NDLI: CpG_MI: a novel approach for identifying functional CpG islands in mammalian genomes

Content Provider	PubMed Central
Author	Su, Jianzhong Zhang, Yan Jie, Lv Liu, Hongbo Tang, Xiaoyan Wang, Fang Qi, Yunfeng Feng, Yujia Li, Xia
Copyright Year	2009
Abstract	CpG islands (CGIs) are CpG-rich regions compared to CpG-depleted bulk DNA of mammalian genomes and are generally regarded as the epigenetic regulatory regions in association with unmethylation, promoter activity and histone modifications. Accurate identification of CpG islands with epigenetic regulatory function in bulk genomes is of wide interest. Here, the common features of functional CGIs are identified using an average mutual information method to differentiate functional CGIs from the remaining CGIs. A new approach (CpG mutual information, CpG_MI) was further explored to identify functional CGIs based on the cumulative mutual information of physical distances between two neighboring CpGs. Compared to current approaches, CpG_MI achieved the highest prediction accuracy. This approach also identified new functional CGIs overlapping with gene promoter regions which were missed by other algorithms. Nearly all CGIs identified by CpG_MI overlapped with histone modification marks. CpG_MI could also be used to identify potential functional CGIs in other mammalian genomes, as the CpG dinucleotide contents and cumulative mutual information distributions are almost the same among six mammalian genomes in our analysis. It is a reliable quantitative tool for the identification of functional CGIs from bulk genomes and helps in understanding the relationships between genomic functional elements and epigenomic modifications.
Related Links	http://dx.doi.org/10.1093/nar/gkp882
Starting Page	6
File Format	PDF
ISSN	03051048
e-ISSN	13624962
Journal	Nucleic Acids Research
Issue Number	1
Volume Number	38
Language	English
Publisher	Oxford University Press
Publisher Date	2010-01-01
Access Restriction	Open
Rights Holder	Oxford University Press
Subject Keyword	Genetics Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Genetics

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