Enhancing resolution of natural methylome reprogramming behavior in plants

BackgroundNatural methylome reprogramming within chromatin involves changes in local energy landscapes that are subject to thermodynamic principles. Signal detection permits the discrimination of methylation signal from dynamic background noise that is induced by thermal fluctuation. Current genome-wide methylation analysis methods do not incorporate biophysical properties of DNA, and focus largely on DNA methylation density changes, which limits resolution of natural, more subtle methylome behavior in relation to gene activity.\n\nResultsWe present here a novel methylome analysis procedure, Methyl-IT, based on information thermodynamics and signal detection. Methylation analysis involves a signal detection step, and the method was designed to discriminate methylation regulatory signal from background variation. Comparisons with commonly used programs and two publicly available methylome datasets, involving stages of seed development and drought stress effects, were implemented. Information divergence between methylation levels from different groups, measured in terms of Hellinger divergence, provides discrimination power between control and treatment samples. Differentially informative methylation positions (DIMPs) achieved higher sensitivity and accuracy than standard differentially methylated positions (DMPs) identified by other methods. Differentially methylated genes (DMG) that are based on DIMPs were significantly enriched in biologically meaningful networks.\n\nConclusionsMethyl-IT analysis enhanced resolution of natural methylome reprogramming behavior to reveal network-associated responses, offering resolution of gene pathway influences not attainable with previous methods.