Unknown

Dataset Information

Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity.


ABSTRACT: 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-analy

SUBMITTER: Pillon NJ 

PROVIDER: S-EPMC6981202 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature