Gymnastik- och idrottshögskolan, GIH

KEY POINTS: For individuals showing suboptimal adaptations to resistance training, manipulation of training volume is a potential measure to facilitate responses. This remains unexplored. Here, 34 untrained individuals performed contralateral resistance training with moderate and low volume for 12 weeks. Moderate volume led to larger increases in muscle cross-sectional area, strength and type II fibre-type transitions. These changes coincided with greater activation of signalling pathways controlling muscle growth and greater induction of ribosome synthesis. Thirteen and sixteen participants, respectively, displayed clear benefits of moderate-volume training on muscle hypertrophy and strength. This coincided with greater total RNA accumulation in the early-phase of the training period, suggesting that ribosomal biogenesis regulates the dose-response relationship between training volume and muscle hypertrophy. These results demonstrate that there is a dose-dependent relationship between training volume and outcomes. On the individual level, benefits of higher training volume were associated with increased ribosomal biogenesis.

ABSTRACT: Resistance-exercise volume is a determinant of training outcomes. However not all individuals respond in a dose-dependent fashion. In this study, 34 healthy individuals (males n = 16, 23.6 (4.1) years; females n = 18, 22.0 (1.3)) performed moderate- (3 sets per exercise, MOD) and low-volume (1 set, LOW) resistance training in a contralateral fashion for 12 weeks (2-3 sessions × week^-1 ). Muscle cross-sectional area (CSA) and strength were assessed at weeks 0 and 12, along with biopsy sampling (m. Vastus lateralis). Muscle biopsies were also sampled before and one hour after the fifth session (Week 2). MOD resulted in larger increases in muscle CSA (5.2 (3.8)% versus 3.7 (3.7)%, P < 0.001) and strength (3.4-7.7% difference, all P < 0.05. This coincided with greater reductions in type IIX fibres from week 0 to 12 (MOD, -4.6; LOW -3.2%-point), greater phosphorylation of S6-kinase 1 (p85 S6K1^Thr412 , 19%; p70 S6K1^Thr389 , 58%) and ribosomal protein S6^Ser235/236 (37%), greater rested-state total RNA (8.8%) and greater exercise-induced c-Myc mRNA expression (25%; Week 2, all P < 0.05). Thirteen and sixteen participants, respectively, displayed clear benefits in response to MOD on muscle hypertrophy and strength. Benefits were associated with greater accumulation of total RNA at Week 2 in the MOD leg, with every 1% difference increasing the odds of MOD benefit by 7.0% (P = 0.005) and 9.8% (P = 0.002). In conclusion, MOD led to greater functional and biological adaptations than LOW. Associations between dose-dependent total RNA accumulation and increases in muscle mass and strength points to ribosome biogenesis as a determinant of dose-dependent training responses. This article is protected by copyright. All rights reserved.

BACKGROUND: Human skeletal muscle responds to weight-bearing exercise with significant inter-individual differences. Investigation of transcriptome responses could improve our understanding of this variation. However, this requires bioinformatic pipelines to be established and evaluated in study-specific contexts. Skeletal muscle subjected to mechanical stress, such as through resistance training (RT), accumulates RNA due to increased ribosomal biogenesis. When a fixed amount of total-RNA is used for RNA-seq library preparations, mRNA counts are thus assessed in different amounts of tissue, potentially invalidating subsequent conclusions. The purpose of this study was to establish a bioinformatic pipeline specific for analysis of RNA-seq data from skeletal muscles, to explore the effects of different normalization strategies and to identify genes responding to RT in a volume-dependent manner (moderate vs. low volume). To this end, we analyzed RNA-seq data derived from a twelve-week RT intervention, wherein 25 participants performed both low- and moderate-volume leg RT, allocated to the two legs in a randomized manner. Bilateral muscle biopsies were sampled from m. vastus lateralis before and after the intervention, as well as before and after the fifth training session (Week 2).

RESULT: Bioinformatic tools were selected based on read quality, observed gene counts, methodological variation between paired observations, and correlations between mRNA abundance and protein expression of myosin heavy chain family proteins. Different normalization strategies were compared to account for global changes in RNA to tissue ratio. After accounting for the amounts of muscle tissue used in library preparation, global mRNA expression increased by 43-53%. At Week 2, this was accompanied by dose-dependent increases for 21 genes in rested-state muscle, most of which were related to the extracellular matrix. In contrast, at Week 12, no readily explainable dose-dependencies were observed. Instead, traditional normalization and non-normalized models resulted in counterintuitive reverse dose-dependency for many genes. Overall, training led to robust transcriptome changes, with the number of differentially expressed genes ranging from 603 to 5110, varying with time point and normalization strategy.

CONCLUSION: Optimized selection of bioinformatic tools increases the biological relevance of transcriptome analyses from resistance-trained skeletal muscle. Moreover, normalization procedures need to account for global changes in rRNA and mRNA abundance.