CpX Hunter web tool allows high-throughput identification of CpG, CpA, CpT, and CpC islands: A case study in Drosophila genome
J_ČLÁNEK
Date
2025Author
Bartas, Martin
Petrovič, Michal
Brázda, Václav
Trenz, Oldřich
Ďurčanský, Aleš
Šťastný, Jiří
Metadata
Show full item recordAbstract
With continuous advances in DNA sequencing methods, accessibility to high-quality genomic information for all living organisms is ever increasing. However, to interpret this information effectively and formulate hypotheses, users often require higher level programming skills. Therefore, the generation of web-based tools is becoming increasingly popular. CpG island regions in genomes are often found in gene promoters and are prone to DNA methylation; with their methylation status determining if a gene is expressed. Notably, understanding the biological impact of CpX modifications on genomic regulation is becoming increasingly important as these modifications have been associated with diseases such as cancer and neurodegeneration. However, there is currently no easy-to-use scalable tool to detect and quantify CpX islands in full genomes. We have developed a Java-based web server for CpX island analyses that benefits from the DNA Analyzer Web server environment and overcomes several limitations. For a pilot demonstration study, we selected a well-described model organism Drosophila melanogaster. Subsequent analysis of obtained CpX islands revealed several interesting and previously undescribed phenomena. One of them is the fact, that nearly half of long CpG islands were located on chromosome X, and that long CpA and CpT islands were significantly overrepresented at the subcentromeric regions of autosomes (chr2 and chr3) and also on chromosome Y. Wide genome overlays of predicted CpX islands revealed their co-occurrence with various (epi)genomics features comprising cytosine methylations, accessible chromatin, transposable elements, or binding of transcription factors and other proteins. CpX Hunter is freely available as a web tool at: https://bioinformatics.ibp.cz/#/analyse/cpg