Inferring the rate and time-scale of dengue virus evolution

Dengue is often referred to as an emerging disease because of the rapid increases in incidence and prevalence that have been observed in recent decades. To understand the rate at which genetic diversification occurs in dengue virus and to infer the time-scale of its evolution, we employed a maximum likelihood method that uses information about times of virus sampling to estimate the rate of molecular evolution in a large number of viral envelope (E) gene sequences and to place bounds around the dates of appearance of all serotypes and specific genotypes. Our analysis reveals that dengue virus generally evolves according to a molecular clock, although some serotype-specific and genotype-specific rate differences were observed, and that its origin is more recent than previously suggested, with the virus appearing approximately 1,000 years ago. Furthermore, we estimate that the zoonotic transfer of dengue from sylvatic (monkey) to sustained human transmission occurred between 125 and 320 years ago, that the current global genetic diversity in the four serotypes of dengue virus only appeared during the past century, and that the recent rise in genetic diversity can be loosely correlated both to human activities such as population growth, urbanization, and mass transport and to the emergence of dengue hemorrhagic fever as a major disease problem.     

Models of coding sequence evolution

Probabilistic models of sequence evolution are in widespreaduse in phylogenetics and molecular sequence evolution. Thesemodels have become increasingly sophisticated and combined withstatistical model comparison techniques have helped to shedlight on how genes and proteins evolve. Models of codon evolutionhave been particularly useful, because, in addition to providinga significant improvement in model realism for protein-codingsequences, codon models can also be designed to test hypothesesabout the selective pressures that shape the evolution of thesequences. Such models typically assume a phylogeny and canbe used to identify sites or lineages that have evolved adaptively.Recently some of the key assumptions that underlie phylogenetictests of selection have been questioned, such as the assumptionthat the rate of synonymous changes is constant across sitesor that a single phylogenetic tree can be assumed at all sitesfor recombining sequences. While some of these issues have beenaddressed through the development of novel methods, others remainas caveats that need to be considered on a case-by-case basis.Here, we outline the theory of codon models and their applicationto the detection of positive selection. We review some of themore recent developments that have improved their power andutility, laying a foundation for further advances in the modelingof coding sequence evolution.      

Time-dependent rates of molecular evolution

For over half a century, it has been known that the rate of morphological evolution appears to vary with the time frame of measurement. Rates of microevolutionary change, measured between successive generations, were found to be far higher than rates of macroevolutionary change inferred from the fossil record. More recently, it has been suggested that rates of molecular evolution are also time dependent, with the estimated rate depending on the timescale of measurement. This followed surprising observations that estimates of mutation rates, obtained in studies of pedigrees and laboratory mutation-accumulation lines, exceeded long-term substitution rates by an order of magnitude or more. Although a range of studies have provided evidence for such a pattern, the hypothesis remains relatively contentious. Furthermore, there is ongoing discussion about the factors that can cause molecular rate estimates to be dependent on time. Here we present an overview of our current understanding of time-dependent rates. We provide a summary of the evidence for time-dependent rates in animals, bacteria and viruses. We review the various biological and methodological factors that can cause rates to be time dependent, including the effects of natural selection, calibration errors, model misspecification and other artefacts. We also describe the challenges in calibrating estimates of molecular rates, particularly on the intermediate timescales that are critical for an accurate characterization of time-dependent rates. This has important consequences for the use of molecular-clock methods to estimate timescales of recent evolutionary events.     

The impact of fossils and taxon sampling on ancient molecular dating analyses

The number and complexity of molecular dating studies has increased over the past decade. Along with a broadening acceptance of their utility has come significant controversy over the methods and models that are appropriate, as well as the accuracy of the estimates yielded by molecular clock analyses. Radically different age estimates have been published for the same divergences from analyses of different datasets with different fossil constraints obtained with different methods, and the underlying explanation for these differences is often unclear. Here we utilize two previously published datasets to examine the effect of fossil calibrations and taxon sampling on the age estimates for two deep eukaryote divergences in an attempt to discern the relative impact of these factors. Penalized likelihood, non-parametric rate smoothing, and Bayesian methods were utilized to generate age estimates for the origin of the Metazoa from a 7-gene dataset and for the divergence of Eukaryotes from a 129-gene dataset. From these analyses, it is clear that the fossil calibrations chosen and the method for applying constraints to these nodes have a large impact on age estimates, while the degree of taxon sampling within a dataset is less important in terms of the resulting age estimates. Concerns and recommendations for addressing these two factors when initiating a dating analysis are discussed.     

Tempo and mode of mitochondrial DNA evolution in vertebrates at the amino acid sequence level: Rapid evolution in warm-blooded vertebrates

Summary By using complete sequence data of mitochondrial DNAs, three Markov models (Day-hoff, Proportional, and Poisson models) for amino acid substitutions during evolution were applied in maximum likelihood analyses of mitochondrially encoded proteins to estimate a phylogenetic tree depicting human, cow, whale, and murids (mouse and rat), with chicken, frog, and carp as outgroups. A cow/whale clade was confirmed with a more than 99.8% confidence level by any of the three models, but the branching order among human, murids, and the cow/whale clade remained uncertain. It turned out that the Dayhoff model is by far the most appropriate model among the alternatives in approximating the amino acid substitutions of mitochondrially encoded proteins, which is consistent with a previous analysis of a more limited data set. It was shown that the substitution rate of mitochondrially encoded proteins has increased in the order of fishes, amphibians, birds, and mammals and that the rate in mammals is at least six times, probably an order of magnitude, higher than that in fishes. The higher evolutionary rate in birds and mammals than in amphibians and fishes was attributed to relaxation of selective constraints operating on proteins in warm-blooded vertebrates and to high mutation rate of bird and mammalian mitochondrial DNAs.Offprint requests to: M. Hasegawa     

Effects of allometry,productivity and lifestyle on rates and limits of body size evolution

Body size affects nearly all aspects of organismal biology, so it is important to understand the constraints and dynamics of body size evolution. Despite empirical work on the macroevolution and macroecology of minimum and maximum size, there is little general quantitative theory on rates and limits of body size evolution. We present a general theory that integrates individual productivity, the lifestyle component of the slow–fast life-history continuum, and the allometric scaling of generation time to predict a clade''s evolutionary rate and asymptotic maximum body size, and the shape of macroevolutionary trajectories during diversifying phases of size evolution. We evaluate this theory using data on the evolution of clade maximum body sizes in mammals during the Cenozoic. As predicted, clade evolutionary rates and asymptotic maximum sizes are larger in more productive clades (e.g. baleen whales), which represent the fast end of the slow–fast lifestyle continuum, and smaller in less productive clades (e.g. primates). The allometric scaling exponent for generation time fundamentally alters the shape of evolutionary trajectories, so allometric effects should be accounted for in models of phenotypic evolution and interpretations of macroevolutionary body size patterns. This work highlights the intimate interplay between the macroecological and macroevolutionary dynamics underlying the generation and maintenance of morphological diversity.     

Comparative methods for the analysis of gene-expression evolution: an example using yeast functional genomic data

Understanding the evolution of gene function is a primary challenge of modern evolutionary biology. Despite an expanding database from genomic and developmental studies, we are lacking quantitative methods for analyzing the evolution of some important measures of gene function, such as gene-expression patterns. Here, we introduce phylogenetic comparative methods to compare different models of gene-expression evolution in a maximum-likelihood framework. We find that expression of duplicated genes has evolved according to a nonphylogenetic model, where closely related genes are no more likely than more distantly related genes to share common expression patterns. These results are consistent with previous studies that found rapid evolution of gene expression during the history of yeast. The comparative methods presented here are general enough to test a wide range of evolutionary hypotheses using genomic-scale data from any organism.     

Joint estimation of contemporary seed and pollen dispersal rates among plant populations

There are few statistical methods for estimating contemporary dispersal among plant populations. A maximum-likelihood procedure is introduced here that uses pre- and post-dispersal population samples of biparentally inherited genetic markers to jointly estimate contemporary seed and pollen immigration rates from a set of discrete external sources into a target population. Monte Carlo simulations indicate that accurate estimates and reliable confidence intervals can be obtained using this method for both pollen and seed migration rates at modest sample sizes (100 parents/population and 100 offspring) when population differentiation is moderate (F(ST) ≥ 0.1), or by increasing pre-dispersal samples (to about 500 parents/population) when genetic divergence is weak (F(ST) = 0.01). The method exhibited low sensitivity to the number of source populations and achieved good accuracy at affordable genetic resolution (10 loci with 10 equifrequent alleles each). Unsampled source populations introduced positive biases in migration rate estimates from sampled sources, although they were minor when the proportion of immigration from the latter was comparatively low. A practical application of the method to a metapopulation of the Australian resprouter shrub Banksia attenuata revealed comparable levels of directional seed and pollen migration among dune groups, and the estimate of seed dispersal was higher than a previous estimate based on conservative assignment tests. The method should be of interest to researchers and managers assessing broad-scale nonequilibrium seed and pollen gene flow dynamics in plants.     

The origin and evolution of porcine reproductive and respiratory syndrome viruses

Porcine reproductive and respiratory syndrome viruses (PRRSV) are divided into North American and European types, which show about 40% difference in their amino acid sequences. The divergence time of these two types has been estimated to be about 1980 from epidemiological data. This suggested that PRRSV have evolved at a higher evolutionary rate (order of 10(-2)/site/year) compared with other RNA viruses of 10(-3) to 10(-5)/site/year. Here, to test the evolutionary history of PRRSV speculated by the epidemiological background, we estimated the divergence time and evolutionary rate of PRRSV with molecular evolutionary analysis. Estimated divergence time (1972-1988) corresponded well to that estimated by the epidemiological data, and the evolutionary rate (4.71-9.8) x 10(-2) of PRRSV was indeed the highest among RNA viruses so far reported. Furthermore, we inferred important sites for the adaptation in order to examine how PRRSV have adapted to swine since they emerged. The adaptive sites were located not only in the epitopes related to immunity but also in the transmembrane regions including a signal peptide. In particular, the adaptive sites in the transmembrane regions were considered to affect compatibility to the host cell membrane. We conclude that PRRSV were transmitted from another host species to swine in about 1980 and have adapted to swine by altering the transmembrane regions.     

Independent evolutionary origins of landlocked alewife populations and rapid parallel evolution of phenotypic traits

Alewife, Alosa pseudoharengus, populations occur in two discrete life-history variants, an anadromous form and a landlocked (freshwater resident) form. Landlocked populations display a consistent pattern of life-history divergence from anadromous populations, including earlier age at maturity, smaller adult body size, and reduced fecundity. In Connecticut (USA), dams constructed on coastal streams separate anadromous spawning runs from lake-resident landlocked populations. Here, we used sequence data from the mtDNA control region and allele frequency data from five microsatellite loci to ask whether coastal Connecticut landlocked alewife populations are independently evolved from anadromous populations or whether they share a common freshwater ancestor. We then used microsatellite data to estimate the timing of the divergence between anadromous and landlocked populations. Finally, we examined anadromous and landlocked populations for divergence in foraging morphology and used divergence time estimates to calculate the rate of evolution for foraging traits. Our results indicate that landlocked populations have evolved multiple times independently. Tests of population divergence and estimates of gene flow show that landlocked populations are genetically isolated, whereas anadromous populations exchange genes. These results support a 'phylogenetic raceme' model of landlocked alewife divergence, with anadromous populations forming an ancestral core from which landlocked populations independently diverged. Divergence time estimates suggest that landlocked populations diverged from a common anadromous ancestor no longer than 5000 years ago and perhaps as recently as 300 years ago, depending on the microsatellite mutation rate assumed. Examination of foraging traits reveals landlocked populations to have significantly narrower gapes and smaller gill raker spacings than anadromous populations, suggesting that they are adapted to foraging on smaller prey items. Estimates of evolutionary rates (in haldanes) indicate rapid evolution of foraging traits, possibly in response to changes in available resources.     

Heterogeneous rate of protein evolution in serotonin genes

Serotonin (5-hydroxytryptamine) is a neurotransmitter crucial for cardiovascular, gastrointestinal, and brain function. It is also involved in several aspects of behavior and associated with a variety of personality disorders in humans. Its dual role as a crucial element in vital physiological functions (strictly evolutionary conserved) and in traits that differ substantially across species makes the evolution of serotonin function particularly interesting. We studied the evolution of serotonin function through the identification of the selective forces shaping the evolution of genes in its functional pathway in primates and rodents. Serotonin genes are highly conserved and show no signals of positive selection, suggesting functional constraint as the main force driving their evolution. They show, nevertheless, considerable differences in constraint between primates and rodents, with some genes showing dramatic differences between the 2 groups. These genes most likely represent cases of functional divergence between primates and rodents and point out to the relevance of using closely related species in gene-based evolutionary studies to avoid the effect of unrecognized functional differences between distant species. Within each group (rodents or primates), genes also show heterogeneity in evolution. Genes from the same gene family (with structure and function alike) tend to evolve at a similar rate, but this is not always the case. A few serotonin genes show substantial differences in constraint with the rest of members of their family, suggesting the presence of important and unrecognized functional differences among the genes, which may be involved in species-specific evolution.     

Application of pattern-mixture models to outcomes that are potentially missing not at random using pseudo maximum likelihood estimation

In this work, we fit pattern-mixture models to data sets with responses that are potentially missing not at random (MNAR, Little and Rubin, 1987). In estimating the regression parameters that are identifiable, we use the pseudo maximum likelihood method based on exponential families. This procedure provides consistent estimators when the mean structure is correctly specified for each pattern, with further information on the variance structure giving an efficient estimator. The proposed method can be used to handle a variety of continuous and discrete outcomes. A test built on this approach is also developed for model simplification in order to improve efficiency. Simulations are carried out to compare the proposed estimation procedure with other methods. In combination with sensitivity analysis, our approach can be used to fit parsimonious semi-parametric pattern-mixture models to outcomes that are potentially MNAR. We apply the proposed method to an epidemiologic cohort study to examine cognition decline among elderly.     

A mitogenomic timescale for birds detects variable phylogenetic rates of molecular evolution and refutes the standard molecular clock

Current understanding of the diversification of birds is hindered by their incomplete fossil record and uncertainty in phylogenetic relationships and phylogenetic rates of molecular evolution. Here we performed the first comprehensive analysis of mitogenomic data of 48 vertebrates, including 35 birds, to derive a Bayesian timescale for avian evolution and to estimate rates of DNA evolution. Our approach used multiple fossil time constraints scattered throughout the phylogenetic tree and accounts for uncertainties in time constraints, branch lengths, and heterogeneity of rates of DNA evolution. We estimated that the major vertebrate lineages originated in the Permian; the 95% credible intervals of our estimated ages of the origin of archosaurs (258 MYA), the amniote-amphibian split (356 MYA), and the archosaur-lizard divergence (278 MYA) bracket estimates from the fossil record. The origin of modern orders of birds was estimated to have occurred throughout the Cretaceous beginning about 139 MYA, arguing against a cataclysmic extinction of lineages at the Cretaceous/Tertiary boundary. We identified fossils that are useful as time constraints within vertebrates. Our timescale reveals that rates of molecular evolution vary across genes and among taxa through time, thereby refuting the widely used mitogenomic or cytochrome b molecular clock in birds. Moreover, the 5-Myr divergence time assumed between 2 genera of geese (Branta and Anser) to originally calibrate the standard mitochondrial clock rate of 0.01 substitutions per site per lineage per Myr (s/s/l/Myr) in birds was shown to be underestimated by about 9.5 Myr. Phylogenetic rates in birds vary between 0.0009 and 0.012 s/s/l/Myr, indicating that many phylogenetic splits among avian taxa also have been underestimated and need to be revised. We found no support for the hypothesis that the molecular clock in birds "ticks" according to a constant rate of substitution per unit of mass-specific metabolic energy rather than per unit of time, as recently suggested. Our analysis advances knowledge of rates of DNA evolution across birds and other vertebrates and will, therefore, aid comparative biology studies that seek to infer the origin and timing of major adaptive shifts in vertebrates.     

Low rates of expression profile divergence in highly expressed genes and tissue-specific genes during mammalian evolution

Evolutionary rates provide important information about the pattern and mechanism of evolution. Although the rate of gene sequence evolution has been well studied, the rate of gene expression evolution is poorly understood. In particular, it is unclear whether the gene expression level and tissue specificity influence the divergence of expression profiles between orthologous genes. Here we address this question using a microarray data set comprising the expression signals of 10,607 pairs of orthologous human and mouse genes from over 60 tissues per species. We show that the level of gene expression and the degree of tissue specificity are generally conserved between the human and mouse orthologs. The rate of gene expression profile change during evolution is negatively correlated with the level of gene expression, measured by either the average or the highest level among all tissues examined. This is analogous to the observation that the rate of gene (or protein) sequence evolution is negatively correlated with the gene expression level. The impacts of the degree of tissue specificity on the evolutionary rate of gene sequence and that of expression profile, however, are opposite. Highly tissue-specific genes tend to evolve rapidly at the gene sequence level but slowly at the expression profile level. Thus, different forces and selective constraints must underlie the evolution of gene sequence and that of gene expression.