'; ?> 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 Sun, 01 Feb 2026 03:26:12 EST Sun, 01 Feb 2026 03:26:12 EST jirtle@radonc.duke.edu james001@jirtle.com A smoothing method for DNA methylome analysis to enhance epigenomic signature detection in epigenome-wide association studies. Oussalah A, Mousel L, Trégouët DA, Guéant JL
Methods (Feb 2026)

Epigenome-wide association studies (EWAS) are instrumental for mapping DNA methylation changes in human traits and diseases but often suffer from low statistical power and false positives, especially in small cohorts. We developed an EWAS smoothing method that exploits co-methylation of adjacent CpG probes within CpG islands via a sliding-window average and generalized it using Savitzky-Golay filtering. We applied the smoothing approach-with window widths of 1-3 CpGs and, for generalization, Savitzky-Golay filters of varying polynomial orders and window sizes-across five distinct EWAS settings. Performance was quantified by signal-to-noise ratio (SNR), noise-variance reduction, variance ratio (VR), Bayes factors, and sample-size sensitivity. In the MMACHC epimutation dataset, a 5-CpG window (width, w = 2) increased SNR by 90 %, reduced noise variance by 80 %, and elevated VR by 176 % at the target CpG island, with no genome-wide false positives. For MLH1, smoothing preserved the top association and suppressed background signals. In the aging EWAS, a "Polyepigenetic CpG aging score" was derived following smoothing. This score correlated strongly with chronological age in the discovery cohort (Spearman's ρ = 0.89; P = 3.0 × 10) and was independently validated in a separate dataset, significantly distinguishing newborns from nonagenarians (P = 3.4 × 10). Savitzky-Golay filtering of order 0 with a 5-CpG window yielded optimal SNR across bootstrap iterations, supporting this configuration as a robust choice for methylation array smoothing. As an extension of the Savitzky-Golay-based smoothing framework, reanalysis of a liver cancer dataset identified five top loci surpassing a smoothed P-value threshold of 1 × 10. Among these, MIR10A within the HOXB3 locus was the only previously reported functionally relevant site. In conclusion, the smoothing method improves EWAS performance by enhancing SNR, enabling detection of meaningful associations even in small cohorts, and offers a valuable tool for reanalyzing existing Infinium methylation array datasets to uncover previously undetected epigenomic signatures.]]> Wed, 31 Dec 1969 19:00:00 EST Multiomics Data Synthesis of FAM83H in Amelogenesis Imperfecta. Leban T, Kunej T
Int Dent J (Feb 2026)

FAM83H is a critical gene implicated in amelogenesis imperfecta type IIIA (AI type IIIA), but its precise role in enamel formation remains poorly understood. Fragmented datasets, inconsistent terminology, and limited integrative analyses hinder functional interpretation. This study presents a comprehensive multi-omics analysis of FAM83H-associated AI type IIIA.]]> Wed, 31 Dec 1969 19:00:00 EST A cell type enrichment analysis tool for brain DNA methylation data (CEAM). Müller J, Laroche VT, Imm J, Weymouth L, Harvey J, Reijnders RA, Smith AR, van den Hove D, Lunnon K, Cavill R, Pishva E
Epigenetics (Dec 2026)

DNA methylation (DNAm) signatures are highly cell type-specific, yet most epigenome-wide association studies (EWAS) are performed on bulk tissue, potentially obscuring critical cell type-specific patterns. Existing computational tools for detecting cell type-specific DNAm changes are often limited by the accuracy of cell type deconvolution algorithms. Here, we introduce CEAM (Cell-type Enrichment Analysis for Methylation), a robust and interpretable framework for cell type enrichment analysis in DNA methylation data. CEAM applies over-representation analysis with cell type-specific CpG panels from Illumina EPIC arrays derived from nuclei-sorted cortical post-mortem brains from neurologically healthy aged individuals. The constructed CpG panels were systematically evaluated using both simulated datasets and published EWAS results from Alzheimer's disease, Lewy body disease, and multiple sclerosis. CEAM demonstrated resilience to shifts in cell type composition, a common confounder in EWAS, and remained robust across a wide range of differentially methylated positions, when upstream modeling of cell type composition was modeled with sufficient accuracy. Application to existing EWAS findings generated in neurodegenerative diseases revealed enrichment patterns concordant with established disease biology, confirming CEAM's biological relevance. The workflow is publicly available as an interactive Shiny app (https://um-dementia-systems-biology.shinyapps.io/CEAM/) enabling rapid, interpretable analysis of cell type-specific DNAm changes from bulk EWAS.]]> Wed, 31 Dec 1969 19:00:00 EST Forensic genetics in the omics era. Kayser M
Nat Rev Genet (Feb 2026)

Recent advances in forensic genetics, driven by technological innovation coupled with the use of an expanding range of nucleic acid markers, have markedly improved the scope, accuracy and reliability of evidential information obtainable from human biological traces recovered at crime scenes. The majority of these biomarkers have been identified using non-targeted omics approaches, including genomics, transcriptomics, epigenomics and microbiome profiling. Moreover, targeted massively parallel sequencing, in some cases non-targeted whole-genome sequencing, are being applied to the analyses of biological trace material. These approaches and methods are being used for the identification of perpetrators (including monozygotic twins), their relatives or victims of criminal activities; the prediction of phenotypic and behavioural traits of unknown individuals; and the determination of trace characteristics, including tissue type and time of deposition.]]> Wed, 31 Dec 1969 19:00:00 EST : a computational suite for DNA methylation sequencing data analysis. Loyfer N, Rosenski J, Kaplan T
Life Sci Alliance (Apr 2026)

Next-generation methylation-aware sequencing of DNA sheds light on the fundamental role of methylation in cellular function in health and disease, increasing the number of covered CpG sites from hundreds of thousands in previous array-based approaches to tens of millions across the whole genome. While array-based approaches are limited to single-CpG resolution, next-generation sequencing allows for a more detailed, single-molecule fragment-level analysis; however, existing tools to fully use this capability are not yet well developed. Here, we present , an extensive computational suite tailored for methylation sequencing data. allows fast access and ultracompact anonymized representation of high-throughput methylome data, obtained through various library preparation and sequencing methods, with a custom epiread file format achieving a compression factor of over 100x from the input BAM file. In addition, contains state-of-the-art algorithms for genomic segmentation, biomarker identification, genetic and epigenetic data integration, and more. offers fragment-level analysis and informative visualizations, across multiple genomic regions and samples.]]> Wed, 31 Dec 1969 19:00:00 EST Histone variants: Distinct building blocks of the chromatin acting at the core. Hari-Sundar Gandhivel V, Shivaprasad PV
Curr Opin Plant Biol (Feb 2026)

Histone variants alter the core properties of the nucleosomes they decorate and hence constitute a significant epigenetic layer to control cellular processes. Historically, histone variants have been studied using classical genetics to implicate the functions associated with them. However, over the last few years, advanced (epi)genomics and structural investigations have revealed the fine molecular steps involved in histone variant-specific genome regulation. This review outlines the key mechanistic findings that uncovered both structural and functional aspects of plant histone variants in unprecedented resolution. We also highlight the key avenues that might hold potential for future studies, including chromatin engineering using histone variants.]]> Wed, 31 Dec 1969 19:00:00 EST Synergistic integration of clinical and multi-omics data for early MCI diagnosis using an attention-based graph fusion network. Yu S, Zhao J, Ouyang J, Wang X, Kou P, Zhu K, Liu P
J Neurosci Methods (Apr 2026)

Mild cognitive impairment (MCI), a precursor to Alzheimer's disease (AD), requires precise early diagnosis. Single-omics approaches often miss disease complexity, motivating integrative and interpretable solutions.]]> Wed, 31 Dec 1969 19:00:00 EST TALE Homeodomain Proteins in Plant Reproductive Development and Environmental Stress Resilience. Niu X, Jiang X, Li H, Qin R, Qin Y
Plant Cell Environ (Feb 2026)

TALE (Three Amino acid Loop Extension) homeodomain transcription factors are key conserved elements in eukaryotic developmental patterning. In plants, this superclass divides into the KNOX and BELL families, which are essential for regulating meristem maintenance, organogenesis, and tissue identity. Recent advances show that TALE proteins are intricately involved in plant reproductive processes, including gametophyte differentiation, embryonic axis formation, and floral organogenesis. They function as molecular scaffolds, integrating spatiotemporal signals and hormonal signaling like auxin, cytokinin, and gibberellin to control phase transitions and reproductive cell fate determination. The lineage-specific expansions and domain rearrangements of TALE genes across bryophytes, gymnosperms, and angiosperms indicate repeated co-option and neofunctionalization throughout land plant evolution. Emerging insights from epigenomics and protein interactomes reveal that TALE complexes modulate cell type-specific transcriptional responses. This review synthesizes current understanding of TALE-mediated regulatory networks during plant reproductive development and presents a conceptual framework for investigating their roles in developmental plasticity and stress-responsive fertility. We also highlight opportunities to utilize TALE-based regulatory modules to develop climate-resilient crops through multi-omics and genome editing approaches. Decoding the reproductive logic embedded in TALE networks offers transformative potential for reprogramming plant development in an era of agricultural and ecological uncertainty.]]> Wed, 31 Dec 1969 19:00:00 EST ‑folate axis as a modulator of the epigenetic landscape in autoimmune diseases (Review). Navarro-Rodríguez PM, Bajeca-Serrano RF, Turrubiates-Hernández FJ, Ceja-Gálvez HR, Hernández-Bello J, Hernández-Ramírez CO, Ramírez-de Los Santos S, Muñoz-Valle JF
Int J Mol Med (Mar 2026)

The one‑carbon metabolism pathway, regulated by the methylenetetrahydrofolate reductase (MTHFR) enzyme, represents a key nexus where genetic predisposition and nutrient status converge to shape the epigenetic landscape of autoimmune diseases. The objective of the present review is to synthesize evidence of how the ‑folate axis drives epigenomic patterns in these conditions. One of the main diseases involved is rheumatoid arthritis, where drug‑naïve patients show T‑cell and synovial hypomethylation with cytokine‑driven DNMT suppression, a process aggravated by reduced folate availability and polymorphisms that constrain S‑adenosylmethionine supply. Similarly, in systemic lupus erythematosus, CD4 T cells exhibit global hypomethylation with an interferon‑skewed signature (such as ), associated with impaired activity and a folate‑dependent SAM:SAH imbalance that further diminishes DNMT function. Finally, in celiac disease, intestinal differential methylation, including LINE‑1 hypomethylation, is observed, driven by gluten‑induced villous atrophy and folate malabsorption. Overall, impaired one‑carbon metabolism and ‑dependent methylation capacity may be key determinants of epigenomic dysfunction underlying autoimmune disease and its clinical severity.17.]]> Wed, 31 Dec 1969 19:00:00 EST Melatonin-enabled omics: understanding plant responses to single and combined abiotic stresses for climate-smart agriculture. Raza A, Li Y, Charagh S, Guo C, Zhao M, Hu Z
GM Crops Food (Dec 2026)

Climate change-driven single and combined abiotic stresses pose escalating threats to sustainable, climate-smart agriculture and global food security. Melatonin (MLT, a powerful plant biostimulant) has established noteworthy potential in improving stress tolerance by regulating diverse physiological, biochemical, and molecular responses. Therefore, this review delivers a comprehensive synopsis of MLT-enabled omics responses across genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics, phenomics, ionomics, and microbiomics levels that collectively regulate plant adaptation to multiple abiotic stresses. We also highlight the crosstalk between these omics layers and the power of integrated multi-omics (panomics) approaches to harness the complex regulatory networks underlying MLT-enabled stress tolerance. Lastly, we argue for translating these omics insights into actionable strategies through advanced genetic engineering and synthetic biology platforms to develop MLT-enabled, stress-smart crop plants.]]> Wed, 31 Dec 1969 19:00:00 EST CRISPR 2.0: Expanding the genome engineering Toolbox for epigenetics, RNA editing, and molecular diagnostics. Pradhan K, Anoop S
Gene (Feb 2026)

Non-canonical CRISPR systems adaptation has led to genome editing through nucleases, and the development of transcriptional and epigenetic regulation, transcriptome editing, and molecular diagnostics has resulted in a diversified set of tools-CRISPR 2.0. In this review, the author summarizes the mechanisms and recent engineering advances of (i) dCas9-based epigenetic effectors, (ii) RNA-targeting Cas13 systems and engineered RNA editors, (iii) DNA base editors and prime editors, and (iv) CRISPR-powered diagnostic platforms and their translational readiness. There is a critical comparison of the various approaches (e.g., RNAi/ASO versus Cas13-based methods; base editing versus prime editing) along with practical translational considerations such as delivery technologies, safety (off-target/edit windows, mosaicism), and regulatory pathways which are evaluated. Three concise case studies refer to map laboratory evidence to clinical or near-clinical outcomes and the ethical and governance discussion is widened to include global access, intellectual property and equity in deployment. Finally, the authors classify technologies according to their level of readiness - diagnostics and some ex-vivo therapeutic approaches are already in or very close to clinical use, chosen in-vivo editing methods are undergoing early trials, and AI-assisted nuclease design is still mostly theoretical but is getting better fast. This comprehensive viewpoint is intended to help researchers and physicians understand which CRISPR tools are most likely to be translated soon and where more validation is required.]]> Wed, 31 Dec 1969 19:00:00 EST Multi-omic biomarker detection in ovarian cancer. Abuhassan Q, Al-Assi G, Rekha MM, Chanania K, Bavanilatha M, Arora V, Sinha A, Hayitova M
Clin Chim Acta (Feb 2026)

Ovarian cancer remains one of the most lethal gynecologic malignancies, largely because of late-stage diagnosis and the absence of reliable biomarkers for early detection and therapeutic stratification. Recent advances in high-throughput technologies have enabled multi-omics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics to elucidate the comprehensive molecular landscape of ovarian cancer. This narrative review synthesizes current progress in applying multi-omics strategies to biomarker discovery, highlighting how integrative analyses uncover novel diagnostic, prognostic, and predictive candidates beyond the limitations of single-omics studies. We discuss methodological frameworks, computational pipelines and translational challenges in harmonizing heterogeneous datasets, as well as the potential of systems biology and machine learning to improve biomarker validation. Particular emphasis is placed on the identification of noncoding RNAs, protein signatures, and metabolic alterations as promising biomarker classes. Finally, we outline future directions for clinical implementation, including the development of multiparameter biomarker panels and precision medicine applications. By bridging molecular complexity with translational utility, multi-omics approaches hold transformative potential to advance biomarker identification and improve patient outcomes in ovarian cancer.]]> Wed, 31 Dec 1969 19:00:00 EST Emerging Role of ctDNA Fragmentomics and Epigenetic Signatures in the Early Detection, Minimal Residual Disease Assessment, and Precision Monitoring of Renal Cell Carcinoma. Kamli H, Khan NU
J Cell Mol Med (Feb 2026)

Renal cell carcinoma (RCC) presents a significant global health challenge, with a substantial proportion of patients diagnosed with advanced or metastatic disease due to the limitations of current diagnostic imaging and the lack of validated non-invasive biomarkers. These conventional methods, including computed tomography and magnetic resonance imaging, often lack the sensitivity and specificity to differentiate benign from malignant small renal masses reliably or to detect minimal residual disease (MRD) post-treatment. This review explores the transformative potential of liquid biopsy, explicitly focusing on circulating tumour DNA (ctDNA) fragmentomics and epigenetic signatures, to overcome these clinical hurdles. This review also explores how the analysis of ctDNA fragmentation patterns-such as size distribution, end motifs, and nucleosome footprints-provides a mutation-independent method to enhance RCC detection, even in low-shedding tumours. Concurrently, RCC-specific epigenetic alterations, particularly DNA methylation profiles, offer particular biomarkers for early detection, tumour classification, and prognostication. This Review examines evidence that integrating these multi-analyte approaches-combining fragmentomic and epigenetic data-synergistically improves diagnostic accuracy, enables sensitive MRD assessment, and allows precision monitoring of treatment response and tumour evolution. Despite existing technical and biological challenges, the convergence of ctDNA fragmentomics and epigenetic profiling heralds a new era for the non-invasive, dynamic, and personalised management of RCC, promising to improve patient outcomes through earlier intervention and tailored therapeutic strategies.]]> Wed, 31 Dec 1969 19:00:00 EST Genomic imprinting in an early-diverging angiosperm reveals an ancient mechanism for seed initiation in flowering plants. Florez-Rueda AM, Scharmann M, de Souza LP, Fernie AR, Bachelier JB, Figueiredo DD
New Phytol (Feb 2026)

]]> Wed, 31 Dec 1969 19:00:00 EST Radiogenomics: Current Understandings and Future Perspectives. Zhang X, Lai Q, Cao J, Ching JCF, Teng X, Zhang J, Lee SWY, Ren G, Cai J
MedComm (2020) (Feb 2026)

Radiogenomics is a rapidly developing field that links radiological image features (radiomics) to genomic-level data (genomics, transcriptomics, and epigenomics), addressing the limitations of single-omic approaches. Radiomics provides a noninvasive and cost-effective method to capture tissue-level characteristics, while genomics elucidates the underlying molecular mechanisms. The central hypothesis is that the formation of imaging phenotypes is associated with the genetic and molecular processes, and thus can reflect underlying biological activities. This review presents the fundamental principles of radiogenomic analysis, covering key concepts in image analysis and gene analysis, as well as advanced analytical techniques for linking imaging and genomic data. Moreover, we summarize recent research findings across various human diseases, including oncology and nononcology, to highlight the current understandings and achievements in this field. Radiogenomics shows potential in clinical applications for elucidating disease mechanisms, detecting genomic variations noninvasively, and improving prognosis predictions. However, its implementation in clinical practice is limited by data scarcity, analytical methods, and barriers in translational processes. Future research should focus on enhancing data quality and establishing guidelines, developing analytical platforms, and validating current findings through animal models and clinical trials.]]> Wed, 31 Dec 1969 19:00:00 EST Advancements in Pathogenic Genes and Biomarkers for Non-syndromic Cleft Lip With or Without Cleft Palate Via Multiomics. Yang C, Ding L, Dong Y, Wang Y, Cao S, Yuan Z, Jia S
Int Dent J (Feb 2026)

Non-syndromic cleft lip with or without cleft palate (nsCL/P) is a common congenital malformation influenced by a combination of environmental and genetic factors. nsCL/P is usually diagnosed using fetal ultrasound during the late second trimester; however, these results are often affected by factors such as instruments, fetal position, and maternal obesity. Moreover, by this time, structural anomalies in the fetuses are already formed and missed optimal time for intervention. Therefore, identifying more efficient and non-invasive biomarkers before fetal ultrasound is essential. In recent years, rapidly evolving omics technologies, including genomics, transcriptomics, proteomics, lipidomics, epigenomics, and single-cell omics, have been used to identify several nsCL/P-associated risk genes. Additionally, omics technologies have proven invaluable for investigating non-invasive biomarkers for prenatal diagnosis of nsCL/P. Therefore, this article reviews the current applications of multi-omics technologies in nsCL/P research, focusing on their use to identify pathogenic genes and the research advances in prenatal diagnosis. We highlighted the technological landscape and applications of multi-omics in nsCL/P, and explored the potential opportunities and challenges for future clinical practice.]]> Wed, 31 Dec 1969 19:00:00 EST Epigenetic Age Estimation for Hawaiian False Killer Whales (Pseudorca crassidens) in the Absence of 'Known-Age' Individuals. Martien KK, Baird RW, Robertson KM, Kratofil MA, Mahaffy SD, West KL, Chivers SJ, Archer FI
Mol Ecol Resour (Feb 2026)

Epigenetic aging models hold great promise for enhancing many aspects of wildlife research and management. However, their utility is limited by the need to train models using known-aged animals, which are rare among wildlife species. We present a novel approach to developing methylation-based age prediction models that enables us to train models using samples from individuals whose chronological age is estimated with uncertainty based on photo-identification catalogue data. Our approach incorporates this uncertainty into model training by representing the age of each individual with a probability distribution rather than a point estimate. We similarly represent the methylation profiles of individuals as binomial distributions and produce a distribution of predicted age for each sample that reflects the uncertainty in both its age and methylation profile. We compared age models trained using a wide range of parameterisations, training data sets and analytical methods to determine how well they predicted the catalogue-based age estimates. The resulting model has a median absolute error of 1.70 years, outperforming many published clocks trained with known-age samples. This approach significantly expands the range of species for which accurate methylation-based age models can be developed, particularly those of conservation concern where known-age samples are limited. By producing distributions of predicted age, it also enables researchers to accurately communicate the uncertainty in their age estimates to subsequent data users.]]> Wed, 31 Dec 1969 19:00:00 EST Spatial metabolomics and multiomics integration for breakthroughs in precision medicine for kidney disease. Sharma K, Hansen J, Susztak K, Eberlin L, Anderton CR, Alexandrov T, Iyengar R
Nat Rev Nephrol (Feb 2026)

Precision medicine is now a feasible prospect for nephrologists as numerous therapeutic options are available for various forms of kidney disease. However, implementation of this strategy will require high-dimensional diagnostic approaches to identify patients who will respond to an intervention and monitor mechanisms of action relevant to the underlying disease process. With the advent of spatial omics, comprehensive and thorough molecular analysis of biological samples is now possible. In particular, spatial metabolomics analysis of kidney biopsy samples could have an important role in facilitating precision medicine for kidney diseases. Spatial metabolomics can be used to monitor changes in the functional outcomes of genes and proteins in specific anatomical compartments such as the glomeruli, tubules, blood vessels and interstitial spaces. Spatial metabolomics studies have identified adenine in regions of interstitial fibrosis and arteriosclerosis in diabetic kidney disease, provided new insights into the regulation of N-glycans in glomeruli from patients with diabetes, and enabled a new metabolomic classification of kidney cancer subtypes. Use of computational informatic platforms to integrate genomics, transcriptomics, proteomics and epigenomics with metabolomics will further enhance the value of spatial metabolomics for clinical applications.]]> Wed, 31 Dec 1969 19:00:00 EST Multi-omic screening for pleural mesothelioma in Asbestos-Exposed Populations: A literature review and Recommendations. Zwijsen K, Heirwegh E, Schillebeeckx E, Marcq E, Covaci A, de Beeck KO, van Meerbeeck JP, Raskin J, Janssens A, Snoeckx A, Lamote K
Lung Cancer (Feb 2026)

Pleural mesothelioma (PM) is an aggressive thoracic cancer related to historical exposure to asbestos fibres. Symptoms often appear at an advanced stage, leading to delayed diagnosis and dismal prognosis. Early diagnosis is thus crucial in improving patient outcome. Current biomarker research for early detection focuses on different -omics research fields (genomics, proteomics, transcriptomics, metabolomics and volatomics), however with no clinically useful result. Moreover, currently no screening program is advocated for asymptomatic individuals with an established asbestos exposure. The aim of this review is to summarise the advances in different -omics fields and to pinpoint state-of-the art biomarkers with the highest potential to serve as primary targets in clinical trials for early PM detection or screening.]]> Wed, 31 Dec 1969 19:00:00 EST Evaluating DNA methylation episignatures as a first-tier diagnostic test in individuals with suspected genetic disorders. Tkemladze T, Campbell C, Bregvadze K, Kvaratskhelia E, Abzianidze E, Demain L, Jenkinson S, Hilton S, Levy M, Kerkhof J, Gokhale D, Sadikovic B, Banka S
Eur J Hum Genet (Feb 2026)

DNA methylation (DNAm) episignature analysis is an emerging tool for diagnosing individuals with neurodevelopmental disorders, congenital anomalies, and growth disorders. We evaluated its clinical utility as a first-tier test in 62 individuals without prior molecular testing. DNAm arrays identified a diagnosis in 30.6% (19/62) of cases. The positivity rate was highest for Fragile X syndrome (100%, 5/5), followed by syndromic disorders (44%, 8/18) and imprinting disorders (25%, 6/24), including Silver-Russell, Beckwith-Wiedemann, and Prader-Willi syndromes. No diagnoses were made in 15 individuals with non-syndromic neurodevelopmental disorders. Alternative diagnoses were identified in 4.8% (3/62) of cases. These findings suggest that DNAm arrays can serve as an effective first-tier diagnostic tool, particularly for syndromic and imprinting disorders, with potential to improve diagnostic efficiency and reduce reliance on sequential genetic testing. While these findings support the use of DNAm arrays as an effective first-tier tool in selected populations, larger, unselected cohort studies are needed to validate its generalizability.]]> Wed, 31 Dec 1969 19:00:00 EST