Abstract
The distribution of a phenotype on a phylogenetic tree is often a quantity of interest. Many phenotypes have imperfect heritability, so that a measurement of the phenotype for an individual can be thought of as a single realization from the phenotype distribution of that individual. If all individuals in a phylogeny had the same phenotype distribution, measured phenotypes would be randomly distributed on the tree leaves. This is, however, often not the case, implying that the phenotype distribution evolves over time. Here we propose a new model based on this principle of evolving phenotype distribution on the branches of a phylogeny, which is different from ancestral state reconstruction where the phenotype itself is assumed to evolve. We develop an efficient Bayesian inference method to estimate the parameters of our model and to test the evidence for changes in the phenotype distribution. We use multiple simulated data sets to show that our algorithm has good sensitivity and specificity properties. Since our method identifies branches on the tree on which the phenotype distribution has changed, it is able to break down a tree into components for which this distribution is unique and constant. We present two applications of our method, one investigating the association between HIV genetic variation and human leukocyte antigen and the other studying host range distribution in a lineage of Salmonella enterica, and we discuss many other potential applications.
Highlights
The distribution of a phenotype on a phylogenetic tree is often a quantity of interest
Here we present a novel Bayesian statistical method that takes as input a phylogenetic tree and discrete tip phenotype measurements and identifies the branches on which the phenotype distribution has changed
We propose that using our algorithm, one can determine whether host Human leukocyte antigen (HLA) alleles are randomly distributed on the tips of the virus phylogenetic tree or whether there are clades where the distributions are distinct from each other
Summary
The distribution of a phenotype on a phylogenetic tree is often a quantity of interest. We build a stochastic model in which changepoints occur on a phylogenetic tree (Didelot et al 2009), each of which affects the distribution of observed phenotype for the descendent leaves. The dimensionality of the model parameters changes with b as the number of sections on the tree depends on b and each section has its own distribution over the phenotype space.
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