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A Novel comparative method for identifying shifts in the rate of character evolution on trees

机译:一种识别树上角色进化速率变化的新型比较方法

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Evolutionary biologists since Darwin have been fascinated by differences in the rate of trait-evolutionary change across lineages. Despite this continued interest, we still lack methods for identifying shifts in evolutionary rates on the growing tree of life while accommodating uncertainty in the evolutionary process. Here we introduce a Bayesian approach for identifying complex patterns in the evolution of continuous traits. The method (auteur) uses reversible-jump Markov chain Monte Carlo sampling to more fully characterize the complexity of trait evolution, considering models that range in complexity from those with a single global rate to potentially ones in which each branch in the tree has its own independent rate. This newly introduced approach performs well in recovering simulated rate shifts and simulated rates for datasets nearing the size typical for comparative phylogenetic study (i.e., ≥64 tips). Analysis of two large empirical datasets of vertebrate body size reveal overwhelming support for multiple-rate models of evolution, and we observe exceptionally high rates of body-size evolution in a group of emydid turtles relative to their evolutionary background. auteur will facilitate identification of exceptional evolutionary dynamics, essential to the study of both adaptive radiation and stasis.
机译:自达尔文以来,进化生物学家就着迷于跨世系的性状进化变化速率的差异。尽管人们一直对此怀有浓厚的兴趣,但我们仍然缺乏在不断发展的生命树上确定进化速率变化的方法,同时又适应了进化过程中的不确定性。在这里,我们介绍一种用于确定连续性状进化中复杂模式的贝叶斯方法。该方法(auteur)使用可逆跳马尔可夫链蒙特卡洛采样来更全面地描述性状进化的复杂性,考虑模型的复杂性,从具有单一全局速率的模型到可能在树中每个分支都有其自身的模型独立率。这种新引入的方法在恢复模拟速率变化和数据集模拟速率方面表现良好,该数据集的大小接近比较系统发生研究的典型规模(即≥64个技巧)。对两个大型脊椎动物体经验数据集的分析表明,它们对多重速率的进化模型提供了压倒性的支持,并且我们观察到一组相对于其进化背景的em龟,其体形进化的速率异常高。奥特(Auteur)将有助于识别异常的进化动力学,这对于研究适应性辐射和血瘀都至关重要。

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