Abstract

Adaptive evolution has shaped major biological processes. Finding the protein-coding genes and the sites that have been subjected to adaptation during evolutionary time is a major endeavor. However, very few methods fully automate the identification of positively selected genes, and widespread sources of genetic innovations such as gene duplication and recombination are absent from most pipelines. Here, we developed DGINN, a highly-flexible and public pipeline to Detect Genetic INNovations and adaptive evolution in protein-coding genes. DGINN automates, from a gene's sequence, all steps of the evolutionary analyses necessary to detect the aforementioned innovations, including the search for homologs in databases, assignation of orthology groups, identification of duplication and recombination events, as well as detection of positive selection using five methods to increase precision and ranking of genes when a large panel is analyzed. DGINN was validated on nineteen genes with previously-characterized evolutionary histories in primates, including some engaged in host-pathogen arms-races. Our results confirm and also expand results from the literature, including novel findings on the Guanylate-binding protein family, GBPs. This establishes DGINN as an efficient tool to automatically detect genetic innovations and adaptive evolution in diverse datasets, from the user's gene of interest to a large gene list in any species range.

中文翻译：

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DGINN，一种自动化且高度灵活的管道，用于检测蛋白质编码基因的遗传创新。

 抽象的

适应性进化塑造了主要的生物过程。寻找在进化过程中经历适应的蛋白质编码基因和位点是一项重大努力。然而，很少有方法能够完全自动化地识别积极选择的基因，并且大多数管道中都缺乏广泛的遗传创新来源，例如基因复制和重组。在这里，我们开发了 DGINN，这是一个高度灵活的公共管道，用于检测蛋白质编码基因的遗传创新和适应性进化。 DGINN 从基因序列自动化检测上述创新所需的进化分析的所有步骤，包括在数据库中搜索同源物、直系群的分配、重复和重组事件的识别，以及使用五种方法检测正选择分析大型面板时提高基因精度和排序的方法。 DGINN 在灵长类动物中具有先前表征的进化历史的 19 个基因上得到了验证，其中包括一些参与宿主与病原体军备竞赛的基因。我们的结果证实并扩展了文献的结果，包括鸟苷酸结合蛋白家族GBP的新发现。这使 DGINN 成为一种有效的工具，可以自动检测不同数据集中的遗传创新和适应性进化，从用户感兴趣的基因到任何物种范围内的大型基因列表。