Whole-genome bisulfite sequencing (WGBS) is the standard method for profiling DNA methylation at single-nucleotide resolution. Different tools have been developed to extract differentially methylated regions (DMRs), often built upon assumptions from mammalian data. Here, we present MethylScore, a pipeline to analyse WGBS data and to account for the substantially more complex and variable nature of plant DNA methylation. MethylScore uses an unsupervised machine learning approach to segment the genome by classification into states of high and low methylation. It processes data from genomic alignments to DMR output and is designed to be usable by novice and expert users alike. We show how MethylScore can identify DMRs from hundreds of samples and how its data-driven approach can stratify associated samples without prior information. We identify DMRs in the A. thaliana 1,001 Genomes dataset to unveil known and unknown genotype–epigenotype associations .

Major depression is a complex disorder with no single, direct causal mechanism. Morbidity has been linked to genetic processes, developmental history, and unique environmental exposures. Epigenetic mechanisms, especially DNA methylation, are also likely important factors in the pathogenesis of major depressive disorder (MDD). A community-based twin sample has many advantages for epigenetic studies, given the shared genetic and developmental histories of same-sex twin pairs. This article describes the rationale and study design for the Mood and Methylation Study in which 133 twin pairs (101 monozygotic and 32 dizygotic), both discordant and concordant for lifetime history of MDD, were evaluated on a large number of variables related to MDD. The twins also provided blood samples for an epigenome-wide association study of differentially methylated regions (DMR) relevant to MDD. Although MDD is typically considered a disorder of the central nervous system, it is unfeasible to obtain a large sample of brain tissues. However, epigenetic variation is not limited to the affected tissue but can also be detected in peripheral blood leukocytes. Thus, this study focused on monocytes for the major analyses. Additional plans for the study include gene expression analysis from the same set of twins using RNA-seq and validation of significant DMRs in postmortem brain tissues from a separate sample. Moreover, sufficient samples have been collected to perform future ‘multi-omic’ analyses, including metabolome, microbiome, and transcriptome. Our long-term goal is to understand how epigenomic and other ‘omic’ factors can be manipulated for diagnostic, preventive, and therapeutic purposes for MDD and its related conditions.

Identification of individuals within pairs of monozygotic (MZ) twins remains unresolved using common forensic DNA typing technology. For some criminal cases involving MZ twins as suspects, the twins had to be released due to inability to identify which of the pair was the perpetrator. In this study, we performed a genome-wide scan on whole blood-derived DNA from four pairs of healthy phenotypically concordant MZ twins using the methylated DNA immunoprecipitation sequencing technology to identify candidate DNA methylation markers with capacity to distinguish MZ twins within a pair. We identified 38 differential methylation regions showing within-pair methylation differences in all four MZ pairs. These are all located in CpG islands, 17 of which are promoter-associated, 17 are intergenic islands, and four are intragenic islands. Genes associated with these markers are related with cell proliferation, differentiation, and growth and development, including zinc finger proteins, PRRX2, RBBP9, or are involved in G-protein signaling, such as the regulator of G-protein signaling 16. Further validation studies on additional MZ twins are now required to evaluate the broader utility of these 38 markers for forensic use.

A growing number of studies focusing on the developmental origin of health and disease hypothesis have identified links among early nutrition, epigenetic processes and diseases also in later life. Different epigenetic mechanisms are elicited by dietary factors in early critical developmental ages that are able to affect the susceptibility to several diseases in adulthood. The studies here reviewed suggest that maternal and neonatal diet may have long-lasting effects in the development of non-communicable chronic adulthood diseases, in particular the components of the so-called metabolic syndrome, such as insulin resistance, type 2 diabetes, obesity, dyslipidaemia, hypertension, and CVD. Both maternal under- and over-nutrition may regulate the expression of genes involved in lipid and carbohydrate metabolism. Early postnatal nutrition may also represent a vital determinant of adult health by making an impact on the development and function of gut microbiota. An inadequate gut microbiota composition and function in early life seems to account for the deviant programming of later immunity and overall health status. In this regard probiotics, which have the potential to restore the intestinal microbiota balance, may be effective in preventing the development of chronic immune-mediated diseases. More recently, the epigenetic mechanisms elicited by probiotics through the production of SCFA are hypothesised to be the key to understand how they mediate their numerous health-promoting effects from the gut to the peripheral tissues.