Abstract
Dedicated stem cells ensure postnatal growth, repair and homeostasis of skeletal muscle. Following injury, muscle stem cells (MuSCs) exit from quiescence and divide to reconstitute the stem cell pool and give rise to muscle progenitors. The transcriptomes of pooled MuSCs have provided a rich source of information for describing the genetic programs of distinct static cell states; however, bulk microarray and RNA sequencing provide only averaged gene expression profiles, blurring the heterogeneity and developmental dynamics of asynchronous MuSC populations. Instead, the granularity required to identify distinct cell types, states, and their dynamics can be afforded by single cell analysis. We were able to compare the transcriptomes of thousands of MuSCs and primary myoblasts isolated from homeostatic or regenerating muscles by single cell RNA sequencing. Using computational approaches, we could reconstruct dynamic trajectories and place, in a pseudotemporal manner, the transcriptomes of individual MuSC within these trajectories. This approach allowed for the identification of distinct clusters of MuSCs and primary myoblasts with partially overlapping but distinct transcriptional signatures, as well as the description of metabolic pathways associated with defined MuSC states.