Detection of convergent and parallel evolution at the amino acid sequence level

Adaptive evolution at the molecular level can be studied by detecting convergent and parallel evolution at the amino acid sequence level. For a set of homologous protein sequences, the ancestral amino acids at all interior nodes of the phylogenetic tree of the proteins can be statistically inferred. The amino acid sites that have experienced convergent or parallel changes on independent evolutionary lineages can then be identified by comparing the amino acids at the beginning and end of each lineage. At present, the efficiency of the methods of ancestral sequence inference in identifying convergent and parallel changes is unknown. More seriously, when we identify convergent or parallel changes, it is unclear whether these changes are attributable to random chance. For these reasons, claims of convergent and parallel evolution at the amino acid sequence level have been disputed. We have conducted computer simulations to assess the efficiencies, of the parsimony and Bayesian methods of ancestral sequence inference in identifying convergent and parallel-change sites. Our results showed that the Bayesian method performs better than the parsimony method in identifying parallel changes, and both methods are inefficient in identifying convergent changes. However, the Bayesian method is recommended for estimating the number of convergent-change sites because it gives a conservative estimate. We have developed statistical tests for examining whether the observed numbers of convergent and parallel changes are due to random chance. As an example, we reanalyzed the stomach lysozyme sequences of foregut fermenters and found that parallel evolution is statistically significant, whereas convergent evolution is not well supported.      

Ancestral sequence reconstruction in primate mitochondrial DNA: compositional bias and effect on functional inference

Reconstruction of ancestral DNA and amino acid sequences is an important means of inferring information about past evolutionary events. Such reconstructions suggest changes in molecular function and evolutionary processes over the course of evolution and are used to infer adaptation and convergence. Maximum likelihood (ML) is generally thought to provide relatively accurate reconstructed sequences compared to parsimony, but both methods lead to the inference of multiple directional changes in nucleotide frequencies in primate mitochondrial DNA (mtDNA). To better understand this surprising result, as well as to better understand how parsimony and ML differ, we constructed a series of computationally simple "conditional pathway" methods that differed in the number of substitutions allowed per site along each branch, and we also evaluated the entire Bayesian posterior frequency distribution of reconstructed ancestral states. We analyzed primate mitochondrial cytochrome b (Cyt-b) and cytochrome oxidase subunit I (COI) genes and found that ML reconstructs ancestral frequencies that are often more different from tip sequences than are parsimony reconstructions. In contrast, frequency reconstructions based on the posterior ensemble more closely resemble extant nucleotide frequencies. Simulations indicate that these differences in ancestral sequence inference are probably due to deterministic bias caused by high uncertainty in the optimization-based ancestral reconstruction methods (parsimony, ML, Bayesian maximum a posteriori). In contrast, ancestral nucleotide frequencies based on an average of the Bayesian set of credible ancestral sequences are much less biased. The methods involving simpler conditional pathway calculations have slightly reduced likelihood values compared to full likelihood calculations, but they can provide fairly unbiased nucleotide reconstructions and may be useful in more complex phylogenetic analyses than considered here due to their speed and flexibility. To determine whether biased reconstructions using optimization methods might affect inferences of functional properties, ancestral primate mitochondrial tRNA sequences were inferred and helix-forming propensities for conserved pairs were evaluated in silico. For ambiguously reconstructed nucleotides at sites with high base composition variability, ancestral tRNA sequences from Bayesian analyses were more compatible with canonical base pairing than were those inferred by other methods. Thus, nucleotide bias in reconstructed sequences apparently can lead to serious bias and inaccuracies in functional predictions.     

Assessing the accuracy of ancestral protein reconstruction methods

The phylogenetic inference of ancestral protein sequences is a powerful technique for the study of molecular evolution, but any conclusions drawn from such studies are only as good as the accuracy of the reconstruction method. Every inference method leads to errors in the ancestral protein sequence, resulting in potentially misleading estimates of the ancestral protein's properties. To assess the accuracy of ancestral protein reconstruction methods, we performed computational population evolution simulations featuring near-neutral evolution under purifying selection, speciation, and divergence using an off-lattice protein model where fitness depends on the ability to be stable in a specified target structure. We were thus able to compare the thermodynamic properties of the true ancestral sequences with the properties of “ancestral sequences” inferred by maximum parsimony, maximum likelihood, and Bayesian methods. Surprisingly, we found that methods such as maximum parsimony and maximum likelihood that reconstruct a “best guess” amino acid at each position overestimate thermostability, while a Bayesian method that sometimes chooses less-probable residues from the posterior probability distribution does not. Maximum likelihood and maximum parsimony apparently tend to eliminate variants at a position that are slightly detrimental to structural stability simply because such detrimental variants are less frequent. Other properties of ancestral proteins might be similarly overestimated. This suggests that ancestral reconstruction studies require greater care to come to credible conclusions regarding functional evolution. Inferred functional patterns that mimic reconstruction bias should be reevaluated.     

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 method for constructing maximum parsimony ancestral amino acid sequences on a given network

A solution is presented for the problem of how to find ancestral codons which minimize the number of mutations over a given network of species for which character-states of aligned amino acid sequences among the contemporary species are known. Three theorems which allow this “maximum parsimony” problem to be solved are proved; then the use of these theorems in finding maximum parsimony ancestral codons is illustrated on a network of chicken and mammalian alpha globin amino acid sequences at two alignment positions.     

A method for molecular phylogeny construction by direct use of nucleotide sequence data

Summary A method for molecular phylogeny construction is newly developed. The method, called the stepwise ancestral sequence method, estimates molecular phylogenetic trees and ancestral sequences simultaneously on the basis of parsimony and sequence homology. For simplicity the emphasis is placed more on parsiomony than on sequence homology in the present study, though both are certainly important. Because parsimony alone will sometimes generate plural candidate trees, the method retains not one but five candidates from which one can then single out the final tree taking other criteria into account.The properties and performance of the method are then examined by simulating an evolving gene along a model phylogenetic tree. The estimated trees are found to lie in a narrow range of the parsimony criteria used in the present study. Thus, other criteria such as biological evidence and likelihood are necessary to single out the correct tree among them, with biological evidence taking precedence over any other criterion. The computer simulation also reveals that the method satisfactorily estimates both tree topology and ancestral sequences, at least for the evolutionary model used in the present study.     

Techniques for determining protein sequence evolution applied to primates

Each amino acid in a protein is considered to be an individual, mutable characteristic of the species from which the protein is extracted. For a branching tree representing the evolutionary history of the known sequences in different species, our computer programs use majority logic and parsimony of mutations to determine the most likely ancestral amino acid for each position of the protein at each node of the tree. The number of mutations necessary between the ancestral and present species is summed for each branch and the entire tree. The programs then move branches to make many different configurations, from which we select the one with the minimum number of mutations as the most likely evolutionary history. We used this method to elucidate primate phylogeny from sequences of fibrinopeptides, carbonic anhydrase, and the hemoglobin beta, delta and alpha chains. All available sequences indicate that the early Pongidae had diverged into two lines before the divergence of an ancestor for the human line alone. We have constructed some probable ancestral sequences at major points during primate evolution and have developed tentative trees showing the order of divergences and evolutionary distances among primate groups. Further questions on primate evolution could be answered in the future by the detemination of the appropriate sequences.     

Stochastic versus augmented maximum parsimony method for estimating superimposed mutations in the divergent evolution of protein sequences. Methods tested on cytochrome c amino acid sequences.

Two ways of estimating superimposed fixed mutations in the divergent descent of proteins are examined. One method counts these in terms of a Poisson process operating within selective constraints. The other uses the maximum parsimony method to connect the contemporary sequences through intervening ancestral sequences in an evolutionary tree, and then, from the distribution of fixed mutations in dense regions of this genealogy, estimates how many fixations should be added to sparse regions. An algorithm is described which determines such augmented distances. The two methods yield similar estimates of genetic divergence when tested on a series of cytochrome c amino acid sequences. Within those constraints imposed by Darwinian selection, the dynamic behavior of the evolutionary divergence of proteins is described by the probabilistic pathways of the stochastic model. The parsimony model provides a valid Aufbau-Prinzip for examining which of those pathways occurred along a particular lineage. Concordance of the numerical magnitudes of genetic divergence estimates made by the two methods reveals them as logically consistent complements, not as mutually exclusive antagonists. Both methods indicate that cytochrome c has evolved in a non-uniform manner over geological time and more rapidly than previously estimated.     

The augmentation algorithm and molecular phylogenetic trees

Summary The augmentation procedure of G.W. Moore leads to correct estimates of the total number of nucleotide substitutions separating two genes descendent from a common ancestor provided the data base is sufficiently dense. These estimates are in agreement with the true distance values from simulations of known evolutionary pathways. The estimates, on the average, are unbiased: they neither overaugment nor underaugment seriously. The variance of the population of augmented distance values reflects accurately the variance of the population of true distance values and is thus not abnormally large due to procedural defects in the algorithm.The augmented distances are in agreement with stochastic models tested on real data when the latter take proper account of the restricted mutability of codons resulting from natural selection.When the experimental data base is not dense, the augmented distance values and population variance may underestimate both the true distance values and their variance. This has a logical consequence that there exist significant and numerous errors in the ancestral sequences reconstructed by the parsimony principle from such data bases.The restrictions, resulting from natural selection, on the mutability of different nucleotide sites is shown to bear critically on the accuracy of estimates of the total number of nucleotide replacements made by stochastic models.     

The effect of unequal transversion rates on the accuracy of evolutionary parsimony.

Evolutionary parsimony is an easy-to-use method of phylogenetic inference that is based on nucleic acid sequences and that does not require the assumption that evolutionary processes in the various sites on the molecule are identical. It does, however, require a parameter constraint, known as the "balanced transversion" assumption. We show that the accuracy of the procedure is fairly insensitive to moderate violations of this assumption--and that the procedure thus is applicable under more general conditions than previously thought.     

The early adaptive evolution of calmodulin

Interaction between gene duplication and natural selection in molecular evolution was investigated utilizing a phylogenetic tree constructed by the parsimony procedure from amino acid sequences of 50 calmodulin- family protein members. The 50 sequences, belonging to seven protein lineages related by gene duplication (calmodulin itself, troponin-C, alkali and regulatory light chains of myosin, parvalbumin, intestinal calcium-binding protein, and glial S-100 phenylalanine-rich protein), came from a wide range of eukaryotic taxa and yielded a denser tree (more branch points within each lineage) than in earlier studies. Evidence obtained from the reconstructed pattern of base substitutions and deletions in these ancestral loci suggests that, during the early history of the family, selection acted as a transforming force on expressed genes among the duplicates to encode molecular sites with new or modified functions. In later stages of descent, however, selection was a conserving force that preserved the structures of many coadapted functional sites. Each branch of the family was found to have a unique average tempo of evolutionary change, apparently regulated through functional constraints. Proteins whose functions dictate multiple interaction with several other macromolecules evolved more slowly than those which display fewer protein-protein and protein-ion interactions, e.g., calmodulin and next troponin-C evolved at the slowest average rates, whereas parvalbumin evolved at the fastest. The history of all lineages, however, appears to be characterized by rapid rates of evolutionary change in earlier periods, followed by slower rates in more recent periods. A particularly sharp contrast between such fast and slow rates is found in the evolution of calmodulin, whose rate of change in earlier eukaryotes was manyfold faster than the average rate over the past 1 billion years. In fact, the amino acid replacements in the nascent calmodulin lineage occurred at residue positions that in extant metazoans are largely invariable, lending further support to the Darwinian hypothesis that natural selection is both a creative and a conserving force in molecular evolution.      

SIMMAP: Stochastic character mapping of discrete traits on phylogenies

Background  

Character mapping on phylogenies has played an important, if not critical role, in our understanding of molecular, morphological, and behavioral evolution. Until very recently we have relied on parsimony to infer character changes. Parsimony has a number of serious limitations that are drawbacks to our understanding. Recent statistical methods have been developed that free us from these limitations enabling us to overcome the problems of parsimony by accommodating uncertainty in evolutionary time, ancestral states, and the phylogeny.     

Analyses of physiological evolutionary response

Selection studies are useful if they can provide us with insights into the patterns and processes of evolution in populations under controlled conditions. In this context it is particularly valuable to be able to analyze the limitations of and constraints on evolutionary responses to allow predictions concerning evolutionary change. The concept of a selection pathway is presented as a means of visualizing this predictive process and the constraints that help define the population's response to selection. As pointed out by Gould and Lewontin, history and chance are confounding forces that can mask or distort the adaptive response. Students of the evolutionary responses of organisms are very interested in the effects of these confounding forces, since they play a critical role not only in the laboratory but also in natural selection in the field. In this article, we describe some methods that are a bit different from those used in most studies for examining data from laboratory selection studies. These analytical methods are intended to provide insights into the physiological mechanisms by which evolutionary responses to the environment proceed. Interestingly, selection studies often exhibit disparate responses in replicate populations. We offer methods for analyzing these disparate responses in replicate populations to better understand this very important source of variability in the evolutionary response. We review the techniques of Travisano et al. and show that these approaches can be used to investigate the relative roles of adaptation, history, and chance in the evolutionary responses of populations of Drosophila melanogaster to selection for enhanced desiccation resistance. We anticipate that a wider application of these techniques will provide valuable insights into the organismal, genetic, and molecular nature of the constraints, as well as the factors that serve to enhance or, conversely, to mask the effects of chance. Such studies should help to provide a more detailed understanding of the processes producing evolutionary change in populations.     

Molecular approaches to the study of evolution and phylogeny of the Nemertina

Molecular biological tools currently available to us are revolutionizing the way in which we can address questions in evolutionary biology. The purpose of this article is to provide an overview of molecular techniques and applications available to biologists who are interested in evolutionary studies but who have little acquaintance with molecular biology. In evolutionary biology, techniques designed to determine degree of nucleic acid similarity are in common use and will be dealt with first. Another approach, namely gene expression studies, has strong implications for evolutionary biology but generally requires substantial familiarity with molecular biological tools. Expression studies provide powerful tools for discerning processes of speciation, as in the selection of genetic variants, as well as discerning lineages, e.g., expression of specific homeobox genes during segment formation. For investigations where either nucleic acid identity or gene expression are the ultimate goal, detailed information, protocols and appropriate controls are beyond the scope of this work but, where possible, recent review articles are cited.     

A New Method of Inference of Ancestral Nucleotide and Amino Acid Sequences

A statistical method was developed for reconstructing the nucleotide or amino acid sequences of extinct ancestors, given the phylogeny and sequences of the extant species. A model of nucleotide or amino acid substitution was employed to analyze data of the present-day sequences, and maximum likelihood estimates of parameters such as branch lengths were used to compare the posterior probabilities of assignments of character states (nucleotides or amino acids) to interior nodes of the tree; the assignment having the highest probability was the best reconstruction at the site. The lysozyme c sequences of six mammals were analyzed by using the likelihood and parsimony methods. The new likelihood-based method was found to be superior to the parsimony method. The probability that the amino acids for all interior nodes at a site reconstructed by the new method are correct was calculated to be 0.91, 0.86, and 0.73 for all, variable, and parsimony-informative sites, respectively, whereas the corresponding probabilities for the parsimony method were 0.84, 0.76, and 0.51, respectively. The probability that an amino acid in an ancestral sequence is correctly reconstructed by the likelihood analysis ranged from 91.3 to 98.7% for the four ancestral sequences.     

Molecular systematics: A synthesis of the common methods and the state of knowledge

The comparative and evolutionary analysis of molecular data has allowed researchers to tackle biological questions that have long remained unresolved. The evolution of DNA and amino acid sequences can now be modeled accurately enough that the information conveyed can be used to reconstruct the past. The methods to infer phylogeny (the pattern of historical relationships among lineages of organisms and/or sequences) range from the simplest, based on parsimony, to more sophisticated and highly parametric ones based on likelihood and Bayesian approaches. In general, molecular systematics provides a powerful statistical framework for hypothesis testing and the estimation of evolutionary processes, including the estimation of divergence times among taxa. The field of molecular systematics has experienced a revolution in recent years, and, although there are still methodological problems and pitfalls, it has become an essential tool for the study of evolutionary patterns and processes at different levels of biological organization. This review aims to present a brief synthesis of the approaches and methodologies that are most widely used in the field of molecular systematics today, as well as indications of future trends and state-of-the-art approaches.     

Reconstruction of ancestral protein sequences and its applications

Background  

Modern-day proteins were selected during long evolutionary history as descendants of ancient life forms. In silico reconstruction of such ancestral protein sequences facilitates our understanding of evolutionary processes, protein classification and biological function. Additionally, reconstructed ancestral protein sequences could serve to fill in sequence space thus aiding remote homology inference.     

Evolution of type II DNA methyltransferases. A gene duplication model

On the basis of consensus sequences, which had previously been defined for two groups of closely related cytosine-specific and adenine-specific DNA methyltransferases, homologies can be detected that indicate a common origin for these proteins. Intramolecular comparisons of several of these enzymes reveal homology relationships, which suggests that gene duplication is a phylogenetic principle in the evolution of the Mtases. One or two duplications of an ancestral gene encoding a 12,000 to 16,000 Mr protein, followed by divergent evolution, may have led to very different protein structures and could explain the differences in amino acid sequences, molecular weights and biochemical properties. Intermolecular and intramolecular homologies were also recognized in type II restriction endonucleases, suggesting a very similar evolutionary pathway.     

On investigating the statistical properties of the populous path algorithm by computer simulation

Summary Goodman et al.'s (1974) populous path algorithm for estimating hidden mutational change in protein evolution is designed to be used as an adjunct to the maximum parsimony method. When the algorithm is so used, the augmented maximum parsimony distances, far from being overestimates, are underestimates of the actual number of nucleotide substitutions which occur in Tateno and Nei's (1978) computer simulation by the Poisson process model, even when the simulation is carried out at two and a half times the sequence density. Although underestimates, our evidence shows that they are nevertheless more accurate than estimates obtained by a Poisson correction. In the maximum parsimony reconstruction, there is a bias towards overrepresenting the number of shared nucleotide identities between adjacent ancestral and descendant nodal sequences with the bias being stronger in those portions of the evolutionary tree sparser in sequence data. Because of this particular property of maximum parsimony reconstructed sequences, the conclusions of Tateno and Nei concerning the statistical properties of the populous path algorithm are invalid. We conclude that estimates of protein evolutionary rates by the maximum parsimony - populous path approach will become more accurate rather than less as larger numbers of closely related species are included in the analysis.