SEARCH · Search PubMed

Results for “epigenomics”

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 37 records · Page 2Linked to original sources

PubMed2026

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n = 929), CARDIA (n = 1123), JHS (n = 1365), ARIC (n = 2338), and HCHS/SOL (n = 1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R² ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans↗

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↗

PubMed2024

Epigenome-wide Association Study Shows Differential DNA Methylation of MDC1, KLF9, and CUTA in Autoimmune Thyroid Disease.

CONTEXT: Autoimmune thyroid disease (AITD) includes Graves disease (GD) and Hashimoto disease (HD), which often run in the same family. AITD etiology is incompletely understood: Genetic factors may account for up to 75% of phenotypic variance, whereas epigenetic effects (including DNA methylation [DNAm]) may contribute to the remaining variance (eg, why some individuals develop GD and others HD). OBJECTIVE: This work aimed to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) comparing GD to HD. METHODS: Whole-blood DNAm was measured across the genome using the Infinium MethylationEPIC array in 32 Australian patients with GD and 30 with HD (discovery cohort) and 32 Danish patients with GD and 32 with HD (replication cohort). Linear mixed models were used to test for differences in quantile-normalized β values of DNAm between GD and HD and data were later meta-analyzed. Comb-p software was used to identify DMRs. RESULTS: We identified epigenome-wide significant differences (P < 9E-8) and replicated (P < .05) 2 DMPs between GD and HD (cg06315208 within MDC1 and cg00049440 within KLF9). We identified and replicated a DMR within CUTA (5 CpGs at 6p21.32). We also identified 64 DMPs and 137 DMRs in the meta-analysis. CONCLUSION: Our study reveals differences in DNAm between GD and HD, which may help explain why some people develop GD and others HD and provide a link to environmental risk factors. Additional research is needed to advance understanding of the role of DNAm in AITD and investigate its prognostic and therapeutic potential.

Humans↗

PubMed2024

An epigenome-wide study of selenium status and DNA methylation in the Strong Heart Study.

BACKGROUND: Selenium (Se) is an essential nutrient linked to adverse health endpoints at low and high levels. The mechanisms behind these relationships remain unclear and there is a need to further understand the epigenetic impacts of Se and their relationship to disease. We investigated the association between urinary Se levels and DNA methylation (DNAm) in the Strong Heart Study (SHS), a prospective study of cardiovascular disease (CVD) among American Indians adults. METHODS: Selenium concentrations were measured in urine (collected in 1989-1991) using inductively coupled plasma mass spectrometry among 1,357 participants free of CVD and diabetes. DNAm in whole blood was measured cross-sectionally using the Illumina MethylationEPIC BeadChip (850 K) Array. We used epigenome-wide robust linear regressions and elastic net to identify differentially methylated cytosine-guanine dinucleotide (CpG) sites associated with urinary Se levels. RESULTS: The mean (standard deviation) urinary Se concentration was 51.8 (25.1) μg/g creatinine. Across 788,368 CpG sites, five differentially methylated positions (DMP) (hypermethylated: cg00163554, cg18212762, cg11270656, and hypomethylated: cg25194720, cg00886293) were significantly associated with Se in linear regressions after accounting for multiple comparisons (false discovery rate p-value: 0.10). The top hypermethylated DMP (cg00163554) was annotated to the Disco Interacting Protein 2 Homolog C (DIP2C) gene, which relates to transcription factor binding. Elastic net models selected 425 hypo- and hyper-methylated DMPs associated with urinary Se, including three sites (cg00163554 [DIP2C], cg18212762 [MAP4K2], cg11270656 [GPIHBP1]) identified in linear regressions. CONCLUSIONS: Urinary Se was associated with minimal changes in DNAm in adults from American Indian communities across the Southwest and the Great Plains in the United States, suggesting that other mechanisms may be driving health impacts. Future analyses should explore other mechanistic biomarkers in human populations, determine these relationships prospectively, and investigate the potential role of differentially methylated sites with disease endpoints.

Humans↗

PubMed2025

Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: In Pancreatic Ductal Adenocarcinoma (PDAC), current prognostic scores are unable to fully capture the biological heterogeneity of the disease. While some approaches investigating the role of multi-omics in PDAC are emerging, the analysis of methylation data is under exploited. MATERIALS AND METHODS: We analyzed CpG sites from two publicly available datasets, the TCGA-PAAD used as discovery set and the CPTAC-PDA as external test set. Single mutations and co-mutation of KRAS and TP53 genes were identified as targets, and differentially methylated CpG sites (DMC) were detected accordingly. We trained and validated Random Forest (RF) models to predict each target. Area Under the Receiver Operating Characteristic curve (AUROC) and Area Under the Precision-Recall curve (AUPRC) were used as performance metrics. Then, we performed consensus clustering from the DMCs to identify novel patients' profiles. Finally, we trained and validated a combination of eXtreme Gradient Boosting (XGB) and tree models to select an epigenomic prognostic determinant. RESULTS: From 598 DMCs extracted, an RF model predicted KRAS and TP53 co-mutation on the external test set with AUROC of 0.77 and AUPRC of 0.87. The consensus clustering allowed us to identify 4 clusters (C1, C2, C3, and C4) of patients. The C4 cluster captured a subgroup of patients with favorable Overall Survival (OS) with respect to others. The XGB model perfectly predicted C4 vs other clusters on the discovery set. In both cohorts, patients were stratified into two risk groups according to methylation levels of cg16854533, individuated as the most important CpG site. CONCLUSION: We analyzed methylation data to develop a classifier for the TP53 and KRAS mutational status. Four prognostic clusters were pointed out and a prognostic model using a CpG site was validated in an independent cohort. Our results evidence that the proposed use of methylation data facilitates risk stratification for PDAC.

Humans↗

PubMed2026

Nanopore-based epigenomic profiling reveals the absence of widespread CpG methylation in the African swine fever virus genome.

DNA methylation is a critical epigenetic mechanism implicated in regulating replication and transcription in DNA viruses. However, the epigenetic landscape of African swine fever virus (ASFV), a large double-stranded DNA virus infecting pigs, remains controversial. Here, we systematically profiled the DNA methylome of the first ASFV strain isolated in Hong Kong (HK_NT_202103) using Oxford Nanopore Technologies (ONT) R10.4.1 sequencing. We employed a paired design: native whole-genome sequencing (WGS) against a methylation-free whole-genome amplification (WGA) control. Using conservative thresholds, we found no evidence of 5-methylcytosine (5mC), especially typical CpG methylation, across the viral genome. Importantly, clear CpG methylation signals were successfully detected in the host genome from WGS data, confirming the functionality of the workflow to detect 5mC at CG sites. While widespread 5mC seems absent, a small number of putative N6-methyladenine (6mA) loci were identified. A specific 6mA candidate exhibited raw ionic current disruptions and gene-level intersection with another ASFV isolate (CAS19-01/2019), although it lacked single-base consensus across different methylation callers or between the two isolates. Although our biological findings are restricted to a single isolate under specific experimental conditions, this study introduces a novel, highly rigorous ONT framework for viral epigenomics research. Furthermore, the absence of ASFV CpG methylation indicates that host CpG-depletion remains a viable strategy for viral metagenomic enrichment. Ultimately, our work offers a critical methodological baseline for ASFV surveillance and highlights the necessity of targeted experimental validation for rare viral modifications.

African Swine Fever Virus↗

PubMed2026

Disentangling covariate effects on single-cell-resolved epigenomes with DeepDive.

Understanding the effects of individual biological factors from single-cell-resolved epigenomic data is hindered by multicollinearity, particularly in human cohorts. We introduce DeepDive, a deep-learning framework designed to systematically disentangle known and unknown sources of variation in single-nucleus ATAC-seq data. DeepDive accurately reconstructs chromatin accessibility, outperforms state-of-the-art methods with incomplete covariate information, and robustly recovers true biological signals from even highly entangled covariates, unlocking counterfactual, "what-if," analyses. Applying DeepDive to pancreatic islet cells, we perform counterfactual analyses to prioritize covariates associated with a type 2 diabetes-linked beta-cell subtype and nominate transcription regulators. DeepDive offers a powerful and unbiased tool for mechanistic discovery in complex human disease cohorts.

disentanglement↗

PubMed2024

Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures.

Regular exercise has many physical and brain health benefits, yet the molecular mechanisms mediating exercise effects across tissues remain poorly understood. Here we analyzed 400 high-quality DNA methylation, ATAC-seq, and RNA-seq datasets from eight tissues from control and endurance exercise-trained (EET) rats. Integration of baseline datasets mapped the gene location dependence of epigenetic control features and identified differing regulatory landscapes in each tissue. The transcriptional responses to 8 weeks of EET showed little overlap across tissues and predominantly comprised tissue-type enriched genes. We identified sex differences in the transcriptomic and epigenomic changes induced by EET. However, the sex-biased gene responses were linked to shared signaling pathways. We found that many G protein-coupled receptor-encoding genes are regulated by EET, suggesting a role for these receptors in mediating the molecular adaptations to training across tissues. Our findings provide new insights into the mechanisms underlying EET-induced health benefits across organs.

Animals↗

PubMed2026

ChromCall: assigning chromatin status to defined genomic regions using epigenomic profiling data.

MOTIVATION: Chromatin regulation is crucial for modulating gene expression and cellular function by altering DNA accessibility. Defining and understanding chromatin regulation across diverse biological conditions, including health and disease, requires quantification of both the presence and enrichment level of diverse DNA-binding factors and chromatin modifications across defined genomic regions. Existing approaches mainly rely on peak-based or genome-wide models, which identify high-signal regions but do not annotate chromatin status at predefined functional genomic regions, such as promoters or enhancers. This lack of region-based annotation limits downstream comparative and integrative analyses across multiple factors and datasets, prompting us to create ChromCall. RESULTS: ChromCall is an R package for region-based chromatin enrichment analysis that provides a robust and extensible foundation for transparent and reproducible epigenomic profiling at predefined genomic regions. We applied ChromCall to ChIP-seq data from glioblastoma (GBM) brain tumours and found that the promoters of genes implicated in treatment resistance are significantly more likely to exhibit a combination of histone marks associated with phenotypic plasticity. This highlights a potential novel mechanism of therapeutic escape in these deadly tumours. AVAILABILITY AND IMPLEMENTATION: The R package is available on https://github.com/GliomaGenomics/ChromCall and the version used in this paper is archived at https://doi.org/10.5281/zenodo.19580967.

Chromatin↗

PubMed2025

Epigenome-Wide Analysis Identifies Pollution-Sensitive Loci in Fibrotic Interstitial Lung Disease.

Rationale: Particulate matter ⩽2.5 μm (PM2.5) adversely impacts patients with fibrotic interstitial lung disease (fILD). Objectives: We sought to determine whether PM2.5-associated epigenetic alterations contribute to the environmental pathogenesis of fILD. Methods: A retrospective two-cohort study applied satellite-derived PM2.5 and constituent exposure matching to the residential location of patients with fILD. Robust linear regressions were used to evaluate cohort-specific, epigenome-wide differential blood DNA methylation with increasing pollutant exposures (Illumina MethylationEPIC BeadChip). Cox and linear regressions were used to evaluate associations of cytosine-phosphate-guanine (CpG) loci with transplant-free survival and lung function. A Wilcoxon test was used to evaluate cartilage-associated protein (CRTAP) levels in fILD and control lungs. Measurements and Main Results: The University of Pittsburgh cohort (n = 306) had 5-year median PM2.5 exposures of 12.1 μg/m3 compared with 5.1 μg/m3 in the University of British Columbia cohort (n = 170). Higher pollutant exposures in the University of Pittsburgh cohort were associated with lower methylation at cg25354716, annotated to CRTAP, a critical extracellular matrix remodeling enzyme. Higher exposures in the University of British Columbia cohort were associated with higher methylation at cg01019301, annotated to TLN2 (talin-2), a cytoskeletal protein involved in fibroblast migration. A 10% increase in cg25354716 methylation was associated with a hazard ratio of 0.81 for death or lung transplantation in the meta-analyzed cohorts (95% confidence interval = 0.69-0.96; P = 0.01), whereas the same change in cg01019301 was associated with a hazard ratio of 1.36 (95% confidence interval = 1.07-1.74; P = 0.01). CRTAP protein was more abundant in lungs from patients with fILD compared with those from donor controls (P < 0.001). Conclusions: PM2.5 is associated with altered blood DNA methylation in fILD. This work identifies novel pollution-sensitive targets that hold potential for therapeutic modulation in fILD.

Humans↗

PubMed2025

Distinct transcriptional and epigenomic programs define Hofbauer cells in term placenta.

Hofbauer cells (HBCs) are fetal macrophages located in the placenta that contribute to antimicrobial defense, angiogenesis, tissue remodeling, and metabolic processes within the chorionic villi. Although their roles in placental biology are increasingly recognized, the mechanisms that regulate HBC identity and function are not yet fully defined. This study aimed to define the core transcriptomic and epigenomic features of HBCs in term placentas and to examine their capacity for transcriptional responsiveness and phenotypic variation. Using chromatin accessibility profiling and bulk RNA-seq, we found that HBCs exhibit a unique gene expression and chromatin accessibility profile compared with other fetal and adult macrophages. We identified a coordinated transcriptional network involving nuclear receptors (NRs) NR4A1-3, the glucocorticoid receptor, and RFX family members (RFX1, RFX2, RFX5) that appears to shape HBC identity, particularly through pathways linked to lipid metabolism and angiogenesis. Although exploratory in nature, in vitro stimulation studies showed that HBCs exhibited increased transcriptional activity in response to combined IL-4 and rosiglitazone treatment, including induction of the lipid transporter CD36. Mass cytometry analysis revealed surface markers indicative of both immature and mature macrophage states. These results together indicate that HBCs are a distinct and diverse population of macrophages with a specialized, adaptable regulatory program in the human placenta.

Female↗

PubMed2026

Targeted long-read genomic and epigenomic profiling enhances timely comprehensive variant discovery in hypotonia and muscle weakness.

BACKGROUND: Identifying the genetic basis of hypotonia and muscle weakness is critical for patient management and family counseling. However, diagnosis is often hindered by diverse genomic alterations, including repeat expansions, structural variants (SVs), and methylation defects. Standard-of-care testing, largely based on short-read sequencing, is limited in its ability to detect this heterogeneous variation landscape, leaving many patients undiagnosed or requiring lengthy sequential testing. Long-read sequencing represents a promising solution. However, its application as a first-tier diagnostic assay for hypotonia remains unexplored. METHODS: We retrospectively analyzed 227 patients with hypotonia to assess diagnostic yield, time-to-diagnosis, and costs associated with standard-of-care testing. A long-read whole-genome sequencing (LR-WGS) workflow with targeted analysis of hypotonia-associated genes was developed to detect and prioritize pathogenic SNVs, SVs, and CNVs, repeat expansions, and methylation changes at key disease loci. The workflow was validated in a reference-positive cohort with known diagnoses (n = 15) and applied to an unsolved cohort (n = 14). Variant interpretation followed ACMG guidelines and was confirmed with orthogonal methods. RESULTS: Standard-of-care testing achieved a diagnostic yield of 42% with an average time-to-diagnosis of 68.7 days; however, 30% of diagnosed patients experienced significant delays (average 169 days) due to sequential testing. The LR-WGS based approach identified all known pathogenic variants in the positive cohort, including SMN1 deletions, methylation defects at 15q11.2/Prader-Willi locus, FMR1 repeat expansions, and sequence and copy-number variants in > 100 genes underlying myopathies and muscular dystrophies. The targeted long-read pipeline reduced prioritized variant calls by 97.9-99.9% and, in the unsolved cohort, yielded one definitive diagnosis (de novo COL6A3 deletion) and one possible diagnosis (aberrant methylation and copy number at POMK), for an additional 14% yield. Among patients diagnosed after sequential testing (n = 29), LR-WGS is expected to reduce time-to-diagnosis by ~ 85% and decrease cumulative diagnostic delays, with projected healthcare cost savings of $396,000-439,000. Across the entire 227 patient cohort, LR-WGS is anticipated to reduce testing costs by 6.5%, yielding an average savings of $105 per patient. CONCLUSIONS: LR-WGS enables comprehensive discovery of genomic and epigenomic variants in hypotonia and muscle weakness, improving diagnostic yield, shortening diagnostic timelines, and reducing costs compared with current standard-of-care testing.

Humans↗

PubMed2026

Clinical Relevance of Post-Treatment Circulating Tumor DNA Detection in Early Breast Cancer Using a Tissue-Free Epigenomic Assay: A 2-Year Landmark Analysis.

PURPOSE: Circulating tumor DNA (ctDNA) may serve as a biomarker to facilitate early identification of asymptomatic distant tumor spread in patients with breast cancer. The primary objective of this study was to assess clinical validity and prognostic value of post-treatment tissue-free ctDNA detection by evaluating its sensitivity for distant metastatic recurrence and its association with long-term outcomes. PATIENTS AND METHODS: Plasma samples were prospectively collected from patients with stage I-III early breast cancer who participated in the adjuvant SUCCESS-A phase III clinical trial (ClinicalTrials.gov identifier: NCT02181101). In this study, plasma samples collected approximately 2 years after completion of adjuvant chemotherapy from 313 SUCCESS A patients without evidence of prior disease recurrence were retrospectively analyzed using a tissue-free epigenomic ctDNA assay (Guardant Reveal). Survival analyses were performed using a landmark approach based on the time of sample collection. RESULTS: Overall, ctDNA was detected in 18 of 313 samples (5.8%). Of all ctDNA detected samples, 94% (17/18) were from patients who subsequently developed a distant recurrence, with ctDNA detected at a median interval of 7.9 months before recurrence. ctDNA positivity was strongly associated with a significantly shorter distant recurrence-free interval (hazard ratio [HR], 33.3 [95% CI, 4.12 to 268]; P < .0001) and poorer overall survival (HR, 27.3 [95% CI, 1.15 to 647]; P < .0001). The sensitivity for distant recurrence in patients who had a sample collected within 1 year before recurrence was 73% (11/15). The specificity in nonrecurred patients was 99.6% (267/268). CONCLUSION: Tissue-free detection of ctDNA 2 years after adjuvant chemotherapy was highly prognostic in an early-stage breast cancer cohort, and can be used to stratify patients with early-stage breast cancer at high risk for recurrence during follow-up who may benefit from early interventions.

Humans↗

PubMed2026

Genomic and epigenomic diversity of breast cancer across Western and MENA populations: implications for precision oncology.

Breast cancer is the most common malignancy in women worldwide and is increasingly recognized as a biologically diverse disease shaped by both molecular and ancestral context. Women from the Middle East and North Africa (MENA) populations, including Saudi Arabia, often present at a younger age and with more aggressive subtypes such as HER2-positive and triple-negative breast cancer (TNBC) compared with Western cohorts. These clinical patterns reflect a distinctive genomic background marked by high consanguinity, founder mutations in key susceptibility genes, and population-specific somatic alterations that are not fully captured in global reference datasets. This review brings together current evidence on somatic, germline, transcriptomic, and epigenomic diversity in breast cancer across Western and MENA populations, with a focus on Saudi cohorts. Drawing on a previously published systematic review of more than 2,500 MENA breast cancer cases, TP53 accounted for approximately 24% and PIK3CA for roughly 10% of curated somatic mutation records pooled across 44 studies (proportions of mutation calls, not per-patient prevalence); in a separate single-center Saudi cohort, only 3.7% of patients underwent BRCA testing, and 37.5% of this clinically selected, testing-referred subgroup carried a pathogenic variant, a figure that should not be read as general-population BRCA prevalence. Variants of uncertain significance exceeded 20% across several regional genomic studies. We summarize conserved driver events, such as recurrent TP53 and PIK3CA mutations, while highlighting regional features, including unique stop-gain and loss-of-function variants, a high copy-number burden, and early-onset disease linked to ancestral architecture. We also discuss emerging data on MENA-specific regulatory signatures, including immune-enriched and basal-myo transcriptomic clusters, CIMP-like methylation patterns, and non-coding RNA networks; these associations are numerically suggestive in available cohorts but have not reached statistical significance in existing studies and warrant validation in larger, dedicated MENA/Saudi cohorts before being considered established determinants of treatment response and resistance. Finally, we examine the clinical implications of this diversity for biomarker development, pharmacogenomics, and access to targeted therapies, and outline practical steps toward ancestry-aware precision oncology in the region.

BRCA↗

PubMed2026

Genome-wide epigenomic atlas and multi-omics responses of Eriocheir sinensis to natural extreme heat.

BACKGROUND: Global climate warming has led to increasingly frequent and prolonged extreme summer heat events, posing severe environmental challenges to aquaculture systems. Extreme summer heat can disrupt the performance of pond-cultured ectotherms. The Chinese mitten crab (Eriocheir sinensis) is an economically important freshwater crustacean, but coordinated molecular differences following contrasting natural summers remain incompletely characterized. RESULTS: We performed a comprehensive multi-omics analysis integrating meteorological monitoring, mRNA/lncRNA transcriptomics, small-RNA profiling of miRNAs, DNA methylomics, and LC-MS metabolomics in E. sinensis populations collected from Yancheng, China, between 2020 and 2024. Across the ten farms, survival was significantly lower in 2024, whereas yield and the proportion of large individuals showed nonsignificant downward trends. Gene-set analyses showed negative enrichment of cellular heat-response, protein-folding, oxidative-phosphorylation, and mitochondrial ATP-production terms in the 2024 cohort at the time of sampling. The integrated transcript annotation contained 72,240 lncRNAs and 63,833 mRNAs, and CpG was the predominant methylation context. Differential methylation analysis identified 73 regions and 185 cytosines, with hypomethylated events predominating within the significant subset. Metabolomic profiles differed between annual cohorts and mapped to carbohydrate, lipid, and amino-acid pathways. Cross-omics integration prioritized eight candidate genes-ADCY9, UNC79, UBN1, IFT52, ACO2, LOC126986070, LOC127001126, and LOC126997895-and qPCR reproduced the reported directions of expression for selected RNAs. CONCLUSION: This study provides the first integrative multi-omics framework for understanding chronic heat adaptation in E. sinensis. By linking transcriptomic, epigenomic, and metabolic remodeling, we elucidate the molecular mechanisms underlying energy imbalance, epigenetic reprogramming, and immune dysregulation during prolonged thermal stress. These findings offer valuable insights and genomic resources for breeding heat-tolerant crab strains and improving aquaculture resilience under ongoing climate change.

DNA methylation↗

PubMed2017

Rapid and reversible epigenome editing by endogenous chromatin regulators.

Understanding the causal link between epigenetic marks and gene regulation remains a central question in chromatin biology. To edit the epigenome we developed the FIRE-Cas9 system for rapid and reversible recruitment of endogenous chromatin regulators to specific genomic loci. We enhanced the dCas9-MS2 anchor for genome targeting with Fkbp/Frb dimerizing fusion proteins to allow chemical-induced proximity of a desired chromatin regulator. We find that mSWI/SNF (BAF) complex recruitment is sufficient to oppose Polycomb within minutes, leading to activation of bivalent gene transcription in mouse embryonic stem cells. Furthermore, Hp1/Suv39h1 heterochromatin complex recruitment to active promoters deposits H3K9me3 domains, resulting in gene silencing that can be reversed upon washout of the chemical dimerizer. This inducible recruitment strategy provides precise kinetic information to model epigenetic memory and plasticity. It is broadly applicable to mechanistic studies of chromatin in mammalian cells and is particularly suited to the analysis of endogenous multi-subunit chromatin regulator complexes.Understanding the link between epigenetic marks and gene regulation requires the development of new tools to directly manipulate chromatin. Here the authors demonstrate a Cas9-based system to recruit chromatin remodelers to loci of interest, allowing rapid, reversible manipulation of epigenetic states.

CRISPR-Cas Systems↗

PubMed2026

3D epigenome of glial cell types in developing human cortex.

The human cortex is complex and heterogeneous, undergoing extensive expansion during development1,2. Our prior study of neurogenesis, including radial glia (RG), intermediate progenitor cells, excitatory neurons and interneurons demonstrated that chromatin looping underlies transcriptional regulation for lineage-specific genes, shedding light on how non-coding genetic variants contribute to neuropsychiatric disorders by means of cell-type-specific gene regulation3. RG have a crucial role in generating cellular diversity through both neurogenesis and gliogenesis and can be further classified into ventricular RG (vRG) and outer RG (oRG)4,5. Given their significance in cortical development, we conducted a comprehensive three-dimensional (3D) epigenomic analysis of four main glial populations, including vRG, oRG, oligodendrocyte precursor cells and microglia, from the mid-gestational human neocortex. By integrating gene expression, chromatin accessibility, DNA methylation and 3D chromatin interactions, we identified cell-type-specific candidate cis-regulatory elements (cCREs) and validated their regulatory function using transgenic mouse embryos. Using machine learning, we prioritized 112 schizophrenia risk variants within glia cCREs and further confirmed the predicted vRG enhancer disruption by the rs4449074 risk allele in vivo. Finally, oRG cCREs are enriched for human accelerated regions compared with other cCREs and a subset of human accelerated regions show activity differences from their chimpanzee orthologues that interact with genes involved in neuronal development. Our findings advance the understanding of human-specific gene regulation during corticogenesis.

Journal Article↗

PubMed2025

Epigenome-wide association study of placental co-methylated regions in newborns for prenatal opioid exposure.

The increasing incidence of opioid use during pregnancy has led to a rise in the number of infants exposed to opioids in utero. Prenatal opioid exposure may have consequences for health and (neuro)development, including neonatal opioid withdrawal syndrome (NOWS). It is unknown which infants are at greatest risk for NOWS. DNA methylation (DNAm) is an epigenetic mark reflecting both allelic variation and environmental exposures, which may provide biomarkers for prenatal opioid exposure and infant NOWS. The placenta is an accessible, biologically relevant tissue in which to directly investigate the epigenetic effects of prenatal opioid exposure. Therefore, the aims of this study were to examine whether prenatal opioid exposure is associated with differential DNAm, including epigenetic age acceleration (EAA) in the placenta. We performed an epigenome-wide association study based on co-methylated regions and single CpG sites in placental samples from in utero opioid-exposed (n = 19) and nonexposed infants (n = 143), correcting for potential confounders. We did not identify statistically significant differential DNAm profiles, but the strongest associations were found for cg06621211; cg18688392 (ZMIZ1, adjusted P = .068) and cg04460738 (KCNMA1, adjusted P = .068), although effect sizes were very small. One of these DNAm patterns (cg06621211) was in part under control of genetic variants through methylation quantitative trait loci. The involved single nucleotide polymorphism did not show significant associations in recent genome-wide association studies for phenotypes related to substance use, and the finding was not driven by potential co-occurring substance use based on sensitivity analyses. There was also no association between placental EAA and in utero opioid exposure. In conclusion, placental DNAm showed limited associations with in utero opioid exposure and NOWS diagnosis.

DNA methylation↗