DNA methylation profiling of the human major histocompatibility complex: a pilot study for the human epigenome project.
Autor: | Vardhman K Rakyan, Thomas Hildmann, Karen L Novik, Jörn Lewin, Jörg Tost, Antony V Cox, T Dan Andrews, Kevin L Howe, Thomas Otto, Alexander Olek, Judith Fischer, Ivo G Gut, Kurt Berlin, Stephan Beck |
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Jazyk: | angličtina |
Rok vydání: | 2004 |
Předmět: | |
Zdroj: | PLoS Biology, Vol 2, Iss 12, p e405 (2004) |
Druh dokumentu: | article |
ISSN: | 1544-9173 1545-7885 |
DOI: | 10.1371/journal.pbio.0020405 |
Popis: | The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine-guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data. |
Databáze: | Directory of Open Access Journals |
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