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寻找同源基因的十年协同进展。

Ten Years of Collaborative Progress in the Quest for Orthologs.

机构信息

LIRMM, University of Montpellier, CNRS, Montpellier, France.

SPYGEN, Le Bourget-du-Lac, France.

出版信息

Mol Biol Evol. 2021 Jul 29;38(8):3033-3045. doi: 10.1093/molbev/msab098.

Abstract

Accurate determination of the evolutionary relationships between genes is a foundational challenge in biology. Homology-evolutionary relatedness-is in many cases readily determined based on sequence similarity analysis. By contrast, whether or not two genes directly descended from a common ancestor by a speciation event (orthologs) or duplication event (paralogs) is more challenging, yet provides critical information on the history of a gene. Since 2009, this task has been the focus of the Quest for Orthologs (QFO) Consortium. The sixth QFO meeting took place in Okazaki, Japan in conjunction with the 67th National Institute for Basic Biology conference. Here, we report recent advances, applications, and oncoming challenges that were discussed during the conference. Steady progress has been made toward standardization and scalability of new and existing tools. A feature of the conference was the presentation of a panel of accessible tools for phylogenetic profiling and several developments to bring orthology beyond the gene unit-from domains to networks. This meeting brought into light several challenges to come: leveraging orthology computations to get the most of the incoming avalanche of genomic data, integrating orthology from domain to biological network levels, building better gene models, and adapting orthology approaches to the broad evolutionary and genomic diversity recognized in different forms of life and viruses.

摘要

准确确定基因之间的进化关系是生物学中的一个基本挑战。同源性——进化相关性——在许多情况下可以基于序列相似性分析来确定。相比之下,两个基因是否是由一个物种形成事件(直系同源物)或复制事件(旁系同源物)直接从共同祖先继承而来,这更具挑战性,但提供了关于基因历史的关键信息。自 2009 年以来,这项任务一直是 Quest for Orthologs (QFO) 联盟的重点。第六届 QFO 会议在日本冈崎市与第 67 届国立基础生物学研究所会议同时举行。在这里,我们报告了会议期间讨论的最新进展、应用和即将面临的挑战。新工具和现有工具的标准化和可扩展性方面取得了稳步进展。会议的一个特点是展示了一组可用于系统发育分析的工具,以及将同源性从基因单元扩展到网络的几个发展方向。本次会议揭示了未来的几个挑战:利用同源性计算从即将到来的基因组数据洪流中获取最大价值,整合从域到生物网络水平的同源性,构建更好的基因模型,并使同源性方法适应不同形式的生命和病毒所识别的广泛进化和基因组多样性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdf7/8321534/68f6786c9c86/msab098f1.jpg

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