'; ?> 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 Tue, 20 Jan 2026 02:39:57 EST Tue, 20 Jan 2026 02:39:57 EST jirtle@radonc.duke.edu james001@jirtle.com Current Overview of Multi-omics Analyses in Microscopic Polyangiitis and Granulomatosis with Polyangiitis. Miyamoto AT, Kumanogoh A, Nishide M
Intern Med (Jan 2026)

Anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) is an autoimmune disease characterized by autoantibodies against neutrophil cytoplasmic antigens such as myeloperoxidase (MPO) and proteinase 3 (PR3). AAV affects small blood vessels, leading to systemic inflammation and multiorgan damage. Recent advances in multi-omics analyses, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have significantly improved our understanding of AAV complex pathophysiology. Genome-wide association studies (GWASs) have revealed robust genetic associations, especially within the human leukocyte antigen (HLA) region. Epigenomic analyses have elucidated regulatory mechanisms that affect autoantigen gene expression and disease activity. Transcriptomic approaches, particularly single-cell RNA sequencing (scRNA-seq), have identified distinct gene expression profiles and cellular interactions, which have been further enriched by the recent application of spatial transcriptomics of diseased tissues. Proteomic and metabolomic approaches have been used to identify potential biomarkers. This review discusses recent advances in multi-omics research aimed at developing personalized diagnostic and therapeutic strategies based on the molecular and genetic profiles of AAV.]]> Wed, 31 Dec 1969 19:00:00 EST Maternal UPD(20) Leading to Mulchandani-Bhoj-Conlin Syndrome: A Rare Neonatal Case With Additional TRPS1 Deletion. Zhang J, Chen X, Chen M, Wu S, Huang F, Pan R, Chen G
Am J Med Genet A (Feb 2026)

Mulchandani-Bhoj-Conlin syndrome is an extremely rare imprinting disorder caused by maternal uniparental disomy of chromosome 20, primarily characterized by intrauterine growth restriction, severe postnatal growth failure, and feeding difficulties. Here, we report a neonate diagnosed with Mulchandani-Bhoj-Conlin syndrome via whole exome sequencing and copy number variation analysis, which also identified a 0.26 Mb deletion on chromosome 8q23.3 affecting the TRPS1 gene, associated with Trichorhinophalangeal syndrome. We describe the clinical features and genetic findings of this infant, with the aim of contributing to a better understanding of these two rare diseases.]]> 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-omics to study chronic respiratory diseases and viral infections. Idrees S, Chen H, Sadaf T, Rehman SF, Johansen MD, Paudel KR, Liu G, Wang Y, Luecken MD, Hortle E, Philp AS, Budden KF, O'Rourke M, Kaiko GE, Lucas SEM, Dickinson JL, Allen PC, Powell JE, Zhang LY, Chambers DC, Corte T, Caramori G, Sauler M, Wark PA, Gote-Schniering J, Lehmann M, Conlon TM, Kapellos TS, Yildirim AÖ, Faner R, Dharmage SC, Wheelock CE, van den Berge M, Nawijn MC, Polverino F, Belz GT, Chotirmall SH, Segal LN, Faiz A, Hansbro PM
Eur Respir Rev (Jan 2026)

Despite recent advances, the underlying mechanisms of the development and progression of many chronic respiratory diseases remain to be elucidated. Factors such as heterogeneity and complexity of human diseases and difficulty interpreting large datasets hinder research into chronic respiratory diseases. Omics assesses the changes in specific biological entities, such as mRNA expression, epigenetics/epigenomics, genomics, proteomics, metagenomics and metabolomics, and provides valuable insights into the roles of these processes in chronic respiratory diseases. High-throughput omics at bulk, single-cell and spatial levels empower the exploration of disease-related changes through untargeted data-driven statistical methods. Multi-omics is the exploration and integration of multiple biological processes, which compared to a single-omics, can provide a substantially greater and more holistic overview of the pathogenic mechanisms that underpin complex diseases. Multi-omics analysis can comprehensively characterise the mechanisms that drive chronic respiratory diseases, capturing unique biological signatures and cellular interactions at different omics levels. Use of these methods has begun to identify key factors and biomarkers in chronic respiratory diseases. Here, we review current omics approaches and highlight recent advances in respiratory research achieved using multi-omics and integrative methods. Our review provides a valuable resource for researchers and clinicians in this area.]]> 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 H3K27me3-dependent imprinting and transcriptional regulation in early mouse embryos requires EZHIP-mediated restriction of PRC2 activity. Diop S, Richart L, Petitalot A, Boni J, Mollier C, Altay B, Dauphin A, Raynal V, Maître JL, Ancelin K, Margueron R
Nat Commun (Jan 2026)

Zygotes inherit parental genomes with distinct chromatin structures. In eutherian mammals, this asymmetry is considered crucial for embryonic development, notably because it enables genomic imprinting. Besides the well-established role of DNA methylation in this process, a transient form of imprinting in mice has been shown to rely instead on H3K27me3. Here, we show that maternal deletion of Ezhip, encoding a negative regulator of PRC2, initially increases the asymmetric distribution of H3K27me3 among the parental genomes at the zygotic stage but subsequently impairs H3K27me3-dependent imprinting and mitigates X-chromosome inactivation in pre-implantation embryos. We show that EZHIP protein, translated from the maternal mRNA pool, is present during the first cell divisions post-fertilization and limits PRC2 enzymatic activity. In its absence, the H3K27me3 landscape is both expanded and flattened, and the asymmetry between the two parental genomes is lost. Our study reveals the deleterious consequences on early embryonic development of unleashing PRC2 activity.]]> 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 hitchhiker's guide to single-cell epigenomics: Methods and applications for cancer research. Moreno-Gonzalez M, Sierra I, Kind J
Int J Cancer (Jan 2026)

Genetic mutations are well known to influence tumorigenesis, tumor progression, treatment response and relapse, but the role of epigenetic variation in cancer progression is still largely unexplored. The lack of epigenetic understanding in cancer evolution is in part due to the limited availability of methods to examine such a heterogeneous disease. However, in the last decade the development of several single-cell methods to profile diverse chromatin features (chromatin accessibility, histone modifications, DNA methylation, etc.) has propelled the study of cancer epigenomics. In this review, we detail the current landscape of single-omic and multi-omic single-cell methods with a particular focus on the examination of histone modifications. Furthermore, we provide recommendations on both the application of these methods to cancer research and how to perform initial computational analyses. Together, this review serves as a referential framework for incorporating single-cell methods as an important tool for tumor biology.]]> 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 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 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 A data-driven pan-cancer proteogenomic analysis reveals the characteristics of human cancer protein expression. Li Y, Liu X, Wang Z, Wu Q, Sha C, Li X
iScience (Jan 2026)

Genomics and epigenomics outline potential cellular changes, while proteomics reflects actual molecular events. To systematically bridge the molecular hierarchies and validate their functional interplay, we established the most comprehensive pan-cancer paired multi-omics resource to date, systematically integrating proteomic, transcriptomic, and genomic data from both tumor and adjacent normal tissues spanning 15 cancer types (2,555 tumor samples), thereby enabling a robust cross-omics exploration. Analysis revealed that tumor tissues exhibit higher correlation between transcriptomic and proteomic expression levels compared to normal tissues. Key tumor development pathways exhibited strong mRNA-protein correlations. Genes with high mRNA-protein correlation and high expression were associated with lower survival rates, highlighting potential therapeutic targets. We developed a comprehensive tool, the CPGTA R package, based on reintegrated datasets that facilitates multi-omics data integration and reanalysis. Our research enhances cancer molecular characterization while providing insights into mechanisms underlying cancer progression and treatment resistance.]]> 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 Comprehensive epigenomic and transcriptomic analysis identifies FABP7 and CLIC6 as methylation-driven prognostic biomarker for a novel breast cancer subtype. Fahima K, Hosen MR, Mahmud Z
Comput Biol Med (Jan 2026)

Breast cancer (BRCA) is the most prevalent malignancy among women and exhibits significant molecular and clinical heterogeneity. To improve risk stratification and identify novel molecular subtypes, we employed integrative analysis on DNA CpG methylation and transcriptomic data to construct a methylation-driven prognostic model for BRCA. Using LASSO, we identified a 10-gene prognostic signature that effectively stratified patients into two groups designated as high-risk and low-risk groups. Kaplan-Mayer survival analysis revealed worse overall survival of the high-risk patients in the TCGA cohort (p < 0.0001). The risk model was independently validated in two external GEO datasets GSE86166 (p = 0.00011) and GSE42568 (p = 0.00013) demonstrating its resilience and clinical relevance. In addition, the risk groups were not associated with any canonical molecular subtypes of breast cancer. Among the 10 genes, FABP7 and CLIC6 were differentially expressed between the risk groups. FABP7 had the highest negative LASSO coefficients followed by CLIC6. In further analysis, FABP7 (R = 0.42, p = 3e-04) and CLIC6 (R = 0.48, P < 0.001) both showed a strong inverse correlation between CpG methylation and expression, with more than two-fold higher expression in low-risk group and linked to improved survival in all three independent cohort. Functional enrichment analysis identified that genes overexpressed in the low-risk subtype were significantly enriched in immune-related pathways. Immunological analysis indicated a more immunogenic tumor microenvironment in the FABP7 and CLIC6 positive, low-risk group, with significantly higher infiltration of CD8 T cells (p = 0.047) and resting NK cells (p = 0.0391), while FABP7 and CLIC6 negative, high-risk tumors had increased M2 macrophages (p = 9.19 × 10) and Tregs (p = 0.0122). To summarize, this integrative model identified a novel methylation-based risk classifier/molecular subtype for BRCA, highlighting FABP7 and CLIC6 as a key prognostic biomarker with potential utility for risk stratification for strategic treatment. These findings require further validation through wet-lab experiments and prospective clinical studies to support clinical translation.]]> 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 Epigenomics-guided precision oncology: Chromatin variants in prostate tumor evolution. Furlano K, Keshavarzian T, Biernath N, Fendler A, de Santis M, Weischenfeldt J, Lupien M
Int J Cancer (Jan 2026)

Prostate cancer is a common malignancy that in 5%-30% leads to treatment-resistant and highly aggressive disease. Metastasis-potential and treatment-resistance is thought to rely on increased plasticity of the cancer cells-a mechanism whereby cancer cells alter their identity to adapt to changing environments or therapeutic pressures to create cellular heterogeneity. To understand the molecular basis of this plasticity, genomic studies have uncovered genetic variants to capture clonal heterogeneity of primary tumors and metastases. As cellular plasticity is largely driven by non-genetic events, complementary studies in cancer epigenomics are now being conducted to identify chromatin variants. These variants, defined as genomic loci in cancer cells that show changes in chromatin state due to the loss or gain of epigenomic marks, inclusive of histone post-translational modifications, DNA methylation and histone variants, are considered the fundamental units of epigenomic heterogeneity. In prostate cancer chromatin variants hold the promise of guiding the new era of precision oncology. In this review, we explore the role of epigenomic heterogeneity in prostate cancer, focusing on how chromatin variants contribute to tumor evolution and therapy resistance. We therefore discuss their impact on cellular plasticity and stochastic events, highlighting the value of single-cell sequencing and liquid biopsy epigenomic assays to uncover new therapeutic targets and biomarkers. Ultimately, this review aims to support a new era of precision oncology, utilizing insights from epigenomics to improve prostate cancer patient outcomes.]]> 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 Epigenomic, transcriptomic, and proteomic characterization of breast cancer cell line reference samples. Nepal C, Chen W, Chen Z, Wrobel JA, Xie L, Liao W, Xiao C, Farmer A, Moos M, Jones W, Chen X, Wang C
Cell Rep Methods (Jan 2026)

Next-generation sequencing requires accuracy, reproducibility, and standardized reference materials. The Sequencing Quality Control (SEQC-2) multicenter studies on paired breast cancer and B cell lines generated extensive genomic datasets, but integrated epigenomic and proteomic references remain limited. Here, we performed Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), Methyl-seq, RNA sequencing (RNA-seq), and proteomic profiling to establish comprehensive multi-omics reference materials. We identified >7,700 protein groups, with 95% of genes encoding a single peptide isoform. Protein expression from CpG island (CGI)-overlapping transcripts was higher than non-CGI transcripts in both cell lines. Certain SNVs were incorporated into mutated peptides. Chromatin accessibility was regulated by CG density: CG-rich regions showed lower methylation, greater accessibility, and higher gene/protein expression, whereas CG-poor regions exhibited higher methylation, reduced accessibility, and cell line-specific expression patterns. These datasets provide well-defined genomic, epigenomic, transcriptomic, and proteomic characterizations that can serve as benchmarks for validating omics assays and bioinformatics methods, offering a valuable community resource.]]> Wed, 31 Dec 1969 19:00:00 EST Detection of Isodisomy Utilizing SNP Microarray: Frequency, Ascertainment, and Implications. Molinari S, Williams N, Haskell G, Penton A, Arreola A, Gadi I, Phillips K, Tepperberg J, Schwartz S
Am J Med Genet A (Feb 2026)

This study investigates the frequency, ascertainment, and clinical implications of whole chromosomal isodisomy using a database of over 415,000 chromosomal microarray (CMA) tests conducted since 2008 across prenatal, postnatal, and products of conception specimens. In this cohort, 0.04% of cases exhibited the rare chromosomal phenomenon of isodisomy. Analysis of these cases revealed distinct patterns in frequency, chromosome involvement, and parent of origin related to specimen type. Isodisomy 14 was most frequent in prenatal samples, while chromosomes 6, 7, and 15 were more common in postnatal cases. The involvement of imprinted and non-imprinted chromosomes was equivalent for prenatal cases, while imprinted chromosomes consisted of two-thirds of postnatal cases, with paternal uniparental isodisomy more prevalent than maternal across all specimen types. Several cases demonstrated unmasking of pathogenic variants in recessive genes, and findings support prior studies of associations between isodisomy 11 and prenatal or neonatal lethality. These results underscore the diagnostic value of CMA and contribute to an extended understanding of isodisomy's clinical relevance.]]> Wed, 31 Dec 1969 19:00:00 EST (Re)defining the human chromatome: an integrated meta-analysis of localization, function, abundance, physical properties, and domain composition of chromatin proteins. Gribkova AK, Armeev GA, Kirpichnikov MP, Shaytan AK
Nucleic Acids Res (Jan 2026)

The full complement of chromatin-associated proteins-collectively referred to as the chromatome-enables genome functioning in eukaryotes by participating in a wide range of physico-chemical processes. These include mediating diverse specific and nonspecific intermolecular interactions, catalyzing in situ synthesis and modification of macromolecules, facilitating ATP-dependent chromatin remodeling, etc. Despite considerable progress in epigenomics and the structural characterization of many nuclear proteins and their complexes, our understanding of chromatin organization at the proteome scale remains incomplete. This gap hinders the development of a holistic view of genome regulation. In this study, we present a state-of-the-art characterization of the human chromatome based on an integrative meta-analysis of diverse data sources describing the composition, abundance, and sub-nuclear localization of chromatin proteins. This effort is complemented by original analyses of their physico-chemical properties, domain architectures, and interaction patterns. To support and streamline these analyses, we developed a reference dataset of chromatin proteins, integrated with an empirical, function-based classification ontology and an associated interactive web resource-SimChrom-accessible at https://simchrom.intbio.org/. The reference dataset was carefully curated by reconciling data among protein databases, localization, and mass spectrometry-based experimental studies. Sequence-based and AI-assisted structural analyses revealed previously unannotated domains within chromatin proteins that warrant experimental validation, as well as the widespread use of multivalent interaction strategies that underpin chromatin organization. Together, our findings establish a robust framework for future studies aimed at elucidating genome function through detailed analysis of protein-protein and protein-nucleic acid interactions within chromatin.]]> Wed, 31 Dec 1969 19:00:00 EST