单细胞分析发育中的鼠脑和脊髓的分裂池条形码技术。
Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding.
机构信息
Department of Electrical Engineering, University of Washington, Seattle, WA, USA.
Department of Bioengineering, University of Washington, Seattle, WA, USA.
出版信息
Science. 2018 Apr 13;360(6385):176-182. doi: 10.1126/science.aam8999. Epub 2018 Mar 15.
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.
为了实现单细胞的可扩展分析，我们开发了基于分割池连接的转录组测序（SPLiT-seq），这是一种单细胞 RNA 测序（scRNA-seq）方法，通过组合条形码对 RNA 的细胞来源进行标记。SPLiT-seq 与固定细胞或细胞核兼容，允许高效的样本多路复用，并且不需要定制设备。我们使用 SPLiT-seq 分析了来自出生后第 2 天和第 11 天的小鼠大脑和脊髓的 156049 个单核转录组。鉴定出了 100 多种细胞类型，其基因表达模式与细胞功能、区域特异性和分化阶段相对应。拟时分析揭示了驱动四个发育谱系的转录程序，提供了对小鼠中枢神经系统早期出生后发育的快照。SPLiT-seq 为全面的单细胞转录组分析其他类似复杂的多细胞系统提供了一种途径。
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