EBM UMR 6632 LATP, 3 place V Hugo - 13 331 Marseille cedex 03 France.
BMC Bioinformatics. 2009 Sep 10;10:284. doi: 10.1186/1471-2105-10-284.
Understanding genome evolution provides insight into biological mechanisms. For many years comparative genomics and analysis of conserved chromosomal regions have helped to unravel the mechanisms involved in genome evolution and their implications for the study of biological systems. Detection of conserved regions (descending from a common ancestor) not only helps clarify genome evolution but also makes it possible to identify quantitative trait loci (QTLs) and investigate gene function.The identification and comparison of conserved regions on a genome scale is computationally intensive, making process automation essential. Three key requirements are necessary: consideration of phylogeny to identify orthologs between multiple species, frequent updating of the annotation and panel of compared genomes and computation of statistical tests to assess the significance of identified conserved gene clusters.
We developed a modular system superimposed on a multi-agent framework, called CASSIOPE (Clever Agent System for Synteny Inheritance and Other Phenomena in Evolution). CASSIOPE automatically identifies statistically significant conserved regions between multiple genomes based on automated phylogenies and statistical testing. Conserved regions were searched for in 19 species and 1,561 hits were found. To our knowledge, CASSIOPE is the first system to date that integrates evolutionary biology-based concepts and fulfills all three key requirements stated above. All results are available at http://194.57.197.245/cassiopeWeb/displayCluster?clusterId=1
CASSIOPE makes it possible to study conserved regions from a chosen query genetic region and to infer conserved gene clusters based on phylogenies and statistical tests assessing the significance of these conserved regions.Source code is freely available, please contact: Pierre.pontarotti@univ-provence.fr.
理解基因组进化提供了对生物机制的深入了解。多年来,比较基因组学和保守染色体区域的分析帮助揭示了参与基因组进化的机制及其对生物系统研究的意义。检测保守区域(来自共同祖先)不仅有助于阐明基因组进化,还可以识别数量性状位点(QTL)并研究基因功能。在基因组范围内识别和比较保守区域计算量很大,因此实现过程自动化至关重要。需要满足三个关键要求:考虑系统发育以识别多个物种之间的同源物,频繁更新注释和比较基因组面板,以及计算统计检验以评估鉴定的保守基因簇的显著性。
我们开发了一个基于多代理框架的模块化系统,称为 CASSIOPE(进化中同线性继承和其他现象的智能代理系统)。CASSIOPE 根据自动系统发育和统计测试,自动在多个基因组之间识别具有统计学意义的保守区域。在 19 个物种中搜索了保守区域,发现了 1561 个命中。据我们所知,CASSIOPE 是迄今为止第一个集成基于进化生物学概念并满足上述三个关键要求的系统。所有结果均可在 http://194.57.197.245/cassiopeWeb/displayCluster?clusterId=1 上获得。
CASSIOPE 使得可以从选定的查询遗传区域研究保守区域,并根据系统发育和统计检验推断保守基因簇,以评估这些保守区域的显著性。源代码可免费获得,请联系:Pierre.pontarotti@univ-provence.fr。