Cellular diversity and lineage trajectory: insights from mouse single cell transcriptomes

Abstract

Single cell RNA-sequencing (scRNA-seq) technology has matured to the point that it is possible to generate large single cell atlases of developing mouse embryos. These atlases allow the dissection of developmental cell lineages and molecular changes during embryogenesis. When coupled with single cell technologies for profiling the chromatin landscape, epigenome, proteome and metabolome, and spatial tissue organisation, these scRNA-seq approaches can now collect a large volume of multi-omic data about mouse embryogenesis. In addition, advances in computational techniques have enabled the inference of developmental lineages of differentiating cells, even without explicitly introduced genetic markers. This Spotlight discusses recent advent of single cell experimental and computational methods, and key insights from applying these methods to the study of mouse embryonic development. We highlight challenges in analysing and interpreting these data to complement and expand our knowledge from traditional developmental biology studies in relation to cell identity, diversity and lineage differentiation.