Department of Biology, University of Massachusetts Boston, Boston, Massachusetts, 02125.
Evolution. 2014 Mar;68(3):743-59. doi: 10.1111/evo.12300. Epub 2013 Nov 18.
Evolutionary biology is a study of life's history on Earth. In researching this history, biologists are often interested in attempting to reconstruct phenotypes for the long extinct ancestors of living species. Various methods have been developed to do this on a phylogeny from the data for extant taxa. In the present article, I introduce a new approach for ancestral character estimation for discretely valued traits. This approach is based on the threshold model from evolutionary quantitative genetics. Under the threshold model, the value exhibited by an individual or species for a discrete character is determined by an underlying, unobserved continuous trait called "liability." In this new method for ancestral state reconstruction, I use Bayesian Markov chain Monte Carlo (MCMC) to sample the liabilities of ancestral and tip species, and the relative positions of two or more thresholds, from their joint posterior probability distribution. Using data simulated under the model, I find that the method has very good performance in ancestral character estimation. Use of the threshold model for ancestral state reconstruction relies on a priori specification of the order of the discrete character states along the liability axis. I test the use of a Bayesian MCMC information theoretic criterion based approach to choose among different hypothesized orderings for the discrete character. Finally, I apply the method to the evolution of feeding mode in centrarchid fishes.
进化生物学是对地球上生命历史的研究。在研究这段历史时，生物学家通常有兴趣尝试重建现存物种的远古灭绝祖先的表型。已经开发出各种方法，以便根据现存分类单元的数据在系统发育树上进行这项工作。在本文中，我介绍了一种用于离散值特征祖先特征估计的新方法。这种方法基于进化数量遗传学中的阈模型。在阈模型下，个体或物种对离散特征的表现由一个称为“易感性”的潜在的、未被观察到的连续特征决定。在这种新的祖先状态重建方法中，我使用贝叶斯马尔可夫链蒙特卡罗（MCMC）从它们的联合后验概率分布中抽样祖先和尖端物种的易感性和两个或更多阈值的相对位置。使用模型模拟的数据，我发现该方法在祖先特征估计方面具有很好的性能。使用阈模型进行祖先状态重建依赖于沿易感性轴对离散特征状态的顺序的先验指定。我测试了使用基于贝叶斯 MCMC 信息理论标准的方法来选择离散特征的不同假设顺序。最后，我将该方法应用于鲈形目鱼类摄食方式的演化。
