Dataset Information

The Influence of Hydroxylation on Maintaining CpG Methylation Patterns: A Hidden Markov Model Approach.

ABSTRACT: DNA methylation and demethylation are opposing processes that when in balance create stable patterns of epigenetic memory. The control of DNA methylation pattern formation by replication dependent and independent demethylation processes has been suggested to be influenced by Tet mediated oxidation of 5mC. Several alternative mechanisms have been proposed suggesting that 5hmC influences either replication dependent maintenance of DNA methylation or replication independent processes of active demethylation. Using high resolution hairpin oxidative bisulfite sequencing data, we precisely determine the amount of 5mC and 5hmC and model the contribution of 5hmC to processes of demethylation in mouse ESCs. We develop an extended hidden Markov model capable of accurately describing the regional contribution of 5hmC to demethylation dynamics. Our analysis shows that 5hmC has a strong impact on replication dependent demethylation, mainly by impairing methylation maintenance.

SUBMITTER: Giehr P

PROVIDER: S-EPMC4880293 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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The Influence of Hydroxylation on Maintaining CpG Methylation Patterns: A Hidden Markov Model Approach.

Giehr Pascal P Kyriakopoulos Charalampos C Ficz Gabriella G Wolf Verena V Walter Jörn J

PLoS computational biology 20160525 5

DNA methylation and demethylation are opposing processes that when in balance create stable patterns of epigenetic memory. The control of DNA methylation pattern formation by replication dependent and independent demethylation processes has been suggested to be influenced by Tet mediated oxidation of 5mC. Several alternative mechanisms have been proposed suggesting that 5hmC influences either replication dependent maintenance of DNA methylation or replication independent processes of active deme ...[more]

PMID: 27224554

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Project description:Individual variation in maternal care in mammals shows a significant heritable component, with the maternal behavior of daughters resembling that of their mothers. In laboratory mice, genetically distinct inbred strains show stable differences in maternal care during the first postnatal week. Moreover, cross fostering and reciprocal breeding studies demonstrate that differences in maternal care between inbred strains persist in the absence of genetic differences, demonstrating a non-genetic or epigenetic contribution to maternal behavior. In this study we applied a mathematical tool, called hidden Markov model (HMM), to analyze the behavior of female mice in the presence of their young. The frequency of several maternal behaviors in mice has been previously described, including nursing/grooming pups and tending to the nest. However, the ordering, clustering, and transitions between these behaviors have not been systematically described and thus a global description of maternal behavior is lacking. Here we used HMM to describe maternal behavior patterns in two genetically distinct mouse strains, C57BL/6 and BALB/c, and their genetically identical reciprocal hybrid female offspring. HMM analysis is a powerful tool to identify patterns of events that cluster in time and to determine transitions between these clusters, or hidden states. For the HMM analysis we defined seven states: arched-backed nursing, blanket nursing, licking/grooming pups, grooming, activity, eating, and sleeping. By quantifying the frequency, duration, composition, and transition probabilities of these states we were able to describe the pattern of maternal behavior in mouse and identify aspects of these patterns that are under genetic and nongenetic inheritance. Differences in these patterns observed in the experimental groups (inbred and hybrid females) were detected only after the application of HMM analysis whereas classical statistical methods and analyses were not able to highlight them.

Dataset Information

The Influence of Hydroxylation on Maintaining CpG Methylation Patterns: A Hidden Markov Model Approach.

Publications

The Influence of Hydroxylation on Maintaining CpG Methylation Patterns: A Hidden Markov Model Approach.

Similar Datasets

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