Large-Scale Comparative Analysis of Codon Models Accounting for Protein and Nucleotide Selection

Molecular Footprints on Osmoregulation-Related Genes Associated with Freshwater Colonization by Cetaceans and Sirenians

The genetic basis underlying adaptive physiological mechanisms has been extensively explored in mammals after colonizing the seas. However, independent lineages of aquatic mammals exhibit complex patterns of secondary colonization in freshwater environments. This change in habitat represents new osmotic challenges, and additional changes in key systems, such as the osmoregulatory system, are expected. Here, we studied the selective regime on coding and regulatory regions of 20 genes related to the osmoregulation system in strict aquatic mammals from independent evolutionary lineages, cetaceans, and sirenians, with representatives in marine and freshwater aquatic environments. We identified positive selection signals in genes encoding the protein vasopressin (AVP) in mammalian lineages with secondary colonization in the fluvial environment and in aquaporins for lineages inhabiting the marine and fluvial environments. A greater number of sites with positive selection signals were found for the dolphin species compared to the Amazonian manatee. Only the AQP5 and AVP genes showed selection signals in more than one independent lineage of these mammals. Furthermore, the vasopressin gene tree indicates greater similarity in river dolphin sequences despite the independence of their lineages based on the species tree. Patterns of distribution and enrichment of Transcription Factors in the promoter regions of target genes were analyzed and appear to be phylogenetically conserved among sister species. We found accelerated evolution signs in genes ACE, AQP1, AQP5, AQP7, AVP, NPP4, and NPR1 for the fluvial mammals. Together, these results allow a greater understanding of the molecular bases of the evolution of genes responsible for osmotic control in aquatic mammals.

Evolutionary Shortcuts via Multinucleotide Substitutions and Their Impact on Natural Selection Analyses

Inference and interpretation of evolutionary processes, in particular of the types and targets of natural selection affecting coding sequences, are critically influenced by the assumptions built into statistical models and tests. If certain aspects of the substitution process (even when they are not of direct interest) are presumed absent or are modeled with too crude of a simplification, estimates of key model parameters can become biased, often systematically, and lead to poor statistical performance. Previous work established that failing to accommodate multinucleotide (or multihit, MH) substitutions strongly biases dN/dS-based inference towards false-positive inferences of diversifying episodic selection, as does failing to model variation in the rate of synonymous substitution (SRV) among sites. Here, we develop an integrated analytical framework and software tools to simultaneously incorporate these sources of evolutionary complexity into selection analyses. We found that both MH and SRV are ubiquitous in empirical alignments, and incorporating them has a strong effect on whether or not positive selection is detected (1.4-fold reduction) and on the distributions of inferred evolutionary rates. With simulation studies, we show that this effect is not attributable to reduced statistical power caused by using a more complex model. After a detailed examination of 21 benchmark alignments and a new high-resolution analysis showing which parts of the alignment provide support for positive selection, we show that MH substitutions occurring along shorter branches in the tree explain a significant fraction of discrepant results in selection detection. Our results add to the growing body of literature which examines decades-old modeling assumptions (including MH) and finds them to be problematic for comparative genomic data analysis. Because multinucleotide substitutions have a significant impact on natural selection detection even at the level of an entire gene, we recommend that selection analyses of this type consider their inclusion as a matter of routine. To facilitate this procedure, we developed, implemented, and benchmarked a simple and well-performing model testing selection detection framework able to screen an alignment for positive selection with two biologically important confounding processes: site-to-site synonymous rate variation, and multinucleotide instantaneous substitutions.

Evolution is not Uniform Along Coding Sequences

Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. Notably, amino acids located at the surface of proteins are known to evolve more rapidly than those in the core. In particular, amino acids at the N- and C-termini of protein sequences are likely to be more exposed than those at the core of the folded protein due to their location in the peptidic chain, and they are known to be less structured. Because of these reasons, we would expect that amino acids located at protein termini would evolve faster than residues located inside the chain. Here we test this hypothesis and found that amino acids evolve almost twice as fast at protein termini compared with those in the center, hinting at a strong topological bias along the sequence length. We further show that the distribution of solvent-accessible residues and functional domains in proteins readily explain how structural and functional constraints are weaker at their termini, leading to the observed excess of amino acid substitutions. Finally, we show that the specific evolutionary rates at protein termini may have direct consequences, notably misleading in silico methods used to infer sites under positive selection within genes. These results suggest that accounting for positional information should improve evolutionary models.

Next-generation development and application of codon model in evolution

To date, numerous nucleotide, amino acid, and codon substitution models have been developed to estimate the evolutionary history of any sequence/organism in a more comprehensive way. Out of these three, the codon substitution model is the most powerful. These models have been utilized extensively to detect selective pressure on a protein, codon usage bias, ancestral reconstruction and phylogenetic reconstruction. However, due to more computational demanding, in comparison to nucleotide and amino acid substitution models, only a few studies have employed the codon substitution model to understand the heterogeneity of the evolutionary process in a genome-scale analysis. Hence, there is always a question of how to develop more robust but less computationally demanding codon substitution models to get more accurate results. In this review article, the authors attempted to understand the basis of the development of different types of codon-substitution models and how this information can be utilized to develop more robust but less computationally demanding codon substitution models. The codon substitution model enables to detect selection regime under which any gene or gene region is evolving, codon usage bias in any organism or tissue-specific region and phylogenetic relationship between different lineages more accurately than nucleotide and amino acid substitution models. Thus, in the near future, these codon models can be utilized in the field of conservation, breeding and medicine.

Evaluation of Methods to Detect Shifts in Directional Selection at the Genome Scale

Identifying the footprints of selection in coding sequences can inform about the importance and function of individual sites. Analyses of the ratio of nonsynonymous to synonymous substitutions (dN/dS) have been widely used to pinpoint changes in the intensity of selection, but cannot distinguish them from changes in the direction of selection, that is, changes in the fitness of specific amino acids at a given position. A few methods that rely on amino-acid profiles to detect changes in directional selection have been designed, but their performances have not been well characterized. In this paper, we investigate the performance of six of these methods. We evaluate them on simulations along empirical phylogenies in which transition events have been annotated and compare their ability to detect sites that have undergone changes in the direction or intensity of selection to that of a widely used dN/dS approach, codeml's branch-site model A. We show that all methods have reduced performance in the presence of biased gene conversion but not CpG hypermutability. The best profile method, Pelican, a new implementation of Tamuri AU, Hay AJ, Goldstein RA. (2009. Identifying changes in selective constraints: host shifts in influenza. PLoS Comput Biol. 5(11):e1000564), performs as well as codeml in a range of conditions except for detecting relaxations of selection, and performs better when tree length increases, or in the presence of persistent positive selection. It is fast, enabling genome-scale searches for site-wise changes in the direction of selection associated with phenotypic changes.

X chromosomes show relaxed selection and complete somatic dosage compensation across Timema stick insect species

Sex chromosomes have evolved repeatedly across the tree of life. As they are present in different copy numbers in males and females, they are expected to experience different selection pressures than the autosomes, with consequences including a faster rate of evolution, increased accumulation of sexually antagonistic alleles and the evolution of dosage compensation. Whether these consequences are general or linked to idiosyncrasies of specific taxa is not clear as relatively few taxa have been studied thus far. Here, we use whole-genome sequencing to identify and characterize the evolution of the X chromosome in five species of Timema stick insects with XX:X0 sex determination. The X chromosome had a similar size (approximately 12% of the genome) and gene content across all five species, suggesting that the X chromosome originated prior to the diversification of the genus. Genes on the X showed evidence of relaxed selection (elevated dN/dS) and a slower evolutionary rate (dN + dS) than genes on the autosomes, likely due to sex-biased mutation rates. Genes on the X also showed almost complete dosage compensation in somatic tissues (heads and legs), but dosage compensation was absent in the reproductive tracts. Contrary to prediction, sex-biased genes showed little enrichment on the X, suggesting that the advantage X-linkage provides to the accumulation of sexually antagonistic alleles is weak. Overall, we found the consequences of X-linkage on gene sequences and expression to be similar across Timema species, showing the characteristics of the X chromosome are surprisingly consistent over 30 million years of evolution.

Dynamics of sex-biased gene expression during development in the stick insect Timema californicum

Sexually dimorphic phenotypes are thought to arise primarily from sex-biased gene expression during development. Major changes in developmental strategies, such as the shift from hemimetabolous to holometabolous development, are therefore expected to have profound consequences for the dynamics of sex-biased gene expression. However, no studies have previously examined sex-biased gene expression during development in hemimetabolous insects, precluding comparisons between developmental strategies. Here we characterized sex-biased gene expression at three developmental stages in a hemimetabolous stick insect (Timema californicum): hatchlings, juveniles, and adults. As expected, the proportion of sex-biased genes gradually increased during development, mirroring the gradual increase of phenotypic sexual dimorphism. Sex-biased genes identified at early developmental stages were generally consistently male- or female-biased at later stages, suggesting their importance in sexual differentiation. Additionally, we compared the dynamics of sex-biased gene expression during development in T. californicum to those of the holometabolous fly Drosophila melanogaster by reanalyzing publicly available RNA-seq data from third instar larval, pupal and adult stages. In D. melanogaster, 84% of genes were sex-biased at the adult stage (compared to only 20% in T. californicum), and sex-biased gene expression increased abruptly at the adult stage when morphological sexual dimorphism is manifested. Our findings are consistent with the prediction that the dynamics of sex-biased gene expression during development differ extensively between holometabolous and hemimetabolous insect species.

An ancient truncated duplication of the anti‐Mullerian hormone receptor type 2 gene is a potential conserved master sex determinant in the Pangasiidae catfish family

The evolution of sex determination (SD) in teleosts is amazingly dynamic, as reflected by the variety of different master sex-determining genes identified. Pangasiids are economically important catfishes in South Asian countries, but little is known about their SD system. Here, we generated novel genomic resources for 12 Pangasiids and characterized their SD system. Based on a Pangasianodon hypophthalmus chromosome-scale genome assembly, we identified an anti-Müllerian hormone receptor type Ⅱ gene (amhr2) duplication, which was further characterized as being sex-linked in males and expressed only in testes. These results point to a Y chromosome male-specific duplication (amhr2by) of the autosomal amhr2a. Sequence annotation revealed that the P. hypophthalmus Amhr2by is truncated in its N-terminal domain, lacking the cysteine-rich extracellular part of the receptor that is crucial for ligand binding, suggesting a potential route for its neofunctionalization. Reference-guided assembly of 11 additional Pangasiids, along with sex-linkage studies, revealed that this truncated amhr2by duplication is a male-specific conserved gene in Pangasiids. Reconstructions of the amhr2 phylogeny suggested that amhr2by arose from an ancient duplication/insertion event at the root of the Siluroidei radiation that is dated to ~100 million years ago. Together these results bring multiple lines of evidence supporting that amhr2by is an ancient and conserved master sex-determining gene in Pangasiids, a finding that highlights the recurrent use of the transforming growth factor β pathway, which is often used for the recruitment of teleost master SD genes, and provides another empirical case towards firther understanding of dynamics of SD systems.

Convergent consequences of parthenogenesis on stick insect genomes

The shift from sexual reproduction to parthenogenesis has occurred repeatedly in animals, but how the loss of sex affects genome evolution remains poorly understood. We generated reference genomes for five independently evolved parthenogenetic species in the stick insect genus Timema and their closest sexual relatives. Using these references and population genomic data, we show that parthenogenesis results in an extreme reduction of heterozygosity and often leads to genetically uniform populations. We also find evidence for less effective positive selection in parthenogenetic species, suggesting that sex is ubiquitous in natural populations because it facilitates fast rates of adaptation. Parthenogenetic species did not show increased transposable element (TE) accumulation, likely because there is little TE activity in the genus. By using replicated sexual-parthenogenetic comparisons, our study reveals how the absence of sex affects genome evolution in natural populations, providing empirical support for the negative consequences of parthenogenesis as predicted by theory.

The Evolutionary History of Vertebrate Adhesion GPCRs and Its Implication on Their Classification

Adhesion G protein-coupled receptors (aGPCRs) form a structurally separate class of GPCRs with an unresolved evolutionary history and classification. Based on phylogenetic relations of human aGPCRs, nine families (A-G, L, V) were distinguished. Taking advantage of available genome data, we determined the aGPCR repertoires in all vertebrate classes. Although most aGPCR families show a high numerical stability in vertebrate genomes, the full repertoire of family E, F, and G members appeared only after the fish-tetrapod split. We did not find any evidence for new aGPCR families in vertebrates which are not present in the human genome. Based on ortholog sequence alignments, selection analysis clearly indicated two types of tetrapod aGPCRs: (i) aGPCR under strong purifying selection in tetrapod evolution (families A, B, D, L, V); and (ii) aGPCR with signatures of positive selection in some tetrapod linages (families C, E, G, F). The alignments of aGPCRs also allowed for a revised definition of reference positions within the seven-transmembrane-helix domain (relative position numbering scheme). Based on our phylogenetic cluster analysis, we suggest a revised nomenclature of aGPCRs including their transcript variants. Herein, the former families E and L are combined to one family (L) and GPR128/ADGRG7 forms a separate family (E). Furthermore, our analyses provide valuable information about the (patho)physiological relevance of individual aGPCR members.

BASE: A novel workflow to integrate nonubiquitous genes in comparative genomics analyses for selection

Inferring the selective forces that orthologous genes underwent across different lineages can help us understand the evolutionary processes that have shaped their extant diversity and the phenotypes they underlie. The most widespread metric to estimate the selection regimes of coding genes-across sites and phylogenies-is the ratio of nonsynonymous to synonymous substitutions (dN/dS, also known as ω). Nowadays, modern sequencing technologies and the large amount of already available sequence data allow the retrieval of thousands of orthologous genes across large numbers of species. Nonetheless, the tools available to explore selection regimes are not designed to automatically process all genes, and their practical usage is often restricted to the single-copy ones which are found across all species considered (i.e., ubiquitous genes). This approach limits the scale of the analysis to a fraction of single-copy genes, which can be as low as an order of magnitude in respect to those which are not consistently found in all species considered (i.e., nonubiquitous genes). Here, we present a workflow named BASE that-leveraging the CodeML framework-eases the inference and interpretation of gene selection regimes in the context of comparative genomics. Although a number of bioinformatics tools have already been developed to facilitate this kind of analyses, BASE is the first to be specifically designed to allow the integration of nonubiquitous genes in a straightforward and reproducible manner. The workflow-along with all relevant documentation-is available at github.com/for-giobbe/BASE.

Inferring the number and position of changes in selective regime in a non-equilibrium mutation-selection framework

BACKGROUND

Recovering the historical patterns of selection acting on a protein coding sequence is a major goal of evolutionary biology. Mutation-selection models address this problem by explicitly modelling fixation rates as a function of site-specific amino acid fitness values.However, they are restricted in their utility for investigating directional evolution because they require prior knowledge of the locations of fitness changes in the lineages of a phylogeny.

RESULTS

We apply a modified mutation-selection methodology that relaxes assumptions of equlibrium and time-reversibility. Our implementation allows us to identify branches where adaptive or compensatory shifts in the fitness landscape have taken place, signalled by a change in amino acid fitness profiles. Through simulation and analysis of an empirical data set of [Formula: see text]-lactamase genes, we test our ability to recover the position of adaptive events within the tree and successfully reconstruct initial codon frequencies and fitness profile parameters generated under the non-stationary model.

CONCLUSION

We demonstrate successful detection of selective shifts and identification of the affected branch on partitions of 300 codons or more. We successfully reconstruct fitness parameters and initial codon frequencies in simulated data and demonstrate that failing to account for non-equilibrium evolution can increase the error in fitness profile estimation. We also demonstrate reconstruction of plausible shifts in amino acid fitnesses in the bacterial [Formula: see text]-lactamase family and discuss some caveats for interpretation.

The evolutionary history of manatees told by their mitogenomes

The manatee family encompasses three extant congeneric species: Trichechus senegalensis (African manatee), T. inunguis (Amazonian manatee), and T. manatus (West Indian manatee). The fossil record for manatees is scant, and few phylogenetic studies have focused on their evolutionary history. We use full mitogenomes of all extant manatee species to infer the divergence dates and biogeographical histories of these species and the effect of natural selection on their mitogenomes. The complete mitochondrial genomes of T. inunguis (16,851 bp), T. senegalensis (16,882 bp), and T. manatus (16,882 bp), comprise 13 protein-coding genes, 2 ribosomal RNA genes (rRNA - 12S and 16S), and 22 transfer RNA genes (tRNA), and (D-loop/CR). Our analyses show that the first split within Trichechus occurred during the Late Miocene (posterior mean 6.56 Ma and 95% HPD 3.81–10.66 Ma), followed by a diversification event in the Plio-Pleistocene (posterior mean 1.34 Ma, 95% HPD 0.1–4.23) in the clade composed by T. inunguis and T. manatus; T. senegalensis is the sister group of this clade with higher support values (pp > 0.90). The branch-site test identified positive selection on T. inunguis in the 181st position of the ND4 amino acid gene (LRT = 6.06, p = 0.0069, BEB posterior probability = 0.96). The ND4 gene encodes one subunit of the NADH dehydrogenase complex, part of the oxidative phosphorylation machinery. In conclusion, our results provide novel insight into the evolutionary history of the Trichechidae during the Late Miocene, which was influenced by geological events, such as Amazon Basin formation.

Nonsynonymous Polymorphism Counts in Bacterial Genomes: a Comparative Examination

Genomic data reveal single-nucleotide polymorphisms (SNPs) that may carry information about the evolutionary history of bacteria. However, it remains unclear what inferences about selection can be made from genomic SNP data. Bacterial species are often sampled during epidemic outbreaks or within hosts during the course of chronic infections. SNPs obtained from genomic analysis of these data are not necessarily fixed. Treating them as fixed during analysis by using measures such as the ratio of nonsynonymous to synonymous evolutionary changes (dN/dS) may lead to incorrect inferences about the strength and direction of selection. In this study, we consider data from a range of whole-genome sequencing studies of bacterial pathogens and explore patterns of nonsynonymous variation to assess whether evidence of selection can be identified by investigating SNP counts alone across multiple WGS studies. We visualize these SNP data in ways that highlight their relationship to neutral baseline expectations. These neutral expectations are based on a simple model of mutation, from which we simulate SNP accumulation to investigate how SNP counts are distributed under alternative assumptions about positive and negative selection. We compare these patterns with empirical SNP data and illustrate the general difficulty of detecting positive selection from SNP data. Finally, we consider whether SNP counts observed at the between-host population level differ from those observed at the within-host level and find some evidence that suggests that dynamics across these two scales are driven by different underlying processes.IMPORTANCE Identifying selection from SNP data obtained from whole-genome sequencing studies is challenging. Some current measures used to identify and quantify selection acting on genomes rely on fixed differences; thus, these are inappropriate for SNP data where variants are not fixed. With the increase in whole-genome sequencing studies, it is important to consider SNP data in the context of evolutionary processes. How SNPs are counted and analyzed can help in understanding mutation accumulation and trajectories of strains. We developed a tool for identifying possible evidence of selection and for comparative analysis with other SNP data. We propose a model that provides a rule-of-thumb guideline and two new visualization techniques that can be used to interpret and compare SNP data. We quantify the expected proportion of nonsynonymous SNPs in coding regions under neutrality and demonstrate its use in identifying evidence of positive and negative selection from simulations and empirical data.

Divergent genes in gerbils: prevalence, relation to GC-biased substitution, and phenotypic relevance

Background

Two gerbil species, sand rat (Psammomys obesus) and Mongolian jird (Meriones unguiculatus), can become obese and show signs of metabolic dysregulation when maintained on standard laboratory diets. The genetic basis of this phenotype is unknown. Recently, genome sequencing has uncovered very unusual regions of high guanine and cytosine (GC) content scattered across the sand rat genome, most likely generated by extreme and localized biased gene conversion. A key pancreatic transcription factor PDX1 is encoded by a gene in the most extreme GC-rich region, is remarkably divergent and exhibits altered biochemical properties. Here, we ask if gerbils have proteins in addition to PDX1 that are aberrantly divergent in amino acid sequence, whether they have also become divergent due to GC-biased nucleotide changes, and whether these proteins could plausibly be connected to metabolic dysfunction exhibited by gerbils.

Results

We analyzed ~ 10,000 proteins with 1-to-1 orthologues in human and rodents and identified 50 proteins that accumulated unusually high levels of amino acid change in the sand rat and 41 in Mongolian jird. We show that more than half of the aberrantly divergent proteins are associated with GC biased nucleotide change and many are in previously defined high GC regions. We highlight four aberrantly divergent gerbil proteins, PDX1, INSR, MEDAG and SPP1, that may plausibly be associated with dietary metabolism.

Conclusions

We show that through the course of gerbil evolution, many aberrantly divergent proteins have accumulated in the gerbil lineage, and GC-biased nucleotide substitution rather than positive selection is the likely cause of extreme divergence in more than half of these. Some proteins carry putatively deleterious changes that could be associated with metabolic and physiological phenotypes observed in some gerbil species. We propose that these animals provide a useful model to study the ‘tug-of-war’ between natural selection and the excessive accumulation of deleterious substitutions mutations through biased gene conversion.

Synonymous Site-to-Site Substitution Rate Variation Dramatically Inflates False Positive Rates of Selection Analyses: Ignore at Your Own Peril

Most molecular evolutionary studies of natural selection maintain the decades-old assumption that synonymous substitution rate variation (SRV) across sites within genes occurs at levels that are either nonexistent or negligible. However, numerous studies challenge this assumption from a biological perspective and show that SRV is comparable in magnitude to that of nonsynonymous substitution rate variation. We evaluated the impact of this assumption on methods for inferring selection at the molecular level by incorporating SRV into an existing method (BUSTED) for detecting signatures of episodic diversifying selection in genes. Using simulated data we found that failing to account for even moderate levels of SRV in selection testing is likely to produce intolerably high false positive rates. To evaluate the effect of the SRV assumption on actual inferences we compared results of tests with and without the assumption in an empirical analysis of over 13,000 Euteleostomi (bony vertebrate) gene alignments from the Selectome database. This exercise reveals that close to 50% of positive results (i.e., evidence for selection) in empirical analyses disappear when SRV is modeled as part of the statistical analysis and are thus candidates for being false positives. The results from this work add to a growing literature establishing that tests of selection are much more sensitive to certain model assumptions than previously believed.

Relaxed Selection and the Rapid Evolution of Reproductive Genes

Evolutionary genomic studies find that reproductive protein genes, those directly involved in reproductive processes, diversify more rapidly than most other gene categories. Strong postcopulatory sexual selection acting within species is the predominant hypothesis proposed to account for the observed pattern. Recently, relaxed selection due to sex-specific gene expression has also been put forward to explain the relatively rapid diversification. We contend that relaxed selection due to sex-limited gene expression is the correct null model for tests of molecular evolution of reproductive genes and argue that it may play a more significant role in the evolutionary diversification of reproductive genes than previously recognized. We advocate for a re-evaluation of adaptive explanations for the rapid diversification of reproductive genes.

Integrated structural and evolutionary analysis reveals common mechanisms underlying adaptive evolution in mammals

Understanding the molecular basis of adaptation to the environment is a central question in evolutionary biology, yet linking detected signatures of positive selection to molecular mechanisms remains challenging. Here we demonstrate that combining sequence-based phylogenetic methods with structural information assists in making such mechanistic interpretations on a genomic scale. Our integrative analysis shows that positively selected sites tend to colocalize on protein structures and that positively selected clusters are found in functionally important regions of proteins, indicating that positive selection can contravene the well-known principle of evolutionary conservation of functionally important regions. This unexpected finding, along with our discovery that positive selection acts on structural clusters, opens previously unexplored strategies for the development of better models of protein evolution. Remarkably, proteins where we detect the strongest evidence of clustering belong to just two functional groups: Components of immune response and metabolic enzymes. This gives a coherent picture of pathogens and xenobiotics as important drivers of adaptive evolution of mammals.