Journal of Human Sport and Exercise

Muscle genomics and aerobic training

Yecid Mina-Paz, Diana Carolina Zambrano, Andrés Jenuer Matta, Alejandra Rodríguez, Felipe García-Vallejo

DOI: https://doi.org/10.14198/jhse.2022.173.11

Abstract

The performance in physical activity is determined not only by physiological processes such as age, body composition, gender and degree of training, but also by the genomics and even epigenetic events occurring during the training programs. In this context, using bioinformatics resources, we aimed to analyse the expression of genes associated with muscle function in vastus lateral samples. We used data from DNA microarray experiments reported in NCBI's GEO DataSet database under the series number GSE117070. Differential expression was calculated using the Z-ratio equation. We also used the software Cytoscape 3.6 to build a protein-protein interaction network with over-expressed genes. We found that seven genes out of the 397 genes analysed in the 41 individuals subjected to aerobic exercise with an increase in training intensity through the percentage of VO2max, were over-expressed based on the statistical approach. The Protein-Protein Interaction (PPI) network showed 477 nodes, two connected components, 17 multi-edge node pairs and an average number of neighbours of 2.092. The node with the highest number of interactions was TPM1 with 150. GO categories of biological processes most relevant of the network included indispensable processes for muscle function and contraction such as polymerization of actin filaments and ATP synthesis from electron transport chain.


Keywords

Aerobic training; Muscle; DNA microarray; Differential expression; Network

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DOI: https://doi.org/10.14198/jhse.2022.173.11





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