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生态特征对硬骨鱼类分子进化速率的影响:多变量方法。

The Effects of Ecological Traits on the Rate of Molecular Evolution in Ray-Finned Fishes: A Multivariable Approach.

机构信息

Department of Integrative Biology and Biodiversity Institute of Ontario, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.

Department of Mathematics and Statistics, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.

出版信息

J Mol Evol. 2020 Nov;88(8-9):689-702. doi: 10.1007/s00239-020-09967-9. Epub 2020 Oct 3.

Abstract

Myriad environmental and biological traits have been investigated for their roles in influencing the rate of molecular evolution across various taxonomic groups. However, most studies have focused on a single trait, while controlling for additional factors in an informal way, generally by excluding taxa. This study utilized a dataset of cytochrome c oxidase subunit I (COI) barcode sequences from over 7000 ray-finned fish species to test the effects of 27 traits on molecular evolutionary rates. Environmental traits such as temperature were considered, as were traits associated with effective population size including body size and age at maturity. It was hypothesized that these traits would demonstrate significant correlations with substitution rate in a multivariable analysis due to their associations with mutation and fixation rates, respectively. A bioinformatics pipeline was developed to assemble and analyze sequence data retrieved from the Barcode of Life Data System (BOLD) and trait data obtained from FishBase. For use in phylogenetic regression analyses, a maximum likelihood tree was constructed from the COI sequence data using a multi-gene backbone constraint tree covering 71% of the species. A variable selection method that included both single- and multivariable analyses was used to identify traits that contribute to rate heterogeneity estimated from different codon positions. Our analyses revealed that molecular rates associated most significantly with latitude, body size, and habitat type. Overall, this study presents a novel and systematic approach for integrative data assembly and variable selection methodology in a phylogenetic framework.

摘要

已经研究了许多环境和生物特征,以了解它们在影响不同分类群的分子进化率方面的作用。然而,大多数研究都集中在单一特征上,而以非正规的方式控制其他因素,通常是通过排除分类单元。本研究利用了来自 7000 多种栉鳍鱼类的细胞色素 c 氧化酶亚基 I(COI)条形码序列数据集,以测试 27 个特征对分子进化率的影响。考虑了环境特征,如温度,还考虑了与有效种群大小相关的特征,包括体型和成熟年龄。由于与突变和固定率分别相关,因此假设这些特征在多变量分析中会因与替代率的相关性而表现出显著相关性。开发了一个生物信息学管道,用于组装和分析从生命条形码数据系统(BOLD)中检索的序列数据和从 FishBase 获得的特征数据。为了在系统发育回归分析中使用,使用覆盖 71%物种的多基因骨干约束树从 COI 序列数据构建了最大似然树。使用包括单变量和多变量分析的变量选择方法,确定了与从不同密码子位置估计的速率异质性相关的特征。我们的分析表明,与纬度、体型和生境类型最密切相关的分子速率。总体而言,本研究在系统发育框架中提出了一种新颖而系统的综合数据组装和变量选择方法。

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