Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse.

ABSTRACT: We have developed a mouse DNA methylation array that contains 296,070 probes representing the diversity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc ^Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.

SUBMITTER: Zhou W

PROVIDER: S-EPMC9306256 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

High-throughput DNA methylation profiling using universal bead arrays.

Project description:We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.

| S-EPMC1415217 | biostudies-literature

A statistical method for excluding non-variable CpG sites in high-throughput DNA methylation profiling.

Project description:High-throughput DNA methylation arrays are likely to accelerate the pace of methylation biomarker discovery for a wide variety of diseases. A potential problem with a standard set of probes measuring the methylation status of CpG sites across the whole genome is that many sites may not show inter-individual methylation variation among the biosamples for the disease outcome being studied. Inclusion of these so-called "non-variable sites" will increase the risk of false discoveries and reduce statistical power to detect biologically relevant methylation markers.We propose a method to estimate the proportion of non-variable CpG sites and eliminate those sites from further analyses. Our method is illustrated using data obtained by hybridizing DNA extracted from the peripheral blood mononuclear cells of 311 samples to an array assaying 1505 CpG sites. Results showed that a large proportion of the CpG sites did not show inter-individual variation in methylation.Our method resulted in a substantial improvement in association signals between methylation sites and outcome variables while controlling the false discovery rate at the same level.

| S-EPMC2876131 | biostudies-literature

Extraction and high-throughput sequencing of oak heartwood DNA: Assessing the feasibility of genome-wide DNA methylation profiling.

Project description:Tree ring features are affected by environmental factors and therefore are the basis for dendrochronological studies to reconstruct past environmental conditions. Oak wood often provides the data for these studies because of the durability of oak heartwood and hence the availability of samples spanning long time periods of the distant past. Wood formation is regulated in part by epigenetic mechanisms such as DNA methylation. Studies of the methylation state of DNA preserved in oak heartwood thus could identify epigenetic tree ring features informing on past environmental conditions. In this study, we aimed to establish protocols for the extraction of DNA, the high-throughput sequencing of whole-genome DNA libraries (WGS) and the profiling of DNA methylation by whole-genome bisulfite sequencing (WGBS) for oak (Quercus robur) heartwood drill cores taken from the trunks of living standing trees spanning the AD 1776-2014 time period. Heartwood contains little DNA, and large amounts of phenolic compounds known to hinder the preparation of high-throughput sequencing libraries. Whole-genome and DNA methylome library preparation and sequencing consistently failed for oak heartwood samples more than 100 and 50 years of age, respectively. DNA fragmentation increased with sample age and was exacerbated by the additional bisulfite treatment step during methylome library preparation. Relative coverage of the non-repetitive portion of the oak genome was sparse. These results suggest that quantitative methylome studies of oak hardwood will likely be limited to relatively recent samples and will require a high sequencing depth to achieve sufficient genome coverage.

| S-EPMC8601515 | biostudies-literature

Mapping DNA methylation with high-throughput nanopore sequencing.

Project description:DNA chemical modifications regulate genomic function. We present a framework for mapping cytosine and adenosine methylation with the Oxford Nanopore Technologies MinION using this nanopore sequencer's ionic current signal. We map three cytosine variants and two adenine variants. The results show that our model is sensitive enough to detect changes in genomic DNA methylation levels as a function of growth phase in Escherichia coli.

| S-EPMC5704956 | biostudies-literature

High-throughput sequencing of cytosine methylation in plant DNA.

Project description:: Cytosine methylation is a significant and widespread regulatory factor in plant systems. Methods for the high-throughput sequencing of methylation have allowed a greatly improved characterisation of the methylome. Here we discuss currently available methods for generation and analysis of high-throughput sequencing of methylation data. We also discuss the results previously acquired through sequencing plant methylomes, and highlight remaining challenges in this field.

| S-EPMC3691832 | biostudies-literature

DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patients.

Project description:In addition to genetic predisposition, environmental and lifestyle factors contribute to the pathogenesis of type 2 diabetes (T2D). Epigenetic changes may provide the link for translating environmental exposures into pathological mechanisms. In this study, we performed the first comprehensive DNA methylation profiling in pancreatic islets from T2D and non-diabetic donors. We uncovered 276 CpG loci affiliated to promoters of 254 genes displaying significant differential DNA methylation in diabetic islets. These methylation changes were not present in blood cells from T2D individuals nor were they experimentally induced in non-diabetic islets by exposure to high glucose. For a subgroup of the differentially methylated genes, concordant transcriptional changes were present. Functional annotation of the aberrantly methylated genes and RNAi experiments highlighted pathways implicated in ?-cell survival and function; some are implicated in cellular dysfunction while others facilitate adaptation to stressors. Together, our findings offer new insights into the intricate mechanisms of T2D pathogenesis, underscore the important involvement of epigenetic dysregulation in diabetic islets and may advance our understanding of T2D aetiology.

| S-EPMC3321176 | biostudies-literature

PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data.

Project description:SUMMARY:Performing highly parallelized preprocessing of methylation array data using Python can accelerate data preparation for downstream methylation analyses, including large scale production-ready machine learning pipelines. We present a highly reproducible, scalable pipeline (PyMethylProcess) that can be quickly set-up and deployed through Docker and PIP. AVAILABILITY AND IMPLEMENTATION:Project Home Page: https://github.com/Christensen-Lab-Dartmouth/PyMethylProcess. Available on PyPI (pymethylprocess), Docker (joshualevy44/pymethylprocess). SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

| S-EPMC6954637 | biostudies-literature

A high-throughput DNA methylation analysis of a single cell.

Project description:In recent years, the field of epigenetics has grown dramatically and has become one of the most dynamic and fast-growing branches of molecular biology. The amount of diseases suspected of being influenced by DNA methylation is rising steadily and includes common diseases such as schizophrenia, bipolar disorder, Alzheimer's disease, diabetes, atherosclerosis, cancer, major psychosis, lupus and Parkinson's disease. Due to cellular heterogeneity of methylation patterns, epigenetic analyses of single cells become a necessity. One rationale is that DNA methylation profiles are highly variable across individual cells, even in the same organ, dependent on the function of the gene, disease state, exposure to environmental factors (e.g. radiation, drugs or nutrition), stochastic fluctuations and various other causes. Using a polymerase chain reaction (PCR)-slide microreaction system, we present here a methylation-sensitive PCR analysis, the restriction enzyme-based single-cell methylation assay (RSMA), in the analysis of DNA methylation patterns in single cells. This method addresses the problems of cell heterogeneity in epigenetics research; it is comparably affordable, avoids complicated microfluidic systems and offers the opportunity for high-throughput screening, as many single cells can be screened in parallel. In addition to this study, critical principles and caveats of single cell methylation analyses are discussed.

| S-EPMC3074158 | biostudies-literature

Parent-of-Origin DNA Methylation Dynamics during Mouse Development.

Project description:Parent-specific differentially methylated regions (DMRs) are established during gametogenesis and regulate parent-specific expression of imprinted genes. Monoallelic expression of imprinted genes is essential for development, suggesting that imprints are faithfully maintained in embryos and adults. To test this hypothesis, we targeted a reporter for genomic methylation to the imprinted Dlk1-Dio3 intergenic DMR (IG-DMR) to assess the methylation of both parental alleles at single-cell resolution. Biallelic gain or loss of IG-DMR methylation occurred in a small fraction of mouse embryonic stem cells, significantly affecting developmental potency. Mice carrying the reporter in either parental allele showed striking parent-specific changes in IG-DMR methylation, causing substantial and consistent tissue- and cell-type-dependent signatures in embryos and postnatal animals. Furthermore, dynamics in DNA methylation persisted during adult neurogenesis, resulting in inter-individual diversity. This substantial cell-cell DNA methylation heterogeneity implies that dynamic DNA methylation variations in the adult may be of functional importance.

| S-EPMC5119552 | biostudies-literature

DNA methylation dynamics of genomic imprinting in mouse development.

Project description:DNA methylation is an essential epigenetic mark crucial for normal mammalian development. This modification controls the expression of a unique class of genes, designated as imprinted, which are expressed monoallelically and in a parent-of-origin-specific manner. Proper parental allele-specific DNA methylation at imprinting control regions (ICRs) is necessary for appropriate imprinting. Processes that deregulate DNA methylation of imprinted loci cause disease in humans. DNA methylation patterns dramatically change during mammalian development: first, the majority of the genome, with the exception of ICRs, is demethylated after fertilization, and subsequently undergoes genome-wide de novo DNA methylation. Secondly, after primordial germ cells are specified in the embryo, another wave of demethylation occurs, with ICR demethylation occurring late in the process. Lastly, ICRs reacquire DNA methylation imprints in developing germ cells. We describe the past discoveries and current literature defining these crucial dynamics in relation to imprinted genes and the rest of the genome.

| S-EPMC6044325 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data