Transcriptional profiling reveals extraordinary diversity among skeletal muscle tissues
Abstract
Skeletal muscle comprises a family of diverse tissues with highly specialized functions. Many acquired diseases, including HIV and COPD, affect specific muscles while sparing others. Even monogenic muscular dystrophies selectively affect certain muscle groups. These observations suggest that factors intrinsic to muscle tissues influence their resistance to disease. Nevertheless, most studies have not addressed transcriptional diversity among skeletal muscles. Here we use RNAseq to profile mRNA expression in skeletal, smooth, and cardiac muscle tissues from mice and rats. Our data set, MuscleDB, reveals extensive transcriptional diversity, with greater than 50% of transcripts differentially expressed among skeletal muscle tissues. We detect mRNA expression of hundreds of putative myokines that may underlie the endocrine functions of skeletal muscle. We identify candidate genes that may drive tissue specialization, including Smarca4, Vegfa, and Myostatin. By demonstrating the intrinsic diversity of skeletal muscles, these data provide a resource for studying the mechanisms of tissue specialization.
Data availability
RNA Sequencing data have been deposited in GEO under accession code GSE100505. Analyzed data are available on http://muscledb.org.
Article and author information
Author details
Funding
National Institute of Arthritis and Musculoskeletal and Skin Diseases (AR069266)
- Karyn A Esser
- Michael E Hughes
National Institute of Arthritis and Musculoskeletal and Skin Diseases (AR066082)
- Karyn A Esser
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All animal procedures were conducted in compliance with the guidelines of the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC) and were approved by the Institutional Animal Care and Use Committee at University of Kentucky (IACUC assurance number: A-3336-01).
Reviewing Editor
- Andrew Brack, University of California, San Francisco, United States
Publication history
- Received: December 22, 2017
- Accepted: May 15, 2018
- Accepted Manuscript published: May 29, 2018 (version 1)
- Version of Record published: June 19, 2018 (version 2)
Copyright
© 2018, Terry et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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