MethGET: web-based bioinformatics software for correlating genome-wide DNA methylation and gene expression

Abstract

Background: DNA methylation is a major epigenetic modification involved in regulating gene expression. The effects of DNA methylation on gene expression differ by genomic location and vary across kingdoms, species and environmental conditions. To identify the functional regulatory roles of DNA methylation, the correlation between DNA methylation changes and alterations in gene expression is crucial. With the advance of next-generation sequencing, genome-wide methylation and gene expression profiling have become feasible. Current bioinformatics tools for investigating such correlation are designed to the assessment of DNA methylation at CG sites. The correlation of non-CG methylation and gene expression is very limited. Some bioinformatics databases allow correlation analysis, but they are limited to specific genomes such as that of humans and do not allow userprovided data. Results: Here, we developed a bioinformatics web tool, MethGET (Methylation and Gene Expression Teller), that is specialized to analyse the association between genome-wide DNA methylation and gene expression. MethGET is the first web tool to which users can supply their own data from any genome. It is also the tool that correlates gene expression with CG, CHG, and CHH methylation based on whole-genome bisulfite sequencing data. MethGET not only reveals the correlation within an individual sample (single-methylome) but also performs comparisons between two groups of samples (multiple-methylomes). For single-methylome analyses, MethGET provides Pearson correlations and ordinal associations to investigate the relationship between DNA methylation and gene expression. It also groups genes with different gene expression levels to view the methylation distribution at specific genomic regions. Multiple-methylome analyses include comparative analyses and heatmap representations between two groups. These functions enable the detailed investigation of the role of DNA methylation in gene regulation. Additionally, we applied MethGET to rice regeneration data and discovered that CHH methylation in the gene body region may play a role in the tissue culture process, which demonstrates the capability of MethGET for use in epigenomic research.

Air pollution-induced epigenetic changes: disease development and a possible link with hypersensitivity pneumonitis

“…MethHC databases can also be utilized to visualize DNA methylation and gene expression on a web platform (Huang et al 2015). MethGET is another web-based bioinformatics platform that correlates genomewide DNA methylation and gene expression (Teng et al 2020). The Gene-Ontology (GO) database provides a useful tool to analyse the functions of all dysregulated genes (Harris et al 2004).…”

Multi-omics data integration reveals link between epigenetic modifications and gene expression in sugar beet (Beta vulgaris subsp. vulgaris) in response to cold

“…Integration of gene expression and DNA methylation additionally requires consideration of sequence contexts of cytosines while discriminating between different types of genomic features affected by methylation. We used MethGet to assess associations between expression and methylation for each replicate, individually [ 48 ]. Gene expression data was normalized for transcript length to allow for the comparison of gene expression within samples.…”

Epigenomic and transcriptomic analyses reveal early activation of the HPG axis in in vitro‐produced male dairy calves

“…The overall correlations between DNA methylation level changes and gene expression changes between both groups of samples were determined with MethGET, 43 through Pearson's correlation coefficient. Briefly, the Cytosine reports generated by Bismark were converted to a CGmap format using a script provided by the software.…”