New results from our interdisciplinary work are now online.
The recently published article, entitled “
The investigation used experimental tissue samples from laboratory rats. The tibialis anterior muscle in rats was silenced with tetrodotoxin to reduce the muscle mass over different periods of time and then allowed to recover, such that the fraction of restored muscle mass after seven days of recovery, during which the rats resumed habitual physical activity, could be measured and compared to a control sample. A transcriptome-wide analysis demonstrated that 3714 genes were differentially expressed across all conditions after disuse-induced atrophy. The most differentially expressed genes after microarray analysis were identified across all conditions and were cross-referenced with the most frequently occurring differentially expressed genes between conditions. Transcript expression of these genes and another specific gene (Fboxo32/MAFbx), of interest due to a known link with disuse atrophy, were analysed to identify which genes showed significant changes in gene expression during recovery. In fact, some genes demonstrated significantly decreased DNA methylation at key time points after disuse-induced atrophy, that corresponded with significantly increased gene expression. This is the first study to demonstrate that skeletal muscle atrophy in response to disuse is accompanied by epigenetic modifications that are associated with alterations in gene expression, and that these epigenetic modifications and gene expression profiles are reversible by returning to normal activity.
Part of the data analysis was performed with MethylCal, a bespoke Python-based program designed to aid the analysis of such experiments in epigenetics. MethylCal determines the calibration solution between the known concentration of methylated DNA in standard laboratory samples and several observed properties, and then applies this calibration to the experimental DNA samples, enabling us to trace the level of gene expression. Examining the varying methylation concentrations of experimental samples exposed to different conditions therefore allows us to determine the important factors affecting gene expression.
In this recent work, MethylCal was used to analyse the results obtained via high-resolution melting (HRM) and hence determine whether some gene tests were sent for further follow-up using a more sophisticated method of determining the methylation concentration: pyrosequencing. This method allows the methylated regions of a sample to be sequenced and gives a more quantitative calculation of the methylation calculation for a specific site of the gene region, rather than a global percentage methylation concentration for the entire region. (For my colleagues in extragalactic astronomy, consider it like measuring the star formation rates in individual HII regions within the disk of a galaxy, rather than integrating everything across the disk to obtain the global star formation rate.) Samples that showed no methylation with the HRM analysis were excluded from further study, whereas those with some level of methylation were sent for pyrosequencing.