Clustering of main orthologs for multiple genomes.
Clustering of main orthologs for multiple genomes.
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DOI：
10.1142/9781860948732_0022
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发表时间：
2007-01-01
期刊：
影响因子：
--
通讯作者：
Jiang, Tao
中科院分区：
文献类型：
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作者：
Fu, Zheng;Jiang, Tao
多个基因组共享的直系同源基因的鉴定对于比较基因组学的功能和进化研究至关重要。虽然在实践中通常是通过序列相似性搜索和协调树构建来完成，但最近在（11）中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紧密相关基因组之间的直系同源识别。 MSOAR 假设直系同源基因在最简约的进化场景中彼此对应，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为配对基因组比较。在本文中，我们将 MSOAR 扩展到多个（密切相关的）基因组，并提出了一种称为 MultiMSOAR 的直系同源聚类方法，以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 是著名程序 Inparanoid 的扩展，用于成对基因组比较。比较表明，MultiMSOAR 可以有效区分主要直向同源物和内旁系同源物，从而提供更详细和准确的直向同源信息。
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 a high-throughput system MSOAR for ortholog identification between closely related genomes based on genome rearrangement and gene duplication have been proposed in (11). MSOAR assumes that orthologous genes correspond to each other in the most parsimonious evolutionary scenario minimizing the number of genome rearrangement and (post-speciation) gene duplication events. However, the parsimony approach used by MSOAR limits it to pairwsie 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.