Steiner, M. C. | Search bioRxiv

bioRxiv2026

Exercise induces Skeletal Muscle Methylome and Transcriptome changes, regardless of Age and COPD

Skeletal muscle atrophy and deconditioning contribute to functional limitation and disability in COPD. While transcriptome and DNA methylation changes accompany exercise in healthy muscle, their interaction with COPD status and ageing, and integrative analyses of methylome-transcriptome responses have not been explored. We performed gene expression and DNA methylation profiling in skeletal muscle of sedentary volunteers with COPD, age-matched older adults, and younger healthy individuals, before and during (1,4 and 8 weeks) supervised aerobic exercise training and after four weeks of detraining. Exercise induced transcriptomic and DNA methylation changes, but these responses were unaffected by COPD status or age. Subsequent analysis focusing on temporal exercise effects independent of disease or age revealed differential transcriptomic changes across time points, a subset of which significantly associated with DNA methylome alterations. Transient transcriptomic changes not linked to DNA methylation were enriched for inflammatory and oxidative stress pathways, whereas persistent methylation-associated adaptations were related to immunomodulation and tissue remodelling. Together, this study provides insight into molecular mechanisms contributing to skeletal muscle adaptation to aerobic exercise training in sedentary individuals.

genomics↗

bioRxiv2024

Study design and the sampling of deleterious rare variants in biobank-scale datasets

One key component of study design in population genetics is the "geographic breadth" of a sample (i.e., how broad a region across which individuals are sampled). How the geographic breadth of a sample impacts observations of rare, deleterious variants is unclear, even though such variants are of particular interest for biomedical and evolutionary applications. Here, in order to gain insight into the effects of sample design on ascertained genetic variants, we formulate a stochastic model of dispersal, genetic drift, selection, mutation, and geographically concentrated sampling. We use this model to understand the effects of the geographic breadth of sampling effort on the discovery of negatively selected variants. We find that samples which are more geographically broad will discover a greater number variants as compared geographically narrow samples (an effect we label "discovery"); though the variants will be detected at lower average frequency than in narrow samples (e.g. as singletons, an effect we label "dilution"). Importantly, these effects are amplified for larger sample sizes and moderated by the magnitude of fitness effects. We validate these results using both population genetic simulations and empirical analyses in the UK Biobank. Our results are particularly important in two contexts: the association of large-effect rare variants with particular phenotypes and the inference of negative selection from allele frequency data. Overall, our findings emphasize the importance of considering geographic breadth when designing and carrying out genetic studies, especially at biobank scale. SignificanceAs genetic studies grow, researchers are increasingly seeking to identify rare genetic variants with large impacts on traits. In this paper, we combine theoretical methods and data analysis to show how differences in sampling with respect to geographic location can influence the number and frequency of genetic variants that are found. Our results suggest that geographically broad samples will include more distinct genetic variants, though each variant will be found at a lower frequency, as compared to geographically narrow samples. Our results can help researchers to consider the implications of study design on expected results when constructing new genetic samples.

genetics↗