Skeletal muscle gene expression in response to resistance exercise: sex specific regulation

<p>Abstract</p> <p>Background</p> <p>The molecular mechanisms underlying the sex differences in human muscle morphology and function remain to be elucidated. The sex differences in the skeletal muscle transcriptome in both the resting state and following anabolic stimuli, such as resistance exercise (RE), might provide insight to the contributors of sexual dimorphism of muscle phenotypes. 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 (4 h post-exercise) or late recovery (24 h 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 (4 h post-exercise, n = 3 males, n = 4 females; 24 h 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.</p> <p>Results</p> <p>This investigation identified extensive sex differences present in the muscle transcriptome at baseline and following acute RE. In the resting state, female muscle had a greater transcript abundance of genes involved in fatty acid oxidation and gene transcription/translation processes. After strenuous RE at the same relative intensity, the time course of the transcriptional modulation was sex-dependent. Males experienced prolonged changes while females exhibited a rapid restoration. Most of the biological processes involved in the RE-induced transcriptional regulation were observed in both males and females, but sex specificity was suggested for several signaling pathways including activation of notch signaling and TGF-beta signaling in females. Sex differences in skeletal muscle transcriptional regulation might implicate a mechanism behind disproportional muscle growth in males as compared with female counterparts after RE training at the same relative intensity.</p> <p>Conclusions</p> <p>Sex differences exist in skeletal muscle gene transcription both at rest and following acute RE, suggesting that sex is a significant modifier of the transcriptional regulation in skeletal muscle. The findings from the present study provide insight into the molecular mechanisms for sex differences in muscle phenotypes and for muscle transcriptional regulation associated with training adaptations to resistance exercise.</p

Genetic analysis of a rat model of aerobic capacity and metabolic fitness.

Aerobic capacity is a strong predictor of all-cause mortality and can influence many complex traits. To explore the biological basis underlying this connection, we developed via artificial selection two rat lines that diverge for intrinsic (i.e. inborn) aerobic capacity and differ in risk for complex disease traits. Here we conduct the first in-depth pedigree and molecular genetic analysis of these lines, the high capacity runners (HCR) and low capacity runners (LCR). Our results show that both HCR and LCR lines maintain considerable narrow-sense heritability (h(2)) for the running capacity phenotype over 28 generations (h(2) = 0.47 ± 0.02 and 0.43 ± 0.02, respectively). To minimize inbreeding, the lines were maintained by rotational mating. Pedigree records predict that the inbreeding coefficient increases at a rate of <1% per generation, ~37-38% slower than expected for random mating. Genome-wide 10K SNP genotype data for generations 5, 14, and 26 demonstrate substantial genomic evolution: between-line differentiation increased progressively, while within-line diversity deceased. Genome-wide average heterozygosity decreased at a rate of <1% per generation, consistent with pedigree-based predictions and confirming the effectiveness of rotational breeding. Linkage disequilibrium index r(2) decreases to 0.3 at ~3 Mb, suggesting that the resolution for mapping quantitative trait loci (QTL) can be as high as 2-3 cM. To establish a test population for QTL mapping, we conducted an HCR-LCR intercross. Running capacity of the F1 population (n=176) was intermediate of the HCR and LCR parentals (28 pairs); and the F2 population (n=645) showed a wider range of phenotypic distribution. Importantly, heritability in the F0-F2 pedigree remained high (h(2)~0.6). These results suggest that the HCR-LCR lines can serve as a valuable system for studying genomic evolution, and a powerful resource for mapping QTL for a host of characters relevant to human health

Expression of macrophage genes within skeletal muscle correlates inversely with adiposity and insulin resistance in humans.

Background Local inflammation in obese adipose tissue has been shown to contribute to insulin resistance, however, the role of macrophage infiltration within skeletal muscle is still debateable. This study aimed to evaluate the association of skeletal muscle macrophage gene expression with adiposity levels and insulin sensitivity in obese patients. Methods Twenty-two non-diabetic obese patients and 23 healthy lean controls were included. Obese patients underwent a 3-month weight loss intervention. Macrophage gene expression in skeletal muscle (quantitative RT-PCR), body composition (DXA) and insulin sensitivity (homeostatic model assessment and oral glucose tolerance test) were compared between groups and their associations were analyzed. To validate skeletal muscle findings, we repeated the analyses with macrophage gene expression in adipose tissue. Results Expression levels of macrophage genes (CD68, CD11b, CD206, CD16, CD40, and CD163) were lower in skeletal muscle tissue of obese versus lean participants. Macrophage gene expression was also found to be inversely associated with adiposity, fasting insulin, and HOMA (r=-0.4~-0.6, pThe accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author