Search

Previous studies revealed extensive genetic introgression between Ovis species, which affects genetic adaptation and morphological traits. However, the exact evolutionary scenarios underlying the hybridization between sheep and allopatric wild relatives remain unknown. To address this problem, we here integrate the reference genomes of several ovine and caprine species: domestic sheep, argali, bighorn sheep, snow sheep, and domestic goats. Additionally, we use 856 whole genomes representing 169 domestic sheep populations and their six wild relatives: Asiatic mouflon, urial, argali, snow sheep, thinhorn sheep, and bighorn sheep. We implement a comprehensive set of analyses to test introgression among these species. We infer that the argali lineage originated ∼3.08 to 3.35 Mya and hybridized with the ancestor of Pachyceriforms (e.g. bighorn sheep and snow sheep) at ∼1.56 Mya. Previous studies showed apparent introgression from North American Pachyceriforms into the Bashibai sheep, a Chinese native sheep breed, despite of their wide geographic separation. We show here that, in fact, the apparent introgression from the Pachyceriforms into Bashibai can be explained by the old introgression from Pachyceriforms into argali and subsequent recent introgression from argali into Bashibai. Our results illustrate the challenges of estimating complex introgression histories and provide an example of how indirect and direct introgression can be distinguished., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

We here present CLUES2, a full-likelihood method to infer natural selection from sequence data that is an extension of the method CLUES. We make several substantial improvements to the CLUES method that greatly increases both its applicability and its speed. We add the ability to use ancestral recombination graphs on ancient data as emissions to the underlying hidden Markov model, which enables CLUES2 to use both temporal and linkage information to make estimates of selection coefficients. We also fully implement the ability to estimate distinct selection coefficients in different epochs, which allows for the analysis of changes in selective pressures through time, as well as selection with dominance. In addition, we greatly increase the computational efficiency of CLUES2 over CLUES using several approximations to the forward-backward algorithms and develop a new way to reconstruct historic allele frequencies by integrating over the uncertainty in the estimation of the selection coefficients. We illustrate the accuracy of CLUES2 through extensive simulations and validate the importance sampling framework for integrating over the uncertainty in the inference of gene trees. We also show that CLUES2 is well-calibrated by showing that under the null hypothesis, the distribution of log-likelihood ratios follows a χ2 distribution with the appropriate degrees of freedom. We run CLUES2 on a set of recently published ancient human data from Western Eurasia and test for evidence of changing selection coefficients through time. We find significant evidence of changing selective pressures in several genes correlated with the introduction of agriculture to Europe and the ensuing dietary and demographic shifts of that time. In particular, our analysis supports previous hypotheses of strong selection on lactase persistence during periods of ancient famines and attenuated selection in more modern periods., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Segregation distorters (SDs) are genetic elements that distort the Mendelian segregation ratio to favor their own transmission and are able to spread even when they incur fitness costs on organisms carrying them. Depending on the biology of the host organisms and the genetic architecture of the SDs, the population dynamics of SDs can be highly variable. Inbreeding is considered an effective mechanism for inhibiting the spread of SDs in populations, and can evolve as a defense mechanism against SDs in some systems. However, we show that inbreeding in the form of selfing in fact promotes the spread of SDs acting as pollen killers in a toxin-antidote system in hermaphroditic plants by two mechanisms: (i) By reducing the effective recombination rate between killer and antidote loci in the two-locus system and (ii) by increasing the proportion of SD alleles in individual flowers, rather than in the general gene-pool. We also show that in rice (Oryza sativa L.), a typical hermaphroditic plant, all molecularly characterized SDs associated with pollen killing were involved in population hybridization and have introgressed across different species. Paradoxically, these loci, which are associated with hybrid incompatibility and can be thought of as Bateson-Dobzhansky-Muller incompatibility loci are expected to reduce gene-flow between species, in fact cross species boundaries more frequently than random loci, and may act as important drivers of introgression., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Commonly used methods for inferring phylogenies were designed before the emergence of high-throughput sequencing and can generally not accommodate the challenges associated with noisy, diploid sequencing data. In many applications, diploid genomes are still treated as haploid through the use of ambiguity characters; while the uncertainty in genotype calling-arising as a consequence of the sequencing technology-is ignored. In order to address this problem, we describe two new probabilistic approaches for estimating genetic distances: distAngsd-geno and distAngsd-nuc, both implemented in a software suite named distAngsd. These methods are specifically designed for next-generation sequencing data, utilize the full information from the data, and take uncertainty in genotype calling into account. Through extensive simulations, we show that these new methods are markedly more accurate and have more stable statistical behaviors than other currently available methods for estimating genetic distances-even for very low depth data with high error rates., (© The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

One of the most powerful and commonly used approaches for detecting local adaptation in the genome is the identification of extreme allele frequency differences between populations. In this article, we present a new maximum likelihood method for finding regions under positive selection. It is based on a Gaussian approximation to allele frequency changes and it incorporates admixture between populations. The method can analyze multiple populations simultaneously and retains power to detect selection signatures specific to ancestry components that are not representative of any extant populations. Using simulated data, we compare our method to related approaches, and show that it is orders of magnitude faster than the state-of-the-art, while retaining similar or higher power for most simulation scenarios. We also apply it to human genomic data and identify loci with extreme genetic differentiation between major geographic groups. Many of the genes identified are previously known selected loci relating to hair pigmentation and morphology, skin, and eye pigmentation. We also identify new candidate regions, including various selected loci in the Native American component of admixed Mexican-Americans. These involve diverse biological functions, such as immunity, fat distribution, food intake, vision, and hair development., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Throughout its distribution across Eurasia, domestic pig (Sus scrofa) populations have acquired differences through natural and artificial selection, and have often interbred. We resequenced 80 Eurasian pigs from nine different Asian and European breeds; we identify 42,288 reliable SNPs on the Y chromosome in a panel of 103 males, among which 96.1% are newly detected. Based on these new data, we elucidate the evolutionary history of pigs through the lens of the Y chromosome. We identify two highly divergent haplogroups: one present only in Asia and one fixed in Europe but present in some Asian populations. Analyzing the European haplotypes present in Asian populations, we find evidence of three independent waves of introgression from Europe to Asia in last 200 years, agreeing well with the literature and historical records. The diverse European lineages were brought in China by humans and left significant imprints not only on the autosomes but also on the Y chromosome of geographically and genetically distinct Chinese pig breeds. We also find a general excess of European ancestry on Y chromosomes relative to autosomes in Chinese pigs, an observation that cannot be explained solely by sex-biased migration and genetic drift. The European Y haplotype is associated with leaner meat production, and we hypothesize that the European Y chromosome increased in frequency in Chinese populations due to artificial selection. We find evidence of Y chromosomal gene flow between Sumatran wild boar and Chinese pigs. Our results demonstrate how human-mediated admixture and selection shaped the distribution of modern swine Y chromosomes., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Adaptive introgression-the flow of adaptive genetic variation between species or populations-has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a hidden Markov model-based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized data sets for realistic population and selection parameters. We apply Ancestry_HMM-S to a data set of an admixed Drosophila melanogaster population from South Africa and we identify 17 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in data sets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

The rooting of the SARS-CoV-2 phylogeny is important for understanding the origin and early spread of the virus. Previously published phylogenies have used different rootings that do not always provide consistent results. We investigate several different strategies for rooting the SARS-CoV-2 tree and provide measures of statistical uncertainty for all methods. We show that methods based on the molecular clock tend to place the root in the B clade, whereas methods based on outgroup rooting tend to place the root in the A clade. The results from the two approaches are statistically incompatible, possibly as a consequence of deviations from a molecular clock or excess back-mutations. We also show that none of the methods provide strong statistical support for the placement of the root in any particular edge of the tree. These results suggest that phylogenetic evidence alone is unlikely to identify the origin of the SARS-CoV-2 virus and we caution against strong inferences regarding the early spread of the virus based solely on such evidence., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Genetic introgression not only provides material for adaptive evolution but also confounds our understanding of evolutionary history. This is particularly true for canids, a species complex in which genome sequencing and analysis has revealed a complex history of admixture and introgression. Here, we sequence 19 new whole genomes from high-altitude Tibetan and Himalayan wolves and dogs and combine these into a larger data set of 166 whole canid genomes. Using these data, we explore the evolutionary history and adaptation of these and other canid lineages. We find that Tibetan and Himalayan wolves are closely related to each other, and that ∼39% of their nuclear genome is derived from an as-yet-unrecognized wolf-like lineage that is deeply diverged from living Holarctic wolves and dogs. The EPAS1 haplotype, which is present at high frequencies in Tibetan dog breeds and wolves and confers an adaptive advantage to animals living at high altitudes, was probably derived from this ancient lineage. Our study underscores the complexity of canid evolution and demonstrates how admixture and introgression can shape the evolutionary trajectories of species., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

There are many compelling examples of molecular convergence at individual genes. However, the prevalence and the relative importance of adaptive genome-wide convergence remain largely unknown. Many recent works have reported striking examples of excess genome-wide convergence, but some of these studies have been called into question because of the use of inappropriate null models. Here, we sequenced and compared the genomes of 12 species of anole lizards that have independently converged on suites of adaptive behavioral and morphological traits. Despite extensive searches for a genome-wide signature of molecular convergence, we found no evidence supporting molecular convergence at specific amino acids either at individual genes or at genome-wide comparisons; we also uncovered no evidence supporting an excess of adaptive convergence in the rates of amino acid substitutions within genes. Our findings indicate that comprehensive phenotypic convergence is not mirrored at genome-wide protein-coding levels in anoles, and therefore, that adaptive phenotypic convergence is likely not constrained by the evolution of many specific protein sequences or structures., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The probability of point mutations is expected to be highly influenced by the flanking nucleotides that surround them, known as the sequence context. This phenomenon may be mainly attributed to the enzyme that modifies or mutates the genetic material, because most enzymes tend to have specific sequence contexts that dictate their activity. Here, we develop a statistical model that allows for the detection and evaluation of the effects of different sequence contexts on mutation rates from deep population sequencing data. This task is computationally challenging, as the complexity of the model increases exponentially as the context size increases. We established our novel Bayesian method based on sparse model selection methods, with the leading assumption that the number of actual sequence contexts that directly influence mutation rates is minuscule compared with the number of possible sequence contexts. We show that our method is highly accurate on simulated data using pentanucleotide contexts, even when accounting for noisy data. We next analyze empirical population sequencing data from polioviruses and HIV-1 and detect a significant enrichment in sequence contexts associated with deamination by the cellular deaminases ADAR 1/2 and APOBEC3G, respectively. In the current era, where next-generation sequencing data are highly abundant, our approach can be used on any population sequencing data to reveal context-dependent base alterations and may assist in the discovery of novel mutable sites or editing sites., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

We sequenced the genome of the strawberry poison frog, Oophaga pumilio, at a depth of 127.5× using variable insert size libraries. The total genome size is estimated to be 6.76 Gb, of which 4.76 Gb are from high copy number repetitive elements with low differentiation across copies. These repeats encompass DNA transposons, RNA transposons, and LTR retrotransposons, including at least 0.4 and 1.0 Gb of Mariner/Tc1 and Gypsy elements, respectively. Expression data indicate high levels of gypsy and Mariner/Tc1 expression in ova of O. pumilio compared with Xenopus laevis. We further observe phylogenetic evidence for horizontal transfer (HT) of Mariner elements, possibly between fish and frogs. The elements affected by HT are present in high copy number and are highly expressed, suggesting ongoing proliferation after HT. Our results suggest that the large amphibian genome sizes, at least partially, can be explained by a process of repeated invasion of new transposable elements that are not yet suppressed in the germline. We also find changes in the spliceosome that we hypothesize are related to permissiveness of O. pumilio to increases in intron length due to transposon proliferation. Finally, we identify the complement of ion channels in the first genomic sequenced poison frog and discuss its relation to the evolution of autoresistance to toxins sequestered in the skin.

FADS genes encode fatty acid desaturases that are important for the conversion of short chain polyunsaturated fatty acids (PUFAs) to long chain fatty acids. Prior studies indicate that the FADS genes have been subjected to strong positive selection in Africa, South Asia, Greenland, and Europe. By comparing FADS sequencing data from present-day and Bronze Age (5-3k years ago) Europeans, we identify possible targets of selection in the European population, which suggest that selection has targeted different alleles in the FADS genes in Europe than it has in South Asia or Greenland. The alleles showing the strongest changes in allele frequency since the Bronze Age show associations with expression changes and multiple lipid-related phenotypes. Furthermore, the selected alleles are associated with a decrease in linoleic acid and an increase in arachidonic and eicosapentaenoic acids among Europeans; this is an opposite effect of that observed for selected alleles in Inuit from Greenland. We show that multiple SNPs in the region affect expression levels and PUFA synthesis. Additionally, we find evidence for a gene-environment interaction influencing low-density lipoprotein (LDL) levels between alleles affecting PUFA synthesis and PUFA dietary intake: carriers of the derived allele display lower LDL cholesterol levels with a higher intake of PUFAs. We hypothesize that the selective patterns observed in Europeans were driven by a change in dietary composition of fatty acids following the transition to agriculture, resulting in a lower intake of arachidonic acid and eicosapentaenoic acid, but a higher intake of linoleic acid and α-linolenic acid., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

A recent study conducted the first genome-wide scan for selection in Inuit from Greenland using single nucleotide polymorphism chip data. Here, we report that selection in the region with the second most extreme signal of positive selection in Greenlandic Inuit favored a deeply divergent haplotype that is closely related to the sequence in the Denisovan genome, and was likely introgressed from an archaic population. The region contains two genes, WARS2 and TBX15, and has previously been associated with adipose tissue differentiation and body-fat distribution in humans. We show that the adaptively introgressed allele has been under selection in a much larger geographic region than just Greenland. Furthermore, it is associated with changes in expression of WARS2 and TBX15 in multiple tissues including the adrenal gland and subcutaneous adipose tissue, and with regional DNA methylation changes in TBX15., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

We present a new haplotype-based statistic (nSL) for detecting both soft and hard sweeps in population genomic data from a single population. We compare our new method with classic single-population haplotype and site frequency spectrum (SFS)-based methods and show that it is more robust, particularly to recombination rate variation. However, all statistics show some sensitivity to the assumptions of the demographic model. Additionally, we show that nSL has at least as much power as other methods under a number of different selection scenarios, most notably in the cases of sweeps from standing variation and incomplete sweeps. This conclusion holds up under a variety of demographic models. In many aspects, our new method is similar to the iHS statistic; however, it is generally more robust and does not require a genetic map. To illustrate the utility of our new method, we apply it to HapMap3 data and show that in the Yoruban population, there is strong evidence of selection on genes relating to lipid metabolism. This observation could be related to the known differences in cholesterol levels, and lipid metabolism more generally, between African Americans and other populations. We propose that the underlying causes for the selection on these genes are pleiotropic effects relating to blood parasites rather than their role in lipid metabolism.

Much of the phenotypic variation observed between even closely related species may be driven by differences in gene expression levels. The current availability of reliable techniques like RNA-Seq, which can quantify expression levels across species, has enabled comparative studies. Ornstein-Uhlenbeck (OU) processes have been proposed to model gene expression evolution as they model both random drift and stabilizing selection and can be extended to model changes in selection regimes. The OU models provide a statistical framework that allows comparisons of specific hypotheses of selective regimes, including random drift, constrained drift, and expression level shifts. In this way, inferences may be made about the mode of selection acting on the expression level of a gene. We augment this model to include within-species expression variance, allowing for modeling of nonevolutionary expression variance that could be caused by individual genetic, environmental, or technical variation. Through simulations, we explore the reliability of parameter estimates and the extent to which different selective regimes can be distinguished using phylogenies of varying size using both the typical OU model and our extended model. We find that if individual variation is not accounted for, nonevolutionary expression variation is often mistaken for strong stabilizing selection. The methods presented in this article are increasingly relevant as comparative expression data becomes more available and researchers turn to expression as a primary evolving phenotype.

The Tibetan and Andean Plateaus and Ethiopian highlands are the largest regions to have long-term high-altitude residents. Such populations are exposed to lower barometric pressures and hence atmospheric partial pressures of oxygen. Such "hypobaric hypoxia" may limit physical functional capacity, reproductive health, and even survival. As such, selection of genetic variants advantageous to hypoxic adaptation is likely to have occurred. Identifying signatures of such selection is likely to help understanding of hypoxic adaptive processes. Here, we seek evidence of such positive selection using five Ethiopian populations, three of which are from high-altitude areas in Ethiopia. As these populations may have been recipients of Eurasian gene flow, we correct for this admixture. Using single-nucleotide polymorphism genotype data from multiple populations, we find the strongest signal of selection in BHLHE41 (also known as DEC2 or SHARP1). Remarkably, a major role of this gene is regulation of the same hypoxia response pathway on which selection has most strikingly been observed in both Tibetan and Andean populations. Because it is also an important player in the circadian rhythm pathway, BHLHE41 might also provide insights into the mechanisms underlying the recognized impacts of hypoxia on the circadian clock. These results support the view that Ethiopian, Andean, and Tibetan populations living at high altitude have adapted to hypoxia differently, with convergent evolution affecting different genes from the same pathway.

Environmental or genomic changes during evolution can relax negative selection pressure on specific loci, permitting high frequency polymorphisms at previously conserved sites. Here, we jointly analyze population genomic and comparative genomic data to search for functional processes showing relaxed negative selection specifically in the human lineage, whereas remaining evolutionarily conserved in other mammals. Consistent with previous studies, we find that olfactory receptor genes display such a signature of relaxation in humans. Intriguingly, proteasome genes also show a prominent signal of human-specific relaxation: multiple proteasome subunits, including four members of the catalytic core particle, contain high frequency nonsynonymous polymorphisms at sites conserved across mammals. Chimpanzee proteasome genes do not display a similar trend. Human proteasome genes also bear no evidence of recent positive or balancing selection. These results suggest human-specific relaxation of negative selection in proteasome subunits; the exact biological causes, however, remain unknown.

The use of codon substitution models to compare synonymous and nonsynonymous substitution rates is a widely used approach to detecting positive Darwinian selection affecting protein evolution. However, in several recent papers, Hughes and colleagues claim that codon-based likelihood-ratio tests (LRTs) are logically flawed as they lack prior hypotheses and fail to accommodate random fluctuations in synonymous and nonsynonymous substitutions Friedman and Hughes (2007) also used site-based LRTs to analyze 605 gene families consisting of human and mouse paralogues. They found that the outcome of the tests was largely determined by irrelevant factors such as the GC content at the third codon positions and the synonymous rate d(S), but not by the nonsynonymous rate d(N) or the d(N)/d(S) ratio, factors that should be related to selection. Here, we reanalyze those data. Contra Friedman and Hughes, we found that the test results are related to sequence length and the average d(N)/d(S) ratio. We examine the criticisms of Hughes and suggest that they are based on misunderstandings of the codon models and on statistical errors. Our analyses suggest that codon-based tests are useful tools for comparative analysis of genomic data sets.

In this report, we investigate the statistical power of several tests of selective neutrality based on patterns of genetic diversity within and between species. The goal is to compare tests based solely on population genetic data with tests using comparative data or a combination of comparative and population genetic data. We show that in the presence of repeated selective sweeps on relatively neutral background, tests based on the d(N)/d(S) ratios in comparative data almost always have more power to detect selection than tests based on population genetic data, even if the overall level of divergence is low. Tests based solely on the distribution of allele frequencies or the site frequency spectrum, such as the Ewens-Watterson test or Tajima's D, have less power in detecting both positive and negative selection because of the transient nature of positive selection and the weak signal left by negative selection. The Hudson-Kreitman-Aguadé test is the most powerful test for detecting positive selection among the population genetic tests investigated, whereas McDonald-Kreitman test typically has more power to detect negative selection. We discuss our findings in the light of the discordant results obtained in several recently published genomic scans.

In recent years, several studies have reported the successful extraction of ancient DNA (aDNA) from both frozen and nonfrozen sediments (even in the absence of macrofossils) in order to obtain genetic "profiles" from past environments. One of the hazards associated with this approach, particularly in nonfrozen environments, is the potential for vertical migration of aDNA across strata. To assess the extent of this problem, we extracted aDNA from sediments up to 3300 years old at 2 cave sites in the North Island of New Zealand. These sites are ideal for this purpose as the presence or absence of DNA from nonindigenous fauna (such as sheep) in sediments deposited prior to European settlement can serve as an indicator of DNA movement. Additionally, these strata are well defined and dated. DNA from sheep was found in strata that also contained moa DNA, indicating that genetic material had migrated downwards. Quantitative polymerase chain reaction analyses demonstrated that the amount of sheep DNA decreased as the age of sediments increased. Our results suggest that sedimentary aDNA is unlikely to be deposited from wind-borne DNA and that physical remains of organisms or their ejecta need to have been incorporated in the sediments for their DNA to be detected. Our study indicates that DNA from sediments can still offer a rich source of information on past environments, provided that the risk from vertical migration can be controlled for.

We present a likelihood method for estimating codon usage bias parameters along the lineages of a phylogeny. The method is an extension of the classical codon-based models used for estimating dN/dS ratios along the lineages of a phylogeny. However, we add one extra parameter for each lineage: the selection coefficient for optimal codon usage (S), allowing joint maximum likelihood estimation of S and the dN/dS ratio. We apply the method to previously published data from Drosophila melanogaster, Drosophila simulans, and Drosophila yakuba and show, in accordance with previous results, that the D. melanogaster lineage has experienced a reduction in the selection for optimal codon usage. However, the D. melanogaster lineage has also experienced a change in the biological mutation rates relative to D. simulans, in particular, a relative reduction in the mutation rate from A to G and an increase in the mutation rate from C to T. However, neither a reduction in the strength of selection nor a change in the mutational pattern can alone explain all of the data observed in the D. melanogaster lineage. For example, we also confirm previous results showing that the Notch locus has experienced positive selection for previously classified unpreferred mutations.

We develop codon-based models for simultaneously inferring the mutational effects of CpG and CpNpG methylation in coding regions. In a data set of 369 tomato genes, we show that there is very little effect of CpNpG methylation but a strong effect of CpG methylation affecting almost all genes. We further show that the CpNpG and CpG effects are largely uncorrelated. Our results suggest different roles of CpG and CpNpG methylation, with CpNpG methylation possibly playing a specialized role in defense against transposons and RNA viruses.

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.

Codon-based substitution models have been widely used to identify amino acid sites under positive selection in comparative analysis of protein-coding DNA sequences. The nonsynonymous-synonymous substitution rate ratio (d(N)/d(S), denoted omega) is used as a measure of selective pressure at the protein level, with omega > 1 indicating positive selection. Statistical distributions are used to model the variation in omega among sites, allowing a subset of sites to have omega > 1 while the rest of the sequence may be under purifying selection with omega < 1. An empirical Bayes (EB) approach is then used to calculate posterior probabilities that a site comes from the site class with omega > 1. Current implementations, however, use the naive EB (NEB) approach and fail to account for sampling errors in maximum likelihood estimates of model parameters, such as the proportions and omega ratios for the site classes. In small data sets lacking information, this approach may lead to unreliable posterior probability calculations. In this paper, we develop a Bayes empirical Bayes (BEB) approach to the problem, which assigns a prior to the model parameters and integrates over their uncertainties. We compare the new and old methods on real and simulated data sets. The results suggest that in small data sets the new BEB method does not generate false positives as did the old NEB approach, while in large data sets it retains the good power of the NEB approach for inferring positively selected sites.

Mammalian fertilization exhibits species specificity, and the proteins mediating sperm-egg interactions evolve rapidly between species. In this study, we demonstrate that the evolution of seven genes involved in mammalian fertilization is promoted by positive Darwinian selection by using likelihood ratio tests (LRTs). Several of these proteins are sperm proteins that have been implicated in binding the mammalian egg coat zona pellucida glycoproteins, which were shown previously to be subjected to positive selection. Taken together, these represent the major candidates involved in mammalian fertilization, indicating positive selection is pervasive amongst mammalian reproductive proteins. A new LRT is implemented to determine if the d(N)/d(S) ratio is significantly greater than one. This is a more refined test of positive selection than the previous LRTs which only identified if there was a class of sites with a d(N)/d(S) ratio >1 but did not test if that ratio was significantly greater than one.

The nonsynonymous (amino acid-altering) to synonymous (silent) substitution rate ratio (omega = d(N)/d(S)) provides a measure of natural selection at the protein level, with omega = 1, >1, and <1, indicating neutral evolution, purifying selection, and positive selection, respectively. Previous studies that used this measure to detect positive selection have often taken an approach of pairwise comparison, estimating substitution rates by averaging over all sites in the protein. As most amino acids in a functional protein are under structural and functional constraints and adaptive evolution probably affects only a few sites at a few time points, this approach of averaging rates over sites and over time has little power. Previously, we developed codon-based substitution models that allow the omega ratio to vary either among lineages or among sites. In this paper we extend previous models to allow the omega ratio to vary both among sites and among lineages and implement the new models in the likelihood framework. These models may be useful for identifying positive selection along prespecified lineages that affects only a few sites in the protein. We apply those branch-site models as well as previous branch- and site-specific models to three data sets: the lysozyme genes from primates, the tumor suppressor BRCA1 genes from primates, and the phytochrome (PHY) gene family in angiosperms. Positive selection is detected in the lysozyme and BRCA genes by both the new and the old models. However, only the new models detected positive selection acting on lineages after gene duplication in the PHY gene family. Additional tests on several data sets suggest that the new models may be useful in detecting positive selection after gene duplication in gene family evolution.

We present a new likelihood method for detecting constrained evolution at synonymous sites and other forms of nonneutral evolution in putative pseudogenes. The model is applicable whenever the DNA sequence is available from a protein-coding functional gene, a pseudogene derived from the protein-coding gene, and an orthologous functional copy of the gene. Two nested likelihood ratio tests are developed to test the hypotheses that (1) the putative pseudogene has equal rates of silent and replacement substitutions; and (2) the rate of synonymous substitution in the functional gene equals the rate of substitution in the pseudogene. The method is applied to a data set containing 74 human processed-pseudogene loci, 25 mouse processed-pseudogene loci, and 22 rat processed-pseudogene loci. Using the informatics resources of the Human Genome Project, we localized 67 of the human-pseudogene pairs in the genome and estimated the GC content of a large surrounding genomic region for each. We find that, for pseudogenes deposited in GC regions similar to those of their paralogs, the assumption of equal rates of silent and replacement site evolution in the pseudogene is upheld; in these cases, the rate of silent site evolution in the functional genes is approximately 70% the rate of evolution in the pseudogene. On the other hand, for pseudogenes located in genomic regions of much lower GC than their functional gene, we see a sharp increase in the rate of silent site substitutions, leading to a large rate of rejection for the pseudogene equality likelihood ratio test.

Approximate methods for estimating the numbers of synonymous and nonsynonymous substitutions between two DNA sequences involve three steps: counting of synonymous and nonsynonymous sites in the two sequences, counting of synonymous and nonsynonymous differences between the two sequences, and correcting for multiple substitutions at the same site. We examine complexities involved in those steps and propose a new approximate method that takes into account two major features of DNA sequence evolution: transition/transversion rate bias and base/codon frequency bias. We compare the new method with maximum likelihood, as well as several other approximate methods, by examining infinitely long sequences, performing computer simulations, and analyzing a real data set. The results suggest that when there are transition/transversion rate biases and base/codon frequency biases, previously described approximate methods for estimating the nonsynonymous/synonymous rate ratio may involve serious biases, and the bias can be both positive and negative. The new method is, in general, superior to earlier approximate methods and may be useful for analyzing large data sets, although maximum likelihood appears to always be the method of choice.