MicroRNAs (miRNA) are small non-coding RNAs that function as post-transcriptional repressors of gene expression. MicroRNAs silence mRNA translation by direct repression and/or mRNA decay, ultimately influencing protein abundance. However, a single miRNA can target multiple genes; likewise, multiple miRNAs can impact a single transcript, complicating a relatively simple process. MicroRNA research is likely to be clinically relevant since miRNAs regulate nearly two-thirds, if not all, of the mammalian genome (Friedman et al. 2009), highlighting miRNAs as a novel target to manipulate gene expression and perhaps control disease. Since the discovery of miRNAs in 1993 in C. elegans (Lee et al. 1993), interest in miRNA biology has been on the rise. A quick search on Pubmed indicates that ∼9000 articles have been published in this area prior to mid-2010, with a peak increase in 2009. The miRNA research in human skeletal muscle is incredibly limited and that involving exercise is nearly non-existent.
MicroRNAs are ubiquitously expressed in a broad range of tissues while some miRNAs are tissue-specific. Muscle-specific miRNAs (myomiRs), miR-1, -133a, -133b and -206, are appropriately termed because elevated expression is limited primarily to striated muscle (Beuvink et al. 2007), indicating that they may regulate tissue specificity and function. Unfortunately, little is known of the biological role of myomiRs in skeletal muscle or their specific gene targets. At a minimum, it appears that myomiRs may be associated with muscle growth and regeneration (Chen et al. 2006; Nakasa et al. 2009), implicating a potential role in skeletal muscle adaptation to exercise. Indeed, myomiR expression is acutely altered during post-exercise recovery in humans and rats (Drummond et al. 2008; Safdar et al. 2009) while models of muscle overload can significantly alter myomiR expression to new steady state levels (McCarthy & Esser, 2007).
In an article in this issue of The Journal of Physiology, Nielsen et al. (2010) provide intriguing data in skeletal muscle of young men that myomiR expression levels transiently increased 1 h after a bout of endurance exercise while myomiR expression at rest decreased to a new steady state level following 12 weeks of aerobic training, returning to pre-exercise levels following a period of inactivity. Interestingly, muscle-specific miRNA expression levels not only change with exercise but the expression patterns are different following an acute bout of exercise versus at rest following repeated exercise or inactivity. But what do these alterations in miRNA expression mean in light of how the muscle adapts to the demands of physical activity?
As highlighted by Nielsen et al. (2010), making associations between specific miRNAs and a predicted downstream target can be very difficult. In fact, inverse relationships between individual myomiRs and predicted targets, Cdc42 and ERK1/2, could not be determined. This raises some uncertainty or complexity of one-to-one relationships between miRNAs and their targets. Is it possible that miRNAs function collectively to regulate expression of a predicted gene target? As appropriately coined in a recent review, miRNAs may ‘hunt in packs’ (Lanceta et al. 2010). Thus, even modest changes in a group of miRNAs may impact the expression of several (or hundreds) of genes perhaps with a goal of regulating a specific signalling network (e.g. cell cycle control). The complexity of miRNA biology makes it incredibly difficult to deduce relationships between miRNAs and their targets (especially in human models). The use of miRNA and gene arrays complimented by bioinformatics prediction software to indentify groups of miRNAs, related signalling networks, and gene targets may help us make sense of the biological relevance of miRNAs. Furthermore, paralleling human studies with mechanistic cell experiments (functional assays) may significantly aid in validating miRNA targets following exercise.