The advent of high-throughput droplet-based single-cell RNA-seq (scRNA-seq) enables researchers to understand the full complexity of cellular diversity on a cell-by-cell basis. No longer limited by known cell-type markers or bulk RNA-seq analyses, our understanding of complex biological systems is being transformed. In a new publication in Nature Communications, Pal et al. use the Chromium™ Single Cell 3’ Gene Expression Solution to perform large scale single cell analysis of the developing mouse mammary gland. The researchers discovered that a distinct transcriptional switch occurs at the onset of puberty, rendering a relatively homogenous cellular population into a more diverse and heterogeneous landscape. The information gleaned from these single cell investigations allow for a more comprehensive understanding of the molecular regulatory networks driving mammary gland differentiation.
The mammary epithelium comprises two primary cellular lineages, but the degree of heterogeneity within these compartments and their lineage relationships during development remain an open question. Here we report single-cell RNA profiling of mouse mammary epithelial cells spanning four developmental stages in the post-natal gland. Notably, the epithelium undergoes a large-scale shift in gene expression from a relatively homogeneous basal-like program in pre-puberty to distinct lineage-restricted programs in puberty. Interrogation of single-cell transcriptomes reveals different levels of diversity within the luminal and basal compartments, and identifies an early progenitor subset marked by CD55. Moreover, we uncover a luminal transit population and a rare mixed-lineage cluster amongst basal cells in the adult mammary gland. Together these findings point to a developmental hierarchy in which a basal-like gene expression program prevails in the early post-natal gland prior to the specification of distinct lineage signatures, and the presence of cellular intermediates that may serve as transit or lineage-primed cells.
Read the full article in Nature Communications.
Single-cell analysis resources