Modeling DNA Methylation Profiles through a Dynamic Equilibrium between Methylation and Demethylation

Abstract

DNA methylation is a heritable epigenetic mark that plays a key role in regulating gene expression. Mathematical modeling has been extensively applied to unravel the regulatory mechanisms of this process. In this study, we aimed to investigate DNA methylation by performing a high-depth analysis of particular loci, and by subsequent modeling of the experimental results. In particular, we performed an in-deep DNA methylation profiling of two genomic loci surrounding the transcription start site of the D-Aspartate Oxidase and the D-Serine Oxidase genes in different samples (n = 51). We found evidence of cell-to-cell differences in DNA methylation status. However, these cell differences were maintained between different individuals, which indeed showed very similar DNA methylation profiles. Therefore, we hypothesized that the observed pattern of DNA methylation was the result of a dynamic balance between DNA methylation and demethylation, and that this balance was identical between individuals. We hence developed a simple mathematical model to test this hypothesis. Our model reliably captured the characteristics of the experimental data, suggesting that DNA methylation and demethylation work together in determining the methylation state of a locus. Furthermore, our model suggested that the methylation status of neighboring cytosines plays an important role in this balance.

5-methylcytosine turnover: Mechanisms and therapeutic implications in cancer

“…DNA methylation is tightly controlled by DNMTs and TETs which are, despite their opposing activities, both expressed during ESCs differentiation into somatic lineages. This co-expression leads to genome-scale oscillatory dynamics and cell-to-cell heterogeneity further impacting gene expression ( Gu et al, 2018 ; Rulands et al, 2018 ; De Riso et al, 2020 ). TET activity has been found to require DNMT3 expression to keep steady-state DNA methylation levels in the genome of pluripotent ESCs ( Charlton et al, 2020 ).…”

“…DNA methylation steady state is defined as the equilibrium of DNA methylation levels reached when the average methylation rates are similar to demethylation ones ( Figure 2A ) ( Ginno et al, 2020 ). The steady state is itself characterized by DNA methylation turnover referred as different combinations of enzymatic rates of methylation/demethylation, suggesting that CpGs with a similar steady state can vary from each other by having distinct methylation/demethylation rate values ( De Riso et al, 2020 ; Ginno et al, 2020 ). DNA methylation turnover is very active through cell fate transition and the high oscillatory methylation dynamic observed appears to be context-specific in the genome ( Figure 2B ).…”

“…Actually, DNA methylation and TFs binding act in a synergistic manner to regulate the spatio temporal expression of genes and chromatin remodeling, leading to local DNA methylation changes. Zinc finger cysteine-X-X-cysteine (ZF-CXXC) domain-containing proteins specifically target unmethylated CpGs at CGIs which are commonly hypomethylated and where they have chromatin-modifying activities ( Gu et al, 2018 ; Van De Lagemaat et al, 2018 ; De Riso et al, 2020 ). The first CXXC domain containing protein to have been discovered in mammals a few years ago is the CXXC finger protein 1 (CPF1), a key component of the SETD1 (SET domain 1) H3K4 methyltransferase complex responsible for H3K4 methylation ( Clouaire et al, 2012 ).…”

“…To get through the challenges faced by bulk measurements and sequence dependent approaches, novel experimental methods combining single-cell sequencing, modeling, and knock-out of (de)methylation enzymes revealed highly dynamic methylation changes in early development both in vitro and in vivo ( Rulands et al, 2018 ; Song et al, 2019 ; Charlton et al, 2020 ; De Riso et al, 2020 ; Shi et al, 2021 ). The co-engagement of DNMTs and TET enzymes on the same DNA molecule has been evidenced not long ago by Rulands et al by using single-cell sequencing and a modelling method.…”

MC profiling: a novel approach to analyze DNA methylation heterogeneity from bulk bisulfite sequencing data

“…In previous studies, we directly estimated the distribution of MCs at targeted loci analyzed through high-depth amplicon bisulfite sequencing, thus obtaining information on the regulatory mechanisms of DNA methylation (41,42).…”