6	smartseq
1451627	SRR3639266	SRP076212	SRS1488669	SRX1826711	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189513: 1lld-BTN17-C74 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Astro|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189513		GSM2189513	1lld-BTN17-C74 BTN17 Mic-scRNA-Seq	1293965206	4284653	2016-07-18 10:56:32	668744980	1293965206	4284653	2	4284653	index:0,count:4284653,average:151,stdev:0|index:1,count:4284653,average:151,stdev:0	GSM2189513_r1						7.41	2.83	0.03	870848185	863766880	818513414	815545288	99.19	99.64	3620451	3419947	272.410	781.477	233	17876	63.12	67.22	3895520	2285082	3895520	2285082	65.01	63.52	3895520	2353661	3895520	2159313	259161845	29.76	0.98	0	5.16	0	0.12	0	0.14	0	0.00	0	15.23	0	3620451	0	302	0	293.62	0	1.56	0	0.01	0	1.17	0	0.00	0	111.77	0	1.05	0	42156	0	4284653	0	221172	0	5270	0	6203	0	0	0	652729	0	245	0	0	0	5452	0	995591	0	8994	0	1010282	0	79.34	0	3399279	0	10774	900574	83.587711156488	4284653.0	3620451.0	42156.0	221172.0	5270.0	6203.0	0.0	652729.0	3399279.0	84.5	1.0	5.2	0.1	0.1	0.0	15.2	79.3	151	151	151.00	7	646982603	29.0	21.6	21.8	27.7	0.0	30.5	20.0	smartseq
1451628	SRR3640266	SRP076212	SRS1489038	SRX1827080	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189882: D2_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189882		GSM2189882	D2_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	75764850	505099	2016-07-18 10:56:32	31927204	75764850	505099	2	505099	index:0,count:505099,average:75,stdev:0|index:1,count:505099,average:75,stdev:0	GSM2189882_r1						1.59	2.29	0.05	62430879	70969639	58132966	67005623	113.68	115.26	453695	411939	227.516	1280.863	174	2400	77.6	83.67	499058	352063	499058	352063	64.89	65.72	499058	294417	499058	276537	8647037	13.85	2.00	0	6.52	0	0.16	0	0.17	0	0.00	0	9.84	0	453695	0	150	0	147.56	0	4.98	0	0.10	0	1.06	0	0.03	0	129.88	0	0.49	0	10086	0	505099	0	32938	0	833	0	863	0	0	0	49708	0	60	0	0	0	451	0	73267	0	693	0	74471	0	83.30	0	420757	0	20843	72462	3.476562874826	505099.0	453695.0	10086.0	32938.0	833.0	863.0	0.0	49708.0	420757.0	89.8	2.0	6.5	0.2	0.2	0.0	9.8	83.3	75	75	75.00	6	37882425	24.8	25.0	25.1	25.2	0.0	33.7	25.3	smartseq
1451629	SRR3641266	SRP076212	SRS1489292	SRX1827334	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190136: H3_1000700101-OGC9-sal_1_22ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190136		GSM2190136	H3_1000700101-OGC9-sal_1_22ul_1 OGC09-sal FACS-scRNA-Seq	47590200	317268	2016-07-18 10:56:32	15914402	47590200	317268	2	317268	index:0,count:317268,average:75,stdev:0|index:1,count:317268,average:75,stdev:0	GSM2190136_r2						1.15	2.51	0.04	38797873	42621243	36632442	40671153	109.85	111.02	292628	259831	202.035	1288.134	125	1696	85.67	91.07	316711	250686	316711	250686	76.34	77.41	316711	223406	316711	213064	2851970	7.35	1.59	0	5.48	0	0.18	0	0.08	0	0.00	0	7.50	0	292628	0	150	0	147.70	0	4.10	0	0.04	0	1.07	0	0.01	0	95.18	0	0.23	0	5058	0	317268	0	17373	0	565	0	268	0	0	0	23807	0	36	0	0	0	497	0	72102	0	384	0	73019	0	86.76	0	275255	0	21601	68940	3.191518911162	317268.0	292628.0	5058.0	17373.0	565.0	268.0	0.0	23807.0	275255.0	92.2	1.6	5.5	0.2	0.1	0.0	7.5	86.8	75	75	75.00	6	23795100	24.6	25.3	25.1	24.9	0.0	35.3	30.2	smartseq
1451643	SRR3638267	SRP076212	SRS1488266	SRX1826308	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189110: 1-0-g-0-BTN22-C46-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189110		GSM2189110	1-0-g-0-BTN22-C46-10ul-1 BTN22 Mic-scRNA-Seq	71727300	478182	2016-07-18 10:56:32	33490506	71727300	478182	2	478182	index:0,count:478182,average:75,stdev:0|index:1,count:478182,average:75,stdev:0	GSM2189110_r2						1.0	3.28	0.06	62114331	60714383	59952971	58936095	97.75	98.3	441402	405808	223.366	973.626	188	2096	67.6	70.09	465877	298380	465877	298380	68.36	68.33	465877	301737	465877	290900	17032251	27.42	0.88	0	3.28	0	0.07	0	0.11	0	0.00	0	7.51	0	441402	0	150	0	148.15	0	1.34	0	0.01	0	1.23	0	0.00	0	114.76	0	0.67	0	4231	0	478182	0	15666	0	331	0	541	0	0	0	35908	0	43	0	0	0	509	0	57004	0	445	0	58001	0	89.03	0	425736	0	13957	56988	4.083112416708	478182.0	441402.0	4231.0	15666.0	331.0	541.0	0.0	35908.0	425736.0	92.3	0.9	3.3	0.1	0.1	0.0	7.5	89.0	75	75	75.00	7	35863650	29.6	20.7	20.7	28.9	0.0	33.6	21.8	smartseq
1451644	SRR3639267	SRP076212	SRS1488670	SRX1826712	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189514: 1lld-BTN17-C90 BTN17 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN17|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189514		GSM2189514	1lld-BTN17-C90 BTN17 Mic-scRNA-Seq	1684917494	5579197	2016-07-18 10:56:32	859384587	1684917494	5579197	2	5579197	index:0,count:5579197,average:151,stdev:0|index:1,count:5579197,average:151,stdev:0	GSM2189514_r1						2.06	8.17	0.05	1157139254	1147969178	1113487821	1108194681	99.21	99.52	4758242	4317178	280.661	886.185	225	21117	70.17	73.03	5041856	3338881	5041856	3338881	69.18	68.9	5041856	3291957	5041856	3150413	284242272	24.56	0.90	0	3.33	0	0.15	0	0.07	0	0.00	0	14.49	0	4758242	0	302	0	293.61	0	1.75	0	0.02	0	1.20	0	0.00	0	113.48	0	1.05	0	50374	0	5579197	0	186061	0	8569	0	3702	0	0	0	808684	0	1210	0	0	0	8520	0	2029990	0	11712	0	2051432	0	81.95	0	4572181	0	27787	1840727	66.244178932594	5579197.0	4758242.0	50374.0	186061.0	8569.0	3702.0	0.0	808684.0	4572181.0	85.3	0.9	3.3	0.2	0.1	0.0	14.5	82.0	151	151	151.00	7	842458747	27.9	22.5	22.8	26.8	0.0	31.0	20.4	smartseq
1451645	SRR3640267	SRP076212	SRS1489038	SRX1827080	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189882: D2_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189882		GSM2189882	D2_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	73708800	491392	2016-07-18 10:56:32	31132928	73708800	491392	2	491392	index:0,count:491392,average:75,stdev:0|index:1,count:491392,average:75,stdev:0	GSM2189882_r2						1.6	2.24	0.04	60587727	68876171	56406743	65025726	113.68	115.28	440222	399793	227.563	1251.912	174	2347	77.62	83.71	484486	341690	484486	341690	64.89	65.73	484486	285668	484486	268312	8371916	13.82	2.03	0	6.52	0	0.17	0	0.16	0	0.00	0	10.09	0	440222	0	150	0	147.51	0	5.00	0	0.10	0	1.06	0	0.03	0	136.08	0	0.53	0	9961	0	491392	0	32029	0	822	0	781	0	0	0	49567	0	66	0	0	0	436	0	69983	0	736	0	71221	0	83.07	0	408193	0	20598	69224	3.360714632489	491392.0	440222.0	9961.0	32029.0	822.0	781.0	0.0	49567.0	408193.0	89.6	2.0	6.5	0.2	0.2	0.0	10.1	83.1	75	75	75.00	6	36854400	24.8	24.9	25.1	25.2	0.0	33.7	25.3	smartseq
1451646	SRR3641267	SRP076212	SRS1489292	SRX1827334	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190136: H3_1000700101-OGC9-sal_1_22ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190136		GSM2190136	H3_1000700101-OGC9-sal_1_22ul_1 OGC09-sal FACS-scRNA-Seq	47229150	314861	2016-07-18 10:56:32	15869669	47229150	314861	2	314861	index:0,count:314861,average:75,stdev:0|index:1,count:314861,average:75,stdev:0	GSM2190136_r3						1.16	2.5	0.03	38700220	42566986	36527685	40615825	109.99	111.19	291781	258740	202.525	1299.878	126	1616	85.8	91.21	315889	250334	315889	250334	76.35	77.44	315889	222777	315889	212538	2802915	7.24	1.61	0	5.50	0	0.18	0	0.09	0	0.00	0	7.06	0	291781	0	150	0	147.72	0	4.04	0	0.04	0	1.09	0	0.01	0	80.96	0	0.23	0	5073	0	314861	0	17326	0	557	0	281	0	0	0	22242	0	29	0	0	0	545	0	71892	0	387	0	72853	0	87.17	0	274455	0	21584	68748	3.185137138621	314861.0	291781.0	5073.0	17326.0	557.0	281.0	0.0	22242.0	274455.0	92.7	1.6	5.5	0.2	0.1	0.0	7.1	87.2	75	75	75.00	6	23614575	24.6	25.4	25.1	24.9	0.0	35.2	30.3	smartseq
1451656	SRR3638268	SRP076212	SRS1488266	SRX1826308	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189110: 1-0-g-0-BTN22-C46-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189110		GSM2189110	1-0-g-0-BTN22-C46-10ul-1 BTN22 Mic-scRNA-Seq	70791750	471945	2016-07-18 10:56:32	33611116	70791750	471945	2	471945	index:0,count:471945,average:75,stdev:0|index:1,count:471945,average:75,stdev:0	GSM2189110_r3						1.03	3.32	0.06	61071450	59703901	58929759	57938907	97.76	98.32	434875	400497	220.799	968.392	188	2031	67.6	70.1	458894	293984	458894	293984	68.37	68.36	458894	297307	458894	286662	16762394	27.45	0.85	0	3.29	0	0.07	0	0.11	0	0.00	0	7.68	0	434875	0	150	0	148.05	0	1.37	0	0.01	0	1.22	0	0.00	0	113.27	0	0.73	0	4021	0	471945	0	15511	0	319	0	508	0	0	0	36243	0	32	0	0	0	469	0	55642	0	436	0	56579	0	88.86	0	419364	0	13776	55352	4.018002322880	471945.0	434875.0	4021.0	15511.0	319.0	508.0	0.0	36243.0	419364.0	92.1	0.9	3.3	0.1	0.1	0.0	7.7	88.9	75	75	75.00	7	35395875	29.7	20.7	20.7	28.9	0.0	33.4	21.5	smartseq
1451657	SRR3639268	SRP076212	SRS1488671	SRX1826713	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189515: 1qt_BTN15_C47_IL4884-711-506_AAGAGGCA-ACTGCATA BTN15 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	Illumina HiSeq 2000	experiment;;BTN15|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189515		GSM2189515	1qt_BTN15_C47_IL4884-711-506_AAGAGGCA-ACTGCATA BTN15 Mic-scRNA-Seq	473518502	2344151	2016-07-18 10:56:32	330007704	473518502	2344151	2	2344151	index:0,count:2344151,average:101,stdev:0|index:1,count:2344151,average:101,stdev:0	GSM2189515_r1						2.54	3.12	0.16	359195161	354473334	337039921	333812306	98.69	99.04	2068213	1858747	241.591	868.045	180	9491	80.41	85.87	2302872	1663127	2302872	1663127	82.19	82.41	2302872	1699886	2302872	1596155	43248411	12.04	1.15	0	5.60	0	0.52	0	0.10	0	0.00	0	11.15	0	2068213	0	202	0	198.35	0	1.71	0	0.01	0	1.22	0	0.01	0	172.22	0	0.48	0	27028	0	2344151	0	131389	0	12248	0	2246	0	0	0	261444	0	279	0	0	0	4247	0	630774	0	6057	0	641357	0	82.62	0	1936824	0	13905	616623	44.345415318231	2344151.0	2068213.0	27028.0	131389.0	12248.0	2246.0	0.0	261444.0	1936824.0	88.2	1.2	5.6	0.5	0.1	0.0	11.2	82.6	101	101	101.00	38	236759251	26.6	23.0	22.9	27.5	0.0	34.4	17.1	smartseq
1451658	SRR3640268	SRP076212	SRS1489038	SRX1827080	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189882: D2_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189882		GSM2189882	D2_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	74290650	495271	2016-07-18 10:56:32	31756512	74290650	495271	2	495271	index:0,count:495271,average:75,stdev:0|index:1,count:495271,average:75,stdev:0	GSM2189882_r3						1.57	2.24	0.05	61050299	69341834	56829379	65450360	113.58	115.17	443845	402997	226.985	1239.084	174	2288	77.55	83.64	488099	344198	488099	344198	64.9	65.74	488099	288057	488099	270538	8480513	13.89	1.98	0	6.53	0	0.17	0	0.16	0	0.00	0	10.06	0	443845	0	150	0	147.49	0	4.99	0	0.10	0	1.06	0	0.03	0	118.87	0	0.56	0	9793	0	495271	0	32332	0	819	0	781	0	0	0	49826	0	81	0	0	0	431	0	70831	0	731	0	72074	0	83.09	0	411513	0	20560	70107	3.409873540856	495271.0	443845.0	9793.0	32332.0	819.0	781.0	0.0	49826.0	411513.0	89.6	2.0	6.5	0.2	0.2	0.0	10.1	83.1	75	75	75.00	6	37145325	24.8	25.0	25.1	25.2	0.0	33.5	24.8	smartseq
1451659	SRR3641268	SRP076212	SRS1489292	SRX1827334	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190136: H3_1000700101-OGC9-sal_1_22ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190136		GSM2190136	H3_1000700101-OGC9-sal_1_22ul_1 OGC09-sal FACS-scRNA-Seq	46815750	312105	2016-07-18 10:56:32	15843922	46815750	312105	2	312105	index:0,count:312105,average:75,stdev:0|index:1,count:312105,average:75,stdev:0	GSM2190136_r4						1.13	2.5	0.03	38258676	42042390	36103065	40109875	109.89	111.1	288602	255993	202.254	1263.489	136	1572	85.74	91.21	312746	247453	312746	247453	76.42	77.52	312746	220557	312746	210336	2761559	7.22	1.66	0	5.54	0	0.17	0	0.09	0	0.00	0	7.27	0	288602	0	150	0	147.67	0	4.13	0	0.04	0	1.08	0	0.01	0	102.14	0	0.24	0	5185	0	312105	0	17287	0	546	0	273	0	0	0	22684	0	36	0	0	0	478	0	71080	0	388	0	71982	0	86.93	0	271315	0	21372	67621	3.163999625678	312105.0	288602.0	5185.0	17287.0	546.0	273.0	0.0	22684.0	271315.0	92.5	1.7	5.5	0.2	0.1	0.0	7.3	86.9	75	75	75.00	6	23407875	24.6	25.4	25.2	24.9	0.0	35.2	30.2	smartseq
1451672	SRR3638269	SRP076212	SRS1488266	SRX1826308	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189110: 1-0-g-0-BTN22-C46-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189110		GSM2189110	1-0-g-0-BTN22-C46-10ul-1 BTN22 Mic-scRNA-Seq	70061850	467079	2016-07-18 10:56:32	33022905	70061850	467079	2	467079	index:0,count:467079,average:75,stdev:0|index:1,count:467079,average:75,stdev:0	GSM2189110_r4						1.03	3.33	0.06	60486080	59112852	58365923	57371235	97.73	98.3	430100	396370	221.676	968.945	188	2016	67.61	70.11	454048	290783	454048	290783	68.4	68.39	454048	294199	454048	283652	16593838	27.43	0.86	0	3.28	0	0.08	0	0.11	0	0.00	0	7.74	0	430100	0	150	0	148.10	0	1.37	0	0.01	0	1.21	0	0.00	0	88.50	0	0.71	0	4000	0	467079	0	15341	0	353	0	491	0	0	0	36135	0	35	0	0	0	463	0	54314	0	461	0	55273	0	88.80	0	414759	0	13761	54190	3.937940556646	467079.0	430100.0	4000.0	15341.0	353.0	491.0	0.0	36135.0	414759.0	92.1	0.9	3.3	0.1	0.1	0.0	7.7	88.8	75	75	75.00	7	35030925	29.7	20.7	20.7	28.9	0.0	33.4	21.5	smartseq
1451673	SRR3639269	SRP076212	SRS1488672	SRX1826714	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189516: 1t-BTN16-C01 BTN16 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN16|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189516		GSM2189516	1t-BTN16-C01 BTN16 Mic-scRNA-Seq	1007000880	3334440	2016-07-18 10:56:32	539696218	1007000880	3334440	2	3334440	index:0,count:3334440,average:151,stdev:0|index:1,count:3334440,average:151,stdev:0	GSM2189516_r1						1.61	3.42	0.17	660704508	631609805	638362885	610555861	95.6	95.64	2756138	2607267	270.521	608.048	233	14128	65.37	67.75	2925337	1801600	2925337	1801600	65.58	65.17	2925337	1807593	2925337	1732849	183232281	27.73	0.72	0	2.91	0	0.41	0	0.13	0	0.00	0	16.80	0	2756138	0	302	0	293.27	0	1.72	0	0.01	0	1.15	0	0.00	0	90.26	0	1.15	0	24130	0	3334440	0	97078	0	13713	0	4304	0	0	0	560285	0	620	0	0	0	2591	0	783269	0	8104	0	794584	0	79.75	0	2659060	0	10529	715931	67.996105992972	3334440.0	2756138.0	24130.0	97078.0	13713.0	4304.0	0.0	560285.0	2659060.0	82.7	0.7	2.9	0.4	0.1	0.0	16.8	79.7	151	151	151.00	7	503500440	28.7	22.1	22.4	26.8	0.0	29.6	19.0	smartseq
1451674	SRR3640269	SRP076212	SRS1489038	SRX1827080	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189882: D2_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189882		GSM2189882	D2_1000700102-OGC9-sal_1_6ul_1 OGC09-sal FACS-scRNA-Seq	73352400	489016	2016-07-18 10:56:32	31219614	73352400	489016	2	489016	index:0,count:489016,average:75,stdev:0|index:1,count:489016,average:75,stdev:0	GSM2189882_r4						1.59	2.2	0.04	60421734	68682644	56292375	64877963	113.67	115.25	438545	397549	228.344	1279.698	174	2241	77.67	83.7	481802	340638	481802	340638	64.93	65.76	481802	284755	481802	267626	8331466	13.79	1.98	0	6.46	0	0.16	0	0.16	0	0.00	0	10.00	0	438545	0	150	0	147.54	0	4.96	0	0.10	0	1.05	0	0.03	0	110.03	0	0.53	0	9673	0	489016	0	31586	0	774	0	787	0	0	0	48910	0	68	0	0	0	465	0	69945	0	676	0	71154	0	83.22	0	406959	0	20510	68978	3.363139931741	489016.0	438545.0	9673.0	31586.0	774.0	787.0	0.0	48910.0	406959.0	89.7	2.0	6.5	0.2	0.2	0.0	10.0	83.2	75	75	75.00	6	36676200	24.7	25.0	25.1	25.2	0.0	33.6	25.0	smartseq
1451675	SRR3641269	SRP076212	SRS1489293	SRX1827335	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190137: H3_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190137		GSM2190137	H3_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq	41752050	278347	2016-07-18 10:56:32	14068660	41752050	278347	2	278347	index:0,count:278347,average:75,stdev:0|index:1,count:278347,average:75,stdev:0	GSM2190137_r1						1.62	2.75	0.03	34287033	36032873	32379072	34318349	105.09	105.99	257126	225062	209.435	1470.178	130	1366	82.36	87.47	278979	211777	278979	211777	78.16	78.77	278979	200972	278979	190720	3812888	11.12	1.51	0	5.39	0	0.25	0	0.07	0	0.00	0	7.30	0	257126	0	150	0	147.68	0	3.51	0	0.03	0	1.12	0	0.01	0	83.50	0	0.21	0	4199	0	278347	0	15006	0	685	0	207	0	0	0	20329	0	33	0	0	0	418	0	66387	0	368	0	67206	0	86.98	0	242120	0	21897	63472	2.898661917158	278347.0	257126.0	4199.0	15006.0	685.0	207.0	0.0	20329.0	242120.0	92.4	1.5	5.4	0.2	0.1	0.0	7.3	87.0	75	75	75.00	6	20876025	24.8	25.1	24.9	25.2	0.0	35.2	30.1	smartseq
1451785	SRR3638270	SRP076212	SRS1488267	SRX1826309	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189111: 1-0-g-0-BTN22-C51-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189111		GSM2189111	1-0-g-0-BTN22-C51-10ul-1 BTN22 Mic-scRNA-Seq	44296050	295307	2016-07-18 10:56:32	20965927	44296050	295307	2	295307	index:0,count:295307,average:75,stdev:0|index:1,count:295307,average:75,stdev:0	GSM2189111_r1						1.47	3.64	0.03	38842181	37834809	37268885	36544154	97.41	98.06	272041	250364	241.821	1013.725	188	1189	70.19	73.2	289033	190952	289033	190952	71.32	71.28	289033	194013	289033	185952	9392450	24.18	0.96	0	3.78	0	0.10	0	0.12	0	0.00	0	7.65	0	272041	0	150	0	148.27	0	1.35	0	0.01	0	1.19	0	0.00	0	66.44	0	0.70	0	2835	0	295307	0	11165	0	303	0	364	0	0	0	22599	0	21	0	0	0	281	0	32228	0	309	0	32839	0	88.34	0	260876	0	10980	32330	2.944444444444	295307.0	272041.0	2835.0	11165.0	303.0	364.0	0.0	22599.0	260876.0	92.1	1.0	3.8	0.1	0.1	0.0	7.7	88.3	75	75	75.00	7	22148025	29.9	20.3	20.4	29.5	0.0	33.4	21.7	smartseq
1451786	SRR3639270	SRP076212	SRS1488673	SRX1826715	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189517: 1t-BTN16-C09 BTN16 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN16|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189517		GSM2189517	1t-BTN16-C09 BTN16 Mic-scRNA-Seq	1440075524	4768462	2016-07-18 10:56:32	740708399	1440075524	4768462	2	4768462	index:0,count:4768462,average:151,stdev:0|index:1,count:4768462,average:151,stdev:0	GSM2189517_r1						2.18	4.26	0.06	976806799	961306194	938811138	925758360	98.41	98.61	3974457	3728342	285.912	684.437	233	18674	66.26	69.06	4240161	2633349	4240161	2633349	67.22	66.68	4240161	2671706	4240161	2542543	289081787	29.59	0.71	0	3.38	0	0.36	0	0.07	0	0.00	0	16.22	0	3974457	0	302	0	293.86	0	1.67	0	0.01	0	1.22	0	0.01	0	104.04	0	1.07	0	34042	0	4768462	0	161240	0	17184	0	3479	0	0	0	773342	0	595	0	0	0	6558	0	1173138	0	12257	0	1192548	0	79.97	0	3813217	0	9164	1091872	119.147970318638	4768462.0	3974457.0	34042.0	161240.0	17184.0	3479.0	0.0	773342.0	3813217.0	83.3	0.7	3.4	0.4	0.1	0.0	16.2	80.0	151	151	151.00	7	720037762	28.2	22.2	22.7	26.9	0.0	30.6	19.8	smartseq
1451787	SRR3640270	SRP076212	SRS1489039	SRX1827081	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189883: D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189883		GSM2189883	D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	216000	1440	2016-07-18 10:56:32	113309	216000	1440	2	1440	index:0,count:1440,average:75,stdev:0|index:1,count:1440,average:75,stdev:0	GSM2189883_r1						1.09	2.18	0.59	104243	111941	96954	105129	107.38	108.43	904	855	138.488	844.626	115	14	80.64	87.41	1010	729	1010	729	73.34	75.66	1010	663	1010	631	11507	11.04	1.67	0	4.86	0	0.00	0	0.00	0	0.00	0	37.22	0	904	0	150	0	146.04	0	4.07	0	0.05	0	1.00	0	0.01	0	2.59	0	0.24	0	24	0	1440	0	70	0	0	0	0	0	0	0	536	0	0	0	0	0	5	0	205	0	0	0	210	0	57.92	0	834	0	160	169	1.056250000000	1440.0	904.0	24.0	70.0	0.0	0.0	0.0	536.0	834.0	62.8	1.7	4.9	0.0	0.0	0.0	37.2	57.9	75	75	75.00	6	108000	23.5	27.2	25.1	24.2	0.0	35.2	29.2	smartseq
1451788	SRR3641270	SRP076212	SRS1489297	SRX1827340	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190142: H4_1000700102-OGC9-sal_1_8ul_1 OGC09-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC09-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190142		GSM2190142	H4_1000700102-OGC9-sal_1_8ul_1 OGC09-sal FACS-scRNA-Seq	84292500	561950	2016-07-18 10:56:32	35417897	84292500	561950	2	561950	index:0,count:561950,average:75,stdev:0|index:1,count:561950,average:75,stdev:0	GSM2190142_r2						1.38	1.88	0.02	69713803	80026771	64962171	75688117	114.79	116.51	509554	465418	221.052	1205.446	174	2612	78.06	84.08	558082	397737	558082	397737	63.07	64.11	558082	321365	558082	303283	8835165	12.67	1.90	0	6.50	0	0.21	0	0.07	0	0.00	0	9.05	0	509554	0	150	0	147.60	0	4.80	0	0.08	0	1.16	0	0.03	0	155.62	0	0.54	0	10688	0	561950	0	36517	0	1152	0	376	0	0	0	50868	0	57	0	0	0	499	0	81560	0	738	0	82854	0	84.18	0	473037	0	25720	79589	3.094440124417	561950.0	509554.0	10688.0	36517.0	1152.0	376.0	0.0	50868.0	473037.0	90.7	1.9	6.5	0.2	0.1	0.0	9.1	84.2	75	75	75.00	6	42146250	24.5	25.2	25.3	24.9	0.0	33.8	25.5	smartseq
1451800	SRR3638271	SRP076212	SRS1488267	SRX1826309	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189111: 1-0-g-0-BTN22-C51-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189111		GSM2189111	1-0-g-0-BTN22-C51-10ul-1 BTN22 Mic-scRNA-Seq	44281950	295213	2016-07-18 10:56:32	20704388	44281950	295213	2	295213	index:0,count:295213,average:75,stdev:0|index:1,count:295213,average:75,stdev:0	GSM2189111_r2						1.47	3.68	0.03	38862534	37915948	37325797	36649288	97.56	98.19	272200	250138	244.053	1024.295	196	1147	70.29	73.24	288691	191339	288691	191339	71.36	71.34	288691	194240	288691	186377	9437071	24.28	0.96	0	3.71	0	0.09	0	0.12	0	0.00	0	7.58	0	272200	0	150	0	148.31	0	1.33	0	0.01	0	1.18	0	0.00	0	55.94	0	0.66	0	2828	0	295213	0	10939	0	279	0	344	0	0	0	22390	0	36	0	0	0	310	0	32306	0	329	0	32981	0	88.50	0	261261	0	11034	32354	2.932209534167	295213.0	272200.0	2828.0	10939.0	279.0	344.0	0.0	22390.0	261261.0	92.2	1.0	3.7	0.1	0.1	0.0	7.6	88.5	75	75	75.00	7	22140975	29.8	20.3	20.4	29.5	0.0	33.6	21.9	smartseq
1451801	SRR3639271	SRP076212	SRS1488674	SRX1826716	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189518: 1t-BTN16-C10 BTN16 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN16|major cell type;;Macrophage|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189518		GSM2189518	1t-BTN16-C10 BTN16 Mic-scRNA-Seq	1477908876	4893738	2016-07-18 10:56:32	755767166	1477908876	4893738	2	4893738	index:0,count:4893738,average:151,stdev:0|index:1,count:4893738,average:151,stdev:0	GSM2189518_r1						1.96	3.37	0.24	978911718	970012545	939300167	931138862	99.09	99.13	4087980	3819889	277.539	650.173	230	19855	78.71	82.16	4351570	3217638	4351570	3217638	78.06	78.26	4351570	3191199	4351570	3064664	148043487	15.12	1.07	0	3.51	0	0.18	0	0.07	0	0.00	0	16.22	0	4087980	0	302	0	293.16	0	1.85	0	0.01	0	1.17	0	0.01	0	107.42	0	1.05	0	52279	0	4893738	0	171747	0	8689	0	3462	0	0	0	793607	0	435	0	0	0	7750	0	1501229	0	8935	0	1518349	0	80.03	0	3916233	0	9202	1371551	149.049228428602	4893738.0	4087980.0	52279.0	171747.0	8689.0	3462.0	0.0	793607.0	3916233.0	83.5	1.1	3.5	0.2	0.1	0.0	16.2	80.0	151	151	151.00	7	738954438	26.9	23.6	23.8	25.7	0.0	30.7	20.0	smartseq
1451802	SRR3640271	SRP076212	SRS1489039	SRX1827081	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189883: D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189883		GSM2189883	D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	219450	1463	2016-07-18 10:56:32	114943	219450	1463	2	1463	index:0,count:1463,average:75,stdev:0|index:1,count:1463,average:75,stdev:0	GSM2189883_r2						1.66	2.39	0.0	100965	108121	93804	100674	107.09	107.32	874	824	140.814	1073.182	87	15	81.92	88.5	963	716	963	716	75.74	77.26	963	662	963	625	9561	9.47	2.19	0	4.44	0	0.21	0	0.07	0	0.00	0	39.99	0	874	0	150	0	146.18	0	3.00	0	0.02	0	1.00	0	0.01	0	2.63	0	0.21	0	32	0	1463	0	65	0	3	0	1	0	0	0	585	0	2	0	0	0	2	0	238	0	4	0	246	0	55.30	0	809	0	196	201	1.025510204082	1463.0	874.0	32.0	65.0	3.0	1.0	0.0	585.0	809.0	59.7	2.2	4.4	0.2	0.1	0.0	40.0	55.3	75	75	75.00	6	109725	23.8	27.0	25.6	23.5	0.0	35.2	29.5	smartseq
1451803	SRR3641271	SRP076212	SRS1489293	SRX1827335	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190137: H3_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190137		GSM2190137	H3_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq	41640300	277602	2016-07-18 10:56:32	14090144	41640300	277602	2	277602	index:0,count:277602,average:75,stdev:0|index:1,count:277602,average:75,stdev:0	GSM2190137_r2						1.65	2.73	0.03	34105674	35804480	32200118	34101409	104.98	105.9	255875	224331	209.885	1491.292	131	1332	82.19	87.3	277861	210307	277861	210307	78.05	78.67	277861	199705	277861	189513	3818090	11.19	1.50	0	5.40	0	0.26	0	0.07	0	0.00	0	7.49	0	255875	0	150	0	147.70	0	3.55	0	0.03	0	1.14	0	0.01	0	71.38	0	0.22	0	4165	0	277602	0	14979	0	728	0	197	0	0	0	20802	0	49	0	0	0	407	0	65965	0	390	0	66811	0	86.78	0	240896	0	21866	62874	2.875423031190	277602.0	255875.0	4165.0	14979.0	728.0	197.0	0.0	20802.0	240896.0	92.2	1.5	5.4	0.3	0.1	0.0	7.5	86.8	75	75	75.00	6	20820150	24.9	25.0	24.9	25.2	0.0	35.2	30.0	smartseq
1451818	SRR3638272	SRP076212	SRS1488267	SRX1826309	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189111: 1-0-g-0-BTN22-C51-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189111		GSM2189111	1-0-g-0-BTN22-C51-10ul-1 BTN22 Mic-scRNA-Seq	42965550	286437	2016-07-18 10:56:32	20450957	42965550	286437	2	286437	index:0,count:286437,average:75,stdev:0|index:1,count:286437,average:75,stdev:0	GSM2189111_r3						1.46	3.69	0.03	37602625	36691340	36104462	35444252	97.58	98.17	263544	242268	241.424	981.864	204	1126	70.16	73.11	279772	184895	279772	184895	71.22	71.15	279772	187690	279772	179934	9143956	24.32	0.93	0	3.72	0	0.10	0	0.12	0	0.00	0	7.77	0	263544	0	150	0	148.25	0	1.36	0	0.01	0	1.18	0	0.00	0	68.74	0	0.73	0	2666	0	286437	0	10654	0	292	0	346	0	0	0	22255	0	47	0	0	0	284	0	31251	0	272	0	31854	0	88.29	0	252890	0	10779	31297	2.903516096113	286437.0	263544.0	2666.0	10654.0	292.0	346.0	0.0	22255.0	252890.0	92.0	0.9	3.7	0.1	0.1	0.0	7.8	88.3	75	75	75.00	7	21482775	29.8	20.3	20.4	29.4	0.0	33.4	21.6	smartseq
1451819	SRR3639272	SRP076212	SRS1488675	SRX1826717	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189519: 1t-BTN16-C11 BTN16 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN16|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189519		GSM2189519	1t-BTN16-C11 BTN16 Mic-scRNA-Seq	1506378718	4988009	2016-07-18 10:56:32	766422894	1506378718	4988009	2	4988009	index:0,count:4988009,average:151,stdev:0|index:1,count:4988009,average:151,stdev:0	GSM2189519_r1						1.34	6.94	0.1	1017199646	1021164010	987394814	993122440	100.39	100.58	4241390	3882493	272.963	818.809	230	19586	70.1	72.31	4429178	2973417	4429178	2973417	69.28	69.03	4429178	2938425	4429178	2838590	274724487	27.01	0.74	0	2.59	0	0.09	0	0.03	0	0.00	0	14.84	0	4241390	0	302	0	293.79	0	1.62	0	0.01	0	1.24	0	0.00	0	125.57	0	1.00	0	36995	0	4988009	0	129315	0	4605	0	1596	0	0	0	740418	0	1279	0	0	0	9220	0	1736516	0	9639	0	1756654	0	82.44	0	4112075	0	15716	1557286	99.089208449987	4988009.0	4241390.0	36995.0	129315.0	4605.0	1596.0	0.0	740418.0	4112075.0	85.0	0.7	2.6	0.1	0.0	0.0	14.8	82.4	151	151	151.00	7	753189359	27.9	22.6	22.8	26.7	0.0	30.9	20.3	smartseq
1451820	SRR3640272	SRP076212	SRS1489039	SRX1827081	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189883: D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189883		GSM2189883	D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	214950	1433	2016-07-18 10:56:32	113872	214950	1433	2	1433	index:0,count:1433,average:75,stdev:0|index:1,count:1433,average:75,stdev:0	GSM2189883_r3						1.38	2.47	0.0	102028	108652	94427	102251	106.49	108.29	900	853	134.462	756.282	111	16	78.11	84.8	1011	703	1011	703	72.33	73.46	1011	651	1011	609	13221	12.96	1.47	0	4.95	0	0.07	0	0.00	0	0.00	0	37.12	0	900	0	150	0	145.88	0	4.50	0	0.04	0	1.12	0	0.01	0	5.16	0	0.25	0	21	0	1433	0	71	0	1	0	0	0	0	0	532	0	0	0	0	0	0	0	198	0	2	0	200	0	57.85	0	829	0	158	165	1.044303797468	1433.0	900.0	21.0	71.0	1.0	0.0	0.0	532.0	829.0	62.8	1.5	5.0	0.1	0.0	0.0	37.1	57.9	75	75	75.00	6	107475	23.7	26.9	25.2	24.1	0.0	35.2	29.6	smartseq
1451821	SRR3641272	SRP076212	SRS1489293	SRX1827335	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190137: H3_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190137		GSM2190137	H3_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq	41225700	274838	2016-07-18 10:56:32	14045751	41225700	274838	2	274838	index:0,count:274838,average:75,stdev:0|index:1,count:274838,average:75,stdev:0	GSM2190137_r3						1.63	2.75	0.03	33939749	35646010	32053314	33947076	105.03	105.91	254418	222914	210.330	1458.522	128	1343	82.18	87.25	276210	209078	276210	209078	77.99	78.6	276210	198431	276210	188330	3837447	11.31	1.53	0	5.38	0	0.29	0	0.08	0	0.00	0	7.06	0	254418	0	150	0	147.68	0	3.50	0	0.03	0	1.12	0	0.01	0	61.84	0	0.22	0	4199	0	274838	0	14799	0	793	0	226	0	0	0	19401	0	50	0	0	0	402	0	66240	0	356	0	67048	0	87.19	0	239619	0	22067	63478	2.876603072461	274838.0	254418.0	4199.0	14799.0	793.0	226.0	0.0	19401.0	239619.0	92.6	1.5	5.4	0.3	0.1	0.0	7.1	87.2	75	75	75.00	6	20612850	24.8	25.1	24.9	25.2	0.0	35.2	30.0	smartseq
1451833	SRR3638273	SRP076212	SRS1488267	SRX1826309	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189111: 1-0-g-0-BTN22-C51-10ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189111		GSM2189111	1-0-g-0-BTN22-C51-10ul-1 BTN22 Mic-scRNA-Seq	42719550	284797	2016-07-18 10:56:32	20139243	42719550	284797	2	284797	index:0,count:284797,average:75,stdev:0|index:1,count:284797,average:75,stdev:0	GSM2189111_r4						1.48	3.65	0.03	37362927	36430186	35875005	35204562	97.5	98.13	262038	241258	240.391	968.276	196	1135	70.1	73.06	277953	183696	277953	183696	71.14	71.1	277953	186425	277953	178786	9089075	24.33	0.94	0	3.72	0	0.10	0	0.13	0	0.00	0	7.77	0	262038	0	150	0	148.23	0	1.34	0	0.01	0	1.19	0	0.00	0	56.96	0	0.71	0	2691	0	284797	0	10591	0	279	0	363	0	0	0	22117	0	30	0	0	0	260	0	31249	0	283	0	31822	0	88.29	0	251447	0	10796	31244	2.894034827714	284797.0	262038.0	2691.0	10591.0	279.0	363.0	0.0	22117.0	251447.0	92.0	0.9	3.7	0.1	0.1	0.0	7.8	88.3	75	75	75.00	7	21359775	29.9	20.3	20.4	29.5	0.0	33.5	21.6	smartseq
1451834	SRR3639273	SRP076212	SRS1488676	SRX1826718	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189520: 1t-BTN16-C14 BTN16 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN16|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189520		GSM2189520	1t-BTN16-C14 BTN16 Mic-scRNA-Seq	1714782274	5678087	2016-07-18 10:56:32	878920535	1714782274	5678087	2	5678087	index:0,count:5678087,average:151,stdev:0|index:1,count:5678087,average:151,stdev:0	GSM2189520_r1						3.85	5.67	0.01	1148857529	1166390732	1100041126	1120791469	101.53	101.89	4769713	4489400	273.117	710.138	225	23000	63.56	66.47	5042408	3031479	5042408	3031479	62.97	62.0	5042408	3003275	5042408	2827609	375270533	32.66	0.96	0	3.68	0	0.08	0	0.05	0	0.00	0	15.87	0	4769713	0	302	0	293.67	0	1.79	0	0.01	0	1.18	0	0.00	0	139.06	0	1.05	0	54255	0	5678087	0	208935	0	4540	0	2707	0	0	0	901127	0	330	0	0	0	7079	0	1350598	0	10627	0	1368634	0	80.32	0	4560778	0	13981	1232481	88.153994707102	5678087.0	4769713.0	54255.0	208935.0	4540.0	2707.0	0.0	901127.0	4560778.0	84.0	1.0	3.7	0.1	0.0	0.0	15.9	80.3	151	151	151.00	7	857391137	29.0	21.5	21.9	27.7	0.0	30.7	20.0	smartseq
1451835	SRR3640273	SRP076212	SRS1489039	SRX1827081	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189883: D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189883		GSM2189883	D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	217650	1451	2016-07-18 10:56:32	114928	217650	1451	2	1451	index:0,count:1451,average:75,stdev:0|index:1,count:1451,average:75,stdev:0	GSM2189883_r4						1.6	1.92	0.11	97639	105103	91393	100001	107.64	109.42	856	805	136.056	890.130	116	13	83.53	89.38	938	715	938	715	75.58	76.88	938	647	938	615	8700	8.91	2.27	0	3.86	0	0.21	0	0.07	0	0.00	0	40.73	0	856	0	150	0	145.56	0	2.94	0	0.04	0	1.00	0	0.01	0	5.22	0	0.19	0	33	0	1451	0	56	0	3	0	1	0	0	0	591	0	1	0	0	0	4	0	188	0	0	0	193	0	55.13	0	800	0	153	161	1.052287581699	1451.0	856.0	33.0	56.0	3.0	1.0	0.0	591.0	800.0	59.0	2.3	3.9	0.2	0.1	0.0	40.7	55.1	75	75	75.00	6	108825	23.4	27.0	25.5	24.1	0.0	35.2	29.9	smartseq
1451836	SRR3641273	SRP076212	SRS1489293	SRX1827335	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190137: H3_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190137		GSM2190137	H3_1000700401-OGC7-coc_1_14ul_1 OGC07-sal FACS-scRNA-Seq	41075700	273838	2016-07-18 10:56:32	14079677	41075700	273838	2	273838	index:0,count:273838,average:75,stdev:0|index:1,count:273838,average:75,stdev:0	GSM2190137_r4						1.62	2.84	0.04	33773185	35486187	31899587	33810859	105.07	105.99	253225	221679	210.481	1472.106	110	1322	82.38	87.46	274541	208604	274541	208604	78.11	78.74	274541	197802	274541	187812	3740215	11.07	1.48	0	5.37	0	0.28	0	0.08	0	0.00	0	7.17	0	253225	0	150	0	147.68	0	3.54	0	0.03	0	1.14	0	0.01	0	70.42	0	0.22	0	4064	0	273838	0	14701	0	755	0	218	0	0	0	19640	0	50	0	0	0	435	0	65211	0	320	0	66016	0	87.10	0	238524	0	21933	62285	2.839784799161	273838.0	253225.0	4064.0	14701.0	755.0	218.0	0.0	19640.0	238524.0	92.5	1.5	5.4	0.3	0.1	0.0	7.2	87.1	75	75	75.00	6	20537850	24.8	25.1	24.9	25.2	0.0	35.2	29.9	smartseq
1451848	SRR3639274	SRP076212	SRS1488677	SRX1826719	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189521: 1t-BTN16-C16 BTN16 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN16|major cell type;;Oligo|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189521		GSM2189521	1t-BTN16-C16 BTN16 Mic-scRNA-Seq	1525867986	5052543	2016-07-18 10:56:32	781540644	1525867986	5052543	2	5052543	index:0,count:5052543,average:151,stdev:0|index:1,count:5052543,average:151,stdev:0	GSM2189521_r1						2.66	6.85	0.07	1041956493	1042723045	999321579	1003376406	100.07	100.41	4275633	3902362	280.113	877.935	230	19813	72.1	75.28	4536211	3082601	4536211	3082601	71.92	71.65	4536211	3075130	4536211	2934050	245808287	23.59	0.83	0	3.58	0	0.10	0	0.07	0	0.00	0	15.20	0	4275633	0	302	0	293.64	0	1.64	0	0.01	0	1.18	0	0.00	0	111.59	0	1.06	0	41983	0	5052543	0	180853	0	5250	0	3428	0	0	0	768232	0	590	0	0	0	8903	0	1708551	0	12283	0	1730327	0	81.04	0	4094780	0	17211	1559964	90.637615478473	5052543.0	4275633.0	41983.0	180853.0	5250.0	3428.0	0.0	768232.0	4094780.0	84.6	0.8	3.6	0.1	0.1	0.0	15.2	81.0	151	151	151.00	7	762933993	28.2	22.1	22.6	27.0	0.0	30.8	20.1	smartseq
1451849	SRR3640274	SRP076212	SRS1489039	SRX1827081	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189883: D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC07-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189883		GSM2189883	D2_1000700401-OGC7-coc_1_10ul_1 OGC07-sal FACS-scRNA-Seq	63839550	425597	2016-07-18 10:56:32	23854706	63839550	425597	2	425597	index:0,count:425597,average:75,stdev:0|index:1,count:425597,average:75,stdev:0	GSM2189883_r5						1.27	2.64	0.09	51567962	54434950	48844439	51981694	105.56	106.42	388985	340549	209.664	1474.194	123	2002	83.55	88.48	421465	325014	421465	325014	78.76	79.46	421465	306381	421465	291896	5285973	10.25	1.50	0	5.08	0	0.24	0	0.08	0	0.00	0	8.28	0	388985	0	150	0	147.65	0	3.62	0	0.03	0	1.14	0	0.01	0	127.68	0	0.26	0	6366	0	425597	0	21641	0	1020	0	350	0	0	0	35242	0	85	0	0	0	670	0	99058	0	632	0	100445	0	86.31	0	367344	0	24840	95214	3.833091787440	425597.0	388985.0	6366.0	21641.0	1020.0	350.0	0.0	35242.0	367344.0	91.4	1.5	5.1	0.2	0.1	0.0	8.3	86.3	75	75	75.00	6	31919775	24.6	25.4	25.1	24.9	0.0	34.7	28.0	smartseq
1451850	SRR3641274	SRP076212	SRS1489294	SRX1827336	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2190138: H3_1000700602-OGC11-sal_1_4ul_1 OGC11-sal FACS-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;OGC11-sal|major cell type;;Neuron|protocol;;FACS-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2190138		GSM2190138	H3_1000700602-OGC11-sal_1_4ul_1 OGC11-sal FACS-scRNA-Seq	47247600	314984	2016-07-18 10:56:32	18021937	47247600	314984	2	314984	index:0,count:314984,average:75,stdev:0|index:1,count:314984,average:75,stdev:0	GSM2190138_r1						1.76	2.45	0.02	37527876	40627823	35275356	38551644	108.26	109.29	284366	259707	203.744	1070.262	110	1581	76.21	81.39	310207	216721	310207	216721	68.29	68.83	310207	194203	310207	183278	6018047	16.04	1.82	0	5.74	0	0.33	0	0.14	0	0.00	0	9.25	0	284366	0	150	0	147.51	0	4.11	0	0.04	0	1.12	0	0.02	0	103.09	0	0.29	0	5737	0	314984	0	18078	0	1027	0	443	0	0	0	29148	0	45	0	0	0	339	0	53084	0	373	0	53841	0	84.54	0	266288	0	15830	50831	3.211054958939	314984.0	284366.0	5737.0	18078.0	1027.0	443.0	0.0	29148.0	266288.0	90.3	1.8	5.7	0.3	0.1	0.0	9.3	84.5	75	75	75.00	6	23623800	24.8	25.2	24.8	25.2	0.0	34.6	27.5	smartseq
1451865	SRR3638275	SRP076212	SRS1488268	SRX1826310	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189112: 1-0-g-0-BTN22-C71-18ul-1 BTN22 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN22|major cell type;;Neuron|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189112		GSM2189112	1-0-g-0-BTN22-C71-18ul-1 BTN22 Mic-scRNA-Seq	98846250	658975	2016-07-18 10:56:32	46185748	98846250	658975	2	658975	index:0,count:658975,average:75,stdev:0|index:1,count:658975,average:75,stdev:0	GSM2189112_r2						0.96	3.41	0.16	87308368	84787996	84985231	82915574	97.11	97.56	612305	587581	240.700	767.350	206	2603	38.42	39.5	640200	235264	640200	235264	39.1	38.45	640200	239393	640200	229024	50590629	57.94	0.86	0	2.53	0	0.11	0	0.24	0	0.00	0	6.73	0	612305	0	150	0	148.66	0	1.36	0	0.01	0	1.22	0	0.00	0	131.80	0	0.64	0	5644	0	658975	0	16696	0	719	0	1597	0	0	0	44354	0	33	0	0	0	312	0	35986	0	451	0	36782	0	90.38	0	595609	0	12028	36357	3.022697040239	658975.0	612305.0	5644.0	16696.0	719.0	1597.0	0.0	44354.0	595609.0	92.9	0.9	2.5	0.1	0.2	0.0	6.7	90.4	75	75	75.00	7	49423125	30.1	20.0	20.1	29.8	0.0	33.7	22.5	smartseq
1451866	SRR3639275	SRP076212	SRS1488678	SRX1826720	SRA431419	GEO		Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNAseq	The striatum contributes to many cognitive processes and disorders, but its cell types are incompletely characterized. We show that microfluidic and FACS-based single-cell RNA sequencing of mouse striatum provides a well-resolved classification of striatal cell type diversity. Transcriptome analysis revealed 10 differentiated distinct cell types, including neurons, astrocytes, oligodendrocytes, ependymal, immune, and vascular cells, and enabled the discovery of numerous novel marker genes. Furthermore, we identified two discrete subtypes of medium spiny neurons (MSN) which have specific markers and which overexpress genes linked to cognitive disorders and addiction. We also describe continuous cellular identities, which increase heterogeneity within discrete cell types. Finally, we identified cell type specific transcription and splicing factors that shape cellular identities by regulating splicing and expression patterns. Our findings suggest that functional diversity within a complex tissue arises from a small number of discrete cell types, which can exist in a continuous spectrum of functional states. Overall design: We measured the transcriptome of 1208 single striatal cells using two complementary approaches; microfluidic single-cell RNAseq (Mic-scRNAseq) and single cell isolation by FACS (FACS-scRNAseq) (Table S1). We sampled cells either randomly or enriched specifically for MSNs or astrocytes using FACS from D1- tdTomato (tdTom)/D2-GFP or Aldhl1-GFP mice, respectively		GSM2189522: 1t-BTN16-C18 BTN16 Mic-scRNA-Seq; Mus musculus; RNA-Seq				RNA-Seq	TRANSCRIPTOMIC	cDNA	paired			Acute brain slices were cut from 5-7 weeks old male mouse and after papain treatment dissociated mechanically (SI Methods). Live cells were purified by either magnetic bead-activated cell sorting (MACS;Miltenyi Biotec) or by fluorescence-activated cell sorting (FACS). For cell type specific isolation genetically labeled MSN subtypes D1-, D2-MSN, and astrocytes were purified by FACS. Single cells were captured on a microfluidic chip on the C1 system (Fluidigm) and whole-transcriptome amplified cDNA was prepared on chip using theSMARTer Ultra LowRNAkit for Illumina (Clontech). For smart-seq2 protocol, three MSN populations (D1-MSN tdTom+, D1-MSN GFP+ and tdTom+/GFP+ MSNs) sorted individually into 96 well plates with lysis buffer and spun down and frozen at -80°C and amplified using the protocol as described previously (Picelli et al., 2013). Libraries were prepared using Illumina Nextera XT kit per illumina's protocols.	NextSeq 500	experiment;;BTN16|major cell type;;Microglia|protocol;;Mic-scRNA-Seq|source_name;;striatum	GEO Accession;;GSM2189522		GSM2189522	1t-BTN16-C18 BTN16 Mic-scRNA-Seq	1667030336	5519968	2016-07-18 10:56:32	852061866	1667030336	5519968	2	5519968	index:0,count:5519968,average:151,stdev:0|index:1,count:5519968,average:151,stdev:0	GSM2189522_r1						1.44	2.73	0.05	1157144513	1137218498	1121696874	1103427312	98.28	98.