Molecular Transducers of Human Skeletal Muscle Remodeling under Different Loading States

Tanner Stokes, James A. Timmons, Hannah Crossland, Thomas R. Tripp, Kevin Murphy, Chris McGlory, Cameron J. Mitchell, Sara Y. Oikawa, Robert W. Morton, Bethan E. Phillips, Steven K. Baker, Phillip J. Atherton, Claes Wahlestedt, Stuart M. Phillips

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Loading of skeletal muscle changes the tissue phenotype reflecting altered metabolic and functional demands. In humans, heterogeneous adaptation to loading complicates the identification of the underpinning molecular regulators. A within-person differential loading and analysis strategy reduces heterogeneity for changes in muscle mass by ∼40% and uses a genome-wide transcriptome method that models each mRNA from coding exons and 3′ and 5′ untranslated regions (UTRs). Our strategy detects ∼3–4 times more regulated genes than similarly sized studies, including substantial UTR-selective regulation undetected by other methods. We discover a core of 141 genes correlated to muscle growth, which we validate from newly analyzed independent samples (n = 100). Further validating these identified genes via RNAi in primary muscle cells, we demonstrate that members of the core genes were regulators of protein synthesis. Using proteome-constrained networks and pathway analysis reveals notable relationships with the molecular characteristics of human muscle aging and insulin sensitivity, as well as potential drug therapies.

Original languageEnglish (US)
Article number107980
JournalCell Reports
Issue number5
StatePublished - Aug 4 2020


  • atrophy
  • growth
  • human
  • hypertrophy
  • protein synthesis
  • protein turnover
  • resistance exercise
  • skeletal muscle
  • transcriptome
  • unloading
  • untranslated region

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)


Dive into the research topics of 'Molecular Transducers of Human Skeletal Muscle Remodeling under Different Loading States'. Together they form a unique fingerprint.

Cite this