Differentially methylated region

Maternal effect mutations in the components of the subcortical maternal complex (SCMC) of the human oocyte can cause early embryonic failure, gestational abnormalities and recurrent pregnancy loss. Enigmatically, they are also associated with DNA methylation abnormalities at imprinted genes in conceptuses.

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Head and neck squamous cell carcinomas (HNSCCs) represent a heterogeneous group of cancers for which human papilloma virus (HPV) infection is an emerging risk factor. Previous studies showed promoter hypermethylation in HPV(+) oropharyngeal cancers, but only few consistent target genes have been so far described, and the evidence of a functional impact on gene expression is still limited.

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We previously identified 16,772 colorectal cancer-associated hypermethylated DNA regions that were also detectable in precancerous colorectal lesions (preCRCs) and unrelated to normal mucosal aging. We have now conducted a study to validate 990 of these differentially methylated DNA regions (DMRs) in a new series of preCRCs.

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Single-probe analyses in epigenome-wide association studies (EWAS) have identified associations between DNA methylation and many phenotypes, but do not take into account information from neighboring probes.

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Association studies using a single type of omics data have been successful in identifying diseaseassociated genetic markers, but the underlying mechanisms are unaddressed. To provide a possible explanation of how these genetic factors affect the disease phenotype, integration of multiple omics data is needed.

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CpG methylation variation is involved in human trait formation and disease susceptibility. Analyses within populations have been biased towards CpG-dense regions through the application of targeted arrays. We generate whole-genome bisulfite sequencing data for approximately 30 adipose and blood samples from monozygotic and dizygotic twins for the characterization of non-genetic and genetic effects at single-site resolution.

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We explored the association between gestational age and cord blood DNA methylation at birth and whether DNA methylation could be effective in predicting gestational age due to limitations with the presently used methods.

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DNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions.

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DNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focus on limited numbers of individuals and one to two brain regions.

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The traditional approach to studying the epigenetic mechanism CpG methylation in tissue samples is to identify regions of concordant differential methylation spanning multiple CpG sites (differentially methylated regions).

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Numerous studies have established a link between maternal diet and the physiological and metabolic phenotypes of their offspring. In previous studies in sheep, we demonstrated that different maternal diets altered the transcriptome of fetal tissues. However, the mechanisms underlying transcriptomic changes are poorly understood. DNA methylation is an epigenetic mark regulating transcription and is largely influenced by dietary components of the onecarbon cycle that generate the methyl group donor, SAM.

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Genomic imprinting is a process thereby a subset of genes is expressed in a parent-of-origin specific manner. This evolutionary novelty is restricted to mammals and controlled by genomic DNA segments known as Imprinting Control Regions (ICRs) and germline Differentially Methylated Regions (gDMRs).

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Lipopolysaccharide (LPS) endotoxin stimulates pro-inflammatory pathways and is a key player in the pathological mechanisms involved in the development of endometritis. This study aimed to investigate LPS-induce

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Crassulacean acid metabolism (CAM) photosynthesis is an important carbon fixation pathway especially in arid environments because it leads to higher water-use efficiency compared to C3 and C4 plants. However, the role of DNA methylation in regulation CAM photosynthesis is not fully understood.

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Genome-wide tiling array experiments are increasingly used for the analysis of DNA methylation. Because DNA methylation patterns are tissue and cell type specific, the detection of differentially methylated regions (DMRs) with small effect size is a necessary feature of tiling microarray ‘peak’ finding algorithms, as cellular heterogeneity within a studied tissue may lead to a dilution of the phenotypically relevant effects.

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In mammals, maternal differentially methylated regions (DMRs) acquire DNA methylation during the postnatal growth stage of oogenesis, with paternal DMRs acquiring DNA methylation in the perinatal prospermatagonia.

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Array based methylation profiling is a cost-effective solution to study the association between genome methylation and human disease & development. Available tools to analyze the Illumina Infinium HumanMethylation450 BeadChip focus on comparing methylation levels per locus.

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DNA methylation is an epigenetic modification that is studied at a single-base resolution with bisulfite treatment followed by high-throughput sequencing. After alignment of the sequence reads to a reference genome, methylation counts are analyzed to determine genomic regions that are differentially methylated between two or more biological conditions.

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Identification of differentially methylated regions (DMRs) is the initial step towards the study of DNA methylation-mediated gene regulation. Previous approaches to call DMRs suffer from false prediction, use extreme resources, and/or require library installation and input conversion.

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The development of whole genome bisulfite sequencing has made it possible to identify methylation differences at single base resolution throughout an entire genome. However, a persistent challenge in DNA methylome analysis is the accurate identification of differentially methylated regions (DMRs) between samples.

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