A new study has re-analyzed data obtained by whole genome bisulfate sequencing (WGBS) using the newly developed regional analysis approach known as SOMNiBUS and achieved additional insights into the cytosine DNA methylation patterns and pathogenesis of systemic sclerosis (SSc).
The study, published in Clinical Epigenetics, also found their approach generated nucleotide-level data on SSc-associated gene methylation.
“Currently, the most comprehensive assay for profiling DNA methylation is whole-genome bisulfite sequencing [WGBS], but its precision depends on read depth and it may be subject to sequencing errors,” the authors wrote. “Using SOMNiBUS, we re-analyzed WGBS data previously analyzed using bumphunter, an approach that initially fits single CpG associations, to contrast DNA methylation estimates by both methods.”
Given that abnormal DNA methylation is thought to underlie the onset and progression of SSC, the research team compared the data obtained on methylation status obtained from two different but complementary molecular approaches.
Read more about SSc diagnosis
First, they obtained purified CD4+ T lymphocytes from 9 female patients with SSc and 4 controls and sequenced them using the bumphunter WGBS technique. Next, the sequencing data was divided into regions of dense CpG data and SOMNiBUS was employed to infer the differentially methylated regions (DMRs) and their overlap.
As expected, the results clearly revealed differential methylation between cells from patients with SSC and those from controls. Furthermore, the analysis identified new loci of differential methylation associated with SSC. The SOMNiBUS approach uncovered 131 DMRs and 125 differentially methylated genes (DMGs), while bumphunter identified 599 DMRs and 340 DMGs.
The authors caution that direct comparisons between SOMNiBUS and bumphunter are challenging due to the differences in region construction between the two methods. However, by looking at the overlap in the results from both methods, they were able to achieve a wider range of data specific to the methylation patterns found in cells from patients with SSc, thereby suggesting new avenues of research into the pathogenesis of this condition.
Reference
Yu JCY, Zeng Y, Zhao K. et al. Novel insights into systemic sclerosis using a sensitive computational method to analyze whole-genome bisulfite sequencing data. Clin Epigenet. Published online June 3, 2023. doi.10.1186/s13148-023-01513-w
