Abstract
Skeletal muscle is composed of post-mitotic myofibers that form a syncytium containing hundreds of myonuclei. Using a progressive exercise training model in the mouse and single nucleus RNA-sequencing (snRNA-seq) for high-resolution characterization of myonuclear transcription, we show myonuclear functional specialization in muscle. After 4 weeks of exercise training, snRNA-seq reveals that resident muscle stem cells, or satellite cells, are activated with acute exercise but demonstrate limited lineage progression while contributing to muscle adaptation. In the absence of satellite cells, a portion of nuclei demonstrates divergent transcriptional dynamics associated with mixed-fate identities compared with satellite cell replete muscles. These data provide a compendium of information about how satellite cells influence myonuclear transcription in response to exercise.
| Original language | English |
|---|---|
| Article number | 102838 |
| Journal | iScience |
| Volume | 24 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 20 2021 |
Bibliographical note
Funding Information:The authors thank Dr. Eric T. Wang and Lance Denes at the University of Florida for sequencing expertise, Jennifer Strange of the University of Kentucky Flow Cytometry Core and Dr. Doug Harrison of the University of Kentucky Biology Department/Genetics and Genomics Imaging Center for their technical expertise with fluorescent activated cell sorting and single cell RNA sequencing, respectively. Partial computational support was provided by The University of Kentucky High Performance Computing complex. This work was supported by NIH grants from the National Institutes of Arthritis and Musculoskeletal and Skin Diseases ( AR060701 to C.A.P. and J.J.M., AR071753 to K.A.M, and AR075364 to D.A.E.) and National Institute on Aging ( AG049086 to C.A.P. and J.J.M. and AG063994 to K.A.M). The graphical abstract was generated using BioRender.
Funding Information:
The authors thank Dr. Eric T. Wang and Lance Denes at the University of Florida for sequencing expertise, Jennifer Strange of the University of Kentucky Flow Cytometry Core and Dr. Doug Harrison of the University of Kentucky Biology Department/Genetics and Genomics Imaging Center for their technical expertise with fluorescent activated cell sorting and single cell RNA sequencing, respectively. Partial computational support was provided by The University of Kentucky High Performance Computing complex. This work was supported by NIH grants from the National Institutes of Arthritis and Musculoskeletal and Skin Diseases (AR060701 to C.A.P. and J.J.M. AR071753 to K.A.M, and AR075364 to D.A.E.) and National Institute on Aging (AG049086 to C.A.P. and J.J.M. and AG063994 to K.A.M). The graphical abstract was generated using BioRender. Y.W. D.A.E. J.J.M. and C.A.P. conceived the project and designed study approach. Y.W. performed the transcriptomic and computational analysis. D.A.E. and K.A.M. oversaw mouse experimentation. D.A.E. B.D.P. and K.A.M. performed nuclear isolation and processed samples for snRNA-seq. J.J.M. and C.A.P. supervised and coordinated all aspects of the study, computational analysis, and manuscript writing. The manuscript was written by Y.W. with input from D.A.E. and K.A.M. Figures were created by Y.W. and K.A.M. All authors have critically revised the manuscript. The authors declare no competing interests.
Publisher Copyright:
© 2021 The Authors
Keywords
- Biological sciences
- Stem cells research
- Transcriptomics
ASJC Scopus subject areas
- General