Biology subjects

Moutinho, A. F.

Publications and source records attributed to Moutinho, A. F..

4 recordsLinked to original sources

bioRxiv2022

The silent impact: codon usage bias and protein evolution in bacteria

Bias in synonymous codon usage has been reported across all kingdoms of life. Evidence across species suggests that codon usage bias is often driven by selective pressures, typically for translational efficiency. These selective pressures have been shown to depress the rate at which synonymous sites evolve. We hypothesise that selection on synonymous codon use could also slow the rate of protein evolution if two amino acids have different preferred codons. We test this hypothesis by looking at patterns of protein evolution using polymorphism and substitution data in bacteria. We found that non-synonymous mutations that change from unpreferred to preferred codons are more common than the opposite, but only amongst codons that vary substantially in their preference level. Overall, selection on codon bias seems to have little influence over non-synonymous polymorphism or substitution patterns.

evolutionary biology↗

bioRxiv2021

Site level factors that affect the rate of adaptive evolution in humans and chimpanzees; the effect of contracting population size.

It has previously been shown in other species that the rate of adaptive evolution is higher at sites that are more exposed in a protein structure and lower between amino acid pairs that are more dissimilar. We have investigated whether these patterns are found in the divergence between humans and chimpanzees using an extension of the MacDonald-Kreitman test. We confirm previous findings and find that the rate of adaptive evolution, relative to the rate of mutation, is higher for more exposed amino acids, lower for amino acid pairs that are more dissimilar in terms of their polarity, volume and lower for amino acid pairs that are subject to stronger purifying selection, as measured by the ratio of the numbers of non-synonymous to synonymous polymorphisms (pN /pS). However, the slope of this latter relationship is significantly shallower than in Drosophila species. We suggest that this is due to the population contraction that has occurred since humans and chimpanzees diverged. We demonstrate theoretically that population size reduction can generate an artefactual positive correlation between the rate of adaptive evolution and any factor that is correlated to the mean strength of selection acting against deleterious mutations, even if there has been no adaptive evolution (the converse is also expected). Our measure of selective constraint, pN /pS, is negatively correlated to the mean strength of selection, and hence we would expect the correlation between the rate of adaptive evolution to also be negatively correlated to pN /pS, if there is no adaptive evolution. The fact that our rate of adaptive evolution is positively correlated to pN /pS suggests that the correlation does genuinely exist, but that is has been attenuated by population size contraction.

evolutionary biology↗

bioRxiv2021

Testing the adaptive walk model of gene evolution

Understanding the dynamics of species adaptation to their environments has long been a central focus of the study of evolution. Theories of adaptation propose that populations evolve by "walking" in a fitness landscape. This "adaptive walk" is characterised by a pattern of diminishing returns, where populations further away from their fitness optimum take larger steps than those closer to their optimal conditions. Hence, we expect young genes to evolve faster and experience mutations with stronger fitness effects than older genes because they are further away from their fitness optimum. Testing this hypothesis, however, constitutes an arduous task. Young genes are small, encode proteins with a higher degree of intrinsic disorder, are expressed at lower levels, and are involved in species-specific adaptations. Since all these factors lead to increased protein evolutionary rates, they could be masking the effect of gene age. While controlling for these factors, we used population genomic datasets of Arabidopsis and Drosophila and estimated the rate of adaptive substitutions across genes from different phylostrata. We found that a genes evolutionary age significantly impacts the molecular rate of adaptation. Moreover, we observed that substitutions in young genes tend to have larger physicochemical effects. Our study, therefore, provides strong evidence that molecular evolution follows an adaptive walk model across a large evolutionary timescale.

evolutionary biology↗

bioRxiv2019

The impact of protein architecture on adaptive evolution

Adaptive mutations play an important role in molecular evolution. However, the frequency and nature of these mutations at the intra-molecular level is poorly understood. To address this, we analysed the impact of protein architecture on the rate of adaptive substitutions, aiming to understand how protein biophysics influences fitness and adaptation. Using Drosophila melanogaster and Arabidopsis thaliana population genomics data, we fitted models of distribution of fitness effects and estimated the rate of adaptive amino-acid substitutions both at the protein and amino-acid residue level. We performed a comprehensive analysis covering genome, gene and protein structure, by exploring a multitude of factors with a plausible impact on the rate of adaptive evolution, such as intron number, protein length, secondary structure, relative solvent accessibility, intrinsic protein disorder, chaperone affinity, gene expression, protein function and protein-protein interactions. We found that the relative solvent accessibility is a major driver of adaptive evolution, with most adaptive mutations occurring at the surface of proteins. Moreover, we observe that the rate of adaptive substitutions differs between protein functional classes, with genes encoding for protein biosynthesis and degradation signalling exhibiting the fastest rates of protein adaptation. Overall, our results suggest that adaptive evolution in proteins is mainly driven by inter-molecular interactions, with host-pathogen coevolution likely playing a major role.

evolutionary biology↗