Identification of DNA motifs that regulate DNA methylation

Abstract

DNA methylation is an important epigenetic mark but how its locus-specificity is decided in relation to DNA sequence is not fully understood. Here, we have analyzed 34 diverse whole-genome bisulfite sequencing datasets in human and identified 313 motifs, including 92 and 221 associated with methylation (methylation motifs, MMs) and unmethylation (unmethylation motifs, UMs), respectively. The functionality of these motifs is supported by multiple lines of evidence. First, the methylation levels at the MM and UM motifs are respectively higher and lower than the genomic background. Second, these motifs are enriched at the binding sites of methylation modifying enzymes including DNMT3A and TET1, indicating their possible roles of recruiting these enzymes. Third, these motifs significantly overlap with “somatic QTLs” (quantitative trait loci) of methylation and expression. Fourth, disruption of these motifs by mutation is associated with significantly altered methylation level of the CpGs in the neighbor regions. Furthermore, these motifs together with somatic mutations are predictive of cancer subtypes and patient survival. We revealed some of these motifs were also associated with histone modifications, suggesting a possible interplay between the two types of epigenetic modifications. We also found some motifs form feed forward loops to contribute to DNA methylation dynamics.

Accurate prediction ofcis-regulatory modules reveals a prevalent regulatory genome of humans

“…It has been shown that GWAS SNVs systematically disrupt binding sites of TFs related to the traits ( 8 ), and that variation in TFBSs affects DNA binding, chromatin modification, transcription ( 9–11 ), and susceptibility to complex diseases ( 12 , 13 ) including cancer ( 14–17 ). In principle, variation in a CRM may result in changes in the affinity and interactions between TFs and cognate binding sites, thereby altering histone modifications and target gene expressions in relevant cells ( 18 , 19 ). Such alterations in molecular phenotypes can change cellular and organ-related phenotypes ( 20 , 21 ).…”

Accurate prediction of cis-regulatory modules reveals a prevalent regulatory genome of humans

“…It has been shown that complex trait-associated variants systematically disrupt TFBSs of TFs related to the traits (Maurano et al, 2012), and that variation in TFBSs affects DNA binding, chromatin modification, transcription(Kasowski et al, 2013; Kilpinen et al, 2013; McVicker et al, 2013), and susceptibility to complex diseases(Mathelier, Shi, & Wasserman, 2015; Smith & Shilatifard, 2014) including cancer(Herz, Hu, & Shilatifard, 2014; Khurana et al, 2016; Ongen et al, 2014; Zhou, Treloar, & Lupien, 2016). In principle, variation in a CRM may result in changes in the affinity and interactions between TFs and their binding sites, leading to alterations in histone modifications and target gene expressions in relevant cells(M. Wang et al, 2019; Whitaker, Chen, & Wang, 2015). These alterations in molecular phenotypes can lead to changes in cellular and organ-related phenotypes among individuals of a species(Pai, Pritchard, & Gilad, 2015; Ward & Kellis, 2012).…”

Evolutionary Stability Optimizer (ESO): A Novel Approach to Identify and Avoid Mutational Hotspots in DNA Sequences While Maintaining High Expression Levels

“…al. 28 PSSMs are a commonly used tool in computational biology for the identification of motifs, in which the probability of each nucleotide in a subsequence is calculated in a position-dependent manner. Our software is designed to be modular, providing support for updated or different optimization requirements; users may provide their own PSSM matrices for sites to be avoided, providing greater customizability for unique engineering needs.…”