Abstract
BackgroundIn vertebrate genomes, CpG sites can be clustered into CpG islands, and the amount of methylation in a CpG island can change due to gene regulation processes. Thus, single regulatory events can simultaneously change the methylation states of many CpG sites within a CpG island. This should be taken into account when quantifying the amount of change in methylation, for example in form of a branch length in a phylogeny of cell types.ResultsWe propose a probabilistic model (the IWE-SSE 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 (MCMC) method to fit this model to methylation data from cell type phylogenies and apply this method to available data from murine haematopoietic cells and from human cell lines. Combined with simulation studies, these analyses 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 and human cell lines.ConclusionThe MCMC based parameter estimation method for the IWE-SSE model in combination with our MCMC based inference method allows to quantify the amount of methylation changes at single CpG sites as well as on entire CpG islands. Accounting for changes affecting entire islands can lead to more accurate branch length estimation in the presence of simultaneous methylation change.
Highlights
In vertebrate genomes, CpG sites can be clustered into CpG islands, and the amount of methylation in a CpG island can change due to gene regulation processes
With Restricted Bisulfite Sequencing (RRBS) data procured from mouse haematopoiesis [2, 4] we demonstrate that accounting for island-wide events (IWE) can lead to significantly different estimations of branch lengths of cell type genealogies
Structure of our methylation-demethylation model We take into account that several CpGs can form a CpG island, which can be affected by CpG island wide events (IWEs), in which methylation probabilities change and some of the CpG sites in the CpG island can simultaneously change their state at the same time
Summary
We aim to both take simultaneous methylation changes into account and to propose a model that is at the same time simple enough for inference on large datasets with data from several cell types. We aim to fill the gap in the literature where models have so far either just considered evolution of single sites [4], or concerned themselves with inference on smaller scales [19, 21, 24]
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