New avenues for systematically inferring cellcell communication: through single-cell transcriptomics data
Received date: 04 Feb 2020
Accepted date: 12 Apr 2020
Published date: 15 Dec 2020
Copyright
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.
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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