A novel workflow for the qualitative analysis of DNA methylation data.

DNA methylation is an epigenetic modification that plays a pivotal role in major biological mechanisms, such as gene regulation, genomic imprinting, and genome stability. Different combinations of methylated cytosines for a given DNA locus generate different epialleles and alterations of these latter have been associated with several pathological conditions. Existing computational methods and statistical tests relevant to DNA methylation analysis are mostly based on the comparison of average CpG sites methylation levels and they often neglect non-CG methylation. Here, we present EpiStatProfiler, an R package that allows the analysis of CpG and non-CpG based epialleles starting from bisulfite sequencing data through a collection of dedicated extraction functions and statistical tests. EpiStatProfiler is provided with a set of useful auxiliary features, such as customizable genomic ranges, strand-specific epialleles analysis, locus annotation and gene set enrichment analysis. We showcase the package functionalities on two public datasets by identifying putative relevant loci in mice harboring the Huntington's disease-causing Htt gene mutation and in Ctcf +/- mice compared to their wild-type counterparts. To our knowledge, EpiStatProfiler is the first package providing functionalities dedicated to the analysis of epialleles composition derived from any kind of bisulfite sequencing experiment.

MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data.

DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated cytosines are distributed in each single DNA molecule. Here, we propose Methylation Class (MC) profiling as a genome-wide approach to the study of DNA methylation heterogeneity from bulk bisulfite sequencing experiments. The proposed approach is built on the concept of MCs, groups of DNA molecules sharing the same number of methylated cytosines. The relative abundances of MCs from sequencing reads incorporates the information on the average methylation, and directly informs on the methylation level of each molecule. By applying our approach to publicly available bisulfite-sequencing datasets, we individuated cell-to-cell differences as the prevalent contributor to methylation heterogeneity. Moreover, we individuated signatures of loci undergoing imprinting and X-inactivation, and highlighted differences between the two processes. When applying MC profiling to compare different conditions, we identified methylation changes occurring in regions with almost constant average methylation. Altogether, our results indicate that MC profiling can provide useful insights on the epigenetic status and its evolution at multiple genomic regions.

Epigenetic remodelling of Fxyd1 promoters in developing heart and brain tissues.

FXYD1 is a key protein controlling ion channel transport. FXYD1 exerts its function by regulating Na+/K+-ATPase activity, mainly in brain and cardiac tissues. Alterations of the expression level of the FXYD1 protein cause diastolic dysfunction and arrhythmias in heart and decreased neuronal dendritic tree and spine formation in brain. Moreover, FXYD1, a target of MeCP2, plays a crucial role in the pathogenesis of the Rett syndrome, a neurodevelopmental disorder. Thus, the amount of FXYD1 must be strictly controlled in a tissue specific manner and, likely, during development. Epigenetic modifications, particularly DNA methylation, represent the major candidate mechanism that may regulate Fxyd1 expression. In the present study, we performed a comprehensive DNA methylation analysis and mRNA expression level measurement of the two Fxyd1 transcripts, Fxyd1a and Fxyd1b, in brain and heart tissues during mouse development. We found that DNA methylation at Fxyd1a increased during brain development and decreased during heart development along with coherent changes in mRNA expression levels. We also applied ultra-deep methylation analysis to detect cell to cell methylation differences and to identify possible distinct methylation profile (epialleles) distribution between heart and brain and in different developmental stages. Our data indicate that the expression of Fxyd1 transcript isoforms inversely correlates with DNA methylation in developing brain and cardiac tissues suggesting the existence of a temporal-specific epigenetic program. Moreover, we identified a clear remodeling of epiallele profiles which were distinctive for single developmental stage both in brain and heart tissues.