Chapman Brad A, Bowers John E, Schulze Stefan R, Paterson Andrew H
Department of Plant Biology, University of Georgia, Athens, GA 30602, USA.
Bioinformatics. 2004 Jan 22;20(2):180-5. doi: 10.1093/bioinformatics/bth022.
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.
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.
Software and documentation are freely available from http://plantgenome.agtec.uga.edu/bioinformatics/dating/
全基因组复制在真核生物基因组结构的形成过程中发挥了重要作用。目前有关大片段重复染色质的证据为物种进化史带来了新见解,但也给试图利用比较基因组学技术的研究人员带来了重大挑战。了解复制事件相对于分类群分化的时间对于准确而全面的跨物种比较至关重要。
我们描述了一种在系统发育背景下估计复制事件时间的大规模方法。该方法先前已用于分析拟南芥和酿酒酵母的复制事件。此新实现为这些分析提供了更灵活且可重复使用的框架。用Python编程语言编写的脚本驱动了许多免费的生物信息学程序,为研究人员创建了一个免费工具。通过对拟南芥和水稻(Oryza)复制事件的全基因组规模分析,证明了该方法的实用性。
软件和文档可从http://plantgenome.agtec.uga.edu/bioinformatics/dating/免费获取。