Muscle genomics and aerobic training
DOI:
https://doi.org/10.14198/jhse.2022.173.11Keywords:
Aerobic training, Muscle, DNA microarray, Differential expression, NetworkAbstract
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.
Funding
Universidad del Valle, University Institution National Sports SchoolDownloads
References
Bouchard, C. L. (1995). The heritage family study. Aims, design, and measurement protocol. Medicine and science in sports and exercise, 27(5), 721-729. https://doi.org/10.1249/00005768-199505000-00015
Cheadle, C. V. (2003). Análisis de datos de microarrays utilizando la transformación de puntuación Z. . J Mol Diag: JMD. 5 (2): 73-81.
Chicharro, J. L., & Vaquero, A. F. (2006). Fisiología del ejercicio. Madrid: Ed. Médica Panamericana.
Colberg, S. R. (2016). Physical activity/exercise and diabetes: a position statement of the American Diabetes Association. Diabetes care, 39(11), 2065-2079. https://doi.org/10.2337/dc16-1728
De Palma, S., Capitanio, D., Vasso, M., Braghetta, P., Scotton, C., Bonaldo, P., & Gelfi, C. (2014). Muscle proteomics reveals novel insights into the pathophysiological mechanisms of collagen VI myopathies. Journal of proteome research, 5022-5030. https://doi.org/10.1021/pr500675e
Di Prampero, P. E., Botter, A., & Osgnach, C. (2015). The energy cost of sprint running and the role of metabolic power in setting top performances. European journal of applied physiology, 115(3), 451-469. https://doi.org/10.1007/s00421-014-3086-4
Egan, B., & Zierath, J. R. (2013). Exercise metabolism and the molecular regulation of skeletal muscle adaptation. . Cell metabolism, 17(2), 162-184. https://doi.org/10.1016/j.cmet.2012.12.012
Gonzalez‐Freire, M., Semba, R. D., Ubaida‐Mohien, C., Fabbri, E., Scalzo, P., Højlund, K., & Ferrucci, L. (2017). The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature. Journal of cachexia, sarcopenia and muscle, 8(1), 5-18. https://doi.org/10.1002/jcsm.12121
Kanazawa, Y., Ikegami, K., Sujino, M., Koinuma, S., Nagano, M. O., & Shigeyoshi, Y. (2019). Effects of aging on basement membrane of the soleus muscle during recovery following disuse atrophy in rats. Experimental gerontology, 98, 153-161. https://doi.org/10.1016/j.exger.2017.08.014
Liu, D., Sartor, M. A., Nader, G. A., Gutmann, L., Treutelaar, M. K., Pistilli, E. E., & Gordon, P. M. (2010). Skeletal muscle gene expression in response to resistance exercise: sex specific regulation. BMC genomics, 11(1), 659. https://doi.org/10.1186/1471-2164-11-659
Lortie, G. S. (1984). Responses of maximal aerobic power and capacity to aerobic training. International journal of sports medicine, 5(05), 232-236. https://doi.org/10.1055/s-2008-1025911
Pilegaard, H., Ordway, G., Saltin, B., & Neufer, P. (2000). Transcriptional regulation of gene expression in human skeletal muscle during recovery from exercise. Am J Physiol Endocrinol Metab, 279, E806-E814. https://doi.org/10.1152/ajpendo.2000.279.4.e806
Rockman, M. V., & Kruglyak, L. (2006). Genetics of global gene expression. . Nature Reviews Genetics, 7(11), 862-872. https://doi.org/10.1038/nrg1964
Rowlands, D. S., Thomson, J. S., Timmons, B. W., Raymond, F., Fuerholz, A., Mansourian, R., & Kussmann, M. (2011). Transcriptome and translational signaling following endurance exercise in trained skeletal muscle: impact of dietary protein. Physiological Genomics, 43(17), 1004-1020. https://doi.org/10.1152/physiolgenomics.00073.2011
Saltin, B., Henriksson, J., Nygaard, E., Andersen, P., & Jansson, E. (1977). Fiber types and metabolic potentials of skeletal muscles in sedentary man and endurance runners. Annals of the New York Academy of Sciences,, 1(301), 3-29. https://doi.org/10.1111/j.1749-6632.1977.tb38182.x
Samozino, P., Rabita, G., Dorel, S., Slawinski, J., Peyrot, N., Saez de Villarreal, E., & Morin, J. B. (2016). A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running. Scandinavian journal of medicine & science in sports, 26(6), 648-658. https://doi.org/10.1111/sms.12490
Sela, I., Krentsis, I. M., Shlomai, Z., Sadeh, M., Dabby, R., Argov, Z., & Mitrani-Rosenbaum, S. (2011). The proteomic profile of hereditary inclusion body myopathy. PLoS One, 6(1), e16334. https://doi.org/10.1371/journal.pone.0016334
Timmons, J. A., Knudsen, S., Rankinen, T., Koch, L. G., Sarzynski, M., Jensen, T., & Åkerström, T. (2010). Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans. Journal of applied physiology, 108(6), 1487-1496. https://doi.org/10.1152/japplphysiol.01295.2009
Trappe, S., Luden, N., Minchev, K., Raue, U., Jemiolo, B., & Trappe, T. A. (2015). Skeletal muscle signature of a champion sprint runner. Journal of Applied Physiology, 12 (118), 1460-1466. https://doi.org/10.1152/japplphysiol.00037.2015
Turner, D. C., Seaborne, R. A., & Sharples, A. P. (2019). Comparative Transcriptome and Methylome Analysis in Human Skeletal Muscle Anabolism, Hypertrophy and Epigenetic Memory. Scientific reports, 9(1), 4251. https://doi.org/10.1101/465708
Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017). 10 years of GWAS discovery: biology, function, and translation. The American Journal of Human Genetics, 101(1), 5-22. https://doi.org/10.1016/j.ajhg.2017.06.005
Wasserman, K., Hansen, J. E., Sue, D. Y., Whipp, B. J., & Froelicher, V. F. (1987). Principles of exercise testing and interpretation. Journal of Cardiopulmonary Rehabilitation and Prevention(7(4), 189). https://doi.org/10.1097/00008483-198704000-00014
Xu, Q., Wu, N., Cui, L., Wu, Z., & Qiu, G. (2017 ). Filamin B: the next hotspot in skeletal research? Journal of Genetics and Genomics, 44(7), 335-342. https://doi.org/10.1016/j.jgg.2017.04.007
Downloads
Statistics
Published
How to Cite
Issue
Section
License
Copyright (c) 2018 Journal of Human Sport and Exercise
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Each author warrants that his or her submission to the Work is original and that he or she has full power to enter into this agreement. Neither this Work nor a similar work has been published elsewhere in any language nor shall be submitted for publication elsewhere while under consideration by JHSE. Each author also accepts that the JHSE will not be held legally responsible for any claims of compensation.
Authors wishing to include figures or text passages that have already been published elsewhere are required to obtain permission from the copyright holder(s) and to include evidence that such permission has been granted when submitting their papers. Any material received without such evidence will be assumed to originate from the authors.
Please include at the end of the acknowledgements a declaration that the experiments comply with the current laws of the country in which they were performed. The editors reserve the right to reject manuscripts that do not comply with the abovementioned requirements. The author(s) will be held responsible for false statements or failure to fulfill the above-mentioned requirements.
This title is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license (CC BY-NC-ND 4.0).
You are free to share, copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the license terms under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
Transfer of Copyright
In consideration of JHSE’s publication of the Work, the authors hereby transfer, assign, and otherwise convey all copyright ownership worldwide, in all languages, and in all forms of media now or hereafter known, including electronic media such as CD-ROM, Internet, and Intranet, to JHSE. If JHSE should decide for any reason not to publish an author’s submission to the Work, JHSE shall give prompt notice of its decision to the corresponding author, this agreement shall terminate, and neither the author nor JHSE shall be under any further liability or obligation.
Each author certifies that he or she has no commercial associations (e.g., consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article, except as disclosed on a separate attachment. All funding sources supporting the Work and all institutional or corporate affiliations of the authors are acknowledged in a footnote in the Work.
Each author certifies that his or her institution has approved the protocol for any investigation involving humans or animals and that all experimentation was conducted in conformity with ethical and humane principles of research.
Competing Interests
Biomedical journals typically require authors and reviewers to declare if they have any competing interests with regard to their research.
JHSE require authors to agree to Copyright Notice as part of the submission process.