MOTIVATION: Whole genome duplications have played a major role in determining the structure of eukaryotic genomes. Current evidence revealing large blocks of duplicated chromatin yields new insights into the evolutionary history of species, but also presents a major challenge for researchers attempting to utilize comparative genomics techniques. Understanding the timing of duplication events relative to divergence among taxa is critical to accurate and comprehensive cross-species comparisons. RESULTS: We describe a large-scale approach to estimate the timing of duplication events in a phylogenetic context. The methodology has been previously utilized for analysis of Arabidopsis and Saccharomyces duplication events. This new implementation provides a more flexible and reusable framework for these analyses. Scripts written in the Python programming language drive a number of freely available bioinformatics programs, creating a no-cost tool for researchers. The usefulness of the approach is demonstrated through genome-scale analysis of Arabidopsis and Oryza (rice) duplications. AVAILABILITY: Software and documentation are freely available from http://plantgenome.agtec.uga.edu/bioinformatics/dating/
MOTIVATION: Whole genome duplications have played a major role in determining the structure of eukaryotic genomes. Current evidence revealing large blocks of duplicated chromatin yields new insights into the evolutionary history of species, but also presents a major challenge for researchers attempting to utilize comparative genomics techniques. Understanding the timing of duplication events relative to divergence among taxa is critical to accurate and comprehensive cross-species comparisons. RESULTS: We describe a large-scale approach to estimate the timing of duplication events in a phylogenetic context. The methodology has been previously utilized for analysis of Arabidopsis and Saccharomyces duplication events. This new implementation provides a more flexible and reusable framework for these analyses. Scripts written in the Python programming language drive a number of freely available bioinformatics programs, creating a no-cost tool for researchers. The usefulness of the approach is demonstrated through genome-scale analysis of Arabidopsis and Oryza (rice) duplications. AVAILABILITY: Software and documentation are freely available from http://plantgenome.agtec.uga.edu/bioinformatics/dating/
Authors: Jim Leebens-Mack; Todd Vision; Eric Brenner; John E Bowers; Steven Cannon; Mark J Clement; Clifford W Cunningham; Claude dePamphilis; Rob deSalle; Jeff J Doyle; Jonathan A Eisen; Xun Gu; John Harshman; Robert K Jansen; Elizabeth A Kellogg; Eugene V Koonin; Brent D Mishler; Hervé Philippe; J Chris Pires; Yin-Long Qiu; Seung Y Rhee; Kimmen Sjölander; Douglas E Soltis; Pamela S Soltis; Dennis W Stevenson; Kerr Wall; Tandy Warnow; Christian Zmasek Journal: OMICS Date: 2006