DNA methylation estimation using methylation-sensitive restriction enzyme bisulfite sequencing (MREBS)
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ABSTRACT:
PROVIDER: PRJNA509235 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8310180.fastq.gz | Fastqsanger.gz | |||
| SRR8310181.fastq.gz | Fastqsanger.gz | |||
| SRR8310182.fastq.gz | Fastqsanger.gz | |||
| SRR8310183.fastq.gz | Fastqsanger.gz | |||
| SRR8310176.fastq.gz | Fastqsanger.gz |
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Project description:We introduce methylation-sensitive restriction enzyme bisulfite sequencing (MREBS) which has the reduced sequencing requirements of RRBS, but significantly expands the coverage of CpG sites in the genome. Here, we compare MREBS to WGBS and RRBS.
2018-12-11 | GSE123566 | GEO
Project description:Whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) are widely used for measuring DNA methylation levels on a genome-wide scale. Both methods have limitations: WGBS is expensive and prohibitive for most large-scale projects; RRBS only interrogates 6-12% of the CpGs in the human genome. Here, we introduce methylation-sensitive restriction enzyme bisulfite sequencing (MREBS) which has the reduced sequencing requirements of RRBS, but significantly expands the coverage of CpG sites in the genome. We built a multiple regression model that combines the two features of MREBS: the bisulfite conversion ratios of single cytosines (as in WGBS and RRBS) as well as the number of reads that cover each locus (as in MRE-seq). This combined approach allowed us to estimate differential methylation across 60% of the genome using read count data alone, and where counts were sufficiently high in both samples (about 1.5% of the genome), our estimates were significantly improved by the single CpG conversion information. We show that differential DNA methylation values based on MREBS data correlate well with those based on WGBS and RRBS. This newly developed technique combines the sequencing cost of RRBS and DNA methylation estimates on a portion of the genome similar to WGBS, making it ideal for large-scale projects of mammalian genomes.
| S-EPMC6448829 | biostudies-literature
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: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 ⤠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.
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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 ≤ 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.
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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.
2017-02-08 | GSE78103 | GEO
Project description:Single-cell multi-omics are powerful means to study cell-to-cell heterogeneity. Here, we present a single-tube, bisulfite-free method for the simultaneous, genome-wide analysis of DNA methylation and genetic variants in single cells: epigenomics and genomics of single cells analyzed by restriction (epi-gSCAR). By applying this method, we obtained DNA methylation measurements of up to 506,063 CpGs and up to 1,244,188 single-nucleotide variants from single leukemia-derived cells. We demonstrate that epi-gSCAR generates accurate and reproducible measurements of DNA methylation and allows to differentiate between two cell lines based on the DNA methylation and genetic profiles.
2020-10-28 | GSE131723 | GEO
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.
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Project description:To interrogate single-base resolution 6mA sites in the genome-wide, we develop DA-6mA-seq (DpnI-Assisted N6-methylAdenine sequencing), an optimized sequencing method taking advantage of restriction enzyme DpnI, which exclusively cleaves methylated adenine sites. We find DpnI also recognizes other sequence motifs besides the canonical GATC restriction sites, largely expanding the application range of this method. DA-6mA-seq requires less starting material and lower sequencing depth than previous methods, but achieves higher sensitivity, providing a good strategy to identify 6mA in large genome with a low abundance of 6mA. We rebuild the 6mA maps of Chlamydomonas by DA-6mA-seq and then apply this method to another two eukaryotic organisms, Plasmodium and Penicillium. Further analysis reveals most 6mA sites are symmetric at various sequence contexts, suggesting 6mA may function as a new heritable epigenetic mark in eukaryotes. A new sequencing method is developed to detect 6mA in eukaryotes
2016-04-12 | E-GEOD-74430 | biostudies-arrayexpress
Project description:To interrogate single-base resolution 6mA sites in the genome-wide, we develop DA-6mA-seq (DpnI-Assisted N6-methylAdenine sequencing), an optimized sequencing method taking advantage of restriction enzyme DpnI, which exclusively cleaves methylated adenine sites. We find DpnI also recognizes other sequence motifs besides the canonical GATC restriction sites, largely expanding the application range of this method. DA-6mA-seq requires less starting material and lower sequencing depth than previous methods, but achieves higher sensitivity, providing a good strategy to identify 6mA in large genome with a low abundance of 6mA. We rebuild the 6mA maps of Chlamydomonas by DA-6mA-seq and then apply this method to another two eukaryotic organisms, Plasmodium and Penicillium. Further analysis reveals most 6mA sites are symmetric at various sequence contexts, suggesting 6mA may function as a new heritable epigenetic mark in eukaryotes.
2016-04-12 | GSE74430 | GEO