Genome-wide profiling of DNA methylation at single-base resolution based on MeDIP-bisulfite high-throughput sequencing and ridge regression
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ABSTRACT:
PROVIDER: PRJNA263640 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1610760_1.fastq.gz | Fastqsanger.gz | |||
| SRR1610760_2.fastq.gz | Fastqsanger.gz | |||
| SRR1610761_1.fastq.gz | Fastqsanger.gz | |||
| SRR1610761_2.fastq.gz | Fastqsanger.gz | |||
| SRR1610762_1.fastq.gz | Fastqsanger.gz |
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Project description:Unraveling complexity of DNA methylome is essential to decipher DNA methylation mechanism in life. However, this has been subjected to technological constraints to balance between cost and accurate measurement of the DNA methylation level. In this study, by innovatively introducing C-hydroxylmethylated adapters, we have developed MeDIP-Bisulfite sequencing (MB-seq), which could obtain DNA methylome of repertoire CpGs at single-base resolution. We found MB-seq only costs 10% of MethylC-seq, but covers 85% of total CpGs in human genome. Unlike absolute methylation levels determined by MethylC-seq and RRBS, MB-seq presented relative methylation levels that are linearly inflated. This has enlightened us to develop a MB-seq corresponding correction method for methylation level based on ridge regression, which integrates the data of MB-seq and RRBS to predict the methylation level of total 28.2 million CpGs on human genome with high accuracy (Pearson correlation coefficient, PCC=0.90). Moreover, by employing MB-seq, we generated the DNA methylome of an ovarian epithelial cell line (T29) and its oncogenic counterpart (T29H), respectively. After ridge regression, we identified 131,790 differential methylation regions (DMRs) with high accuracy between T29 and T29H, far more than 7,567 obtained from RRBS. Taken together, our result demonstrated that the MB-seq combined with ridge regression is a wide applicable approach for profiling of DNA methylome.
2015-10-01 | GSE62277 | GEO
Project description:Unraveling complexity of DNA methylome is essential to decipher DNA methylation mechanism in life. However, this has been subjected to technological constraints to balance between cost and accurate measurement of the DNA methylation level. In this study, by innovatively introducing C-hydroxylmethylated adapters, we have developed MeDIP-Bisulfite sequencing (MB-seq), which could obtain DNA methylome of repertoire CpGs at single-base resolution. We found MB-seq only costs 10% of MethylC-seq, but covers 85% of total CpGs in human genome. Unlike absolute methylation levels determined by MethylC-seq and RRBS, MB-seq presented relative methylation levels that are linearly inflated. This has enlightened us to develop a MB-seq corresponding correction method for methylation level based on ridge regression, which integrates the data of MB-seq and RRBS to predict the methylation level of total 28.2 million CpGs on human genome with high accuracy (Pearson correlation coefficient, PCC=0.90). Moreover, by employing MB-seq, we generated the DNA methylome of an ovarian epithelial cell line (T29) and its oncogenic counterpart (T29H), respectively. After ridge regression, we identified 131,790 differential methylation regions (DMRs) with high accuracy between T29 and T29H, far more than 7,567 obtained from RRBS. Taken together, our result demonstrated that the MB-seq combined with ridge regression is a wide applicable approach for profiling of DNA methylome.
2015-10-01 | GSE62279 | GEO
Project description:Unraveling complexity of DNA methylome is essential to decipher DNA methylation mechanism in life. However, this has been subjected to technological constraints to balance between cost and accurate measurement of the DNA methylation level. In this study, by innovatively introducing C-hydroxylmethylated adapters, we have developed MeDIP-Bisulfite sequencing (MB-seq), which could obtain DNA methylome of repertoire CpGs at single-base resolution. We found MB-seq only costs 10% of MethylC-seq, but covers 85% of total CpGs in human genome. Unlike absolute methylation levels determined by MethylC-seq and RRBS, MB-seq presented relative methylation levels that are linearly inflated. This has enlightened us to develop a MB-seq corresponding correction method for methylation level based on ridge regression, which integrates the data of MB-seq and RRBS to predict the methylation level of total 28.2 million CpGs on human genome with high accuracy (Pearson correlation coefficient, PCC=0.90). Moreover, by employing MB-seq, we generated the DNA methylome of an ovarian epithelial cell line (T29) and its oncogenic counterpart (T29H), respectively. After ridge regression, we identified 131,790 differential methylation regions (DMRs) with high accuracy between T29 and T29H, far more than 7,567 obtained from RRBS. Taken together, our result demonstrated that the MB-seq combined with ridge regression is a wide applicable approach for profiling of DNA methylome.
2015-10-01 | GSE62276 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2015-10-01 | GSE62280 | GEO
Project description:In this study, we have developed MB-seq, a novel DNA methylome profiling technology combining MeDIP-seq with bisulfite conversion, which can precisely detect the 5mC sites and determine their DNA methylation level at single-base resolution in a cost-effective way. In addition, we have developed a new alternative method, MRB-seq (MeDIP-repetitive elements removal-bisulfite sequencing), which interrogates 5mCs in functional regions by depleting nearly half of repeat fragments enriched by MeDIP. Comparing MB-seq and MRB-seq to whole-genome BS-seq using the same batch of DNA from YH peripheral blood mononuclear cells. We found that the sequencing data of MB-seq and MRB-seq almost reaches saturation after generating 7-8 Gbp data, whereas BS-seq requires about 100 Gbp data to achieve the same effect. In comparison to MeDIP-seq and BS-seq, MB-seq offers several key advantages, including single-base resolution, discriminating the methylated sites within a CpG and non-CpG pattern and overcoming the false positive of MeDIP-seq due to the non-specific binding of 5-methylcytidine antibody to genomic fragments.
2017-08-17 | GSE94071 | GEO
Project description:Non-canonical base modifications of bacterial origin in a eukaryotic genome [MeDIP-seq]
| PRJNA588094 | ENA
Project description:Methylation of cytosines at the 5th carbon position of the aromatic ring has long been regarded as the predominant type of DNA base modification in eukaryotes. Often called “the fifth base”, C5-methylcytosine (5mC) plays an important role in genome defense against mobile genetic elements, and is mostly associated with transcriptional silencing, establishment of the closed chromatin configuration, and repressive histone modifications. Recently, another type of DNA modification, N6-methyladenine (6mA), has been added to the repertoire of modified bases in eukaryotic DNA, and was mostly linked to elevated transcription levels. In prokaryotes, 5mC and 6mA typically constitute components of restriction-modification (R-M) systems, along with N4-methylcytosine (4mC), which so far has been confined to bacteria. Here we report the first case of 4mC occurrence in eukaryotic DNA. We find that bdelloid rotifers, small freshwater invertebrates known for their ability to reproduce clonally and to acquire genes from non-metazoan sources, lack the canonical eukaryotic C5-methyltransferases but instead encode an amino-methyltransferase of bacterial origin, N4CMT, which is present in all bdelloid families separated by tens of millions of years of evolution. The recombinant N4CMT introduces 4mC into genomic DNA in vivo and in vitro. Using SMRT-seq (PRJNA558051), MeDIP-seq, ChIP-seq, and RNA-seq, we examined genome-wide distribution of non-canonical base modifications over annotated genomic features and observed an excess of 4mC in silenced transposable elements and certain tandem repeats, while 6mA tends to associate with transcribed genes and active chromatin. The presence of the chromodomain in N4CMT explains its affinity for repressive histone marks, H3K9me3 and especially H3K27me3. Our results expand the known repertoire of eukaryotic base modifications, shed light on the process of recruitment of methyl groups as epigenetic marks in DNA, and highlight the role of horizontal gene transfer as an important driver of evolutionary innovation in eukaryotes.
2022-01-07 | GSE140050 | GEO
Project description:Gas hydrates, also known as clathrates, are cages of ice-like water crystals encasing gas molecules such as methane (CH4). Despite the global importance of gas hydrates, their microbiomes remain mysterious. Microbial cells are physically associated with hydrates, and the taxonomy of these hydrate-associated microbiomes is distinct from non-hydrate-bearing sites. Global 16S rRNA gene surveys show that members of sub-clade JS-1 of the uncultivated bacterial candidate phylum Atribacteria are the dominant taxa in gas hydrates. The Atribacteria phylogeny is highly diverse, suggesting the potential for wide functional variation and niche specialization. Here, we examined the distribution, phylogeny, and metabolic potential of uncultivated Atribacteria in cold, salty, and high-pressure sediments beneath Hydrate Ridge, off the coast of Oregon, USA, using a combination of 16S rRNA gene amplicon, metagenomic, and metaproteomic analysis. Methods were developed to extract bacterial cellular protein from these sediments, as outlined below. Sample Description Three sediments samples were collected from beneath Hydrate Ridge, off the coast of Oregon, USA. Sediments were cored at ODP site 1244 (44°35.1784´N; 125°7.1902´W; 895 m water depth) on the eastern flank of Hydrate Ridge ~3 km northeast of the southern summit on ODP Leg 204 in 2002 and stored at -80°C at the IODP Gulf Coast Repository. E10H5 sediment is from 68.5 meters below sediment surface interface C1H2 sediment is from 2 meters below sediment surface interface. C3H4 sediment is from 21 meters below sediment surface interface.
2020-01-22 | PXD012479 | Pride
Project description: Not available
| S-EPMC7702219 | biostudies-literature
Project description:Genome-wide profiling of DNA methylation at single-base resolution based on MeDIP-bisulfite high-throughput sequencing and ridge regression (MethyC + MeDIP)
| PRJNA263639 | ENA