Purpose: We used gene microarray analysis to compare the global expression profile of genes involved in adaptation to training in skeletal muscle from chronically strength-trained (ST), endurance-trained (ET), and untrained control subjects (Con).
Methods: Resting skeletal muscle samples were obtained from the vastus lateralis of 20 subjects (Con n = 7, ET n = 7, ST n = 6; trained [TR] groups >8 yr specific training). Total RNA was extracted from tissue for two color microarray analysis and quantative (Q)-PCR. Trained subjects were characterized by performance measures of peak oxygen uptake (V˙O2peak) on a cycle ergometer and maximal concentric and eccentric leg strength on an isokinetic dynamometer.
Results: Two hundred and sixty-three genes were differentially expressed in trained subjects (ET + ST) compared with Con (P < 0.05), whereas 21 genes were different between ST and ET (P < 0.05). These results were validated by reverse transcriptase polymerase chain reaction for six differentially regulated genes (EIFSJ, LDHB, LMO4, MDH1, SLC16A7, and UTRN. Manual cluster analyses revealed significant regulation of genes involved in muscle structure and development in TR subjects compared with Con (P ≤ 0.05) and expression correlated with measures of performance (P < 0.05). ET had increased whereas ST had decreased expression of gene clusters related to mitochondrial/oxidative capacity (P ≤ 0.05). These mitochondrial gene clusters correlated with V˙O2peak (P < 0.05). V˙O2peak also correlated with expression of gene clusters that regulate fat and carbohydrate oxidation (P < 0.05).
Conclusion: We demonstrate that chronic training subtly coregulates numerous genes from important functional groups that may be part of the long-term adaptive process to adapt to repeated training stimuli.
1Department of Physiology, Monash University, Clayton, Victoria, AUSTRALIA; 2Centre for Aging, Rehabilitation, Exercise and Sport, Victoria University, Melbourne AUSTRALIA; 3Exercise Metabolism Group, School of Medical Sciences, RMIT University, Bundoora, Victoria, AUSTRALIA; 4Liggins Institute, University of Auckland, Auckland, NEW ZEALAND; and 5Victorian Bioinformatics Consortium, Monash University, Clayton, Victoria, AUSTRALIA
Address for correspondence: Nigel K. Stepto, Ph.D., Exercise Physiology Centre for Aging, Rehabilitation, Exercise and Sport, School of Sport and Exercise Science, Victoria University, PO Box 14428, Melbourne, Victoria, 8001, Australia; E-mail: email@example.com.
Submitted for publication October 2007.
Accepted for publication August 2008.