Differentiation dynamics of mammary epithelial cells revealed by single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-seq) is widely used to profile the transcriptome of individual cells. This provides biological resolution that cannot be matched by bulk RNA sequencing, at the cost of increased technical noise and data complexity. The differences between scRNA-seq and bulk RNA-seq data mean that the analysis of the former cannot be performed by recycling bioinformatics pipelines for the latter. Rather, dedicated single-cell methods are required at various steps to exploit the cellular resolution while accounting for technical noise. This article describes a computational workflow for low-level analyses of scRNA-seq data, based primarily on software packages from the open-source Bioconductor project. It covers basic steps including quality control, data exploration and normalization, as well as more complex procedures such as cell cycle phase assignment, identification of highly variable and correlated genes, clustering into subpopulations and marker gene detection. Analyses were demonstrated on gene-level count data from several publicly available datasets involving haematopoietic stem cells, brain-derived cells, T-helper cells and mouse embryonic stem cells. This will provide a range of usage scenarios from which readers can construct their own analysis pipelines.

Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in cell populations. Analyzing such high-dimensional single-cell data has its own statistical and computational challenges. Popular multivariate approaches are based on data normalization, followed by dimension reduction and clustering to identify subgroups. However, in the case of cellular differentiation, we would not expect clear clusters to be present but instead expect the cells to follow continuous branching lineages.

The transcription factor Gata-3 is a defining marker of the 'luminal' subtypes of breast cancer. To gain insight into the role of Gata-3 in breast epithelial development and oncogenesis, we have explored its normal function within the mammary gland by conditionally deleting Gata-3 at different stages of development. We report that Gata-3 has essential roles in the morphogenesis of the mammary gland in both the embryo and adult. Through the discovery of a novel marker (beta3-integrin) of luminal progenitor cells and their purification, we demonstrate that Gata-3 deficiency leads to an expansion of luminal progenitors and a concomitant block in differentiation. Remarkably, introduction of Gata-3 into a stem cell-enriched population induced maturation along the alveolar luminal lineage. These studies provide evidence for the existence of an epithelial hierarchy within the mammary gland and establish Gata-3 as a critical regulator of luminal differentiation.