Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

40 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Genome-wide methylation and expression analysis of two breast cancer cell lines [Methyl-MAPS]

ABSTRACT: To improve our understanding of the relationships between methylation and expression we profiled mRNA expression and single-base resolution methylation levels for two breast cancer cell lines, MCF7 and T47D. Expression was profiled using RNA-seq. Methylation was assayed using Methyl-MAPS, which uses methylation-sensitive and -dependent restriction enzyme digests followed by high-throughput sequencing to identify methylation levels at individual CpGs (Edwards et al. 2010, Genome Research). DNA Methylation was assayed for two breast cancer cell lines using Methyl-MAPS.

ORGANISM(S): Homo sapiens

SUBMITTER: Nathan VanderKraats

PROVIDER: E-GEOD-45336 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Publications

Discovering high-resolution patterns of differential DNA methylation that correlate with gene expression changes.

Vanderkraats Nathan D ND Hiken Jeffrey F JF Decker Keith F KF Edwards John R JR

Nucleic acids research 20130607 14

Methylation of the CpG-rich region (CpG island) overlapping a gene's promoter is a generally accepted mechanism for silencing expression. While recent technological advances have enabled measurement of DNA methylation and expression changes genome-wide, only modest correlations between differential methylation at gene promoters and expression have been found. We hypothesize that stronger associations are not observed because existing analysis methods oversimplify their representation of the data ...[more]

PMID: 23748561

Similar Datasets

Molecular profiling of human mammary gland links breast cancer risk to a p27+ cell population with progenitor characteristics

Project description:Gene expression, DNA and histone methylation profiles were performed on multiple cell types purified from normal human nulliparous and parous breast tissue using SAGE-seq, MSDK-seq and ChIP-seq [GSE26141]. SAGE-seq, MSDK-seq and ChIP-seq libraries were made from individual cell types and integrated to find a comprehensive view of parity associated changes.

2013-06-13 | E-GEOD-32017 | biostudies-arrayexpress

Comprehensive Long Span Paired-End-Tag Mapping Reveals Characteristic Patterns of Structural Variations in Epithelial Cancer Genomes

Project description:Somatic genome rearrangements are thought to play important roles in cancer development. We optimized a long span paired-end-tag (PET) sequencing approach using 10 Kb genomic DNA inserts to study human genome structural variations (SVs). The use of 10 Kb insert size allows the identification of breakpoints within repetitive or homology containing regions of a few Kb in size and results in a higher physical coverage compared to small insert libraries with the same sequencing effort. We have applied this approach to comprehensively characterize the SVs of 15 cancer and 2 non-cancer genomes and used a filtering approach to strongly enrich for somatic SVs in the cancer genomes. Our analyses revealed that most inversions, deletions, and insertions are germline SVs, whereas tandem duplications, unpaired inversions, inter-chromosomal translocations, and complex rearrangements are overrepresented among somatic rearrangements in cancer genomes. We demonstrate that the quantitative and connective nature of DNA-PET data is precise in delineating the genealogy of complex rearrangement events, we observe signatures which are compatible with breakage-fusion-bridge cycles, and discover that large duplications are among the initial rearrangements that trigger genome instability for extensive amplification in epithelial cancers. Structural variations of 15 human cancer samples and 2 human normal samples were identified by long span paired-end sequencing

2011-04-06 | E-GEOD-26954 | biostudies-arrayexpress

CpG context and content in evolutionary signatures of brain DNA methylation

Project description:We assayed CpG methylation in cerebral cortex of neurologically and psychiatrically normal human postmortem specimens, as well as mouse forebrain specimens. Cross-species human-mouse DNA methylation conservation analysis shows that DNA methylation is not correlated with sequence conservation. Instead, greater DNA methylation conservation is correlated with increasing CpG density. We identified key genomic features that can be targeted for identification of epigenetic loci that may be developmentally and evolutionarily conserved and wherein aberrations in DNA methylation patterns can confer risk for disease. Characterization of evolutionary signatures of DNA methylation in the brain

2011-10-04 | E-GEOD-32647 | biostudies-arrayexpress

Long Span DNA Paired-End-Tag (DNA-PET) Sequencing Strategy for the Interrogation of Genomic Structural Mutations

Project description:Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. Genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs. The current application of PET sequencing with short insert size DNA is insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We have developed a robust procedure to generate PET sequencing data using large DNA inserts of 10 - 20 kb for the identification of SVs. We compared the characteristics of the large insert libraries with short insert (1 kb) libraries with the same sequencing depths and costs. Although short insert libraries bear an advantage in identifying small deletions, they do not provide a significantly better breakpoint resolution. Large inserts are superior to short inserts in providing higher physical genome coverage and therefore achieve greater sensitivity for the identification of the different types of SVs, including copy number neutral and complex events. Further, large inserts allow the identification of SVs within repetitive sequences which cannot be spanned by short inserts. Structural variations of three cancer cell lines using short (1 kb) and long (10 kb and 20 kb) insert size DNA fragments

2012-10-04 | E-GEOD-32674 | biostudies-arrayexpress

H3K4me3 modification analysis comparing Lsh WT and Lsh-/- MEFs

Project description:DNA methylation is critical for normal development and plays important roles in genome organization and transcriptional regulation. Although DNA methyltransferases have been identified, the factors that establish and contribute to genome-wide methylation patterns remain elusive. Here, we report a high-resolution cytosine methylation map of the murine genome modulated by Lsh, a chromatin remodeling family member that has previously been shown to regulate CpG methylation at repetitive sequences. We provide evidence that Lsh also controls genome-wide cytosine methylation at nonrepeat sequences and relate those changes to alterations in H4K4me3 modification and gene expression. Deletion of Lsh alters the allocation of cytosine methylation in chromosomal regions of 50 kb to 2 Mb and, in addition, leads to changes in the methylation profile at the 5M-CM-"M-BM-^@M-BM-2 end of genes. Furthermore, we demonstrate that loss of Lsh promotesM-CM-"M-BM-^@M-BM-^Tas well as preventsM-CM-"M-BM-^@M-BM-^Tcytosine methylation. Our data indicate that Lsh is an epigenetic modulator that is critical for normal distribution of cytosine methylation throughout the murine genome. Chromatin immunoprecipitation followed by genomic sequencing was used to compare H3K4me3 modifications between wild type murine embryonal fibroblast cell lines (MEFs) and Lsh-/-MEFs.

2011-05-19 | E-GEOD-29393 | biostudies-arrayexpress

Epigenetic regulation of cell type-specific expression patterns in the human mammary epithelium [MSDK-Seq]

Project description:Here we describe the application of high-throughput sequencing technology for profiling histone and DNA methylation, and gene expression patterns of normal human mammary progenitor-enriched and luminal lineage-committed cells. We observed significant differences in histone H3 lysine 27 tri-methylation (H3K27me3) enrichment and DNA methylation of genes expressed in a cell type-specific manner, suggesting their regulation by epigenetic mechanisms and a dynamic interplay between the two processes that together define developmental potential. The technologies we developed and the epigenetically regulated genes we identified will accelerate the characterization of primary cell epigenomes and the dissection of human mammary epithelial lineage-commitment and luminal differentiation. Global profiling of differentially methylated regions in 2 cell types from 6 individuals.

2011-03-01 | E-GEOD-26139 | biostudies-arrayexpress

High-throughput sequencing of ES cell lines, ES-derived cells, and fetal and normal livers

Project description:Publication title: Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal liver To investigate the role of DNA methylation during human development, we developed Methyl-seq, a method that assays DNA methylation at more than 90,000 regions throughout the genome. Performing Methyl-seq on human embryonic stem cells (hESCs), their derivatives and human tissues allowed us to identify several trends during hESC and in vivo liver differentiation. First, differentiation results in DNA methylation changes at a minimal number of assayed regions, both in vitro and in vivo (2-11%). Second, in vitro hESC differentiation is characterized by both de novo methylation and demethylation, whereas in vivo fetal liver development is characterized predominantly by demethylation. Third, hESC differentiation is uniquely characterized by methylation changes specifically at H3K27me3-occupied regions, bivalent domains and low-density CpG promoters (LCPs) suggesting that these regions are more likely to be involved in transcriptional regulation during hESC differentiation. Although both H3K27me3-occupied domains and LCPs are also regions of high variability in DNA methylation state during human liver development, these regions become highly unmethylated, which is a distinct trend from that observed in hESCs. Taken together, our results indicate that hESC differentiation has a unique DNA methylation signature that may not be indicative of in vivo differentiation. Keywords: Methyl-seq, hESC differentiation For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf High-throughput sequencing of ES cell lines, ES-derived cells, and fetal and normal livers (17 samples). Raw data: SRA008154 http://www.ncbi.nlm.nih.gov/sites/entrez?db=sra&cmd=search&term=SRA008154

2011-05-05 | E-GEOD-29071 | biostudies-arrayexpress

Development stages of Lentinula edodes

Project description:Gene expression profiles at different development stages and different growth medium of Lentinula edodes (L54) are comparied. Keywords: time-course

2005-01-19 | E-GEOD-2167 | biostudies-arrayexpress

Genome-wide analysis of histone methylation reveals chromatin state-based regulation of host cellular gene expression induced by hepatitis B viruses

Project description:This SuperSeries is composed of the following subset Series: GSE35462: Genome-wide analysis of histone methylation reveals chromatin state-based regulation of host cellular gene expression induced by hepatitis B viruses (ChIP-Seq dataset) GSE35464: Genome-wide analysis of histone methylation reveals chromatin state-based regulation of host cellular gene expression induced by hepatitis B viruses (DGE dataset) Refer to individual Series

2012-07-31 | E-GEOD-35465 | biostudies-arrayexpress

Methylation profiling of human embryonic stems cells and developing human fetal liver reveals distinct dna methylation patterns characterize these samples

Project description:Publication title: Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal liver; To investigate the role of DNA methylation during human development, we developed Methyl-seq, a method that assays DNA methylation at more than 90,000 regions throughout the genome. Performing Methyl-seq on human embryonic stem cells (hESCs), their derivatives and human tissues allowed us to identify several trends during hESC and in vivo liver differentiation. First, differentiation results in DNA methylation changes at a minimal number of assayed regions, both in vitro and in vivo (2-11%). Second, in vitro hESC differentiation is characterized by both de novo methylation and demethylation, whereas in vivo fetal liver development is characterized predominantly by demethylation. Third, hESC differentiation is uniquely characterized by methylation changes specifically at H3K27me3-occupied regions, bivalent domains and low-density CpG promoters (LCPs) suggesting that these regions are more likely to be involved in transcriptional regulation during hESC differentiation. Although both H3K27me3-occupied domains and LCPs are also regions of high variability in DNA methylation state during human liver development, these regions become highly unmethylated, which is a distinct trend from that observed in hESCs. Taken together, our results indicate that hESC differentiation has a unique DNA methylation signature that may not be indicative of in vivo differentiation. Experiment Overall Design: lumina gene expression beadchips of human ES cell lines, ES-derived cells, and normal liver (15 samples). High-throughput sequencing of ES cell lines, ES-derived cells, and fetal and normal livers (17 samples). Raw data: SRA008154 http://www.ncbi.nlm.nih.gov/sites/entrez?db=sra&cmd=search&term=SRA008154

2009-08-29 | E-GEOD-14966 | 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