Using single‐cell genomics to understand developmental processes and cell fate decisions

Abstract

High-throughput-omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision making is inherently a unicellular process to which "bulk"-omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single-cell methods bridge this gap, allowing high-throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single-cell gene expression data and highlight areas of developmental biology where single-cell techniques have made important contributions. These include understanding of cell-to-cell heterogeneity, the tracing of differentiation pathways, quan-tification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis.