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<p>Abstract</p> <p>Background</p> <p>Unmethylated stretches of CpG dinucleotides (CpG islands) are an outstanding property of mammal genomes. Conventionally, these regions are detected by sliding window approaches using %G + C, CpG observed/expected ratio and length thresholds as main parameters. Recently, clustering methods directly detect clusters of CpG dinucleotides as a statistical property of the genome sequence.</p> <p>Results</p> <p>We compare sliding-window to clustering (i.e. <it>CpGcluster</it>) predictions by applying new ways to detect putative functionality of CpG islands. Analyzing the co-localization with several genomic regions as a function of window size <it>vs</it>. statistical significance (<it>p-value</it>), <it>CpGcluster </it>shows a higher overlap with promoter regions and highly conserved elements, at the same time showing less overlap with <it>Alu </it>retrotransposons. The major difference in the prediction was found for short islands (CpG islets), often exclusively predicted by <it>CpGcluster</it>. Many of these islets seem to be functional, as they are unmethylated, highly conserved and/or located within the promoter region. Finally, we show that window-based islands can spuriously overlap several, differentially regulated promoters as well as different methylation domains, which might indicate a wrong merge of several CpG islands into a single, very long island. The shorter <it>CpGcluster </it>islands seem to be much more specific when concerning the overlap with alternative transcription start sites or the detection of homogenous methylation domains.</p> <p>Conclusions</p> <p>The main difference between sliding-window approaches and clustering methods is the length of the predicted islands. Short islands, often differentially methylated, are almost exclusively predicted by <it>CpGcluster</it>. This suggests that <it>CpGcluster </it>may be the algorithm of choice to explore the function of these short, but putatively functional CpG islands.</p>