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基于系统发育树的表型序列比较分析。

Comparative Analyses of Phenotypic Sequences Using Phylogenetic Trees.

出版信息

Am Nat. 2020 Feb;195(2):E38-E50. doi: 10.1086/706912. Epub 2020 Jan 7.

Abstract

Phenotypic sequences are a type of multivariate trait organized structurally, such as teeth distributed along the dental arch, or temporally, such as the stages of an ontogenetic series. Unlike other multivariate traits, the elements of a phenotypic sequence are distributed along an ordered set, which allows for distinct evolutionary patterns between neighboring and distant positions. In fact, sequence traits share many characteristics with molecular sequences, although important distinctions pose challenges to current comparative methods. We implement an approach to estimate rates of trait evolution that explicitly incorporates the sequence organization of traits. We apply models to study the temporal pattern evolution of cricket calling songs. We test whether neighboring positions along a phenotypic sequence have correlated rates of evolution or whether rate variation is independent of sequence position. Our results show that cricket song evolution is strongly autocorrelated and that models perform well when used with sequence phenotypes even under small sample sizes. Our approach is flexible and can be applied to any multivariate trait with discrete units organized in a sequence-like structure.

摘要

表型序列是一种结构上组织有序的多变量特征,例如沿牙弓分布的牙齿,或时间上的特征,如个体发育系列的阶段。与其他多变量特征不同,表型序列的元素沿有序集分布,这允许相邻和遥远位置之间具有不同的进化模式。事实上,序列特征与分子序列有许多共同特征,尽管重要的区别对当前的比较方法构成了挑战。我们实施了一种估计特征进化率的方法,该方法明确地将特征的序列组织纳入其中。我们应用模型来研究蟋蟀叫声的时间模式进化。我们检验了沿着表型序列的相邻位置是否具有相关的进化率,或者速率变化是否与序列位置无关。我们的结果表明,蟋蟀歌曲的进化具有强烈的自相关性,并且即使在样本量较小的情况下,使用序列表型的模型也能很好地发挥作用。我们的方法具有灵活性,可以应用于任何具有离散单元且以序列样结构组织的多变量特征。

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