Unknown,Transcriptomics,Genomics,Proteomics

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Cluster analysis reveals differential transcript profiles associated with resistance training-induced human skeletal muscle hypertrophy

ABSTRACT: Overall, the widely disparate transcriptomes identified prior to RT among the three clusters support the notion that at least some of the inter-individual heterogeneity in propensity for RT-induced myofiber hypertrophy is likely pre-determined. Baseline comparisons of skeletal muscle transcript profiles from 44 subjects previously clustered (K-means cluster analysis) as non-, modest-, and extreme-responders (Non, n=15; Mod, n=14; Xtr, n=15) based on the magnitudes of change in vastus lateralis myofiber cross-sectional area (CSA) following 16-wk, 3-d/wk, high-intensity RT.

ORGANISM(S): Homo sapiens

SUBMITTER: Anna Thalacker-Mercer

PROVIDER: E-GEOD-42507 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Cluster analysis reveals differential transcript profiles associated with resistance training-induced human skeletal muscle hypertrophy.

Thalacker-Mercer Anna A Stec Michael M Cui Xiangqin X Cross James J Windham Samuel S Bamman Marcas M

Physiological genomics 20130430 12

Using genomic microarray analysis, we sought to identify and annotate differences in the pretraining skeletal muscle transcriptomes among human subjects clustered as nonresponders (Non), modest responders (Mod), and extreme responders (Xtr) based on differential magnitudes of myofiber hypertrophy in response to progressive resistance training (RT) (Non-6 μm², Mod 1,111 μm², or Xtr 2,475 μm²). In prior work, we noted differences among clusters in the prevalence of myogenic stem cells prior to and ...[more]

PMID: 23632419

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Project description:Purpose: Photoperiod is known to cause physiological changes in seasonal mammals, including body weight, physical activity, and reproductive status. Because cats are seasonal breeders, we recently tested the effects of day length on resting metabolic rate, voluntary physical activity, and food intake. In that study, resting metabolic rate, physical activity, and food intake to maintain body weight were greater in cats exposed to long days vs. short days. Because photoperiod has also been demonstrated to affect adipose tissue gene expression in several species, including dairy cows, sheep, and Siberian hamsters, the objective of this study was to determine the effects of day length on the adipose transcriptome profile of cats as assessed by RNA-seq. Methods: Ten healthy adult neutered male domestic shorthair cats were used in a randomized crossover design study. During two 12-wk periods, cats were exposed to either short days (8 hr light:16 hr dark) or long days (16 hr light:8 hr dark). Cats were fed a commercial diet to maintain baseline body weight. Subcutaneous adipose biopsies were collected at wk 12 of each period for RNA isolation and Illumina sequencing. Results: A total of 578 million sequences (28.9 million/sample) were generated by Illumina sequencing. Using a raw p value of P<0.005, 170 mRNA transcripts were differentially expressed between short day- and long day-housed cats. Of the 170 transcripts highlighted, 25 annotated transcripts were up-regulated, while 116 annotated transcripts were down-regulated by long days. Another 29 un-annotated transcripts (name and function not known) were also different between groups. In general, adipose tissue of long day-housed cats had greater expression of genes involved with cholesterol trafficking, fatty acid synthesis and immune function, and lower expression of genes involved with cell cycle and growth, cell development and structure, and protein processing, when compared to short day-housed cats. Subcutaneous adipose tissue mRNA profiles of healthy adult neutered male cats exposed to short days (8 hr light: 16 hr dark) or long days (16 hr light: 8 hr dark) using Illumina sequencing.

Dataset Information

Cluster analysis reveals differential transcript profiles associated with resistance training-induced human skeletal muscle hypertrophy

Publications

Cluster analysis reveals differential transcript profiles associated with resistance training-induced human skeletal muscle hypertrophy.

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