Detecting positive and purifying selection at synonymous sites in yeast and worm

Synonymous edits in the Escherichia coli genome have substantial and condition-dependent effects on fitness

CRISPR-Cas-based genome editing is widely used in bacteria at scales ranging from construction of individual mutants to massively parallel libraries. This procedure relies on guide RNA-directed cleavage of the genome followed by repair with a template that introduces a desired mutation along with synonymous "immunizing" mutations to prevent re-cleavage of the genome after editing. Because the immunizing mutations do not change the protein sequence, they are often assumed to be neutral. However, synonymous mutations can change mRNA structures in ways that alter levels of the encoded proteins. We have tested the assumption that immunizing mutations are neutral by constructing a library of over 50,000 edits that consist of only synonymous mutations in Escherichia coli. Thousands of edits had substantial effects on fitness during growth of E. coli on acetate, a poor carbon source that is toxic at high concentrations. The percentage of high-impact edits varied considerably between genes and at different positions within genes. We reconstructed clones with high-impact edits and found that 69% indeed had significant effects on growth in acetate. Interestingly, fewer edits affected fitness during growth in glucose, a preferred carbon source, suggesting that changes in protein expression caused by synonymous mutations may be most important when an organism encounters challenging conditions. Finally, we showed that synonymous edits can have widespread effects; a synonymous edit at the 5' end of ptsI altered expression of hundreds of genes. Our results suggest that the synonymous immunizing edits introduced during CRISPR-Cas-based genome editing should not be assumed to be innocuous.

Deleterious Variation in Natural Populations and Implications for Conservation Genetics

Deleterious mutations decrease reproductive fitness and are ubiquitous in genomes. Given that many organisms face ongoing threats of extinction, there is interest in elucidating the impact of deleterious variation on extinction risk and optimizing management strategies accounting for such mutations. Quantifying deleterious variation and understanding the effects of population history on deleterious variation are complex endeavors because we do not know the strength of selection acting on each mutation. Further, the effect of demographic history on deleterious mutations depends on the strength of selection against the mutation and the degree of dominance. Here we clarify how deleterious variation can be quantified and studied in natural populations. We then discuss how different demographic factors, such as small population size, nonequilibrium population size changes, inbreeding, and gene flow, affect deleterious variation. Lastly, we provide guidance on studying deleterious variation in nonmodel populations of conservation concern.

No evidence for widespread positive selection on double substitutions within codons in primates and yeasts

Nucleotide substitutions in protein-coding genes can be divided into synonymous (S) and non-synonymous (N) ones that alter amino acids (including nonsense mutations causing stop codons). The S substitutions are expected to have little effect on function. The N substitutions almost always are affected by strong purifying selection that eliminates them from evolving populations. However, additional mutations of nearby bases can modulate the deleterious effect of single N substitutions and, thus, could be subjected to the positive selection. This effect has been demonstrated for mutations in the serine codons, stop codons and double N substitutions in prokaryotes. In all abovementioned cases, a novel technique was applied that allows elucidating the effects of selection on double substitutions considering mutational biases. Here, we applied the same technique to study double N substitutions in eukaryotic lineages of primates and yeast. We identified markedly fewer cases of purifying selection relative to prokaryotes and no evidence of codon double substitutions under positive selection. This is consistent with previous studies of serine codons in primates and yeast. In general, the obtained results strongly suggest that there are major differences between studied pro- and eukaryotes; double substitutions in primates and yeasts largely reflect mutational biases and are not hallmarks of selection. This is especially important in the context of detection of positive selection in codons because it has been suggested that multiple mutations in codons cause false inferences of lineage-specific site positive selection. It is likely that this concern is applicable to previously studied prokaryotes but not to primates and yeasts where markedly fewer double substitutions are affected by positive selection.

Genome Wide Identification and Annotation of NGATHA Transcription Factor Family in Crop Plants

The NGATHA (NGA) transcription factor (TF) belongs to the ABI3/VP1 (RAV) transcriptional subfamily, a subgroup of the B3 superfamily, which is relatively well-studied in Arabidopsis. However, limited data are available on the contributions of NGA TF in other plant species. In this study, 207 NGA gene family members were identified from a genome-wide search against Arabidopsis thaliana in the genome data of 18 dicots and seven monocots. The phylogenetic and sequence alignment analyses divided NGA genes into different clusters and revealed that the numbers of genes varied depending on the species. The phylogeny was followed by the characterization of the Solanaceae (tomato, potato, capsicum, tobacco) and Poaceae (Brachypodium distachyon, Oryza sativa L. japonica, and Sorghum bicolor) family members in comparison with A. thaliana. The gene and protein structures revealed a similar pattern for NGA and NGA-like sequences, suggesting that both are conserved during evolution. Promoter cis-element analysis showed that phytohormones such as abscisic acid, auxin, and gibberellins play a crucial role in regulating the NGA gene family. Gene ontology analysis revealed that the NGA gene family participates in diverse biological processes such as flower development, leaf morphogenesis, and the regulation of transcription. The gene duplication analysis indicates that most of the genes are evolved due to segmental duplications and have undergone purifying selection pressure. Finally, the gene expression analysis implicated that the NGA genes are abundantly expressed in lateral organs and flowers. This analysis has presented a detailed and comprehensive study of the NGA gene family, providing basic knowledge of the gene, protein structure, function, and evolution. These results will lay the foundation for further understanding of the role of the NGA gene family in various plant developmental processes.

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Effects of synonymous mutations beyond codon bias: The evidence for adaptive synonymous substitutions from microbial evolution experiments

Synonymous mutations are often assumed to be neutral with respect to fitness because they do not alter the encoded amino acid and so cannot be 'seen' by natural selection. Yet a growing body of evidence suggests that synonymous mutations can have fitness effects that drive adaptive evolution through their impacts on gene expression and protein folding. Here, we review what microbial experiments have taught us about the contribution of synonymous mutations to adaptation. A survey of site-directed mutagenesis experiments reveals the distributions of fitness effects for nonsynonymous and synonymous mutations are more similar, especially for beneficial mutations, than expected if all synonymous mutations were neutral, suggesting they should drive adaptive evolution more often than is typically observed. A review of experimental evolution studies where synonymous mutations have contributed to adaptation shows they can impact fitness through a range of mechanisms including the creation of illicit RNA polymerase binding sites impacting transcription and changes to mRNA folding stability that modulate translation. We suggest that clonal interference in evolving microbial populations may be the reason synonymous mutations play a smaller role in adaptive evolution than expected based on their observed fitness effects. We finish by discussing the impacts of falsely assuming synonymous mutations are neutral and discuss directions for future work exploring the role of synonymous mutations in adaptive evolution.

Avoidance of protein unfolding constrains protein stability in long-term evolution

Every amino acid residue can influence a protein's overall stability, making stability highly susceptible to change throughout evolution. We consider the distribution of protein stabilities evolutionarily permittable under two previously reported protein fitness functions: flux dynamics and misfolding avoidance. We develop an evolutionary dynamics theory and find that it agrees better with an extensive protein stability data set for dihydrofolate reductase orthologs under the misfolding avoidance fitness function rather than the flux dynamics fitness function. Further investigation with ribonuclease H data demonstrates that not any misfolded state is avoided; rather, it is only the unfolded state. At the end, we discuss how our work pertains to the universal protein abundance-evolutionary rate correlation seen across organisms' proteomes. We derive a closed-form expression relating protein abundance to evolutionary rate that captures Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens experimental trends without fitted parameters.

Analysis of selection in protein-coding sequences accounting for common biases

The evolution of protein-coding genes is usually driven by selective processes, which favor some evolutionary trajectories over others, optimizing the subsequent protein stability and activity. The analysis of selection in this type of genetic data is broadly performed with the metric nonsynonymous/synonymous substitution rate ratio (dN/dS). However, most of the well-established methodologies to estimate this metric make crucial assumptions, such as lack of recombination or invariable codon frequencies along genes, which can bias the estimation. Here, we review the most relevant biases in the dN/dS estimation and provide a detailed guide to estimate this metric using state-of-the-art procedures that account for such biases, along with illustrative practical examples and recommendations. We also discuss the traditional interpretation of the estimated dN/dS emphasizing the importance of considering complementary biological information such as the role of the observed substitutions on the stability and function of proteins. This review is oriented to help evolutionary biologists that aim to accurately estimate selection in protein-coding sequences.

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.

Identifying the drivers of computationally detected correlated evolution among sites under antibiotic selection

The ultimate causes of correlated evolution among sites in a genome remain difficult to tease apart. To address this problem directly, we performed a high-throughput search for correlated evolution among sites associated with resistance to a fluoroquinolone antibiotic using whole-genome data from clinical strains of Pseudomonas aeruginosa, before validating our computational predictions experimentally. We show that for at least two sites, this correlation is underlain by epistasis. Our analysis also revealed eight additional pairs of synonymous substitutions displaying correlated evolution underlain by physical linkage, rather than selection associated with antibiotic resistance. Our results provide direct evidence that both epistasis and physical linkage among sites can drive the correlated evolution identified by high-throughput computational tools. In other words, the observation of correlated evolution is not by itself sufficient evidence to guarantee that the sites in question are epistatic; such a claim requires additional evidence, ideally coming from direct estimates of epistasis, based on experimental evidence.

A comprehensive analysis of the B3 superfamily identifies tissue-specific and stress-responsive genes in chickpea (Cicer arietinum L.)

The aim of this study was to provide a comprehensive analysis of the plant-specific B3 domain-containing transcription factors (TFs) in chickpea. Scanning of the chickpea genome resulted in the identification of 51 B3 domain-containing TFs that were located on seven out of eight chickpea chromosomes. Based on the presence of additional domains other than the B3 domain, the candidates were classified into four subfamilies, i.e., ARF (24), REM (19), LAV (6) and RAV (2). Phylogenetic analysis classified them into four groups in which members of the same group had similar intron-exon organization and motif composition. Genome duplication analysis of the candidate B3 genes revealed an event of segmental duplication that was instrumental in the expansion of the B3 gene family. Ka/Ks analysis showed that the B3 gene family was under purifying selection. Further, chickpea B3 genes showed maximum orthology with Medicago followed by soybean and Arabidopsis. Promoter analyses of the B3 genes led to the identification of several tissue-specific and stress-responsive cis-regulatory elements. Expression profiling of the candidate B3 genes using publicly available RNA-seq data of several chickpea tissues indicated their putative role in plant development and abiotic stress response. These findings were further validated by real-time expression analysis. Overall, this study provides a comprehensive analysis of the B3 domain-containing proteins in chickpea that would aid in devising strategies for crop manipulation in chickpea.

Pituitary adenylate cyclase-activating polypeptide in the testis of the quail Coturnix coturnix: Expression, localization, and phylogenetic analysis

To evaluate the involvement of pituitary adenylate cyclase-activating polypeptide (PACAP)/receptors system in the control of testis activity, we have investigated the expression and localization of PACAP and the distribution of its receptors in the testis of mature samples of quail Coturnix coturnix, and we have performed a phylogenetic analysis of PACAP in birds. Using histological, molecular, and bioinformatics tools, we demonstrated that (a) PACAP messenger RNA shows a high sequence identity with that reported in other birds studied so far and in other vertebrates. Furthermore, we showed that purifying selection acts on PACAP; (b) the PACAP peptide is present only in Leydig cells, whereas its receptors are localized within both Leydig and germ cells; (c) the synthesis of PACAP does not take place in seminiferous tubules. The role of PACAP in the control of spermatogenesis and steroidogenesis in birds is discussed. Finally, we talk about the phylogenetic and evolutionary relationships between PACAP in birds and in other vertebrates.

Evolutionary insights of Bean common mosaic necrosis virus and Cowpea aphid-borne mosaic virus

Plant viral diseases are one of the major limitations in legume production within sub-Saharan Africa (SSA), as they account for up to 100% in production losses within smallholder farms. In this study, field surveys were conducted in the western highlands of Kenya with viral symptomatic leaf samples collected. Subsequently, next-generation sequencing was carried out to gain insights into the molecular evolution and evolutionary relationships of Bean common mosaic necrosis virus (BCMNV) and Cowpea aphid-borne mosaic virus (CABMV) present within symptomatic common bean and cowpea. Eleven near-complete genomes of BCMNV and two for CABMV were obtained from western Kenya. Bayesian phylogenomic analysis and tests for differential selection pressure within sites and across tree branches of the viral genomes were carried out. Three well-supported clades in BCMNV and one supported clade for CABMNV were resolved and in agreement with individual gene trees. Selection pressure analysis within sites and across phylogenetic branches suggested both viruses were evolving independently, but under strong purifying selection, with a slow evolutionary rate. These findings provide valuable insights on the evolution of BCMNV and CABMV genomes and their relationship to other viral genomes globally. The results will contribute greatly to the knowledge gap involving the phylogenomic relationship of these viruses, particularly for CABMV, for which there are few genome sequences available, and inform the current breeding efforts towards resistance for BCMNV and CABMV.

Selection Acting on Genomes

Populations evolve as mutations arise in individual organisms and, through hereditary transmission, may become "fixed" (shared by all individuals) in the population. Most mutations are lethal or have negative fitness consequences for the organism. Others have essentially no effect on organismal fitness and can become fixed through the neutral stochastic process known as random drift. However, mutations may also produce a selective advantage that boosts their chances of reaching fixation. Regions of genomes where new mutations are beneficial, rather than neutral or deleterious, tend to evolve more rapidly due to positive selection. Genes involved in immunity and defense are a well-known example; rapid evolution in these genes presumably occurs because new mutations help organisms to prevail in evolutionary "arms races" with pathogens. In recent years genome-wide scans for selection have enlarged our understanding of the genome evolution of various species. In this chapter, we will focus on methods to detect selection on the genome. In particular, we will discuss probabilistic models and how they have changed with the advent of new genome-wide data now available.

Population genomics of parallel evolution in gene expression and gene sequence during ecological adaptation

Natural selection often produces parallel phenotypic changes in response to a similar adaptive challenge. However, the extent to which parallel gene expression differences and genomic divergence underlie parallel phenotypic traits and whether they are decoupled or not remains largely unexplored. We performed a population genomic study of parallel ecological adaptation among replicate ecotype pairs of the rough periwinkle (Littorina saxatilis) at a regional geographical scale (NW Spain). We show that genomic changes underlying parallel phenotypic divergence followed a complex pattern of both repeatable differences and of differences unique to specific ecotype pairs, in which parallel changes in expression or sequence are restricted to a limited set of genes. Yet, the majority of divergent genes were divergent either for gene expression or coding sequence, but not for both simultaneously. Overall, our findings suggest that divergent selection significantly contributed to the process of parallel molecular differentiation among ecotype pairs, and that changes in expression and gene sequence underlying phenotypic divergence could, at least to a certain extent, be considered decoupled processes.

The Contribution of Purifying Selection, Linkage, and Mutation Bias to the Negative Correlation between Gene Expression and Polymorphism Density in Yeast Populations

The negative correlation between the rate of protein evolution and expression level of a gene has been recognized as a universal law of the evolutionary biology (Koonin 2011). In our study, we apply a population-based approach to systematically investigate the relative importance of unequal mutation rate, linkage, and selection in the origin of the expression-polymorphism anticorrelation. We analyzed the DNA sequence of protein coding genes of 24 Saccharomyces cerevisiae and 58 Schizosaccharomyces pombe strains. We found that highly expressed genes had a substantially decreased number of polymorphic sites when compared with genes transcribed less extensively. This expression-dependent reduction was especially strong in the nonsynonymous sites, although it was also present in the synonymous sites and untranslated regions, both up and down of a gene. Most importantly, no such trend was found in introns. We used these observations, as well as analyses of site frequency spectra and data from mutation accumulation experiments, to show that the purifying selection acting on nonsynonymous sites was the main, but not exclusive, factor impeding molecular evolution within the coding sequences of highly expressed genes. Linkage could not fully explain the observed pattern of polymorphism within the untranslated regions and synonymous sites, although the contribution of selection acting directly on synonymous variants was extremely small. Finally, we found that the impact of mutational bias was rather negligible.

Co-evolutionary interactions between host resistance and pathogen avirulence genes in rice-Magnaporthe oryzae pathosystem

Rice and Magnaporthe oryzae constitutes an ideal pathosystem for studying host-pathogen interaction in cereals crops. There are two alternative hypotheses, viz. Arms race and Trench warfare, which explain the co-evolutionary dynamics of hosts and pathogens which are under continuous confrontation. Arms race proposes that both R- and Avr- genes of host and pathogen, respectively, undergo positive selection. Alternatively, trench warfare suggests that either R- or Avr- gene in the pathosystem is under balanced selection intending to stabilize the genetic advantage gained over the opposition. Here, we made an attempt to test the above-stated hypotheses in rice-M. oryzae pathosystem at loci of three R-Avr gene pairs, Piz-t-AvrPiz-t, Pi54-AvrPi54 and Pita-AvrPita using allele mining approach. Allele mining is an efficient way to capture allelic variants existing in the population and to study the selective forces imposed on the variants during evolution. Results of nucleotide diversity, neutrality statistics and phylogenetic analyses reveal that Piz-t, Pi54 and AvrPita are diversified and under positive selection at their corresponding loci, while their counterparts, AvrPiz-t, AvrPi54 and Pita are conserved and under balancing selection, in nature. These results imply that rice-M. oryzae populations are engaged in a trench warfare at least at the three R/Avr loci studied. It is a maiden attempt to study the co-evolution of three R-Avr gene pairs in this pathosystem. Knowledge gained from this study will help in understanding the evolutionary dynamics of host-pathogen interaction in a better way and will also aid in developing new durable blast resistant rice varieties in future.

Synonymous Mutations at the Beginning of the Influenza A Virus Hemagglutinin Gene Impact Experimental Fitness

The fitness effects of synonymous mutations can provide insights into biological and evolutionary mechanisms. We analyzed the experimental fitness effects of all single-nucleotide mutations, including synonymous substitutions, at the beginning of the influenza A virus hemagglutinin (HA) gene. Many synonymous substitutions were deleterious both in bulk competition and for individually isolated clones. Investigating protein and RNA levels of a subset of individually expressed HA variants revealed that multiple biochemical properties contribute to the observed experimental fitness effects. Our results indicate that a structural element in the HA segment viral RNA may influence fitness. Examination of naturally evolved sequences in human hosts indicates a preference for the unfolded state of this structural element compared to that found in swine hosts. Our overall results reveal that synonymous mutations may have greater fitness consequences than indicated by simple models of sequence conservation, and we discuss the implications of this finding for commonly used evolutionary tests and analyses.

Differences in the genetic control of early egg development and reproduction between C. elegans and its parthenogenetic relative D. coronatus

BACKGROUND

The free-living nematode Diploscapter coronatus is the closest known relative of Caenorhabditis elegans with parthenogenetic reproduction. It shows several developmental idiosyncracies, for example concerning the mode of reproduction, embryonic axis formation and early cleavage pattern (Lahl et al. in Int J Dev Biol 50:393-397, 2006). Our recent genome analysis (Hiraki et al. in BMC Genomics 18:478, 2017) provides a solid foundation to better understand the molecular basis of developmental idiosyncrasies in this species in an evolutionary context by comparison with selected other nematodes. Our genomic data also yielded indications for the view that D. coronatus is a product of interspecies hybridization.

RESULTS

In a genomic comparison between D. coronatus, C. elegans, other representatives of the genus Caenorhabditis and the more distantly related Pristionchus pacificus and Panagrellus redivivus, certain genes required for central developmental processes in C. elegans like control of meiosis and establishment of embryonic polarity were found to be restricted to the genus Caenorhabditis. The mRNA content of early D. coronatus embryos was sequenced and compared with similar stages in C. elegans and Ascaris suum. We identified 350 gene families transcribed in the early embryo of D. coronatus but not in the other two nematodes. Looking at individual genes transcribed early in D. coronatus but not in C. elegans and A. suum, we found that orthologs of most of these are present in the genomes of the latter species as well, suggesting heterochronic shifts with respect to expression behavior. Considerable genomic heterozygosity and allelic divergence lend further support to the view that D. coronatus may be the result of an interspecies hybridization. Expression analysis of early acting single-copy genes yields no indication for silencing of one parental genome.

CONCLUSIONS

Our comparative cellular and molecular studies support the view that the genus Caenorhabditis differs considerably from the other studied nematodes in its control of development and reproduction. The easy-to-culture parthenogenetic D. coronatus, with its high-quality draft genome and only a single chromosome when haploid, offers many new starting points on the cellular, molecular and genomic level to explore alternative routes of nematode development and reproduction.

Widespread position-specific conservation of synonymous rare codons within coding sequences

Synonymous rare codons are considered to be sub-optimal for gene expression because they are translated more slowly than common codons. Yet surprisingly, many protein coding sequences include large clusters of synonymous rare codons. Rare codons at the 5’ terminus of coding sequences have been shown to increase translational efficiency. Although a general functional role for synonymous rare codons farther within coding sequences has not yet been established, several recent reports have identified rare-to-common synonymous codon substitutions that impair folding of the encoded protein. Here we test the hypothesis that although the usage frequencies of synonymous codons change from organism to organism, codon rarity will be conserved at specific positions in a set of homologous coding sequences, for example to tune translation rate without altering a protein sequence. Such conservation of rarity–rather than specific codon identity–could coordinate co-translational folding of the encoded protein. We demonstrate that many rare codon cluster positions are indeed conserved within homologous coding sequences across diverse eukaryotic, bacterial, and archaeal species, suggesting they result from positive selection and have a functional role. Most conserved rare codon clusters occur within rather than between conserved protein domains, challenging the view that their primary function is to facilitate co-translational folding after synthesis of an autonomous structural unit. Instead, many conserved rare codon clusters separate smaller protein structural motifs within structural domains. These smaller motifs typically fold faster than an entire domain, on a time scale more consistent with translation rate modulation by synonymous codon usage. While proteins with conserved rare codon clusters are structurally and functionally diverse, they are enriched in functions associated with organism growth and development, suggesting an important role for synonymous codon usage in organism physiology. The identification of conserved rare codon clusters advances our understanding of distinct, functional roles for otherwise synonymous codons and enables experimental testing of the impact of synonymous codon usage on the production of functional proteins.

Proteins are long linear polymers that must fold into complex three-dimensional shapes in order to carry out their cellular functions. Every protein is synthesized by the ribosome, which decodes each trinucleotide codon in an mRNA coding sequence in order to select the amino acid residue that will occupy each position in the protein sequence. Most amino acids can be encoded by more than one codon, but these synonymous codons are not used with equal frequency. Rare codons are associated with generally slower rates for protein synthesis, and for this reason have traditionally been considered mildly deleterious for efficient protein production. However, because synonymous codon substitutions do not change the sequence of the encoded protein, the majority view is that they merely reflect genomic ‘background noise’. To the contrary, here we show that the positions of many synonymous rare codons are conserved in mRNA sequences that encode structurally similar proteins from a diverse range of organisms. These results suggest that rare codons have a functional role related to the production of functional proteins, potentially to regulate the rate of protein synthesis and the earliest steps of protein folding, while synthesis is still underway.

Old genes experience stronger translational selection than young genes

Selection on synonymous codon usage for translation efficiency and/or accuracy has been identified as a widespread mechanism in many living organisms. However, it remains unknown whether translational selection associates closely with gene age and acts differentially on genes with different evolutionary ages. To address this issue, here we investigate the strength of translational selection acting on different aged genes in human. Our results show that old genes present stronger translational selection than young genes, demonstrating that translational selection correlates positively with gene age. We further explore the difference of translational selection in duplicates vs. singletons and in housekeeping vs. tissue-specific genes. We find that translational selection acts comparably in old singletons and old duplicates and stronger translational selection in old genes is contributed primarily by housekeeping genes. For young genes, contrastingly, singletons experience stronger translational selection than duplicates, presumably due to redundant function of duplicated genes during their early evolutionary stage. Taken together, our results indicate that translational selection acting on a gene would not be constant during all stages of evolution, associating closely with gene age.

Are Synonymous Sites in Primates and Rodents Functionally Constrained?

It has been claimed that synonymous sites in mammals are under selective constraint. Furthermore, in many studies the selective constraint at such sites in primates was claimed to be more stringent than that in rodents. Given the larger effective population sizes in rodents than in primates, the theoretical expectation is that selection in rodents would be more effective than that in primates. To resolve this contradiction between expectations and observations, we used processed pseudogenes as a model for strict neutral evolution, and estimated selective constraint on synonymous sites using the rate of substitution at pseudosynonymous and pseudononsynonymous sites in pseudogenes as the neutral expectation. After controlling for the effects of GC content, our results were similar to those from previous studies, i.e., synonymous sites in primates exhibited evidence for higher selective constraint that those in rodents. Specifically, our results indicated that in primates up to 24% of synonymous sites could be under purifying selection, while in rodents synonymous sites evolved neutrally. To further control for shifts in GC content, we estimated selective constraint at fourfold degenerate sites using a maximum parsimony approach. This allowed us to estimate selective constraint using mutational patterns that cause a shift in GC content (GT ↔ TG, CT ↔ TC, GA ↔ AG, and CA ↔ AC) and ones that do not (AT ↔ TA and CG ↔ GC). Using this approach, we found that synonymous sites evolve neutrally in both primates and rodents. Apparent deviations from neutrality were caused by a higher rate of C → A and C → T mutations in pseudogenes. Such differences are most likely caused by the shift in GC content experienced by pseudogenes. We conclude that previous estimates according to which 20-40% of synonymous sites in primates were under selective constraint were most likely artifacts of the biased pattern of mutation.

Evolutionary Rate Heterogeneity of Primary and Secondary Metabolic Pathway Genes in Arabidopsis thaliana

Primary metabolism is essential to plants for growth and development, and secondary metabolism helps plants to interact with the environment. Many plant metabolites are industrially important. These metabolites are produced by plants through complex metabolic pathways. Lack of knowledge about these pathways is hindering the successful breeding practices for these metabolites. For a better knowledge of the metabolism in plants as a whole, evolutionary rate variation of primary and secondary metabolic pathway genes is a prerequisite. In this study, evolutionary rate variation of primary and secondary metabolic pathway genes has been analyzed in the model plant Arabidopsis thaliana. Primary metabolic pathway genes were found to be more conserved than secondary metabolic pathway genes. Several factors such as gene structure, expression level, tissue specificity, multifunctionality, and domain number are the key factors behind this evolutionary rate variation. This study will help to better understand the evolutionary dynamics of plant metabolism.

Functional and Structural Consequence of Rare Exonic Single Nucleotide Polymorphisms: One Story, Two Tales

Genetic variation arising from single nucleotide polymorphisms (SNPs) is ubiquitously found among human populations. While disease-causing variants are known in some cases, identifying functional or causative variants for most human diseases remains a challenging task. Rare SNPs, rather than common ones, are thought to be more important in the pathology of most human diseases. We propose that rare SNPs should be divided into two categories dependent on whether the minor alleles are derived or ancestral. Derived alleles are less likely to have been purified by evolutionary processes and may be more likely to induce deleterious effects. We therefore hypothesized that the rare SNPs with derived minor alleles would be more important for human diseases and predicted that these variants would have larger functional or structural consequences relative to the rare variants for which the minor alleles are ancestral. We systematically investigated the consequences of the exonic SNPs on protein function, mRNA structure, and translation. We found that the functional and structural consequences are more significant for the rare exonic variants for which the minor alleles are derived. However, this pattern is reversed when the minor alleles are ancestral. Thus, the rare exonic SNPs with derived minor alleles are more likely to be deleterious. Age estimation of rare SNPs confirms that these potentially deleterious SNPs are recently evolved in the human population. These results have important implications for understanding the function of genetic variations in human exonic regions and for prioritizing functional SNPs in genome-wide association studies of human diseases.

A codon model of nucleotide substitution with selection on synonymous codon usage

The quality of phylogenetic inference made from protein-coding genes depends, in part, on the realism with which the codon substitution process is modeled. Here we propose a new mechanistic model that combines the standard M0 substitution model of Yang (1997) with a simplified model from Gilchrist (2007) that includes selection on synonymous substitutions as a function of codon-specific nonsense error rates. We tested the newly proposed model by applying it to 104 protein-coding genes in brewer's yeast, and compared the fit of the new model to the standard M0 model and to the mutation-selection model of Yang and Nielsen (2008) using the AIC. Our new model provided significantly better fit in approximately 85% of the cases considered for the basic M0 model and in approximately 25% of the cases for the M0 model with estimated codon frequencies, but only in a few cases when the mutation-selection model was considered. However, our model includes a parameter that can be interpreted as a measure of the rate of protein production, and the estimates of this parameter were highly correlated with an independent measure of protein production for the yeast genes considered here. Finally, we found that in some cases the new model led to the preference of a different phylogeny for a subset of the genes considered, indicating that substitution model choice may have an impact on the estimated phylogeny.

The relationship between dN/dS and scaled selection coefficients

Numerous computational methods exist to assess the mode and strength of natural selection in protein-coding sequences, yet how distinct methods relate to one another remains largely unknown. Here, we elucidate the relationship between two widely used phylogenetic modeling frameworks: dN/dS models and mutation-selection (MutSel) models. We derive a mathematical relationship between dN/dS and scaled selection coefficients, the focal parameters of MutSel models, and use this relationship to gain deeper insight into the behaviors, limitations, and applicabilities of these two modeling frameworks. We prove that, if all synonymous changes are neutral, standard MutSel models correspond to dN/dS ≤ 1. However, if synonymous codons differ in fitness, dN/dS can take on arbitrarily high values even if all selection is purifying. Thus, the MutSel modeling framework cannot necessarily accommodate positive, diversifying selection, while dN/dS cannot distinguish between purifying selection on synonymous codons and positive selection on amino acids. We further propose a new benchmarking strategy of dN/dS inferences against MutSel simulations and demonstrate that the widely used Goldman-Yang-style dN/dS models yield substantially biased dN/dS estimates on realistic sequence data. In contrast, the less frequently used Muse-Gaut-style models display much less bias. Strikingly, the least-biased and most precise dN/dS estimates are never found in the models with the best fit to the data, measured through both AIC and BIC scores. Thus, selecting models based on goodness-of-fit criteria can yield poor parameter estimates if the models considered do not precisely correspond to the underlying mechanism that generated the data. In conclusion, establishing mathematical links among modeling frameworks represents a novel, powerful strategy to pinpoint previously unrecognized model limitations and strengths.

The genomic and phenotypic diversity of Schizosaccharomyces pombe

Natural variation within species reveals aspects of genome evolution and function. The fission yeast Schizosaccharomyces pombe is an important model for eukaryotic biology, but researchers typically use one standard laboratory strain. To extend the usefulness of this model, we surveyed the genomic and phenotypic variation in 161 natural isolates. We sequenced the genomes of all strains, finding moderate genetic diversity (π = 3 × 10(-3) substitutions/site) and weak global population structure. We estimate that dispersal of S. pombe began during human antiquity (∼340 BCE), and ancestors of these strains reached the Americas at ∼1623 CE. We quantified 74 traits, finding substantial heritable phenotypic diversity. We conducted 223 genome-wide association studies, with 89 traits showing at least one association. The most significant variant for each trait explained 22% of the phenotypic variance on average, with indels having larger effects than SNPs. This analysis represents a rich resource to examine genotype-phenotype relationships in a tractable model.

A generalized mechanistic codon model

Models of codon evolution have attracted particular interest because of their unique capabilities to detect selection forces and their high fit when applied to sequence evolution. We described here a novel approach for modeling codon evolution, which is based on Kronecker product of matrices. The 61 × 61 codon substitution rate matrix is created using Kronecker product of three 4 × 4 nucleotide substitution matrices, the equilibrium frequency of codons, and the selection rate parameter. The entities of the nucleotide substitution matrices and selection rate are considered as parameters of the model, which are optimized by maximum likelihood. Our fully mechanistic model allows the instantaneous substitution matrix between codons to be fully estimated with only 19 parameters instead of 3,721, by using the biological interdependence existing between positions within codons. We illustrate the properties of our models using computer simulations and assessed its relevance by comparing the AICc measures of our model and other models of codon evolution on simulations and a large range of empirical data sets. We show that our model fits most biological data better compared with the current codon models. Furthermore, the parameters in our model can be interpreted in a similar way as the exchangeability rates found in empirical codon models.

Mitogenomic analyses propose positive selection in mitochondrial genes for high-altitude adaptation in galliform birds

Galliform birds inhabit very diverse habitats, including plateaus that are above 3000 m in altitude. At high altitude, lower temperature and hypoxia are two important factors influencing survival. Mitochondria, as the ultimate oxygen transductor, play an important role in aerobic respiration through oxidative phosphorylation (OXPHOS). We analyzed the mitochondrial genomes of six high-altitude phasianidae birds and sixteen low-altitude relatives in an attempt to determine the role of mitochondrial genes in high-altitude adaptation. We reconstructed the phylogenetic relationships of these phasianidae birds and relatives and found at least four lineages that independently occupied this high-altitude habitat. Selective analyses revealed significant evidence for positive selection in the genes ND2, ND4, and ATP6 in three of the high-altitude lineages. This result strongly suggests that adaptive evolution of mitochondrial genes played a critical role during the independent acclimatization to high altitude by galliform birds.

Unraveling patterns of site-to-site synonymous rates variation and associated gene properties of protein domains and families

In protein-coding genes, synonymous mutations are often thought not to affect fitness and therefore are not subject to natural selection. Yet increasingly, cases of non-neutral evolution at certain synonymous sites were reported over the last decade. To evaluate the extent and the nature of site-specific selection on synonymous codons, we computed the site-to-site synonymous rate variation (SRV) and identified gene properties that make SRV more likely in a large database of protein-coding gene families and protein domains. To our knowledge, this is the first study that explores the determinants and patterns of the SRV in real data. We show that the SRV is widespread in the evolution of protein-coding sequences, putting in doubt the validity of the synonymous rate as a standard neutral proxy. While protein domains rarely undergo adaptive evolution, the SRV appears to play important role in optimizing the domain function at the level of DNA. In contrast, protein families are more likely to evolve by positive selection, but are less likely to exhibit SRV. Stronger SRV was detected in genes with stronger codon bias and tRNA reusage, those coding for proteins with larger number of interactions or forming larger number of structures, located in intracellular components and those involved in typically conserved complex processes and functions. Genes with extreme SRV show higher expression levels in nearly all tissues. This indicates that codon bias in a gene, which often correlates with gene expression, may often be a site-specific phenomenon regulating the speed of translation along the sequence, consistent with the co-translational folding hypothesis. Strikingly, genes with SRV were strongly overrepresented for metabolic pathways and those associated with several genetic diseases, particularly cancers and diabetes.

The impact of RNA structure on coding sequence evolution in both bacteria and eukaryotes

Background

Many studies have found functional RNA secondary structures are selectively conserved among species. But, the effect of RNA structure selection on coding sequence evolution remains unknown. To address this problem, we systematically investigated the relationship between nucleotide conservation level and its structural sensitivity in four model organisms, Escherichia coli, yeast, fly, and mouse.

Results

We define structurally sensitive sites as those with putative local structure-disruptive mutations. Using both the Mantel-Haenszel procedure and association test, we found structurally sensitive nucleotide sites evolved more slowly than non-sensitive sites in all four organisms. Furthermore, we observed that this association is more obvious in highly expressed genes and region near the start codon.

Conclusion

We conclude that structurally sensitive sites in mRNA sequences normally have less nucleotide divergence in all species we analyzed. This study extends our understanding of the impact of RNA structure on coding sequence evolution, and is helpful to the development of a codon model with RNA structure information.

Low structural variation in the host-defense peptide repertoire of the dwarf clawed frog Hymenochirus boettgeri (Pipidae)

THE skin secretion of many amphibians contains peptides that are able to kill a broad range of microorganisms (antimicrobial peptides: AMPs) and potentially play a role in innate immune defense. Similar to the toxin arsenals of various animals, amphibian AMP repertoires typically show major structural variation, and previous studies have suggested that this may be the result of diversifying selection in adaptation to a diverse spectrum of pathogens. Here we report on transcriptome analyses that indicate a very different pattern in the dwarf clawed frog H. boettgeri. Our analyses reveal a diverse set of transcripts containing two to six tandem repeats, together encoding 14 distinct peptides. Five of these have recently been identified as AMPs, while three more are shown here to potently inhibit the growth of gram-negative bacteria, including multi-drug resistant strains of the medically important Pseudomonas aeruginosa. Although the number of predicted peptides is similar to the numbers of related AMPs in Xenopus and Silurana frog species, they show significantly lower structural variation. Selection analyses confirm that, in contrast to the AMPs of other amphibians, the H. boettgeri peptides did not evolve under diversifying selection. Instead, the low sequence variation among tandem repeats resulted from purifying selection, recent duplication and/or concerted gene evolution. Our study demonstrates that defense peptide repertoires of closely related taxa, after diverging from each other, may evolve under differential selective regimes, leading to contrasting patterns of structural diversity.

Evolution at two levels of gene expression in yeast

Despite the greater functional importance of protein levels, our knowledge of gene expression evolution is based almost entirely on studies of mRNA levels. In contrast, our understanding of how translational regulation evolves has lagged far behind. Here we have applied ribosome profiling—which measures both global mRNA levels and their translation rates—to two species of Saccharomyces yeast and their interspecific hybrid in order to assess the relative contributions of changes in mRNA abundance and translation to regulatory evolution. We report that both cis- and trans-acting regulatory divergence in translation are abundant, affecting at least 35% of genes. The majority of translational divergence acts to buffer changes in mRNA abundance, suggesting a widespread role for stabilizing selection acting across regulatory levels. Nevertheless, we observe evidence of lineage-specific selection acting on several yeast functional modules, including instances of reinforcing selection acting at both levels of regulation. Finally, we also uncover multiple instances of stop-codon readthrough that are conserved between species. Our analysis reveals the underappreciated complexity of post-transcriptional regulatory divergence and indicates that partitioning the search for the locus of selection into the binary categories of “coding” versus “regulatory” may overlook a significant source of selection, acting at multiple regulatory levels along the path from genotype to phenotype.

Synonymous site conservation in the HIV-1 genome

BACKGROUND

Synonymous or silent mutations are usually thought to evolve neutrally. However, accumulating recent evidence has demonstrated that silent mutations may destabilize RNA structures or disrupt cis regulatory motifs superimposed on coding sequences. Such observations suggest the existence of stretches of codon sites that are evolutionary conserved at both DNA-RNA and protein levels. Such stretches may point to functionally important regions within protein coding sequences not necessarily reflecting functional constraints on the amino-acid sequence. The HIV-1 genome is highly compact, and often harbors overlapping functional elements at the protein, RNA, and DNA levels. This superimposition of functions leads to complex selective forces acting on all levels of the genome and proteome. Considering the constraints on HIV-1 to maintain such a highly compact genome, we hypothesized that stretches of synonymous conservation would be common within its genome.

RESULTS

We used a combined computational-experimental approach to detect and characterize regions exhibiting strong purifying selection against synonymous substitutions along the HIV-1 genome. Our methodology is based on advanced probabilistic evolutionary models that explicitly account for synonymous rate variation among sites and rate dependencies among adjacent sites. These models are combined with a randomization procedure to automatically identify the most statistically significant regions of conserved synonymous sites along the genome. Using this procedure we identified 21 conserved regions. Twelve of these are mapped to regions within overlapping genes, seven correlate with known functional elements, while the functions of the remaining four are yet unknown. Among these four regions, we chose the one that deviates most from synonymous rate homogeneity for in-depth computational and experimental characterization. In our assays aiming to quantify viral fitness in both early and late stages of the replication cycle, no differences were observed between the mutated and the wild type virus following the introduction of synonymous mutations.

CONCLUSIONS

The contradiction between the inferred purifying selective forces and the lack of effect of these mutations on viral replication may be explained by the fact that the phenotype was measured in single-cycle infection assays in cell culture. Such a system does not account for the complexity of HIV-1 infections in vivo, which involves multiple infection cycles and interaction with the host immune system.

Strong purifying selection at synonymous sites in D. melanogaster

Synonymous sites are generally assumed to be subject to weak selective constraint. For this reason, they are often neglected as a possible source of important functional variation. We use site frequency spectra from deep population sequencing data to show that, contrary to this expectation, 22% of four-fold synonymous (4D) sites in Drosophila melanogaster evolve under very strong selective constraint while few, if any, appear to be under weak constraint. Linking polymorphism with divergence data, we further find that the fraction of synonymous sites exposed to strong purifying selection is higher for those positions that show slower evolution on the Drosophila phylogeny. The function underlying the inferred strong constraint appears to be separate from splicing enhancers, nucleosome positioning, and the translational optimization generating canonical codon bias. The fraction of synonymous sites under strong constraint within a gene correlates well with gene expression, particularly in the mid-late embryo, pupae, and adult developmental stages. Genes enriched in strongly constrained synonymous sites tend to be particularly functionally important and are often involved in key developmental pathways. Given that the observed widespread constraint acting on synonymous sites is likely not limited to Drosophila, the role of synonymous sites in genetic disease and adaptation should be reevaluated.

Non-silent story on synonymous sites in voltage-gated ion channel genes

Synonymous mutations are usually referred to as “silent”, but increasing evidence shows that they are not neutral in a wide range of organisms. We looked into the relationship between synonymous codon usage bias and residue importance of voltage-gated ion channel proteins in mice, rats, and humans. We tested whether translationally optimal codons are associated with transmembrane or channel-forming regions, i.e., the sites that are particularly likely to be involved in the closing and opening of an ion channel. Our hypothesis is that translationally optimal codons are preferred at the sites within transmembrane domains or channel-forming regions in voltage-gated ion channel genes to avoid mistranslation-induced protein misfolding or loss-of-function. Using the Mantel-Haenszel procedure, which applies to categorical data, we found that translationally optimal codons are more likely to be used at transmembrane residues and the residues involved in channel-forming. We also found that the conservation level at synonymous sites in the transmembrane region is significantly higher than that in the non-transmembrane region. This study provides evidence that synonymous sites in voltage-gated ion channel genes are not neutral. Silent mutations at channel-related sites may lead to dysfunction of the ion channel.

The interface of protein structure, protein biophysics, and molecular evolution

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction.

Modeling HIV-1 drug resistance as episodic directional selection

The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

When exposed to treatment, HIV-1 and other rapidly evolving viruses have the capacity to acquire drug resistance mutations (DRAMs), which limit the efficacy of antivirals. There are a number of experimentally well characterized HIV-1 DRAMs, but many mutations whose roles are not fully understood have also been reported. In this manuscript we construct evolutionary models that identify the locations and targets of mutations conferring resistance to antiretrovirals from viral sequences sampled from treated and untreated individuals. While the evolution of drug resistance is a classic example of natural selection, existing analyses fail to detect the majority of DRAMs. We show that, in order to identify resistance mutations from sequence data, it is necessary to recognize that in this case natural selection is both episodic (it only operates when the virus is exposed to the drugs) and directional (only mutations to a particular amino-acid confer resistance while allowing the virus to continue replicating). The new class of models that allow for the episodic and directional nature of adaptive evolution performs very well at recovering known DRAMs, can be useful at identifying unknown resistance-associated mutations, and is generally applicable to a variety of biological scenarios where similar selective forces are at play.

Selection on the protein-coding genome

Populations evolve as mutations arise in individual organisms and, through hereditary transmission, may become "fixed" (shared by all individuals) in the population. Most mutations are lethal or have negative fitness consequences for the organism. Others have essentially no effect on organismal fitness and can become fixed through the neutral stochastic process known as random drift. However, mutations may also produce a selective advantage that boosts their chances of reaching fixation. Regions of genes where new mutations are beneficial, rather than neutral or deleterious, tend to evolve more rapidly due to positive selection. Genes involved in immunity and defense are a well-known example; rapid evolution in these genes presumably occurs because new mutations help organisms to prevail in evolutionary "arms races" with pathogens. In recent years, genome-wide scans for selection have enlarged our understanding of the evolution of the protein-coding regions of the various species. In this chapter, we focus on the methods to detect selection in protein-coding genes. In particular, we discuss probabilistic models and how they have changed with the advent of new genome-wide data now available.

Statistics and truth in phylogenomics

Phylogenomics refers to the inference of historical relationships among species using genome-scale sequence data and to the use of phylogenetic analysis to infer protein function in multigene families. With rapidly decreasing sequencing costs, phylogenomics is becoming synonymous with evolutionary analysis of genome-scale and taxonomically densely sampled data sets. In phylogenetic inference applications, this translates into very large data sets that yield evolutionary and functional inferences with extremely small variances and high statistical confidence (P value). However, reports of highly significant P values are increasing even for contrasting phylogenetic hypotheses depending on the evolutionary model and inference method used, making it difficult to establish true relationships. We argue that the assessment of the robustness of results to biological factors, that may systematically mislead (bias) the outcomes of statistical estimation, will be a key to avoiding incorrect phylogenomic inferences. In fact, there is a need for increased emphasis on the magnitude of differences (effect sizes) in addition to the P values of the statistical test of the null hypothesis. On the other hand, the amount of sequence data available will likely always remain inadequate for some phylogenomic applications, for example, those involving episodic positive selection at individual codon positions and in specific lineages. Again, a focus on effect size and biological relevance, rather than the P value, may be warranted. Here, we present a theoretical overview and discuss practical aspects of the interplay between effect sizes, bias, and P values as it relates to the statistical inference of evolutionary truth in phylogenomics.

Selection for translation efficiency on synonymous polymorphisms in recent human evolution

Synonymous mutations are considered to be "silent" as they do not affect protein sequence. However, different silent codons have different translation efficiency (TE), which raises the question to what extent such mutations are really neutral. We perform the first genome-wide study of natural selection operating on TE in recent human evolution, surveying 13,798 synonymous single nucleotide polymorphisms (SNPs) in 1,198 unrelated individuals from 11 populations. We find evidence for both negative and positive selection on TE, as measured based on differentiation in allele frequencies between populations. Notably, the likelihood of an SNP to be targeted by positive or negative selection is correlated with the magnitude of its effect on the TE of the corresponding protein. Furthermore, negative selection acting against changes in TE is more marked in highly expressed genes, highly interacting proteins, complex members, and regulatory genes. It is also more common in functional regions and in the initial segments of highly expressed genes. Positive selection targeting sites with a large effect on TE is stronger in lowly interacting proteins and in regulatory genes. Similarly, essential genes are enriched for negative TE selection while underrepresented for positive TE selection. Taken together, these results point to the significant role of TE as a selective force operating in humans and hence underscore the importance of considering silent SNPs in interpreting associations with complex human diseases. Testifying to this potential, we describe two synonymous SNPs that may have clinical implications in phenylketonuria and in Best's macular dystrophy due to TE differences between alleles.

Statistical methods for detecting natural selection from genomic data

In the study of molecular and phenotypic evolution, understanding the relative importance of random genetic drift and positive selection as the mechanisms for driving divergences between populations and maintaining polymorphisms within populations has been a central issue. A variety of statistical methods has been developed for detecting natural selection operating at the amino acid and nucleotide sequence levels. These methods may be largely classified into those aimed at detecting recurrent and/or recent/ongoing natural selection by utilizing the divergence and/or polymorphism data. Using these methods, pervasive positive selection has been identified for protein-coding and non-coding sequences in the genomic analysis of some organisms. However, many of these methods have been criticized by using computer simulation and real data analysis to produce excessive false-positives and to be sensitive to various disturbing factors. Importantly, some of these methods have been invalidated experimentally. These facts indicate that many of the statistical methods for detecting natural selection are unreliable. In addition, the signals that have been believed as the evidence for fixations of advantageous mutations due to positive selection may also be interpreted as the evidence for fixations of deleterious mutations due to random genetic drift. The genomic diversity data are rapidly accumulating in various organisms, and detection of natural selection may play a critical role for clarifying the relative role of random genetic drift and positive selection in molecular and phenotypic evolution. It is therefore important to develop reliable statistical methods that are unbiased as well as robust against various disturbing factors, for inferring natural selection.

Evolutionary models accounting for layers of selection in protein-coding genes and their impact on the inference of positive selection

The selective forces acting on a protein-coding gene are commonly inferred using evolutionary codon models by contrasting the rate of nonsynonymous substitutions to the rate of synonymous substitutions. These models usually assume that the synonymous substitution rate, Ks, is homogenous across all sites, which is justified if synonymous sites are free from selection. However, a growing body of evidence indicates that the DNA and RNA levels of protein-coding genes are subject to varying degrees of selective constraints due to various biological functions encoded at these levels. In this paper, we develop evolutionary models that account for these layers of selection by allowing for both among-site variability of substitution rates at the DNA/RNA level (which leads to Ks variability among protein-coding sites) and among-site variability of substitution rates at the protein level (Ka variability). These models are constructed so that positive selection is either allowed or not. This enables statistical testing of positive selection when variability at the DNA/RNA substitution rate is accounted for. Using this methodology, we show that variability of the baseline DNA/RNA substitution rate is a widespread phenomenon in coding sequence data of mammalian genomes, most likely reflecting varying degrees of selection at the DNA and RNA levels. Additionally, we use simulations to examine the impact that accounting for the variability of the baseline DNA/RNA substitution rate has on the inference of positive selection. Our results show that ignoring this variability results in a high rate of erroneous positive-selection inference. Our newly developed model, which accounts for this variability, does not suffer from this problem and hence provides a likelihood framework for the inference of positive selection on a background of variability in the baseline DNA/RNA substitution rate.

Variation in the analysis of positively selected sites using nonsynonymous/synonymous rate ratios: an example using influenza virus

Sites in a gene showing the nonsynonymous/synonymous rate ratio (ω) >1 have been frequently identified to be under positive selection. To examine the performance of such analysis, sites of the ω ratio >1 in the HA1 gene of H3N2 subtype human influenza viruses were identified from seven overlapping sequence data sets in this study. Our results showed that the sites of the ω ratio >1 were of significant variation among the data sets even though they targeted similar clusters, indicating that the analysis is likely to be either of low sensitivity or of low specificity in identifying sites under positive selection. Most (43/45) of the sites showing ω >1 calculated from at least one data set are involved in B-cell epitopes which cover less than a half sites in the protein, suggesting that the analysis is likely to be of low sensitivity rather than of low specificity. It was further found that the analysis sensitivity could not be enhanced by including more sequences or covering longer time intervals. Previously some reports also likely identified only a portion of the sites under positive selection in the viral gene using the ω ratio. Low sensitivity of the analysis may result from that some sites under positive selection in the gene are also under negative (purifying) selection simultaneously for functional constrains, and so their ω ratios could be <1. Theoretically, the sites under the two opposite selection forces at the same time favor only certain nonsynonymous changes, e.g. those changing the antigenicity of the gene and maintaining the gene function. This study also suggested that sometimes we can identify more sites under positive selection using the ω ratio by integrating the positively selected sites estimated from multiple data sets.

Genome-wide survey of natural selection on functional, structural, and network properties of polymorphic sites in Saccharomyces paradoxus

BACKGROUND

To characterize the genetic basis of phenotypic evolution, numerous studies have identified individual genes that have likely evolved under natural selection. However, phenotypic changes may represent the cumulative effect of similar evolutionary forces acting on functionally related groups of genes. Phylogenetic analyses of divergent yeast species have identified functional groups of genes that have evolved at significantly different rates, suggestive of differential selection on the functional properties. However, due to environmental heterogeneity over long evolutionary timescales, selection operating within a single lineage may be dramatically different, and it is not detectable via interspecific comparisons alone. Moreover, interspecific studies typically quantify selection on protein-coding regions using the D(n)/D(s) ratio, which cannot be extended easily to study selection on noncoding regions or synonymous sites. The population genetic-based analysis of selection operating within a single lineage ameliorates these limitations.

FINDINGS

We investigated selection on several properties associated with genes, promoters, or polymorphic sites, by analyzing the derived allele frequency spectrum of single nucleotide polymorphisms (SNPs) in 28 strains of Saccharomyces paradoxus. We found evidence for significant differential selection between many functionally relevant categories of SNPs, underscoring the utility of function-centric approaches for discovering signatures of natural selection. When comparable, our findings are largely consistent with previous studies based on interspecific comparisons, with one notable exception: our study finds that mutations from an ancient amino acid to a relatively new amino acid are selectively disfavored, whereas interspecific comparisons have found selection against ancient amino acids. Several of our findings have not been addressed through prior interspecific studies: we find that synonymous mutations from preferred to unpreferred codons are selected against and that synonymous SNPs in the linker regions of proteins are relatively less constrained than those within protein domains.

CONCLUSIONS

We present the first global survey of selection acting on various functional properties in S. paradoxus. We found that selection pressures previously detected over long evolutionary timescales have also shaped the evolution of S. paradoxus. Importantly, we also make novel discoveries untenable via conventional interspecific analyses.

Lipid-binding surfaces of membrane proteins: evidence from evolutionary and structural analysis

Membrane proteins function in the diverse environment of the lipid bilayer. Experimental evidence suggests that some lipid molecules bind tightly to specific sites on the membrane protein surface. These lipid molecules often act as co-factors and play important functional roles. In this study, we have assessed the evolutionary selection pressure experienced at lipid-binding sites in a set of α-helical and β-barrel membrane proteins using posterior probability analysis of the ratio of synonymous vs. nonsynonymous substitutions (ω-ratio). We have also carried out a geometric analysis of the membrane protein structures to identify residues in close contact with co-crystallized lipids. We found that residues forming cholesterol-binding sites in both β(2)-adrenergic receptor and Na(+)-K(+)-ATPase exhibit strong conservation, which can be characterized by an expanded cholesterol consensus motif for GPCRs. Our results suggest the functional importance of aromatic stacking interactions and interhelical hydrogen bonds in facilitating protein-cholesterol interactions, which is now reflected in the expanded motif. We also find that residues forming the cardiolipin-binding site in formate dehydrogenase-N γ-subunit and the phosphatidylglycerol binding site in KcsA are under strong purifying selection pressure. Although the lipopolysaccharide (LPS)-binding site in ferric hydroxamate uptake receptor (FhuA) is only weakly conserved, we show using a statistical mechanical model that LPS binds to the least stable FhuA β-strand and protects it from the bulk lipid. Our results suggest that specific lipid binding may be a general mechanism employed by β-barrel membrane proteins to stabilize weakly stable regions. Overall, we find that the residues forming specific lipid binding sites on the surfaces of membrane proteins often experience strong purifying selection pressure.