Chromatin and Sequence Features that Define the Fine and Gross Structure of Genomics Methylation Patterns
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE21242 | GEO | 2010/04/16
SECONDARY ACCESSION(S): PRJNA126517
REPOSITORIES: GEO
Similar Datasets
Project description:We report a new method for genome-wide methylation profiling that is able to probe methylation status in both single-copy DNA and interspersed repeats. This method, MethylMAPS, uses methylation-sensitive and -dependent enzymes to fractionate the genome according to methylation state. Methylated and unmethylated fragments are then sequenced with Next-Gen sequencing to map methylated and unmethylated CpG sites in the genome. We have used this method to determine the methylation status of >275 million CpG sites in human and mouse DNA from breast and brain tissues. We conclude that methylation is the default state of most CpG dinucleotides and that a combination of local dinucleotide frequencies, the interaction of repeated sequences, and the presence or absence of histone variants or modifications shields a population of CpG sites (most of which are in and around promoters) from DNA methyltransferases that lack intrinsic sequence specificity. Genome-wide methylation mapping in two normal human breast tissues, human brain tissue and mouse brain tissue.
2010-04-16 | E-GEOD-21242 | biostudies-arrayexpress
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Florencia Pauli mailto:fpauli@hudsonalpha.org). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track is produced as part of the ENCODE project. The track displays the methylation status of specific CpG dinucleotides in the given cell types as identified by the Illumina Infinium Human Methylation 450 Bead Array platform (http://www.illumina.com/products/methylation_450_beadchip_kits.ilmn). In general, methylation of CpG sites within a promoter causes silencing of the gene associated with that promoter. The Infinium Human Methylation 450 platform uses bisulfite treated genomic DNA to assay the methylation status of more than 450,000 CpG sites covering all designatable RefSeq genes, including promoter, 5' and 3' regions, without bias against those lacking CpG islands. Additionally, the assay includes CpG islands and shores, CpG sites outside of CpG islands, non-CpG methylated sites identified in human stem cells, differentially methylated sites identified in tumor versus normal (multiple forms of cancer) and across several tissue types, CpG islands outside of coding regions, miRNA promoter regions, and disease-associated regions identified through GWAS. Detailed information for the CpG targets is in an CSV formatted spreadsheet in the supplemental directory (http://hgdownload-test.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeHaibMethyl450/supplemental/). For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell). Genomic DNA was isolated from each cell line with the QIAGEN DNeasy Blood & Tissue Kit according to the instructions provided by the manufacturer. DNA concentrations and a level of quality of each preparation was determined by fluorescence with the Qubit Fluorometer (Invitrogen). Genomic DNA was treated with sodium bisulfite, converting unmethylated cytosines of CpG dinucleotides into uracils; methylated cytosines did not get converted. After bisulfite treatment, the methylation status of a site was assayed by single base-pair extension with a Cy3 or Cy5 labeled nucleotide on oligo-beads specific for the methylated or unmethylated state. The bisulfite conversion reaction was done using the Zymo Research EZ-96 DNA Methylation Kit (http://www.zymoresearch.com/product/ez-96-dna-methylation-kit-d5003). One step of the protocol was modified. During the incubation, a 30 second 95oC denaturing step every hour was included to increase reaction efficiency as recommended by the Illumina Infinium Human Methylation27 protocol. The bead arrays were run according to the protocol provided by Illumina (http://hgdownload-test.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeHaibMethyl450/supplemental/wgEncodeHaibMethyl450IlluminaProtocol.pdf). A beta value was calculated for each CpG target with Illumina's Bead Studio software with the Methylation Module v3.2. Beta-value = intensity value from the methylated bead type/(intensity values from the methylated + intensity value from unmethylated bead types + 100). The data was then quality-filtered using p-values. Beta values with p-value greater than 0.01 are considered to fall below the minimum intensity and threshold are displayed as "NA". Any beta value equal to or greater than 0.6 was considered fully methylated. Any beta value equal to or less than 0.2 was considered to be fully unmethylated. Beta values between 0.2 and 0.6 were considered to be partially methylated. Score in the bed files is beta value x 1000
2012-09-07 | E-GEOD-40699 | biostudies-arrayexpress
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Florencia Pauli mailto:fpauli@hudsonalpha.org). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track is produced as part of the ENCODE project. The track displays the methylation status of specific CpG dinucleotides in the given cell types as identified by the Illumina Infinium HumanMethylation27 BeadArray platform (http://www.illumina.com/pages.ilmn?ID=243). In general, methylation of CpG sites within a promoter causes silencing of the gene associated with that promoter. Detailed information for the CpG targets is in an XLS formatted spreadsheet on the Myers' lab protocols website (http://hudsonalpha.org/myers-lab/protocols). For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell). Genomic DNA was isolated from each cell line with the QIAGEN DNeasy Blood & Tissue Kit according to the instructions provided by the manufacturer. DNA concentrations and a level of quality of each preparation was determined by fluorescence with the Qubit Fluorometer (Invitrogen). The Methyl27K platform uses bisulfite treated genomic DNA to assay the methylation status of 27,578 CpG sites within more than 14,000 genes. When genomic DNA is treated with sodium bisulfite, unmethylated cytosine of CpG dinucleotides are converted into uracils; methylated cytosines do not get converted. After bisulfite treatment, the methylation status of a site is assayed by single base-pair extension with a Cy3 or Cy5 labeled nucleotide on oligo-beads specific for the methylated or unmethylated state. A beta value is calculated by Illumina's Bead Studio software for each CpG target. This value represents the intensity value from the methylated bead type divided by the sum of the intensity values from the methylated and unmethylated bead types for any given CpG target. Bisulfite conversion reaction was done using the Zymo Research EZ-96 DNA Methylation Kit (http://www.zymoresearch.com/epigenetics/dna-methylation/ez-96-dna-methylation-kit). One step of the protocol was modified. During the incubation, a 30 sec 95oC denaturing step every hour was included to increase reaction efficiency as recommended by the Illumina Infinium Human Methylation27 protocol. The bead arrays were run according to the protocol provided by Illumina (http://www.illumina.com/pagesnrn.ilmn?ID=275). The intensity data from the BeadArray was processed using Illumina's BeadStudio software with the Methylation Module v3.2. The data was then quality-filtered using p-values. Any beta value equal to or greater than 0.6 is considered fully methylated. Any beta value equal to or less than 0.2 is considered to be fully unmethylated. Beta values between 0.2 and 0.6 are considered to be partially methylated. Beta-values are quality filtered and spots that fall below the minimum intensity threshold are displayed as "NA". Score in the bed files is beta value x 1000
2012-09-07 | E-GEOD-40700 | biostudies-arrayexpress
Project description:We analyzed levels of 5-methyl cytosine nnnn CCCGGG target sites by sequential restriction digest by SmaI and XmaI enzymes, ligating Illumina adaptors to the restriction fragments and reading methylation-specific signatures at the ends of restriction fragments by paired ends Illumina high throughput sequencing. Digital restriction enzyme analysis of methylation (DREAM) was performed to determine the methylation profile of SW48 colon cancer cell line genomic DNA. Genomic DNA spiked in with unmethylated, partially methylated and fully methylated standards was sequentially cut at CCCGGG sites with the methylation-sensitive enzyme SmaI (blunt ends) and its methylation-tolerant neoschizomer XmaI (5'CCGG overhangs), creating different end sequences that represented methylation status of the CCCGGG sites. These end sequences were analyzed by Illumina high throughput sequencing. Methylation status at individual CCCGGG sites across the genome was determined by counting the methylated reads with the CCGGG signature and unmethylated reads with the GGG signature at the beginnings of the sequencing reads after alignment to the human genome.
2015-09-08 | E-GEOD-66296 | biostudies-arrayexpress
Project description:We describe an optimized microarray method for identifying genome-wide CpG island methylation called Microarray-based Methylation Assessment of Single Samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimised combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared to a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison to previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation. Keywords: Methylation genomic hybridizations.
2006-10-31 | GSE5326 | GEO
Project description:Determination of the profile of genes commonly aberrantly methylated in colorectal cancer (CRC) has substantial potential value for diagnostic and therapeutic application. However, our knowledge of the DNA methylation pattern in CRC is currently limited. Therefore, we analyzed the methylation profile of 27,578 CpG sites spanning more than 14,000 genes in CRC and in adjacent normal mucosa using beadchip array-based technology. We identified 621 CpG sites located in promoter region and CpG islands that were significantly hypermethylated in CRC compared to normal mucosa. Genes on chromosome 18 showed promoter hypermethylation most frequently. According to gene ontology analysis, the most common biologically relevant class of genes affected by methylation was the class associated with the cadherin signaling pathway. In comparison with genome-wide expression array, mRNA expression was more like to be down-regulated in the genes demonstrating promoter hypermethylation, although this was not statistically significant. We validated 10 CpG sites that were shown to be hypermethylated in the array studies (ADHFE1, BOLL, SLC6A15, ADAMTS5, TFPI2, EYA4, NPY, TWIST1, LAMA1, GAS7) and 2 CpG sites showing hypomethylaion (MAEL, SFT2D3) in CRC compared to normal mucosa using pyrosequencing. The methylation status measured by pyrosequencing was consistent with the methylation array data. In conclusion, we have shown that methylation profiling based on beadchip arrays is an effective method for screening for aberrantly methylated genes in CRC. In addition, we identified novel methylated genes that are candidate diagnostic or prognostic markers for CRC. We measured the methylation status of the 27,578 CpG sites (Human Methylation27 DNA Analysis BeadChip) in 22 pairs of CRC tissue and adjacent normal mucosa to identify genes that are commonly aberrantly methylated in CRC.
2010-06-24 | E-GEOD-17648 | biostudies-arrayexpress
Project description:Methylation of DNA at CpG dinucleotides represents one of the most important epigenetic mechanisms involved in the control of gene expression in vertebrate cells. In this report, we conducted high-throughput nucleosome reconstitution experiments on 572 KB of human DNA and 668 KB of mouse DNA that was unmethylated or methylated in order to investigate the effects of this epigenetic modification on the positioning and stability of nucleosomes. The DNA loci from both species contained the genes that encode the serum albumin family, the MYC protein, and the tumor suppressor p53. The results demonstrated that a small subset of nucleosomes positioned by nucleotide sequence was sensitive to methylation where the modification increased the affinity of these sequences for the histone octamer. The features that distinguished these nucleosomes from the bulk of the methylation-insensitive nucleosomes were an increase in the frequency of CpG dinucleotides and a unique rotational orientation of CpGs such that their minor grooves tended to face toward the histones in the nucleosome rather than away. We propose that these features serve to enhance the affinity of methylated DNA for the histone octamer and that this effect could be involved in gene regulatory mechanisms such as silencing. These methylation-sensitive nucleosomes were preferentially associated with exons as compared to introns while unmethylated CpG islands near transcription start sites became enriched in nucleosomes upon methylation. The results of this study suggest that the effects of DNA methylation on nucleosome stability in vitro can recapitulate what has been observed in the cell and provide a direct link between DNA methylation and the structure and function of chromatin. For the human data, there were 3 unmethylated nucleosome replicates, 2 methylated nucleosome replicates, an unmethylated MNase control, and an unmethylated sonicated control. For the mouse data, there were 2 unmethylated nucleosome replicates, 2 methylated nucleosome replicates, an unmethylated MNase control, a methylated MNase control, and an unmethylated sonicated control.
2013-01-28 | E-GEOD-37224 | biostudies-arrayexpress
Project description:The enhancer/promoter of the vitellogenin II (VTG) gene has been extensively studied as a model system of vertebrate transcriptional control. While deletion mutagenesis and in vivo footprinting identified the transcription factor (TF) binding sites governing its tissue specificity, DNase hypersensitivity- and DNA methylation studies revealed the epigenetic changes accompanying its hormone-dependent activation. Moreover, upon induction with estrogen (E2), the region flanking the estrogen-responsive element (ERE) was reported to undergo active DNA demethylation. We now show that although the VTG ERE is methylated in embryonic chicken liver and in LMH/2A hepatocytes, its induction by E2 was not accompanied by extensive demethylation. In contrast, E2 failed to activate a VTG enhancer/promoter-controlled luciferase reporter gene methylated by SssI. Surprisingly, this inducibility difference could be traced not to the ERE, but rather to a single CpG in an E-box (CACGTG) sequence upstream of the VTG TATA box, which is unmethylated in vivo, but methylated by SssI. We demonstrate that this E-box binds the upstream stimulating factor USF1/2. Selective methylation of the CpG within this binding site with an E-box-specific DNA methyltranferase Eco72IM was sufficient to attenuate USF1/2 binding in vitro and abolish the hormone-induced transcription of the VTG gene in the reporter system.
2020-05-27 | PXD015594 | Pride
Project description:DNA methylation profiling of cancer and control samples. The Illumina GoldenGate Methylation Cancer Panel I was used to obtain DNA methylation profiles across 1,505 CpG sites CpGs distributed across 807 genes in blood DNA specimens. DNA samples were extracted from blood specimens, bisulfite treated and subsequently used for GoldenGate Methylation Cancer Panel I Array (Illumina) according to manufacturer’s protocol together with normalization methylated, hemimethylated and unmethylated DNA controls (Qiagen).
2012-11-01 | E-GEOD-33614 | biostudies-arrayexpress
Project description:DNA methylation (mC) on CpG sites is the most common epigenetic modification. Recently methylation on non-CpG context was found to widely occur on genomic DNA. However, how non-CpG methylation influences DNA/protein interaction and regulates transcription is unknown. Using single-molecule assays, we studied the interactions of transcription factors (TFs) GR, ER and BMAL1-CLOCK with methylated or unmethylated cognate DNA binding sequences. The results demonstrated that these TFs interact with methylated DNA discriminatively. We then performed BisChIP-seq with GR and BMAL1-CLOCK in HEK-293T cells and showed that they can recognize and bind to the methylated sites within chromatin. The effects of non-CpG methylation on transcriptional regulation were validated by in vitro transcription assays with correlated RNA level, and further studied mechanistically by crystallographic analyses and molecular dynamics simulations. We conclude that the non-CpG methylation of DNA provides another general mechanism for regulating gene expression through affecting TFs binding affinity.
2016-06-22 | GSE64171 | GEO