Compound tests for the detection of hitchhiking under positive selection

Many statistical tests have been developed for detecting positive selection. Most of these tests draw conclusions based on significant deviations from the patterns of polymorphism predicted by the neutral model. However, many non-equilibrium forces may cause similar deviations, and thus the tests usually have low statistical specificity to positive selection. The main challenge is hence to construct test statistics that are reasonably powerful in detecting positive selection, but are relatively insensitive to other forces. Recently, Zeng et al. (2006) proposed a new test, DH, which is a compound of Tajima's D and Fay and Wu's H, and showed that DH has reasonably high statistical specificity to positive selection. In this report, we expand the idea of a compound test by combining Fay and Wu's H or DH with the Ewens-Watterson (EW) test. We refer to these 2 new tests as HEW and DHEW, respectively. Compared to the DH test, HEW and DHEW are more robust against the presence of recombination, and are also more powerful in detecting positive selection. Furthermore, the DHEW test, similar to DH, is also relatively insensitive to background selection and demography. The HEW test, on the other hand, tends to be somewhat less conservative than DH and DHEW in some cases.     

Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level

Detecting positive Darwinian selection at the DNA sequence level has been a subject of considerable interest. However, positive selection is difficult to detect because it often operates episodically on a few amino acid sites, and the signal may be masked by negative selection. Several methods have been developed to test positive selection that acts on given branches (branch methods) or on a subset of sites (site methods). Recently, Yang, Z., and R. Nielsen (2002. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol. Biol. Evol. 19:908-917) developed likelihood ratio tests (LRTs) based on branch-site models to detect positive selection that affects a small number of sites along prespecified lineages. However, computer simulations suggested that the tests were sensitive to the model assumptions and were unable to distinguish between relaxation of selective constraint and positive selection (Zhang, J. 2004. Frequent false detection of positive selection by the likelihood method with branch-site models. Mol. Biol. Evol. 21:1332-1339). Here, we describe a modified branch-site model and use it to construct two LRTs, called branch-site tests 1 and 2. We applied the new tests to reanalyze several real data sets and used computer simulation to examine the performance of the two tests by examining their false-positive rate, power, and robustness. We found that test 1 was unable to distinguish relaxed constraint from positive selection affecting the lineages of interest, while test 2 had acceptable false-positive rates and appeared robust against violations of model assumptions. As test 2 is a direct test of positive selection on the lineages of interest, it is referred to as the branch-site test of positive selection and is recommended for use in real data analysis. The test appeared conservative overall, but exhibited better power in detecting positive selection than the branch-based test. Bayes empirical Bayes identification of amino acid sites under positive selection along the foreground branches was found to be reliable, but lacked power.     

Not so different after all: a comparison of methods for detecting amino acid sites under selection

We consider three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection: (1) a suite of fast likelihood-based counting methods that employ either a single most likely ancestral reconstruction, weighting across all possible ancestral reconstructions, or sampling from ancestral reconstructions; (2) a random effects likelihood (REL) approach, which models variation in nonsynonymous and synonymous rates across sites according to a predefined distribution, with the selection pressure at an individual site inferred using an empirical Bayes approach; and (3) a fixed effects likelihood (FEL) method that directly estimates nonsynonymous and synonymous substitution rates at each site. All three methods incorporate flexible models of nucleotide substitution bias and variation in both nonsynonymous and synonymous substitution rates across sites, facilitating the comparison between the methods. We demonstrate that the results obtained using these approaches show broad agreement in levels of Type I and Type II error and in estimates of substitution rates. Counting methods are well suited for large alignments, for which there is high power to detect positive and negative selection, but appear to underestimate the substitution rate. A REL approach, which is more computationally intensive than counting methods, has higher power than counting methods to detect selection in data sets of intermediate size but may suffer from higher rates of false positives for small data sets. A FEL approach appears to capture the pattern of rate variation better than counting methods or random effects models, does not suffer from as many false positives as random effects models for data sets comprising few sequences, and can be efficiently parallelized. Our results suggest that previously reported differences between results obtained by counting methods and random effects models arise due to a combination of the conservative nature of counting-based methods, the failure of current random effects models to allow for variation in synonymous substitution rates, and the naive application of random effects models to extremely sparse data sets. We demonstrate our methods on sequence data from the human immunodeficiency virus type 1 env and pol genes and simulated alignments.     

Site-directed mutagenesis using positive antibiotic selection

Various mutsgenesis protocols have been established that use the hybridization of a mismatched oligonucleotide to prime DNA synthesis on an M13 phagemid template. For efficient mutagenesis, all of these methods require a means to select for the mutant strand before or during amplification in anEscherichia coli host. In the Altered Sites II protocol, the mismatched oligonucleotide and an oligonucleotide that restores antibiotic resistance to the phagemid are simultaneously hybridized to the template and coupled by DNA synthesis and ligation. The restored antibiotic resistance is then used to select only those phagemids which incorporate the antibiotic repair oligonucleotide. Generally, between 60 and 90% of the phagemids recovered will incorporate both oligonucleotides. This method provides a simple an efficient technique for introducing specific mutations into DNA.     

Haplotype structure and evidence for positive selection at the human IL13 locus

Interleukin-13 (IL13) is believed to play an important role in the pathogenesis of atopy and allergic asthma. To better understand genetic variation at the IL13 locus, we resequenced a 5.1-kb genomic region spanning the entire locus and identified 26 single-nucleotide polymorphisms (SNPs) in 74 individuals from three major populations-Chinese, Caucasian, and African. Our survey suggests exceptionally high and significant geographic structure at the IL13 locus between African and outside Africa populations. This unusual pattern suggests that positive selection that acts in some local populations may have played a role on the IL13 locus. In support of this suggestion, we found a significant excess of high frequency-derived SNPs in the Chinese population and Caucasian population, respectively, as expected after a recent episode of positive selection. Further, the unusual haplotype structure indicates that different scenarios of the action of positive selection on the IL13 locus in different populations may exist. In the Caucasian population, the skewed haplotype distribution dominated by one common haplotype supports the hypothesis of simple directional selection. Whereas, in the Chinese population, the two-round hitchhiking hypothesis may explain the skewed haplotype structure with three dominant ones. These findings may provide insight into the likely relative roles of selection and population history in establishing present-day variation at the IL13 locus, and, motivate further studies of this locus as an important candidate in common diseases association studies.     

Widespread positive selection in synonymous sites of mammalian genes

Evolution of protein sequences is largely governed by purifying selection, with a small fraction of proteins evolving under positive selection. The evolution at synonymous positions in protein-coding genes is not nearly as well understood, with the extent and types of selection remaining, largely, unclear. A statistical test to identify purifying and positive selection at synonymous sites in protein-coding genes was developed. The method compares the rate of evolution at synonymous sites (Ks) to that in intron sequences of the same gene after sampling the aligned intron sequences to mimic the statistical properties of coding sequences. We detected purifying selection at synonymous sites in approximately 28% of the 1,562 analyzed orthologous genes from mouse and rat, and positive selection in approximately 12% of the genes. Thus, the fraction of genes with readily detectable positive selection at synonymous sites is much greater than the fraction of genes with comparable positive selection at nonsynonymous sites, i.e., at the level of the protein sequence. Unlike other genes, the genes with positive selection at synonymous sites showed no correlation between Ks and the rate of evolution in nonsynonymous sites (Ka), indicating that evolution of synonymous sites under positive selection is decoupled from protein evolution. The genes with purifying selection at synonymous sites showed significant anticorrelation between Ks and expression level and breadth, indicating that highly expressed genes evolve slowly. The genes with positive selection at synonymous sites showed the opposite trend, i.e., highly expressed genes had, on average, higher Ks. For the genes with positive selection at synonymous sites, a significantly lower mRNA stability is predicted compared to the genes with negative selection. Thus, mRNA destabilization could be an important factor driving positive selection in nonsynonymous sites, probably, through regulation of expression at the level of mRNA degradation and, possibly, also translation rate. So, unexpectedly, we found that positive selection at synonymous sites of mammalian genes is substantially more common than positive selection at the level of protein sequences. Positive selection at synonymous sites might act through mRNA destabilization affecting mRNA levels and translation.     

Statistical methods for detecting molecular adaptation

The past few years have seen the development of powerful statistical methods for detecting adaptive molecular evolution. These methods compare synonymous and nonsynonymous substitution rates in protein-coding genes, and regard a nonsynonymous rate elevated above the synonymous rate as evidence for darwinian selection. Numerous cases of molecular adaptation are being identified in various systems from viruses to humans. Although previous analyses averaging rates over sites and time have little power, recent methods designed to detect positive selection at individual sites and lineages have been successful. Here, we summarize recent statistical methods for detecting molecular adaptation, and discuss their limitations and possible improvements.     

A Bayesian model comparison approach to inferring positive selection

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

Evidence for positive selection on Drosophila melanogaster seminal fluid protease homologs

Proteins present in the seminal fluid of Drosophila melanogaster (accessory gland proteins Acps) contribute to female postmating behavioral changes, sperm storage, sperm competition, and immunity. Consequently, male-female coevolution and host-pathogen interactions are thought to underlie the rapid, adaptive evolution that characterizes several Acp-encoding genes. We propose that seminal fluid proteases are likely targets of selection due to their demonstrated or potential roles in between-sex interactions and immune processes. We use within- and between-species sequence data for 5 predicted protease-encoding Acp loci to test this hypothesis. Our polymorphism-based analyses find evidence for positive selection at 2 genes, both of which encode predicted serine protease homologs. One of these genes, CG6069, also shows evidence for consistent selection on a subset of codons over a deeper evolutionary time scale. The second gene, CG9997, was previously shown to be essential for normal sperm usage, suggesting that sexual selection may underlie its history of adaptation.     

Evidence for positive selection on the floral scent gene isoeugenol-O-methyltransferase

Isoeugenol-O-methyltransferase (IEMT) is an enzyme involved in the production of the floral volatile compounds methyl eugenol and methyl isoeugenol in Clarkia breweri (Onagraceae). IEMT likely evolved by gene duplication from caffeic acid-O-methyltransferase followed by amino acid divergence, leading to the acquisition of its novel function. To investigate the selective context under which IEMT evolved, maximum likelihood methods that estimate variable d(N)/d(S) ratios among lineages, among sites, and among a combination of both lineages and sites were utilized. Statistically significant support was obtained for a hypothesis of positive selection driving the evolution of IEMT since its origin. Subsequent Bayesian analyses identified several sites in IEMT that have experienced positive selection. Most of these positions are in the active site of IEMT and have been shown by site-directed mutagenesis to have large effects on substrate specificity. Although the selective agent is unknown, the adaptive evolution of this gene may have resulted in increased effectiveness of pollinator attraction or herbivore repellence.     

Maximum likelihood methods for detecting adaptive evolution after gene duplication

The rapid accumulation of genomic sequences in public databases will finally allow large scale studies of gene family evolution, including evaluation of the role of positive Darwinian selection following a duplication event. This will be possible because recent statistical methods of comparing synonymous and nonsynonymous substitution rates permit reliable detection of positive selection at individual amino acid sites and along evolutionary lineages. Here, we summarize maximum-likelihood based methods, and present a framework for their application to analysis of gene families. Using these methods, we investigated the role of positive Darwinian selection in the ECP-EDN gene family of primates and the Troponin C gene family of vertebrates. We also comment on the limitations of these methods and discuss directions for further improvements.     

Maximum-likelihood methods for detecting recent positive selection and localizing the selected site in the genome

Two maximum-likelihood methods are proposed for detecting recent, strongly positive selection and for localizing the target of selection along a recombining chromosome. The methods utilize the compact mutation frequency spectrum at multiple neutral loci that are partially linked to the selected site. Using simulated data, we show that the power of the tests lies between 80 and 98% in most cases, and the false positive rate could be as low as approximately 10% when the number of sampled marker loci is sufficiently large (> or = 20). The confidence interval around the estimated position of selection is reasonably narrow. The methods are applied to X chromosome data of Drosophila melanogaster from a European and an African population. Evidence of selection was found for both populations (including a selective sweep that was shared between both populations).     

Major role of positive selection in the evolution of conservative segments of Drosophila proteins

Slow evolution of conservative segments of coding and non-coding DNA is caused by the action of negative selection, which removes new mutations. However, the mode of selection that affects the few substitutions that do occur within such segments remains unclear. Here, we show that the fraction of allele replacements that were driven by positive selection, and the strength of this selection, is the highest within the conservative segments of Drosophila protein-coding genes. The McDonald-Kreitman test, applied to the data on variation in Drosophila melanogaster and in Drosophila simulans, indicates that within the most conservative protein segments, approximately 72 per cent (approx. 80%) of allele replacements were driven by positive selection, as opposed to only approximately 44 per cent (approx. 53%) at rapidly evolving segments. Data on multiple non-synonymous substitutions at a codon lead to the same conclusion and additionally indicate that positive selection driving allele replacements at conservative sites is the strongest, as it accelerates evolution by a factor of approximately 40, as opposed to a factor of approximately 5 at rapidly evolving sites. Thus, random drift plays only a minor role in the evolution of conservative DNA segments, and those relatively rare allele replacements that occur within such segments are mostly driven by substantial positive selection.     

Haplotype allelic classes for detecting ongoing positive selection

Background  

Natural selection eliminates detrimental and favors advantageous phenotypes. This process leaves characteristic signatures in underlying genomic segments that can be recognized through deviations in allelic or haplotypic frequency spectra. To provide an identifiable signature of recent positive selection that can be detected by comparison with the background distribution, we introduced a new way of looking at genomic polymorphisms: haplotype allelic classes.     

Reliabilities of parsimony-based and likelihood-based methods for detecting positive selection at single amino acid sites.

The reliabilities of parsimony-based and likelihood-based methods for inferring positive selection at single amino acid sites were studied using the nucleotide sequences of human leukocyte antigen (HLA) genes, in which positive selection is known to be operating at the antigen recognition site. The results indicate that the inference by parsimony-based methods is robust to the use of different evolutionary models and generally more reliable than that by likelihood-based methods. In contrast, the results obtained by likelihood-based methods depend on the models and on the initial parameter values used. It is sometimes difficult to obtain the maximum likelihood estimates of parameters for a given model, and the results obtained may be false negatives or false positives depending on the initial parameter values. It is therefore preferable to use parsimony-based methods as long as the number of sequences is relatively large and the branch lengths of the phylogenetic tree are relatively small.     

Stabilizing selection on behavior and morphology masks positive selection on the signal in a salamander pheromone signaling complex

Natural selection maintains the integration and coordination of sets of phenotypic characters that collectively perform a task. In functional complexes in which characters span molecular to behavioral levels of organization, we might then expect similar modes of selection to produce similar patterns in evolutionary divergence at each level. To test this expectation, we diagnosed selection at behavioral, morphological, and molecular levels for courtship pheromone signaling by plethodontid salamanders. At the levels of morphology and behavior tens of millions of years of stasis (stabilizing selection) occur on each side of a transition from vaccination to olfactory delivery modes. As a proxy for the molecular level, we used plethodontid receptivity factor (PRF), a protein that is an active component of the pheromone. We cloned PRF from 12 Plethodon spp. spanning the delivery transition and obtained multiple alleles from each individual surveyed. Analyses of 61 alleles for PRF identified elevated nonsynonymous over synonymous substitution rates along lineages in a molecular phylogeny, and at 8% of sites in the protein, indicating that positive (directional) selection has acted on this vertebrate pheromone gene. Structural models showed PRF is in a family of cytokines characterized by a four-alpha-helix bundle. Positive selection in PRF was associated with receptor binding sites that are under purifying selection in other cytokines of that family. The evolutionary dynamics of the plethodontid pheromone delivery complex consists of stabilizing selection on morphological and behavioral aspects of signal delivery but positive selection on the signal mediated by receptors. Thus, different selection modes prevail at different levels in this reproductive functional complex. Evolutionary studies of integrated sets of characters therefore require separate analyses of selective action at each level.     

Comparisons of positive assortative mating and sexual selection models

A series of theoretical models of positive assortative mating and sexual selection are contrasted. It is established that for a dominant trait partial positive assortative mating generally implies some fixation, whereas sexual selection exhibits a unique globally stable polymorphism exhibiting Hardy-Weinberg proportions. The effects of monogamy against polygamy do not qualitatively alter the equilibrium outcomes, although the rate of evolutionary change is generally slowed with monogamy vis-à-vis polygamy. For sexual selection the influence of timing of random mating as against preferential mating causes no change in the equilibrium states, although the rates of convergence can be slowed if sexual selection occurs late in the breeding season. Under assortative mating the timing can alter the equilibrium outcomes. The amount of heterozygosity is always deficient in cases of assortative mating, but always exhibits Hardy-Weinberg ratios under a sexual selection mechanism. This suggests that observations consistent with Hardy-Weinberg equilibrium states cannot preclude ipso facto certain forms of selection forces, including mating patterns and some natural selection structures.     

The effect of positive selection on a sexual reproduction gene in Thalassiosira weissflogii (Bacillariophyta): results obtained from maximum-likelihood and parsimony-based methods

Maximum-Likelihood-based and parsimony-based methods were used to test for potential effects of positive selection on the sexually induced gene 1 (Sig1) in Thalassiosira weissflogii. The Sig proteins are thought to play a role in mediating sperm-egg recognition during the sexual reproduction phase. The results obtained from parsimony-based analyses showed that none of the amino acid sites were influenced by positive selection. Maximum-likelihood analyses indicated that positive selection was affecting a maximum of seven and a minimum of four amino acid sites in the polypeptide derived from Sig1. It was concluded that the results obtained from the maximum-likelihood-based method are more reliable than those obtained from the parsimony-based approach. This is apparently the first study that has shown that reproductive proteins in unicellular eukaryotes are influenced by positive selection.     

Frequent false detection of positive selection by the likelihood method with branch-site models

Positive Darwinian selection promotes fixations of advantageous mutations during gene evolution and is probably responsible for most adaptations. Detecting positive selection at the DNA sequence level is of substantial interest because such information provides significant insights into possible functional alterations during gene evolution as well as important nucleotide substitutions involved in adaptation. Efficient detection of positive selection, however, has been difficult because selection often operates on only a few sites in a short period of evolutionary time. A likelihood-based method with branch-site models was recently introduced to overcome such difficulties. Here I examine the accuracy of the method using computer simulation. I find that the method detects positive selection in 20%-70% of cases when the DNA sequences are generated by computer simulation under no positive selection. Although the frequency of such false detection varies depending on, among other things, the tree topology, branch length, and selection scheme, the branch-site likelihood method generally gives misleading results. Thus, detection of positive selection by this method alone is unreliable. This unreliability may have resulted from its over-sensitivity to violations of assumptions made in the method, such as certain distributions of selective strength among sites and equal transition/transversion ratios for synonymous and nonsynonymous substitutions.