Quartet-mapping, a generalization of the likelihood-mapping procedure.

Likelihood-mapping (LM) was suggested as a method of displaying the phylogenetic content of an alignment. However, statistical properties of the method have not been studied. Here we analyze the special case of a four-species tree generated under a range of evolution models and compare the results with those of a natural extension of the likelihood-mapping approach, geometry-mapping (GM), which is based on the method of statistical geometry in sequence space. The methods are compared in their abilities to indicate the correct topology. The performance of both methods in detecting the star topology is especially explored. Our results show that LM tends to reject a star tree more often than GM. When assumptions about the evolutionary model of the maximum-likelihood reconstruction are not matched by the true process of evolution, then LM shows a tendency to favor one tree, whereas GM correctly detects the star tree except for very short outer branch lengths with a statistical significance of >0.95 for all models. LM, on the other hand, reconstructs the correct bifurcating tree with a probability of >0.95 for most branch length combinations even under models with varying substitution rates. The parameter domain for which GM recovers the true tree is much smaller. When the exterior branch lengths are larger than a (analytically derived) threshold value depending on the tree shape (rather than the evolutionary model), GM reconstructs a star tree rather than the true tree. We suggest a combined approach of LM and GM for the evaluation of starlike trees. This approach offers the possibility of testing for significant positive interior branch lengths without extensive statistical and computational efforts.     

Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo

The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon--known as heterotachy--can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.     

A novel comparative method for identifying shifts in the rate of character evolution on trees

Evolutionary biologists since Darwin have been fascinated by differences in the rate of trait-evolutionary change across lineages. Despite this continued interest, we still lack methods for identifying shifts in evolutionary rates on the growing tree of life while accommodating uncertainty in the evolutionary process. Here we introduce a Bayesian approach for identifying complex patterns in the evolution of continuous traits. The method (auteur) uses reversible-jump Markov chain Monte Carlo sampling to more fully characterize the complexity of trait evolution, considering models that range in complexity from those with a single global rate to potentially ones in which each branch in the tree has its own independent rate. This newly introduced approach performs well in recovering simulated rate shifts and simulated rates for datasets nearing the size typical for comparative phylogenetic study (i.e., ≥64 tips). Analysis of two large empirical datasets of vertebrate body size reveal overwhelming support for multiple-rate models of evolution, and we observe exceptionally high rates of body-size evolution in a group of emydid turtles relative to their evolutionary background. auteur will facilitate identification of exceptional evolutionary dynamics, essential to the study of both adaptive radiation and stasis.     

Accelerated Evolutionary Rate May Be Responsible for the Emergence of Lineage-Specific Genes in Ascomycota

The evolutionary origin of “orphan” genes, genes that lack sequence similarity to any known gene, remains a mystery. One suggestion has been that most orphan genes evolve rapidly so that similarity to other genes cannot be traced after a certain evolutionary distance. This can be tested by examining the divergence rates of genes with different degrees of lineage specificity. Here the lineage specificity (LS) of a gene describes the phylogenetic distribution of that gene’s orthologues in related species. Highly lineage-specific genes will be distributed in fewer species in a phylogeny. In this study, we have used the complete genomes of seven ascomycotan fungi and two animals to define several levels of LS, such as Eukaryotes-core, Ascomycota-core, Euascomycetes-specific, Hemiascomycetes-specific, Aspergillus-specific, and Saccharomyces-specific. We compare the rates of gene evolution in groups of higher LS to those in groups with lower LS. Molecular evolutionary analyses indicate an increase in nonsynonymous nucleotide substitution rates in genes with higher LS. Several analyses suggest that LS is correlated with the evolutionary rate of the gene. This correlation is stronger than those of a number of other factors that have been proposed as predictors of a gene’s evolutionary rate, including the expression level of genes, gene essentiality or dispensability, and the number of protein-protein interactions. The accelerated evolutionary rates of genes with higher LS may reflect the influence of selection and adaptive divergence during the emergence of orphan genes. These analyses suggest that accelerated rates of gene evolution may be responsible for the emergence of apparently orphan genes. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. [Reviewing Editor: Dr. Martin Kreitman]     

False-positive results obtained from the branch-site test of positive selection

Natural selection operating at the amino acid sequence level can be detected by comparing the rates of synonymous (r(S)) and nonsynonymous (r(N)) nucleotide substitutions, where r(N)/r(S) (omega) > 1 and omega < 1 suggest positive and negative selection, respectively. The branch-site test has been developed for detecting positive selection operating at a group of amino acid sites for a pre-specified (foreground) branch of a phylogenetic tree by taking into account the heterogeneity of omega among sites and branches. Here the performance of the branch-site test was examined by computer simulation, with special reference to the false-positive rate when the divergence of the sequences analyzed was small. The false-positive rate was found to inflate when the assumptions made on the omega values for the foreground and other (background) branches in the branch-site test were violated. In addition, under a similar condition, false-positive results were often obtained even when Bonferroni correction was conducted and the false-discovery rate was controlled in a large-scale analysis. False-positive results were also obtained even when the number of nonsynonymous substitutions for the foreground branch was smaller than the minimum value required for detecting positive selection. The existence of a codon site with a possibility of occurrence of multiple nonsynonymous substitutions for the foreground branch often caused the branch-site test to falsely identify positive selection. In the re-analysis of orthologous trios of protein-coding genes from humans, chimpanzees, and macaques, most of the genes previously identified to be positively selected for the human or chimpanzee branch by the branch-site test contained such a codon site, suggesting a possibility that a significant fraction of these genes are false-positives.     

Evaluation of methods for determination of a reconstructed history of gene sequence evolution

With whole-genome sequences being completed at an increasing rate, it is important to develop and assess tools to analyze them. Following annotation of the protein content of a genome, one can compare sequences with previously characterized homologous genes to detect novel functions within specific proteins in the evolution of the newly sequenced genome. One common statistical method to detect such changes is to compare the ratios of nonsynonymous (K(a)) to synonymous (K(s)) nucleotide substitution rates. Here, the effects of several parameters that can influence this calculation (sequence reconstruction method, phylogenetic tree branch length weighting, GC content, and codon bias) are examined. Also, two new alternative measures of adaptive evolution, the point accepted mutations (PAM)/neutral evolutionary distance (NED) ratio and the sequence space assessment (SSA) statistic are presented. All of these methods are compared using two sequence families: the recent divergence of leptin orthologs in primates, and the more ancient divergence of the deoxyribonucleoside kinase family. The examination of these and other measures to detect changes of gene function along branches of a phylogenetic tree will become increasingly important in the postgenomic era.     

Statistical method for estimating the standard errors of branch lengths in a phylogenetic tree reconstructed without assuming equal rates of nucleotide substitution among different lineages.

A statistical method is developed for estimating the standard errors of branch lengths in a phylogenetic tree reconstructed without assuming equal rates of nucleotide substitution among different lineages. This method can be easily used for testing whether the length of an interior branch in a reconstructed tree is positive, i.e., whether the topology of the tree is correct. Computer simulations indicate that this method is appropriate for a statistical test. As an example, this method is applied to phylogenetic trees reconstructed for the four hominoid species: human, chimpanzee, gorilla, and orangutan. The results obtained show that the present method provides a powerful statistical test.     

PHYLOGENETIC ANALYSES OF THE CORRELATED EVOLUTION OF CONTINUOUS CHARACTERS: A SIMULATION STUDY

We use computer simulation to compare the statistical properties of several methods that have been proposed for estimating the evolutionary correlation between two continuous traits, and define alternative evolutionary correlations that may be of interest. We focus on Felsenstein's (1985) method and some variations of it and on several “minimum evolution” methods (of which the procedure of Huey and Bennett [1987] is a special case), as compared with a nonphylogenetic correlation. The last, a simple correlation of trait values across the tips of a phylogeny, virtually always yields inflated Type I error rates, relatively low power, and relatively poor estimates of evolutionary correlations. We therefore cannot recommend its use. In contrast, Felsenstein's (1985) method yields acceptable significance tests, high power, and good estimates of what we term the input correlation and the standardized realized evolutionary correlation, given complete phylogenetic information and knowledge of the rate and mode of character change (e.g., gradual and proportional to time [“Brownian motion”] or punctuational, with change only at speciation events). Inaccurate branch length information may affect any method adversely, but only rarely does it cause Felsenstein's (1985) method to perform worse than do the others tested. Other proposed methods generally yield inflated Type I error rates and have lower power. However, certain minimum evolution methods (although not the specific procedure used by Huey and Bennett [1987]) often provide more accurate estimates of what we term the unstandardized realized evolutionary correlation, and their use is recommended when estimation of this correlation is desired. We also demonstrate how correct Type I error rates can be obtained for any method by reference to an empirical null distribution derived from computer simulations, and provide practical suggestions on choosing an analytical method, based both on the evolutionary correlation of interest and on the availability of branch lengths and knowledge of the model of evolutionary change appropriate for the characters being analyzed. Computer programs that implement the various methods and that will simulate (correlated) character evolution along a known phylogeny are available from the authors on request. These programs can be used to test the effectiveness of any new methods that might be proposed, and to check the generality of our conclusions with regard to other phylogenies.     

Intron evolution: a statistical comparison of two models.

The two most frequently occurring explanations for the existence and distribution of introns in the genes of different species are: (1) introns are remnants of the original genetic material. (2) Introns were introduced during evolution. We construct mathematical models corresponding to these two explanations, and calculate the probabilities that the intron distribution in genes from different species coding for actin, alpha-tubulin, triosephosphate isomerase and superoxide dismutase are described by these models. In both models, the branch lengths as well as the structure of the corresponding evolutionary tree is taken into account. Every branch in the evolutionary tree is assumed to have its own individual rate of loss of introns for the first model and rate of gain of introns for the second model. These rate constants are estimated from the actual number of introns. Using the rate constants we stimulate the intron evolution and calculate the probabilities that the actual intron arrangements are produced. The results for actin and alpha-tubulin, which are the two genes we have the most data for, favor the model corresponding conjecture (1), i.e. the idea that introns are old. This contradicts the results from an earlier attempt to model intron evolution where almost the same data was used (Dibb & Newman, 1989, EMBO J. 8, 2015-2021).     

Determining evolutionary distances from highly diverged nucleic acid sequences: Operator metrics

Summary Operator metrics are explicity designed to measure evolutionary distances from nucleic acid sequences when substitution rates differ greatly among the organisms being compared, or when substitutions have been extensive. Unlike lengths calculated by the distance matrix and parsimony methods, in which substitutions in one branch of a tree can alter the measured length of another branch, lengths determined by operator metrics are not affected by substitutions outside the branch.In the method, lengths (operator metrics) corresponding to each of the branches of an unrooted tree are calculated. The metric length of a branch reconstructs the number of (transversion) differences between sequences at a tip and a node (or between nodes) of a tree. The theory is general and is fundamentally independent of differences in substitution rates among the organisms being compared. Mathematically, the independence has been obtained becuase the metrics are eigen vectors of fundamental equations which describe the evolution of all unrooted trees.Even under conditions when both the distance matrix method or a simple parsimony length method are show to indicate lengths than are an order of magnitude too large or too small, the operator metrics are accurate. Examples, using data calculated with evolutionary rates and branchings designed to confuse the measurement of branch lengths and to camouflage the topology of the true tree, demonstrate the validity of operator metrics. The method is robust. Operator metric distances are easy to calculated, can be extended to any number of taxa, and provide a statistical estimate of their variances.The utility of the method is demonstrated by using it to analyze the origins and evolutionary of chloroplasts, mitochondria, and eubacteria.     

Hotspots of Biased Nucleotide Substitutions in Human Genes

Genes that have experienced accelerated evolutionary rates on the human lineage during recent evolution are candidates for involvement in human-specific adaptations. To determine the forces that cause increased evolutionary rates in certain genes, we analyzed alignments of 10,238 human genes to their orthologues in chimpanzee and macaque. Using a likelihood ratio test, we identified protein-coding sequences with an accelerated rate of base substitutions along the human lineage. Exons evolving at a fast rate in humans have a significant tendency to contain clusters of AT-to-GC (weak-to-strong) biased substitutions. This pattern is also observed in noncoding sequence flanking rapidly evolving exons. Accelerated exons occur in regions with elevated male recombination rates and exhibit an excess of nonsynonymous substitutions relative to the genomic average. We next analyzed genes with significantly elevated ratios of nonsynonymous to synonymous rates of base substitution (d_N/d_S) along the human lineage, and those with an excess of amino acid replacement substitutions relative to human polymorphism. These genes also show evidence of clusters of weak-to-strong biased substitutions. These findings indicate that a recombination-associated process, such as biased gene conversion (BGC), is driving fixation of GC alleles in the human genome. This process can lead to accelerated evolution in coding sequences and excess amino acid replacement substitutions, thereby generating significant results for tests of positive selection.     

Ancestral inference and the study of codon bias evolution: implications for molecular evolutionary analyses of the Drosophila melanogaster subgroup

Reliable inference of ancestral sequences can be critical to identifying both patterns and causes of molecular evolution. Robustness of ancestral inference is often assumed among closely related species, but tests of this assumption have been limited. Here, we examine the performance of inference methods for data simulated under scenarios of codon bias evolution within the Drosophila melanogaster subgroup. Genome sequence data for multiple, closely related species within this subgroup make it an important system for studying molecular evolutionary genetics. The effects of asymmetric and lineage-specific substitution rates (i.e., varying levels of codon usage bias and departures from equilibrium) on the reliability of ancestral codon usage was investigated. Maximum parsimony inference, which has been widely employed in analyses of Drosophila codon bias evolution, was compared to an approach that attempts to account for uncertainty in ancestral inference by weighting ancestral reconstructions by their posterior probabilities. The latter approach employs maximum likelihood estimation of rate and base composition parameters. For equilibrium and most non-equilibrium scenarios that were investigated, the probabilistic method appears to generate reliable ancestral codon bias inferences for molecular evolutionary studies within the D. melanogaster subgroup. These reconstructions are more reliable than parsimony inference, especially when codon usage is strongly skewed. However, inference biases are considerable for both methods under particular departures from stationarity (i.e., when adaptive evolution is prevalent). Reliability of inference can be sensitive to branch lengths, asymmetry in substitution rates, and the locations and nature of lineage-specific processes within a gene tree. Inference reliability, even among closely related species, can be strongly affected by (potentially unknown) patterns of molecular evolution in lineages ancestral to those of interest.     

A PARAMETRIC METHOD FOR ASSESSING DIVERSIFICATION‐RATE VARIATION IN PHYLOGENETIC TREES

Phylogenetic hypotheses are frequently used to examine variation in rates of diversification across the history of a group. Patterns of diversification‐rate variation can be used to infer underlying ecological and evolutionary processes responsible for patterns of cladogenesis. Most existing methods examine rate variation through time. Methods for examining differences in diversification among groups are more limited. Here, we present a new method, parametric rate comparison (PRC), that explicitly compares diversification rates among lineages in a tree using a variety of standard statistical distributions. PRC can identify subclades of the tree where diversification rates are at variance with the remainder of the tree. A randomization test can be used to evaluate how often such variance would appear by chance alone. The method also allows for comparison of diversification rate among a priori defined groups. Further, the application of the PRC method is not restricted to monophyletic groups. We examined the performance of PRC using simulated data, which showed that PRC has acceptable false‐positive rates and statistical power to detect rate variation. We apply the PRC method to the well‐studied radiation of North American Plethodon salamanders, and support the inference that the large‐bodied Plethodon glutinosus clade has a higher historical rate of diversification compared to other Plethodon salamanders.     

Rate Variation as a Function of Gene Origin in Plastid-Derived Genes of Peridinin-Containing Dinoflagellates

Peridinin-pigmented dinoflagellates contain secondary plastids that seem to have undergone more nearly complete plastid genome reduction than other eukaryotes. Many typically plastid-encoded genes appear to have been transferred to the nucleus, with a few remaining genes found on minicircles. To understand better the evolution of the dinoflagellate plastid, four categories of plastid-associated genes in dinoflagellates were defined based on their history of transfer and evaluated for rate of sequence evolution, including minicircle genes (presumably plastid-encoded), genes probably transferred from the plastid to the nucleus (plastid-transferred), and genes that were likely acquired directly from the nucleus of the previous plastid host (nuclear-transferred). The fourth category, lateral-transferred genes, are plastid-associated genes that do not appear to have a cyanobacterial origin. The evolutionary rates of these gene categories were compared using relative rate tests and likelihood ratio tests. For comparison with other secondary plastid-containing organisms, rates were calculated for the homologous sequences from the haptophyte Emiliania huxleyi. The evolutionary rate of minicircle and plastid-transferred genes in the dinoflagellate was strikingly higher than that of nuclear-transferred and lateral-transferred genes and, also, substantially higher than that of all plastid-associated genes in the haptophyte. Plastid-transferred genes in the dinoflagellate had an accelerated rate of evolution that was variable but, in most cases, not as extreme as the minicircle genes. Furthermore, the nuclear-transferred and lateral-transferred genes showed rates of evolution that are similar to those of other taxa. Thus, nucleus-to-nucleus transferred genes have a more typical rate of sequence evolution, while those whose history was wholly or partially within the dinoflagellate plastid genome have a markedly accelerated rate of evolution. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. [Reviewing Editor: Dr. Debashish Battacharya]     

Interior-branch and bootstrap tests of phylogenetic trees

We have compared statistical properties of the interior-branch and bootstrap tests of phylogenetic trees when the neighbor-joining tree- building method is used. For each interior branch of a predetermined topology, the interior-branch and bootstrap tests provide the confidence values, PC and PB, respectively, that indicate the extent of statistical support of the sequence cluster generated by the branch. In phylogenetic analysis these two values are often interpreted in the same way, and if PC and PB are high (say, > or = 0.95), the sequence cluster is regarded as reliable. We have shown that PC is in fact the complement of the P-value used in the standard statistical test, but PB is not. Actually, the bootstrap test usually underestimates the extent of statistical support of species clusters. The relationship between the confidence values obtained by the two tests varies with both the topology and expected branch lengths of the true (model) tree. The most conspicuous difference between PC and PB is observed when the true tree is starlike, and there is a tendency for the difference to increase as the number of sequences in the tree increases. The reason for this is that the bootstrap test tends to become progressively more conservative as the number of sequences in the tree increases. Unlike the bootstrap, the interior-branch test has the same statistical properties irrespective of the number of sequences used when a predetermined tree is considered. Therefore, the interior-branch test appears to be preferable to the bootstrap test as long as unbiased estimators of evolutionary distances are used. However, when the interior-branch is applied to a tree estimated from a given data set, PC may give an overestimate of statistical confidence. For this case, we developed a method for computing a modified version (P'C) of the PC value and showed that this P'C tends to give a conservative estimate of statistical confidence, though it is not as conservative as PB. In this paper we have introduced a model in which evolutionary distances between sequences follow a multivariate normal distribution. This model allowed us to study the relationships between the two tests analytically.      

Limitations of the evolutionary parsimony method of phylogenetic analysis [published erratum appears in Mol Biol Evol 1990 Mar;7(2):201]

Lake's evolutionary parsimony (EP) method of constructing a phylogenetic tree is primarily applied to four DNA sequences. In this method, three quantities--X, Y, and Z--that correspond to three possible unrooted trees are computed, and an invariance property of these quantities is used for choosing the best tree. However, Lake's method depends on a number of unrealistic assumptions. We therefore examined the theoretical basis of his method and reached the following conclusions: (1) When the rates of two transversional changes from a nucleotide are unequal, his invariance property breaks down. (2) Even if the rates of two transversional changes are equal, the invariance property requires some additional conditions. (3) When Kimura's two- parameter model of nucleotide substitution applies and the rate of nucleotide substitution varies greatly with branch, the EP method is generally better than the standard maximum-parsimony (MP) method in recovering the correct tree but is inferior to the neighbor-joining (NJ) and a few other distance matrix methods. (4) When the rate of nucleotide substitution is the same or nearly the same for all branches, the EP method is inferior to the MP method even if the proportion of transitional changes is high. (5) When Lake's assumptions fail, his chi2 test may identify an erroneous tree as the correct tree. This happens because the test is not for comparing different trees. (6) As long as a proper distance measure is used, the NJ method is better than the EP and MP methods whether there is a transition/transversion bias or whether there is variation in substitution rate among different nucleotide sites.      

载脂蛋白多基因家族分子进化的研究

与脂质运输有关的载脂蛋白基因构成一个复杂的多基因家族。为探讨这种演化时间长的基因家族的进化规律,本文首先建立了一种在非均衡进化速率条件下计算系统发生树中任意分支长度的简易方法,并可在此基础上算出无根分支系统树中分歧年代的期望值。进一步对本文科１０个种属共２６种载脂蛋白的系统演作作了实际分析,结果提示：①ＡｐｏＡ－Ｉ＇ＡｐｏＡ－ＩＶ,ＡｐｏＥ及ＡｐｏＡ－ＩＩ的共同祖先可能在奥陶纪水生脊椎动物中就已存     

ABRUPT DECELERATION OF MOLECULAR EVOLUTION LINKED TO THE ORIGIN OF ARBORESCENCE IN FERNS

Molecular rate heterogeneity, whereby rates of molecular evolution vary among groups of organisms, is a well‐documented phenomenon. Nonetheless, its causes are poorly understood. For animals, generation time is frequently cited because longer‐lived species tend to have slower rates of molecular evolution than their shorter‐lived counterparts. Although a similar pattern has been uncovered in flowering plants, using proxies such as growth form, the underlying process has remained elusive. Here, we find a deceleration of molecular evolutionary rate to be coupled with the origin of arborescence in ferns. Phylogenetic branch lengths within the “tree fern” clade are considerably shorter than those of closely related lineages, and our analyses demonstrate that this is due to a significant difference in molecular evolutionary rate. Reconstructions reveal that an abrupt rate deceleration coincided with the evolution of the long‐lived tree‐like habit at the base of the tree fern clade. This suggests that a generation time effect may well be ubiquitous across the green tree of life, and that the search for a responsible mechanism must focus on characteristics shared by all vascular plants. Discriminating among the possibilities will require contributions from various biological disciplines, but will be necessary for a full appreciation of molecular evolution.     

Detecting positive selection within genomes: the problem of biased gene conversion

The identification of loci influenced by positive selection is a major goal of evolutionary genetics. A popular approach is to perform scans of alignments on a genome-wide scale in order to find regions evolving at accelerated rates on a particular branch of a phylogenetic tree. However, positive selection is not the only process that can lead to accelerated evolution. Notably, GC-biased gene conversion (gBGC) is a recombination-associated process that results in the biased fixation of G and C nucleotides. This process can potentially generate bursts of nucleotide substitutions within hotspots of meiotic recombination. Here, we analyse the results of a scan for positive selection on genes on branches across the primate phylogeny. We show that genes identified as targets of positive selection have a significant tendency to exhibit the genomic signature of gBGC. Using a maximum-likelihood framework, we estimate that more than 20 per cent of cases of significantly elevated non-synonymous to synonymous substitution rates ratio (d_N/d_S), particularly in shorter branches, could be due to gBGC. We demonstrate that in some cases, gBGC can lead to very high d_N/d_S (more than 2). Our results indicate that gBGC significantly affects the evolution of coding sequences in primates, often leading to patterns of evolution that can be mistaken for positive selection.     

Dissecting Genomic Determinants of Positive Selection with an Evolution-Guided Regression Model

In evolutionary genomics, it is fundamentally important to understand how characteristics of genomic sequences, such as gene expression level, determine the rate of adaptive evolution. While numerous statistical methods, such as the McDonald–Kreitman (MK) test, are available to examine the association between genomic features and the rate of adaptation, we currently lack a statistical approach to disentangle the independent effect of a genomic feature from the effects of other correlated genomic features. To address this problem, I present a novel statistical model, the MK regression, which augments the MK test with a generalized linear model. Analogous to the classical multiple regression model, the MK regression can analyze multiple genomic features simultaneously to infer the independent effect of a genomic feature, holding constant all other genomic features. Using the MK regression, I identify numerous genomic features driving positive selection in chimpanzees. These features include well-known ones, such as local mutation rate, residue exposure level, tissue specificity, and immune genes, as well as new features not previously reported, such as gene expression level and metabolic genes. In particular, I show that highly expressed genes may have a higher adaptation rate than their weakly expressed counterparts, even though a higher expression level may impose stronger negative selection. Also, I show that metabolic genes may have a higher adaptation rate than their nonmetabolic counterparts, possibly due to recent changes in diet in primate evolution. Overall, the MK regression is a powerful approach to elucidate the genomic basis of adaptation.