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    CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure

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    Author
    Bock, C; Paulsen, M; Tierling, S; Mikeska, T; Lengauer, T; Walter, J
    Date
    2006-03-01
    Source Title
    PLoS Genetics
    Publisher
    PUBLIC LIBRARY SCIENCE
    University of Melbourne Author/s
    Mikeska, Thomas
    Affiliation
    Clinical Pathology
    Metadata
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    Document Type
    Journal Article
    Citations
    Bock, C., Paulsen, M., Tierling, S., Mikeska, T., Lengauer, T. & Walter, J. (2006). CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure. PLOS GENETICS, 2 (3), pp.243-252. https://doi.org/10.1371/journal.pgen.0020026.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/256299
    DOI
    10.1371/journal.pgen.0020026
    Abstract
    CpG island methylation plays an important role in epigenetic gene control during mammalian development and is frequently altered in disease situations such as cancer. The majority of CpG islands is normally unmethylated, but a sizeable fraction is prone to become methylated in various cell types and pathological situations. The goal of this study is to show that a computational epigenetics approach can discriminate between CpG islands that are prone to methylation from those that remain unmethylated. We develop a bioinformatics scoring and prediction method on the basis of a set of 1,184 DNA attributes, which refer to sequence, repeats, predicted structure, CpG islands, genes, predicted binding sites, conservation, and single nucleotide polymorphisms. These attributes are scored on 132 CpG islands across the entire human Chromosome 21, whose methylation status was previously established for normal human lymphocytes. Our results show that three groups of DNA attributes, namely certain sequence patterns, specific DNA repeats, and a particular DNA structure, are each highly correlated with CpG island methylation (correlation coefficients of 0.64, 0.66, and 0.49, respectively). We predicted, and subsequently experimentally examined 12 CpG islands from human Chromosome 21 with unknown methylation patterns and found more than 90% of our predictions to be correct. In addition, we applied our prediction method to analyzing Human Epigenome Project methylation data on human Chromosome 6 and again observed high prediction accuracy. In summary, our results suggest that DNA composition of CpG islands (sequence, repeats, and structure) plays a significant role in predisposing CpG islands for DNA methylation. This finding may have a strong impact on our understanding of changes in CpG island methylation in development and disease.

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