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Polymorphism‐aware estimation of species trees and evolutionary forces from genomic sequences with <scp>RevBayes</scp>

Authors :
Rui Borges
Bastien Boussau
Sebastian Höhna
Ricardo J. Pereira
Carolin Kosiol
BBSRC
University of St Andrews. Centre for Biological Diversity
University of St Andrews. School of Biology
University of St Andrews. St Andrews Bioinformatics Unit
Le Cocon
Département PEGASE [LBBE] (PEGASE)
Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE)
Université Claude Bernard Lyon 1 (UCBL)
Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)
Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE)
Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)
Source :
Methods in Ecology and Evolution, Methods in Ecology and Evolution, 2022, 13 (11), pp.2339-2346. ⟨10.1111/2041-210X.13980⟩
Publication Year :
2022
Publisher :
Wiley, 2022.

Abstract

Funding information: Austrian Science Fund, Grant/Award Number: P34524-B; Biotechnology and Biological Sciences Research Council, Grant/Award Number: BB/W000768/1; Deutsche Forschungsgemeinschaft, Grant/Award Number: HO 6201/1-1; Vienna Science and Technology Fund, Grant/Award Number: MA016-061. 1. The availability of population genomic data through new sequencing technologies gives unprecedented opportunities for estimating important evolutionary forces such as genetic drift, selection and mutation biases across organisms. Yet, analytical methods that can handle polymorphisms jointly with sequence divergence across species are rare and not easily accessible to empiricists. 2. We implemented polymorphism-aware phylogenetic models (PoMos), an alternative approach for species tree estimation, in the Bayesian phylogenetic software RevBayes. PoMos naturally account for incomplete lineage sorting, which is known to cause difficulties for phylogenetic inference in species radiations, and scale well with genome-wide data. Simultaneously, PoMos can estimate mutation and selection biases. 3. We have applied our methods to resolve the complex phylogenetic relationships of a young radiation of Chorthippus grasshoppers, based on coding sequences. In addition to establishing a well-supported species tree, we found a mutation bias favouring AT alleles and selection bias promoting the fixation of GC alleles, the latter consistent with GC-biased gene conversion. The selection bias is two orders of magnitude lower than genetic drift, validating the critical role of nearly neutral evolutionary processes in species radiation. 4. PoMos offer a wide range of models to reconstruct phylogenies and can be easily combined with existing models in RevBayes—for example, relaxed clock and divergence time estimation—offering new insights into the evolutionary processes underlying molecular evolution and, ultimately, species diversification. Publisher PDF

Details

ISSN :
2041210X
Volume :
13
Database :
OpenAIRE
Journal :
Methods in Ecology and Evolution
Accession number :
edsair.doi.dedup.....24c84d4431714b20fffe5bbd4712c527