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At least 199 records · Page 11Linked to original sources

Epigenetic alterations in rheumatoid arthritis: multilayer mechanisms and translational opportunities.

Rheumatoid arthritis (RA) is a chronic inflammatory disease driven by immune dysregulation, in which genetic susceptibility and environmental exposures promote persistent synovitis, progressive joint damage, and systemic comorbidities. Recent epigenomic studies show several recurring abnormalities. Many RA susceptibility variants lie outside protein-coding sequence and map to immune-cell and synovial fibroblast regulatory elements, linking inherited risk to enhancer activity, methylation quantitative trait effects, and distal gene control. Blood-based epigenome-wide association studies identify disease-associated DNA methylation signatures, but these signals require careful control for leukocyte composition, smoking, treatment exposure, and disease stage. RA fibroblast-like synoviocytes also display stable methylome remodeling, including relative hypomethylation at loci involved in inflammation, migration, matrix degradation, and apoptosis resistance, while TET3-associated 5-hydroxymethylcytosine has emerged as a functional contributor to chemokine production and invasive stromal behavior. Histone modifications, chromatin accessibility, and 3D genome organization define pathogenic regulatory states and connect non-coding risk loci to effector genes in immune and stromal compartments. Finally, miRNAs, lncRNAs, circRNAs, snoRNAs, extracellular RNAs, and m6A-related pathways add post-transcriptional and chromatin-linked layers with potential biomarker value. We synthesize these findings and discuss translational opportunities for diagnosis, stratification, flare monitoring, and therapeutic targeting, while emphasizing incomplete replication, uneven evidence across epigenetic layers, biospecimen variability, and the need for causal, longitudinal, cell-type-resolved validation.

Humans↗

Multimodal atlas of human atherosclerosis links granular vascular cell states to coronary artery disease risk.

Advances in single-cell and spatial assays have revolutionized the scale and resolution of molecular tissue profiling. Here we present MetaPlaq, a multimodal atlas of human atherosclerotic arterial beds comprising over a million cells across single-cell transcriptomics, epigenomics and high-resolution spatial expression assays. We map granular cell states and disease-relevant transcriptional programs within the native tissue context of coronary arteries. Furthermore, we map cardiovascular GWAS signals to smooth muscle cells (SMCs) and endothelial cells (ECs) and uncover the cis-regulatory architecture governing their phenotypic transitions. Our comprehensive epigenomic reference allowed us to build cell-specific enhancer-gene link maps and multimodal gene regulatory networks (GRNs) underlying disease-relevant states such as osteogenic SMCs and ECs undergoing mesenchymal transition. We also integrate SMC and EC disease-associated gene sets with GRNs to nominate key transcription factors such as PRRX1, BNC2 and ELK3 regulating atherosclerosis-relevant transcriptional programs. Finally, we layer single-cell and spatial modalities to fine-map GWAS variants with improved cell and anatomical context. We highlight candidate cell-specific regulatory mechanisms at less characterized CAD loci, including FGD5 and MCF2L in ECs. Together, this atlas represents an important step towards fully interpreting genetic risk loci and informing new therapeutic strategies for cardiovascular disease.

Journal Article↗

[Variability of the number of chloroplasts in a population of stoma guard cells in the sugar beet (Beta vulgaris L.)].

Diploid sugar beet plants demonstrate a broad variability of the number of chloroplasts in stoma guard cells, which is related to myxoploidy of cell populations in leaf apical meristems (epigenomic variability). In addition to random organelle segregation between daughter cells, this variability is affected by factors disrupting the mitotic cycle: (1) plant treatment with a mitotic poison, such as colchicine; (2) duration of the life cycle of a plant; the variability in second-year plants is greater than in first-year ones; (3) the mode of plant reproduction; the variability in inbred plants is greater than in the initial population. Treatment of germinating seeds with a diluted colchicine solution increases the number of organelles in cells in the myxoploid generation (generation C0) and the variance of the distributions in the first vegetation year. The variability in the organelle number in stoma cells correlates with that in maternal meristem cells. It is concluded that the epidermal cell monolayer (including stoma guard cells) keeps record of the epigenomic and epiplastome variability in meristem cells. The variability of the number of chloroplasts in stoma guard cells is approximated by binomials with negative powers.

Beta vulgaris↗

Genomic Profiling of Chromatin State Using CUT&Tag.

Alterations in chromatin state, mediated through histone modifications and the incorporation of histone variants, are fundamental to establishing transcriptional networks and cell identity. Recent advances in low-input epigenome profiling methods, such as CUT&Tag and CUT&RUN, have enabled the study of chromatin states from very limited starting materials. In this chapter, we describe procedures for generating CUT&Tag libraries to profile histone modifications and histone variants in early-developing zebrafish embryos.

Animals↗

Epigenetic orchestration of cancer-immune dynamics: mechanisms, technologies, and clinical advancements.

BACKGROUND: Epigenetic dysregulation plays a pivotal role in cancer immune evasion by orchestrating tumour antigen silencing, immune cell dysfunction, and the formation of an immunosuppressive microenvironment. By disrupting successive phases of the cancer-immunity cycle-from antigen presentation to T cell exhaustion-these aberrations facilitate immune escape and tumour progression, highlighting the need for targeted epigenetic intervention. AIM OF REVIEW: This review systematically dissects how epigenetic alterations impair anti-tumour immunity at each stage of the CI cycle. It not only integrates fragmented mechanistic evidence but also emphasizes underexplored crosstalk between specific epigenetic regulators and immune cell types. It further highlights emerging technologies-such as single-cell epigenomics, spatial multi-omics, and CRISPR-based screens-that are driving discovery of novel therapeutic targets and refining patient stratification. Key scientific concepts of review. We discuss how epigenetic interventions, alone or in combination with immunotherapies, can reinvigorate immune responses and overcome resistance to current treatments. A particular focus is given to how integrative high-resolution platforms are mapping immunoepigenetic landscapes, enabling mechanism-informed, precision immunotherapy strategies. By bridging epigenetic regulation with translational immuno-oncology, this review outlines a future where epigenetic reprogramming becomes central to overcoming immune evasion in cancer.

Humans↗

Scalable screening of ternary-code DNA methylation dynamics associated with human traits.

Epigenome-wide association studies (EWASs) are transforming our understanding of the interplay between epigenetics and complex human traits. We introduce the methylation screening array (MSA) to enable scalable and quantitative screening of trait-associated DNA cytosine modifications in large human populations. The MSA integrates EWASs and cell-type-linked methylation signatures, covering diverse traits and diseases. Using the MSA to profile the ternary-code DNA methylations-dissecting 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC), and unmodified cytosine-revealed a previously unappreciated role of 5hmC in mediating human trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5mCs in defining epigenetic cell identities. In-depth analyses highlighted the cell-type context of EWAS and genome-wide association study (GWAS) hits. Targeting aging, we uncovered shared and tissue-specific 5hmC aging dynamics and tissue-specific rates of mitotic hyper- and hypomethylation. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

Humans↗

scATAnno: Automated Cell Type Annotation for Single-cell ATAC-seq Data.

Recent advances in single-cell epigenomic techniques have increased the demand for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) analysis. One key analytical task is to determine cell type identity based on epigenetic data. Here, we introduce scATAnno, a Python package designed to automatically annotate scATAC-seq data using large-scale scATAC-seq reference atlases. This workflow generates reference atlases from publicly available datasets, enabling accurate cell type annotation by integrating query data with reference atlases without the use of single-cell RNA sequencing (scRNA-seq) data. To enhance annotation accuracy, we incorporated k-nearest neighbors (KNN)-based and weighted distance-based uncertainty scores to effectively detect cell populations within the query data that are distinct from all cell types in the reference data. We compared and benchmarked scATAnno against five other published cell annotation approaches, demonstrating its superior performance across multiple datasets and metrics. We further showcased the utility of scATAnno across multiple datasets, including peripheral blood mononuclear cells (PBMCs), triple-negative breast cancer (TNBC), and basal cell carcinoma (BCC), and demonstrated that scATAnno accurately annotates cell types across diverse biological conditions. Overall, scATAnno is a useful tool for scATAC-seq reference atlas construction and cell type annotation and can facilitate the interpretation of new scATAC-seq datasets in complex biological systems. scATAnno is publicly available at https://scatanno-main.readthedocs.io/.

Single-Cell Analysis↗

Bridging the gap: multi-omic insights into exercise responses in postmenopausal women.

Postmenopausal women represent the fastest-growing demographic at risk of sarcopenia and cardiometabolic disease, yet exercise biology research remains disproportionately derived from male or hormone-replete phenotypes. Menopause constitutes a chronic endocrine perturbation characterized by sustained reductions in estrogen and progesterone, and altered androgen balance, superimposed on the acute and chronic perturbations induced by exercise. This hormonal shift modifies substrate metabolism, inflammation, redox balance, and recovery capacity, factors that shape molecular responses to exercise across tissues and time. Here, we synthesize current evidence on exercise responses in postmenopausal females across genomics, epigenomics, transcriptomics, proteomics, and metabolomics/lipidomics. Across omics layers, direct data in postmenopausal cohorts remain limited, with frequent underreporting of menopausal status, hormone therapy exposure, circulating hormone concentrations, medication use, and biosampling timing relative to exercise and hormone dosing. We outline a menopause-aware framework for exercise-omics that prioritizes endocrine stratification, repeated sampling across exercise and recovery, and integrative multi-omics approaches linking molecular responses to functional outcomes. We also outline minimum reporting standards to improve reproducibility, inclusivity, and translational relevance. Advancing menopause-aware exercise-omics will be essential for developing precision exercise strategies that improve health span and functional independence in later life.

Humans↗

A Strong Dysregulated Myeloid Component in the Epigenetic Landscape of Systemic Sclerosis: An Integrated DNA Methylome and Transcriptome Analysis.

OBJECTIVE: Nongenetic factors influence systemic sclerosis (SSc) pathogenesis, underscoring epigenetics as a relevant contributor to the disease. We aimed to unravel DNA methylation abnormalities associated with SSc through an epigenome-wide association study. METHODS: We analyzed DNA methylation data from whole-blood samples in 179 patients with SSc and 241 unaffected individuals to identify differentially methylated positions (DMPs) with a false discovery rate (FDR) <0.05. These results were further integrated with RNA sequencing data from the same patients to assess their functional consequence. Additionally, we examined the impact of DNA methylation changes on transcription factors and analyzed the relationship between alterations of the methylation and gene expression profile and serum proteins levels. RESULTS: This analysis yielded 525 DMPs enriched in immune-related pathways, with leukocyte cell-cell adhesion being the most significant (FDR = 4.91 &#xd7; 10-9), prioritizing integrins as they were exposed by integrating methylome and transcriptome data. Furthermore, through this integrative approach, we observed an enrichment of neutrophil-related pathways, highlighting this myeloid cell type as a relevant contributor in SSc pathogenesis. In addition, we uncovered novel profibrotic and proinflammatory mechanisms involved in the disease. Finally, the altered epigenetic and transcriptomic signature revealed an increased activity of CCAAT/enhancer-binding protein transcription factor family in SSc, which is crucial in the myeloid lineage development. CONCLUSION: Our findings uncover the impaired epigenetic regulation of the disease and its impact on gene expression, identifying new molecules for potential clinical applications and improving our understanding of SSc pathogenesis.

Humans↗

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation↗

Genome-Wide Profiling of Histone Modifications in Fission Yeast Using CUT&Tag.

Eukaryotic DNA is organized in the nucleus in the form of chromatin. Nucleosomes, the fundamental unit of chromatin, are subject to many posttranslational modifications (PTMs) as well as compositional variations through incorporation of histone variants. These alterations play important roles in regulation of genome structure and activity. Genome-wide profiling of these regulatory features is essential for understanding of genome function. Chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-Seq) is a widely used method to assay genome-wide localization in fission yeast but suffers from the requirement for a large amount of input chromatin, antibodies, and a cumbersome experimental pipeline. New methods such as Cleavage Under Targets and Tagmentation (CUT&Tag), which combine the specificity of targeted cleavage and adapter insertion with the sensitivity of next-generation sequencing, enable identification and characterization of various epigenetic marks affording low input requirement as well as more streamlined protocols. However, these approaches have not been adapted for use in fission yeast, Schizosaccharomyces pombe. Here, we describe an adapted CUT&Tag protocol for epigenomic profiling in fission yeast using the heterochromatin-associated histone H3K9 methylation PTM for benchmarking.

Schizosaccharomyces↗

HiChIP for Plant Tissues.

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.

Chromatin↗

A Standardized Protocol for Generating iPSC-Derived Human Microglia for Functional Genomic Assays.

Human induced pluripotent stem cell (iPSC)-derived microglia (iMG) provide an in vitro experimental system for studying human microglial biology, neuroinflammation, and genetic risk mechanisms associated with neurological disease. This chapter describes a standardized, scalable, and reproducible protocol for the differentiation of human iPSCs into functional microglia-like cells, with particular emphasis on applications in transcriptional and epigenomic network analysis. The protocol supports high-viability floating iMG production, compatibility with pooled CRISPR perturbation approaches, and downstream multiomic profiling, including single-cell RNA sequencing, chromatin accessibility assays, and proteomics. Detailed procedures are provided for iPSC maintenance, hematopoietic progenitor cell generation, microglial maturation, functional genomics integration, and quality control.

Humans↗

Integrating multi-omics approaches in acute myeloid leukemia (AML): Advancements and clinical implications.

Acute myeloid leukemia (AML) is a highly heterogeneous and aggressive hematologic malignancy characterized by clonal proliferation of myeloid precursors. Despite significant advancements in genomic profiling and targeted therapies, patient outcomes remain suboptimal due to disease complexity, resistance mechanisms, and high relapse rates. The integration of multi-omics approaches-spanning genomics, epigenomics, transcriptomics, proteomics, and metabolomics-has revolutionized AML research, offering a comprehensive understanding of leukemogenesis, tumor heterogeneity, and therapeutic vulnerabilities. Recent studies leveraging high-throughput sequencing, mass spectrometry, and advanced computational tools have uncovered novel biomarkers, clonal evolution dynamics, and microenvironmental interactions that drive AML progression and resistance. For instance, single-cell multi-omics has revealed chemotherapy-resistant leukemic stem cell populations, while proteogenomic analyses have identified actionable targets such as MCL1 and metabolic dependencies like OXPHOS. Clinically, integrated omics platforms are refining risk stratification, minimal residual disease (MRD) monitoring, and personalized therapy selection. However, challenges such as data integration complexity, cost barriers, and ethical considerations remain. This review highlights the transformative potential of multi-omics in AML, emphasizing recent advancements in technology, biomarker discovery, and therapeutic innovation. By bridging the gap between molecular insights and clinical practice, multi-omics integration promises to redefine AML management, paving the way for precision oncology and improved patient outcomes.

Humans↗

The emerging impact of CRISPR and gene editing on global crop improvement.

The advent of CRISPR-based genome editing has revolutionized crop improvement, offering unprecedented precision and efficiency in modifying key agronomic traits. This review comprehensively examines the mechanisms, applications, and future potential of CRISPR technology in enhancing global crop production. CRISPR-Cas systems, originally identified as adaptive immune mechanisms in bacteria and archaea, have been repurposed for targeted genome editing in plants. The CRISPR-Cas9 system, in particular, has emerged as a powerful tool for introducing site-specific double-strand breaks, enabling precise genetic modifications. The three-stage process of adaptation, expression, and interference underlies the CRISPR mechanism, with guide RNAs directing Cas endonucleases to specific genomic loci. Advances in CRISPR technology have expanded its applications beyond gene knockouts, encompassing base editing, prime editing, and epigenome editing. These innovations have facilitated the development of crops with enhanced yield, stress tolerance, disease resistance, nutritional content, and post-harvest quality. However, challenges related to off-target effects, regulatory hurdles, ethical concerns, and public acceptance must be addressed to fully harness the potential of CRISPR in agriculture. Integration of CRISPR with other cutting-edge technologies, such as synthetic biology, artificial intelligence, and high-throughput phenotyping, holds immense promise for accelerating crop improvement efforts. As research continues to refine CRISPR tools and expand their applicability across diverse plant species, this transformative technology is poised to play a pivotal role in shaping a sustainable, resilient, and productive global food system for future generations.

Gene Editing↗

Spatial biology reveals altered macrophage states in immunosuppressed non-melanoma skin cancer.

Immunosuppressed patients with non-melanoma skin cancer experience worse clinical outcomes, yet the tumor immune microenvironment associated with systemic immunosuppression remains incompletely defined. Using integrated single-cell, spatial transcriptomic, multiplex immunofluorescence, and spatial epigenomic profiling across immunocompetent and immunosuppressed tumors, we found that overall immune-cell composition was largely preserved despite differences in immune-cell distribution, spatial organization, and T cell clonality. Immunosuppressed tumors demonstrated reduced intratumoral macrophage densities, decreased T cell clonal diversity, altered antigen-presenting cell and T cell spatial interactions, and distinct fibroblast- and macrophage-associated spatial niches. Multi-cohort validation across complementary spatial and single-cell platforms identified consistent alterations in innate-adaptive immune organization in immunosuppressed tumors. Together, these findings define spatial and functional remodeling of the tumor immune microenvironment under systemic immunosuppression and provide a framework for future therapeutic investigation in high-risk patients.

Humans↗

Interpretable data integration for single-cell and spatial multi-omics.

Integrating single-cell or spatial transcriptomic and epigenomic data enables scrutinizing the transcriptional regulatory mechanisms controlling cell fate. Current integration methods usually align multi-omics data into a shared latent space but fail to reveal the underlying connections between genes and regulatory elements. The correlation- or regression-based regulatory inference methods cannot dissect different transcriptional regulation codes for cells under different spatial and temporal states. To address both problems, we develop a feature-guided optimal transport (FGOT) method, which simultaneously uncovers cellular heterogeneity and their associated transcriptional regulatory links. FGOT also provides post hoc interpretability for existing integration methods. FGOT is applicable for paired/unpaired single-cell multi-omics data and paired spatial multi-omics data. Benchmarking and validating via histone modification data or three-dimensional (3D) genomics data show good robustness and accuracy in integration and inference of regulatory links. The method allows systematic screening of cell-state and spatial-location-specific regulatory elements in diseases at the single-cell level. A record of this paper's transparent peer review process is included in the supplemental information.

Single-Cell Analysis↗

Epigenetic alterations in bioaccumulators of cadmium: Lessons from mammalian kidneys and plants.

Faced with unpredictable changes in global weather patterns, release and redistribution of metals through land erosion and water movements add to the increasing use of metals in industrial activities causing high levels of environmental pollution and concern to the health of all living organisms. Cadmium is released into the environment by smelting and mining, entering the food chain via contaminated soils, water, and phosphate fertilizers. Bioaccumulation of cadmium in plants represents the first major step into the human food chain and contributes to toxicity of several organs, especially the kidneys, where biomagnification of cadmium occurs over decades of exposure. Even in small amounts, cadmium brings about alterations at the molecular and cellular levels in eukaryotes through mutagenicity, molecular mimicry at metal binding sites and oxidative stress. The epigenome dictates expression of a gene's output through a number of regulatory steps involving chromatin remodeling, nucleosome unwinding, DNA accessibility, or nucleic acid modifications that ultimately impact the transcriptional and translational machinery. Several epigenetic enzymes exhibit zinc-dependence as zinc metalloenzymes and zinc finger proteins thus making them susceptible to deregulation through displacement by cadmium. In this review, we summarize the literature on cadmium-induced epigenetic mechanisms in mammalian kidneys and plants, compare similarities in the epigenetic defense between these bioaccumulators, and explore how future studies could advance our understanding of the cadmium-induced stress response and disruption to biological health.

Cadmium↗