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Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex

机译:低覆盖率单细胞mRNA测序揭示了发育中的大脑皮层中的细胞异质性和激活的信号通路

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摘要

Large-scale surveys of single-cell gene expression have the potential to reveal rare cell populations and lineage relationships, but require efficient methods for cell capture and mRNA sequencing. Although cellular barcoding strategies allow parallel sequencing of single cells at ultra-low depths, the limitations of shallow sequencing have not been directly investigated. By capturing 301 single cells from 11 populations using microfluidics and analyzing single-cell transcriptomes across downsampled sequencing depths, we demonstrate that shallow single-cell mRNA sequencing (~50,000 reads per cell) is sufficient for unbiased cell-type classification and biomarker identification. In developing cortex we identify diverse cell types including multiple progenitor and neuronal subtypes, and we identify EGR1 and FOS as previously unreported candidate targets of Notch signaling in human but not mouse radial glia. Our strategy establishes an efficient method for unbiased analysis and comparison of cell populations from heterogeneous tissue by microfluidic single-cell capture and low-coverage sequencing of many cells.
机译:单细胞基因表达的大规模调查有可能揭示稀有细胞群和谱系关系,但需要有效的方法进行细胞捕获和mRNA测序。尽管细胞条形码策略允许在超低深度对单个细胞进行平行测序 ,但尚未直接研究浅测序的局限性。通过使用微流控技术从11个种群中捕获301个单细胞并在向下采样的测序深度范围内分析单细胞转录组,我们证明了浅单细胞mRNA测序(每个细胞约50,000个读数)足以进行无偏见的细胞类型分类和生物标记物识别。在发育中的皮层中,我们确定了多种细胞类型,包括多种祖细胞和神经元亚型,并且我们确定了EGR1和FOS作为人类Notch信号传导的先前未报道的候选靶标,但不是小鼠radial神经胶质。我们的策略建立了一种有效的方法,可通过微流控单细胞捕获和许多细胞的低覆盖率测序来对来自异质组织的细胞群体进行无偏分析和比较。

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