Comprehensive Classification of Retinal Bipolar Neurons by Single-Cell Transcriptomics

被引:748
作者
Shekhar, Karthik [1 ]
Lapan, Sylvain W. [2 ,8 ]
Whitney, Irene E. [4 ,5 ]
Tran, Nicholas M. [4 ,5 ]
Macosko, Evan Z. [2 ,6 ]
Kowalczyk, Monika [1 ]
Adiconis, Xian [1 ,6 ]
Levin, Joshua Z. [1 ,6 ]
Nemesh, James [2 ,6 ]
Goldman, Melissa [2 ,6 ]
McCarroll, Steven A. [2 ,6 ,7 ]
Cepko, Constance L. [2 ,3 ,8 ]
Regev, Aviv [1 ,8 ,9 ,10 ]
Sanes, Joshua R. [4 ,5 ]
机构
[1] Broad Inst Harvard & MIT, Cambridge, MA 02142 USA
[2] Harvard Med Sch, Dept Genet, Boston, MA 02115 USA
[3] Harvard Med Sch, Dept Ophthalmol, Boston, MA 02115 USA
[4] Harvard Univ, Ctr Brain Sci, Cambridge, MA 02130 USA
[5] Harvard Univ, Dept Mol & Cellular Biol, Cambridge, MA 02130 USA
[6] Broad Inst Harvard & MIT, Stanley Ctr Psychiat Res, Cambridge, MA 02142 USA
[7] Broad Inst Harvard & MIT, Program Med & Populat Genet, Cambridge, MA 02142 USA
[8] Howard Hughes Med Inst, Chevy Chase, MD 20815 USA
[9] MIT, Dept Biol, Cambridge, MA 02139 USA
[10] MIT, Koch Inst, Cambridge, MA 02139 USA
关键词
RNA-SEQ; AMACRINE CELLS; EXPRESSION; PATHWAYS; PROTEIN; PARALLEL; GANGLION; IDENTIFICATION; HETEROGENEITY; LOCALIZATION;
D O I
10.1016/j.cell.2016.07.054
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Patterns of gene expression can be used to characterize and classify neuronal types. It is challenging, however, to generate taxonomies that fulfill the essential criteria of being comprehensive, harmonizing with conventional classification schemes, and lacking superfluous subdivisions of genuine types. To address these challenges, we used massively parallel single-cell RNA profiling and optimized computational methods on a heterogeneous class of neurons, mouse retinal bipolar cells (BCs). From a population of similar to 25,000 BCs, we derived a molecular classification that identified 15 types, including all types observed previously and two novel types, one of which has a non-canonical morphology and position. We validated the classification scheme and identified dozens of novel markers using methods that match molecular expression to cell morphology. This work provides a systematic methodology for achieving comprehensive molecular classification of neurons, identifies novel neuronal types, and uncovers transcriptional differences that distinguish types within a class.
引用
收藏
页码:1308 / +
页数:46
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