Modeling methylation dynamics with simultaneous changes in CpG islands

MotivationProbabilistic models for methylation dynamics of CpG sites are usually based on sequence evolution models that assume indepedence between sites. In vertebrate genomes, CpG sites can be clustered in CpG islands, and the amount of methylation in a CpG island can change due to gene regulation processes. We propose a probabilistic model of methylation dynamics that accounts for simultaneous methylation changes in multiple CpG sites belonging to the same CpG island. We further propose a Markov-chain Monte-Carlo method to fit this model to methylation data from cell type phylogenies and apply this method to available data from murine haematopoietic cells.\n\nResultsBranch lengths in cell phylogenies show the amount of changes in methylation in the development of one cell type from another. We show that accounting for CpG island wide methylation changes has a strong effect on the inferred branch lengths and leads to a significantly better model fit for the methylation data from murine haematopoietic cells.\n\nAvailabilityAn implementation of the methods presented in this article is freely available as C++ source code on https://github.com//statgenlmu//IWEPoissonPaper under the terms of the GNU general public license (GPLv3).