Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding

被引：886

作者：

Rosenberg, Alexander B. ^{[1
]}

Roco, Charles M. ^{[2
]}

Muscat, Richard A. ^{[1
]}

Kuchina, Anna ^{[1
]}

Sample, Paul ^{[1
]}

Yao, Zizhen ^{[3
]}

Graybuck, Lucas T. ^{[3
]}

Peeler, David J. ^{[2
]}

Mukherjee, Sumit ^{[1
]}

Chen, Wei ^{[4
]}

Pun, Suzie H. ^{[2
]}

Sellers, Drew L. ^{[2
,5
]}

Tasic, Bosiljka ^{[3
]}

Seelig, Georg ^{[1
,4
,6
]}

机构：

[1] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA

[2] Univ Washington, Dept Bioengn, Seattle, WA 98195 USA

[3] Allen Inst Brain Sci, Seattle, WA USA

[4] Univ Washington, Mol Engn & Sci Inst, Seattle, WA 98195 USA

[5] Inst Stem Cell & Regenerat Med, Seattle, WA USA

[6] Univ Washington, Paul G Allen Sch Comp Sci & Engn, Seattle, WA 98195 USA

来源：

SCIENCE | 2018年 / 360卷 / 6385期

基金：

美国国家卫生研究院;

关键词：

RNA-SEQ; CEREBELLAR CORTEX; MOTOR-NEURONS; EXPRESSION; TRANSCRIPTOMICS; HIPPOCAMPUS; DIVERSITY; INTERNEURONS; PRECURSORS; SUBTYPES;

D O I：

10.1126/science.aam8999

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

To facilitate scalable profiling of single cells, we developed split-pool ligation-based transcriptome sequencing (SPLiT-seq), a single-cell RNA-seq (scRNA-seq) method that labels the cellular origin of RNA through combinatorial barcoding. SPLiT-seq is compatible with fixed cells or nuclei, allows efficient sample multiplexing, and requires no customized equipment. We used SPLiT-seq to analyze 156,049 single-nucleus transcriptomes from postnatal day 2 and 11 mouse brains and spinal cords. More than 100 cell types were identified, with gene expression patterns corresponding to cellular function, regional specificity, and stage of differentiation. Pseudotime analysis revealed transcriptional programs driving four developmental lineages, providing a snapshot of early postnatal development in the murine central nervous system. SPLiT-seq provides a path toward comprehensive single-cell transcriptomic analysis of other similarly complex multicellular systems.

引用

页码：176 / +

页数：7

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