Single-cell sequencing is poised to elucidate how cells contribute to tissue function.
Single-cell sequencing has cracked open the problem of tissue heterogeneity and enabled the study of new cell types and rare cell populations. Novel applications and analytical tools are now putting emphasis on inferring the functional roles of cells in tissues and developmental events, as well as the genetic programs that drive them.
Transcriptional similarity is widely used to categorize individual cells within a tissue. The same data can also provide functional insight into cell states. Researchers are increasingly using single-cell data to identify cell-type-specific markers and then label and map these cell types back in the intact tissue. For example, one study identified many rare cell types in the gut that likely function in secretion (Nature 525, 251–255, 2015), while another combined unbiased single-cell RNA-seq with imaging of the mouse sympathetic ganglion to reveal specific neuronal populations that innervate the muscles behind goosebumps and nipple erection (Nat. Neurosci. 19, 1331–1340, 2016).
Computational approaches are also being developed to infer the gene-regulatory changes that drive differences in cell state. Pseudotime inference can place single cells along reconstructed developmental trajectories, making it possible to pick out the cells involved in developmental transitions. Better methods are needed to extract the gene regulatory changes that drive these transitions and cellular decisions. To understand transitions in the blood cell differentiation cascade, one approach profiled single-cell gene expression from mixtures of blood cells at different states and generated a dynamic model of the underlying transcription factor regulatory networks (Nat. Biotechnol. 33, 269–276, 2015). Time-course experiments will be more feasible as single-cell sequencing becomes less expensive and more accessible, and the added dimension should help researchers to glean which changes are causal with respect to cell state.
Perturbation experiments are also promising routes to finding function. Combining the CRISPR editing system with single-cell studies will be a powerful way to screen for the effect of gene knockouts on single-cell transcription and cellular phenotypes. Now that single-cell RNA sequencing has become routine at large scales, we look forward to experimental and analytical developments that shed light on cellular functions.