Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

48 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Genome-wide DNA methylation profiling of mouse liver

ABSTRACT: To determine whether differences between background strains or housing conditions altered the hepatic methylome, We report the generation and analysis of genome-wide DNA methylation profiles at nucleotide resolution in mouse liver from two male mice on a mixed background (mixed-1, mixed-2) and two males on a pure Black-6 (B6-1, B62) background. Using Enhanced high-throughput Reduced Representation Bisulfite Sequencing (ERRBS), we enriched CpG islands in mouse liver, and covered a representative sampling of conserved non-coding elements, transposons and other genomic features,Â for mouse liver. We found that the total CpG methylation of each methylome was strikingly similar among the 4 mouse liver samples from two different genetic backgrounds. Analysis of all CpG sites with at least 10x coverage showed a bimodal distribution of methylation, with all samples having 25% of hypermethylated CpG sites and 60% as hypomethylated CpG sites. Given the high percent of genome coverage and robust depth at single nucleotide level, these datasets provide a resource for investigation into changes in DNA methylation patterns in liver disease, tumorigenesis and regeneration. Ehanced reduced representation bisulfite sequencing (MspI 70~320bp size fraction) of liver tissue

ORGANISM(S): Mus musculus

SUBMITTER: Kirsten Edepli

PROVIDER: E-GEOD-80761 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Romidepsin and azacitidine synergize in their epigenetic modulatory effects to induce apoptosis in CTCL

Project description:We demonstrate that the combination of the HDAC inhibitor, romidepsin, and the demethylating agent, azacitidine, exerts synergistic anti-proliferative effects and induction of apoptosis involving activation of the caspase cascade in CTCL cell lines as well as CD4+ T cells derived from patients with SÃ©zary Syndrome (SS) with high tumor burden. We identified genes that were selectively induced by the combination treatment, such the tumor suppressor gene RhoB. We performed global CpG methylation-sequencing in a CTCL cell line and in patient cells. Results showed a subset of genes with a unique change in methylation profile in the combination treatment as compared to single drugs.

2016-03-30 | E-GEOD-66732 | biostudies-arrayexpress

methylSig: a whole genome DNA methylation analysis pipeline

Project description:DNA methylation plays critical roles in gene regulation and cellular specification without altering DNA sequences. The wide application of reduced representation bisulfite sequencing (RRBS) and whole genome bisulfite sequencing (bis-seq) opens the door to study DNA methylation at single CpG site resolution. One challenging question is how best to test for significant methylation differences between groups of biological samples in order to minimize false positive findings. Current methods to analyze genome-wide bisulfite sequencing data use a smoothing approach or a simple statistical test based on the binomial distribution. Comparative DNA methylation profiling in AML blasts and normal CD34(+) control cells

2014-08-22 | E-GEOD-55569 | biostudies-arrayexpress

DNA methylation status of myelinating Schwann cells during development and in diabetic neuropathy [Bisulfite-Seq]

Project description:DNA methylation is a key epigenetic regulator of mammalian embryogenesis and somatic cell differentiation. Using high-resolution genome-scale maps of methylation patterns, we show that the formation of myelin in the peripheral nervous system, proceeds with progressive DNA demethylation, which coincides with an upregulation of critical genes of the myelination process. More importantly, we found that, in addition to expression of DNA methyltransferases and demethylases, the levels of S-adenosylmethionine (SAMe), the principal biological methyl donor, could also play a critical role in regulating DNA methylation during myelination and in the pathogenesis of diabetic neuropathy. In summary, this study provides compelling evidence that SAMe levels need to be tightly controlled to prevent aberrant DNA methylation patterns, and together with recently published studies on the influence of SAMe on histone methylation in cancer and embryonic stem cell differentiation show that in diverse biological processes, the methylome, and consequently gene expression patterns, are critically dependent on levels of SAMe. DNA methylome maps of developmental Schwann cell myelination, GNMT-KO and diabetic mice were generated by Reduced-Representation Bisulfite Sequencing, with 2-3 replicates per sample group.

2014-01-27 | E-GEOD-45343 | biostudies-arrayexpress

DNA methylation status of myelinating Schwann cells during development and in diabetic neuropathy [Bisulfite-Seq2]

Project description:DNA methylation is a key epigenetic regulator of mammalian embryogenesis and somatic cell differentiation. Using high-resolution genome-scale maps of methylation patterns, we show that the formation of myelin in the peripheral nervous system, proceeds with progressive DNA demethylation, which coincides with an upregulation of critical genes of the myelination process. More importantly, we found that, in addition to expression of DNA methyltransferases and demethylases, the levels of S-adenosylmethionine (SAMe), the principal biological methyl donor, could also play a critical role in regulating DNA methylation during myelination and in the pathogenesis of diabetic neuropathy. In summary, this study provides compelling evidence that SAMe levels need to be tightly controlled to prevent aberrant DNA methylation patterns, and together with recently published studies on the influence of SAMe on histone methylation in cancer and embryonic stem cell differentiation show that in diverse biological processes, the methylome, and consequently gene expression patterns, are critically dependent on levels of SAMe. DNA methylome maps of mouse Schwann cells in which GNMT was silenced by lentiviral vectors, cultured in normal medium or low methionine medium.

2014-01-27 | E-GEOD-51031 | biostudies-arrayexpress

Genome-wide DNA methylation profiling of mouse liver

Project description:To determine whether differences between background strains or housing conditions altered the hepatic methylome, We report the generation and analysis of genome-wide DNA methylation profiles at nucleotide resolution in mouse liver from two male mice on a mixed background (mixed-1, mixed-2) and two males on a pure Black-6 (B6-1, B62) background. Using Enhanced high-throughput Reduced Representation Bisulfite Sequencing (ERRBS), we enriched CpG islands in mouse liver, and covered a representative sampling of conserved non-coding elements, transposons and other genomic features, for mouse liver. We found that the total CpG methylation of each methylome was strikingly similar among the 4 mouse liver samples from two different genetic backgrounds. Analysis of all CpG sites with at least 10x coverage showed a bimodal distribution of methylation, with all samples having 25% of hypermethylated CpG sites and 60% as hypomethylated CpG sites. Given the high percent of genome coverage and robust depth at single nucleotide level, these datasets provide a resource for investigation into changes in DNA methylation patterns in liver disease, tumorigenesis and regeneration.

2016-06-13 | GSE80761 | GEO

ProMetheus: a database of hmSILAC-validated protein methylation sites

Project description:Protein arginine (R) methylation is a post-translational modification that has been shown to play a role in various biological processes, such as RNA splicing, DNA repair, immune response, signal transduction and tumor development. Here, we present a dataset of high-quality methylations obtained from several different heavy methyl SILAC (hmSILAC) experiments analyzed with a machine learning model that was trained to recognize hmSILAC doublets and show that this model allows for improved high-confidence identification of methyl-peptides. The results of our analysis of the interactions between R-methylated proteins further support the idea that this modification plays a role in modulating protein:protein interactions and suggest a potential new role of R methylation in immunity and macrophage metabolism. Moreover, we intersect the methyl-site dataset with a phosphosite dataset to investigate the cross-talk between R methylation and phosphorylation. Finally, we explore the application of hmSILAC to identify unconventional methylated residues on both histone and non-histone proteins.

2022-06-02 | PXD027949 | Pride

Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in Acute Myeloid Leukemia

Project description:Here we used Illumina NGS for high-throughput profiling of the DNA methylome in two human colon cancer derived cell lines, two human normal bone marrow CD34+ controls and in five human Acutre Myeloid Leukeima patient samples. These data can be used to determine the CpG cytosine methylation pattern at base pair resolution in each sample and to determine differentially methylated cytosines and regions between samples Reduced Representation Bisulfite Sequencing (RRBS) and Extended Reduced Representation Bisulfite Sequencing (ERRBS) on genomic DNA. We used colon cancer cell lines (two) to establish reproducbility and range of assay sensitivity. We used Acute Myeloid Leukemia patient samples and CD34+ bone marrow cells as controls to determine the methylome pattern in the patient samples

2012-06-01 | E-GEOD-37454 | biostudies-arrayexpress

Fundamental differences in promoter CpG island DNA hypermethylation between human cancer and genetically engineered mouse models of cancer [RRBS]

Project description:Genetic and epigenetic alterations are essential for the initiation and progression of human cancer. We previously reported that primary human medulloblastomas showed extensive cancer-specific CpG island DNA hypermethylation in critical developmental pathways. To determine whether genetically engineered mouse models (GEMMs) of medulloblastoma have comparable epigenetic changes, we assessed genome-wide DNA methylation in three mouse models of medulloblastoma. In contrast to human samples, very few loci with cancer-specific DNA hypermethylation were detected, and in almost all cases the degree of methylation was relatively modest compared to the dense hypermethylation in the human cancers. To determine if this finding was common to other GEMMs, we examined a Burkitt lymphoma and breast cancer model and did not detect promoter CpG island DNA hypermethylation, suggesting that human cancers and at least some GEMMs are fundamentally different with respect to this epigenetic modification. These findings provide an opportunity to both better understand the mechanism of aberrant DNA methylation in human cancer and construct better GEMMs to serve as preclinical platforms for therapy development. Examination of DNA methylation in one representative human medulloblastoma patient sample and three different mouse models of medulloblastoma using RRBS

2013-10-10 | E-GEOD-45341 | biostudies-arrayexpress

Naive Pluripotent Stem Cells Display Transcriptional and Epigenetic Signatures of the Human Pre-Implantation Embryo

Project description:Significant interest has been devoted to the isolation of human pluripotent stem cells displaying the naive state of mouse embryonic stem cells. However, to what extent naive human cells isolated in culture resemble pluripotent cells in vivo remains unclear. Here we present three lines of evidence indicating that naive pluripotent stem cells generated in the absence of transgenes share defining molecular signatures with the human pre-implantation embryo. First, a comprehensive analysis of the transposcriptome reveals that naive human cells have a retroelement expression profile of human cleavage stage embryos. Second, base-resolution mapping of the DNA methylome in naive human cells reveals a genome-wide reduction in CpG and non-CpG methylation levels. Third, female naive cells exhibit an X chromosome status that is similar to that of the human blastocyst. Our work demonstrates that pluripotent stem cells with epigenomic hallmarks of the early human embryo can be directly captured in vitro. Examine the methylomes of 6 naÃ¯ve, 2 primed and 2 re-primed human embryonic stem cells

2016-07-18 | E-GEOD-75868 | biostudies-arrayexpress

Comparative methylomics reveals gene-body H3K36me3 in Drosophila predicts DNA methylation and CpG landscapes in other invertebrates

Project description:Here, we demonstrate that Nematostella vectensis, Ciona intestinalis, Apis mellifera, and B. mori, show two distinct populations of genes differentiated by gene-body CpG density. Genome-scale DNA methylation profiles for A. mellifera spermatozoa reveal CpG-poor genes are methylated in the germ line, as predicted by the depletion of CpGs. We find an evolutionarily conserved distinction between CpG-poor and -rich genes: the former are associated with basic biological processes, the latter with more specialized functions. This distinction is strikingly similar to that recently observed between euchromatin-associated genes in Drosophila that contain intragenic histone 3 lysine 36 trimethylation (H3K36me3) and those that do not, even though Drosophila doesnM-CM-"M-BM-^@M-BM-^Yt display CpG density bimodality or methylation. We confirm that a significant number of CpG-poor genes in N. vectensis, C. intestinalis, A. mellifera and B. mori are orthologs of H3K36me3- rich genes in Drosophila. We propose that over evolutionary time, gene-body H3K36me3 has influenced gene-body DNA methylation levels, and consequently the gene-body CpG density bimodality characteristic of invertebrates that harbor CpG methylation. Examination of DNA methylation in Apis Mellifera sperm

2011-06-16 | E-GEOD-29982 | biostudies-arrayexpress

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