CUT&Tag for Efficient Epigenomic Profiling of Frozen Tissues.

Cleavage Under Targets and Tagmentation (CUT&Tag) provides high-resolution sequencing libraries for profiling diverse chromatin components. This protocol details the steps to generate CUT&Tag libraries from fresh or frozen tissues. This CUT&Tag workflow has nine main steps: isolation of nuclei from tissues, binding of nuclei to Concanavalin A-coated beads, binding of the primary antibody, binding of the secondary antibody, binding pA-Tn5 adapter complex, tagmentation, DNA extraction, PCR, and post-PCR cleanup and size selection. This protocol enabled us to generate and sequence CUT&Tag libraries across a broad range of fresh and frozen tissue types.

Integrative Analysis of CUT&Tag and RNA-Seq Data Through Bioinformatics: A Unified Workflow for Enhanced Insights.

Cleavage Under Targets and Tagmentation (CUT&Tag) is a recent methodology used for robust epigenomic profiling that, unlike conventional chromatin immunoprecipitation (ChIP-Seq), requires only a limited amount of cells as starting material. RNA sequencing (RNA-Seq) reveals the presence and quantity of RNA in a biological sample, describing the continuously changing cellular transcriptome. The integrated analysis of transcriptional activity, histone modifications, and chromatin accessibility via CUT&Tag is still in its infancy compared to the well-established ChIP-Seq. This chapter describes a robust bioinformatics methodology and workflow to perform an integrative CUT&Tag/RNA-Seq analysis.

The Contribution of Genetic and Epigenetic Factors: An Emerging Concept in the Assessment and Prognosis of Inflammatory Bowel Diseases.

Inflammatory bowel disease (IBD) represents heterogeneous and relapsing intestinal conditions with a severe impact on the quality of life of individuals and a continuously increasing prevalence. In recent years, the development of sequencing technology has provided new means of exploring the complex pathogenesis of IBD. An ideal solution is represented by the approach of precision medicine that investigates multiple cellular and molecular interactions, which are tools that perform a holistic, systematic, and impartial analysis of the genomic, transcriptomic, proteomic, metabolomic, and microbiomics sets. Hence, it has led to the orientation of current research towards the identification of new biomarkers that could be successfully used in the management of IBD patients. Multi-omics explores the dimension of variation in the characteristics of these diseases, offering the advantage of understanding the cellular and molecular mechanisms that affect intestinal homeostasis for a much better prediction of disease development and choice of treatment. This review focuses on the progress made in the field of prognostic and predictive biomarkers, highlighting the limitations, challenges, and also the opportunities associated with the application of genomics and epigenomics technologies in clinical practice.

Association of XRCC2 with breast cancer, a multi-omics analysis at genomic, transcriptomic, and epigenomic level.

One of the main causes of cancer-related mortality for women worldwide is breast cancer (BC). The XRCC2 gene, essential for DNA repair, has been implicated in cancer susceptibility. This study aims to evaluate the association between XRCC2 and BC risk. The study was conducted at Zheen International Hospital in Erbil, Iraq, between 2021 and 2024 with a total of 88 samples, including 44 paired normal and cancer tissue samples. Mutation analysis was performed using Next-Generation Sequencing, coupled with in silico tools for variant impact prediction. Expression levels were assessed through RT-PCR, and methylation status was determined using methylation-sensitive restriction enzyme digestion PCR. The study identified seven inherited germline variants in the XRCC2 gene, with five of these mutations being Uncertain Significance, one being Likely Pathogenic, and one being Likely benign. RNA purity was found high with mean A260/280 ratios of 1.986 ± 0.097 in normal (N) and 1.963 ± 0.092 in tumor (T) samples. Tumor samples exhibited a higher RNA concentration (78.56 ± 40.87 ng/µL) than normal samples (71.44 ± 40.79 ng/µL). XRCC2 gene expression was significantly upregulated in tumor tissue, with marked increases in patients aged 40-55 and >56 years and in higher cancer grades (II and III) and invasive ductal carcinoma (p-values ranging from <0.0001 to 0.0392). DNA methylation rates in tumor tissues were low (7%), suggesting limited regulation by methylation. The study suggests that XRCC2 can be classified as an oncogene and that its structural investigation by targeted NGS and expression evaluation can be used as a potential biomarker in BC.

Transcriptomics and epigenetic data integration learning module on Google Cloud.

Multi-omics (genomics, transcriptomics, epigenomics, proteomics, metabolomics, etc.) research approaches are vital for understanding the hierarchical complexity of human biology and have proven to be extremely valuable in cancer research and precision medicine. Emerging scientific advances in recent years have made high-throughput genome-wide sequencing a central focus in molecular research by allowing for the collective analysis of various kinds of molecular biological data from different types of specimens in a single tissue or even at the level of a single cell. Additionally, with the help of improved computational resources and data mining, researchers are able to integrate data from different multi-omics regimes to identify new prognostic, diagnostic, or predictive biomarkers, uncover novel therapeutic targets, and develop more personalized treatment protocols for patients. For the research community to parse the scientifically and clinically meaningful information out of all the biological data being generated each day more efficiently with less wasted resources, being familiar with and comfortable using advanced analytical tools, such as Google Cloud Platform becomes imperative. This project is an interdisciplinary, cross-organizational effort to provide a guided learning module for integrating transcriptomics and epigenetics data analysis protocols into a comprehensive analysis pipeline for users to implement in their own work, utilizing the cloud computing infrastructure on Google Cloud. The learning module consists of three submodules that guide the user through tutorial examples that illustrate the analysis of RNA-sequence and Reduced-Representation Bisulfite Sequencing data. The examples are in the form of breast cancer case studies, and the data sets were procured from the public repository Gene Expression Omnibus. The first submodule is devoted to transcriptomics analysis with the RNA sequencing data, the second submodule focuses on epigenetics analysis using the DNA methylation data, and the third submodule integrates the two methods for a deeper biological understanding. The modules begin with data collection and preprocessing, with further downstream analysis performed in a Vertex AI Jupyter notebook instance with an R kernel. Analysis results are returned to Google Cloud buckets for storage and visualization, removing the computational strain from local resources. The final product is a start-to-finish tutorial for the researchers with limited experience in multi-omics to integrate transcriptomics and epigenetics data analysis into a comprehensive pipeline to perform their own biological research.This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [16] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

Integrated genomic/epigenomic analysis stratifies subtypes of clear cell ovarian carcinoma, highlighting their cellular origin.

The cellular origin of clear cell ovarian carcinoma (CCOC), a major histological subtype of ovarian carcinoma remains elusive. Here, we explored the candidate cellular origin and identify molecular subtypes using integrated genomic/epigenomic analysis. We performed whole exome-sequencing, microarray, and DNA methylation array in 78 CCOC samples according to the original diagnosis. The findings revealed that ARID1A and/or PIK3CA mutations were mutually exclusive with DNA repair related genes, including TP53, BRCA1, and ATM. Clustering of CCOC and other ovarian carcinomas (n = 270) with normal tissues from the fallopian tube, ovarian surface epithelium, endometrial epithelium, and pelvic peritoneum mesothelium (PPM) in a methylation array showed that major CCOC subtypes (with ARID1A and/or PIK3CA mutations) were associated with the PPM-lile cluster (n = 64). This cluster was sub-divided into three clusters: (1) mismatch repair (MMR) deficient with tumor mutational burden-high (n = 2), (2) alteration of ARID1A (n = 51), and (3) ARID1A wild-type (n = 11). The remaining samples (n = 14) were subdivided into (4) ovarian surface epithelium-like (n = 11) and (5) fallopian tube-like (considered as high-grade serous histotype; n = 3). Among these, subtypes (1-3) and others (4 and 5) were found to be associated with immunoreactive signatures and epithelial-mesenchymal transition, respectively. These results contribute to the stratification of CCOC into biological subtypes.

Advancing Health Disparities Science Through Social Epigenomics Research.

Importance: Although scientific and technological discoveries have improved the health of the US population overall, racial and ethnic minority (American Indian and Alaska Native, Asian, Black or African American, Hispanic or Latino, or Native Hawaiian and Pacific Islander persons) and socioeconomically disadvantaged populations continue to experience a disproportionate burden of disease and other adverse health conditions. To better understand and address the drivers of health disparities and inform the development of effective interventions, integrative mechanistic studies examining the dynamic interplay of multiple factors across the life course and even between generations are needed. The emerging field of social epigenomics, which seeks to link social stressors and protective factors to health status through the examination of epigenomic modifications of various biological pathways, is one promising area of research contributing to this need. Observations: This thematic issue of JAMA Network Open highlights new findings from the grantees of the National Institutes of Health (NIH) Social Epigenomics Program. These findings, taken together, examine the associations of a variety of social, behavioral, and structural factors throughout the life course with epigenomic and other biological changes among populations experiencing health disparities. The studies link early-life exposures, structural inequities, and behavioral factors and interventions to epigenetic changes, and in some studies, later health outcomes. While there is still more work to be done to fully characterize the mechanistic pathways linking social exposures to epigenetic changes and health outcomes, the body of work presented in this special issue represents solid progress toward this goal. Conclusions and Relevance: The studies highlighted in this special issue demonstrate important scientific progress in the complex integration of social determinants of health and health disparities with biological pathways and health outcomes to improve understanding of the mechanisms underlying health disparities among various underserved populations. Continued progress remains important in integrating different disciplines to transform the field of health disparities research.

Transcriptomic and Epigenomic Responses to Cortisol-Mediated Stress in Rainbow Trout (Oncorhynchus mykiss) Skeletal Muscle.

The production and release of cortisol during stress responses are key regulators of growth in teleosts. Understanding the molecular responses to cortisol is crucial for the sustainable farming of rainbow trout (Oncorhynchus mykiss) and other salmonid species. While several studies have explored the genomic and non-genomic impacts of cortisol on fish growth and skeletal muscle development, the long-term effects driven by epigenetic mechanisms, such as cortisol-induced DNA methylation, remain unexplored. In this study, we analyzed the transcriptome and genome-wide DNA methylation in the skeletal muscle of rainbow trout seven days after cortisol administration. We identified 550 differentially expressed genes (DEGs) by RNA-seq and 9059 differentially methylated genes (DMGs) via whole-genome bisulfite sequencing (WGBS) analysis. KEGG enrichment analysis showed that cortisol modulates the differential expression of genes associated with nucleotide metabolism, ECM-receptor interaction, and the regulation of actin cytoskeleton pathways. Similarly, cortisol induced the differential methylation of genes associated with focal adhesion, adrenergic signaling in cardiomyocytes, and Wnt signaling. Through integrative analyses, we determined that 126 genes showed a negative correlation between up-regulated expression and down-regulated methylation. KEGG enrichment analysis of these genes indicated participation in ECM-receptor interaction, regulation of actin cytoskeleton, and focal adhesion. Using RT-qPCR, we confirmed the differential expression of lamb3, itga6, limk2, itgb4, capn2, and thbs1. This study revealed for the first time the molecular responses of skeletal muscle to cortisol at the transcriptomic and whole-genome DNA methylation levels in rainbow trout.

Revisiting Epigenetics Fundamentals and Its Biomedical Implications.

In light of the post-genomic era, epigenetics brings about an opportunity to better understand how the molecular machinery works and is led by a complex dynamic set of mechanisms, often intricate and complementary in many aspects. In particular, epigenetics links developmental biology and genetics, as well as many other areas of knowledge. The present work highlights substantial scopes and relevant discoveries related to the development of the term from its first notions. To our understanding, the concept of epigenetics needs to be revisited, as it is one of the most relevant and multifaceted terms in human knowledge. To redirect future novel experimental or theoretical efforts, it is crucial to compile all significant issues that could impact human and ecological benefit in the most precise and accurate manner. In this paper, the reader can find one of the widest compilations of the landmarks and epistemic considerations of the knowledge of epigenetics across the history of biology from the earliest epigenetic formulation to genetic determinism until the present. In the present work, we link the current body of knowledge and earlier pre-genomic concepts in order to propose a new definition of epigenetics that is faithful to its regulatory nature.

Epigenetic disease markers in primary sclerosing cholangitis and primary biliary cholangitis-methylomics of cholestatic liver disease.

BACKGROUND: The epigenome, the set of modifications to DNA and associated molecules that control gene expression, cellular identity, and function, plays a major role in mediating cellular responses to outside factors. Thus, evaluation of the epigenetic state can provide insights into cellular adaptions occurring over the course of disease. METHODS: We performed epigenome-wide association studies of primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC) using the Illumina MethylationEPIC Bead Chip. RESULTS: We found evidence of increased epigenetic age acceleration and differences in predicted immune cell composition in patients with PSC and PBC. Epigenetic profiles demonstrated differences in predicted protein levels including increased levels of tumor necrosis factor receptor superfamily member 1B in patients with cirrhotic compared to noncirrhotic PSC and PBC. Epigenome-wide association studies of PSC discovered strongly associated 5'-C-phosphate-G-3' sites in genes including vacuole membrane protein 1 and SOCS3, and epigenome-wide association studies of PBC found strong 5'-C-phosphate-G-3' associations in genes including NOD-like receptor family CARD domain containing 5, human leukocyte antigen-E, and PSMB8. Analyses identified disease-associated canonical pathways and upstream regulators involved with immune signaling and activation of macrophages and T-cells. A comparison of PSC and PBC data found relatively little overlap at the 5'-C-phosphate-G-3' and gene levels with slightly more overlap at the level of pathways and upstream regulators. CONCLUSIONS: This study provides insights into methylation profiles of patients that support current concepts of disease mechanisms and provide novel data to inspire future research. Studies to corroborate our findings and expand into other -omics layers will be invaluable to further our understanding of these rare diseases with the goal to improve and individualize prognosis and treatment.

Interferon subverts an AHR-JUN axis to promote CXCL13+ T cells in lupus.

Systemic lupus erythematosus (SLE) is prototypical autoimmune disease driven by pathological T cell-B cell interactions1,2. Expansion of T follicular helper (TFH) and T peripheral helper (TPH) cells, two T cell populations that provide help to B cells, is a prominent feature of SLE3,4. Human TFH and TPH cells characteristically produce high levels of the B cell chemoattractant CXCL13 (refs. 5,6), yet regulation of T cell CXCL13 production and the relationship between CXCL13+ T cells and other T cell states remains unclear. Here, we identify an imbalance in CD4+ T cell phenotypes in patients with SLE, with expansion of PD-1+/ICOS+ CXCL13+ T cells and reduction of CD96hi IL-22+ T cells. Using CRISPR screens, we identify the aryl hydrocarbon receptor (AHR) as a potent negative regulator of CXCL13 production by human CD4+ T cells. Transcriptomic, epigenetic and functional studies demonstrate that AHR coordinates with AP-1 family member JUN to prevent CXCL13+ TPH/TFH cell differentiation and promote an IL-22+ phenotype. Type I interferon, a pathogenic driver of SLE7, opposes AHR and JUN to promote T cell production of CXCL13. These results place CXCL13+ TPH/TFH cells on a polarization axis opposite from T helper 22 (TH22) cells and reveal AHR, JUN and interferon as key regulators of these divergent T cell states.

Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology.

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

The pathogenesis of gout: molecular insights from genetic, epigenomic and transcriptomic studies.

The pathogenesis of gout involves a series of steps beginning with hyperuricaemia, followed by the deposition of monosodium urate crystal in articular structures and culminating in an innate immune response, mediated by the NLRP3 inflammasome, to the deposited crystals. Large genome-wide association studies (GWAS) of serum urate levels initially identified the genetic variants with the strongest effects, mapping mainly to genes that encode urate transporters in the kidney and gut. Other GWAS highlighted the importance of uncommon genetic variants. More recently, genetic and epigenetic genome-wide studies have revealed new pathways in the inflammatory process of gout, including genetic associations with epigenomic modifiers. Epigenome-wide association studies are also implicating epigenomic remodelling in gout, which perhaps regulates the responsiveness of the innate immune system to monosodium urate crystals. Notably, genes implicated in gout GWAS do not include those encoding components of the NLRP3 inflammasome itself, but instead include genes encoding molecules involved in its regulation. Knowledge of the molecular mechanisms underlying gout has advanced through the translation of genetic associations into specific molecular mechanisms. Notable examples include ABCG2, HNF4A, PDZK1, MAF and IL37. Current genetic studies are dominated by participants of European ancestry; however, studies focusing on other population groups are discovering informative population-specific variants associated with gout.

[Gene-age interaction study of breast cancer prognosis based on epigenomic data].

Objective: Exploring gene-age interactions associated with breast cancer prognosis based on epigenomic data. Methods: Differential expression analysis of DNA methylation was conducted using multiple independent epigenomic datasets of breast cancer from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The false discovery rate (FDR) method was used for multiple corrections, retaining differentially methylated sites with q-FDR≤0.05. A three-stage analytic strategy was implemented, using a multivariable Cox proportional hazards regression model to examine gene-age interactions. In the discovery phase, signals with q-FDR ≤ 0.05 were screened out using TCGA-BRCA database. In validation phaseⅠ, the interaction was validated using GSE72245 data, with criteria of P≤0.05 and consistent effect direction. In validation phaseⅡ, the signals were further validated using GSE37754 and GSE75067 data. A prognostic prediction model was constructed by incorporating clinical indicators and interaction signals. Results: The three-stage analytic strategy identified a methylation site (cg16126280EBF1), which interacted with age to jointly affect the overall survival time of patients (interaction HR= 1.001 1,95%CI:1.000 7-1.001 5,P<0.001). Stratified analysis by age showed that the effect of hypermethylation of cg16126280EBF1 was completely opposite in younger patients (HR=0.550 5, 95%CI: 0.383 8-0.789 6, P=0.001) and older patients (HR=2.166 5, 95%CI: 1.285 2-3.652 2, P=0.004). Conclusions: The DNA methylation site cg16126280EBF1 exhibits an interaction with age, jointly influencing the prognosis of breast cancer in a complex association pattern. This finding contributes new population-based evidence for the development of age-specific targeted drugs.

Epigenomic Profiling of B Cell Subsets by CUT&Tag.

Epigenetic programs play a key role in regulating the development and function of immune cells. However, conventional methods for profiling epigenetic mechanisms, such as the post-translational modifications to histones, present several technical challenges that prevent a complete understanding of gene regulation. Here, we provide a detailed protocol of the Cleavage Under Targets and Tagmentation (CUT&Tag) chromatin profiling technique for identifying histone modifications in human and mouse lymphocytes.

Using High-Throughput Measurements to Identify Principles of Transcriptional and Epigenetic Regulators.

To achieve exquisite control over the epigenome, we need a better predictive understanding of how transcription factors, chromatin regulators, and their individual domain's function, both as modular parts and as full proteins. Transcriptional effector domains are one class of protein domains that regulate transcription and chromatin. These effector domains either repress or activate gene expression by interacting with chromatin-modifying enzymes, transcriptional cofactors, and/or general transcriptional machinery. Here, we discuss important design considerations for high-throughput investigations of effector domains, recent advances in discovering new domains in human cells and testing how domain function depends on amino acid sequence. For every effector domain, we would like to know the following: What role does the cell type, signaling state, and targeted context have on activation, silencing, and epigenetic memory? Large-scale measurements of transcriptional activities can help systematically answer these questions and identify general rules for how all these parameters affect effector domain activities. Last, we discuss what steps need to be taken to turn a newly discovered effector domain into a robust, precise epigenome editor. With more carefully considered high-throughput investigations, soon we will have better predictive control over the epigenome.

Designing Epigenome Editors: Considerations of Biochemical and Locus Specificities.

The advent of locus-specific protein recruitment technologies has enabled a new class of studies in chromatin biology. Epigenome editors (EEs) enable biochemical modifications of chromatin at almost any specific endogenous locus. Their locus-specificity unlocks unique information including the functional roles of distinct modifications at specific genomic loci. Given the growing interest in using these tools for biological and translational studies, there are many specific design considerations depending on the scientific question or clinical need. Here, we present and discuss important design considerations and challenges regarding the biochemical and locus specificities of epigenome editors. These include how to: account for the complex biochemical diversity of chromatin; control for potential interdependency of epigenome editors and their resultant modifications; avoid sequestration effects; quantify the locus specificity of epigenome editors; and improve locus-specificity by considering concentration, affinity, avidity, and sequestration effects.

Fluorescent Reporter Systems to Investigate Chromatin Effector Proteins in Living Cells.

Epigenetic research faces the challenge of the high complexity and tight regulation in chromatin modification networks. Although many isolated mechanisms of chromatin-mediated gene regulation have been described, solid approaches for the comprehensive analysis of specific processes as parts of the bigger epigenome network are missing. In order to expand the toolbox of methods by a system that will help to capture and describe the complexity of transcriptional regulation, we describe here a robust protocol for the generation of stable reporter systems for transcriptional activity and summarize their applications. The system allows for the induced recruitment of a chromatin regulator to a fluorescent reporter gene, followed by the detection of transcriptional changes using flow cytometry. The reporter gene is integrated into an endogenous chromatin environment, thus enabling the detection of regulatory dependencies of the investigated chromatin regulator on endogenous cofactors. The system allows for an easy and dynamic readout at the single-cell level and the ability to compensate for cell-to-cell variances of transcription. The modular design of the system enables the simple adjustment of the method for the investigation of different chromatin regulators in a broad panel of cell lines. We also summarize applications of this technology to characterize the silencing velocity of different chromatin effectors, removal of activating histone modifications, analysis of stability and reversibility of epigenome modifications, the investigation of the effects of small molecule on chromatin effectors and of functional effector-coregulator relationships. The presented method allows to investigate the complexity of transcriptional regulation by epigenetic effector proteins in living cells.