CLUSTERING OF MAIN ORTHOLOGS FOR MULTIPLE GENOMES
CLUSTERING OF MAIN ORTHOLOGS FOR MULTIPLE GENOMES
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DOI：
10.1142/s0219720008003540
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发表时间：
2008-06-01
影响因子：
1
通讯作者：
Jiang, Tao
中科院分区：
文献类型：
--
作者：
Fu, Zheng;Jiang, Tao
在比较基因组学中，多个基因组共有的直向同源基因的识别对于功能和进化研究都是至关重要的。虽然在实践中通常通过序列相似性搜索和协调树构建来完成，但最近Fu等人提出了一种新的组合方法和高通量系统MSOAR，用于基于基因组重排和基因复制的密切相关基因组之间的直系同源物鉴定。(1)MSOAR假设在最简约的进化场景中，直向同源基因相互对应，从而最大限度地减少基因组重排和（物种形成后）基因复制事件的数量。然而，MSOAR使用的简约方法将其限制于成对基因组比较。在本文中，我们将MSOAR扩展到多个（密切相关的）基因组，并提出了一个直系同源聚类方法，称为MultiMSOAR，推断多个基因组中的主要直系同源。作为初步实验，我们将MultiMSOAR应用于大鼠，小鼠和人类基因组，并使用公共数据库中的基因注释和基因功能分类来验证我们的结果。我们进一步将我们的结果与MultiParanoid预测的直系同源簇进行比较，MultiParanoid是着名的成对基因组比较程序InParanoid的扩展。比较结果表明，MultiMSOAR能有效区分主要的直系同源物和旁系同源物，从而提供更详细、更准确的直系同源信息。
The identification of orthologous genes shared by multiple genomes is critical for both functional and evolutionary studies in comparative genomics. While it is usually done by sequence similarity search and reconciled tree construction in practice, recently a new combinatorial approach and high-throughput system MSOAR for ortholog identification between closely related genomes based on genome rearrangement and gene duplication has been proposed in Fu et al.(1) MSOAR assumes that orthologous genes correspond to each other in the most parsimonious evolutionary scenario, minimizing the number of genome rearrangement and (postspeciation) gene duplication events. However, the parsimony approach used by MSOAR limits it to pairwise genome comparisons. In this paper, we extend MSOAR to multiple (closely related) genomes and propose an ortholog clustering method, called MultiMSOAR, to infer main orthologs in multiple genomes. As a preliminary experiment, we apply MultiMSOAR to rat, mouse, and human genomes, and validate our results using gene annotations and gene function classifications in the public databases. We further compare our results to the ortholog clusters predicted by MultiParanoid, which is an extension of the well-known program InParanoid for pairwise genome comparisons. The comparison reveals that MultiMSOAR gives more detailed and accurate orthology information, since it can effectively distinguish main orthologs from inparalogs.