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PubMed2026

Characterization of DNA methylation in PBMCs and donor-matched iPSCs shows age-related methylation is reset during stem cell reprogramming.

DNA methylation is an important epigenetic mechanism that helps define and maintain cellular functions. It is influenced by many factors, including environmental exposures, genotype, cell type, sex, and aging. Since age is the primary risk factor for developing neurodegenerative diseases, it is important to determine if age-related DNA methylation is retained when cells are reprogrammed to an induced Pluripotent Stem Cell (iPSC) state. Here, we selected peripheral blood mononuclear cells (PBMCs; n = 99) from a cohort of diverse and healthy individuals enrolled in the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT) study to reprogram to iPSCs. After reprogramming, the resulting iPSCs were evaluated for DNA methylation signatures to determine if they reflect the confounding factors of aging and environmental effects. Data from genome-wide DNA methylation arrays in both cell types showed that age-related methylation measured by epigenetic clocks is largely reset to an early methylation age after reprogramming of PBMCs to iPSCs. We further examined the epigenetic age of each cell type using an Epigenome-wide Association Study (EWAS) and identified a set of methylation Quantitative Trait Loci in each cell type. Our results show that age-related DNA methylation is largely reset in iPSCs, and each cell type has a unique set of methylation sites that are modified by population-level genetic variation.

DNA Methylation↗

PubMed2018

Quantitation of DNA Methylation by Quantitative Multiplex Methylation-Specific PCR (QM-MSP) Assay.

The defining feature of the Quantitative Multiplex Methylation-Specific PCR (QM-MSP) method to sensitively quantify DNA methylation is the two-step PCR approach for a multiplexed analysis of a panel of up to 12 genes in clinical samples with minimal quantities of DNA. In the first step, for up to 12 genes tested, one pair of gene-specific primers (forward and reverse) amplifies the methylated and unmethylated copies of the same gene simultaneously and in multiplex, in one PCR reaction. This methylation-independent amplification step produces amplicons of up to 109 copies per μL after 36 cycles of PCR. In the second step, the amplicons of the first reaction (STEP 1) are quantified with a standard curve using real-time PCR and two independent fluorophores to detect methylated/unmethylated DNA of each gene in the same well (e.g., 6FAM and VIC). One methylated copy is detectable in 100,000 reference gene copies. Methylation is reported on a continuous scale. For the gene panel, the highest level of normal DNA methylation above which a sample would be called positive is derived by using Receiver Operating Characteristic (ROC), maximizing assay specificity and sensitivity to distinguish between normal/benign versus tumor DNA. QM-MSP can be applied to clinical samples of fresh or fixed ductal cells, ductal fluid, nipple fluid, fine needle aspirates, core biopsies, and tumor tissue sections.

Breast Neoplasms↗

PubMed2020

Harsh Parenting Predicts Novel HPA Receptor Gene Methylation and NR3C1 Methylation Predicts Cortisol Daily Slope in Middle Childhood.

Adverse experiences in childhood are associated with altered hypothalamic-pituitary-adrenal (HPA) axis function and negative health outcomes throughout life. It is now commonly accepted that abuse and neglect can alter epigenetic regulation of HPA genes. Accumulated evidence suggests harsh parenting practices such as spanking are also strong predictors of negative health outcomes. We predicted harsh parenting at 2.5 years old would predict HPA gene DNA methylation similarly to abuse and neglect, and cortisol output at 8.5 years old. Saliva samples were collected three times a day across 3 days to estimate cortisol diurnal slopes. Methylation was quantified using the Illumina Infinium MethylationEPIC array BeadChip (850 K) with DNA collected from buccal cells. We used principal components analysis to compute a summary statistic for CpG sites across candidate genes. The first and second components were used as outcome variables in mixed linear regression analyses with harsh parenting as a predictor variable. We found harsh parenting significantly predicted methylation of several HPA axis genes, including novel gene associations with AVPRB1, CRHR1, CRHR2, and MC2R (FDR corrected p < 0.05). Further, we found NR3C1 methylation predicted a steeper diurnal cortisol slope. Our results extend the current literature by demonstrating harsh parenting may influence DNA methylation similarly to more extreme early life experiences such as abuse and neglect. Further, we show NR3C1 methylation is associated with diurnal HPA function. Elucidating the molecular consequences of harsh parenting on health can inform best parenting practices and provide potential treatment targets for common complex disorders.

Child↗

PubMed2026

Methylation histology reveals the molecular mechanism by which red light-mediated DNA methylation delays leaf senescence in pak choi (Brassica rapa subsp. chinensis).

Leaf senescence is a key factor affecting the postharvest quality and shelf life of vegetables. The specific mechanisms by which light environment and DNA methylation mediate leaf senescence remain unclear. This study explored the molecular mechanism by which red light (RL) LED delays leaf senescence through DNA methylation in pak choi (Brassica rapa subsp. chinensis). In this study, RL treatment significantly suppressed leaf senescence in pak choi during postharvest storage and downregulated the expression of senescence-associated genes (SAGs). Experiments with methylation inhibitors confirmed its association with DNA methylation. Furthermore, whole-genome bisulfite sequencing revealed that during storage-induced senescence, pak choi exhibited significantly reduced methylation levels across its genome, particularly in promoter regions, and RL treatment reversed this effect. Furthermore, virus-induced gene silencing and overexpression experiments confirmed the central role of the demethylase BrDML3 (BraA01g004250.3.5C) in this process. Subsequently, a transcription factor under its regulation, BrNAC55 (BraA05g032630.3.5C), was identified and shown to promote leaf senescence by activating downstream SAGs (BrSGR1, BrPPH, BrSAUR36) to promote leaf senescence. In addition, this study found that BrNAC55 can also form a feedback loop with BrDML3, continuously amplifying leaf senescence. This study elucidates the mechanism by which RL-mediated DNA methylation delays leaf senescence, providing a foundation for postharvest preservation technologies.

DNA Methylation↗

PubMed2026

DNA methylation matters: methylation of the γ-globin (HBG) gene promoters is required for postnatal silencing of HbF.

Sufficient levels of fetal hemoglobin (HbF) can ameliorate the pathophysiologic basis of sickle cell disease and β-thalassemia postnatally. DNA methylation has long been posited to mediate silencing of HbF expression, but this has been controversial. Recent publications provide definitive evidence for the critical role of HBG gene promoter methylation in silencing and insight into the mechanisms involved. The data support a model in which methylation of CpG sites in the HBG promoters and repressive transcription factors recruit the MBD2-NuRD chromatin remodeling complex, which enforces silencing. These findings have implications for the treatment of β-globin disorders.

DNA Methylation↗

PubMed2026

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases.

MOTIVATION: Epigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. RESULTS: We developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG- searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. AVAILABILITY AND IMPLEMENTATION: The eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

DNA methylation↗

PubMed2026

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation↗

PubMed2026

Mammalian DNA methyltransferases in DNA methylation and imprinted gene expression in extraembryonic ectoderm of post-implantation embryos.

DNA methylation in mammals is mainly catalyzed by three DNA methyltransferases (DNMTs). Conventionally, DNMT1 is considered the primary DNMT protein for maintenance DNA methylation, whereas DNMT3A and DNMT3B function in de novo DNA methylation. In two previous studies, we demonstrated that DNMT3A and DNMT3B maintain genome-wide DNA methylation in embryonic stem (ES) cells and in the epiblast of post-implantation embryos. Interestingly, DNMT3A and DNMT3B also sustain genome-wide DNA methylation in the extraembryonic ectoderm (EXE) of post-implantation embryos, including repeats, genic and intergenic regions. Although DNMT1 plays a major role in maintaining DNA methylation at the imprinting control regions (ICRs) in the imprinted regions, DNMT3A and DNMT3B are required for preserving DNA methylation at the ICRs of a subset of imprinted regions in EXE, similar to the observations in ES cells and epiblast. Surprisingly, de novo DNA methylation mediated by DNMT3A and DNMT3B leads to increased DNA methylation at a large subset of imprinted regions. These results are consistent with what we previously elucidated in the epiblast of post-implantation embryos. Importantly, loss of DNA methylation at the ICR of an imprinted region, resulting from the absence of DNMT1 or two DNMT3 proteins, causes allelic expression switch of the corresponding imprinted genes in that imprinted region. This study provides further evidence that DNMT3A and DNMT3B exert both maintenance and de novo DNA methylation functions across the genome in post-implantation embryos. It also validates some previous findings for DNA methylation-dependent allelic expression switch of imprinted genes.

DNA methylation↗

PubMed2025

Genome-wide DNA methylation and transcriptome sequencing analyses of lens tissue in an age-related mouse cataract model.

DNA methylation is known to be associated with cataracts. In this study, we used a mouse model and performed DNA methylation and transcriptome sequencing analyses to find epigenetic indicators for age-related cataracts (ARC). Anterior lens capsule membrane tissues from young and aged mice were analyzed by MethylRAD-seq to detect the genome-wide methylation of extracted DNA. The young and aged mice had 76,524 and 15,608 differentially methylated CCGG and CCWGG sites, respectively. The Pearson correlation analysis detected 109 and 33 differentially expressed genes (DEGs) with negative methylation at CCGG and CCWGG sites, respectively, in their promoter regions. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses showed that DEGs with abnormal methylation at CCGG sites were primarily associated with protein kinase C signaling (Akap12, Capzb), protein threonine kinase activity (Dmpk, Mapkapk3), and calcium signaling pathway (Slc25a4, Cacna1f), whereas DEGs with abnormal methylation at CCWGG sites were associated with ribosomal protein S6 kinase activity (Rps6ka3). These genes were validated by pyrosequencing methylation analysis. The results showed that the ARC group (aged mice) had lower Dmpk and Slc25a4 methylation levels and a higher Rps6ka3 methylation than the control group (young mice), which is consistent with the results of the joint analysis of differentially methylated and differentially expressed genes. In conclusion, we confirmed the genome-wide DNA methylation pattern and gene expression profile of ARC based on the mouse cataract model with aged mice. The identified methylation molecular markers have great potential for application in the future diagnosis and treatment of ARC.

Animals↗

PubMed2026

Sex-specific differences in liver DNA methylation patterns and epigenetic aging in mice.

Biological sex has been shown to influence aging outcomes, contributing to distinct trajectories in disease susceptibility and lifespan. DNA methylation patterns provide a quantitative measure of biological aging. This study investigated whether aged male and female mice display distinct liver DNA methylation patterns and differences in epigenetic aging. Liver samples were collected from 17 aged c57BL/6 mice (6 males, 11 females). Genomic DNA was extracted and bisulfite-converted before targeted enrichment of 2,045 murine age-associated CpG loci. Biological age (DNAge) was estimated using a previously developed DNA methylation-based predictor generated through elastic net regression. The difference (ΔDNAge) between DNAge and chronological age was computed. Sex-specific differences were assessed by comparing site-specific methylation ratios, ΔDNAge values, and through principal component analysis (PCA) and multiple linear regression. Twelve CpG sites across six genes (Fam84b, Zswim6, Hsf4, Mn1, Qprt, and Rapgefl1) showed significant sex-associated differences in methylation. Fam84b demonstrated the largest and most consistent sex-associated effect, with all three associated CpG sites showing higher methylation in males (regression coefficients: -0.204, -0.281, and -0.294). Zswim6 exhibited consistent lower methylation ratios in females, whereas the other genes showed higher methylation in females. There were no sex differences in biological age or ΔDNAge (P = 0.596). Although the epigenetic clock did not reveal differences between sexes in aging, aged mice did exhibit sex-specific liver methylation patterns different from those reported in younger mice, suggesting that sex-dependent epigenetic changes may emerge later in life and may reflect sexual dimorphism in liver function with age.NEW & NOTEWORTHY Males and females are known to age differently and develop certain diseases at different rates. Here, we examined the livers of aged male and female mice to see if they show different DNA methylation patterns. We found that aged male and female mice had distinct DNA methylation patterns at specific genes. Interestingly, most of these methylation differences were not present in younger mice, suggesting that sex differences in the genome may change with age.

Animals↗

PubMed2026

A tunable, ultrasensitive threshold in enzymatic activity governs the DNA methylation landscape.

DNA methylation is a widely studied epigenetic mark, affecting gene expression and cellular function at multiple levels. DNA methylation in the mammalian genome occurs primarily at cytosine-phosphate-guanine (CpG) dinucleotides, and patterning of the methylation landscape (i.e., the presence or absence of CpG methylation at a given genomic location) exhibits a generally bimodal distribution. Although much is known about the enzymatic writers and erasers of CpG methylation, it is not fully understood how these enzymes, along with genetic, chromatin, and regulatory factors, control the genome-wide methylation landscape. In this study, methylation is analyzed at annotated CpG islands (CGIs) and independent CpGs as a function of their proximity to other CpG substrates. Analysis is aided by a computationally efficient stochastic mathematical model of methylation dynamics, enabling parameterization from data. We find that methylation exhibits a switch-like dependence on local CpG density with a threshold of 7-8 CpGs per 100 bp and a Hill coefficient of 4-5. The threshold and steepness of the switch is modified in cell lines in which key enzymes are knocked out. Modeling further elucidates how enzymatic parameters, including catalytic rates and lengthscales of inter-CpG interaction, tune the properties of the switch. Together, the results support a model in which competition between opposing TET1-3 demethylating enzymes and DNA methyltransferases (DNMT3A/B) results in an ultrasensitive switch, analogous to the protein phosphorylation switch (termed "zero-order ultrasensitivity"). Our study provides insight to the mechanisms underlying establishment and maintenance of bimodal DNA methylation landscapes, and further provides a flexible pipeline for gleaning molecular insights to the cellular methylation machinery across cell-specific, epigenomic data sets.

DNA Methylation↗

PubMed2026

Failures to maintain CpG-methylation of CoRSIVs in bovine sperm are associated with low sire conception.

In brief: Correlated regions of systemic interindividual epigenetic variation (CoRSIVs) are genomic regions with CpG-methylation patterns that differ between individuals, yet are consistent between tissues, within the same individual. Analyzing two groups of Holstein bull methylomes-nine with a high sire-conception rate (SCR) and nine with a low SCR-we found that a common type of CoRSIVs was significantly associated with reduced SCR and is thus suggested as a biomarker for SCR because it was highly methylated in sperm, but failed to retain hypermethylation in the gametes of males with low SCR. Abstract: Correlated regions of systemic interindividual epigenetic variation (CoRSIVs) are genomic regions with CpG-methylation patterns that differ between individuals, yet are consistent between tissues, within the same individual; therefore, their methylation can be profiled in bodily fluids that are easily obtained, such as blood and semen. Bearing in mind the simple epigenetic profiling of CoRSIVs, we tested whether this type of differentially methylated region (DMR) is associated with bovine fertility. Sequence Read Archive (SRA) meth BLAST was used to estimate CoRSIVs methylation status in 18 healthy, representative, and age-matched Holstein bulls, among which nine had high (H) sire-conception rate (SCR), and the other nine had low (L) SCR (group averages of SCR: 3.3 ± 0.6 and -3.8 ± 1.8, respectively). This method was also applied to morula and trophoblast SRA methylomes. Analysis with meth BLAST was effective for most (80%) CoRSIVs and showed that CoRSIVs are reprogrammed during blastocyst formation, although this method was incapable of specifically determining the methylation level in CoRSIVs with retrotransposons. In sperm, the effect of global methylation was evident in a common (25%) type of CoRSIVs that is highly (94.5% ± 4.3%) methylated in sperm. Specifically, a failure to retain hypermethylation in the sperm plus strand was significantly (p < 0.00025) indicative of low SCR. Comparing global DNA methylation using the latter type of CoRSIVs between sperm and blood can be used as a better biomarker for fertility than using other differentially methylated regions with more complex epigenetics.

Animals↗

PubMed2025

Altered mitochondrial DNA methylation in blood in individuals with mild cognitive impairment.

BACKGROUND: Previous studies reported that altered mitochondrial methylation in Alzheimer's disease (AD), however, whether epigenetic modifications in mitochondrial genomes contribute to preclinical AD remains unclear. This study aimed to investigate mitochondrial methylation changes in individuals with cognitive decline. RESEARCH DESIGN AND METHODS: We examined whole mitochondrial genome methylation in 50 individuals with mild cognitive impairment (MCI) and 50 individuals without MCI, using bisulfite amplicon sequencing, assessing methylation at 366 Cytosine-guanine oligodeoxynucleotide (CpG) sites. RESULTS: We found the overall methylation level of mitochondrial DNA (mtDNA) in each subject was relatively low, ranging from 0% to 15%. Global methylation was significantly higher in individuals with cognitive decline compared to controls (3.86% vs. 3.46%, p = 0.037), with 34 differentially methylated CpG sites identified. Methylation differences (MD) between cognitive decline individuals and controls were 22.93 ± 5.60% at chrM6465 (Q = 0.013), 12.55 ± 3.02% at chrM9612 (Q = 0.013), 11.45 ± 3.88% at chrM11762 (Q = 0.159) and 11.03 ± 3.88% at chrM11766 (Q = 0.172), respectively, while the level of MD at chrM15812 was -13.11 ± 4.31% (Q = 0.159) after Benjamini-Hochberg FDR adjusted. Furthermore, Methylation at specific sites were significantly correlated with Mini-Mental State Examination scores, distinguishing individuals with cognitive decline from controls. CONCLUSIONS: Our study provides an mtDNA methylation map and suggests a role for these sites in preclinical AD pathogenesis.

Humans↗

PubMed2026

Sex-biased DNA methylation in small hive beetles (Aethina tumida).

DNA methylation is an important epigenomic modification that significantly influences various cellular and organismal functions. In this study, we investigate the methylome of the small hive beetle, Aethina tumida. Our analysis reveals an average of 58,306 CpG methylation marks per beetle, representing approximately 0.99% of the genome's total CpGs. Notably, 85.4% of these methylation marks are located within genic regions on autosomes, with similar rates observed in both male and female beetles. However, male beetles exhibit a lower number of methylation marks and upregulated genes on Chromosome X when compared to female beetles. To evaluate the impact of epialleles on methylation, we identified 5828 associations between SNPs and methylation, with genotypes accounting for 39.2% of the variation observed at highly methylated sites. Interestingly, unfertilised eggs display slightly higher levels of DNA methylation compared to adult beetles, whereas embryos show methylation levels that are only about half of those in adults. This suggests that DNA methylation is dynamic during early development.

Animals↗

PubMed2019

Histone H3 lysine K4 methylation and its role in learning and memory.

Epigenetic modifications such as histone methylation permit change in chromatin structure without accompanying change in the underlying genomic sequence. A number of studies in animal models have shown that dysregulation of various components of the epigenetic machinery causes cognitive deficits at the behavioral level, suggesting that proper epigenetic control is necessary for the fundamental processes of learning and memory. Histone H3 lysine K4 (H3K4) methylation comprises one component of such epigenetic control, and global levels of this mark are increased in the hippocampus during memory formation. Modifiers of H3K4 methylation are needed for memory formation, shown through animal studies, and many of the same modifiers are mutated in human cognitive diseases. Indeed, all of the known H3K4 methyltransferases and four of the known six H3K4 demethylases have been associated with impaired cognition in a neurologic or psychiatric disorder. Cognitive impairment in such patients often manifests as intellectual disability, consistent with a role for H3K4 methylation in learning and memory. As a modification quintessentially, but not exclusively, associated with transcriptional activity, H3K4 methylation provides unique insights into the regulatory complexity of writing, reading, and erasing chromatin marks within an activated neuron. The following review will discuss H3K4 methylation and connect it to transcriptional events required for learning and memory within the developed nervous system. This will include an initial discussion of the most recent advances in the developing methodology to analyze H3K4 methylation, namely mass spectrometry and deep sequencing, as well as how these methods can be applied to more deeply understand the biology of this mark in the brain. We will then introduce the core enzymatic machinery mediating addition and removal of H3K4 methylation marks and the resulting epigenetic signatures of these marks throughout the neuronal genome. We next foray into the brain, discussing changes in H3K4 methylation marks within the hippocampus during memory formation and retrieval, as well as the behavioral correlates of H3K4 methyltransferase deficiency in this region. Finally, we discuss the human cognitive diseases connected to each H3K4 methylation modulator and summarize advances in developing drugs to target them.

Animals↗

PubMed2025

Multiomics Reveal Associations Between CpG Methylation, Histone Modifications and Transcription in a Species That has Lost DNMT3, the Colorado Potato Beetle.

Insects display exceptional phenotypic plasticity, which can be mediated by epigenetic modifications, including CpG methylation and histone modifications. In vertebrates, both are interlinked and CpG methylation is associated with gene repression. However, little is known about these regulatory systems in invertebrates, where CpG methylation is mainly restricted to gene bodies of transcriptionally active genes. A widely conserved mechanism involves the co-transcriptional deposition of H3K36 trimethylation and the targeted methylation of unmethylated CpGs by the de novo DNA methyltransferase DNMT3. However, DNMT3 has been lost multiple times in invertebrate lineages raising the question of how the links between CpG methylation, histone modifications and gene expression are affected by its loss. Here, we report the epigenetic landscape of Leptinotarsa decemlineata, a beetle species that has lost DNMT3 but retained CpG methylation. We combine RNA-seq, enzymatic methyl-seq and CUT&Tag to study gene expression, CpG methylation and patterns of H3K36me3 and H3K27ac histone modifications on a genome-wide scale. Despite the loss of DNMT3, H3K36me3 mirrors CpG methylation patterns. Together, they give rise to signature profiles for expressed and not expressed genes. H3K27ac patterns show a prominent peak at the transcription start site that is predictive of expressed genes irrespective of their methylation status. Our study provides new insights into the evolutionary flexibility of epigenetic modification systems that urge caution when generalizing across species.

Animals↗

PubMed2026

Endothelial cell-specific DNA methylation alterations in breast cancer.

DNA methylation alterations are well-established contributors to carcinogenesis, yet, in the tumor microenvironment (TME), patterns of lineage and cell-specific methylation alterations are not well understood. Single-cell DNA methylation profiling in the TME is limited by technical challenges and high costs. Here, we use bulk DNA methylation, cell type deconvolution (HiTIMED), and an interaction testing framework (CellDMC) to identify reproducible, computationally inferred lineage-specific epigenetic alterations in the TME supported by orthogonal data sources. Tumor endothelial cells (TECs), critical regulators of angiogenesis, vascular permeability, and immune cell trafficking, acquire structural and functional abnormalities that promote tumor growth. We hypothesize that TECs have altered DNA methylation compared with endothelial cells in non-tumor tissues. In genome-scale methylation data from discovery and validation datasets (tumor n = 1071; non-tumor n = 415), we identify and validate >4500 TEC-specific CpGs with altered methylation, many mapping to genes involved in angiogenesis and endothelial function. Integration with gene expression data indicates that TEC-specific methylation alterations may reprogram transcriptional networks controlling angiogenesis. High-resolution, cell lineage-specific epigenetic landscapes can be inferred from bulk methylation data, implicating TEC-specific DNA methylation alterations as potential drivers of cancer angiogenesis and vascular dysfunction and providing a framework for future mechanistic and translational studies of the tumor vasculature.

DNA Methylation↗

PubMed2026

diffMONT: predicting methylation-specific PCR biomarkers based on nanopore sequencing data for clinical application.

MOTIVATION: DNA methylation serves as a key biomarker in clinical diagnostics, especially in cancer detection. With methylation-specific PCR (MSP), a widely used approach, patient samples can be screened fast and efficiently for differential methylation. During MSP, methylated regions are selectively amplified with specific primers. With nanopore sequencing, knowledge about DNA methylation is generated during direct DNA sequencing without needing pretreatment of the DNA. Multiple methods, mainly developed for whole-genome bisulfite sequencing (WGBS) data, exist to predict differentially methylated regions (DMRs) in the genome. However, the predicted DMRs are often very large and not sufficiently discriminating to generate meaningful results in MSP, creating a gap between theoretical cancer marker research and practical application, as no tool currently provides methylation difference predictions tailored for PCR-based diagnostics. RESULTS: Here, we present diffMONT, a tool that predicts differentially methylated regions specifically suited for MSP primer design, enabling rapid translation into practical applications. diffMONT takes into account (i) the specific length of primer and amplicon regions, (ii) the fact that one condition should be unmethylated, and (iii) a minimal required amount of differentially methylated cytosines within the primer regions. We compared the results of diffMONT to metilene and DSS based on a publicly available nanopore sequencing dataset and show that the regions predicted by diffMONT are more specific toward hypermethylated regions. diffMONT accelerates the design of methylation-specific diagnostic assays, bridging the gap between theoretical research and clinical application. AVAILABILITY AND IMPLEMENTATION: The source code for diffMONT, an open-source Python-based tool, is available at https://github.com/rnajena/diffMONT/, with an archived release under https://zenodo.org/records/17641031.

DNA Methylation↗