Hidden Markov Modelling Reveals Neighborhood Dependence of Dnmt3a and 3b Activity

Abstract

DNA methylation is an epigenetic mark whose important role in development has been widely recognized. This epigenetic modification results in heritable information not encoded by the DNA sequence. The underlying mechanisms controlling DNA methylation are only partly understood. Several mechanistic models of enzyme activities responsible for DNA methylation have been proposed. Here, we extend existing Hidden Markov Models (HMMs) for DNA methylation by describing the occurrence of spatial methylation patterns over time and propose several models with different neighborhood dependences. Furthermore, we investigate correlations between the neighborhood dependence and other genomic information. We perform numerical analysis of the HMMs applied to comprehensive hairpin and non-hairpin bisulfite sequencing measurements and accurately predict wild-type data. We find evidence that the activities of Dnmt3a and Dnmt3b responsible for de novo methylation depend on 5’ (left) but not on 3’ (right) neighboring CpGs in a sequencing string.

@article{luckHiddenMarkovModellingReveals2019,
 author = {Alexander Lück and Pascal Giehr and Karl Nordström and Jörn Walter and Verena Wolf},
 doi = {10.1109/TCBB.2019.2910814},
 journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)},
 month = {4},
 number = {5},
 pages = {1598-1609},
 publisher = {IEEE},
 title = {Hidden Markov Modelling Reveals Neighborhood Dependence of Dnmt3a and 3b Activity},
 volume = {16},
 year = {2019}
}