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

Author

Listed:
  • Longqi Liu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    Xili University Town)

  • Chuanyu Liu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Andrés Quintero

    (German Cancer Research Center (DKFZ)
    Heidelberg University Hospital)

  • Liang Wu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Yue Yuan

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Mingyue Wang

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Mengnan Cheng

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Lizhi Leng

    (Central South University
    Ministry of Health)

  • Liqin Xu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Guoyi Dong

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Rui Li

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    Xili University Town)

  • Yang Liu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Xiaoyu Wei

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Jiangshan Xu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Xiaowei Chen

    (China National GeneBank, BGI-Shenzhen)

  • Haorong Lu

    (China National GeneBank, BGI-Shenzhen)

  • Dongsheng Chen

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Quanlei Wang

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Chinese Academy of Sciences)

  • Qing Zhou

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Xinxin Lin

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Guibo Li

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Shiping Liu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Qi Wang

    (German Cancer Research Center (DKFZ))

  • Hongru Wang

    (Chinese Academy of Sciences)

  • J. Lynn Fink

    (BGI-Shenzhen)

  • Zhengliang Gao

    (Tongji University School of Medicine)

  • Xin Liu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Yong Hou

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Shida Zhu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen)

  • Huanming Yang

    (BGI-Shenzhen
    James D. Watson Institute of Genome Sciences)

  • Yunming Ye

    (Xili University Town)

  • Ge Lin

    (Central South University
    Ministry of Health
    National Engineering and Research Center of Human Stem Cell)

  • Fang Chen

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    University of Copenhagen)

  • Carl Herrmann

    (German Cancer Research Center (DKFZ)
    Heidelberg University Hospital)

  • Roland Eils

    (Heidelberg University Hospital
    Berlin Institute of Health and Charité)

  • Zhouchun Shang

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    Tongji University School of Medicine)

  • Xun Xu

    (BGI-Shenzhen
    China National GeneBank, BGI-Shenzhen
    Chinese Academy of Sciences)

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.

Suggested Citation

  • 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 & Ha, 2019. "Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-08205-7
    DOI: 10.1038/s41467-018-08205-7
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    Cited by:

    1. Yichuan Cao & Xiamiao Zhao & Songming Tang & Qun Jiang & Sijie Li & Siyu Li & Shengquan Chen, 2024. "scButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Geert-Jan Huizing & Ina Maria Deutschmann & Gabriel Peyré & Laura Cantini, 2023. "Paired single-cell multi-omics data integration with Mowgli," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Jules Samaran & Gabriel Peyré & Laura Cantini, 2024. "scConfluence: single-cell diagonal integration with regularized Inverse Optimal Transport on weakly connected features," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    4. Kai Cao & Qiyu Gong & Yiguang Hong & Lin Wan, 2022. "A unified computational framework for single-cell data integration with optimal transport," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    5. Fangfang Yan & Akiko Suzuki & Chihiro Iwaya & Guangsheng Pei & Xian Chen & Hiroki Yoshioka & Meifang Yu & Lukas M. Simon & Junichi Iwata & Zhongming Zhao, 2024. "Single-cell multiomics decodes regulatory programs for mouse secondary palate development," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    6. Akshaya Ramakrishnan & Aikaterini Symeonidi & Patrick Hanel & Katharina T. Schmid & Maria L. Richter & Michael Schubert & Maria Colomé-Tatché, 2023. "epiAneufinder identifies copy number alterations from single-cell ATAC-seq data," Nature Communications, Nature, vol. 14(1), pages 1-10, December.

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