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Journal articles
Genome-wide computational prediction of tandem gene arrays: application in yeasts.
Abstract : BACKGROUND: This paper describes an efficient in silico method for detecting tandem gene arrays (TGAs) in fully sequenced and compact genomes such as those of prokaryotes or unicellular eukaryotes. The originality of this method lies in the search of protein sequence similarities in the vicinity of each coding sequence, which allows the prediction of tandem duplicated gene copies independently of their functionality. RESULTS: Applied to nine hemiascomycete yeast genomes, this method predicts that 2% of the genes are involved in TGAs and gene relics are present in 11% of TGAs. The frequency of TGAs with degenerated gene copies means that a significant fraction of tandem duplicated genes follows the birth-and-death model of evolution. A comparison of sequence identity distributions between sets of homologous gene pairs shows that the different copies of tandem arrayed paralogs are less divergent than copies of dispersed paralogs in yeast genomes. It suggests that paralogs included in tandem structures are more recent or more subject to the gene conversion mechanism than other paralogs. CONCLUSION: The method reported here is a useful computational tool to provide a database of TGAs composed of functional or nonfunctional gene copies. Such a database has obvious applications in the fields of structural and comparative genomics. Notably, a detailed study of the TGA catalog will make it possible to tackle the fundamental questions of the origin and evolution of tandem gene clusters.
https://hal-pasteur.archives-ouvertes.fr/pasteur-00670632
Contributor : Ed. Bmc Connect in order to contact the contributor
Submitted on : Wednesday, February 15, 2012 - 5:16:04 PM
Last modification on : Thursday, January 20, 2022 - 4:16:13 PM
Long-term archiving on: : Wednesday, December 14, 2016 - 6:52:38 AM
Contributor : Ed. Bmc Connect in order to contact the contributor
Submitted on : Wednesday, February 15, 2012 - 5:16:04 PM
Last modification on : Thursday, January 20, 2022 - 4:16:13 PM
Long-term archiving on: : Wednesday, December 14, 2016 - 6:52:38 AM