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Transcription factors associated with regulation of transcriptome in human thigh and calf muscles at baseline and after six days of disuse

GSE271607 Homo sapiens Expression profiling by high throughput sequencing 40 samples 2024/09/08 GPL21697
Summary
Disuse has a negative impact on the postural muscles of the trunk and legs. Different leg muscles demonstrate a differentiated and conservative response to disuse, in terms of a decrease in muscle mass, strength, aerobic performance, and changes in gene expression. We aimed to identify transcription factors regulating gene expression at baseline and after disuse in human m. soleus – a “slow” muscle with a strong postural function, and “mixed“ m. vastus lateralis. Biopsies were taken from these muscles prior to and after 6 days of strict disuse (dry immersion). The enriched transcription factor binding sites (and corresponding factors) in the individual promoter regions of co-expressed genes were examined using the positional weight matrix approach. The baseline transcriptomic profiles and the disuse-induced changes (RNA-seq) differ significantly between muscles. In particular, the specific and significant response to disuse in m. soleus was found to be strongly related to the suppression of genes regulating the mitochondrial energy metabolism, the activation of the inflammatory response and the ubiquitin-proteasome system. This response is associated with the proinflammatory transcription factors such as families IRF, STAT, and other. The validity of approximately two-thirds of the predicted transcription factors was indirectly confirmed by the analysis of their function described in the literature. These identified transcription factors appear to be promising candidates for future targeted studies that mechanistically investigate gene expression regulation in various muscles at baseline, following disuse or inactivity.
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NCBI GEO page ↗ Paper (PMID 39978540) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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