Tertiary Windowing to Detect Positive Diversifying Selection

As a protein-encoding gene evolves, different selective pressures act on the gene temporally and spatially. An examination of the ratio of nonsynonymous-to-synonymous nucleotide substitution rate ratios (K_a/K_s) has proven to be a valuable method to examine selective pressures on protein encoding genes, including detecting positive diversifying selection. To gain power over averaging all sites in a gene together, examination of sites in primary sequence windows has frequently been employed. However, selection acts on folded proteins and sites that are close in tertiary space may not be close in primary sequence. A new method for the examination of K_a/K_s ratios based upon windows in tertiary structure is introduced and applied to the leptin gene family in mammals. Tertiary sequence windowing detects new sites under positive diversifying selection and detects positive diversifying selection with a more significant signal along various branches of the leptin gene family tree.Reviewing Editor: Dr. Rasmus Nielsen     

Statistical analysis of the envelope gene and the prM region of Japanese encephalitis virus: Evidence suggestive of positive selection

The variation in nucleotide sequence observed in the envelope (E) gene and the prM (precursor of M protein) region of different strains of Japanese encephalitis virus (JEV) was analysed. Presence of selective forces acting on these regions was investigated by computing the relative rates of synonymous (K _s) and nonsynonymous (K _a) substitutions. The ratioK _s/K _a was used as an indicator of the overall selective constraints on the amino acid sequence of JEV proteins. The possibility that different regions of the gene may be subject to varying selective pressures was tested by dividing the gene into three regions and estimating theK _s/K _a ratio for each region. On the basis of analysis of a limited number (17) of strains of JEV, evidence suggestive of positive selection acting on certain regions of the E gene of the virus, and in some cases on the entire gene, was obtained. Analysis ofK _a diversity in the prM region of 46 JEV strains grouped into three genotypes revealed that strains included in genotype II were more heterogeneous than strains belonging to genotype I, while the differences between meanK _a values for genotypes I and III and genotypes II and III were not statistically significant. Analysis of host-specific heterogeneity in the prM region revealed that pig isolates were more X_a-diverse than human isolates.     

CRK: An evolutionary approach for distinguishing biologically relevant interfaces from crystal contacts

Protein crystals contain two different types of interfaces: biologically relevant ones, observed in protein–protein complexes and oligomeric proteins, and nonspecific ones, corresponding to crystal lattice contacts. Because of the increasing complexity of the objects being tackled in structural biology, distinguishing biological contacts from crystal contacts is not always a trivial task and can lead to wrong interpretation of macromolecular structures. We devised an approach (CRK, core‐rim K_a/K_s ratio) for distinguishing biologically relevant interfaces from nonspecific ones. Given a protein–protein interface, CRK finds a set of homologs to the sequences of the proteins involved in the interface, retrieves and aligns the corresponding coding sequences, on which it carries out a residue‐by‐residue K_a/K_s ratio (ω) calculation. It divides interface residues into a “rim” and a “core” set and analyzes the selection pressure on the residues belonging to the two sets. We developed and tested CRK on different datasets and test cases, consisting of biologically relevant contacts, nonspecific ones or of both types. The method proves very effective in distinguishing the two categories of interfaces, with an overall accuracy rate of 84%. As it relies on different principles when compared with existing tools, CRK is optimally suited to be used in combination with them. In addition, CRK has potential applications in the validation of structures of oligomeric proteins and protein complexes. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Coding sequence divergence between two closely related plant species: Arabidopsis thaliana and Brassica rapa ssp. pekinensis

To characterize the coding-sequence divergence of closely related genomes, we compared DNA sequence divergence between sequences from a Brassica rapa ssp. pekinensis EST library isolated from flower buds and genomic sequences from Arabidopsis thaliana. The specific objectives were (i) to determine the distribution of and relationship between K _a and K _s, (ii) to identify genes with the lowest and highest K _a:K _s values, and (iii) to evaluate how codon usage has diverged between two closely related species. We found that the distribution of K _a:K _s was unimodal, and that substitution rates were more variable at nonsynonymous than synonymous sites, and detected no evidence that K _a and K _s were positively correlated. Several genes had K _a:K _s values equal to or near zero, as expected for genes that have evolved under strong selective constraint. In contrast, there were no genes with K _a:K _s >1 and thus we found no strong evidence that any of the 218 sequences we analyzed have evolved in response to positive selection. We detected a stronger codon bias but a lower frequency of GC at synonymous sites in A. thaliana than B. rapa. Moreover, there has been a shift in the profile of most commonly used synonymous codons since these two species diverged from one another. This shift in codon usage may have been caused by stronger selection acting on codon usage or by a shift in the direction of mutational bias in the B. rapa phylogenetic lineage.     

A genetic component of extinction risk in mammals

Genetic factors may play an important role in species extinction but their actual effect remains poorly understood, particularly because of a strong and potentially masking effect expected from ecological traits. We investigated the role of genetics in mammal extinction taking both ecological and genetic factors into account. As a proxy for the role of genetics we used the ratio of the rates of nonsynonymous (amino acid changing) to synonymous (leaving the amino acid unchanged) nucleotide substitutions, K_a / K_s. Because most nonsynonymous substitutions are likely to be slightly deleterious and thus selected against, this ratio is a measure of the inefficiency of selection: if large (but less than 1), it implies a low efficiency of selection against nonsynonymous mutations. As a result, nonsynonymous mutations may accumulate and thus contribute to extinction. As a proxy for the role of ecology we used body mass W, with which most extinction‐related ecological traits strongly correlate. As a measure of extinction risk we used species’ affiliation with the five levels of extinction threat according to the IUCN Red List of Threatened Species. We calculated K_a / K_s for mitochondrial protein‐coding genes of 211 mammalian species, each of which was characterized by body mass and the level of threat. Using logistic regression analysis, we then constructed a set of logistic regression models of extinction risk on ln(K_a / K_s) and lnW. We found that K_a / K_s and body mass are responsible for a 38% and a 62% increase in extinction risk, respectively. Given that the standard error of these values is 13%, the contribution of genetic factors to extinction risk in mammals is estimated to be one‐quarter to one‐half of the total of ecological and genetic effects. We conclude that the effect of genetics on extinction is significant, though it is almost certainly smaller than the effect of ecological traits. Synthesis Mutation provides the material for evolution. However, most mutations that play a role in evolution are slightly deleterious and thus may contribute to extinction. We assess the role of mitochondrial DNA mutations in mammalian extinction risk and find it to be one‐quarter to one‐half of the total of mutation and body mass effects, where body mass represents an integral measure of extinction‐related ecological traits. Genetic factors may be all the more important, because ecological traits associated with large body mass would both promote and protect from extinction, while mutation accumulation caused by low effective population size seems to have no counterbalance.     

Expected Relationship Between the Silent Substitution Rate and the GC Content: Implications for the Evolution of Isochores

The relationship between the silent substitution rate (K _s) and the GC content along the genome is a focal point of the debate about the origin of the isochore structure in vertebrates. Recent estimation of the silent substitution rate showed a positive correlation between K _s and GC content, in contradiction with the predictions of both the regional mutation bias model and the selection or biased gene conversion model. The aim of this paper is to help resolve this contradiction between theoretical studies and data. We analyzed the relationship between K _s and GC content under (1) uniform mutation bias, (2) a regional mutation bias, and (3) mutation bias and selection. We report that an increase in K _s with GC content is expected under mutation bias because of either nonequilibrium of the isochore structure or an increasing mutation rate from AT toward GC nucleotides in GC-richer isochores. We show by simulations that CpG deamination tends to increase the mutation rate with GC content in a regional mutation bias model. We also demonstrate that the relationship between K _s and GC under the selectionist or biased gene conversion model is positive under weak selection if the mutation selection equilibrium GC frequency is less than 0.5. Received: 28 March 2001 / Accepted: 16 May 2001     

SNP deserts of Asian cultivated rice: genomic regions under domestication

When performing a genome‐wide comparison between indica (93‐11) and japonica (Nipponbare), we find 8% of the genome, which have an extremely low SNP rate (< 1 SNP/kb). Inside these ‘SNP deserts’, experimentally confirmed genes show increased K_a/K_s that indicate adaptive selection. To further elucidate this connection, we survey the level and pattern of genetic variation in both cultivated and wild rice groups, using 155 noncoding regions located within SNP deserts. The results suggest that cultivated rice has greatly reduced genetic variation within SNP deserts as compared to either the nondesert or corresponding genomic regions in wild rice. Consistent with this reduction in genetic variation, we find a biased distribution of derived allele frequency in the cultivated group, indicative of positive selection. Furthermore, over half of the confirmed, domestication‐related genes are found within SNP deserts, also suggesting that SNP deserts are strongly related to domestication, and might be the key sites in the process of domestication.     

On transition bias in mitochondrial genes of pocket gophers

The relative contribution of mutation and purifying selection to transition bias has not been quantitatively assessed in mitochondrial protein genes. The observed transition/transversion (s/v) ratio is (μ _s P _s)/(μ _v P _v), where μ _s and μ _v denote mutation rate of transitions and transversions, respectively, andP _s andP _v denote fixation probabilities of transitions and transversions, respectively. Because selection against synonymous transitions can be assumed to be roughly equal to that against synonymous transversions,P _s/P_v ≈ 1 at fourfold degenerate sites, so that thes/v ratio at fourfold degenerate sites is approximately μ _s /μ _v , which is a measure of mutational contribution to transition bias. Similarly, thes/v ratio at nondegenerate sites is also an estimate of μ _s /μ _v if we assume that selection against nonsynonymous transitions is roughly equal to that against nonsynonymous transversions. In two mitochondrial genes, cytochrome oxidase subunit I (COI) and cytochromeb (cyt-b) in pocket gophers, thes/v ratio is about two at nondegenerate and fourfold degenerate sites for both the COI and the cyt-b genes. This implies that mutation contribution to transition bias is relatively small. In contrast, thes/v ratio is much greater at twofold degenerate sites, being 48 for COI and 40 for cyt-b. Given that the μ _s /μ _v ratio is about 2, theP _s/P_v ratio at twofold degenerate sites must be on the order of 20 or greater. This suggests a great effect of purifying selection on transition bias in mitochondrial protein genes because transitions are synonymous and transversions are nonsynonymous at twofold degenerate sites in mammalian mitochondrial genes. We also found that nonsynonymous mutations at twofold degenerate sites are more neutral than nonsynonymous mutations at nondegenerate sites, and that the COI gene is subject to stronger purifying selection than is the cyt-b gene. A model is presented to integrate the effect of purifying selection, codon bias, DNA repair and GC content ons/v ratio of protein-coding genes. Correspondence to: X. Xia     

Positive selection in MAOA gene is human exclusive: determination of the putative amino acid change selected in the human lineage

Monoamine oxidase A (MAOA) is the X-linked gene responsible for deamination and subsequent degradation of several neurotransmitters and other amines. Among other activities, the gene has been shown to play a role in locomotion, circadian rhythm, and pain sensitivity and to have a critical influence on behavior and cognition. Previous studies have reported a non-neutral evolution of the gene attributable to positive selection in the human lineage. To determine whether this selection was human-exclusive or shared with other species, we performed a population genetic analysis of the pattern of nucleotide variation in non-human species, including bonobo, chimpanzee, gorilla, and orangutan. Footprints of positive selection were absent in all analyzed species, suggesting that positive selection has been recent and unique to humans. To determine which human-unique genetic changes could have been responsible for this differential evolution, the coding region of the gene was compared between human, chimpanzee, and gorilla. Only one human exclusive non-conservative change is present in the gene: Glu151Lys. This human substitution affects protein dimerization according to a three-dimensional structural model that predicts a non-negligible functional shift. This is the only candidate position at present to have been selected to fixation in humans during an episode of positive selection. Divergence analysis among species has shown that, even under positive selection in the human lineage, the MAOA gene did not experience accelerated evolution in any of the analyzed lineages, and that tools such as K_a/K_s would not have detected the selective history of the gene.     

Differential selection in HIV-1 gp120 between subtype B and East Asian variant B’

HIV-1 evolves strongly and undergoes geographic differentiation as it spreads in diverse host populations around the world. For instance, distinct genomic backgrounds can be observed between the pandemic subtype B, prevalent in Europe and North-America, and its offspring clade B’ in East Asia. Here we ask whether this differentiation affects the selection pressure experienced by the virus. To answer this question we evaluate selection pressure on the HIV-1 envelope protein gp120 at the level of individual codons using a simple and fast estimation method based on the ratio k _a /k _s of amino acid changes to synonymous changes. To validate the approach we compare results to those from a state-of-the-art mixed-effect method. The agreement is acceptable, but the analysis also demonstrates some limitations of the simpler approach. Further, we find similar distributions of codons under stabilizing and directional selection pressure in gp120 for subtypes B and B’ with more directional selection pressure in variable loops and more stabilizing selection in the constant regions. Focusing on codons with increased k _a /k _s values in B’, we show that these codons are scattered over the whole of gp120, with remarkable clusters of higher density in regions flanking the variable loops. We identify a significant statistical association of glycosylation sites and codons with increased k _a /k _s values.     

Detection of site-specific positive Darwinian selection on pandemic influenza A/H1N1 virus genome: integrative approaches

In the twenty-first century, the first pandemic novel human influenza A/H1N1virus (NIV) outbreak was reported at Mexico and USA on March and early April, 2009 respectively. The outbreak occurred among human populations due to the presence of meager or no immune response against newly emerged viruses. The success of vaccines and drugs depends on their low susceptibility to the formation of escape mutants in virus. Identification of excess, non-synonymous substitutions over synonymous ones is a main indicator of positive Darwinian selection in protein-coding genes of NIVs. The positive Darwinian selection operating on each site of proteins were inferred by computing ω, the ratio of the non-synonymous/synonymous substitutions [dN/dS (or) K_a/K_s], which was calculated by three different methods in terms of codon-based maximum likelihood, branch-site and empirical Bayesian methods under various models. Totally, nine sites from PB2, PB1, HA, M2 and NS1 are inferred as positively selected. The function for amino acid sites of NIVs proteins under positive selection are inferred by comparing the sites with experimentally determined functionally known amino acid sites. Completely 4 positively selected sites of PB1, HA and M2 are found to be involved in B-cell epitopes (BCEs). Interestingly, most of these sites are also involving in T-cell epitopes (TCEs). However, more sites under positive selection forces are involved in TCEs than those of BCEs. Amino acid sites engaged in both BCEs and TCEs should be measured as highly suitable targets, because these sites could induce the strong humoral and cellular immune responses against targets.     

SUBPOPULATION DIFFERENTIATION ASSOCIATED WITH NONRIBOSOMAL PEPTIDE SYNTHETASE GENE CLUSTER DYNAMICS IN THE CYANOBACTERIUM PLANKTOTHRIX SPP.1

The Plankthotrix Anagn. et Komárek population in the mesotrophic Lake Steinsfjorden has been intensively studied over several decades. This Planktothrix population produces a number of different classes of oligopetides. However, over the study period, only four main oligopeptide profiles (chemotypes) have been associated with the strains isolated from the lake. The chemotypes show distinct interactions with the environment, demonstrated by shifts in abundance along time series and vertical profiles. Here, we present genetic analysis of nonribosomal peptide synthetase (NRPS) gene regions in strains representing the four Planktothrix chemotypes in Lake Steinsfjorden. On the basis of phylogenetic analyses, we show that the NRPS genes for microcystin (mcy) and cyanopeptolin (oci) display the same clustering as do the chemotypes. Nucleotide diversity in mcy and oci was significantly higher between strains of different chemotypes than between strains of the same chemotype. K_a/K_s (nonsynonymous vs. synonymous mutations) values indicated positive selection in several polymorphic regions of the mcy and oci genes. Notably, incongruence between the phylogenetic trees for different gene segments and split decomposition analyses for segments of oci suggested horizontal gene transfer (HGT) events between strains showing different oligopeptide profiles. The oci HGT region encodes a module responsible for incorporating a variable amino acid in cyanopeptolin and is one of the regions suggested to be under positive selection. Taken together, our data suggest that there are four genetically distinct sympatric subpopulations—displayed as distinct chemotypes—in Lake Steinsfjorden. The diversification process of the chemotypes, and consequently the subpopulations, is driven by HGT and reinforced by positive selection of the corresponding NRPS gene regions.     

Selective modes determine evolutionary rates,gene compactness and expression patterns in Brassica

It has been well documented that most nuclear protein‐coding genes in organisms can be classified into two categories: positively selected genes (PSGs) and negatively selected genes (NSGs). The characteristics and evolutionary fates of different types of genes, however, have been poorly understood. In this study, the rates of nonsynonymous substitution (K_a) and the rates of synonymous substitution (K_s) were investigated by comparing the orthologs between the two sequenced Brassica species, Brassica rapa and Brassica oleracea, and the evolutionary rates, gene structures, expression patterns, and codon bias were compared between PSGs and NSGs. The resulting data show that PSGs have higher protein evolutionary rates, lower synonymous substitution rates, shorter gene length, fewer exons, higher functional specificity, lower expression level, higher tissue‐specific expression and stronger codon bias than NSGs. Although the quantities and values are different, the relative features of PSGs and NSGs have been largely verified in the model species Arabidopsis. These data suggest that PSGs and NSGs differ not only under selective pressure (K_a/K_s), but also in their evolutionary, structural and functional properties, indicating that selective modes may serve as a determinant factor for measuring evolutionary rates, gene compactness and expression patterns in Brassica.     

The Roles of Gene Duplication,Gene Conversion and Positive Selection in Rodent Esp and Mup Pheromone Gene Families with Comparison to the Abp Family

Three proteinaceous pheromone families, the androgen-binding proteins (ABPs), the exocrine-gland secreting peptides (ESPs) and the major urinary proteins (MUPs) are encoded by large gene families in the genomes of Mus musculus and Rattus norvegicus. We studied the evolutionary histories of the Mup and Esp genes and compared them with what is known about the Abp genes. Apparently gene conversion has played little if any role in the expansion of the mouse Class A and Class B Mup genes and pseudogenes, and the rat Mups. By contrast, we found evidence of extensive gene conversion in many Esp genes although not in all of them. Our studies of selection identified at least two amino acid sites in β-sheets as having evolved under positive selection in the mouse Class A and Class B MUPs and in rat MUPs. We show that selection may have acted on the ESPs by determining K_a/K_s for Exon 3 sequences with and without the converted sequence segment. While it appears that purifying selection acted on the ESP signal peptides, the secreted portions of the ESPs probably have undergone much more rapid evolution. When the inner gene converted fragment sequences were removed, eleven Esp paralogs were present in two or more pairs with K_a/K_s >1.0 and thus we propose that positive selection is detectable by this means in at least some mouse Esp paralogs. We compare and contrast the evolutionary histories of all three mouse pheromone gene families in light of their proposed functions in mouse communication.     

Expanding knowledge of the Rubisco kinetics variability in plant species: environmental and evolutionary trends

The present study characterizes the kinetic properties of ribulose‐1,5‐bisphosphate carboxylase/oxygenase (Rubisco) from 28 terrestrial plant species, representing different phylogenetic lineages, environmental adaptations and photosynthetic mechanisms. Our findings confirm that past atmospheric CO₂/O₂ ratio changes and present environmental pressures have influenced Rubisco kinetics. One evolutionary adaptation to a decreasing atmospheric CO₂/O₂ ratio has been an increase in the affinity of Rubisco for CO₂ (K_c falling), and a consequent decrease in the velocity of carboxylation (k_cat^c), which in turn has been ameliorated by an increase in the proportion of leaf protein accounted by Rubisco. The trade‐off between K_c and k_cat^c was not universal among the species studied and deviations from this relationship occur in extant forms of Rubisco. In species adapted to particular environments, including carnivorous plants, crassulacean acid metabolism species and C₃ plants from aquatic and arid habitats, Rubisco has evolved towards increased efficiency, as demonstrated by a higher k_cat^c/K_c ratio. This variability in kinetics was related to the amino acid sequence of the Rubisco large subunit. Phylogenetic analysis identified 13 residues under positive selection during evolution towards specific Rubisco kinetic parameters. This crucial information provides candidate amino acid replacements, which could be implemented to optimize crop photosynthesis under a range of environmental conditions.     

Sensitivity of Patterns of Molecular Evolution to Alterations in Methodology: A Critique of Hughes and Yeager

Employing a set of 43 othologous mouse and rat genes, Hughes and Yeager (J. Mol. Evol. 45:125–130, 1997) reported (1) no correlation between synonymous and nonsynonymous rates of nucleotide substitution, (2) a positive correlation between intronic GC contents (GC _i) and intronic substitution rates (K _i), (3) that the average K _i value was very similar to the average K _s value, and (4) that the compositional correlation between the rat and the mouse genes is stronger at the third codon position (GC₃) than at the first and second codon positions (GC₁₂). We have examined the robustness of these results to alterations in substitution rate estimation protocol, alignment protocol, and statistical procedure. We find that a significant correlation between K _a and K _s is observed either if a rank correlation statistic is used instead of regression analysis, if one outlier is excluded from the analysis, or if a regression weighted by gene size is employed. The correlation between K _i and GC _i we find to be sensitive to changes in alignment protocol and disappears on the use of weighted means. The finding that K _s and K _i are approximately the same is dependent on the method for estimating K _s values. Finally, the variance around the regression line of rat GC₃ versus mouse GC₃ we find to be significantly higher than that in GC₁₂. The source of the discrepancy between this and Hughes and Yeager's result is unclear. The variance around the line for GC₄ is higher still, as might be expected. Using a methodology that may be considered preferable to that of Hughes and Yeager, we find that all four of their results are contradicted. More importantly this analysis reinforces the need for caution in assembling and analyzing data sets, as the degree of sensitivity to what many might consider minor methodological alterations is unexpected. Received: 2 February 1998 / Accepted: 23 March 1998     

Predicting protein pKa by environment similarity

A statistical method to predict protein pK_a has been developed by using the 3D structure of a protein and a database of 434 experimental protein pK_a values. Each pK_a in the database is associated with a fingerprint that describes the chemical environment around an ionizable residue. A computational tool, MoKaBio, has been developed to identify automatically ionizable residues in a protein, generate fingerprints that describe the chemical environment around such residues, and predict pK_a from the experimental pK_a values in the database by using a similarity metric. The method, which retrieved the pK_a of 429 of the 434 ionizable sites in the database correctly, was crossvalidated by leave‐one‐out and yielded root mean square error (RMSE) = 0.95, a result that is superior to that obtained by using the Null Model (RMSE 1.07) and other well‐established protein pK_a prediction tools. This novel approach is suitable to rationalize protein pK_a by comparing the region around the ionizable site with similar regions whose ionizable site pK_a is known. The pK_a of residues that have a unique environment not represented in the training set cannot be predicted accurately, however, the method offers the advantage of being trainable to increase its predictive power. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Distinguishing HIV-1 drug resistance, accessory, and viral fitness mutations using conditional selection pressure analysis of treated versus untreated patient samples

Background  

HIV can evolve drug resistance rapidly in response to new drug treatments, often through a combination of multiple mutations [1–3]. It would be useful to develop automated analyses of HIV sequence polymorphism that are able to predict drug resistance mutations, and to distinguish different types of functional roles among such mutations, for example, those that directly cause drug resistance, versus those that play an accessory role. Detecting functional interactions between mutations is essential for this classification. We have adapted a well-known measure of evolutionary selection pressure (K _a /K _s ) and developed a conditional K _a /K _s approach to detect important interactions.     

Bayesian model aggregation for ensemble‐based estimates of protein pKa values

This article investigates an ensemble‐based technique called Bayesian Model Averaging (BMA) to improve the performance of protein amino acid pK_a predictions. Structure‐based pK_a calculations play an important role in the mechanistic interpretation of protein structure and are also used to determine a wide range of protein properties. A diverse set of methods currently exist for pK_a prediction, ranging from empirical statistical models to ab initio quantum mechanical approaches. However, each of these methods are based on a set of conceptual assumptions that can effect a model's accuracy and generalizability for pK_a prediction in complicated biomolecular systems. We use BMA to combine eleven diverse prediction methods that each estimate pK_a values of amino acids in staphylococcal nuclease. These methods are based on work conducted for the pK_a Cooperative and the pK_a measurements are based on experimental work conducted by the García‐Moreno lab. Our cross‐validation study demonstrates that the aggregated estimate obtained from BMA outperforms all individual prediction methods with improvements ranging from 45 to 73% over other method classes. This study also compares BMA's predictive performance to other ensemble‐based techniques and demonstrates that BMA can outperform these approaches with improvements ranging from 27 to 60%. This work illustrates a new possible mechanism for improving the accuracy of pK_a prediction and lays the foundation for future work on aggregate models that balance computational cost with prediction accuracy. Proteins 2014; 82:354–363. © 2013 Wiley Periodicals, Inc.