Using systems biology to define the essential biological networks responsible for adaptation to endurance exercise training

Abstract

We predict that RNA level regulation is as diverse and powerful as protein level regulation when considering physiological adaptation. Non-coding RNA molecules, such as miRNAs (microRNAs), have emerged as a powerful mechanism for post-transcriptional regulation of mRNA. In an effort to define the role of miRNA in human skeletal-muscle biology, we have initiated profiling of muscle RNA before and after endurance exercise training. The robust molecular phenotype of muscle is established using unbiased analysis strategies of the raw data, reflecting the statistical power of gene ontology and network analysis. We can thus determine the structural features of the skeletal-muscle transcriptome, identify discrete networks activated by training and utilize bioinformatics predictions to establish the interaction between non-coding RNA modulation and Affymetrix expression profiles.