Efficiently resolving the basal clades of a phylogenetic tree using Bayesian and parsimony approaches: a case study using mitogenomic data from 100 higher teleost fishes

Many phylogenetic analyses that include numerous terminals but few genes show high resolution and branch support for relatively recently diverged clades, but lack of resolution and/or support for "basal" clades of the tree. The various benefits of increased taxon and character sampling have been widely discussed in the literature, albeit primarily based on simulations rather than empirical data. In this study, we used a well-sampled gene-tree analysis (based on 100 mitochondrial genomes of higher teleost fishes) to test empirically the efficiency of different methods of data sampling and phylogenetic inference to "correctly" resolve the basal clades of a tree (based on congruence with the reference tree constructed using all 100 taxa and 7990 characters). By itself, increased character sampling was an inefficient method by which to decrease the likelihood of "incorrect" resolution (i.e., incongruence with the reference tree) for parsimony analyses. Although increased taxon sampling was a powerful approach to alleviate "incorrect" resolution for parsimony analyses, it had the general effect of increasing the number of, and support for, "incorrectly" resolved clades in the Bayesian analyses. For both the parsimony and Bayesian analyses, increased taxon sampling, by itself, was insufficient to help resolve the basal clades, making this sampling strategy ineffective for that purpose. For this empirical study, the most efficient of the six approaches considered to resolve the basal clades when adding nucleotides to a dataset that consists of a single gene sampled for a small, but representative, number of taxa, is to increase character sampling and analyze the characters using the Bayesian method.     

Bayesian inference of the metazoan phylogeny; a combined molecular and morphological approach

Metazoan phylogeny remains one of evolutionary biology's major unsolved problems. Molecular and morphological data, as well as different analytical approaches, have produced highly conflicting results due to homoplasy resulting from more than 570 million years of evolution. To date, parsimony has been the only feasible combined approach but is highly sensitive to long-branch attraction. Recent development of stochastic models for discrete morphological characters and computationally efficient methods for Bayesian inference has enabled combined molecular and morphological data analysis with rigorous statistical approaches less prone to such inconsistencies. We present the first statistically founded analysis of a metazoan data set based on a combination of morphological and molecular data and compare the results with a traditional parsimony analysis. Interestingly, the Bayesian analyses demonstrate a high degree of congruence between morphological and molecular data, and both data sets contribute to the result of the combined analysis. Additionally, they resolve several irregularities obtained in previous studies and show high credibility values for controversial groups such as the ecdysozoans and lophotrochozoans. Parsimony, on the contrary, shows conflicting results, with morphology being congruent to the Bayesian results and the molecular data set producing peculiarities that are largely reflected in the combined analysis.     

Effects of data incompleteness on the relative performance of parsimony and Bayesian approaches in a supermatrix phylogenetic reconstruction of Mustelidae and Procyonidae (Carnivora)

Missing data are commonly thought to impede a resolved or accurate reconstruction of phylogenetic relationships, and probabilistic analysis techniques are increasingly viewed as less vulnerable to the negative effects of data incompleteness than parsimony analyses. We test both assumptions empirically by conducting parsimony and Bayesian analyses on an approximately 1.5 × 10⁶‐cell (27 965 characters × 52 species) mustelid–procyonid molecular supermatrix with 62.7% missing entries. Contrary to the first assumption, phylogenetic relationships inferred from our analyses are fully (Bayesian) or almost fully (parsimony) resolved topologically with mostly strong support and also largely in accord with prior molecular estimations of mustelid and procyonid phylogeny derived with parsimony, Bayesian, and other probabilistic analysis techniques from smaller but complete or nearly complete data sets. Contrary to the second assumption, we found no compelling evidence in support of a relationship between the inferior performance of parsimony and taxon incompleteness (i.e. the proportion of missing character data for a taxon), although we found evidence for a connection between the inferior performance of parsimony and character incompleteness (i.e. no overlap in character data between some taxa). The relatively good performance of our analyses may be related to the large number of sampled characters, so that most taxa (even highly incomplete ones) are represented by a sufficient number of characters allowing both approaches to resolve their relationships. © The Willi Hennig Society 2009.     

treespace: Statistical exploration of landscapes of phylogenetic trees

The increasing availability of large genomic data sets as well as the advent of Bayesian phylogenetics facilitates the investigation of phylogenetic incongruence, which can result in the impossibility of representing phylogenetic relationships using a single tree. While sometimes considered as a nuisance, phylogenetic incongruence can also reflect meaningful biological processes as well as relevant statistical uncertainty, both of which can yield valuable insights in evolutionary studies. We introduce a new tool for investigating phylogenetic incongruence through the exploration of phylogenetic tree landscapes. Our approach, implemented in the R package treespace , combines tree metrics and multivariate analysis to provide low‐dimensional representations of the topological variability in a set of trees, which can be used for identifying clusters of similar trees and group‐specific consensus phylogenies. treespace also provides a user‐friendly web interface for interactive data analysis and is integrated alongside existing standards for phylogenetics. It fills a gap in the current phylogenetics toolbox in R and will facilitate the investigation of phylogenetic results.     

Phylogenetics of the woodrat genus Neotoma (Rodentia: Muridae): implications for the evolution of phenotypic variation in male external genitalia

Interspecific morphological variation in animal genitalia has long attracted the attention of evolutionary biologists because of the role genital form may play in the generation and/or maintenance of species boundaries. Here we examine the origin and evolution of genital variation in rodents of the muroid genus Neotoma. We test the hypothesis that a relatively rare genital form has evolved only once in Neotoma. We use four mitochondrial and four nuclear markers to evaluate this hypothesis by establishing a phylogenetic framework in which to examine genital evolution. We find intron seven of the beta-fibrinogen gene to be a highly informative nuclear marker for the levels of differentiation that characterize Neotoma with this locus evolving at a rate slower than cytochrome b but faster than 12S. We estimate phylogenetic relationships within Neotoma using both maximum parsimony and maximum likelihood-based Bayesian methods. Our Bayesian and parsimony reconstructions differ in significant ways, but we show that our parsimony analysis may be influenced by long-branch attraction. Furthermore, our estimate of Neotoma phylogeny remains consistent across various data partitioning strategies in the Bayesian analyses. Using ancestral state reconstruction, we find support for the monophyly of taxa that possess the relatively rare genital form. However, we also find support for the independent evolution of the common genital form and discuss possible underlying developmental shifts that may have contributed to our observed patterns of morphological evolution.     

Is congruence between data partitions a reliable predictor of phylogenetic accuracy? Empirically testing an iterative procedure for choosing among phylogenetic methods

The relationship between phylogenetic accuracy and congruence between data partitions collected from the same taxa was explored for mitochondrial DNA sequences from two well-supported vertebrate phylogenies. An iterative procedure was adopted whereby accuracy, phylogenetic signal, and congruence were measured before and after modifying a simple reconstruction model, equally weighted parsimony. These modifications included transversion parsimony, successive weighting, and six-parameter parsimony. For the data partitions examined, there is a generally positive relationship between congruence and phylogenetic accuracy. If congruence increased without decreasing resolution or phylogenetic signal, this increased congruence was a good predictor of accuracy. If congruence increased as a result of poor resolution, the degree of congruence was not a good predictor of accuracy. For all sets of data partitions, six-parameter parsimony methods show a consistently positive relationship between congruence and accuracy. Unlike successive weighting, six-parameter parsimony methods were not strongly influenced by the starting tree.     

Systematics of Ipomoea subgenus Quamoclit (Convolvulaceae) based on ITS sequence data and a Bayesian phylogenetic analysis

A Bayesian phylogenetic analysis of 36 Ipomoea species using sequence data from the internal transcribed spacer region was compared with classification schemes based on traditional methods and a previously published cpDNA restriction fragment length polymorphism (RFLP) study. These molecular studies support a diversity of groups that were circumscribed on the basis of phenetic principles and agree generally with the results from cpDNA RFLP analyses. The congruence between the phylogenetic hypotheses based on new molecular data and the understanding of relationships developed in earlier studies indicate that these classifications may reflect evolutionary history. Two large clades of species, with one including sections Tricolores, Calonyction, and Pharbitis and the other including sections Mina and Leptocallis, were identified. Furthermore, morphologically distinct groups of Ipomoea species received support from the DNA sequence data. Indices of convergence for the Markov chain Monte Carlo (MCMC) in the Bayesian phylogenetic analysis were evaluated. A limited range of posterior probabilities for each node in the trees from a set of five MCMC samples provides a useful index of convergence. Bayesian node support values were generally higher than bootstrap values from a maximum parsimony analysis. This is consistent with the notion that these measures of support estimate different qualities of the data.     

Probabilistic methods outperform parsimony in the phylogenetic analysis of data simulated without a probabilistic model

To understand patterns and processes of the diversification of life, we require an accurate understanding of taxon interrelationships. Recent studies have suggested that analyses of morphological character data using the Bayesian and maximum likelihood Mk model provide phylogenies of higher accuracy compared to parsimony methods. This has proved controversial, particularly studies simulating morphology‐data under Markov models that assume shared branch lengths for characters, as it is claimed this leads to bias favouring the Bayesian or maximum likelihood Mk model over parsimony models which do not explicitly make this assumption. We avoid these potential issues by employing a simulation protocol in which character states are randomly assigned to tips, but datasets are constrained to an empirically realistic distribution of homoplasy as measured by the consistency index. Datasets were analysed with equal weights and implied weights parsimony, and the maximum likelihood and Bayesian Mk model. We find that consistent (low homoplasy) datasets render method choice largely irrelevant, as all methods perform well with high consistency (low homoplasy) datasets, but the largest discrepancies in accuracy occur with low consistency datasets (high homoplasy). In such cases, the Bayesian Mk model is significantly more accurate than alternative models and implied weights parsimony never significantly outperforms the Bayesian Mk model. When poorly supported branches are collapsed, the Bayesian Mk model recovers trees with higher resolution compared to other methods. As it is not possible to assess homoplasy independently of a tree estimate, the Bayesian Mk model emerges as the most reliable approach for categorical morphological analyses.     

Probabilistic methods surpass parsimony when assessing clade support in phylogenetic analyses of discrete morphological data

Fossil taxa are critical to inferences of historical diversity and the origins of modern biodiversity, but realizing their evolutionary significance is contingent on restoring fossil species to their correct position within the tree of life. For most fossil species, morphology is the only source of data for phylogenetic inference; this has traditionally been analysed using parsimony, the predominance of which is currently challenged by the development of probabilistic models that achieve greater phylogenetic accuracy. Here, based on simulated and empirical datasets, we explore the relative efficacy of competing phylogenetic methods in terms of clade support. We characterize clade support using bootstrapping for parsimony and Maximum Likelihood, and intrinsic Bayesian posterior probabilities, collapsing branches that exhibit less than 50% support. Ignoring node support, Bayesian inference is the most accurate method in estimating the tree used to simulate the data. After assessing clade support, Bayesian and Maximum Likelihood exhibit comparable levels of accuracy, and parsimony remains the least accurate method. However, Maximum Likelihood is less precise than Bayesian phylogeny estimation, and Bayesian inference recaptures more correct nodes with higher support compared to all other methods, including Maximum Likelihood. We assess the effects of these findings on empirical phylogenies. Our results indicate probabilistic methods should be favoured over parsimony.     

Molecular systematics of the Eastern Fence Lizard (Sceloporus undulatus): a comparison of Parsimony, Likelihood, and Bayesian approaches

Phylogenetic analysis of large datasets using complex nucleotide substitution models under a maximum likelihood framework can be computationally infeasible, especially when attempting to infer confidence values by way of nonparametric bootstrapping. Recent developments in phylogenetics suggest the computational burden can be reduced by using Bayesian methods of phylogenetic inference. However, few empirical phylogenetic studies exist that explore the efficiency of Bayesian analysis of large datasets. To this end, we conducted an extensive phylogenetic analysis of the wide-ranging and geographically variable Eastern Fence Lizard (Sceloporus undulatus). Maximum parsimony, maximum likelihood, and Bayesian phylogenetic analyses were performed on a combined mitochondrial DNA dataset (12S and 16S rRNA, ND1 protein-coding gene, and associated tRNA; 3,688 bp total) for 56 populations of S. undulatus (78 total terminals including other S. undulatus group species and outgroups). Maximum parsimony analysis resulted in numerous equally parsimonious trees (82,646 from equally weighted parsimony and 335 from weighted parsimony). The majority rule consensus tree derived from the Bayesian analysis was topologically identical to the single best phylogeny inferred from the maximum likelihood analysis, but required approximately 80% less computational time. The mtDNA data provide strong support for the monophyly of the S. undulatus group and the paraphyly of "S. undulatus" with respect to S. belli, S. cautus, and S. woodi. Parallel evolution of ecomorphs within "S. undulatus" has masked the actual number of species within this group. This evidence, along with convincing patterns of phylogeographic differentiation suggests "S. undulatus" represents at least four lineages that should be recognized as evolutionary species.     

An examination of the monophyly of morning glory taxa using Bayesian phylogenetic inference

The objective of this study was to obtain a quantitative assessment of the monophyly of morning glory taxa, specifically the genus Ipomoea and the tribe Argyreieae. Previous systematic studies of morning glories intimated the paraphyly of Ipomoea by suggesting that the genera within the tribe Argyreieae are derived from within Ipomoea; however, no quantitative estimates of statistical support were developed to address these questions. We applied a Bayesian analysis to provide quantitative estimates of monophyly in an investigation of morning glory relationships using DNA sequence data. We also explored various approaches for examining convergence of the Markov chain Monte Carlo (MCMC) simulation of the Bayesian analysis by running 18 separate analyses varying in length. We found convergence of the important components of the phylogenetic model (the tree with the maximum posterior probability, branch lengths, the parameter values from the DNA substitution model, and the posterior probabilities for clade support) for these data after one million generations of the MCMC simulations. In the process, we identified a run where the parameter values obtained were often outside the range of values obtained from the other runs, suggesting an aberrant result. In addition, we compared the Bayesian method of phylogenetic analysis to maximum likelihood and maximum parsimony. The results from the Bayesian analysis and the maximum likelihood analysis were similar for topology, branch lengths, and parameters of the DNA substitution model. Topologies also were similar in the comparison between the Bayesian analysis and maximum parsimony, although the posterior probabilities and the bootstrap proportions exhibited some striking differences. In a Bayesian analysis of three data sets (ITS sequences, waxy sequences, and ITS + waxy sequences) no supoort for the monophyly of the genus Ipomoea, or for the tribe Argyreieae, was observed, with the estimate of the probability of the monophyly of these taxa being less than 3.4 x 10(-7).     

First molecular data on the phylum Loricifera: an investigation into the phylogeny of ecdysozoa with emphasis on the positions of Loricifera and Priapulida

Recent progress in molecular techniques has generated a wealth of information for phylogenetic analysis. Among metazoans all but a single phylum have been incorporated into some sort of molecular analysis. However, the minute and rare species of the phylum Loricifera have remained elusive to molecular systematists. Here we report the first molecular sequence data (nearly complete 18S rRNA) for a member of the phylum Loricifera, Pliciloricus sp. from Korea. The new sequence data were analyzed together with 52 other ecdysozoan sequences, with all other phyla represented by three or more sequences. The data set was analyzed using parsimony as an optimality criterion under direct optimization as well as using a Bayesian approach. The parsimony analysis was also accompanied by a sensitivity analysis. The results of both analyses are largely congruent, finding monophyly of each ecdysozoan phylum, except for Priapulida, in which the coelomate Meiopriapulus is separate from a clade of pseudocoelomate priapulids. The data also suggest a relationship of the pseudocoelomate priapulids to kinorhynchs, and a relationship of nematodes to tardigrades. The Bayesian analysis placed the arthropods as the sister group to a clade that includes tardigrades and nematodes. However, these results were shown to be parameter dependent in the sensitivity analysis. The position of Loricifera was extremely unstable to parameter variation, and support for a relationship of loriciferans to any particular ecdysozoan phylum was not found in the data.     

A molecular analysis of the interrelationships of tetraodontiform fishes (Acanthomorpha: Tetraodontiformes)

Tetraodontiform fishes (e.g., triggerfishes, boxfishes, pufferfishes, and giant ocean sunfishes) have long been recognized as a monophyletic group. Morphological analyses have resulted in conflicting hypotheses of relationships among the tetraodontiform families. Molecular data from the single-copy nuclear gene RAG1 and from two mitochondrial ribosomal genes, 12S and 16S, were used to test these morphology-based hypotheses. Total evidence (RAG1+12S+16S), RAG1-only, and mitochondrial-only analyses were performed using both maximum parsimony and Bayesian criteria. Total evidence and RAG1-only analyses recover a monophyletic Tetraodontiformes. However, the relationships recovered within the order differ, and none completely conform to previous hypotheses. Analysis of mitochondrial data alone fails to recover a monophyletic Tetraodontiformes and therefore does not support any of the morphology-based topologies. The RAG1 data appear to give the best estimate of tetraodontiform phylogeny, resulting in many strongly supported nodes and showing a high degree of congruence between both parsimony and Bayesian analyses. All analyses recover every tetraodontiform family for which more than one representative is included as a strongly supported monophyletic group. Balistidae and Monacanthidae are recovered as sister groups with robust support in every analysis, and all analyses except the Bayesian analyses of the mitochondrial data alone recover a strongly supported sister-group relationship between Tetraodontidae and Diodontidae. Many of the intrafamilial relationships recovered from the molecular data presented here corroborate previous morphological hypotheses.     

Parsimony Analysis as a Specific Kind of Homology Estimation and the Implications for Character Weighting

“Remane-Hennigian systematists” still reject parsimony analysis for phylogenetics, because homology or apomorphy analyses are not included. In contrast, “pattern cladists” regard homology as a deductive concept after applying a parsimony test of character congruence. However, as in molecular phylogeny, selection of “good” characters is always done on the basis of ana priorihomology analysis. The distribution criterion of homology—“homologous characters have identical or hierarchical distribution”—is the basis of parsimony analysis. Because this criterion also might fail in cases of genealogical reticulation or concerted homoplasy, character congruence is not a strict test but another probabilistic criterion of homology. A synthetic approach is proposed for phenotypic analysis with application ofa prioricriteria of homology. The resultinga prioriprobabilities of homology serve as criteria for selection and weighting of characters (very low = not selected/poor/mediocre/good/Dollo characters). After application of a parsimony algorithm the final cladogram decides homology estimations.     

Phylogeny of sipunculan worms: A combined analysis of four gene regions and morphology

The intra-phyletic relationships of sipunculan worms were analyzed based on DNA sequence data from four gene regions and 58 morphological characters. Initially we analyzed the data under direct optimization using parsimony as optimality criterion. An implied alignment resulting from the direct optimization analysis was subsequently utilized to perform a Bayesian analysis with mixed models for the different data partitions. For this we applied a doublet model for the stem regions of the 18S rRNA. Both analyses support monophyly of Sipuncula and most of the same clades within the phylum. The analyses differ with respect to the relationships among the major groups but whereas the deep nodes in the direct optimization analysis generally show low jackknife support, they are supported by 100% posterior probability in the Bayesian analysis. Direct optimization has been useful for handling sequences of unequal length and generating conservative phylogenetic hypotheses whereas the Bayesian analysis under mixed models provided high resolution in the basal nodes of the tree.     

A phylogeny of anisopterous dragonflies (Insecta,Odonata) using mtRNA genes and mixed nucleotide/doublet models

The application of mixed nucleotide/doublet substitution models has recently received attention in RNA‐based phylogenetics. Within a Bayesian approach, it was shown that mixed models outperformed analyses relying on simple nucleotide models. We analysed an mt RNA data set of dragonflies representing all major lineages of Anisoptera plus outgroups, using a mixed model in a Bayesian and parsimony (MP) approach. We used a published mt 16S rRNA secondary consensus structure model and inferred consensus models for the mt 12S rRNA and tRNA valine. Secondary structure information was used to set data partitions for paired and unpaired sites on which doublet or nucleotide models were applied, respectively. Several different doublet models are currently available of which we chose the most appropriate one by a Bayes factor test. The MP reconstructions relied on recoded data for paired sites in order to account for character covariance and an application of the ratchet strategy to find most parsimonious trees. Bayesian and parsimony reconstructions are partly differently resolved, indicating sensitivity of the reconstructions to model specification. Our analyses depict a tree in which the damselfly family Lestidae is sister group to a monophyletic clade Epiophlebia + Anisoptera, contradicting recent morphological and molecular work. In Bayesian analyses, we found a deep split between Libelluloidea and a clade ‘Aeshnoidea’ within Anisoptera largely congruent with Tillyard’s early ideas of anisopteran evolution, which had been based on evidently plesiomorphic character states. However, parsimony analysis did not support a clade ‘Aeshnoidea’, but instead, placed Gomphidae as sister taxon to Libelluloidea. Monophyly of Libelluloidea is only modestly supported, and many inter‐family relationships within Libelluloidea do not receive substantial support in Bayesian and parsimony analyses. We checked whether high Bayesian node support was inflated owing to either: (i) wrong secondary consensus structures; (ii) under‐sampling of the MCMC process, thereby missing other local maxima; or (iii) unrealistic prior assumptions on topologies or branch lengths. We found that different consensus structure models exert strong influence on the reconstruction, which demonstrates the importance of taxon‐specific realistic secondary structure models in RNA phylogenetics.     

The relative performance of Bayesian and parsimony approaches when sampling characters evolving under homogeneous and heterogeneous sets of parameters

We tested whether it is beneficial for the accuracy of phylogenetic inference to sample characters that are evolving under different sets of parameters, using both Bayesian MCMC (Markov chain Monte Carlo) and parsimony approaches. We examined differential rates of evolution among characters, differential character-state frequencies and character-state space, and differential relative branch lengths among characters. We also compared the relative performance of parsimony and Bayesian analyses by progressively incorporating more of these heterogeneous parameters and progressively increasing the severity of this heterogeneity. Bayesian analyses performed better than parsimony when heterogeneous simulation parameters were incorporated into the substitution model. However, parsimony outperformed Bayesian MCMC when heterogeneous simulation parameters were not incorporated into the Bayesian substitution model. The higher the rate of evolution simulated, the better parsimony performed relative to Bayesian analyses. Bayesian and parsimony analyses converged in their performance as the number of simulated heterogeneous model parameters increased. Up to a point, rate heterogeneity among sites was generally advantageous for phylogenetic inference using both approaches. In contrast, branch-length heterogeneity was generally disadvantageous for phylogenetic inference using both parsimony and Bayesian approaches. Parsimony was found to be more conservative than Bayesian analyses, in that it resolved fewer incorrect clades.
© The Willi Hennig Society 2006.     

Reconstructing phylogenies from allozyme data: comparing method performance with congruence

Allozyme data are widely used to infer the phylogenies of populations and closely-related species. Numerous parsimony, distance, and likelihood methods have been proposed for phylogenetic analysis of these data; the relative merits of these methods have been debated vigorously, but their accuracy has not been well explored. In this study, I compare the performance of 13 phylogenetic methods (six parsimony, six distance, and continuous maximum likelihood) by applying a congruence approach to eight allozyme data sets from the literature. Clades are identified that are supported by multiple data sets other than allozymes (e.g. morphology, DNA sequences), and the ability of different methods to recover these 'known' clades is compared. The results suggest that (1) distance and likelihood methods generally outperform parsimony methods, (2) methods that utilize frequency data tend to perform well, and (3) continuous maximum likelihood is among the most accurate methods, and appears to be robust to violations of its assumptions. These results are in agreement with those from recent simulation studies, and help provide a basis for empirical workers to choose among the many methods available for analysing allozyme characters.     

Paleobotany in cladistics and cladistics in paleobotany: enlightenment and uncertainty

Data on fossil taxa can, and should, be incorporated into cladistic analyses. Potential problems with such analyses include large amounts of missing data, and uncertainty about homology of parts that are present. Ambiguity of character data may also occur with extant taxa, but rarely to the extent that it occurs in fossil data. Such ambiguity reduces the strength of the test of character congruence among taxa, in effect relaxing the criterion of parsimony. In order to minimize such effects, composite fossil taxa should be avoided when possible, and polymorphisms reduced by breaking terminals into monomorphic subunits. When results including fossils differ radically from those that exclude fossils, such differences should be approached with caution, keeping in mind the reduced strength of the parsimony analysis when large numbers of cells in a matrix are scored as ambiguous. At this point, there is no simple way to compare the “strength” of parsimony between two data sets that have different numbers of characters and/or taxa in relation to missing data. However, methods under development may provide ways to incorporate the effect of missing values into relative measures of group support such as Bremer support, character removal, and the bootstrap.