Coestimation of recombination, substitution and molecular adaptation rates by approximate Bayesian computation

Abstract

The estimation of parameters in molecular evolution may be biased when some processes are not considered. For example, the estimation of selection at the molecular level using codon-substitution models can have an upward bias when recombination is ignored. Here we address the joint estimation of recombination, molecular adaptation and substitution rates from coding sequences using approximate Bayesian computation (ABC). We describe the implementation of a regression-based strategy for choosing subsets of summary statistics for coding data, and show that this approach can accurately infer recombination allowing for intracodon recombination breakpoints, molecular adaptation and codon substitution rates. We demonstrate that our ABC approach can outperform other analytical methods under a variety of evolutionary scenarios. We also show that although the choice of the codon-substitution model is important, our inferences are robust to a moderate degree of model misspecification. In addition, we demonstrate that our approach can accurately choose the evolutionary model that best fits the data, providing an alternative for when the use of full-likelihood methods is impracticable. Finally, we applied our ABC method to co-estimate recombination, substitution and molecular adaptation rates from 24 published human immunodeficiency virus 1 coding data sets.

Recombination in viruses: Mechanisms, methods of study, and evolutionary consequences

“…Overall, the accuracy of these analytical tools depends on the amount of genetic diversity. In general, most methods are less robust under low levels of genetic diversity, with Lamarc showing the best performance in such conditions (Lopes et al, 2014).…”

“…An interesting example was performed by Wilson et al (2009), in which they applied ABC to estimate recombination rates among other evolutionary parameters (such as mutation and dN/dS). This methodology is likely to be used in next year for the analysis of highly recombinant viruses, such as those recently described by Lopes et al (2014) with HIV-1 data.…”

CodABC: A Computational Framework to Coestimate Recombination, Substitution, and Molecular Adaptation Rates by Approximate Bayesian Computation

“…In such cases, an approximate Bayesian computation (ABC) approach ( Beaumont 2010 ; Csillery et al 2010 ) can provide a reasonable solution. We have recently proposed an ABC strategy for the joint estimation of recombination, nonsynonymous/synonymous rate ratios, and substitution rates that outperforms other methods based on maximum likelihood and that is quite robust to model misspecification ( Lopes et al 2014 ). Here, we present a user-friendly computational tool that implements this methodology, called “CodABC.” In contrast to other ABC tools, CodABC allows for the analysis of coding data while jointly considering multiple parameters and complex codon substitution models.…”

Advances in Computer Simulation of Genome Evolution: Toward More Realistic Evolutionary Genomics Analysis by Approximate Bayesian Computation

“…These methods provide promising alternative analytical strategies and can generate very accurate inferences because of their joint consideration of different evolutionary processes. For example, they have already outperformed approximate maximum likelihood methods based on more approximate models (Lopes et al 2014;Arenas et al 2015). Nevertheless, ABC approaches definitely require extensive computer simulation with evolutionary frameworks that must be able to model the evolutionary process in a way that is as realistic as possible.…”