Abstract

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.

Keywords

Multicellular organismCellBiologyComputational biologyTranscriptomeSingle-cell analysisWorkflowCell biologyComputer scienceGeneticsGeneGene expression

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Publication Info

Year
2020
Type
review
Volume
11
Issue
12
Pages
866-880
Citations
168
Access
Closed

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Xin Shao, Xiaoyan Lu, Jie Liao et al. (2020). New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data. Protein & Cell , 11 (12) , 866-880. https://doi.org/10.1007/s13238-020-00727-5

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DOI
10.1007/s13238-020-00727-5