Single-cell RNA sequencing for the study of development, physiology and disease

Abstract

An ongoing technological revolution is continually improving our ability to carry out very high-resolution studies of gene expression patterns. Current technology enables the global gene expression profiles of single cells to be defined, facilitating dissection of heterogeneity in cell populations that was previously hidden. In contrast to gene expression studies that use bulk RNA samples and provide only a virtual average of the diverse constituent cells, single-cell studies enable the molecular distinction of all cell types within a complex population mix, such as a tumour or developing organ. For instance, single-cell gene expression profiling has contributed to improved understanding of how histologically identical, adjacent cells make different differentiation decisions during development. Beyond development, single-cell gene expression studies have enabled the characteristics of previously known cell types to be more fully defined and facilitated the identification of novel categories of cells, contributing to improvements in our understanding of both normal and disease-related physiological processes and leading to the identification of new treatment approaches. Although limitations remain to be overcome, technology for the analysis of single-cell gene expression patterns is improving rapidly and beginning to provide a detailed atlas of the gene expression patterns of all cell types in the human body.

Key points

  • RNA sequencing of single cells (scRNA-seq) enables the global gene expression patterns of individual cells to be defined.

  • Almost all tissues and organs include a heterogeneous mix of cell types; the heterogeneity of these cell populations can be defined through the use of scRNA-seq.

  • scRNA-seq can fully define the expression of transcription factors, growth factors, receptors, solute transporters and other proteins for each cell type present, providing insights into cell function and cell–cell crosstalk.

  • scRNA-seq is an increasingly powerful tool for the analysis of development as well as normal and disease processes.

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Fig. 1: General strategy for scRNA-seq.
Fig. 2: Microdroplet-based scRNA-seq.
Fig. 3: Creation of a single-cell-resolution virtual organ.
Fig. 4: Use of cluster and combine methodology to define cell types.
Fig. 5: Use of cluster and subcluster methodology to define cell subtypes.
Fig. 6: Multilineage priming.

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Nature Reviews Nephrology thanks L. Oxburgh, K. Kiryluk and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Correspondence to S. Steven Potter.

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Related links

Chan Zuckerberg Initiative Atlas Project: https://www.chanzuckerberg.com/human-cell-atlas

Human BioMolecular Atlas Program: https://commonfund.nih.gov/hubmap

LGEA (Lung Gene Expression Analysis) Web Portal: https://research.cchmc.org/pbge/lunggens/mainportal.html

lungMAP consortium: https://www.lungmap.net/

Glossary

Splicing patterns

Sequences recognized by RNA-processing enzymes of the spliceosome, which splice out introns. Introns almost always begin with the bases GU and terminate with AG, but additional sequences around splice sites are required to provide sufficient specificity.

Early response genes

Genes that are activated rapidly in response to a variety of stimuli, including stress and growth factors. About 40 immediate early response genes exist, including members of the FOS and JUN families.

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Potter, S.S. Single-cell RNA sequencing for the study of development, physiology and disease. Nat Rev Nephrol 14, 479–492 (2018). https://doi.org/10.1038/s41581-018-0021-7

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