Deciphering cell-cell interactions and communication from gene expression

Cell-cell interactions orchestrate organismal development, homeostasis and single-cell functions. When cells do not properly interact or improperly decode molecular messages, disease ensues. Thus, the identification and quantification of intercellular signalling pathways has become a common analysis performed across diverse disciplines. The expansion of protein-protein interaction databases and recent advances in RNA sequencing technologies have enabled routine analyses of intercellular signalling from gene expression measurements of bulk and single-cell data sets. In particular, ligand-receptor pairs can be used to infer intercellular communication from the coordinated expression of their cognate genes. In this Review, we highlight discoveries enabled by analyses of cell-cell interactions from transcriptomic data and review the methods and tools used in this context. Cell-cell interactions and communication can be inferred from RNA sequencing data of, for example, ligand-receptor pairs. The authors review insights gained and the methods and tools used in studies of cell-cell interactions based on transcriptomic data.

Automated summary

Intercellular interactions and communication can be inferred from RNA sequencing data, such as ligand-receptor pairs, which has led to new insights and methodologies for studying cell-cell interactions.