Bayesian detection of convergent rate changes of conserved noncoding elements on phylogenetic trees
Conservation of DNA sequence over evolutionary time is a strong indicator of function, and gain or loss of sequence conservation can be used to infer changes in function across a phylogeny. Changes in evolutionary rates on particular lineages in phylogeny can indicate shared functional shifts, and thus can be used to detect genomic correlates of phenotypic convergence. However, existing methods do not allow easy detection of patterns of rate variation, which causes challenges for detecting convergent rate shifts or other complex evolutionary scenarios. Here, we introduce PhyloAcc, a new Bayesian method to model substitution rate changes in conserved elements across a phylogeny. The method can handle diverse evolutionary patterns and complex patterns of convergence, assumes a latent conservation state for each branch on the phylogenetic tree, estimates element-wise substitution rates per state, and detects changes of substitution rate as the posterior probability of a state switch. Simulations show that PhyloAcc can detect rate shifts in multiple species better than likelihood ratio based methods, and has higher accuracy to detect complex patterns of substitution rate changes than prevalent Bayesian relaxed clock models. We demonstrate the utility of this method in two classic examples of convergent phenotypes: loss of flight in birds and the transition to marine life in mammals. In each case, our approach reveals numerous examples of conserved non-exonic elements with accelerations specific to the phenotypically convergent lineages. This method is widely applicable to any set of conserved elements where multiple independent rate changes are expected on a phylogeny.
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