A New Phylogenetic Method for Identifying Exceptional Phenotypic Diversification

Abstract

Currently available phylogenetic methods for studying the rate of evolution in a continuously valued character assume that the rate is constant throughout the tree or that it changes along specific branches according to an a priori hypothesis of rate variation provided by the user. Herein, we describe a new method for studying evolutionary rate variation in continuously valued characters given an estimate of the phylogenetic history of the species in our study. According to this method, we propose no specific prior hypothesis for how the variation in evolutionary rate is structured throughout the history of the species in our study. Instead, we use a Bayesian Markov Chain Monte Carlo approach to estimate evolutionary rates and the shift point between rates on the tree.We do this by simultaneously sampling rates and shift points in proportion to their posterior probability, and then collapsing the posterior sample into an estimate of the parameters of interest. We use simulation to show that the method is quite successful at identifying the phylogenetic position of a shift in the rate of evolution, and that estimated rates are asymptotically unbiased. We also provide an empirical example of the method using data for Anolis lizards.

Detecting Polygenic Adaptation in Admixture Graphs

“…Lastly, we note that despite some clear methodological and conceptual differences, our method bears a close relationship to a number of methods for inferring changes in the rate of phenotypic evolution on species phylogenies over macroevolutionary timescales. Our use of the Normal model of drift as an approximation to the Wright-Fisher diffusion is closely analogous to the use of Brownian motion models in some phylogenetic methods (Venditti et al 2011;Eastman et al 2011;Revell et al 2012;Rabosky et al 2013;Jhwueng and O'Meara 2015). It may also be worth exploring the relationship between Ornstein-Uhlenbeck models for phenotypic evolution on phylogenies (Uyeda and Harmon 2014;Khabbazian et al 2016) and the aforementioned hypothetical extension of our method to include stabilizing selection, as the two processes are closely related (Lande 1976;Simons et al 2017).…”

The hypothesis of adaptive radiation in evolutionary biology: hard facts about a hazy concept

“…From 2003 to 2012, a set of methods for testing the hypotheses of radiation and adaptation began to emerge (Alfaro et al 2009;Glor 2010;Losos and Mahler 2010;Pisani et al 2012;Revell et al 2012;Stadler 2011). However, these methods were not widely adopted, and we see two limitations that could have constrained this: (a) Researchers are not aware of these methods and (b) they are not able to apply them to their data due to a lack of adequate experience in applying the tests and/or to having adopted an inappropriate study design.…”

Bayesian Inference of the Evolution of a Phenotype Distribution on a Phylogenetic Tree

“…Application of this method can provide quantitative insights, for example an estimate of the phenotypic evolutionary rate. The maximum-likelihood approach to ancestral state reconstruction (Yang et al 1995) has been extended in many ways by refining the model of phenotypic evolution on the tree, for example by allowing the detection of branches where the phenotypic evolutionary rate changes (Revell 2008; Revell et al 2011). However, ancestral state reconstruction is problematic for any phenotype with imperfect heritability: Identical genotypes can then have different phenotypic values, implying an infinitely high rate of phenotypic evolution between them that is not biologically meaningful.…”