Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: E-GEOD-24235
PROVIDER: PRJNA132933 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Human skeletal muscle transcriptional response to exercise
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Project description:Resistance Exercise Reverses Aging in Human Skeletal Muscle
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Project description:The molecular mechanisms underlying the sex differences in human muscle morphology and function remain to be elucidated. The purpose of the study was to detect the sex differences in the skeletal muscle transcriptome in both the resting state and following anabolic stimuli, resistance exercise. We used microarrays to profile the transcriptome of the biceps brachii of young men and women who underwent an acute unilateral RE session following 12 weeks of progressive training. Bilateral muscle biopsies were obtained either at an early (4h post-exercise) or late recovery (24h post-exercise) time point. Muscle transcription profiles were compared in the resting state between men (n=6) and women (n=8), and in response to acute RE in trained exercised vs. untrained non-exercised control muscle for each sex and time point separately (4h post-exercise, n=3 males, n=4 females; 24h post-exercise, n=3 males, n=4 females). A logistic regression-based method (LRpath), following Bayesian moderated t-statistic (IMBT), was used to test gene functional groups and biological pathways enriched with differentially expressed genes.
2010-12-06 | E-GEOD-24235 | biostudies-arrayexpress
Project description:Skeletal muscle is a complex heterogeneous tissue comprised of diverse muscle fiber and non-fiber cell types that, in addition to movement, influences other systems such as immunity, metabolism and cognition. We investigated gene expression patterns of resident human skeletal muscle cells using both single-cell RNA-seq and RNA-seq of single muscle fiber dissections from vastus lateralis. We generated transcriptome profiles of the major multinucleated human skeletal muscle fiber-types as well as 11 human skeletal muscle mononuclear cell types, including immune, endothelial, pericyte and satellite cells. We delineated two fibro-adipogenic progenitor cell subtypes that may contribute to heterotopic ossification and muscular dystrophy fibrosis under pathological conditions. An important application of cell type signatures is for computational deconvolution of cell type specific gene expression changes using data from bulk transcriptome experiments. Analysis of transcriptome data from a 12 week resistance exercise training study using these human skeletal muscle cell-type signatures revealed significant changes in specific mononuclear cell-type proportions related to age, sex, acute exercise and training. This characterization of human skeletal muscle cell types will resolve cell-type specific changes in large-scale physical activity muscle transcriptome studies and can further the understanding of the diverse effects of exercise and the pathophysiology of muscle disease.
2020-02-01 | GSE130977 | GEO
Project description:Regulation of microRNA in myositis skeletal muscle after exercise (mRNA)
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Project description:Regulation of microRNA in myositis skeletal muscle after exercise (microRNA)
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Project description:Skeletal muscle adapts to exercise training of various modes, intensities and durations with a programmed gene expression response. This study dissects the independent and combined effects of exercise mode, intensity and duration to identify which exercise has the most positive effects on skeletal muscle health. Full details on exercise groups can be found in: Kraus et al Med Sci Sports Exerc. 2001 Oct;33(10):1774-84 and Bateman et al Am J Cardiol. 2011 Sep 15;108(6):838-44. This study uses a middle aged group of subjects that have 3+ markers of metabolic syndrome. One group remains an inactive control, while 5 groups undergo 9 mo supervised exercise training. Exercise groups are as follows: Inactive control (group B); Mild aerobic exercise - low amount/mod intensity (group A); Moderate aerobic exercise - low amt/vig intensity (group D); High aerobic exercise - high amt/vig intensity (group C); resistance training only (group F); and mod aerobic + resistance training (group E). Each group has 10 subjects (5 men and 5 women), however 3 subjects failed array QC, leaving 8 subjects in group E and 9 subjects in group F. Data were all analyzed pre to post training in a RM ANCOVA, covaried for age and sex or regression to determine genotype/phenotype interactions.
2015-05-14 | E-GEOD-48278 | biostudies-arrayexpress
Project description:Skeletal muscle is a complex heterogeneous tissue comprised of diverse muscle fiber and non-fiber cell types that, in addition to movement, influences other systems such as immunity, metabolism and cognition. We investigated gene expression patterns of resident human skeletal muscle cells using single-cell RNA-seq of dissections from vastus lateralis. We generate transcriptome profiles of 11 mononuclear human skeletal muscle mononuclear cell types, including immune, endothelial, pericyte and satellite cells. We delineate two fibro-adipogenic progenitor cell subtypes that may contribute to heterotopic ossification and muscular dystrophy fibrosis under pathological conditions. An important application of cell type signatures is for computational deconvolution of cell type specific changes using data from bulk transcriptome experiments. Analysis of transcriptome data from a 12 week resistance training study using the human skeletal muscle cell-type signatures revealed significant changes in specific mononuclear cell-type proportions related to age, sex, acute exercise and training. This characterization of human skeletal muscle cell subtypes will resolve cell type specific changes in large-scale physical activity muscle transcriptome studies and can further the understanding of the diverse effects of exercise and the pathophysiology of muscle disease.
2020-01-16 | GSE130646 | GEO
Project description:Impact of age and contraction mode on transcriptome response of human skeletal muscle to resistance exercise
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Project description:Dynamics of the human skeletal muscle transcriptome in response to exercise
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