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2,207 results for “epigenome”
Epigenome-Wide Association Study of DNA Methylation and Adult Asthma in the Agricultural Lung Health Study
<p>In an epigenome-wide association study of blood DNA methylation in adults conducted in the Agricultural Lung Health Study, 524 differentially methylated CpG sites were associated with non-atopic asthma (FDR<0.05) and 1,086 differentially methylated CpGs were associated with atopic asthma. No CpG sites were differentially methylated in relation to atopy alone. </p>
Machine learning datasets for epigenomic landscapes in epidermal differentiation
<p>Datasets for training classification and regression models on sequence and epigenomic features. The data used here is generated from an integrative analysis of the Genomics of Gene Regulation dataset (https://www.encodeproject.org/awards/U01HG007919). For classification models, the peak files used to label genomic regions as positives or negatives can be found in `ggr.label_files.tar.gz`. For regression models, the bigwig files used for target signals can be found at the ENCODE portal. he processed dataset stored in hdf5 format files along with processing details are in the file `nn.ggr.hdf5_files.tar.gz`.</p>
Dual DNA/protein tagging of open chromatin unveils dynamics of epigenomic landscapes in leukemia
<p>The architecture of chromatin specifies eukaryotic cell identity by controlling transcription factor access to sites of gene regulation. Here we describe a dual transposase/peroxidase approach, integrative DNA And Protein Tagging (iDAPT), which detects both DNA (iDAPT-seq) and protein (iDAPT-MS) associated with accessible regions of chromatin. In addition to direct identification of bound transcription factors, iDAPT enables the inference of their gene regulatory networks, protein interactors, and regulation of chromatin accessibility. We applied iDAPT to profile the epigenomic consequences of granulocytic differentiation of acute promyelocytic leukemia, yielding previously undescribed mechanistic insights with potential therapeutic implications. Our findings demonstrate the power of iDAPT as a discovery platform for both the dynamic epigenomic landscapes and their transcription factor components associated with biological phenomena and disease.</p>
Data from: Evolutionary epigenomics of retrotransposon-mediated methylation spreading in rice
Plant genomes contain numerous transposable elements (TEs), and many hypotheses on the evolutionary drivers that restrict TE activity have been postulated. Few models, however, have focused on the evolutionary epigenomic interaction between the plant host and its TE. The host genome recruits epigenetic factors, such as methylation, to silence TEs but methylation can spread beyond the TE sequence and influence the expression of nearby host genes. In this study, we investigated this epigenetic trade-off between TE and proximal host gene silencing by studying the epigenomic regulation of repressing long terminal repeat (LTR) retrotransposons (RTs) in Oryza sativa. Results showed significant evidence of methylation spreading originating from the LTR-RT sequences, and the extent of spreading was dependent on 5 factors: 1) LTR-RT family, 2) time since the LTR-RT insertion, 3) recombination rate of the LTR-RT region, 4) level of LTR-RT sequence methylation, and 5) chromosomal location. Methylation spreading had negative effects by reducing host gene expression, but only on host genes with LTR-RT inserted in its introns. Our results also suggested high levels of LTR-RT methylation might have a role in suppressing TE-mediated deleterious ectopic recombination. In the end, despite the methylation spreading, no strong epigenetic trade-off was detected and majority of LTR-RT may have only minor epigenetic effects on nearby host genes.
Example modbed files can be used for visualization on the WashU Epigenome Browser
<p>Example modbed files can be used for visualization on the <a href="https://epigenomegateway.wustl.edu/browser/">WashU Epigenome Browser</a>. Please check README for more details.</p><p>Please contact Daofeng Li (dli23@wustl.edu) if you have any questions.</p><h3>Description of the files:</h3><p>HG00621.remora.modbed.gz: Genome wide ONT remora data</p><p>remora-test-chr11.modbed.gz: ONT remora data only on chr11</p><p>HG00621.hifi.cpg.modbed.gz: Genome wide PacBio Hifi data</p><p>hifi-test-chr11.cpg.modbed.gz: PacBio Hifi data only on chr11 at CpG mode</p><p>hifi-test.modbed-hbg.gz: PacBio Hifi data only on chr11:5162720-5356331</p><p>GSM4411218_tracks_m6A_DS75167.dm6.modbed.gz: Fruit fly Fiber-seq data</p><h3>Note:</h3><p>Please note that you would need <a href="https://www.htslib.org/doc/tabix.html">Tabix</a> to index the .gz files.</p>
Blood-based epigenome–wide analyses of chronic low–grade inflammation across diverse population cohorts
<p>Authors: Robert F. Hillary, Hong Kiat Ng, Daniel L. McCartney, Hannah R. Elliott, Rosie M. Walker, Archie Campbell, Felicia Huang, Kenan Direk, Paul Welsh, Naveed Sattar, Janie Corley, Caroline Hayward, Andrew M. McIntosh, Cathie Sudlow, Kathryn L. Evans, Simon R. Cox, John C. Chambers, Marie Loh, Caroline L. Relton, Riccardo E. Marioni, Paul D. Yousefi, Matthew Suderman</p> <p>Epigenome-wide association studies were performed on log-transformed blood C-reactive protein levels in Generation Scotland. Log-transformed CRP was the outcome. CpG beta-values were the exposure and were measured using the EPIC array (n=752,722 sites). </p> <p>A basic model adjusted for age, sex, experimental batch and Houseman-estimated white blood cell proportions. A fully-adjusted model further adjusted for alcohol consumption (units/week), log-transformed body mass index (kg/m2), education (11-category ordinal variable), deprivation (Scottish Index of Multiple Deprivation), EpiSmokEr (a methylation-based surrogate score for cigarette smoking) and 20 genetic principal components (to control for population structure).</p>
Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence
<p>Choudhary, P., Monasso, G. S., Karhunen, V., Ronkainen, J., Mancano, G., Howe, C. G., Niu, Z., Zeng, X., Guan, W., Dou, J., Feinberg, J. I., Mordaunt, C., Pesce, G., Baïz, N., Alfano, R., Martens, D. S., Wang, C., Isaevska, E., Keikkala, E., Mustaniemi, S., … Sebert, S. (2023). <a href="https://pubmed.ncbi.nlm.nih.gov/38052982/">Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence.</a> Molecular psychiatry, 10.1038/s41380-023-02331-5. Advance online publication. https://doi.org/10.1038/s41380-023-02331-5</p> <p>Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.</p>
In-depth comparative toxicogenomics of glyphosate and Roundup herbicides: Histopathology, transcriptome and epigenome signatures, and DNA damage
<p><span><span><span><span><span><span><span><span><span><span><span>Whether or not glyphosate activates cellular mechanisms involved in carcinogenesis remains controversial. We tested whether glyphosate and three glyphosate-based commercial herbicide formulations activate mechanisms known to be key characteristics of carcinogens. The mammalian stem cell-based genotoxicity ToxTracker assay showed that the representative EU formulation Roundup MON 52276 and the UK formulation Roundup MON 76473, but not glyphosate and the US Roundup formulation MON 76207, activated oxidative stress and unfolded protein responses. High-throughput molecular profiling of liver function was performed in female Sprague-Dawley rats exposed to glyphosate or MON 52276 (both at 0.5, 50, 175 mg/kg bw/day glyphosate equivalent concentration) for 90 days. Histopathology and serum biochemistry analysis showed that MON 52276 but not glyphosate treatment increased hepatic steatosis and necrosis. MON 52276 and glyphosate altered the expression of genes in liver reflecting TP53 activation by DNA damage and the regulation of circadian rhythms. The most affected genes in liver also had their expression similarly altered in kidneys. Small RNA profiling in liver showed miR-22 and miR-17 had their levels decreased by MON 52276, while mir-30 levels were decreased, whilst miR-10 levels were increased by glyphosate. DNA methylation profiling of liver revealed 5,727 and 4,496 differentially methylated CpG sites between the control and glyphosate and MON 52276 exposed groups of animals respectively. Direct DNA damage measurement by apurinic/apyrimidinic lesion formation in liver was increased with glyphosate exposure. Altogether, our results show that Roundup herbicide formulations are causing more biological changes than glyphosate alone, activating mechanisms involved in cellular carcinogenesis.</span></span></span></span></span></span></span></span></span></span></span></p>
Blood-based epigenome-wide analyses of cognitive abilities
<p>CpGs and corresponding mean weights for DNAm-based prediction of cognitive abilities (6 traits)</p>
Complementary genomic and epigenomic adaptation to environmental heterogeneity
<p><span>While adaptation is commonly thought to result from selection on DNA sequence-based variation, recent studies have highlighted an analogous epigenetic component as well. However, the relative roles of these mechanisms in facilitating population persistence under environmental heterogeneity remain unclear. To address the underlying genetic and epigenetic mechanisms and their relationship during environmental adaptation, we screened the genomes and epigenomes of nine global populations of a predominately sessile marine invasive tunicate, <em>Botryllus schlosseri</em>. We detected clear population differentiation at the genetic and epigenetic levels. Patterns of genetic and epigenetic structure were significantly influenced by local environmental variables. Among these variables, minimum annual sea surface temperature was simultaneously identified as the top explanatory variable for both genetic and epigenetic variation. However, patterns of population structure driven by genetic and epigenetic variation were somewhat distinct, suggesting possible autonomy of epigenetic variation. We found both shared and specific genes and biological pathways among genetic and epigenetic loci</span><span> associated with environmental factors</span><span>, consistent with complementary and independent contributions of genetic and epigenetic variation to environmental adaptation in this system. Collectively, these mechanisms may facilitate population persistence under environmental change and sustain successful invasions across novel environments.</span></p>
Evaluating deep learning for predicting epigenomic profiles
<p>Datasets and static codebase to replicate figures and results from the project.</p>
Timing of blood sample processing affects the transcriptomic and epigenomic profiles in CD4+ T-cells of atopic subjects
<p><span>Optimal</span><span> pre-analytical conditions for blood sample processing and isolation of selected cell populations for subsequent transcriptomic and epigenomic studies are required to obtain robust and reproducible results. This pilot study was conducted to investigate the potential effects of timing of CD4<sup>+</sup> T-cell processing from peripheral blood of atopic and non-atopic adults on their transcriptomic and epigenetic profiles. Two heparinized blood samples were drawn from each of three atopic and three healthy individuals. For each individual, </span><span>CD4<sup>+</sup></span><span> T-cells were isolated from the first blood sample within 2 hours (immediate) or from the second blood sample after 24 hours storage (delayed). RNA sequencing (RNA-Seq) and histone H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-Seq) analyses were performed. A multiplicity of genes was shown to be differentially expressed in immediately processed </span><span>CD4<sup>+</sup></span><span> T-cells from atopic versus healthy subjects. These differences disappeared when comparing delayed processed cells due to a drastic change in expression levels of atopy-related genes in delayed processed </span><span>CD4<sup>+</sup></span><span> T-cells from atopic donors. This finding was further validated on the epigenomic level by examining H3K27 acetylation profiles. In contrast, transcriptomic and epigenomic profiles of blood </span><span>CD4<sup>+</sup></span><span> T-cells of healthy donors remained rather unaffected. Taken together, for successful transcriptomics and epigenomics studies, detailed standard operating procedures developed on the basis of samples from both healthy and disease conditions are implicitly recommended.</span></p>
Linking the gut microbiome to host DNA methylation by a discovery and replication epigenome-wide association study
<p>BACKGROUND: The datafiles deposited here are products of the research project "<strong>Linking the gut microbiome to host DNA methylation by a discovery and replication epigenome-wide association study"</strong></p><p>Authors: Ayşe Demirkan1,2, Jenny van Dongen3,4, Casey T. Finnicum5, Harm-Jan Westra1, Soesma Jankipersadsing1, Gonneke Willemsen3,4, Richard G. Ijzerman6, Dorret I. Boomsma3,4, Erik A. Ehli5, Marc Jan Bonder1, Jingyuan Fu,1,7 Lude Franke1, Cisca Wijmenga1, Eco J.C. de Geus3,4, Alexander Kurilshikov1, Alexandra Zhernakova1</p><p>1 Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands</p><p>2 Section of Statistical Multi-omics, Department of Clinical and Experimental Medicine, School of Biosciences and Medicine & People-Centered AI institute University of Surrey, Guildford, United Kingdom</p><p>3 Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands</p><p>4 Amsterdam Public Health Research Institute, Amsterdam, the Netherlands</p><p>5 Avera Institute of Human Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD, USA</p><p>6 Department of Endocrinology, Amsterdam University Medical Center, location VUMC, Amsterdam, the Netherlands</p><p>7 Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands</p><p><strong>Corresponding Authors: </strong>Alexandra Zhernakova; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands</p><p>Ayse Demirkan; Section of Statistical Multi-omics, Department of Clinical and Experimental Medicine, School of Biosciences and Medicine & People-Centered AI institute University of Surrey, Guildford, United Kingdom.</p><p>FILES: </p><p>1-merged_lld16s.Rata: Epigenome-wide association of 16s microbial abundances in LifeLines-Deep (LLD, n = 616, 450k methylation array) </p><p>2-lld_mgs.Rdata: Epigenome-wide association ofshotgun metagenomic sequencing derived taxa relative abundances (n = 683, 450k methylation array))</p><p>3-lld_<i>mgs_</i>pathways. Rdata: Epigenome-wide association ofshotgun metagenomic sequencing derived bacterial pathway relative abundances (n = 683, 450k methylation array)</p><p>FUNDING: The Lifelines initiative has been made possible by subsidy from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen (UMCG), Groningen University and the Provinces in the North of the Netherlands (Drenthe, Friesland, Groningen). The Netherlands Twin Register acknowledges funding from the Netherlands Organization for Scientific Research (NWO): (NWO 911–09–032; NWO 480-04-004; 480-15-001/674, NWO 916-130-82), Biobanking and Biomolecular Research Infrastructure (184.033.111), and the BBRMI-NL-financed BIOS Consortium (NWO 184.021.007), NWO Large Scale infrastructures X-Omics (184.034.019), Genotype/phenotype database for behaviour genetic and genetic epidemiological studies (ZonMw Middelgroot 911-09-032); Netherlands Twin Registry Repository: researching the interplay between genome and environment (NWO-Groot 480-15-001/674); the Avera Institute, Sioux Falls (USA), the European Research Council (Genetics of Mental Illness 230374), the European Research Council (Genetics of Mental Illness 230374), and INRA-Pfizer. Pfizer provided support for data collection, but did not have any additional role in the study design, data analysis, decision to publish, or preparation of the manuscript.</p><p> </p>
Roadmap Epigenomics Enhancer-Gene links
Open the record for dataset details and reuse information.
Supplementary video for "Rapid brain tumor classification from sparse epigenomic data"
<p>Although the intraoperative, molecular differential diagnosis of the approximately one hundred different brain tumor entities described to date has been a goal of neuropathology in the last decade, this has not yet been achieved in a clinically relevant time frame of less than one hour after biopsy collection. Recent advances in third-generation sequencing technologies have brought this once-elusive goal within reach. However, established machine learning techniques rely on concepts and methods, impractical for live diagnostic workflows in clinical applications. Here, we present MethyLYZR, a Naïve Bayesian framework enabling fully tractable live classification of cancer epigenomes. MethyLYZR can be run in parallel with an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing. Therefore, only the time required for DNA extraction and the Nanopore sequencer's maximum parallel throughput remain limiting factors for even faster time-to-results. We demonstrate the potential utility of the MethyLYZR framework not only for the neurosurgical intraoperative use case but also for other oncologic indications and cell-free DNA from liquid biopsies.</p> <div> <div> <div> <p> </p> <p>The video is a composite of 10 clinical demonstrator runs with timings for DNA extraction and library preparation.</p> </div> </div> </div>
Methylation data for "Rapid brain tumor classification from sparse epigenomic data"
<p>Although the intraoperative, molecular differential diagnosis of the approximately one hundred different brain tumor entities described to date has been a goal of neuropathology in the last decade, this has not yet been achieved in a clinically relevant time frame of less than one hour after biopsy collection. Recent advances in third-generation sequencing technologies have brought this once-elusive goal within reach. However, established machine learning techniques rely on concepts and methods, impractical for live diagnostic workflows in clinical applications. Here, we present MethyLYZR, a Naïve Bayesian framework enabling fully tractable live classification of cancer epigenomes. MethyLYZR can be run in parallel with an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing. Therefore, only the time required for DNA extraction and the Nanopore sequencer's maximum parallel throughput remain limiting factors for even faster time-to-results. We demonstrate the potential utility of the MethyLYZR framework not only for the neurosurgical intraoperative use case but also for other oncologic indications and cell-free DNA from liquid biopsies.</p> <p> </p> <p>This dataset provides methylation data from ONT and PacBio sequencing in feather file format. </p>
Expanded dynamic methylome and quantitative trait detection by long-read epigenome profiling of personal DNA
<p>Scripts and methylation frequencies for "Expanded dynamic methylome and quantitative trait detection by long-read epigenome profiling of personal DNA" manuscript.</p>
The genomic and epigenomic landscapes of hemizygous genes across crops with contrasting mating systems
Open the record for dataset details and reuse information.
Genome graphs detect human polymorphisms in active epigenomic states during influenza infection: validation
<p>Sanger sequencing and qPCR validation data for "Genome graphs detect human polymorphisms in active epigenomic states during influenza infection" manuscript.</p>
data for Multi-tissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
<p>processed data for "Multi-tissue H3K27ac profiling of GTEx samples links epigenomic variation to disease"</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.