Physiological GenomicsGenomicsPeer-reviewed journal article
The interactive effect of sustained sleep restriction and resistance exercise on skeletal muscle transcriptomics in young females
Olivia KnowlesiD, Megan SoriaiD, Nicholas J. SaneriD, Adam J. TrewiniD, Sarah E. AlexanderiD, Spencer RobertsiD, Danielle HiamiD, ANDREW P. GARNHAMiD, Eric James DrinkwateriD, Brad AisbettiD, Séverine LamoniD
Abstract
IntroductionBoth sleep loss and exercise regulate gene expression in skeletal muscle, yet little is known about how the interaction of these stressors affects the transcriptome. The aim of this study was to investigate the effect of nine nights of sleep restriction, with repeated resistance exercise (REx) sessions, on the skeletal muscle transcriptome of young, trained females. MethodsTen healthy females aged 18-35 years undertook a randomised cross-over study of nine nights sleep restriction (SR; 5-h time in bed) and normal sleep (NS; [≥]7 h time in bed) with a minimum 6-week washout. Participants completed four REx sessions per condition (day 3, 5, 7 and 9). Muscle biopsies were collected both pre- and post-REx on days 3 and 9. Gene and protein expression were assessed by RNA sequencing and Western Blot, respectively. ResultsThree or nine nights of sleep restriction had no effect on the muscle transcriptome independently of exercise. However, close to 3000 transcripts were differentially regulated (FDR < 0.05) 48 h post the completion of three resistance exercise sessions in both NS and SR conditions. Only 39% of downregulated and 18% of upregulated genes were common between both conditions, indicating a moderating effect of sleep restriction on the response to exercise. ConclusionSleep restriction and resistance exercise interacted to alter the enrichment of skeletal muscle transcriptomic pathways in young, resistance-trained females. Performing exercise when sleep restricted may not provide the same adaptive response for individuals as if they were fully rested.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 3
- FWCI
- 0.47
- Field percentile
- top 36%
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