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单细胞多组学图谱解析揭示调控异质性。

Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity.

机构信息

BGI-Shenzhen, Shenzhen, 518083, China.

China National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China.

出版信息

Nat Commun. 2019 Jan 28;10(1):470. doi: 10.1038/s41467-018-08205-7.

DOI:10.1038/s41467-018-08205-7
PMID:30692544
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6349937/
Abstract

Integrative analysis of multi-omics layers at single cell level is critical for accurate dissection of cell-to-cell variation within certain cell populations. Here we report scCAT-seq, a technique for simultaneously assaying chromatin accessibility and the transcriptome within the same single cell. We show that the combined single cell signatures enable accurate construction of regulatory relationships between cis-regulatory elements and the target genes at single-cell resolution, providing a new dimension of features that helps direct discovery of regulatory patterns specific to distinct cell identities. Moreover, we generate the first single cell integrated map of chromatin accessibility and transcriptome in early embryos and demonstrate the robustness of scCAT-seq in the precise dissection of master transcription factors in cells of distinct states. The ability to obtain these two layers of omics data will help provide more accurate definitions of "single cell state" and enable the deconvolution of regulatory heterogeneity from complex cell populations.

摘要

单细胞水平多组学层面的综合分析对于准确解析特定细胞群体内的细胞间变异性至关重要。在这里,我们报告了 scCAT-seq 技术,该技术可在同一单细胞内同时检测染色质可及性和转录组。我们表明,组合单细胞特征可准确构建顺式调控元件与单细胞分辨率下靶基因之间的调控关系,提供有助于直接发现特定细胞身份特有的调控模式的新特征维度。此外,我们生成了早期胚胎中染色质可及性和转录组的第一个单细胞综合图谱,并证明了 scCAT-seq 在精确解析不同状态细胞中的主转录因子方面的稳健性。获得这两层组学数据的能力将有助于更准确地定义“单细胞状态”,并能够从复杂的细胞群体中推断出调控异质性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a77f/6349937/68850fc9ec3d/41467_2018_8205_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a77f/6349937/92580bb966c1/41467_2018_8205_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a77f/6349937/db86078971b3/41467_2018_8205_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a77f/6349937/68850fc9ec3d/41467_2018_8205_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a77f/6349937/92580bb966c1/41467_2018_8205_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a77f/6349937/db86078971b3/41467_2018_8205_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a77f/6349937/68850fc9ec3d/41467_2018_8205_Fig3_HTML.jpg

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