REVIEW

New avenues for systematically inferring cellcell communication: through single-cell transcriptomics data

  • Xin Shao 1 ,
  • Xiaoyan Lu 1 ,
  • Jie Liao 1 ,
  • Huajun Chen 2,3 ,
  • Xiaohui Fan , 1,4
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  • 1. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
  • 2. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
  • 3. The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
  • 4. The Save Sight Institute, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2000, Australia

Received date: 04 Feb 2020

Accepted date: 12 Apr 2020

Published date: 15 Dec 2020

Copyright

2020 The Author(s) 2020

Abstract

For multicellular organisms, cell-cell communication is essential to numerous biological processes. Drawing upon the latest development of single-cell RNA-sequencing (scRNA-seq), high-resolution transcriptomic data have deepened our understanding of cellular phenotype heterogeneity and composition of complex tissues, which enables systematic cell-cell communication studies at a single-cell level. We first summarize a common workflow of cell-cell communication study using scRNA-seq data, which often includes data preparation, construction of communication networks, and result validation. Two common strategies taken to uncover cell-cell communications are reviewed, e.g., physically vicinal structure-based and ligand-receptor interaction-based one. To conclude, challenges and current applications of cell-cell communication studies at a single-cell resolution are discussed in details and future perspectives are proposed.

Cite this article

Xin Shao , Xiaoyan Lu , Jie Liao , Huajun Chen , Xiaohui Fan . New avenues for systematically inferring cellcell communication: through single-cell transcriptomics data[J]. Protein & Cell, 2020 , 11(12) : 866 -880 . DOI: 10.1007/s13238-020-00727-5

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