The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Analysis of global mRNA expression in human skeletal muscle during recovery from endurance exercise
Abstract
To search for novel transcriptional pathways that are activated in skeletal muscle after endurance exercise, we used cDNA microarrays to measure global mRNA expression after an exhaustive bout of high‐intensity cycling (∼75 min). Healthy, young, sedentary males performed the cycling bout, and skeletal muscle biopsies were taken from the vastus lateralis before, and at 3 and 48 h after exercise. We examined mRNA expression in individual muscle samples from four subjects using cDNA microarrays, used repeated‐measures significance analysis of microarray (SAM) to determine statistically significant expression changes, and confirmed selected results using real‐time RT‐PCR. In total, the expression of 118 genes significantly increased 3 h postcycling and 8 decreased. At 48 h, the expression of 29 genes significantly increased and 5 decreased. Many of these are potentially important novel genes involved in exercise recovery and adaptation, including several involved in 1 ) metabolism and mitochondrial biogenesis (FOXO1, PPARδ, PPARγ, nuclear receptor binding protein 2, IL‐6 receptor, ribosomal protein L2, aminolevulinate δ‐synthase 2); 2 ) the oxidant stress response (metalothioneins 1B, 1F, 1G, 1H, 1L, 2A, 3, interferon regulatory factor 1); and 3 ) electrolyte transport across membranes [Na + ‐K + ‐ATPase (β3), SERCA3, chloride channel 4]. Others include genes involved in cell stress, proteolysis, apoptosis, growth, differentiation, and transcriptional activation, as well as all three nuclear receptor subfamily 4A family members (Nur77, Nurr1, and Nor1). This study is the first to characterize global mRNA expression during recovery from endurance exercise, and the results provide potential insight into 1 ) the transcriptional contributions to homeostatic recovery in human skeletal muscle after endurance exercise, and 2 ) the transcriptional contributions from a single bout of endurance exercise to the adaptive processes that occur after a period of endurance exercise training.
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Cites
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860
(2004) · doi:10.1016/s0092-8674(04)00452-0 · Cited by 1,356
Transcriptional regulation of gene expression in human skeletal muscle during recovery from exercise
Pilegaard, H., Ordway, G. A., Saltin, B., & Neufer, P. D. (2000) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.2000.279.4.e806 · Cited by 563
Peroxisome proliferator‐activated receptor δ controls muscle development and oxydative capability
Luquet, S., Lopez‐Soriano, J., Holst, D., Fredenrich, A., Melki, J., Rassoulzadegan, M., & Grimaldi, P. A. (2003) · The FASEB Journal · doi:10.1096/fj.03-0269fje · Cited by 509
Norris, A. W., Chen, L., Fisher, S. J., Szanto, I., Ristow, M., Jozsi, A. C., Hirshman, M. F., Rosen, E. D., Goodyear, L. J., Gonzalez, F. J., et al. (2003) · Journal of Clinical Investigation · doi:10.1172/jci17305 · Cited by 417
Carbohydrate and the cytokine response to 2.5 h of running
Nehlsen-Cannarella, S. L., Fagoaga, O. R., Nieman, D. C., Henson, D. A., Butterworth, D. E., Schmitt, R. L., Bailey, E. M., Warren, B. J., Utter, A., & Davis, J. M. (1997) · Journal of Applied Physiology · doi:10.1152/jappl.1997.82.5.1662 · Cited by 311
Exercise training increases lipid metabolism gene expression in human skeletal muscle
Tunstall, R. J., Mehan, K. A., Wadley, G. D., Collier, G. R., Bonen, A., Hargreaves, M., & Cameron-Smith, D. (2002) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00475.2001 · Cited by 292
Rome, S., Clément, K., Rabasa-Lhoret, R., Loizon, E., Poitou, C., Barsh, G. S., Riou, J.-P., Laville, M., & Vidal, H. (2003) · Journal of Biological Chemistry · doi:10.1074/jbc.m300293200 · Cited by 187
Fischer, C. P., Plomgaard, P., Hansen, A. K., Pilegaard, H., Saltin, B., & Pedersen, B. K. (2004) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00206.2004 · Cited by 165
Chen, Y., Nader, G. A., Baar, K. R., Fedele, M. J., Hoffman, E. P., & Esser, K. A. (2002) · The Journal of Physiology · doi:10.1113/jphysiol.2002.021220 · Cited by 158
Modulation of carbohydrate and fat utilization by diet, exercise and environment
Jeukendrup, A. E. (2003) · Biochemical Society Transactions · doi:10.1042/bst0311270 · Cited by 143
Kiens, B., Roepstorff, C., Glatz, J. F. C., Bonen, A., Schjerling, P., Knudsen, J., & Nielsen, J. N. (2004) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01278.2003 · Cited by 143
Roepstorff, C., Wulff Helge, J., Vistisen, B., & Kiens, B. (2004) · Proceedings of the Nutrition Society · doi:10.1079/pns2004332 · Cited by 54
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Egan, B., & Zierath, J. R. (2013) · Cell Metabolism · doi:10.1016/j.cmet.2012.12.012 · Cited by 2,084
AMPK and PPARδ Agonists Are Exercise Mimetics
Narkar, V. A., Downes, M., Yu, R. T., Embler, E., Wang, Y.-X., Banayo, E., Mihaylova, M. M., Nelson, M. C., Zou, Y., Juguilon, H., et al. (2008) · Cell · doi:10.1016/j.cell.2008.06.051 · Cited by 1,222
Gibala, M. J., Little, J. P., Van Essen, M., Wilkin, G. P., Burgomaster, K. A., Safdar, A., Raha, S., & Tarnopolsky, M. A. (2006) · The Journal of Physiology · doi:10.1113/jphysiol.2006.112094 · Cited by 1,082
Self-citationExercise is the real polypill.
Fiuza-Luces, C., Garatachea, N., Berger, N. A., & Lucia, A. (2013) · Physiology · doi:10.1152/physiol.00019.2013 · Cited by 791
Metadata
- Authors
- Mahoney, D. J., Parise, G., Melov, S., Safdar, A., & Tarnopolsky, M. A.
- Venue
- The FASEB Journal
- Publisher
- Wiley
- Published
- 2005-06-28
- Volume
- 19
- Issue
- 11
- Pages
- 1498-1500
- ISSN
- 0892-6638 (ISSN-L)
- 1530-6860
- OpenAlex
- W2137574569
- Cited by
- 426
- References
- 13
- FWCI
- 21.18
- Type
- journal article
- Language
- en
- Open access
- closed
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