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2,207 results for “epigenome”
Maternal Glycemic Dysregulation During Pregnancy and Neonatal Blood DNA Methylation: Meta-analyses of Epigenome-Wide Association Studies
<p>Maternal glycemic dysregulation during pregnancy increases the risk of adverse health outcomes in her offspring, a risk thought to be linearly related to maternal hyperglycemia. It is hypothesized that changes in offspring DNA methylation (DNAm) underline these associations. To address this hypothesis, we conducted fixed-effects meta-analyses of epigenome-wide association study (EWAS) results from eight birth cohorts investigating relationships between cord blood DNAm and fetal exposure to maternal glucose (Nmaximum= 3,503), insulin (Nmaximum= 2,062), and area under the curve of glucose (AUCgluc) following oral glucose tolerance tests (Nmaximum = 1,505). Inflation and bias was addressed with the bacon Bioconductor package for individual cohorts and the meta-analysis results and reported model estimates and standard errors are adjusted. Greater maternal AUCgluc during pregnancy was associated with lower cord blood DNAm at neighboring CpGs cg26974062 and cg02988288 in TXNIP. Follow-up analyses show that these changes may have functional and later-life consequences and warrant further mediation and causal analysis. </p> <p>The corresponding paper can be found here: https://doi.org/10.2337/dc21-1701.</p> <p>Upload of this dataset was completed by The EWAS Catalog team. The data can be queried along with hundreds of other EWAS at ewascatalog.org. To upload your EWAS summary statistics and have a Zenodo DOI generated for you go to ewascatalog.org/upload.</p>
101K workflow jobs dataset (1.2 million tasks); a composition of Epigenomics and Montage workflows
<p>This dataset contains detailed information about more than 101 thousand jobs with 1.2 million tasks. This dataset can be used in various simulation, training, and modelling processes. various information about each job is recorded and the underlying environment was based on IoT/Fog/Cloud in which IoT nodes only generate requests and Fog and Cloud nodes process these requests.</p>
An optimized 4C-seq protocol based on cistrome and epigenome data in the mouse RAW264.7 macrophage cell line
<p>In this protocol, we describe the 4C-seq method in detail using RAW264.7 cells, a mouse macrophage cell line widely used to study acute and metabolic inflammation. We specifically outline how cistrome and epigenome data can be integrated into the primer designing step, critical for the entire protocol. Because intra-TAD chromatin loops are facilitated by transcription factors and coregulators, many of which are co-localized in open chromatin regions, the binding centers of those factors can be obtained by chromatin immunoprecipitation sequencing (ChIP-seq). The binding sites of these factors reflect the coherent loci of the chromatin loops and therefore can be used as references to improve the accuracy of the 4C primers. We specifically describe the 4C protocol using examples of recently identified Ccl2 enhancer and silencer as bait. <br> </p>
Genome graphs detect human polymorphisms in active epigenomic states during influenza infection: code and processed data
<p>Manuscript, figure, and analysis code and processed data for the Groza et al (2022) preprint.</p>
Epigenomic analysis on the HPRC genome graphs
<p>Processed data, analysis and figure code for the epigenomic analysis on the HPRC genome graph.</p>
Plasticity across levels: relating epigenomic, transcriptomic, and phenotypic responses to osmotic stress in a halotolerant microalga
<p>Phenotypic plasticity, the ability of a given genotype to produce alternative phenotypes in response to its environment of development, is an important mechanism for coping with variable environments. While the mechanisms underlying phenotypic plasticity are diverse, their relative contributions need to be investigated quantitatively to better understand the evolvability of plasticity across biological levels. This requires relating plastic responses of the epigenome, transcriptome, and organismal phenotype, and investigating how they vary with the genotype. Here we carried out this approach for responses to osmotic stress in <em>Dunaliella salina</em>, a green microalga that is a model organism for salinity tolerance. We compared two strains that show markedly different demographic responses to osmotic stress, and showed that these phenotypic responses involve strain- and environment-specific variation in gene expression levels, but a relative low - albeit significant - effect of strain × environment interaction. We also found an important genotype effect on the genome-wide methylation pattern, but little contribution from environmental conditions to the latter. However, we did detect a significant marginal effect of epigenetic variation on gene expression, beyond the influence of genetic differences on epigenetic state, and we showed that hypomethylated regions are correlated with higher gene expression. Our results indicate that epigenetic mechanisms are either not involved in the rapid plastic response to environmental change in this species, or involve only few changes in <em>trans</em> that are sufficient to trigger concerted changes in the expression of many genes, and phenotypic responses by multiple traits.</p>
Data from: Microplastic exposure is associated with epigenomic effects in the model organism Pimephales promelas (fathead minnow)
<p>Microplastics have evolutionary and ecological impacts across species, affecting organisms' development, reproduction, and behavior along with contributing to genotoxicity and stress. As plastic pollution is increasing and ubiquitous, gaining a better understanding of organismal responses to microplastics is necessary. Gene methylation is a heritable form of molecular regulation that is influenced by environmental conditions, including exposure to pollutants, therefore determining epigenetic responses to microplastics will reveal potential chronic consequences of this pollutant. We performed an experiment across two generations of fathead minnows (<em>Pimephales promelas</em>) to elucidate transgenerational effects of microplastic exposure. We exposed the first generation of fish to four different treatments of microplastics: two concentrations of each of pre-consumer polyethylene (PE) and PE collected from Lake Ontario. We then raised the second generation from these parents with no microplastic exposure. We used reduced-representation methylation sequencing on adult liver tissue and homogenized larvae to evaluate DNA methylation differences among treatments, sexes, and generations. Our findings show the origin of the plastic had a larger effect in female minnows whereas the effect of concentration was stronger in the males. We also observed transgenerational effects, highlighting a mechanism in which parents can pass on the effects of microplastic exposure to their offspring. Many of the differentially methylated genes found in our analyses are known to interact with estrogenic chemicals associated with plastic and are related to metabolism. This study highlights the persistent and potentially serious impacts of microplastic pollution on gene regulation in freshwater systems.</p>
Dynamic antagonism between key repressive pathways maintains the placental epigenome (source data and custom code)
<p>DNA and Histone-3 Lysine 27 methylation typically function as repressive modifications and operate within distinct genomic compartments. In mammals, the majority of the genome is kept in a DNA methylated state, whereas the Polycomb Repressive Complexes regulate the CpG-rich promoters of developmental genes. In contrast to this general framework, the extraembryonic lineages display noncanonical, globally intermediate DNA methylation levels that includes disruption of local Polycomb domains. To better understand this unusual landscape’s molecular properties, we genetically and chemically perturbed major epigenetic pathways in mouse Trophoblast Stem Cells (TSCs). We find that the extraembryonic epigenome reflects ongoing and dynamic de novo methyltransferase recruitment, which is continuously antagonized by Polycomb to maintain intermediate, locally disordered methylation. Despite its disorganized appearance, our data point to a highly controlled equilibrium between counteracting repressors within extraembryonic cells, one that can seemingly persist indefinitely without bistable features typically seen for embryonic forms of epigenetic regulation.</p> <p> </p>
Atopic dermatitis and DNA methylation at birth: findings from epigenome-wide meta-analyses
<p>Meta-analyses results from "Atopic dermatitis and DNA methylation at birth: findings from epigenome-wide meta-analyses". This data contains summary statistics from 12 meta-analyses of EWAS of atopic dermatitis (AD) using DNA methylation measured using the Illumina Infinium HumanMethylation450 BeadChip. Details on the analyses can be found in the paper. </p> <p>Each of the files are tab-separated with the following column names (description in brackets):</p> <ul> <li>CpG</li> <li>Beta (the effect estimate)</li> <li>SE (standard error)</li> <li>P (P value)</li> <li>Direction (Direction of effect within each cohort)</li> <li>Het_ISq (I2 value of heterogeneity)</li> <li>Het_P (P value from Cochran’s Q-test for heterogeneity)</li> </ul> <p>The files are named in the following way: `AD-PHENOTYPE_MODEL_COHORT-STRAT.tsv`</p> <p>AD-PHENOTYPE: childhood, early-onset, or persistent.<br> MODEL: Model A, B, or C (see paper for details)<br> COHORT-STRAT: If the cohorts were stratified in anyway here is where it will be indicated. DD = AD was defined by doctor diagnosis only, DD-R = AD was defined by doctor diagnosis and/or rash symptoms, HR = AD was defined using the Hanifin-Rajka criteria. </p> <p>For example, the file `childhood_model-C_DD.tsv` contains the summary statistics from the meta-analysis of EWAS of AD within cohorts that defined AD using doctor diagnosis only. </p>
Blood-based epigenome-wide analyses on the prevalence and incidence of nineteen common disease states
<p>Epigenome-wide association studies (EWAS) were performed using whole-blood methylation and self-report disease data (prevalent disease) for 14 conditions at the study baseline of Generation Scotland. Furthermore, EWAS were performed on 19 incident conditions using electronic health record linkage to ascertain diagnoses following the study baseline. Basic and fully-adjusted models were considered, resulting in 66 models in total.</p> <p>medRxiv 2023.01.10.23284387; doi: https://doi.org/10.1101/2023.01.10.23284387</p>
Mapping the epigenomic landscape of human monocytes following innate immune activation reveals context-specific mechanisms driving endotoxin tolerance
<p><strong>Processed datasets for publication at <em>BMC Genomics</em>.</strong></p> <p>We exposed human primary monocytes from healthy donors (n=6) to interferon-γ or differing combinations of endotoxin (lipopolysaccharide), including acute response (2hr LPS; LPS2) and two models of endotoxin tolerance: repeated stimulations (6+6hr; LPS6:6) and prolonged exposure to endotoxin (24hr LPS; LPS24). Another subset of monocytes was left untreated (naïve; UT). We performed total RNA-seq and ATAC-seq for monocytes across these treatment conditions.</p> <p>The following processed datasets include the raw and normalised count data for each gene or ATAC peak, and the bedGraph and bigWig format for genome-wide signal data. [ bigWig files for RNA-seq (monocytes_*_mean.bw); bigWig files for ATAC-seq (Monocyte_ATAC_*_mean_normalised.by.1/size.factor.bw); bedgraph files for eRNA visualization (*RPKM_FR.bedgraph.gz); raw and normalised count files for ATAC-seq and RNA-seq data (Monocyte.featureCounts_RNAseq.txt.gz; Monocyte_filtered_log2.normalized_RNAseq_counts.txt.gz; Meta.file.txt.gz; Monocyte_raw.counts_ATACseq.txt.gz.).]</p> <p><strong>Data curator:</strong></p> <p>Ping Zhang</p> <p> </p>
Clinical subtyping of cancer from plasma based on comprehensive epigenomic profiling
<p><em><strong>Fragment bed files part 1.</strong></em></p> <p> </p> <p>While circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1mL of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors, and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling could unlock clinically actionable information that is currently accessible only via direct tissue sampling. </p> <div class="notranslate"> </div>
Clinical subtyping of cancer from plasma based on comprehensive epigenomic profiling
<p><strong><em>Fragment bed files part 2.</em></strong></p> <p>While circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1mL of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors, and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling could unlock clinically actionable information that is currently accessible only via direct tissue sampling. </p> <p> </p>
Clinical subtyping of cancer from plasma based on comprehensive epigenomic profiling
<p><strong><em>Peak bed files.</em></strong></p> <p> </p> <p>While circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1mL of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors, and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling could unlock clinically actionable information that is currently accessible only via direct tissue sampling. </p>
Clinical subtyping of cancer from plasma based on comprehensive epigenomic profiling
<p><strong><em>Fragment bed files part 3.</em></strong></p> <p> </p> <p>While circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1mL of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors, and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling could unlock clinically actionable information that is currently accessible only via direct tissue sampling. </p>
NeuroPsyBiT-BD Omics: Genomic & Epigenomic Biobank of Bipolar Disorder
ClinicalTrials.gov study NCT07173842. IPD Sharing: YES. Countries: 1. Publications: 16.
Plasticity across levels: relating epigenomic, transcriptomic, and phenotypic responses to osmotic stress in a halotolerant microalga
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Data from: Microplastic exposure is associated with epigenomic effects in the model organism Pimephales promelas (fathead minnow)
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A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids
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Museum epigenomics: characterizing cytosine methylation in historic museum specimens
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.