There’s no denying the power of technology in our lives, whether it be your latest and greatest iPhone bending in your pocket or it be getting the technology to do something more useful, like predict the entire epigenome and how it functions in the regulation of gene expression. We’ve always loved a good tool and/or database, and have told you about ways to predict histone mods from DNA sequence but now an even newer player from Wei Wang’s lab at UCSD can predict all your DNA methylation patterns in addition to histone mods from just DNA motifs.
Here’s what Epigram can do for you:
- It offers an analysis pipeline that predicts histone mods and DNAm from DNA motifs, taking advantage of the motif based specificity of epigenomic modifying complexes.
- Using Epigram to catalogue the cis elements in embryonic stem cells and derived lineages, the team found a number of location preferences for certain DNA motifs within the epigenetic landscape, including:
- A motif that loves the centre of H3K27ac
- Another motif living on the edges of H3K4me3 and H3K9me3
Lead author John Whitaker shares his outlook that “When coupled with genome editing technologies (Crispr/Cas9, TALENs), Epigram will allow scientists to make small changes to the genome that alter the DNA motifs that I have identified and cause in changes to the epigenome. This process is called ‘epigenome editing‘ and will allow scientists to design very controlled experiments that characterize the specific roles of regulators in defining cell type specific roles of gene expression.
For example, DNA motifs that are predictive of H3K27ac could be altered within a regulatory enhancer region. As H3K27ac levels are linked to enhancer activity, these changes should reduce the activity of the enhancer and in turn the expression levels of the enhancers target genes. Looking beyond this, I think it’s likely that many sequence variants that are linked to disease (GWAS hits), will be found to take their effect by altering DNA motifs that are bound by epigenomic regulators. Ultimately, these variants might be corrected by combining stem cell technologies and genome-editing strategies.”