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

  • Longqi Liu
  • , Chuanyu Liu
  • , Andrés Quintero
  • , Liang Wu
  • , Yue Yuan
  • , Mingyue Wang
  • , Mengnan Cheng
  • , Lizhi Leng
  • , Liqin Xu
  • , Guoyi Dong
  • , Rui Li
  • , Yang Liu
  • , Xiaoyu Wei
  • , Jiangshan Xu
  • , Xiaowei Chen
  • , Haorong Lu
  • , Dongsheng Chen
  • , Quanlei Wang
  • , Qing Zhou
  • , Xinxin Lin
  • Guibo Li, Shiping Liu, Qi Wang, Hongru Wang, J. Lynn Fink, Zhengliang Gao, Xin Liu, Yong Hou, Shida Zhu, Huanming Yang, Yunming Ye, Ge Lin, Fang Chen, Carl Herrmann, Roland Eils, Zhouchun Shang, Xun Xu
  • BGI-Shenzhen
  • Harbin Institute of Technology Shenzhen
  • University of Chinese Academy of Sciences
  • German Cancer Research Center
  • Heidelberg University 
  • Central South University
  • Ministry of Health of People's Republic of China
  • CAS - Institute of Vertebrate Paleontology and Paleoanthropology
  • Tongji University
  • Zhejiang University
  • National Engineering and Research Center of Human Stem Cell
  • University of Copenhagen
  • Berlin Institute of Health and Charitè - Universitätsmedizin Berlin
  • Chinese Academy of Sciences

科研成果: 期刊稿件文章同行评审

202 引用 (Scopus)

摘要

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.

源语言英语
文章编号470
期刊Nature Communications
10
1
DOI
出版状态已出版 - 1 12月 2019
已对外发布

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