An empirical codon model for protein sequence evolution

In the past, 2 kinds of Markov models have been considered to describe protein sequence evolution. Codon-level models have been mechanistic with a small number of parameters designed to take into account features, such as transition-transversion bias, codon frequency bias, and synonymous-nonsynonymous amino acid substitution bias. Amino acid models have been empirical, attempting to summarize the replacement patterns observed in large quantities of data and not explicitly considering the distinct factors that shape protein evolution. We have estimated the first empirical codon model (ECM). Previous codon models assume that protein evolution proceeds only by successive single nucleotide substitutions, but our results indicate that model accuracy is significantly improved by incorporating instantaneous doublet and triplet changes. We also find that the affiliations between codons, the amino acid each encodes and the physicochemical properties of the amino acids are main factors driving the process of codon evolution. Neither multiple nucleotide changes nor the strong influence of the genetic code nor amino acids' physicochemical properties form a part of standard mechanistic models and their views of how codon evolution proceeds. We have implemented the ECM for likelihood-based phylogenetic analysis, and an assessment of its ability to describe protein evolution shows that it consistently outperforms comparable mechanistic codon models. We point out the biological interpretation of our ECM and possible consequences for studies of selection.     

A thermodynamic model of protein structure evolution explains empirical amino acid substitution matrices

Proteins evolve under a myriad of biophysical selection pressures that collectively control the patterns of amino acid substitutions. These evolutionary pressures are sufficiently consistent over time and across protein families to produce substitution patterns, summarized in global amino acid substitution matrices such as BLOSUM, JTT, WAG, and LG, which can be used to successfully detect homologs, infer phylogenies, and reconstruct ancestral sequences. Although the factors that govern the variation of amino acid substitution rates have received much attention, the influence of thermodynamic stability constraints remains unresolved. Here we develop a simple model to calculate amino acid substitution matrices from evolutionary dynamics controlled by a fitness function that reports on the thermodynamic effects of amino acid mutations in protein structures. This hybrid biophysical and evolutionary model accounts for nucleotide transition/transversion rate bias, multi‐nucleotide codon changes, the number of codons per amino acid, and thermodynamic protein stability. We find that our theoretical model accurately recapitulates the complex yet universal pattern observed in common global amino acid substitution matrices used in phylogenetics. These results suggest that selection for thermodynamically stable proteins, coupled with nucleotide mutation bias filtered by the structure of the genetic code, is the primary driver behind the global amino acid substitution patterns observed in proteins throughout the tree of life.     

Contrasting Patterns in the Early Stage of SARS-CoV-2 Evolution between Humans and Minks

One of the unique features of SARS-CoV-2 is its apparent neutral evolution during the early pandemic (before February 2020). This contrasts with the preceding SARS-CoV epidemics, where viruses evolved adaptively. SARS-CoV-2 may exhibit a unique or adaptive feature which deviates from other coronaviruses. Alternatively, the virus may have been cryptically circulating in humans for a sufficient time to have acquired adaptive changes before the onset of the current pandemic. To test the scenarios above, we analyzed the SARS-CoV-2 sequences from minks (Neovision vision) and parental humans. In the early phase of the mink epidemic (April to May 2020), nonsynonymous to synonymous mutation ratio per site in the spike protein is 2.93, indicating a selection process favoring adaptive amino acid changes. Mutations in the spike protein were concentrated within its receptor-binding domain and receptor-binding motif. An excess of high-frequency derived variants produced by genetic hitchhiking was found during the middle (June to July 2020) and late phase I (August to September 2020) of the mink epidemic. In contrast, the site frequency spectra of early SARS-CoV-2 in humans only show an excess of low-frequency mutations, consistent with the recent outbreak of the virus. Strong positive selection in the mink SARS-CoV-2 implies that the virus may not be preadapted to a wide range of hosts and illustrates how a virus evolves to establish a continuous infection in a new host. Therefore, the lack of positive selection signal during the early pandemic in humans deserves further investigation.     

A Bayesian model comparison approach to inferring positive selection

A popular approach to detecting positive selection is to estimate the parameters of a probabilistic model of codon evolution and perform inference based on its maximum likelihood parameter values. This approach has been evaluated intensively in a number of simulation studies and found to be robust when the available data set is large. However, uncertainties in the estimated parameter values can lead to errors in the inference, especially when the data set is small or there is insufficient divergence between the sequences. We introduce a Bayesian model comparison approach to infer whether the sequence as a whole contains sites at which the rate of nonsynonymous substitution is greater than the rate of synonymous substitution. We incorporated this probabilistic model comparison into a Bayesian approach to site-specific inference of positive selection. Using simulated sequences, we compared this approach to the commonly used empirical Bayes approach and investigated the effect of tree length on the performance of both methods. We found that the Bayesian approach outperforms the empirical Bayes method when the amount of sequence divergence is small and is less prone to false-positive inference when the sequences are saturated, while the results are indistinguishable for intermediate levels of sequence divergence.     

Models of protein sequence evolution and their applications

Homologous sequences are correlated due to their common ancestry. Probabilistic models of sequence evolution are employed routinely to properly account for these phylogenetic correlations. These increasingly realistic models provide a basis for studying evolution and for exploiting it to better understand protein structure and function. Notable recent advances have been made in the treatment of insertion and deletion events, the estimation of amino-acid replacement rates, and the detection of positive selection.     

Phylogenetic Analysis and Selection Pressures of 5-HT Receptors in Human and Non-human Primates: Receptor of an Ancient Neurotransmitter

Abstract

Neurotransmitter serotonin (5-hydroxytryptamine, 5-HT) an ancient neurotransmitter, involved in several neurophysiological and behavioral functions, acts by interacting with multiple receptors (5-HT₁-5-HT₇). Alterations in serotonergic signalling have also been implicated in various psychiatric disorders. The availability of the genome data of nonhuman primates permits comparative analysis of human 5-HT receptors with sequences of non-human primates to understand evolutionary divergence. We compared and analyzed serotonergic receptor sequences from human and non-human primates. Phylogenetic analysis by Maximum Likelihood (ML) method classified human and primate 5-HT receptors into six unique clusters. There was considerable conservation of 5-HT receptor sequences between human and non-human primates; however, a greater diversity at the sub-group level was observed. Compared to the other subgroups, larger multiplicity and expansion was seen within the 5-HT₄ receptor subtype in both human and non-human primates. Analysis of non-synonymous and synonymous substitution ratios (Ka/Ks ratio) using the Nei-Gojobori method suggests that 5-HT receptor sequences have undergone negative (purifying) selection over the course of evolution in human, chimpanzee and rhesus monkey. Abnormal human and non-human primate psychopathalogy and behavior, in the context of these variations is discussed. Analysis of these 5-HT receptors in other species will help understand the molecular evolution of 5-HT receptors, and its possible influence on complex behaviors, and psychiatric disorders.     

Species-specific size expansion and molecular evolution of the oleosins in angiosperms

Oleosins are hydrophobic plant proteins thought to be important for the formation of oil bodies, which supply energy for seed germination and subsequent seedling growth. To better understand the evolutionary history and diversity of the oleosin gene family in plants, especially angiosperms, we systematically investigated the molecular evolution of this family using eight representative angiosperm species. A total of 73 oleosin members were identified, with six members in each of four monocot species and a greater but variable number in the four eudicots. A phylogenetic analysis revealed that the angiosperm oleosin genes belonged to three monophyletic lineages. Species-specific gene duplications, caused mainly by segmental duplication, led to the great expansion of oleosin genes and occurred frequently in eudicots after the monocot–eudicot divergence. Functional divergence analyses indicate that significant amino acid site-specific selective constraints acted on the different clades of oleosins. Adaptive evolution analyses demonstrate that oleosin genes were subject to strong purifying selection after their species-specific duplications and that rapid evolution occurred with a high degree of evolutionary dynamics in the pollen-specific oleosin genes. In conclusion, this study serves as a foundation for genome-wide analyses of the oleosins. These findings provide insight into the function and evolution of this gene family in angiosperms and pave the way for studies in other plants.