Single cell transcriptome analysis of muscle satellite cells reveals widespread transcriptional heterogeneity

Dong Seong Cho, Jason D. Doles

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


Tissue specific stem cells are indispensable contributors to adult tissue maintenance, repair, and regeneration. In skeletal muscle, satellite cells (SCs) are the resident muscle stem cell population and are required to maintain skeletal muscle homeostasis throughout life. Increasing evidence suggests that SCs are a heterogeneous cell population with substantial biochemical and functional diversity. A major limitation in the field is an incomplete understanding of the nature and extent of this cellular heterogeneity. Single cell analyses are well suited to addressing this issue, especially when coupled to unbiased profiling paradigms such as high throughout RNA sequencing. We performed single cell RNA sequencing (scRNA-seq) on freshly isolated muscle satellite cells and found a surprising degree of heterogeneity at multiple levels, from muscle-specific transcripts to the broader SC transcriptome. We leveraged several comparative bioinformatics techniques and found that individual SCs enrich for unique transcript clusters. We propose that these gene expression “fingerprints” may contribute to observed functional SC diversity. Overall, these studies underscore the importance of several established SC signaling pathways/processes on a single cell level, implicate novel regulators of SC heterogeneity, and lay the groundwork for further investigation into SC heterogeneity in health and disease.

Original languageEnglish (US)
Pages (from-to)54-63
Number of pages10
StatePublished - Dec 15 2017


  • Heterogeneity
  • Muscle stem cell
  • Satellite cell
  • Single cell
  • Transcriptome
  • scRNA-seq

ASJC Scopus subject areas

  • Genetics


Dive into the research topics of 'Single cell transcriptome analysis of muscle satellite cells reveals widespread transcriptional heterogeneity'. Together they form a unique fingerprint.

Cite this