New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data.
10.1007/s13238-020-00727-5
- Author:
Xin SHAO
1
;
Xiaoyan LU
1
;
Jie LIAO
1
;
Huajun CHEN
2
;
Xiaohui FAN
3
Author Information
1. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
2. College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China.
3. College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China. fanxh@zju.edu.cn.
- Publication Type:Review
- Keywords:
cell-cell communication;
chemical signal-dependent communication;
ligand-receptor interaction;
network biology;
physical contact-dependent communication;
single-cell RNA sequencing
- MeSH:
Animals;
Cell Communication;
Humans;
RNA-Seq;
Single-Cell Analysis;
Transcriptome
- From:
Protein & Cell
2020;11(12):866-880
- CountryChina
- Language:English
-
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.
