Project description:Genome wide methylation profiling of gliomas is likely to provide important clues to improving treatment outcomes. Restriction enzyme based approaches have been widely utilized for methylation profiling of cancer genomes and will continue to have importance in combination with higher density microarrays. With the availability of the human genome sequence and microarray probe sequences, these approaches can be readily characterized and optimized via in silico modeling. We adapted the previously described HpaII/MspI based Methylation Sensitive Restriction Enzyme (MSRE) assay for use with two-color Agilent 244K CpG island microarrays. In this assay, fragmented genomic DNA is digested in separate reactions with isoschizomeric HpaII (methylation-sensitive) and MspI (methylation-insensitive) restriction enzymes. Using in silico hybridization, we found that genomic fragmentation with BfaI was superior to MseI, providing a maximum effective coverage of 22,362 CpG islands in the human genome. In addition, we confirmed the presence of an internal control group of fragments lacking HpaII/MspI sites which enable separation of methylated and unmethylated fragments. We used this method on genomic DNA isolated from normal brain, U87MG cells, and a glioblastoma patient tumor sample and confirmed selected differentially methylated CpG islands using bisulfite sequencing. Along with additional validation points, we performed a receiver operating characteristics (ROC) analysis to determine the optimal threshold (p â¤ 0.001). Based on this threshold, we identified ~2400 CpG islands common to all three samples and 145 CpG islands unique to glioblastoma. These data provide general guidance to individuals seeking to maximize effective coverage using restriction enzyme based methylation profiling approaches. Five samples: normal human brain DNA, U87MG cell line, glioblastoma tumor, human DNA treated with SssI enzyme used as positive control, and Genomiphied human DNA used as negative control. Two technical replicates were performed on all samples except the negative control.

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 shows average methylation status in CpG islands. In general, methylation of CpG sites within a promoter causes silencing of the gene associated with that promoter For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf CpG regions were assayed via Methyl-seq, a method developed in the Myers laboratory to measure the methylation status at CpGs throughout the genome. It combines DNA digestion by a methyl-sensitive enzyme HpaII and its methyl-insensitive isoschizomer MspI with the Illumina DNA sequencing platform. The method was first applied in a collaboration with the laboratory of Dr. Julie Baker at Stanford University to study methylation and gene expression changes that occur in human embryonic stem cells before and after differentiation to definitive endoderm. A paper describing the results as well as the method has been submitted for publication [1]. This study profiled genomic DNA and mRNA samples derived from two human embryonic stem cell lines: H9 and BG02. These cells were differentiated into definitive endoderm, embryoid bodies, embryoid body-derived cells, and AFP+ (alpha-fetoprotein positive) hepatocytes. These in vitro samples were profiled with Methyl-seq and compared them with normal tissue samples from 11-week and 24-week fetal liver and adult liver. Methyl-seq assays more than 250,000 methyl-sensitive restriction enzyme cleavage sites, representing more than 90,000 genomic regions. These regions include 35,528 annotated CpG islands, while the remaining 55,084 non-CpG island regions are distributed across the genome in promoters, genes, and intergenic regions. Sequence tags present in MspI libraries but not in HpaII libraries are derived from methylated regions. Conversely, sequence tags that occur in HpaII libraries come from at least partially unmethylated regions. In vitro differentiation: Definitive endoderm precursor cells were generated from H9 hES cells by treating them with activin A. Embryoid bodies (EBs) were generated by growing undifferentitated H9 and BG02 hESCs in suspension. EB-derived cells were obtained by plating clumps of the cells from the EBs. AFP+ fetal hepatocytes were derived from EBs by plating EB cells with FgF, followed by fluorescence activated cell sorting (FACS) to isolate cells expressing the green fluorescent protein (GFP) reporter gene driven from the AFP promoter. Isolation of genomic DNA: Genomic DNA is isolated from biological replicates of each cell line by using the QIAGEN DNeasy Blood & Tissue Kit according to the instructions provided by the manufacturer. DNA concentrations and a level of quality of each preparation is determined by UV absorbance. HpaII and MspI digestions: Cleavage of DNA by restriction endonuclease HpaII is prevented by the presence of a 5-methyl group at the internal C residue of its recognition sequence CCGG. MspI, an isoschizomer of HpaII, cleaves DNA irrespective of the presence of a methyl group at this position. For the MspI library, 5 µg genomic DNA was digested in a 100 µl reaction with 1X NEB Buffer2 and 20 units MspI restriction enzyme and incubated for 18 hr at 37°C. For the HpaII library, 5 µg genomic DNA was digested in a 100 µl reaction with 1X NEB Buffer1 and 20 units HpaII restriction enzyme and incubated for 18 hr at 37°C. Note that in subsequent versions of the Methyl-seq protocol, which will be described later, much lower amounts of genomic DNA were used (1 µg and potentially lower). DNA library construction and sequencing: High-throughput sequencing libraries were generated from DNA fragments of the HpaII or MspI digested genomic DNA according to the protocol posted at the website: http://myers.hudsonalpha.org/content/protocols.html. This approach was recently modified by removing the first PCR amplification step, just prior to the gel electrophoresis size-selection step, which was found to reduce a fragment-size bias in the sequencing libraries. These libraries were sequenced with an Illumina Genome Analyzer (GA2) according to the manufacturer's recommendations. Data analysis: For this analyis, reads that align to human genome sequence version hg19 and contain the 5'-CGG-3' HpaII-cut signature on their 5' end were used. These aligned sequence reads were mapped to CCGG sites predicted in silico on hg19. Sites with four or more Msp1 tags occurring in either the forward or reverse direction were retained for analysis. These "assayable" sites were then grouped with neighboring sites that are within 35-75 bp of each other. Thus, a "region" can be comprised of between 2 and 18 digestion sites that are each within 35-75 bp of another site. Methylated and non-methylated calls were made by using HpaII tag data from all assayable cut sites. For each site across each region, the larger of either the forward read count or reverse read count was used. Regions that have an average of 0 or 1 read per cut site are called methylated, and regions with more than one sequence read per site are called unmethylated.

Project description:5-hydroxymethylcytosine (5-hmC), a derivative of 5-methylcytosine (5-mC), is abundant in the brain for unknown reasons. We mapped the genomic distribution of 5-hmC and 5-mC in human and mouse tissues using glucosylation of 5-hmC coupled with restriction enzyme digestion, and interrogation on microarrays. We detected 5-hmC enrichment in genes with synapse-related functions in the brain. We also identified significant, tissue-specific differential distributions of these DNA modifications at the exon-intron boundary, in both human and mouse. This boundary change was mainly due to 5-hmC in the brain, but due to 5-mC in non-neural contexts. This pattern was replicated in multiple independent datasets, and the brain-specific change in 5-hmC was validated using single-molecule sequencing. Moreover, in the brain, constitutive exons contained higher levels of 5-hmC, relative to alternatively-spliced exons. Our study suggests a novel role for 5-hmC in RNA splicing and synaptic function in the brain The M-NM-2-glucosyltransferase (BGT) enzyme transfers a glucose molecule specifically to the hydroxymethyl group of 5-hmC, thus rendering it resistant to digestion by the methylation insensitive MspI enzyme at the ChmCGG target site; 5-hmC is thus detected by differential resistance to MspI-digestion with and without glucosylation of genomic DNA (gDNA). HpaII (targets the same site, CCGG) cannot cut CmCGG or ChmCGG, and conceptually its difference with MspI digestion is a measure of both 5-mC and 5-hmC. Subtraction of 5-hmC from the HpaII-based estimate therefore measures 5-mC. These estimates were measured on respective Affymetrix whole-genome tiling arrays (2.0 R ) MspI - APRIL_fc1.ch02_coverage.bed Undigested DNA - APRIL_fc1.ch01_coverage.bed GluMspI - APRIL_fc1.ch04_coverage_NONTARGET.bed GluMspI - APRIL_fc1.ch04_coverage.bed MspI - APRIL_fc1.ch02_coverage_NONTARGET.bed Undigested DNA - APRIL_fc1.ch01_coverage_NONTARGET.bed MspI - MARCH_fc1.ch02_coverage_NONTARGET.bed Undigested DNA - MARCH_fc1.ch01_coverage_NONTARGET.bed GluMspI - MARCH_fc1.ch04_coverage_NONTARGET.bed GluMspI - MARCH_fc1.ch04_coverage.bed MspI - MARCH_fc1.ch02_coverage.bed Undigested DNA - MARCH_fc1.ch01_coverage.bed MspI - MAY_fc1.ch02_coverage.bed GluMspI - MAY_fc1.ch04_coverage_NONTARGET.bed GluMspI - MAY_fc1.ch04_coverage.bed Undigested DNA - MAY_fc1.ch01_coverage.bed MspI - MAY_fc1.ch02_coverage_NONTARGET.bed Undigested DNA - MAY_fc1.ch01_coverage_NONTARGET.bed

Project description:DNA methylation in CpG context is fundamental to the epigenetic regulation of gene expression in high eukaryotes. Disorganization of methylation status is implicated in many diseases, cellular differentiation, imprinting, and other biological processes. Techniques that enrich for biologically relevant CpG-rich genomic regions are desired since, depending on the size of an oragnism's methylome, the depth of sequencing required to cover all CpGs can be prohibitively expensive. Currently, restriction-enzyme based Reduced Representation Bisulfite Sequencing and its modified protocols are widely used to study methylation differences. Recently, Agilent Technologies and Roche NimbleGen have aimed to both reduce sequencing costs and capture CpGs of known biological relevance by marketing in-solution custom-capture hybridization platforms. These three methods target approximately 10-13% of the human methylome. For each platform - restriction-enzyme based enhanced reduced representation (ERRBS), capture based Agilent SureSelect Methyl-seq (SSMethylseq), and capture based Roche NimbleGen SeqCap Epi CpGiant (CpGiant) - we used human lung fibroblast cell line IMR90 DNA to make libraries according to each protocol and sequenced to equivalent depth. Overall, SSMethylSeq and CpGiant covered >95% of their designed capture regions whereas ERRBS covered 70% of its expected MspI regions. Methylation levels were concordant across the platforms. The concordance of annotations of CpG units for genomic features, displayed roughly the same proportions of genomic features. SSMethylSeq and CpGiant are most similar and cover marginally more annotated regions than ERRBS. However, the number of CpG units shared by all methods was low, ~26% of any platform. We conclude that captured based methods are largely consistent in terms of covered CpG loci although ERRBS provides comparable data at a significantly reduced price. Furthermore, library preparation for ERRBS can be performed with as little as 75ngs of starting material, whereas micrograms are needed for the capture hybridization techniques. Libraries were made from human lung fibroblast cell line IMR90 DNA for each protocol of ERRBS, Agilent SureSelect Methyl-seq, Roche NimbleGen SeqCap Epi CpGiant, and WGBS, then sequenced as paired-end 100bp on an Illumina HiSeq 2500.

Project description:DNA methylation in CpG context is fundamental to the epigenetic regulation of gene expression in high eukaryotes. Disorganization of methylation status is implicated in many diseases, cellular differentiation, imprinting, and other biological processes. Techniques that enrich for biologically relevant CpG-rich genomic regions are desired since, depending on the size of an oragnism's methylome, the depth of sequencing required to cover all CpGs can be prohibitively expensive. Currently, restriction-enzyme based Reduced Representation Bisulfite Sequencing and its modified protocols are widely used to study methylation differences. Recently, Agilent Technologies and Roche NimbleGen have aimed to both reduce sequencing costs and capture CpGs of known biological relevance by marketing in-solution custom-capture hybridization platforms. These three methods target approximately 10-13% of the human methylome. For each platform - restriction-enzyme based enhanced reduced representation (ERRBS), capture based Agilent SureSelect Methyl-seq (SSMethylseq), and capture based Roche NimbleGen SeqCap Epi CpGiant (CpGiant) - we used human lung fibroblast cell line IMR90 DNA to make libraries according to each protocol and sequenced to equivalent depth. Overall, SSMethylSeq and CpGiant covered >95% of their designed capture regions whereas ERRBS covered 70% of its expected MspI regions. Methylation levels were concordant across the platforms. The concordance of annotations of CpG units for genomic features, displayed roughly the same proportions of genomic features. SSMethylSeq and CpGiant are most similar and cover marginally more annotated regions than ERRBS. However, the number of CpG units shared by all methods was low, ~26% of any platform. We conclude that captured based methods are largely consistent in terms of covered CpG loci although ERRBS provides comparable data at a significantly reduced price. Furthermore, library preparation for ERRBS can be performed with as little as 75ngs of starting material, whereas micrograms are needed for the capture hybridization techniques.

Dataset Information

In silico enhanced restriction enzyme based methylation analysis of the human glioblastoma genome

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets