DNA methylation in human epigenomes depends on local topology of CpG sites

Abstract

In vertebrates, methylation of cytosine at CpG sequences is implicated in stable and heritable patterns of gene expression. The classical model for inheritance, in which individual CpG sites are independent, provides no explanation for the observed non-random patterns of methylation. We first investigate the exact topology of CpG clustering in the human genome associated to CpG islands. Then, by pooling genomic CpG clusters on the basis of short distances between CpGs within and long distances outside clusters, we show a strong dependence of methylation on the number and density of CpG organization. CpG clusters with fewer, or less densely spaced, CpGs are predominantly hyper-methylated, while larger clusters are predominantly hypo-methylated. Intermediate clusters, however, are either hyper- or hypo-methylated but are rarely found in intermediate methylation states. We develop a model for spatially-dependent collaboration between CpGs, where methylated CpGs recruit methylation enzymes that can act on CpGs over an extended local region, while unmethylated CpGs recruit demethylation enzymes that act more strongly on nearby CpGs. This model can reproduce the effects of CpG clustering on methylation and produces stable and heritable alternative methylation states of CpG clusters, thus providing a coherent model for methylation inheritance and methylation patterning.

Strategies for analyzing bisulfite sequencing data

“…On the other hand, many gene-body regions are extensively methylated and CpG-poor . These observations would describe a bimodal model of either hyper-or hypomethylated regions dependent on the local density of CpGs (Lövkvist et al, 2016). However, given the detection of CpG-poor regions with locally reduced levels of methylation (on average 30%) in pluripotent embryonic stem cells and in neuronal progenitors in both mouse and human, a different model seems also reasonable (Stadler et al, 2011).…”

“…The internal data apart from meta information has a tabular structure storing chromosome, start/end position, strand information of the associated CpG base just like many other biological formats like BED, GFF or SAM. By exporting this tabular data into a TAB-delimited file and making sure it is accordingly position-sorted it can be indexed using the generic Tabix tool (Lövkvist et al, 2016). In general "Tabix indexing is a generalization of BAM indexing for generic TAB-delimited files.…”

A Bayesian Approach for Analysis of Whole-Genome Bisulfite Sequencing Data Identifies Disease-Associated Changes in DNA Methylation

“…Briefly, in our ABBA analysis of the macrophage methylome, we used the following (default) settings: a minimum of five CpG, and at least 33% difference in DNA methylation between the disease and control macrophages to identify DMRs. This choice was motivated and supported by data on the local topology of CpG sites in the methylome, showing that the vast majority of the CpG clusters are in the range of 1–11 CpGs (Lövkvist et al 2016), and to increase true positive rate in our DM analysis, following previous assessment and recommendations for methylation analysis using WGBS data (Ziller et al 2015). …”

“…In particular, the automatic adaptation to different correlation structures in CpG methylation levels (without requiring user-defined parameters about the degree of smoothing), as well as the ability of modeling its decay as a function of the genomic distances between CpGs allow ABBA to adapt routinely to methylation changes that occur with different scales and at nonuniform rates across the genome. The importance of the genomic context in the methylome, and the local topology of CpG sites have been recently investigated, showing, among other features, that methylation at small CpG clusters is more likely to induce stable changes in DNA methylation (Lövkvist et al 2016). …”

Noise-induced polarization switching in complex networks

“…In recent work it has been shown that the dynamics in such systems can often lead to bistable system states, where constituents jointly reach a polarized state, e.g., fully methylated or unmethylated configurations in DNA methylation [2,22]. In social networks, one individual may influence another's opinion.…”