title: Identifying CpG islands by different computational techniques.
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.
authors.affiliation: Lehrstuhl für Computational Biology, Universität des Saarlandes, Saarbrücken, Germany.
authors.forename: Barbara
authors.initials: B
authors.lastname: Hutter
authors.forename: Martina
authors.initials: M
authors.lastname: Paulsen
authors.forename: Volkhard
authors.initials: V
authors.lastname: Helms
mesh_terms: D000818:Animals; D019295:Computational Biology; D018899:CpG Islands; D044127:Epigenesis, Genetic; D006801:Humans; D051379:Mice; D011401:Promoter Regions, Genetic; D012091:Repetitive Sequences, Nucleic Acid