Resumen
Functional shifts during protein evolution are expected to yield shifts in substitution rate, and statistical methods can test for this at both codon and amino acid levels. Although methods based on models of sequence evolution serve as powerful tools for studying evolutionary processes, violating underlying assumptions can lead to false biological conclusions. It is not unusual for functional shifts to be accompanied by changes in other aspects of the evolutionary process, such as codon or amino acid frequencies. However, models used to test for functional divergence assume these frequencies remain constant over time. We employed simulation to investigate the impact of non-stationary evolution on functional divergence inference. We investigated three likelihood ratio tests based on codon models and found varying degrees of sensitivity. Joint effects of shifts in frequencies and selection pressures can be large, leading to false signals for positive selection. Amino acid-based tests (FunDi and Bivar) were also compromised when several aspects of the substitution process were not adequately modeled. We applied the same tests to a core genome "scan" for functional divergence between light-adapted ecotypes of the cyanobacteria Prochlorococcus, and carried out gene-specific simulations for ten genes. Results of those simulations illustrated how the inference of functional divergence at the genomic level can be seriously impacted by model misspecification. Although computationally costly, simulations motivated by data in hand are warranted when several aspects of the substitution process are either misspecified or not included in the models upon which the statistical tests were built.
Idioma original | English |
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Páginas (desde-hasta) | 205-215 |
Número de páginas | 11 |
Publicación | Journal of Molecular Evolution |
Volumen | 76 |
N.º | 4 |
DOI | |
Estado | Published - abr. 2013 |
Nota bibliográfica
Funding Information:This research was supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant awarded to JPB. The research utilized computer hardware funder by a grant from the Canadian Foundation for Innovation to JPB. JBP also acknowledges the support of the Centre for Genomics and Evolutionary Bioinformatics (CGEB) which is funded by the Tula Foundation. We thank Olga Zhaxybayeva for providing amino acid alignments for the Prochlorococcus genomic data. We thank Katherine A. Dunn for helpful discussions, and for valuable guidance and advice on the development of Perl programs and the automation of analyses of both simulated data and real genome-scale datasets. We thank Joseph R. Mingrone for helpful discussions, and for many important contributions to the computational work carried out as part of this study. We also thank three anonymous referees for their comments, and for several suggestions that substantially improved this paper.
ASJC Scopus Subject Areas
- Ecology, Evolution, Behavior and Systematics
- Molecular Biology
- Genetics