Nucleotide usage biases distort inferences of the species tree
Abstract
Despite the importance of natural selection in species' evolutionary history, phylogenetic methods that take into account population-level processes typically ignore selection. The assumption of neutrality is often based on the idea that selection occurs at a minority of loci in the genome and is unlikely to compromise phylogenetic inferences significantly. However, genome-wide processes like GC-bias and some variation segregating at the coding regions are known to evolve in the nearly neutral range. As we are now using genome-wide data to estimate species trees, it is natural to ask whether weak but pervasive selection is likely to blur species tree inferences. We developed a polymorphism-aware phylogenetic model tailored for measuring signatures of nucleotide usage biases to test the impact of selection in the species tree. Our analyses indicate that while the inferred relationships among species are not significantly compromised, the genetic distances are systematically underestimated in a node-height dependent manner: i.e., the deeper nodes tend to be more underestimated than the shallow ones. Such biases have implications for molecular dating. We dated the evolutionary history of 30 worldwide fruit fly populations, and we found signatures of GC-bias considerably affecting the estimated divergence times (up to 23%) in the neutral model. Our findings call for the need to account for selection when quantifying divergence or dating species evolution.
Citation
Borges , R , Boussau , B , Szöllősi , G J & Kosiol , C 2022 , ' Nucleotide usage biases distort inferences of the species tree ' , Genome Biology and Evolution , vol. 14 , no. 1 , evab290 . https://doi.org/10.1093/gbe/evab290
Publication
Genome Biology and Evolution
Status
Peer reviewed
ISSN
1759-6653Type
Journal article
Rights
Copyright © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.
Description
This work was supported by the Vienna Science and Technology Fund (WWTF) [MA16-061] and partially supported by the Austrian Science Fund (FWF) [P34524-B]. GJS received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program under grant agreement no. 714774 and the grant GINOP-2.3.2.-15-2016-00057.Collections
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