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. 2016 Sep 22;12(9):e1006294.
doi: 10.1371/journal.pgen.1006294. eCollection 2016 Sep.

The Impact of Endurance Training on Human Skeletal Muscle Memory, Global Isoform Expression and Novel Transcripts

Maléne E Lindholm  1 , Stefania Giacomello  2 , Beata Werne Solnestam  2 , Helene Fischer  1   3 , Mikael Huss  2 , Sanela Kjellqvist  2 , Carl Johan Sundberg  1
Affiliations

The Impact of Endurance Training on Human Skeletal Muscle Memory, Global Isoform Expression and Novel Transcripts

Maléne E Lindholm et al. PLoS Genet. .

Abstract

Regularly performed endurance training has many beneficial effects on health and skeletal muscle function, and can be used to prevent and treat common diseases e.g. cardiovascular disease, type II diabetes and obesity. The molecular adaptation mechanisms regulating these effects are incompletely understood. To date, global transcriptome changes in skeletal muscles have been studied at the gene level only. Therefore, global isoform expression changes following exercise training in humans are unknown. Also, the effects of repeated interventions on transcriptional memory or training response have not been studied before. In this study, 23 individuals trained one leg for three months. Nine months later, 12 of the same subjects trained both legs in a second training period. Skeletal muscle biopsies were obtained from both legs before and after both training periods. RNA sequencing analysis of all 119 skeletal muscle biopsies showed that training altered the expression of 3,404 gene isoforms, mainly associated with oxidative ATP production. Fifty-four genes had isoforms that changed in opposite directions. Training altered expression of 34 novel transcripts, all with protein-coding potential. After nine months of detraining, no training-induced transcriptome differences were detected between the previously trained and untrained legs. Although there were several differences in the physiological and transcriptional responses to repeated training, no coherent evidence of an endurance training induced transcriptional skeletal muscle memory was found. This human lifestyle intervention induced differential expression of thousands of isoforms and several transcripts from unannotated regions of the genome. It is likely that the observed isoform expression changes reflect adaptational mechanisms and processes that provide the functional and health benefits of regular physical activity.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Experimental design and training response.
a) The study was divided into two training periods (1 and 2) with a 9-month break in between. In Period 1, 23 individuals trained one randomized leg 45 min 4 times/week for 12 weeks, while the other leg remained untrained. In Period 2, 12 of the 23 individuals trained both legs with the same protocol as for the trained leg in Period 1, thus 2x45 min each session for 45 sessions in total. Both Periods included a 4-week “pre-test” phase in which individuals underwent a VO2-peak test, a one-legged performance test and biopsies were taken from both legs. After both training periods, skeletal muscle biopsies and performance tests were repeated for both legs; b) Performance results from the physiological 15-min test, c) Citrate synthase enzyme activity and d) β-HAD enzyme activity. Green squares represent the leg that trained in the Period 1, referred to as the trained leg, while purple squares represent the untrained leg, which was only trained in Period 2. Data is presented as mean ± SD for the 12 individuals that completed the whole study. Significance based on two-way repeated measures ANOVA is indicated by * (p<0.05), ** (p<0.001), *** (p<0.0001).
Fig 2
Fig 2. Global transcriptome changes with repeated periods of endurance training.
Gene expression of 12,848 genes (mean FPKM>1) in total was analyzed using multivariate statistics. a) PCA (Principal Component Analysis) and OPLS (orthogonal projections of latent structures by means of partial least squares) of the training response in Period 1. The three-dimensional PCA score plot shows the PC1-3 plane, with biopsies collected before (T1, black) and after Period 1 in the trained leg (T2, red). The OPLS model shows the goodness of fit of the model, which represents the cumulative explained variance (R2, grey) and the goodness of prediction of the model, which represents the cumulative fraction of the total variance that can be predicted by the model from cross-validation (Q2, yellow), (n = 22 individuals). b) The specificity of the training effect was analyzed by comparing the untrained leg after (U2, green) to before (T1, black) Period 1, (n = 21). The training response in Period 2 in c) the previously trained leg (n = 10, before (T3) in blue and after (T4) in purple) and in d) the previously untrained leg (n = 11, before (U3) in dark red and after (U4) in yellow). For PCA and OPLS quality parameters, refer to Tables 1 and 2, respectively.
Fig 3
Fig 3. Training-induced differential isoform expression.
a) Venn diagram representing the number of unique and shared differentially expressed isoforms from Period 1 (green) and both legs trained in Period 2 (blue for previously trained leg and purple for previously untrained leg). b) Examples of isoforms that were differentially expressed in different directions from the same gene in response in Period 1. The bars represent the mean fold change of each isoform (based on batch-corrected FPKM values), all are significant according to the OPLS model (S3 Table), (n = 22 individuals).
Fig 4
Fig 4. Differential novel transcript expression.
Heatmap showing expression of differentially expressed novel transcripts in all individuals before (T1) and after (T2) training in Period 1. Read counts for each novel transcript per individual has been plotted as log2(read count), (n = 22 individuals).
Fig 5
Fig 5. Endurance-induced skeletal muscle memory at the transcriptome level.
Human skeletal muscle gene expression data (12,848 genes) was used to study: a) The presence of any residual effect in the previously trained leg by comparing before training in Period 1 (T1, black) with the same leg before Period 2 (T3, blue). Left: results are presented as a 3D PCA score plot showing the PC1-3 plane. Middle: summary of fit of OPLS; R2 (grey): goodness of fit of the model, which represents the cumulative explained variance; Q2 (yellow): goodness of prediction of the model, which represents the cumulative fraction of the total variance that can be predicted by the model from cross-validation. Right: 2D score plot of OPLS (n = 13) b) Transcriptome differences between the previously trained leg (T3, blue) and the previously untrained leg (U3, brown) before Period 2. Left: a 3D PCA score plot showing the PC1-3 plane. Right: summary of fit of OPLS; R2 and Q2 as described above (n = 12). For PCA and OPLS quality parameters, refer to Tables 1 and 2, respectively.
Fig 6
Fig 6. Comparing intra-individual effects of a repeated environmental training stimulus.
a) Correlation of individual fold changes for performance (green triangles), citrate synthase activity (blue circles) and β-HAD activity (orange squares) for the leg trained in Period 1 (T1 vs T2) and the same leg trained in Period 2 (T3 vs T4) for the 12 individuals that completed both training periods. b) Venn diagram comparing the gene changes in the leg trained in Period 1 with both legs trained in Period 2. Data is based on all available sequencing data from biopsies of the common 12 individuals. c) Pearson’s correlation between the absolute fold changes of the significant genes differentially expressed in Period 1 (T1 vs T2) with the absolute fold changes of the same genes in Period 2, for T3 vs T4 and U3 vs U4, respectively. All correlations were significant (p<0.0001) d) XY-plot of the fold changes of the same genes as in (c) for the leg trained in Period 1 (T1 vs T2) and the same leg trained in Period 2 (T3 vs T4). Examples of genes are highlighted in red with gene names. e) Ontology analysis of the differentially expressed genes in Period 1 (left, T1 vs T2) and the same leg in Period 2 (right, T3 vs T4) for 12 individuals. Top 15 categories based on significance according to IPA are shown. The number at each line represents the number of common genes between the two categories connected by the line. Square color indicates the percentage of upregulated genes among the significant differentially expressed within that category. f) Example of a network that was uniquely enriched in Period 1 (T1 vs T2). Red color indicates an increased expression of that gene or group of genes with training, while green color indicates a decrease.
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Grants and funding

This work was supported by: Centrum för Idrottsforskning: P2011-0137 and P2013-0065. http://centrumforidrottsforskning.se; Karolinska Institutet, KID-funding 5423/08-225. https://internwebben.ki.se/en/kid-funding; and Knut and Alice Wallenberg Foundation, WABI support, WABI20130308 https://www.scilifelab.se/facilities/wabi/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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