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PhyloAcc-GT: A Bayesian Method for Inferring Patterns of Substitution Rate Shifts on Targeted Lineages Accounting for Gene Tree Discordance.

Authors :
Yan H
Hu Z
Thomas GWC
Edwards SV
Sackton TB
Liu JS
Source :
Molecular biology and evolution [Mol Biol Evol] 2023 Sep 01; Vol. 40 (9).
Publication Year :
2023

Abstract

An important goal of evolutionary genomics is to identify genomic regions whose substitution rates differ among lineages. For example, genomic regions experiencing accelerated molecular evolution in some lineages may provide insight into links between genotype and phenotype. Several comparative genomics methods have been developed to identify genomic accelerations between species, including a Bayesian method called PhyloAcc, which models shifts in substitution rate in multiple target lineages on a phylogeny. However, few methods consider the possibility of discordance between the trees of individual loci and the species tree due to incomplete lineage sorting, which might cause false positives. Here, we present PhyloAcc-GT, which extends PhyloAcc by modeling gene tree heterogeneity. Given a species tree, we adopt the multispecies coalescent model as the prior distribution of gene trees, use Markov chain Monte Carlo (MCMC) for inference, and design novel MCMC moves to sample gene trees efficiently. Through extensive simulations, we show that PhyloAcc-GT outperforms PhyloAcc and other methods in identifying target lineage-specific accelerations and detecting complex patterns of rate shifts, and is robust to specification of population size parameters. PhyloAcc-GT is usually more conservative than PhyloAcc in calling convergent rate shifts because it identifies more accelerations on ancestral than on terminal branches. We apply PhyloAcc-GT to two examples of convergent evolution: flightlessness in ratites and marine mammal adaptations, and show that PhyloAcc-GT is a robust tool to identify shifts in substitution rate associated with specific target lineages while accounting for incomplete lineage sorting.<br /> (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Details

Language :
English
ISSN :
1537-1719
Volume :
40
Issue :
9
Database :
MEDLINE
Journal :
Molecular biology and evolution
Publication Type :
Academic Journal
Accession number :
37665177
Full Text :
https://doi.org/10.1093/molbev/msad195