Literature DB >> 19196100

Identifying CpG islands by different computational techniques.

Barbara Hutter1, Martina Paulsen, Volkhard Helms.   

Abstract

CpG islands (CGIs) are generally regarded as important epigenetic regulatory elements due to their association with promoter regions. However, identification of functional CGIs is hampered by repetitive elements and species-specific particularities. Here, we compared the performance of different CGI detection programs on genomic sequences of human and mouse genes. Although mouse CGIs are shorter and G+C poorer than their human counterparts, the different tools tested in our study reliably identify CGIs in promoter regions in both species. Our study confirms that substantially fewer murine than human CGIs coincide with repetitive elements and indicates that such CGIs are subject to accelerated cytosine deamination. In addition, CpG depletion appears to anticorrelate with the epigenetic features of functional regulatory CGIs. Taking into account different deamination rates in unmethylated CGIs versus those in methylated CGIs might support the detection of functional CGIs in other species for which there is little epigenetic information available.

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Year:  2009        PMID: 19196100     DOI: 10.1089/omi.2008.0046

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  3 in total

1.  Computer aided selection of candidate vaccine antigens.

Authors:  Darren R Flower; Isabel K Macdonald; Kamna Ramakrishnan; Matthew N Davies; Irini A Doytchinova
Journal:  Immunome Res       Date:  2010-11-03

2.  Imprinted genes show unique patterns of sequence conservation.

Authors:  Barbara Hutter; Matthias Bieg; Volkhard Helms; Martina Paulsen
Journal:  BMC Genomics       Date:  2010-11-22       Impact factor: 3.969

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

Authors:  Jianzhong Su; Yan Zhang; Jie Lv; Hongbo Liu; Xiaoyan Tang; Fang Wang; Yunfeng Qi; Yujia Feng; Xia Li
Journal:  Nucleic Acids Res       Date:  2009-10-23       Impact factor: 16.971

  3 in total

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