Simplified data access on human skeletal muscle transcriptome responses to differentiated exercise

Abstract

Few studies have investigated exercise-induced global gene expression responses in human skeletal muscle and these have typically focused at one specific mode of exercise and not implemented non-exercise control models. However, interpretation on effects of differentiated exercise necessitate direct comparison between essentially different modes of exercise and the ability to identify true exercise effect, necessitate implementation of independent non-exercise control subjects. Furthermore, muscle transcriptome data made available through previous exercise studies can be difficult to extract and interpret by individuals that are inexperienced with bioinformatics procedures. In a comparative study, we therefore; (1) investigated the human skeletal muscle transcriptome responses to differentiated exercise and non-exercise control intervention, and; (2) set out to develop a straightforward search tool to allow for easy access and interpretation of our data. We provide a simple-to-use spread sheet containing transcriptome data allowing other investigators to easily see how mRNA of their gene(s) of interest behave in skeletal muscle following exercise, both endurance, resistance and non-exercise, to better aid hypothesis-driven question in this field of research.

Figure 1. Experimental design.

Three individual groups of human subjects had a biopsy taken prior to commencing 10 weeks of intervention (Pre). They then completed 10 weeks of intervention as either endurance, resistance or no training. After several days of recovery, subjects reported at the same time point of the day to the laboratory for±single-bout exercise, in which they conducted either endurance exercise (i.e., 2 h of cycling at 60% aerobic intensity), resistance exercise (i.e., rested for 1$\frac{1}{2}$ h followed by a 30 min session including 4 sets x 12 repetitions for three leg exercises) or no exercise (i.e., the subjects rested for 2 h). Biopsies were harvested at the same absolute time points prior to (i.e. similar to post training) and at 0, 2$\frac{1}{2}$, 5 and 22 h post±exercise. RNA was extracted and RNA from time points corresponding to Pre, 2$\frac{1}{2}$ and 5 h (time points for array analysis marked in red in the graph) were hybridized to GeneChip arrays followed by bioinformatics procedures and development of a search tool to allow simplified data access. In parallel, RNA from all time points were included in cDNA synthesis to be used for validation of array data by Real-time PCR.

Figure 2. RT-PCR.

Comparison of results obtained from the microarray data with results obtained using standard real-time RT–PCR. Only time-points Pre and 2$\frac{1}{2}$ and 5 h Post final exercise session are measured with microarrays (Left). All time-points were measured with real-time RT-PCR (Right). MYOG (Myogenin) and EIF2AK3 (eukaryotic translation initiation factor 2-alpha kinase 3) were identified as strength specific and JUND (Jun D) as exercise specific, but dependent on exercise type. Data are shown as geometric mean±back-transformed s.e.m. on a logarithmic axis (log2).

Figure 3. Example.

Illustration of the graphs that can easily be generated for a specific mRNA using the Excel file. In this case the VEGFA mRNA. Besides getting the graphs, the statistical result is also provided, here showing that VEGFA mRNA is differentially regulated by exercise (Differential Exercise) and that within the Endurance group both 2.5 and 5 h are significantly different from Pre (E2.5h and E5h), whereas for the Strength group only 5 h is significant (S5h). Furthermore, within 2.5 h Endurance is different from both Control (EvC2.5h) and Strength (SvE2.5h), whereas at 5 h Endurance is only significantly different from Control (EvC5h) but not Strength (no SvE5h). On the other hand also Strength is different from Control at 5 h (SvC5h).