SEARCH · Search PubMed

Results for “differentially methylated regions”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2025

Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies.

MOTIVATION: DNA methylation at cytosine-phosphate-guanine (CpG) sites is one of the most important epigenetic markers. Therefore, epidemiologists are interested in investigating DNA methylation in large cohorts through epigenome-wide association studies (EWAS). However, the observed EWAS data are bulk data with signals aggregated from distinct cell types. Deconvolution of cell-type-specific signals from EWAS data is challenging because phenotypes can affect both cell-type proportions and cell-type-specific methylation levels. Recently, there has been active research on detecting cell-type-specific risk CpG sites for EWAS data. However, existing methods all assume that the methylation levels of different CpG sites are independent and perform association detection for each CpG site separately. Although these methods significantly improve the detection at the aggregated-level-identifying a CpG site as a risk CpG site as long as it is associated with the phenotype in any cell type, they have low power in detecting cell-type-specific associations for EWAS with typical sample sizes. RESULTS: Here, we develop a new method, Fine-scale inference for Differentially Methylated Regions (FineDMR), to borrow strengths of nearby CpG sites to improve the cell-type-specific association detection. Via a Bayesian hierarchical model built upon Gaussian process functional regression, FineDMR takes advantage of the spatial dependencies between CpG sites. FineDMR can provide cell-type-specific association detection as well as output subject-specific and cell-type-specific methylation profiles for each subject. Simulation studies and real data analysis show that FineDMR substantially improves the power in detecting cell-type-specific associations for EWAS data. AVAILABILITY AND IMPLEMENTATION: FineDMR is freely available at https://github.com/JiaRuofan/Detection-of-Cell-type-specific-DMRs-in-EWAS.

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↗

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↗

PubMed2022

Profiling Genome-Wide DNA Methylation in Children with Autism Spectrum Disorder and in Children with Fragile X Syndrome.

Autism spectrum disorder (ASD) is an early onset, developmental disorder whose genetic cause is heterogeneous and complex. In total, 70% of ASD cases are due to an unknown etiology. Among the monogenic causes of ASD, fragile X syndrome (FXS) accounts for 2-4% of ASD cases, and 60% of individuals with FXS present with ASD. Epigenetic changes, specifically DNA methylation, which modulates gene expression levels, play a significant role in the pathogenesis of both disorders. Thus, in this study, using the Human Methylation EPIC Bead Chip, we examined the global DNA methylation profiles of biological samples derived from 57 age-matched male participants (2-6 years old), including 23 subjects with ASD, 23 subjects with FXS with ASD (FXSA) and 11 typical developing (TD) children. After controlling for technical variation and white blood cell composition, using the conservatory threshold of the false discovery rate (FDR ≤ 0.05), in the three comparison groups, TD vs. AD, TD vs. FXSA and ASD vs. FXSA, we identified 156, 79 and 3100 differentially methylated sites (DMS), and 14, 13 and 263 differential methylation regions (DMRs). Interestingly, several genes differentially methylated among the three groups were among those listed in the SFARI Gene database, including the PAK2, GTF2I and FOXP1 genes important for brain development. Further, enrichment analyses identified pathways involved in several functions, including synaptic plasticity. Our preliminary study identified a significant role of altered DNA methylation in the pathology of ASD and FXS, suggesting that the characterization of a DNA methylation signature may help to unravel the pathogenicity of FXS and ASD and may help the development of an improved diagnostic classification of children with ASD and FXSA. In addition, it may pave the way for developing therapeutic interventions that could reverse the altered methylome profile in children with neurodevelopmental disorders.

Child↗

PubMed2025

DNA methylation and multi-omics profiling of T cells uncovers chemotactic pathways and proliferation-linked hypomethylation in narcolepsy type 1.

Narcolepsy type 1 (NT1) is a chronic sleep disorder caused by a loss of orexin-producing cells in the brain and involves autoimmune mechanisms, including the presence of autoreactive T cells. In this study, we performed genome-wide DNA methylation analysis using both CD4+/CD8+ T cells from 42 NT1 patients and 42 controls across discovery and replication cohorts. To identify methylation changes more robustly associated with the disease, we prioritized differentially methylated regions (DMRs) over single-site differentially methylated positions (DMPs). Furthermore, to validate and interpret DMP-level associations, we integrated genome-wide genotype and gene expression data obtained from the same individuals. As a result, the DMR analysis identified 15 reproducible DMRs in CD4+ T cells and 5 in CD8+ T cells, with most DMRs shared between the two cell types. Shared DMRs included regions associated with CCL5 (p = 2.1E-02) and CCR4 (p = 8.3E-03). Integrative analysis with genotype and gene expression data also showed that the DMP related to S100A4, which promotes lymphocyte migration through CCR5 and CXCR3 receptors, was associated with the disease in CD4+ T cells. Pathway analysis of genes identified through both the DMR and integrative analyses indicated enrichment in cell chemotaxis-related pathways, suggesting that aberrant chemokine-mediated cell migration plays a central role in NT1 pathogenesis. Further, NT1-associated methylation changes were predominantly hypomethylation events, significantly enriched in non-promoter, non-CpG island regions (p = 1.74E-102). We further observed that global hypomethylation levels were correlated with hypoSC, a mitotic index estimated from methylation data, highlighting increased T cell proliferation in NT1.

Humans↗

PubMed2026

Cell-specific DNA methylation in human alpha and beta cells regulates gene expression in type 2 diabetes.

Epigenome-wide studies of pancreatic islets provide valuable insights into type 2 diabetes (T2D) but lack methylomes from individual cell types. Here we show changes to alpha and beta cell-specific methylomes and transcriptomes from people with or without T2D, using whole-genome bisulfite sequencing and RNA sequencing. We discover 22,544 differentially methylated regions annotated to 7,975 genes in alpha versus beta cells, such as INS, GCG, PDX1 and PCSK1, with ~50% showing differential expression. CRISPR-dCas9-DNMT3A-based epigenetic editing increases INS and TH DNA methylation, while CRISPR-dCas9-TET1-based editing decreases GCG methylation, each altering INS, TH or GCG expression and content in beta cells. Pre-T2D/T2D-associated differentially methylated regions in alpha and beta cells overlap 12-18% of T2D-associated genome-wide association study candidates. Additionally, ONECUT2 is epigenetically upregulated in beta cells from people with pre-T2D/T2D and elevated in male Goto-Kakizaki rat islets. ONECUT2 overexpression in beta cells/islets downregulates gene sets impacting insulin secretion and glucose homeostasis, and reduces mitochondrial activity, ATP/ADP ratio and insulin secretion. We also provide 'alpha-beta-methylome' ( https://alpha-beta-methylome.serve.scilifelab.se/app/alpha-beta-methylome/ ), a resource exploring T2D, age and sex associations on methylation, highlighting cell-specific epigenetic regulation and dysfunctions contributing to T2D.

Humans↗

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↗

PubMed2026

Integrative WGBS and ATAC-seq profiling reveals epigenetic and chromatin accessibility signatures associated with clutch length in goose ovaries.

Clutch length is an important reproductive trait in geese, but its epigenetic basis remains poorly characterized. Daily egg production was recorded for 280 individually housed Zi geese, and clutch-related indices were calculated as described in our previous study. Based on these records, six geese with contrasting clutch-length phenotypes were selected and assigned to the long-clutch (LC) and short-clutch (SC) groups. Ovarian tissues from three geese per group were subjected to whole-genome bisulfite sequencing (WGBS) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) to identify candidate epigenetic signatures associated with clutch length. WGBS identified 630,909 differentially methylated regions (DMRs), whereas ATAC-seq identified 902 differentially accessible regions (DARs). Integrated analysis revealed distinct patterns of ovarian DNA methylation and chromatin accessibility between the two groups, suggesting that clutch length variation may be accompanied by epigenomic differences in ovarian tissue. Genes associated with DMRs and/or DARs were enriched in biological processes related to granulosa cell differentiation and endocrine competence, follicular fate regulation, and periovulatory cytoskeletal and signaling remodeling. RERE was prioritized as a candidate locus because it was supported by changes in both DNA methylation and chromatin accessibility, whereas FOXL2, STAR, BAK1, FGF17, PRSS35, ACTR3, and AXIN1 were supported mainly by evidence from a single omics layer. RT-qPCR analysis of selected genes showed expression trends broadly consistent with the corresponding epigenomic differences, providing additional supportive evidence for these candidate associations. Collectively, this study provides an exploratory ovarian epigenomic resource and identifies candidate epigenetic signatures, genes, and biological processes associated with clutch length variation in geese.

DNA methylation↗

PubMed2020

PTSD is associated with increased DNA methylation across regions of HLA-DPB1 and SPATC1L.

Posttraumatic stress disorder (PTSD) is characterized by intrusive thoughts, avoidance, negative alterations in cognitions and mood, and arousal symptoms that adversely affect mental and physical health. Recent evidence links changes in DNA methylation of CpG cites to PTSD. Since clusters of proximal CpGs share similar methylation signatures, identification of PTSD-associated differentially methylated regions (DMRs) may elucidate the pathways defining differential risk and resilience of PTSD. Here we aimed to identify epigenetic differences associated with PTSD. DNA methylation data profiled from blood samples using the MethylationEPIC BeadChip were used to perform a DMR analysis in 187 PTSD cases and 367 trauma-exposed controls from the Grady Trauma Project (GTP). DMRs were assessed with R package bumphunter. We identified two regions that associate with PTSD after multiple test correction. These regions were in the gene body of HLA-DPB1 and in the promoter of SPATC1L. The DMR in HLA-DPB1 was associated with PTSD in an independent cohort. Both DMRs included CpGs whose methylation associated with nearby sequence variation (meQTL) and that associated with expression of their respective genes (eQTM). This study supports an emerging literature linking PTSD risk to genetic and epigenetic variation in the HLA region.

Cytoskeletal Proteins↗

PubMed2025

Cell-Free DNA Bisulfite Sequencing Reveals Epithelial-Mesenchymal Transition Signatures for Breast Cancer.

Cell-free DNA (cfDNA), shed by malignant tumor cells into extracellular fluid, provides valuable epigenetic information indicative of cancer status. Nipple aspirate fluid (NAF), a noninvasive liquid biopsy from at-risk women, contains nucleic acid and protein biomarkers from adjacent cancer cells, showing promise for breast cancer (BrC) detection. However, despite its potential, the application of cfDNA in NAF for BrC screening is still underexplored. Here, we report a proof-of-concept study for using cfDNA bisulfite sequencing (cfBS) to assess tumor DNA methylation signatures from NAF samples. For four healthy individuals and three BrC patients, cfBS achieved greater than 20× sequencing depth with an average coverage of 26.5× on the genome. A total of 7471 differentially methylated regions were identified, with significant hypermethylation in BrC samples compared to healthy controls. Gene set enrichment analysis indicated that the differentially methylated genes (DMGs) were significantly associated with epithelial-mesenchymal transition (EMT). By developing a novel EMT scoring metric, we found that BrC samples had more of a mesenchymal phenotype than samples from healthy individuals. CDH1, WNT2, and TRIM29 were hypermethylated near the promoter region, while COL5A2 was hypermethylated in the coding region. The DNA methylation and EMT changes were validated through The Cancer Genome Atlas Breast Invasive Carcinoma study, which confirmed that DMGs were associated with gene expression change and that our methylation-based EMT score reliably distinguished tumors from healthy controls. Our findings support the utilization of the NAF cfDNA cfBS methylation profile for noninvasive BrC screening and pave the way for enhanced early detection of this disease.

Humans↗

PubMed2026

MultiDMPcaller: a one-stop software for detection and visualization of differentially methylated positions and regions.

MOTIVATION: Whole-genome bisulfite sequencing (WGBS/BS-Seq) is the gold standard for single-base resolution DNA methylome profiling. However, the diverse statistical models of existing computational methods lead to limited overlap between their results, highlighting the need for novel methods to detect differentially methylated positions (DMPs) and differentially methylated regions (DMRs). RESULTS: We developed MultiDMPcaller, an automated downstream methylome analysis software. It processes upstream outputs to profile DMPs, non-DMPs, DMRs, and context-specific (CpG/CHG/CHH) methylation status, alongside visualizing their chromosomal distribution and enrichment. The software features two key innovations: (i) an adaptive two-step P-value adjustment strategy based on organism-specific methylation patterns, with raw P-value ≤0.05 pre-filtering followed by false discovery rate (FDR) correction, to recover potential DMPs usually missed by standard FDR correction in plant CHG/CHH and animal CpG contexts; and (ii) a multiple pairwise comparison approach, which performs m × n pairwise comparisons for m control and n experimental replicates, followed by a voting system supporting both user-defined majority thresholds and model-based adaptive thresholds, to identify robust and reliable DMPs (with a stricter voting threshold exclusively for loci with low methylation differences) and DMRs. On real datasets from Arabidopsis, apple, and mouse, as well as simulated human datasets, MultiDMPcaller's results showed good agreement with those of other software, exhibiting high conservativeness and superior precision, which suggested a low false discovery proportion. AVAILABILITY AND IMPLEMENTATION: MultiDMPcaller is available at GitHub (https://github.com/jiantaoyuNWAFU/MultiDMPcaller) and via a web server (https://ciebioinfo.nwafu.edu.cn).

Software↗

PubMed2026

Multi-omics integrative analysis provides insight into potential molecular responses to sustained high water flow in common carp (Cyprinus carpio) cultured in recirculating aquaculture.

To investigate the potential molecular responses by which water flow intensity affects the growth of common carp (Cyprinus carpio) in a recirculating aquaculture system (RAS), a control group (CG, actual water velocity 0.3 cm/s) and three sustained flow treatment groups were established, including a low-flow group (LF, 1 body length per second, bl/s), a medium-flow group (MF, 2 bl/s), and a high-flow group (HF, 3 bl/s). After 12 weeks of culture in the RAS, growth performance was compared among groups under different flow intensities. The best-performing group and the control group were then selected for the determination of intestinal digestive enzyme activities, as well as transcriptomic and whole-genome bisulfite sequencing analyses of muscle tissue. The results showed that the specific growth rate and feed intake of the HF group were significantly higher than those of the other groups (P < 0.05), whereas no significant difference in feed conversion ratio was observed among groups. Compared with the CG group, lipase activity was significantly higher in the HF group (P < 0.05), while α-amylase and trypsin activities showed increasing trends without significant differences. RNA-seq identified a total of 273 differentially expressed genes, including 72 upregulated genes and 201 downregulated genes in the HF group relative to the CG group. These genes were mainly enriched in glycolysis, pyruvate metabolism, ATP metabolism, the pentose phosphate pathway, the insulin signaling pathway, the PPAR signaling pathway, and the adipocytokine signaling pathway, indicating that sustained high water flow induced a muscle transcriptional response characterized by remodeling of energy metabolism and substrate utilization. Whole-genome bisulfite sequencing analysis showed that DNA methylation in common carp muscle occurred predominantly in the CpG context. Differentially methylated regions between the HF and CG groups were mainly distributed in transcription-related regulatory regions, including promoters, CpG islands, and CpG island shores. In promoter regions, the number of hypermethylated regions in the HF group relative to the CG group was markedly higher than that of hypomethylated regions. Integrated analysis further identified two candidate genes showing both promoter differential methylation and differential expression, namely LOC109094644 and bcorl1, suggesting that adaptation to high water flow may involve IGF-related growth regulation and remodeling of upstream transcriptional programs. The qPCR results were consistent with the transcriptomic data. Taken together, within the tested range, a sustained water flow of 3 bl/s was more conducive to the growth of common carp in the RAS, which may be associated with enhanced lipid digestion and utilization, remodeling of the muscle energy metabolic network, changes in promoter methylation, and the coordinated regulation of key candidate genes. This study provides a theoretical basis for clarifying the exercise adaptation mechanism of common carp in recirculating aquaculture and for optimizing flow velocity parameters.

Animals↗

PubMed2025

Prenatal organophosphate ester exposure and epigenetic changes at birth: a characterization of the methylome in the ECHO cohort.

BACKGROUND: Prenatal exposure to organophosphate esters (OPEs) affects multiple child health domains. Alterations to the DNA methylome are a plausible mechanism through which these changes occur. This study characterized DNA methylation signatures at birth associated with prenatal OPE biomarkers. METHODS: We included 736 mother-infant pairs from 7 sites in the Environmental influences on Child Health Outcomes (ECHO) Cohort. Five OPE biomarkers were quantified in maternal urine samples collected during the second and third trimesters and modeled as log2-transformed continuous variables. Using covariate-adjusted linear regression, we tested associations between OPE biomarkers and locus-specific, regional, and global cord blood DNA methylation changes measured by Illumina 450 K and EPIC arrays, and gestational epigenetic age measured by the Knight gestational age epigenetic clock generated with measures from the 27 K, 450 K, and EPIC arrays. When feasible, we examined relationships by sex. FINDINGS: Global hypomethylation at multiple regions was associated with BDCPP concentrations (p = 0.003 to 0.02, coef = -0.002). Differentially methylated regions annotated to PCDHGB1 and SLC43A2 were associated with BDCPP and DPHP concentrations, respectively (FDR q < 0.05). In sex-specific analyses, global hypomethylation was associated with prenatal BDCPP (p = 0.006 to 0.03, coef = -0.0003 to -0.0002) and DBUP_DIBP (p = 0.01, coef = -0.0007 to -0.0006) concentrations in females; and global hypermethylation was associated with DBUP_DIBP concentrations in males (p < 0.05, coef = 0.0004). BCETP concentrations were significantly associated with decelerated epigenetic aging at birth in females (p < 0.05, coef = -0.05). INTERPRETATION: Prenatal exposure to OPEs impacts child methylation at birth, suggesting a potential mechanism for the association between prenatal OPE exposure and child health outcomes.

Humans↗

PubMed2026

Genotype-dependent DNA methylation patterns are negatively associated with allelic variation rather than heat-induced gene expression in two contrasting potato genotypes.

Potato (Solanum tuberosum L.) is an important food crop that is sensitive to high temperatures, which cause major changes in the transcriptome and a reduction in yield. In several plant species, DNA methylation has been reported to influence gene expression, particularly under abiotic stress conditions. However, the role of DNA methylation in regulating gene expression in heat-tolerant and heat-sensitive potato genotypes is still poorly understood. In this study, we conducted genome-wide DNA methylome and transcriptome analyses of leaves from two contrasting potato cultivars, Annabelle (moderately heat-tolerant) and Camel (heat-sensitive), before and after heat stress (HS). Genome-wide differential methylation analysis revealed that most identified differentially methylated regions (DMRs) were constitutive, reflecting variation between cultivars rather than being induced by HS. While thousands of heat-responsive differentially expressed genes (DEGs) were identified, only a small fraction coincided with heat-induced DMRs. Despite substantial constitutive DNA methylation and transcriptome differences between the cultivars, we found no consistent association between DMRs and DEGs, indicating that DNA methylation does not play a widespread direct regulatory role in gene expression. Surprisingly, hypermethylated genomic regions were associated with lower alternative allele frequencies, whereas hypomethylated regions showed the opposite trend. These findings indicate that the potato DNA methylome is largely stable under HS and that constitutive DNA methylation variation contributes rather to genetic diversity than to the direct regulation of gene expression.

DNA Methylation↗

PubMed2026

Maternal immune activation disrupts epigenomic and functional maturation of cortical excitatory neurons.

Elevated levels of maternal pro-inflammatory cytokines following severe infection during gestation can disrupt offspring neural development and increase the risk of neurodevelopmental disorders. The viral mimetic Poly(I:C) reproduces the effects of gestational influenza exposure, leading to behavioral outcomes that recapitulate neurodevelopmental disorder phenotypes. Although Poly(I:C)-induced maternal immune activation (PIC-MIA) alters the epigenome, behavior and cognition of offspring in adulthood, it remains unclear when these changes occur and how MIA influences the epigenomic regulatory programming across the transition from embryonic development to the mature brain. Here, we examined the effects of PIC-MIA on the epigenomic maturation of the frontal cortex, focusing on excitatory neuron-specific DNA methylation and transcriptomic dynamics throughout perinatal development. Mid-gestation PIC-MIA disrupted development of the excitatory neuron transcriptome, with the largest alterations observed at birth. PIC-MIA altered the development of the mature DNA methylation program of excitatory neurons at thousands of genomic regulatory regions that normally gain or lose methylation during development. Transcription factor binding site analyses of these differentially methylated regions revealed a significant enrichment of Tbr1 motifs within hyper-methylated deep-layer neuron-specific regions at birth. Notably, transcriptional targets of Tbr1 were down-regulated at birth despite up-regulation of Tbr1 transcription, suggesting PIC-MIA uncouples Tbr1 expression from its regulatory function in deep-layer neurons. Electrophysiological recordings of intrinsic and firing properties further confirmed a lasting disruption in deep-layer neuronal activity. Our results suggest that mid-gestation MIA may alter the development of deep-layer neurons through an epigenomic blockade of Tbr1 function, thereby perturbing normal cortical circuit formation.

Journal Article↗

PubMed2025

Epigenetic maps of pearl millet reveal a prominent role for CHH methylation in regulating tissue-specific gene expression.

UNLABELLED: Pearl millet (Pennisetum glaucum) is a major staple food in arid and semi-arid regions of sub-Saharan Africa, India, and South Asia. However, how epigenetic mechanisms regulate tissue-specific gene expression in this crop remains poorly understood. In this study, we profiled multiple epigenetic features in the young panicles and roots of pearl millet using RNA-seq, ATAC-seq, whole-genome bisulfite sequencing, and ChIP-seq (H3K4me3 and H3K36me3). We identified thousands of genes that were differentially expressed between these two tissues. Root-specific genes were enriched for plant hormone signaling, oxidative phosphorylation, and stress responses. Analysis of chromatin accessibility revealed that root-specific accessible chromatin regions (ACRs) were enriched in binding motifs for stress-responsive transcription factors (e.g., NAC, WRKY), whereas ACRs in young panicles were enriched in motifs for developmental regulators (e.g., AP2/ERF). DNA methylation profiling revealed 25,141 tissue-specific differentially methylated regions, with CHH methylation-rather than CG or CHG methylation-showing the strongest tissue specificity. Promoters of root-specific genes had higher levels of CHH methylation compared to those of young panicle-specific genes, suggesting that the roles of CHH methylation in regulating transcription might be tissue dependent. Notably, promoter-associated H3K4me3 marked panicle-specific genes, whereas root-specific expression was primarily linked to chromatin accessibility, suggesting a transcription factor-mediated regulatory mechanism. Together, our findings highlight the distinct epigenetic frameworks governing tissue-specific gene expression in pearl millet and provide valuable insights for advancing the genetic improvement of this crop. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42994-025-00243-2.

CHH methylation↗

PubMed2024

Epigenetic footprints: Investigating placental DNA methylation in the context of prenatal exposure to phenols and phthalates.

BACKGROUND: Endocrine disrupting compounds (EDCs) such as phthalates and phenols can affect placental functioning and fetal health, potentially via epigenetic modifications. We investigated the associations between pregnancy exposure to synthetic phenols and phthalates estimated from repeated urine sampling and genome wide placental DNA methylation. METHODS: The study is based on 387 women with placental DNA methylation assessed with Infinium MethylationEPIC arrays and with 7 phenols, 13 phthalates, and two non-phthalate plasticizer metabolites measured in pools of urine samples collected twice during pregnancy. We conducted an exploratory analysis on individual CpGs (EWAS) and differentially methylated regions (DMRs) as well as a candidate analysis focusing on 20 previously identified CpGs. Sex-stratified analyses were also performed. RESULTS: In the exploratory analysis, when both sexes were studied together no association was observed in the EWAS. In the sex-stratified analysis, 114 individual CpGs (68 in males, 46 in females) were differentially methylated, encompassing 74 genes (36 for males and 38 for females). We additionally identified 28 DMRs in the entire cohort, 40 for females and 42 for males. Associations were mostly positive (for DMRs: 93% positive associations in the entire cohort, 60% in the sex-stratified analysis), with the exception of several associations for bisphenols and DINCH metabolites that were negative. Biomarkers associated with most DMRs were parabens, DEHP, and DiNP metabolite concentrations. Some DMRs encompassed imprinted genes including APC (associated with parabens and DiNP metabolites), GNAS (bisphenols), ZIM2;PEG3;MIMT1 (parabens, monoethyl phthalate), and SGCE;PEG10 (parabens, DINCH metabolites). Terms related to adiposity, lipid and glucose metabolism, and cardiovascular function were among the enriched phenotypes associated with differentially methylated CpGs. The candidate analysis identified one CpG mapping to imprinted LGALS8 gene, negatively associated with ethylparaben. CONCLUSIONS: By combining improved exposure assessment and extensive placental epigenome coverage, we identified several novel genes associated with the exposure, possibly in a sex-specific manner.

Humans↗

PubMed2026

Integrated GWAS and methylation analysis identify DNMT3A as an important regulator of growth in rabbits.

The parameters of individual growth curve can serve as pseudo-phenotype for genetic evaluation in livestock. In this study, we compared five nonlinear growth models using post-weaning body weights of 706 New Zealand White rabbits. Under the best-fitting model, two parameters of mature weight and maturity rate were subjected to GWAS through single-step genomic BLUP framework that integrated phenotypic records from non-genotyped animals with 41,359 SNPs genotyped in 198 individuals. Association analysis identified 147 relevant genomic regions, and also highlighted DNMT3A as a promising candidate gene for further functional investigation. siRNA-mediated knockdown of DNMT3A significantly impaired myoblast proliferation. Whole-genome bisulfite sequencing of DNMT3A-knockdown myoblasts identified 69,480 differentially methylated regions (DMRs). Integrative analyses revealed substantial overlap between DMR-associated genes and GWAS candidate genes, with significant enrichment in vitamin B6 and tyrosine metabolism pathways. These findings suggest that DNMT3A may regulate rabbit growth via mediating DNA methylation of downstream genes.

Animals↗