Large Subunit Mitochondrial rRNA Secondary Structures and Site-Specific Rate Variation in Two Lizard Lineages

A phylogenetic-comparative approach was used to assess and refine existing secondary structure models for a frequently studied region of the mitochondrial encoded large subunit (16S) rRNA in two large lizard lineages within the Scincomorpha, namely the Scincidae and the Lacertidae. Potential pairings and mutual information were analyzed to identify site interactions present within each lineage and provide consensus secondary structures. Many of the interactions proposed by previous models were supported, but several refinements were possible. The consensus structures allowed a detailed analysis of rRNA sequence evolution. Phylogenetic trees were inferred from Bayesian analyses of all sites, and the topologies used for maximum likelihood estimation of sequence evolution parameters. Assigning gamma-distributed relative rate categories to all interacting sites that were homologous between lineages revealed substantial differences between helices. In both lineages, sites within helix G2 were mostly conserved, while those within helix E18 evolved rapidly. Clear evidence of substantial site-specific rate variation (covarion-like evolution) was also detected, although this was not strongly associated with specific helices. This study, in conjunction with comparable findings on different, higher-level taxa, supports the ubiquitous nature of site-specific rate variation in this gene and justifies the incorporation of covarion models in phylogenetic inference.Reviewing Editor: Dr. Yves Van de Peer     

A covarion-based method for detecting molecular adaptation: application to the evolution of primate mitochondrial genomes

A new method for detecting site-specific variation of evolutionary rate (the so-called covarion process) from protein sequence data is proposed. It involves comparing the maximum-likelihood estimates of the replacement rate of an amino acid site in distinct subtrees of a large tree. This approach allows detection of covarion at the gene or the amino acid levels. The method is applied to mammalian-mitochondrial-protein sequences. Significant covarion-like evolution is found in the (simian) primate lineage: some amino acid positions are fast-evolving (i.e. unconstrained) in non-primate mammals but slow-evolving (i.e. highly constrained) in primates, and some show the opposite pattern. Our results indicate that the mitochondrial genome of primates reached a new peak of the adaptive landscape through positive selection.     

PROCOV: maximum likelihood estimation of protein phylogeny under covarion models and site-specific covarion pattern analysis

Background  

The covarion hypothesis of molecular evolution holds that selective pressures on a given amino acid or nucleotide site are dependent on the identity of other sites in the molecule that change throughout time, resulting in changes of evolutionary rates of sites along the branches of a phylogenetic tree. At the sequence level, covarion-like evolution at a site manifests as conservation of nucleotide or amino acid states among some homologs where the states are not conserved in other homologs (or groups of homologs). Covarion-like evolution has been shown to relate to changes in functions at sites in different clades, and, if ignored, can adversely affect the accuracy of phylogenetic inference.     

Heterotachy processes in rhodophyte-derived secondhand plastid genes: Implications for addressing the origin and evolution of dinoflagellate plastids

Serial transfer of plastids from one eukaryotic host to another is the key process involved in evolution of secondhand plastids. Such transfers drastically change the environment of the plastids and hence the selection regimes, presumably leading to changes over time in the characteristics of plastid gene evolution and to misleading phylogenetic inferences. About half of the dinoflagellate protists species are photosynthetic and unique in harboring a diversity of plastids acquired from a wide range of eukaryotic algae. They are therefore ideal for studying evolutionary processes of plastids gained through secondary and tertiary endosymbioses. In the light of these processes, we have evaluated the origin of 2 types of dinoflagellate plastids, containing the peridinin or 19'-hexanoyloxyfucoxanthin (19'-HNOF) pigments, by inferring the phylogeny using "covarion" evolutionary models allowing the pattern of among-site rate variation to change over time. Our investigations of genes from secondary and tertiary plastids derived from the rhodophyte plastid lineage clearly reveal "heterotachy" processes characterized as stationary covarion substitution patterns and changes in proportion of variable sites across sequences. Failure to accommodate covarion-like substitution patterns can have strong effects on the plastid tree topology. Importantly, multigene analyses performed with probabilistic methods using among-site rate and covarion models of evolution conflict with proposed single origin of the peridinin- and 19'-HNOF-containing plastids, suggesting that analysis of secondhand plastids can be hampered by convergence in the evolutionary signature of the plastid DNA sequences. Another type of sequence convergence was detected at protein level involving the psaA gene. Excluding the psaA sequence from a concatenated protein alignment grouped the peridinin plastid with haptophytes, congruent with all DNA trees. Altogether, taking account of complex processes involved in the evolution of dinoflagellate plastid sequences (both at the DNA and amino acid level), we demonstrate the difficulty of excluding independent, tertiary origin for both the peridinin and 19'-HNOF plastids involving engulfment of haptophyte-like algae. In addition, the refined topologies suggest the red algal order, Porphyridales, as the endosymbiont ancestor of the secondary plastids in cryptophytes, haptophytes, and heterokonts.     

Testing for covarion-like evolution in protein sequences

The covarion hypothesis of molecular evolution proposes that selective pressures on an amino acid or nucleotide site change through time, thus causing changes of evolutionary rate along the edges of a phylogenetic tree. Several kinds of Markov models for the covarion process have been proposed. One model, proposed by Huelsenbeck (2002), has 2 substitution rate classes: the substitution process at a site can switch between a single variable rate, drawn from a discrete gamma distribution, and a zero invariable rate. A second model, suggested by Galtier (2001), assumes rate switches among an arbitrary number of rate classes but switching to and from the invariable rate class is not allowed. The latter model allows for some sites that do not participate in the rate-switching process. Here we propose a general covarion model that combines features of both models, allowing evolutionary rates not only to switch between variable and invariable classes but also to switch among different rates when they are in a variable state. We have implemented all 3 covarion models in a maximum likelihood framework for amino acid sequences and tested them on 23 protein data sets. We found significant likelihood increases for all data sets for the 3 models, compared with a model that does not allow site-specific rate switches along the tree. Furthermore, we found that the general model fit the data better than the simpler covarion models in the majority of the cases, highlighting the complexity in modeling the covarion process. The general covarion model can be used for comparing tree topologies, molecular dating studies, and the investigation of protein adaptation.     

Taking Variation of Evolutionary Rates Between Sites into Account in Inferring Phylogenies

As methods of molecular phylogeny have become more explicit and more biologically realistic following the pioneering work of Thomas Jukes, they have had to relax their initial assumption that rates of evolution were equal at all sites. Distance matrix and likelihood methods of inferring phylogenies make this assumption; parsimony, when valid, is less limited by it. Nucleotide sequences, including RNA sequences, can show substantial rate variation; protein sequences show rates that vary much more widely. Assuming a prior distribution of rates such as a gamma distribution or lognormal distribution has deservedly been popular, but for likelihood methods it leads to computational difficulties. These can be resolved using hidden Markov model (HMM) methods which approximate the distribution by one with a modest number of discrete rates. Generalized Laguerre quadrature can be used to improve the selection of rates and their probabilities so as to more nearly approach the desired gamma distribution. A model based on population genetics is presented predicting how the rates of evolution might vary from locus to locus. Challenges for the future include allowing rates at a given site to vary along the tree, as in the ``covarion' model, and allowing them to have correlations that reflect three-dimensional structure, rather than position in the coding sequence. Markov chain Monte Carlo likelihood methods may be the only practical way to carry out computations for these models. Received: 8 February 2001 / Accepted: 20 May 2001     

Topological Estimation Biases with Covarion Evolution

Covarion processes allow changes in evolutionary rates at sites along the branches of a phylogenetic tree. Covarion-like evolution is increasingly recognized as an important mode of protein evolution. Several recent reports suggest that maximum likelihood estimation employing covarion models may support different optimal topologies than estimation using standard rates-across-sites (RAS) models. However, it remains to be demonstrated that ignoring covarion evolution will generally result in topological misestimation. In this study we performed analytical and theoretical studies of limiting distances under the covarion model and four-taxon tree simulations to investigate the extent to which the covarion process impacts on phylogenetic estimation. In particular, we assessed the limits of an RAS model-based maximum likelihood method to recover the phylogenies when the sequence data were simulated under the covarion processes. We find that, when ignored, covarion processes can induce systematic errors in phylogeny reconstruction. Surprisingly, when sequences are evolved under a covarion process but an RAS model is used for estimation, we find that a long branch repel bias occurs.     

Inferring complex DNA substitution processes on phylogenies using uniformization and data augmentation

A new method is developed for calculating sequence substitution probabilities using Markov chain Monte Carlo (MCMC) methods. The basic strategy is to use uniformization to transform the original continuous time Markov process into a Poisson substitution process and a discrete Markov chain of state transitions. An efficient MCMC algorithm for evaluating substitution probabilities by this approach using a continuous gamma distribution to model site-specific rates is outlined. The method is applied to the problem of inferring branch lengths and site-specific rates from nucleotide sequences under a general time-reversible (GTR) model and a computer program BYPASSR is developed. Simulations are used to examine the performance of the new program relative to an existing program BASEML that uses a discrete approximation for the gamma distributed prior on site-specific rates. It is found that BASEML and BYPASSR are in close agreement when inferring branch lengths, regardless of the number of rate categories used, but that BASEML tends to underestimate high site-specific substitution rates, and to overestimate intermediate rates, when fewer than 50 rate categories are used. Rate estimates obtained using BASEML agree more closely with those of BYPASSR as the number of rate categories increases. Analyses of the posterior distributions of site-specific rates from BYPASSR suggest that a large number of taxa are needed to obtain precise estimates of site-specific rates, especially when rates are very high or very low. The method is applied to analyze 45 sequences of the alpha 2B adrenergic receptor gene (A2AB) from a sample of eutherian taxa. In general, the pattern expected for regions under negative selection is observed with third codon positions having the highest inferred rates, followed by first codon positions and with second codon positions having the lowest inferred rates. Several sites show exceptionally high substitution rates at second codon positions that may represent the effects of positive selection.     

Exploring among-site rate variation models in a maximum likelihood framework using empirical data: effects of model assumptions on estimates of topology,branch lengths,and bootstrap support

We have investigated the effects of different among-site rate variation models on the estimation of substitution model parameters, branch lengths, topology, and bootstrap proportions under minimum evolution (ME) and maximum likelihood (ML). Specifically, we examined equal rates, invariable sites, gamma-distributed rates, and site-specific rates (SSR) models, using mitochondrial DNA sequence data from three protein-coding genes and one tRNA gene from species of the New Zealand cicada genus Maoricicada. Estimates of topology were relatively insensitive to the substitution model used; however, estimates of bootstrap support, branch lengths, and R-matrices (underlying relative substitution rate matrix) were strongly influenced by the assumptions of the substitution model. We identified one situation where ME and ML tree building became inaccurate when implemented with an inappropriate among-site rate variation model. Despite the fact the SSR models often have a better fit to the data than do invariable sites and gamma rates models, SSR models have some serious weaknesses. First, SSR rate parameters are not comparable across data sets, unlike the proportion of invariable sites or the alpha shape parameter of the gamma distribution. Second, the extreme among-site rate variation within codon positions is problematic for SSR models, which explicitly assume rate homogeneity within each rate class. Third, the SSR models appear to give severe underestimates of R-matrices and branch lengths relative to invariable sites and gamma rates models in this example. We recommend performing phylogenetic analyses under a range of substitution models to test the effects of model assumptions not only on estimates of topology but also on estimates of branch length and nodal support.     

Maximum-likelihood estimation of site-specific mutation rates in human mitochondrial DNA from partial phylogenetic classification

The mitochondrial DNA hypervariable segment I (HVS-I) is widely used in studies of human evolutionary genetics, and therefore accurate estimates of mutation rates among nucleotide sites in this region are essential. We have developed a novel maximum-likelihood methodology for estimating site-specific mutation rates from partial phylogenetic information, such as haplogroup association. The resulting estimation problem is a generalized linear model, with a nonstandard link function. We develop inference and bias correction tools for our estimates and a hypothesis-testing approach for site independence. We demonstrate our methodology using 16,609 HVS-I samples from the Genographic Project. Our results suggest that mutation rates among nucleotide sites in HVS-I are highly variable. The 16,400–16,500 region exhibits significantly lower rates compared to other regions, suggesting potential functional constraints. Several loci identified in the literature as possible termination-associated sequences (TAS) do not yield statistically slower rates than the rest of HVS-I, casting doubt on their functional importance. Our tests do not reject the null hypothesis of independent mutation rates among nucleotide sites, supporting the use of site-independence assumption for analyzing HVS-I. Potential extensions of our methodology include its application to estimation of mutation rates in other genetic regions, like Y chromosome short tandem repeats.     

An Empirical Analysis of mt 16S rRNA Covarion-Like Evolution in Insects: Site-Specific Rate Variation Is Clustered and Frequently Detected

The structural and functional analysis of rRNA molecules has attracted considerable scientific interest. Empirical studies have demonstrated that sequence variation is not directly translated into modifications of rRNA secondary structure. Obviously, the maintenance of secondary structure and sequence variation are in part governed by different selection regimes. The nature of those selection regimes still remains quite elusive. The analysis of individual bacterial models cannot adequately explore this topic. Therefore, we used primary sequence data and secondary structures of a mitochondrial 16S rRNA fragment of 558 insect species from 15 monophyletic groups to study patterns of sequence variation, and variation of secondary structure. Using simulation studies to establish significance levels of change, we found that despite conservation of secondary structure, the location of sequence variation within the conserved rRNA structure changes significantly between groups of insects. Despite our conservative estimation procedure we found significant site-specific rate changes at 56 sites out of 184. Additionally, site-specific rate variation is somewhat clustered in certain helices. Both results confirm what has been predicted from an application of non-stationary maximum likelihood models to rRNA sequences. Clearly, constraints on sequence variation evolve and leave footprints in the form of evolutionary plasticity in rRNA sequences. Here, we show that a better understanding of the evolution of rRNA sequences can be obtained by integrating both phylogenetic and structural information.     

A mixed branch length model of heterotachy improves phylogenetic accuracy

Evolutionary relationships are typically inferred from molecular sequence data using a statistical model of the evolutionary process. When the model accurately reflects the underlying process, probabilistic phylogenetic methods recover the correct relationships with high accuracy. There is ample evidence, however, that models commonly used today do not adequately reflect real-world evolutionary dynamics. Virtually all contemporary models assume that relatively fast-evolving sites are fast across the entire tree, whereas slower sites always evolve at relatively slower rates. Many molecular sequences, however, exhibit site-specific changes in evolutionary rates, called "heterotachy." Here we examine the accuracy of 2 phylogenetic methods for incorporating heterotachy, the mixed branch length model--which incorporates site-specific rate changes by summing likelihoods over multiple sets of branch lengths on the same tree--and the covarion model, which uses a hidden Markov process to allow sites to switch between variable and invariable as they evolve. Under a variety of simple heterogeneous simulation conditions, the mixed model was dramatically more accurate than homotachous models, which were subject to topological biases as well as biases in branch length estimates. When data were simulated with strong versions of the types of heterotachy observed in real molecular sequences, the mixed branch length model was more accurate than homotachous techniques. Analyses of empirical data sets confirmed that the mixed branch length model can improve phylogenetic accuracy under conditions that cause homotachous models to fail. In contrast, the covarion model did not improve phylogenetic accuracy compared with homotachous models and was sometimes substantially less accurate. We conclude that a mixed branch length approach, although not the solution to all phylogenetic errors, is a valuable strategy for improving the accuracy of inferred trees.     

Evolution of cd59 gene in mammals

The CD59-coding sequences were obtained from 5 mammals by PCR and BLAST, and combined with the available sequences in GenBank, the nucleotide substitution rates of mammalian cd59 were calcu- lated. Results of synonymous and nonsynonymous substitution rates revealed that cd59 experienced negative selection in mammals overall. Four sites experiencing positive selection were found by using "site-specific" model in PAML software. These sites were distributed on the molecular surface, of which 2 sites located in the key functional domain. Furthermore, "branch-site-specific" model detected 1 positive site in cd59a and cd59b lineages which underwent accelerated evolution caused by positive selection after gene duplication in mouse.     

Identifying site-specific substitution rates

A maximum likelihood framework for estimating site-specific substitution rates is presented that does not require any prior assumptions about the rate distribution. We show that, when the branching pattern of the underlying tree is known, the analysis of pairs of positions is sufficient to estimate site-specific rates. In the abscense of a known topology, we introduce an iterative procedure to estimate simultaneously the branching pattern, the branch lengths, and site-specific substitution rates. Simulations show that the evolutionary rate of fast-evolving sites can be reliably inferred and that the accuracy of rate estimates depends mainly on the number of sequences in the data set. Thus, large sets of aligned sequences are necessary for reliable site-specific rate estimates. The method is applied to the complete mitochondrial DNA sequence of 53 humans, providing a complete picture of the site-specific substitution rates in human mitochondrial DNA.     

On the correlation between composition and site-specific evolutionary rate: implications for phylogenetic inference

Model-based phylogenetic reconstruction methods traditionally assume homogeneity of nucleotide frequencies among sequence sites and lineages. Yet, heterogeneity in base composition is a characteristic shared by most biological sequences. Compositional variation in time, reflected in the compositional biases among contemporary sequences, has already been extensively studied, and its detrimental effects on phylogenetic estimates are known. However, fewer studies have focused on the effects of spatial compositional heterogeneity within genes. We show here that different sites in an alignment do not always share a unique compositional pattern, and we provide examples where nucleotide frequency trends are correlated with the site-specific rate of evolution in RNA genes. Spatial compositional heterogeneity is shown to affect the estimation of evolutionary parameters. With standard phylogenetic methods, estimates of equilibrium frequencies are found to be biased towards the composition observed at fast-evolving sites. Conversely, the ancestral composition estimates of some time-heterogeneous but spatially homogeneous methods are found to be biased towards frequencies observed at invariant and slow-evolving sites. The latter finding challenges the result of a previous study arguing against a hyperthermophilic last universal ancestor from the low apparent G + C content of its rRNA sequences. We propose a new model to account for compositional variation across sites. A Gaussian process prior is used to allow for a smooth change in composition with evolutionary rate. The model has been implemented in the phylogenetic inference software PHASE, and Bayesian methods can be used to obtain the model parameters. The results suggest that this model can accurately capture the observed trends in present-day RNA sequences.     

Rates of genome evolution and branching order from whole genome analysis

Accurate estimation of any phylogeny is important as a framework for evolutionary analysis of form and function at all levels of organization from sequence to whole organism. Using alignments of nonrepetitive components of opossum, human, mouse, rat, and dog genomes we evaluated two alternative tree topologies for eutherian evolution. We show with very high confidence that there is a basal split between rodents (as represented by the mouse and rat) and a branch joining primates (as represented by humans) and carnivores (as represented by dogs), consistent with some but not the most widely accepted mammalian phylogenies. The result was robust to substitution model choice with equivalent inference returned from a spectrum of models ranging from a general time reversible model, a model that treated nucleotides as either purines and pyrimidines, and variants of these that incorporated rate heterogeneity among sites. By determining this particular branching order we are able to show that the rate of molecular evolution is almost identical in rodent and carnivore lineages and that sequences evolve approximately 11%-14% faster in these lineages than in the primate lineage. In addition by applying the chicken as outgroup the analyses suggested that the rate of evolution in all eutherian lineages is approximately 30% slower than in the opossum lineage. This pattern of relative rates is inconsistent with the hypothesis that generation time is an important determinant of substitution rates and, by implication, mutation rates. Possible factors causing rate differences between the lineages include differences in DNA repair and replication enzymology, and shifts in nucleotide pools. Our analysis demonstrates the importance of using multiple sequences from across the genome to estimate phylogeny and relative evolutionary rate in order to reduce the influence of distorting local effects evident even in relatively long sequences.     

Epistasis Creates Invariant Sites and Modulates the Rate of Molecular Evolution

Invariant sites are a common feature of amino acid sequence evolution. The presence of invariant sites is frequently attributed to the need to preserve function through site-specific conservation of amino acid residues. Amino acid substitution models without a provision for invariant sites often fit the data significantly worse than those that allow for an excess of invariant sites beyond those predicted by models that only incorporate rate variation among sites (e.g., a Gamma distribution). An alternative is epistasis between sites to preserve residue interactions that can create invariant sites. Through computer-simulated sequence evolution, we evaluated the relative effects of site-specific preferences and site-site couplings in the generation of invariant sites and the modulation of the rate of molecular evolution. In an analysis of ten major families of protein domains with diverse sequence and functional properties, we find that the negative selection imposed by epistasis creates many more invariant sites than site-specific residue preferences alone. Further, epistasis plays an increasingly larger role in creating invariant sites over longer evolutionary periods. Epistasis also dictates rates of domain evolution over time by exerting significant additional purifying selection to preserve site couplings. These patterns illuminate the mechanistic role of epistasis in the processes underlying observed site invariance and evolutionary rates.