用分池条形码对成长中的小鼠大脑和脊髓进行单细胞分析
Alexander B Rosenberg1, Charles M Roco2, Richard A Muscat3
1Department of Electrical Engineering, University of Washington, Seattle, WA, USA. alex.b.rosenberg@gmail.com gseelig@uw.edu.
概括
我们开发了基于分组结合的转录组测序 (SPLiT-seq) 来进行可扩展的单细胞RNA测序. 这种方法在发育中的小鼠大脑和脊髓中发现了100多种细胞类型.
科学领域:
- 分子生物学
- 基因组学
- 神经科学
背景情况:
- 单细胞RNA测序 (scRNA-seq) 对于理解复杂的生物系统至关重要.
- 现有的scRNA-seq方法在可扩展性和与固定样本的兼容性方面面临挑战.
研究的目的:
- 开发一种可扩展和多用途的scRNA-seq方法来进行全面的细胞分析.
- 在单细胞分辨率下分析发育中的小鼠中枢神经系统的转录组.
主要方法:
- 使用组合条形编码开发基于分组结合的转录组序列 (SPLiT-seq).
- 应用SPLiT-seq来分析156,049个单核转录组,这些转录组来自出生后的小鼠大脑和脊髓.
- 使用伪时间分析来调查发育轨迹.
主要成果:
- 根据基因表达模式识别了100多种不同的细胞类型.
- 通过功能,区域特异性和分化阶段来表征细胞类型.
- 揭示了转录程序驱动四个主要的发育系在早产后小鼠中枢神经系统.
结论:
- SPLiT-seq可实现可扩展和高效的单细胞转录基因分析.
- 提供早期出生后中枢神经系统发育的详细快照.
- 提供其他复杂多细胞系统的综合分析方法.
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