'; ?> geneimprint : Hot off the Press http://www.geneimprint.com/site/hot-off-the-press Daily listing of the most recent articles in epigenetics and imprinting, collected from the PubMed database. en-us Fri, 20 Dec 2024 07:26:43 EST Fri, 20 Dec 2024 07:26:43 EST jirtle@radonc.duke.edu james001@jirtle.com EpiGePT: a pretrained transformer-based language model for context-specific human epigenomics. Gao Z, Liu Q, Zeng W, Jiang R, Wong WH
Genome Biol (Dec 2024)

The inherent similarities between natural language and biological sequences have inspired the use of large language models in genomics, but current models struggle to incorporate chromatin interactions or predict in unseen cellular contexts. To address this, we propose EpiGePT, a transformer-based model designed for predicting context-specific human epigenomic signals. By incorporating transcription factor activities and 3D genome interactions, EpiGePT outperforms existing methods in epigenomic signal prediction tasks, especially in cell-type-specific long-range interaction predictions and genetic variant impacts, advancing our understanding of gene regulation. A free online prediction service is available at http://health.tsinghua.edu.cn/epigept .]]> Wed, 31 Dec 1969 19:00:00 EST DNA methylation and histone modifications associated with antipsychotic treatment: a systematic review. Marques D, Vaziri N, Greenway SC, Bousman C
Mol Psychiatry (Jan 2025)

Antipsychotic medications are essential when treating schizophrenia spectrum and other psychotic disorders, but the efficacy and tolerability of these medications vary from person to person. This interindividual variation is likely mediated, at least in part, by epigenomic processes that have yet to be fully elucidated. Herein, we systematically identified and evaluated 65 studies that examine the influence of antipsychotic drugs on epigenomic changes, including global methylation (9 studies), genome-wide methylation (22 studies), candidate gene methylation (16 studies), and histone modification (18 studies). Our evaluation revealed that haloperidol was consistently associated with increased global hypermethylation, which corroborates with genome-wide analyses, mostly performed by methylation arrays. In contrast, clozapine seems to promote hypomethylation across the epigenome. Candidate-gene methylation studies reveal varying effects post-antipsychotic therapy. Some genes like Glra1 and Drd2 are frequently found to undergo hypermethylation, whereas other genes such as SLC6A4, DUSP6, and DTNBP1 are more likely to exhibit hypomethylation in promoter regions. In examining histone modifications, the literature suggests that clozapine changes histone methylation patterns in the prefrontal cortex, particularly elevating H3K4me3 at the Gad1 gene and affecting the transcription of genes like mGlu2 by modifying histone acetylation and interacting with HDAC2 enzymes. Risperidone and quetiapine, however, exhibit distinct impacts on histone marks across different brain regions and cell types, with risperidone reducing H3K27ac in the striatum and quetiapine modifying global H3K9me2 levels in the prefrontal cortex, suggesting antipsychotics demonstrate selective influence on histone modifications, which demonstrates a complex and targeted mode of action. While this review summarizes current knowledge, the intricate dynamics between antipsychotics and epigenetics clearly warrant more exhaustive exploration with the potential to redefine our understanding and treatment of psychiatric conditions. By deciphering the epigenetic changes associated with drug treatment and therapeutic outcomes, we can move closer to personalized medicine in psychiatry.]]> Wed, 31 Dec 1969 19:00:00 EST Using Callus as an Ex Vivo System for Chromatin Analysis. Lavie O, Williams LE
Methods Mol Biol (2025)

Next-generation sequencing has revolutionized epigenetics research, enabling a comprehensive analysis of DNA methylation and histone modification profiles to explore complex biological systems at unprecedented depth. Deciphering the intricate epigenetic mechanisms that regulate gene activity presents significant challenges, including the issue of analyzing heterogeneous cell populations in bulk. Bulk analysis introduces bias and can obscure crucial information by averaging readouts from distinct cells. Various approaches have been developed to address this issue, such as cell-type-specific enrichment or single-cell sequencing techniques. However, the need for transgenic lines with fluorescent markers, along with technical challenges such as efficient protoplast isolation and low yield, limits their widespread adoption and use in multi-omic studies. This review discusses the pros and cons of these approaches, providing a valuable basis for selecting the most suitable strategy to minimize heterogeneity. We will also highlight the use of cotyledon-derived callus as an ex vivo system as a simple, accessible, and robust platform for enabling high-throughput multi-omic analyses.]]> Wed, 31 Dec 1969 19:00:00 EST Omics Approaches to Investigate the Pathogenesis of Suicide. Boldrini M, Xiao Y, Singh T, Zhu C, Jabbi M, Pantazopoulos H, Gürsoy G, Martinowich K, Punzi G, Vallender EJ, Zody M, Berretta S, Hyde TM, Kleinman JE, Marenco S, Roussos P, Lewis DA, Turecki G, Lehner T, Mann JJ
Biol Psychiatry (Dec 2024)

Suicide is the second leading cause of death in U.S. adolescents and young adults and is generally associated with a psychiatric disorder. Suicidal behavior has a complex etiology and pathogenesis. Moderate heritability suggests genetic causes. Associations between childhood and recent life adversity indicate contributions from epigenetic factors. Genomic contributions to suicide pathogenesis remain largely unknown. This article is based on a workshop held to design strategies to identify molecular drivers of suicide neurobiology that would be putative new treatment targets. The panel determined that while bulk tissue studies provide comprehensive information, single-nucleus approaches that identify cell type-specific changes are needed. While single-nuclei techniques lack information on cytoplasm, processes, spines, and synapses, spatial multiomic technologies on intact tissue detect cell alterations specific to brain tissue layers and subregions. Because suicide has genetic and environmental drivers, multiomic approaches that combine cell type-specific epigenome, transcriptome, and proteome provide a more complete picture of pathogenesis. To determine the direction of effect of suicide risk gene variants on RNA and protein expression and how these interact with epigenetic marks, single-nuclei and spatial multiomics quantitative trait loci maps should be integrated with whole-genome sequencing and genome-wide association databases. The workshop concluded with a recommendation for the formation of an international suicide biology consortium that will bring together brain banks and investigators with expertise in cutting-edge omics technologies to delineate the biology of suicide and identify novel potential treatment targets to be tested in cellular and animal models for drug and biomarker discovery to guide suicide prevention.]]> Wed, 31 Dec 1969 19:00:00 EST HiChIP for Plant Tissues. Brik Chaouche R, Raynaud C, Benhamed M, Latrasse D
Methods Mol Biol (2025)

While most epigenomics studies are based on a linear view of genome organization, the necessity to take the three-dimensional chromatin folding into account to understand transcriptional regulation is now clearly recognized. In the past years, approaches combining proximity-based ligation with high-throughput sequencing have opened the way to study long/short-range chromatin interactions and, thus, to analyze 3D chromatin organization. Among them, HiChIP, a protein-based method to capture chromatin interactions, gave rise to the most comprehensive view of the chromatin contacts involving specific chromatin components in a given system. Here, we describe a detailed procedure to produce HiChIP libraries starting from plant tissues.]]> Wed, 31 Dec 1969 19:00:00 EST Insight into metabolic dysregulation of polycystic ovary syndrome utilizing metabolomic signatures: a narrative review. Naigaonkar A, Dadachanji R, Kumari M, Mukherjee S
Crit Rev Clin Lab Sci (Dec 2024)

Polycystic ovary syndrome (PCOS) is a complex multifactorial endocrinopathy affecting reproductive aged women globally, whose presentation is strongly influenced by genetic makeup, ethnic, and geographic diversity leaving these affected women substantially predisposed to reproductive and metabolic perturbations. Sophisticated techniques spanning genomics, proteomics, epigenomics, and transcriptomics have been harnessed to comprehensively understand the enigmatic pathophysiology of PCOS, however, conclusive markers for PCOS are still lacking today. Metabolomics represents a paradigm shift in biotechnological advances enabling the simultaneous identification and quantification of metabolites and the use of this approach has added yet another dimension to help unravel the strong metabolic component of PCOS. Reports dissecting the metabolic signature of PCOS have revealed disparate levels of metabolites such as pyruvate, lactate, triglycerides, free fatty acids, carnitines, branched chain and essential amino acids, and steroid intermediates in major biological compartments. These metabolites have been shown to be altered in women with PCOS overall, after phenotypic subgrouping, in animal models of PCOS, and also following therapeutic intervention. This review seeks to supplement previous reviews by highlighting the aforementioned aspects and to provide easy, coherent and elementary access to significant findings and emerging trends. This will in turn help to delineate the metabolic plot in women with PCOS in various biological compartments including plasma, urine, follicular microenvironment, and gut. This may pave the way to design additional studies on the quest of unraveling the etiology of PCOS and delving into novel biomarkers for its diagnosis, prognosis and management.]]> Wed, 31 Dec 1969 19:00:00 EST Research progress and the prospect of using single-cell sequencing technology to explore the characteristics of the tumor microenvironment. Zhang W, Zhang X, Teng F, Yang Q, Wang J, Sun B, Liu J, Zhang J, Sun X, Zhao H, Xie Y, Liao K, Wang X
Genes Dis (Jan 2025)

In precision cancer therapy, addressing intra-tumor heterogeneity poses a significant obstacle. Due to the heterogeneity of each cell subtype and between cells within the tumor, the sensitivity and resistance of different patients to targeted drugs, chemotherapy, , are inconsistent. Concerning a specific tumor type, many feasible treatments or combinations can be used by specifically targeting the tumor microenvironment. To solve this problem, it is necessary to further study the tumor microenvironment. Single-cell sequencing techniques can dissect distinct tumor cell populations by isolating cells and using statistical computational methods. This technology may assist in the selection of targeted combination therapy, and the obtained cell subset information is crucial for the rational application of targeted therapy. In this review, we summarized the research and application advances of single-cell sequencing technology in the tumor microenvironment, including the most commonly used single-cell genomic and transcriptomic sequencing, and their future development direction was proposed. The application of single-cell sequencing technology has been expanded to include epigenomics, proteomics, metabolomics, and microbiome analysis. The integration of these different omics approaches has significantly advanced the development of single-cell multiomics sequencing technology. This innovative approach holds immense potential for various fields, such as biological research and medical investigations. Finally, we discussed the advantages and disadvantages of using single-cell sequencing to explore the tumor microenvironment.]]> Wed, 31 Dec 1969 19:00:00 EST Cognitive benefits of folic acid supplementation during pregnancy track with epigenetic changes at an imprint regulator. Hilman L, Ondičová M, Caffrey A, Clements M, Conway C, Ward M, Pentieva K, Irwin RE, McNulty H, Walsh CP
BMC Med (Dec 2024)

The human ZFP57 gene is a major regulator of imprinted genes, maintaining DNA methylation marks that distinguish parent-of-origin-specific alleles. DNA methylation of the gene itself has shown sensitivity to environmental stimuli, particularly folate status. However, the role of DNA methylation in ZFP57's own regulation has not been fully investigated.]]> Wed, 31 Dec 1969 19:00:00 EST ChIPmentation for Epigenomic Analysis in Fission Yeast. Dewornu FS, Tong P, Torres-Garcia S, Pidoux A, Allshire R, Shukla M
Methods Mol Biol (2025)

Histone modifications and transcription factor-DNA interactions regulate vital processes such as transcription, recombination, repair, and accurate chromosome segregation. Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has been instrumental in studying genome-wide distribution of DNA-bound or chromatin-associated factors and histone posttranslational modifications (PTMs). Here, we describe a ChIPmentation protocol adapted for fission yeast, Schizosaccharomyces pombe. This method merges Tn5 mediated tagmentation with existing ChIP protocols, resulting in lower sample input requirements with significant reduction in hands-on time and sample preparation costs.]]> Wed, 31 Dec 1969 19:00:00 EST Clinical utility of regions of homozygosity (ROH) identified in exome sequencing: when to pursue confirmatory uniparental disomy testing for imprinting disorders? Huo X, Lu X, Lu D, Liu H, Liu Y, Zhao Q, Sun Y, Dai W, Qiu W, Yu Y, Fan Y
Clin Chem Lab Med (Jan 2025)

Regions of homozygosity (ROH) could implicate uniparental disomy (UPD) on specific chromosomes associated with imprinting disorders. Though the algorithms for ROH detection in exome sequencing (ES) have been developed, optimal reporting thresholds and when to pursue confirmatory UPD testing for imprinting disorders remain in ambiguity. This study used a data-driven approach to assess optimal reporting thresholds of ROH in clinical practice.]]> Wed, 31 Dec 1969 19:00:00 EST Postoperative Innate Immune Dysregulation, Proteomic, and Monocyte Epigenomic Changes After Colorectal Surgery: A Substudy of a Randomized Controlled Trial. Albers-Warlé KI, Helder LS, Groh LA, Polat F, Panhuizen IF, Snoeck MMJ, Kox M, van Eijk L, Joosten LAB, Netea MG, Negishi Y, Mhlanga M, Keijzer C, Scheffer GJ, Warlé MC
Anesth Analg (Jan 2025)

Colorectal surgery is associated with moderate-to-severe postoperative complications in over 25% of patients, predominantly infections. Monocyte epigenetic alterations leading to immune tolerance could explain postoperative increased susceptibility to infections. This research explores whether changes in monocyte DNA accessibility contribute to postoperative innate immune dysregulation.]]> Wed, 31 Dec 1969 19:00:00 EST Parent of origin genetic effects on milk production traits in a population of Iranian Holstein cows. Ghafouri-Kesbi F, Noorian M, Gholizadeh S, Mokhtari M
J Anim Breed Genet (Jan 2025)

The aim was to estimate the relative contribution of imprinting effects from both paternal and maternal sides to phenotypic variation in milk production traits including 305 days milk yield (MY), average daily milk production (ADM), fat percentage (F%), protein percentage (P%), 305 days fat yield (FY), 305 days protein yield (PY), ratio of fat percentage to protein percentage (F:P) and somatic cell score (SCS) in Iranian Holstein cows. To do this, each trait was analysed with a series of four animal models, which were identical for fixed and additive genetic effects but differed for combinations of paternal and maternal imprinting effects. The log-likelihood ratio test (LRT) and Akaike's information criteria (AIC) were used to select the best model for each trait. Correlations between traits due to additive and imprinting effects were estimated by bivariate analyses. For all traits studied, fitting the imprinting effect led to a better data fit. Also, it resulted in a noticeable decrease in additive genetic variance from 8% (SCS) to 28% (F:P). A significant maternal imprinting effect was detected on all traits studied. Estimates of maternal imprinting heritability ( ) were 0.07 ± 0.02, 0.04 ± 0.01, 0.06 ± 0.01, 0.05 ± 0.01, 0.5 ± 0.01, 0.09 ± 0.02, 0.07 ± 0.02 and 0.06 ± 0.01 for MY, ADM, F%, P%, FY, PY, F:P and SCS, respectively. For F:P, in addition to the maternal imprinting effect, a significant paternal imprinting component was also detected with a 7% contribution to phenotypic variance of F:P. Estimates of direct heritability ( ) were 0.29 ± 0.02, 0.17 ± 0.01, 0.22 ± 0.02, 0.11 ± 0.01, 0.18 ± 0.02, 0.22 ± 0.02, 0.15 ± 0.04 and 0.06 ± 0.01 for MY, ADM, F%, P%, FY, PY, F:P and SCS, respectively. Maternal imprinting correlations (r) were in a wide range between -0.75 ± 0.15 (P%-SCS) and 0.95 ± 0.11 (MY-ADM). Additive genetic correlations (r) ranged between -0.54 ± 0.05 (MY-P%) and 0.99 ± 0.01 (MY-ADM) and phenotypic correlations (r) ranged from -0.30 ± 0.01 (MY-F%) to 0.93 ± 0.01 (MY-ADM). The Spearman's correlation between additive breeding values including and excluding imprinting effects deviated from unity especially for top-ranked animals implying re-ranking of top animals following the inclusion of imprinting effects in the model. Since including imprinting effects in the model resulted in better data fit and re-ranking of top animals, including these effects in the genetic evaluation models for milk production traits was recommended.]]> Wed, 31 Dec 1969 19:00:00 EST Exploring the use of immunomethylomics in the characterization of depressed patients: A proof-of-concept study. Van Assche E, Hohoff C, Su Atil E, Wissing SM, Serretti A, Fabbri C, Pisanu C, Squassina A, Minelli A,  , Baune BT
Brain Behav Immun (Jan 2025)

Alterations in DNA methylation and inflammation could represent valid biomarkers for the stratification of patients with major depressive disorder (MDD). This study explored the use of DNA-methylation based immunological cell-type profiles in the context of MDD and symptom severity over time. In 119 individuals with MDD, DNA-methylation was assessed on whole blood using the Illumina Infinium MethylationEPIC 850 k BeadChip. Quality control and data processing, as well as cell type estimation was conducted using the RnBeads package. The cell type composition was estimated using epigenome-wide DNA methylation signatures, applying the Houseman method, considering six cell types (neutrophils, natural killer cells (NK), B cells, CD4+ T cells, CD8+ T cells and monocytes). Two cytokines (IL-6 and IL-1β) and hsCRP were quantified in serum. We performed a hierarchical cluster analysis on the six estimated cell-types and tested the differences between these clusters in relation to the two cytokines and hsCRP, depression severity at baseline, and after 6 weeks of treatment (celecoxib/placebo + vortioxetine). We performed a second cluster analysis with cell-types and cytokines combined. ANCOVA was used to test for differences across clusters. We applied the Bonferroni correction. After quality control, we included 113 participants. Two clusters were identified, cluster 1 was high in CD4+ cells and NK, cluster 2 was high in CD8+ T-cells and B-cells, with similar fractions of neutrophils and monocytes. The clusters were not associated with either of the two cytokines and hsCRP, or depression severity at baseline, but cluster 1 showed higher depression severity after 6 weeks, corrected for baseline (p = 0.0060). The second cluster analysis found similar results: cluster 1 was low in CD8+ T-cells, B-cells, and IL-1β. Cluster 2 was low in CD4+ cells and natural killer cells. Neutrophils, monocytes, IL-6 and hsCRP were not different between the clusters. Participants in cluster 1 showed higher depression severity at baseline than cluster 2 (p = 0.034), but no difference in depression severity after 6 weeks. DNA-methylation based cell-type profiles may be valuable in the immunological characterization and stratification of patients with MDD. Future models should consider the inclusion of more cell-types and cytokines for better a prediction of treatment outcomes.]]> Wed, 31 Dec 1969 19:00:00 EST IDclust: Iterative clustering for unsupervised identification of cell types with single cell transcriptomics and epigenomics. Prompsy P, Saichi M, Raimundo F, Vallot C
NAR Genom Bioinform (Dec 2024)

The increasing diversity of single-cell datasets require systematic cell type characterization. Clustering is a critical step in single-cell analysis, heavily influencing downstream analyses. However, current unsupervised clustering algorithms rely on biologically irrelevant parameters that require manual optimization and fail to capture hierarchical relationships between clusters. We developed IDclust, a framework that identifies clusters with significant biological features at multiple resolutions using biologically meaningful thresholds like fold change, adjusted -value and fraction of expressing cells. By iteratively processing and clustering subsets of the dataset, IDclust guarantees that all clusters found have significantly different features and stops only when no more interpretable cluster is found. It also creates a hierarchy of clusters, enabling visualization of the hierarchical relationships between different clusters. Analyzing multiple single-cell transcriptomic reference datasets, IDclust achieves superior clustering accuracy compared to state of the art algorithms. We showcase its utility by identifying previously unannotated clusters and identifying branching patterns in scATAC datasets. Using it's unsupervised nature and ability to analyze different -omics, we compare the resolution of different histone marks in multi-omic paired-tag dataset. Overall, IDclust automates single-cell exploration, facilitates cell type annotation and provides a biologically interpretable basis for clustering.]]> Wed, 31 Dec 1969 19:00:00 EST Extracting Chromosome Structural Information as One-Dimensional Metrics and Integrating Them with Epigenomics. Wang J, Chen H
Methods Mol Biol (2025)

Hi-C is a powerful method for obtaining genome-wide chromosomal structural information. The typical Hi-C analysis utilizes a two-dimensional (2D) contact matrix, which poses challenges for quantitative comparisons, visualizations, and integrations across multiple datasets. Here, we present a protocol for extracting one-dimensional (1D) features from chromosome structure data by HiC1Dmetrics. Leveraging these 1D features enables integrated analysis of Hi-C and epigenomic data.]]> Wed, 31 Dec 1969 19:00:00 EST Epigenome-wide mediation analysis of the relationship between psychosocial stress and cardiometabolic risk factors in the Health and Retirement Study (HRS). Opsasnick LA, Zhao W, Ratliff SM, Du J, Faul JD, Schmitz LL, Zhou X, Needham BL, Smith JA
Clin Epigenetics (Dec 2024)

Exposure to psychosocial stress is linked to a variety of negative health outcomes, including cardiovascular disease and its cardiometabolic risk factors. DNA methylation has been associated with both psychosocial stress and cardiometabolic disease; however, little is known about the mediating role of DNA methylation on the association between stress and cardiometabolic risk. Thus, using the high-dimensional mediation testing method, we conducted an epigenome-wide mediation analysis of the relationship between psychosocial stress and ten cardiometabolic risk factors in a multi-racial/ethnic population of older adults (n = 2668) from the Health and Retirement Study (mean age = 70.4 years).]]> Wed, 31 Dec 1969 19:00:00 EST Learning Enhancer-Gene associations from Bulk Transcriptomic and Epigenetic Sequencing Data with STITCHIT. Rumpf L, Schulz MH
Methods Mol Biol (2025)

To reveal gene regulation mechanisms, it is essential to understand the role of regulatory elements, which are possibly distant from gene promoters. Integrative analysis of epigenetic and transcriptomic data can be used to gain insights into gene-expression regulation in specific phenotypes. Here, we discuss STITCHIT, an approach to dissect epigenetic variation in a gene-specific manner across many samples for the identification of regulatory elements without relying on peak calling algorithms. The obtained genomic regions are then further refined using a regularized linear model approach, which can also be used to predict gene expression. We illustrate the use of STITCHIT using H3k27ac ChIP-seq and RNA-seq data from the International Human Epigenome Consortium (IHEC).]]> Wed, 31 Dec 1969 19:00:00 EST Metabolomics for enhanced clinical understanding of inflammatory bowel disease. Boye TL, Hammerhøj A, Nielsen OH, Wang Y
Life Sci (Dec 2024)

Metabolomics is an emerging field involving the systematic identification and quantification of numerous metabolites in biological samples. Precision medicine applies multiomics systems biology to individual patients for reliable diagnostic classification, disease monitoring, and treatment. Multiomics systems biology encompasses genomics, transcriptomics, proteomics, epigenomics, and metabolomics. Therefore, metabolomic techniques could be highly valuable for future clinical decision-making. This review provides a technical overview of two commonly used techniques for metabolomics measurements: mass spectrometry (MS) and proton nuclear magnetic resonance (H NMR) spectroscopy. We also discuss recent clinical advances in these techniques. Individuals with inflammatory bowel disease (IBD) exhibit significant variability in prognosis and response to treatment. Since both genetic predisposition and environmental factors contribute to this condition, targeting the metabolome may provide key insights for distinguishing and profiling patients with different clinical needs. Additionally, the considerable overlap in the clinical presentation of various disease subtypes emphasizes the need for enhanced diagnostic methods to improve patient care.]]> Wed, 31 Dec 1969 19:00:00 EST Prediction of Enhancer-Gene Interactions Using Chromatin-Conformation Capture and Epigenome Data Using STARE. Hecker D, Schulz MH
Methods Mol Biol (2025)

Disentangling the relationship of enhancers and genes is an ongoing challenge in epigenomics. We present STARE, our software to quantify the strength of enhancer-gene interactions based on enhancer activity and chromatin contact data. It implements the generalized Activity-by-Contact (gABC) score, which allows predicting putative target genes of candidate enhancers over any desired genomic distance. The only requirement for its application is a measurement of enhancer activity. In addition to regulatory interactions, STARE calculates transcription factor (TF) affinities on gene level. We illustrate its usage on a public single-cell data set of the human heart by predicting regulatory interactions on cell type level, by giving examples on how to integrate them with other data modalities, and by constructing TF affinity matrices.]]> Wed, 31 Dec 1969 19:00:00 EST The epigenetic approach of varicocele: a focus on sperm DNA and m6A-RNA methylation. Naderi N, Tavalaee M, Nasr-Esfahani MH
Hum Reprod Update (Dec 2024)

Varicocele is an abnormal dilation and torsion of the pampiniform venous plexus in the scrotum due to venous reflux, primarily affecting the left side. It affects 15% of men and is a prevalent contributor to male infertility. Varicocele is a complex disorder influenced by genetic, epigenetic, and environmental factors. Epigenetic modifications, which regulate genome activity independently of DNA or RNA sequences, may contribute to the development and severity of varicocele. These include DNA methylation, histone modifications, and RNA modifications like N6-methyladenosine (m6A). Irregularities in DNA and m6A-RNA methylation during spermatogenesis can cause gene expression abnormalities, DNA damage, and decreased fertility in varicocele patients.]]> Wed, 31 Dec 1969 19:00:00 EST