Advances in single-cell RNA sequencing (scRNA-seq) have allowed for comprehensive analysis of the immune system. Here, researchers from New York University describe the available scRNA-seq technologies together with their corresponding strengths and weaknesses. They discuss in depth how scRNA-seq can be used to deconvolve immune system heterogeneity by identifying novel distinct immune cell subsets in health and disease, characterizing stochastic heterogeneity within a cell population and building developmental ‘trajectories’ for immune cells. Finally, they discuss future directions of the field and present integrated approaches to complement molecular information from a single cell with studies of the environment, epigenetic state and cell lineage.
Characterizing heterogeneity within one immune cell population using scRNA-seq
a | Bone marrow-derived dendritic cells (BMDCs) respond to infections and help the immune system recruit other cell types to combat these infections and stop them from spreading. Lipopolysaccharide (LPS) stimulation is used as a technique to mimic infections in vivo. Single-cell RNA sequencing (scRNA-seq) analysis of LPS-stimulated BMDCs revealed variation in antiviral gene expression and mRNA splicing patterns of single BMDCs. Upon stimulation, BMDCs have bimodal expression of the antiviral master regulator genes Irf7 and Stat2, which in turn promotes the bimodal expression of many other antiviral genes. b | Medullary thymic epithelial cells (mTECs) stochastically express tissue-specific self-antigens (tissue-restricted antigens, TRAs) to mediate immune system self-tolerance. Single-cell analysis of mTECs revealed distinct TRA expression patterns. In addition, it allowed for the identification of distinct autoimmune regulator (AIRE)-dependent gene expression patterns in mTEC subpopulations. This variability in AIRE-dependent genes and TRA expression patterns might be the mechanism by which mTECs achieve self-tolerance to multiple tissues.