Dataset Information

Cell Type-Specific DNA Methylation at Intragenic CpG Islands in the Immune System (gene expression data)

ABSTRACT: Human and mouse genomes contain a similar number of CpG islands (CGIs), which are discrete CpG-rich DNA sequences associated with transcription start sites. In both species, about 50% of all CGIs are remote from annotated promoters, but nevertheless often have promoter-like features. To document the role of CGI methylation in cell differentiation, we analysed DNA methylation at a comprehensive CGI set in cells of the mouse hematopoietic lineage. Using a method that potentially detects ~33% of genomic CpGs in the methylated state (>7 million) we found that large differences in gene expression were accompanied by surprisingly few DNA methylation changes. There were, however, many DNA methylation differences between hematopoietic cells and a distantly related tissue, brain. Altered DNA methylation occurred predominantly at CGIs within gene bodies, which have the properties of cell type-restricted promoters, but infrequently at annotated gene promoters or CGI flanking sequences. Elevated intragenic CGI methylation correlated with silencing of the associated gene. Differentially methylated intragenic CGIs tended to lack H3K4me3 and associate with a transcriptionally repressive environment regardless of methylation state. Our results indicate that DNA methylation changes play a relatively minor role in the late stages of differentiation, but point to a distinct role for intragenic CGIs.

ORGANISM(S): Mus musculus

PROVIDER: GSE25578 | GEO | 2011/05/23

SECONDARY ACCESSION(S): PRJNA142413

REPOSITORIES: GEO

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Project description:<p>Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(<a href="http://www.sph.umich.edu/csg/qin/HPeak">http://www.sph.umich.edu/csg/qin/HPeak</a>). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.</p>