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dc.contributor.authorCheng, Chih-Hsienen_US
dc.contributor.authorYang, Chung-Hanen_US
dc.contributor.authorChiu, Hsien-Taien_US
dc.contributor.authorLu, Chin Lungen_US
dc.date.accessioned2019-04-03T06:38:08Z-
dc.date.available2019-04-03T06:38:08Z-
dc.date.issued2010-02-24en_US
dc.identifier.issn1471-2105en_US
dc.identifier.urihttp://dx.doi.org/10.1186/1471-2105-11-102en_US
dc.identifier.urihttp://hdl.handle.net/11536/149918-
dc.description.abstractBackground: Overlapping genes (OGs) are defined as adjacent genes whose coding sequences overlap partially or entirely. In fact, they are ubiquitous in microbial genomes and more conserved between species than nonoverlapping genes. Based on this property, we have previously implemented a web server, named OGtree, that allows the user to reconstruct genome trees of some prokaryotes according to their pairwise OG distances. By analogy to the analyses of gene content and gene order, the OG distance between two genomes we defined was based on a measure of combining OG content (i.e., the normalized number of shared orthologous OG pairs) and OG order (i.e., the normalized OG breakpoint distance) in their whole genomes. A shortcoming of using the concept of breakpoints to define the OG distance is its inability to analyze the OG distance of multi-chromosomal genomes. In addition, the amount of overlapping coding sequences between some distantly related prokaryotic genomes may be limited so that it is hard to find enough OGs to properly evaluate their pairwise OG distances. Results: In this study, we therefore define a new OG order distance that is based on more biologically accurate rearrangements (e. g., reversals, transpositions and translocations) rather than breakpoints and that is applicable to both uni-chromosomal and multi-chromosomal genomes. In addition, we expand the term "gene" to include both its coding sequence and regulatory regions so that two adjacent genes whose coding sequences or regulatory regions overlap with each other are considered as a pair of overlapping genes. This is because overlapping of regulatory regions of distinct genes suggests that the regulation of expression for these genes should be more or less interrelated. Based on these modifications, we have reimplemented our OGtree as a new web server, named OGtree2, and have also evaluated its accuracy of genome tree reconstruction on a testing dataset consisting of 21 Proteobacteria genomes. Our experimental results have finally shown that our current OGtree2 indeed outperforms its previous version OGtree, as well as another similar server, called BPhyOG, significantly in the quality of genome tree reconstruction, because the phylogenetic tree obtained by OGtree2 is greatly congruent with the reference tree that coincides with the taxonomy accepted by biologists for these Proteobacteria. Conclusions: In this study, we have introduced a new web server OGtree2 at http://bioalgorithm.life.nctu.edu.tw/ OGtree2.0/ that can serve as a useful tool for reconstructing more precise and robust genome trees of prokaryotes according to their overlapping genes.en_US
dc.language.isoen_USen_US
dc.titleReconstructing genome trees of prokaryotes using overlapping genesen_US
dc.typeArticleen_US
dc.identifier.doi10.1186/1471-2105-11-102en_US
dc.identifier.journalBMC BIOINFORMATICSen_US
dc.citation.volume11en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000276295200001en_US
dc.citation.woscount7en_US
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