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Large conserved domains of low DNA methylation maintained by 5-hydroxymethycytosine and Dnmt3a [Bisulfite-Seq]

ABSTRACT: Gains and losses in DNA methylation are prominent genomic features of all mammalian cell types. To gain insight into mechanisms that could promote shifts in DNA methylation patterns and thus contribute to cell fate, including malignant transformation, we performed genome-wide mapping of 5-methylcytosine in purified wild type and Dnmt3a conditional knockout hematopoietic stem cells (HSCs). We generated 1,121 million (control HSCs), and 1,213 million (Dnmt3a knockout HSCs) raw reads; about 81.4% and 88.7%, respectively, were successfully aligned to either strand of the reference genome (mm9), obtainig an average CG coverage of 39.5-fold (wild type) and 47.0-fold (Dnmt3a kockout).

ORGANISM(S): Mus musculus

PROVIDER: GSE49714 | GEO | 2013/11/17

SECONDARY ACCESSION(S): PRJNA214817

REPOSITORIES: GEO

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Large conserved domains of low DNA methylation maintained by 5-hydroxymethycytosine and Dnmt3a [Bisulfite-Seq]

Project description:Gains and losses in DNA methylation are prominent genomic features of all mammalian cell types. To gain insight into mechanisms that could promote shifts in DNA methylation patterns and thus contribute to cell fate, including malignant transformation, we performed genome-wide mapping of 5-methylcytosine in purified wild type and Dnmt3a conditional knockout hematopoietic stem cells (HSCs). We generated 1,121 million (control HSCs), and 1,213 million (Dnmt3a knockout HSCs) raw reads; about 81.4% and 88.7%, respectively, were successfully aligned to either strand of the reference genome (mm9), obtainig an average CG coverage of 39.5-fold (wild type) and 47.0-fold (Dnmt3a kockout). Whole genome bisulfite sequencing of secondarily-transplanted wild-type and Dnmt3a conditional knockout hematopoietic stem cells using Illumina HiSeq 2000

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Global methylation alterations in Dnmt3aKO derived malignancies

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Project description:We investigated DNA methylation alterations in Dnmt3aKO-Idh2 mutant HSPCs in comparison with the megarkaryocyte erythroid progenitor (MEP) and Granulocyte Macrophage Progenitor(GMP) of Dnmt3a knockout, Idh2 mutant, WT genotypes. We generated an average of 17.42 million reads per sample (12.17 - 24.53 million) of which an average of 16.39 million could be mapped to the mm9 genome (11.74 - 23.73 million). We achieved an average CpG coverage depth of 27.88-fold (19.52 - 35.89-fold) and average bisulfite conversion efficiency of 99.61% (98.43 - 99.94%).

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Large conserved domains of low DNA methylation maintained by 5-hydroxymethycytosine and Dnmt3a (CMS bisulfite-seq)

Project description:Gains and losses in DNA methylation are prominent genomic features of all mammalian cell types. To gain insight into mechanisms that could promote shifts in DNA 5-hydroxymethylation (5hmc) patterns and thus contribute to cell fate, including malignant transformation, we performed genome-wide mapping of 5hmc in purified wild type and Dnmt3a conditional knockout hematopoietic stem cells (HSCs) using cytosine-5-methylenesulphonate sequencing (CMS-seq). Comparing anti-CMS pulldown to input control, we identified 107,549 and 175,682 peaks of 5hmc enrichment in control and Dnmt3a knockout HSCs, respectively. Whole genome CMS-enriched bisulfite sequencing of secondarily-transplanted wild-type and Dnmt3a conditional knockout hematopoietic stem cells using Illumina HiSeq 2000

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Large conserved domains of low DNA methylation maintained by 5-hydroxymethycytosine and Dnmt3a (CMS bisulfite-seq)

Project description:Gains and losses in DNA methylation are prominent genomic features of all mammalian cell types. To gain insight into mechanisms that could promote shifts in DNA 5-hydroxymethylation (5hmc) patterns and thus contribute to cell fate, including malignant transformation, we performed genome-wide mapping of 5hmc in purified wild type and Dnmt3a conditional knockout hematopoietic stem cells (HSCs) using cytosine-5-methylenesulphonate sequencing (CMS-seq). Comparing anti-CMS pulldown to input control, we identified 107,549 and 175,682 peaks of 5hmc enrichment in control and Dnmt3a knockout HSCs, respectively.

2014-01-22 | GSE53742 | GEO

de novo DNA Methylation Balances Hematopoietic Stem Cell Self-Renewal and Differentiation

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2011-09-30 | E-GEOD-27322 | biostudies-arrayexpress

Epigenetic and genetic changes during mouse hematopoietic stem cell aging [Bisulfite-Seq]

Project description:To investigate the global DNA methylation changes in mouse hematopoietic stem cell aging, we performed whole-genome bisulfite sequencing (WGBS). We generated 1,494 million (4mo HSCs), and 1,493 million (24mo HSCs) raw reads; about 82.6% and 84.3%, respectively, were successfully aligned to either strand of the reference genome (mm9). Of all the cytosines present in the reference genome sequence, about 93% of Cs and 99% of CGs were covered in both datasets, with an average coverage of 46-fold (4mo) and 50-fold (24mo). In contrast to the age-associated hypomethylation observed in studies of somatic cells, mentioned above, HSCs showed an increase of methylation with age. The average methylation level over all 16 million covered CpGs increased from 83.5% in young (4mo) HSC to 84.6% in old (24mo) HSC. We observed a total of 448,166 differentially methylated CpGs (DMCs), defined as those having a 20% or more difference in methylation ratio, of which 38.5% (172,609) were hypomethylated (hypo-DMCs) and 61.5% (275,557) were hypermethylated (hyper-DMCs) with aging. For different genomic features, a slightly greater DNA methylation ratio increase was observed for the gene body, LINEs and SINEs, while CGIs and promoters showed balanced increases and decreases. Localization analysis of DMCs indicates that DNA encoding for ribosome RNA (rDNA) is primarily a hotspot for hypo-DMCs, while promoters without CpG islands, CpG island shores and LINE repetitive elements exhibit both hypo- and hyper-DMCs. Mouse hematopoietic stem cell DNA methylation profiles of 4 month and 24 month old WT mice were generated generated by deep sequencing, in duplicate, using Illumina Hiseq 2000.

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