Single-Cell Transcriptomes Distinguish Stem Cell State Changes and Lineage Specification Programs in Early Mammary Gland Development

Rajshekhar R. Giraddi; Chi-Yeh Chung; Richard E. Heinz; Ozlen Balcioglu; Mark Novotny; Christy L. Trejo; Christopher Dravis; Berhane M. Hagos; Elnaz Mirzaei Mehrabad; Luo Wei Rodewald; Jae Y. Hwang; Cheng Fan; Roger Lasken; Katherine E. Varley; Charles M. Perou; Geoffrey M. Wahl; Benjamin T. Spike

Single-Cell Transcriptomes Distinguish Stem Cell State Changes and Lineage Specification Programs in Early Mammary Gland Development

2018

Summary: The mammary gland consists of cells with gene expression patterns reflecting their cellular origins, function, and spatiotemporal context. However, knowledge of developmental kinetics and mechanisms of lineage specification is lacking. We address this significant knowledge gap by generating a single-cell transcriptome atlas encompassing embryonic, postnatal, and adult mouse mammary development. From these data, we map the chronology of transcriptionally and epigenetically distinct cell states and distinguish fetal mammary stem cells (fMaSCs) from their precursors and progeny. fMaSCs show balanced co-expression of factors associated with discrete adult lineages and a metabolic gene signature that subsides during maturation but reemerges in some human breast cancers and metastases. These data provide a useful resource for illuminating mammary cell heterogeneity, the kinetics of differentiation, and developmental correlates of tumorigenesis. : Single-cell RNA sequencing of developing mouse mammary epithelia reveals the timing of lineage specification. Giraddi et al. find that fetal mammary stem cells co-express factors that define distinct lineages in their progeny and bear functionally relevant metabolic program signatures that change with differentiation and are resurrected in human breast cancers and metastases. Keywords: mammary gland development, stem cells, epithelial lineage specification, single-cell RNA sequencing, cell states, cell fates, heterogeneity

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