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Comparing inference under the multispecies coalescent with and without recombination.

Authors :
Yan Z
Ogilvie HA
Nakhleh L
Source :
Molecular phylogenetics and evolution [Mol Phylogenet Evol] 2023 Apr; Vol. 181, pp. 107724. Date of Electronic Publication: 2023 Jan 28.
Publication Year :
2023

Abstract

Accurate inference of population parameters plays a pivotal role in unravelling evolutionary histories. While recombination has been universally accepted as a fundamental process in the evolution of sexually reproducing organisms, it remains challenging to model it exactly. Thus, existing coalescent-based approaches make different assumptions or approximations to facilitate phylogenetic inference, which can potentially bring about biases in estimates of evolutionary parameters when recombination is present. In this article, we evaluate the performance of population parameter estimation using three methods-StarBEAST2, SNAPP, and diCal2-that represent three different types of inference. We performed whole-genome simulations in which recombination rates, mutation rates, and levels of incomplete lineage sorting were varied. We show that StarBEAST2 using short or medium-sized loci is robust to realistic rates of recombination, which is in agreement with previous studies. SNAPP, as expected, is generally unaffected by recombination events. Most surprisingly, diCal2, a method that is designed to explicitly account for recombination, performs considerably worse than other methods under comparison.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2023 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1095-9513
Volume :
181
Database :
MEDLINE
Journal :
Molecular phylogenetics and evolution
Publication Type :
Academic Journal
Accession number :
36720421
Full Text :
https://doi.org/10.1016/j.ympev.2023.107724