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Stéphane Aris-Brosou

Publications and source records attributed to Stéphane Aris-Brosou.

6 recordsLinked to original sources

Large-scale analyses of synonymous substitution rates can be sensitive to assumptions about the process of mutation.

A popular approach to examine the roles of mutation and selection in the evolution of genomes has been to consider the relationship between codon bias and synonymous rates of molecular evolution. A significant relationship between these two quantities is taken to indicate the action of weak selection on substitutions among synonymous codons. The neutral theory predicts that the rate of evolution is inversely related to the level of functional constraint. Therefore, selection against the use of non-preferred codons among those coding for the same amino acid should result in lower rates of synonymous substitution as compared with sites not subject to such selection pressures. However, reliably measuring the extent of such a relationship is problematic, as estimates of synonymous rates are sensitive to our assumptions about the process of molecular evolution. Previous studies showed the importance of accounting for unequal codon frequencies, in particular when synonymous codon usage is highly biased. Yet, unequal codon frequencies can be modeled in different ways, making different assumptions about the mutation process. Here we conduct a simulation study to evaluate two different ways of modeling uneven codon frequencies and show that both model parameterizations can have a dramatic impact on rate estimates and affect biological conclusions about genome evolution. We reanalyze three large data sets to demonstrate the relevance of our results to empirical data analysis.

Amino Acid Substitution↗

Identifying sites under positive selection with uncertain parameter estimates.

Codon-based substitution models are routinely used to measure selective pressures acting on protein-coding genes. To this effect, the nonsynonymous to synonymous rate ratio (dN/dS = omega) is estimated. The proportion of amino-acid sites potentially under positive selection, as indicated by omega > 1, is inferred by fitting a probability distribution where some sites are permitted to have omega > 1. These sites are then inferred by means of an empirical Bayes or by a Bayes empirical Bayes approach that, respectively, ignores or accounts for sampling errors in maximum-likelihood estimates of the distribution used to infer the proportion of sites with omega > 1. Here, we extend a previous full-Bayes approach to include models with high power and low false-positive rates when inferring sites under positive selection. We propose some heuristics to alleviate the computational burden, and show that (i) full Bayes can be superior to empirical Bayes when analyzing a small data set or small simulated data, (ii) full Bayes has only a small advantage over Bayes empirical Bayes with our small test data, and (iii) Bayesian methods appear relatively insensitive to mild misspecifications of the random process generating adaptive evolution in our simulations, but in practice can prove extremely sensitive to model specification. We suggest that the codon model used to detect amino acids under selection should be carefully selected, for instance using Akaike information criterion (AIC).

Amino Acids↗

Determinants of adaptive evolution at the molecular level: the extended complexity hypothesis.

To explain why informational genes (i.e., those involved in transcription, translation, and related processes) are less likely than housekeeping genes to be horizontally transferred, Jain and coworkers proposed the complexity hypothesis. The underlying idea is that informational genes belong to large, complex systems of coevolving genes. Consequently, the likelihood of the successful horizontal transfer of a single gene from such an integrated system is expected to be low. Here, this hypothesis is extended to explain some of the determinants of the mode of evolution of coding sequences. It is proposed that genes belonging to complex systems are relatively less likely to be under adaptive evolution. To evaluate this "extended complexity hypothesis," 2,428 families and protein domains were analyzed. This analysis found that genes whose products are highly connected, located in intracellular components, and involved in complex processes and functions were more conserved and less likely to be under adaptive evolution than are other gene products. The extended complexity hypothesis suggests that both the mode and the rate of evolution of a protein are influenced by its gene ontology (localization, biological process, and molecular function) and by its connectivity.

Adaptation, Biological↗

How Bayes tests of molecular phylogenies compare with frequentist approaches.

MOTIVATION: The desire to compare molecular phylogenies has stimulated the design of numerous tests. Most of these tests are formulated in a frequentist framework, and it is not known how they compare with Bayes procedures. I propose here two new Bayes tests that either compare pairs of trees (Bayes hypothesis test, BHT), or test each tree against an average of the trees included in the analysis (Bayes significance test, BST). RESULTS: The algorithm, based on a standard Metropolis-Hastings sampler, integrates nuisance parameters out and estimates the probability of the data under each topology. These quantities are used to estimate Bayes factors for composite vs. composite hypotheses. Based on two data sets, the BHT and BST are shown to construct similar confidence sets to the bootstrap and the Shimodaira Hasegawa test, respectively. This suggests that the known difference among previous tests is mainly due to the null hypothesis considered.

Algorithms↗

Least and most powerful phylogenetic tests to elucidate the origin of the seed plants in the presence of conflicting signals under misspecified models.

Several tests of molecular phylogenies have been proposed over the last decades, but most of them lead to strikingly different P-values. I propose that such discrepancies are principally due to different forms of null hypotheses. To support this hypothesis, two new tests are described. Both consider the composite null hypothesis that all the topologies are equidistant from the true but unknown topology. This composite hypothesis can either be reduced to the simple hypothesis at the least favorable distribution (frequentist significance test [FST]) or to the maximum likelihood topology (frequentist hypothesis test [FHT]). In both cases, the reduced null hypothesis is tested against each topology included in the analysis. The tests proposed have an information-theoretic justification, and the distribution of their test statistic is estimated by a nonparametric bootstrap, adjusting P-values for multiple comparisons. I applied the new tests to the reanalysis of two chloroplast genes, psaA and psbB, and compared the results with those of previously described tests. As expected, the FST and the FHT behaved approximately like the Shimodaira-Hasegawa test and the bootstrap, respectively. Although the tests give overconfidence in a wrong tree when an overly simple nucleotide substitution model is assumed, more complex models incorporating heterogeneity among codon positions resolve some conflicts. To further investigate the influence of the null hypothesis, a power study was conducted. Simulations showed that FST and the Shimodaira-Hasegawa test are the least powerful and FHT is the most powerful across the parameter space. Although the size of all the tests is affected by misspecification, the two new tests appear more robust against misspecification of the model of evolution and consistently supported the hypothesis that the Gnetales are nested within gymnosperms.

Bayes Theorem↗

Effects of models of rate evolution on estimation of divergence dates with special reference to the metazoan 18S ribosomal RNA phylogeny.

The molecular clock, i.e., constancy of the rate of evolution over time, is commonly assumed in estimating divergence dates. However, this assumption is often violated and has drastic effects on date estimation. Recently, a number of attempts have been made to relax the clock assumption. One approach is to use maximum likelihood, which assigns rates to branches and allows the estimation of both rates and times. An alternative is the Bayes approach, which models the change of the rate over time. A number of models of rate change have been proposed. We have extended and evaluated models of rate evolution, i.e., the lognormal and its recent variant, along with the gamma, the exponential, and the Ornstein-Uhlenbeck processes. These models were first applied to a small hominoid data set, where an empirical Bayes approach was used to estimate the hyperparameters that measure the amount of rate variation. Estimation of divergence times was sensitive to these hyperparameters, especially when the assumed model is close to the clock assumption. The rate and date estimates varied little from model to model, although the posterior Bayes factor indicated the Ornstein-Uhlenbeck process outperformed the other models. To demonstrate the importance of allowing for rate change across lineages, this general approach was used to analyze a larger data set consisting of the 18S ribosomal RNA gene of 39 metazoan species. We obtained date estimates consistent with paleontological records, the deepest split within the group being about 560 million years ago. Estimates of the rates were in accordance with the Cambrian explosion hypothesis and suggested some more recent lineage-specific bursts of evolution.

Algorithms↗