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Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity

The molecular mechanisms underlying the response to exercise and inactivity are not fully understood. We propose an innovative approach to profile the skeletal muscle transcriptome to exercise and inactivity using 66 published datasets. Data collected from human studies of aerobic and resistance exe...

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Autores principales: Pillon, Nicolas J., Gabriel, Brendan M., Dollet, Lucile, Smith, Jonathon A. B., Sardón Puig, Laura, Botella, Javier, Bishop, David J., Krook, Anna, Zierath, Juleen R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981202/
https://www.ncbi.nlm.nih.gov/pubmed/31980607
http://dx.doi.org/10.1038/s41467-019-13869-w
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author Pillon, Nicolas J.
Gabriel, Brendan M.
Dollet, Lucile
Smith, Jonathon A. B.
Sardón Puig, Laura
Botella, Javier
Bishop, David J.
Krook, Anna
Zierath, Juleen R.
author_facet Pillon, Nicolas J.
Gabriel, Brendan M.
Dollet, Lucile
Smith, Jonathon A. B.
Sardón Puig, Laura
Botella, Javier
Bishop, David J.
Krook, Anna
Zierath, Juleen R.
author_sort Pillon, Nicolas J.
collection PubMed
description The molecular mechanisms underlying the response to exercise and inactivity are not fully understood. We propose an innovative approach to profile the skeletal muscle transcriptome to exercise and inactivity using 66 published datasets. Data collected from human studies of aerobic and resistance exercise, including acute and chronic exercise training, were integrated using meta-analysis methods (www.metamex.eu). Here we use gene ontology and pathway analyses to reveal selective pathways activated by inactivity, aerobic versus resistance and acute versus chronic exercise training. We identify NR4A3 as one of the most exercise- and inactivity-responsive genes, and establish a role for this nuclear receptor in mediating the metabolic responses to exercise-like stimuli in vitro. The meta-analysis (MetaMEx) also highlights the differential response to exercise in individuals with metabolic impairments. MetaMEx provides the most extensive dataset of skeletal muscle transcriptional responses to different modes of exercise and an online interface to readily interrogate the database.
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spelling pubmed-69812022020-01-27 Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity Pillon, Nicolas J. Gabriel, Brendan M. Dollet, Lucile Smith, Jonathon A. B. Sardón Puig, Laura Botella, Javier Bishop, David J. Krook, Anna Zierath, Juleen R. Nat Commun Article The molecular mechanisms underlying the response to exercise and inactivity are not fully understood. We propose an innovative approach to profile the skeletal muscle transcriptome to exercise and inactivity using 66 published datasets. Data collected from human studies of aerobic and resistance exercise, including acute and chronic exercise training, were integrated using meta-analysis methods (www.metamex.eu). Here we use gene ontology and pathway analyses to reveal selective pathways activated by inactivity, aerobic versus resistance and acute versus chronic exercise training. We identify NR4A3 as one of the most exercise- and inactivity-responsive genes, and establish a role for this nuclear receptor in mediating the metabolic responses to exercise-like stimuli in vitro. The meta-analysis (MetaMEx) also highlights the differential response to exercise in individuals with metabolic impairments. MetaMEx provides the most extensive dataset of skeletal muscle transcriptional responses to different modes of exercise and an online interface to readily interrogate the database. Nature Publishing Group UK 2020-01-24 /pmc/articles/PMC6981202/ /pubmed/31980607 http://dx.doi.org/10.1038/s41467-019-13869-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Pillon, Nicolas J.
Gabriel, Brendan M.
Dollet, Lucile
Smith, Jonathon A. B.
Sardón Puig, Laura
Botella, Javier
Bishop, David J.
Krook, Anna
Zierath, Juleen R.
Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity
title Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity
title_full Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity
title_fullStr Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity
title_full_unstemmed Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity
title_short Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity
title_sort transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981202/
https://www.ncbi.nlm.nih.gov/pubmed/31980607
http://dx.doi.org/10.1038/s41467-019-13869-w
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