Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/101583
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Type: | Journal article |
Title: | DNA methylation in human epigenomes depends on local topology of CpG sites |
Author: | Lövkvist, C. Dodd, I. Sneppen, K. Haerter, J. |
Citation: | Nucleic Acids Research, 2016; 44(11):5123-5132 |
Publisher: | Oxford University Press |
Issue Date: | 2016 |
ISSN: | 0305-1048 1362-4962 |
Statement of Responsibility: | Cecilia Lövkvist, Ian B. Dodd, Kim Sneppen and Jan O. Haerter |
Abstract: | In vertebrates, methylation of cytosine at CpG sequences is implicated in stable and heritable patterns of gene expression. The classical model for inheritance, in which individual CpG sites are independent, provides no explanation for the observed non-random patterns of methylation. We first investigate the exact topology of CpG clustering in the human genome associated to CpG islands. Then, by pooling genomic CpG clusters on the basis of short distances between CpGs within and long distances outside clusters, we show a strong dependence of methylation on the number and density of CpG organization. CpG clusters with fewer, or less densely spaced, CpGs are predominantly hyper-methylated, while larger clusters are predominantly hypo-methylated. Intermediate clusters, however, are either hyper- or hypo-methylated but are rarely found in intermediate methylation states. We develop a model for spatially-dependent collaboration between CpGs, where methylated CpGs recruit methylation enzymes that can act on CpGs over an extended local region, while unmethylated CpGs recruit demethylation enzymes that act more strongly on nearby CpGs. This model can reproduce the effects of CpG clustering on methylation and produces stable and heritable alternative methylation states of CpG clusters, thus providing a coherent model for methylation inheritance and methylation patterning. |
Keywords: | Humans Cluster Analysis Computational Biology DNA Methylation Epigenesis, Genetic CpG Islands Genome, Human Algorithms Models, Biological Epigenomics |
Rights: | © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
DOI: | 10.1093/nar/gkw124 |
Grant ID: | http://purl.org/au-research/grants/nhmrc/1025549 |
Published version: | http://dx.doi.org/10.1093/nar/gkw124 |
Appears in Collections: | Aurora harvest 3 Molecular and Biomedical Science publications |
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hdl_101583.pdf | Published version | 1.8 MB | Adobe PDF | View/Open |
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