Hindawi Publishing Corporation BioMed Research International Volume 2013, Article ID 709042, 6 pages http://dx.doi.org/10.1155/2013/709042 Research Article CpGislandEVO: A Database and Genome Browser for Comparative Evolutionary Genomics of CpG Islands Guillermo Barturen, 1,2 Stefanie Geisen, 1,2 Francisco Dios, 1,2 E. J. Maarten Hamberg, 1,2 Michael Hackenberg, 1,2 and José L. Oliver 1,2 1 Departamento de Gen´ etica, Facultad de Ciencias, Universidad de Granada, 18071 Granada, Spain 2 Laborat´ orio de Bioinform´ atica, Instituto de Biotecnolog´ ıa, Centro de Investigaci´ on Biom´ edica, 18100 Granada, Spain Correspondence should be addressed to Jos´ e L. Oliver; oliver@ugr.es Received 20 April 2013; Revised 12 July 2013; Accepted 19 August 2013 Academic Editor: Stephan Koblm¨ uller Copyright © 2013 Guillermo Barturen et al. his is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Hypomethylated, CpG-rich DNA segments (CpG islands, CGIs) are epigenome markers involved in key biological processes. Aberrant methylation is implicated in the appearance of several disorders as cancer, immunodeiciency, or centromere instability. Furthermore, methylation diferences at promoter regions between human and chimpanzee strongly associate with genes involved in neurological/psychological disorders and cancers. herefore, the evolutionary comparative analyses of CGIs can provide insights on the functional role of these epigenome markers in both health and disease. Given the lack of speciic tools, we developed CpGislandEVO. Briely, we irst compile a database of statistically signiicant CGIs for the best assembled mammalian genome sequences available to date. Second, by means of a coupled browser front-end, we focus on the CGIs overlapping orthologous genes extracted from OrthoDB, thus ensuring the comparison between CGIs located on truly homologous genome segments. his allows comparing the main compositional features between homologous CGIs. Finally, to facilitate nucleotide comparisons, we lited genome coordinates between assemblies from diferent species, which enables the analysis of sequence divergence by direct count of nucleotide substitutions and indels occurring between homologous CGIs. he resulting CpGislandEVO database, linking together CGIs and single-cytosine DNA methylation data from several mammalian species, is freely available at our website. 1. Introduction Short stretches of CpG dinucleotides (CpG islands or CGIs) predominantly hypomethylated in healthy tissues [1, 2] are key epigenomic markers in mammalian genomes [3]. Almost all housekeeping genes and a half of the tissue-speciic genes are associated to CGIs [4]. DNA methylation plays an impor- tant role in the origin as well as in the function of CGIs. Aber- rant methylation (mostly hypermethylation) of CGIs can lead to several syndromes, such as cancer [5–10]. Moreover, although it has been shown that certain human diseases may have evolutionary epigenetic origins [11, 12], it remains largely unknown how patterns of DNA methylation difer between closely related species and whether such diferences con- tribute to species-speciic phenotypes [11]. Some methylation databases [13–15] and CGI databases [16] have been devel- oped, but, to our knowledge, no existing genome browser addresses speciically the evolutionary relationships between the CGIs from diferent species. To help describing and understanding the function as well as the mechanisms gen- erating and maintaining CGIs within an evolutionary con- text, we develop here CpGislandEVO (http://bioinfo2.ugr.es/ CpGislandEVO/index.php). he database, coupled to a pow- erful genome browser, links together experimental and pre- dicted CGIs, as well as single-cytosine-resolution DNA methylation data from diferent mammalian species. Early analyses of CGI evolution were based on compo- sitional comparisons between islands from diferent species but located on homologous gene contexts [17, 18]. Recently, the rapidly increasing number of sequenced genomes enabled evolutionary studies relying on multiple-sequence align- ments [19]. Here, we combine both approaches to envisage accurate sequence comparisons between CGIs located on homologous gene contexts.