A penalty of using anonymous dominant markers (AFLPs, ISSRs, and RAPDs) for phylogenetic inference

AFLPs (and to a lesser extent ISSRs and RAPDs) are increasingly being used for phylogenetic inference among closely related species. Presence/absence characters for each AFLP allele treat all absences as homologous to one another. With three or more alleles, terminals are grouped by their shared absence of alleles in character-based phylogenetic-inference methods in a manner that is not redundant with their shared presence of an alternative allele. We conducted simulations to quantify how severe the negative effect of using presence/absence characters of individual bands is for phylogenetic inference relative to standard multistate characters. We examined alternative tree topologies, relative branch lengths, numbers of characters, rates of evolution, and numbers of alternative alleles, using both parsimony and Nei-and-Li distance analyses. Multistate parsimony generally outperformed presence/absence parsimony, which in turn outperformed Nei-and-Li distance. Increasing the character-state space (i.e., the number of alternative character states available) was found to be advantageous for all three methods of analysis examined, but was most advantageous for multistate parsimony. However, the advantage of multistate parsimony relative to Nei-and-Li distance decreased when applied to more divergent characters. More parsimony-informative variation generally alleviated the problem associated with scoring multistate characters as presence/absence characters. The ensemble consistency index was lower for presence/absence characters relative to multistate characters.     

Relative character-state space, amount of potential phylogenetic information, and heterogeneity of nucleotide and amino acid characters

We examined a broad selection of protein-coding loci from a diverse array of clades and genomes to quantify three factors that determine whether nucleotide or amino acid characters should be preferred for phylogenetic inference. First, we quantified the difference in observed character-state space between nucleotides and amino acids. Second, we quantified the loss of potential phylogenetic signal from silent substitutions when amino acids are used. Third, we used the disparity index to quantify the relative compositional heterogeneity of nucleotides and amino acids and then determined how commonly convergent (rather than unique) shifts in nucleotide and amino acid composition occur in a phylogenetic context. The greater potential phylogenetic signal for nucleotide characters was found to be enormous (on average 440% that of amino acids), whereas the greater observed character-state space for amino acids was less impressive (on average 150.4% that of nucleotides). While matrices of amino acid sequences had less compositional heterogeneity than their corresponding nucleotide sequences, heterogeneity in amino acid composition may be more homoplasious than heterogeneity in nucleotide composition. Given the ability of increased taxon sampling to better utilize the greater potential phylogenetic signal of nucleotide characters and decrease the potential for artifacts caused by heterogeneous nucleotide composition among taxa, we suggest that increased taxon sampling be performed whenever possible instead of restricting analyses to amino acid characters.     

Heterogeneity of nucleotide frequencies among evolutionary lineages and phylogenetic inference

A major assumption of many molecular phylogenetic methods is the homogeneity of nucleotide frequencies among taxa, which refers to the equality of the nucleotide frequency bias among species. Changes in nucleotide frequency among different lineages in a data set are thought to lead to erroneous phylogenetic inference because unrelated clades may appear similar because of evolutionarily unrelated similarities in nucleotide frequencies. We tested the effects of the heterogeneity of nucleotide frequency bias on phylogenetic inference, along with the interaction between this heterogeneity and stratified taxon sampling, by means of computer simulations using evolutionary parameters derived from genomic databases. We found that the phylogenetic trees inferred from data sets simulated under realistic, observed levels of heterogeneity for mammalian genes were reconstructed with accuracy comparable to those simulated with homogeneous nucleotide frequencies; the results hold for Neighbor-Joining, minimum evolution, maximum parsimony, and maximum-likelihood methods. The LogDet distance method, specifically designed to deal with heterogeneous nucleotide frequencies, does not perform better than distance methods that assume substitution pattern homogeneity among sequences. In these specific simulation conditions, we did not find a significant interaction between phylogenetic accuracy and substitution pattern heterogeneity among lineages, even when the taxon sampling is increased.     

Bayesian phylogenetic analysis of combined data

The recent development of Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) techniques has facilitated the exploration of parameter-rich evolutionary models. At the same time, stochastic models have become more realistic (and complex) and have been extended to new types of data, such as morphology. Based on this foundation, we developed a Bayesian MCMC approach to the analysis of combined data sets and explored its utility in inferring relationships among gall wasps based on data from morphology and four genes (nuclear and mitochondrial, ribosomal and protein coding). Examined models range in complexity from those recognizing only a morphological and a molecular partition to those having complex substitution models with independent parameters for each gene. Bayesian MCMC analysis deals efficiently with complex models: convergence occurs faster and more predictably for complex models, mixing is adequate for all parameters even under very complex models, and the parameter update cycle is virtually unaffected by model partitioning across sites. Morphology contributed only 5% of the characters in the data set but nevertheless influenced the combined-data tree, supporting the utility of morphological data in multigene analyses. We used Bayesian criteria (Bayes factors) to show that process heterogeneity across data partitions is a significant model component, although not as important as among-site rate variation. More complex evolutionary models are associated with more topological uncertainty and less conflict between morphology and molecules. Bayes factors sometimes favor simpler models over considerably more parameter-rich models, but the best model overall is also the most complex and Bayes factors do not support exclusion of apparently weak parameters from this model. Thus, Bayes factors appear to be useful for selecting among complex models, but it is still unclear whether their use strikes a reasonable balance between model complexity and error in parameter estimates.     

How can third codon positions outperform first and second codon positions in phylogenetic inference? An empirical example from the seed plants

Greater phylogenetic signal is often found in parsimony-based analyses of third codon positions of protein-coding genes relative to their corresponding first and second codon positions, even for early-derived ("basal") clades. We used the Soltis et al. (2000; Bot. J. Linn. Soc. 133:381-461) data matrix of atpB and rbcL from 567 seed plants to quantify how each of six factors (observed character-state space, frequencies of observed character states, substitution probabilities among nucleotides, rate heterogeneity among sites, overall rate of evolution, and number of parsimony-informative characters) contributed to this phenomenon. Each of these six factors was estimated from the original data matrix for parsimony-informative third codon positions considered separately from first and second codon positions combined. One of the most parsimonious trees found was used as the constraint topology; branch lengths were estimated using likelihood-based distances, and characters were simulated on this tree. Differential frequencies of observed character states were found to be the most limiting of the factors simulated for all three codon positions. Differential frequencies of observed character states and differential substitution probabilities among states were relatively advantageous for first and second codon positions. In contrast, differential numbers of observed character states, differential rate heterogeneity among sites, the greater number of parsimony-informative characters, and the higher overall rate of evolution were relatively advantageous for third codon positions. The amount of possible synapomorphy was predictive of the overall success of resolution.     

A phylogenetic framework for root lesion nematodes of the genus Pratylenchus (Nematoda): Evidence from 18S and D2-D3 expansion segments of 28S ribosomal RNA genes and morphological characters

The root lesion nematodes of the genus Pratylenchus Filipjev, 1936 are migratory endoparasites of plant roots, considered among the most widespread and important nematode parasites in a variety of crops. We obtained gene sequences from the D2 and D3 expansion segments of 28S rRNA partial and 18S rRNA from 31 populations belonging to 11 valid and two unidentified species of root lesion nematodes and five outgroup taxa. These datasets were analyzed using maximum parsimony and Bayesian inference. The alignments were generated using the secondary structure models for these molecules and analyzed with Bayesian inference under the standard models and the complex model, considering helices under the doublet model and loops and bulges under the general time reversible model. The phylogenetic informativeness of morphological characters is tested by reconstruction of their histories on rRNA based trees using parallel parsimony and Bayesian approaches. Phylogenetic and sequence analyses of the 28S D2–D3 dataset with 145 accessions for 28 species and 18S dataset with 68 accessions for 15 species confirmed among large numbers of geographical diverse isolates that most classical morphospecies are monophyletic. Phylogenetic analyses revealed at least six distinct major clades of examined Pratylenchus species and these clades are generally congruent with those defined by characters derived from lip patterns, numbers of lip annules, and spermatheca shape. Morphological results suggest the need for sophisticated character discovery and analysis for morphology based phylogenetics in nematodes.     

Weighted parsimony outperforms other methods of phylogenetic inference under models appropriate for morphology

One of the lasting controversies in phylogenetic inference is the degree to which specific evolutionary models should influence the choice of methods. Model‐based approaches to phylogenetic inference (likelihood, Bayesian) are defended on the premise that without explicit statistical models there is no science, and parsimony is defended on the grounds that it provides the best rationalization of the data, while refraining from assigning specific probabilities to trees or character‐state reconstructions. Authors who favour model‐based approaches often focus on the statistical properties of the methods and models themselves, but this is of only limited use in deciding the best method for phylogenetic inference—such decision also requires considering the conditions of evolution that prevail in nature. Another approach is to compare the performance of parsimony and model‐based methods in simulations, which traditionally have been used to defend the use of models of evolution for DNA sequences. Some recent papers, however, have promoted the use of model‐based approaches to phylogenetic inference for discrete morphological data as well. These papers simulated data under models already known to be unfavourable to parsimony, and modelled morphological evolution as if it evolved just like DNA, with probabilities of change for all characters changing in concert along tree branches. The present paper discusses these issues, showing that under reasonable and less restrictive models of evolution for discrete characters, equally weighted parsimony performs as well or better than model‐based methods, and that parsimony under implied weights clearly outperforms all other methods.     

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).     

Incorporation of gap characters and lineage-specific regions into phylogenetic analyses of gene families from divergent clades: an example from the kinesin superfamily across eukaryotes

The kinesin superfamily across eukaryotes was used to examine how incorporation of gap characters scored from conserved regions shared by all members of a gene family and incorporation of amino acid and gap characters scored from lineage‐specific regions affect gene‐tree inference of the gene family as a whole. We addressed these two questions in the context of two different densities of sequence sampling, four alignment programs, and two methods of tree construction. Taken together, our findings suggest the following. First, gap characters should be incorporated into gene‐tree inference, even for divergent sequences. Second, gene regions that are not conserved among all or most sequences sampled should not be automatically discarded without evaluation of potential phylogenetic signal that may be contained in gap and/or sequence characters. Third, among the four alignment programs evaluated using their default alignment parameters, Clustal may be expected to output alignments that result in the greatest gene‐tree resolution and support. Yet, this high resolution and support should be regarded as optimistic, rather than conservative, estimates. Fourth, this same conclusion regarding resolution and support holds for Bayesian gene‐tree analyses relative to parsimony‐jackknife gene‐tree analyses. We suggest that a more conservative approach, such as aligning the sequences using DIALIGN‐T or MAFFT, analyzing the appropriate characters using parsimony, and assessing branch support using the jackknife, is more appropriate for inferring gene trees of divergent gene families. © The Willi Hennig Society 2007.     

A mitochondrial genome phylogeny of the Neuropterida (lace-wings, alderflies and snakeflies) and their relationship to the other holometabolous insect orders

We present a mitochondrial (mt) genome phylogeny inferring relationships within Neuropterida (lacewings, alderflies and camel flies) and between Neuropterida and other holometabolous insect orders. Whole mt genomes were sequenced for Sialis hamata (Megaloptera: Sialidae), Ditaxis latistyla (Neuroptera: Mantispidae), Mongoloraphidia harmandi (Raphidioptera: Raphidiidae), Macrogyrus oblongus (Coleoptera: Gyrinidae), Rhopaea magnicornis (Coleoptera: Scarabaeidae), and Mordella atrata (Coleoptera: Mordellidae) and compared against representatives of other holometabolous orders in phylogenetic analyses. Additionally, we test the sensitivity of phylogenetic inferences to four analytical approaches: inclusion vs. exclusion of RNA genes, manual vs. algorithmic alignments, arbitrary vs. algorithmic approaches to excluding variable gene regions and how each approach interacts with phylogenetic inference methods (parsimony vs. Bayesian inference). Of these factors, phylogenetic inference method had the most influence on interordinal relationships. Bayesian analyses inferred topologies largely congruent with morphologically‐based hypotheses of neuropterid relationships, a monophyletic Neuropterida whose sister group is Coleoptera. In contrast, parsimony analyses failed to support a monophyletic Neuropterida as Raphidioptera was the sister group of the entire Holometabola excluding Hymenoptera, and Neuroptera + Megaloptera is the sister group of Diptera, a relationship which has not previously been proposed based on either molecular or morphological data sets. These differences between analytical methods are due to the high among site rate heterogeneity found in insect mt genomes which is properly modelled by Bayesian methods but results in artifactual relationships under parsimony. Properly analysed, the mt genomic data set presented here is among the first molecular data to support traditional, morphology‐based interpretations of relationships between the three neuropterid orders and their grouping with Coleoptera.     

Evaluating the robustness of phylogenetic methods to among-site variability in substitution processes

Computer simulations provide a flexible method for assessing the power and robustness of phylogenetic inference methods. Unfortunately, simulated data are often obviously atypical of data encountered in studies of molecular evolution. Unrealistic simulations can lead to conclusions that are irrelevant to real-data analyses or can provide a biased view of which methods perform well. Here, we present a software tool designed to generate data under a complex codon model that allows each residue in the protein sequence to have a different set of equilibrium amino acid frequencies. The software can obtain maximum-likelihood estimates of the parameters of the Halpern and Bruno model from empirical data and a fixed tree; given an arbitrary tree and a fixed set of parameters, the software can then simulate artificial datasets.We present the results of a simulation experiment using randomly generated tree shapes and substitution parameters estimated from 1610 mammalian cytochrome b sequences.We tested tree inference at the amino acid, nucleotide and codon levels and under parsimony, maximum-likelihood, Bayesian and distance criteria (for a total of more than 650 analyses on each dataset). Based on these simulations, nucleotide-level analyses seem to be more accurate than amino acid and codon analyses. The performance of distance-based phylogenetic methods appears to be quite sensitive to the choice of model and the form of rate heterogeneity used. Further studies are needed to assess the generality of these conclusions. For example, fitting parameters of the Halpern Bruno model to sequences from other genes will reveal the extent to which our conclusions were influenced by the choice of cytochrome b. Incorporating codon bias and more sources heterogeneity into the simulator will be crucial to determining whether the current results are caused by a bias in the current simulation study in favour of nucleotide analyses.     

Bias and conflict in phylogenetic inference of myco-heterotrophic plants: a case study in Thismiaceae

Due to morphological reduction and absence of amplifiable plastid genes, the identification of photosynthetic relatives of heterotrophic plants is problematic. Although nuclear and mitochondrial gene sequences may offer a welcome alternative source of phylogenetic markers, the presence of rate heterogeneity in these genes may introduce bias/systematic error in phylogenetic analyses. We examine the phylogenetic position of Thismiaceae based on nuclear 18S rDNA and mitochondrial atpA DNA sequence data, as well as using parsimony, likelihood and Bayesian inference methods. Significant differences in evolutionary rates of these genes between closely related taxa lead to conflicting results: while parsimony analyses of 18S rDNA and combined data strongly support the monophyly of Thismiaceae, Bayesian inference, with and without a relaxed molecular clock, as well as the Swofford–Olsen–Waddell–Hillis (SOWH) test confidently reject this hypothesis. We show that rate heterogeneity in our data leads to long-branch attraction artifacts in parsimony analysis. However, using model-based inference methods the question of whether Thismiaceae are monophyletic remains elusive. On the one hand maximum likelihood nonparametric bootstrapping and parametric hypothesis tests fail to support a paraphyletic Thismiaceae, on the other hand Bayesian inference methods (both without and with a relaxed clock) significantly reject a monophyletic Thismiaceae. These results show that an adequate sampling, the use of rate homogeneous data, and the application of different inference methods are important factors for developing phylogenetic hypotheses of myco-heterotrophic plants. © The Willi Hennig Society 2009.     

Conjugate Gibbs sampling for Bayesian phylogenetic models.

We propose a new Markov Chain Monte Carlo (MCMC) sampling mechanism for Bayesian phylogenetic inference. This method, which we call conjugate Gibbs, relies on analytical conjugacy properties, and is based on an alternation between data augmentation and Gibbs sampling. The data augmentation step consists in sampling a detailed substitution history for each site, and across the whole tree, given the current value of the model parameters. Provided convenient priors are used, the parameters of the model can then be directly updated by a Gibbs sampling procedure, conditional on the current substitution history. Alternating between these two sampling steps yields a MCMC device whose equilibrium distribution is the posterior probability density of interest. We show, on real examples, that this conjugate Gibbs method leads to a significant improvement of the mixing behavior of the MCMC. In all cases, the decorrelation times of the resulting chains are smaller than those obtained by standard Metropolis Hastings procedures by at least one order of magnitude. The method is particularly well suited to heterogeneous models, i.e. assuming site-specific random variables. In particular, the conjugate Gibbs formalism allows one to propose efficient implementations of complex models, for instance assuming site-specific substitution processes, that would not be accessible to standard MCMC methods.     

Identifiability of parameters in MCMC Bayesian inference of phylogeny

Methods for Bayesian inference of phylogeny using DNA sequences based on Markov chain Monte Carlo (MCMC) techniques allow the incorporation of arbitrarily complex models of the DNA substitution process, and other aspects of evolution. This has increased the realism of models, potentially improving the accuracy of the methods, and is largely responsible for their recent popularity. Another consequence of the increased complexity of models in Bayesian phylogenetics is that these models have, in several cases, become overparameterized. In such cases, some parameters of the model are not identifiable; different combinations of nonidentifiable parameters lead to the same likelihood, making it impossible to decide among the potential parameter values based on the data. Overparameterized models can also slow the rate of convergence of MCMC algorithms due to large negative correlations among parameters in the posterior probability distribution. Functions of parameters can sometimes be found, in overparameterized models, that are identifiable, and inferences based on these functions are legitimate. Examples are presented of overparameterized models that have been proposed in the context of several Bayesian methods for inferring the relative ages of nodes in a phylogeny when the substitution rate evolves over time.     

The phylogeny of Iberian Aphodiini species (Coleoptera, Scarabaeoidea, Scarabaeidae, Aphodiinae) based on morphology

Abstract.  The phylogeny of Iberian Aphodiini species was reconstructed based on morphology. Wing venation, mouthparts, male and female genitalia, and external morphology provided ninety-four characters scored for ninety-three Aphodiini species. Phylogenetic analyses were based on maximum parsimony and Bayesian inference criteria. Maximum parsimony consensus trees recovered Acrossus species as a sister group of the remaining Aphodiini, followed by two other branches, one including Neagolius , Plagiogonus , Ahermodontus and Ammoecius species, and the other including Oxyomus , Nimbus , Heptaulacus and Euheptaulacus species. The remaining studied taxa clustered in an unresolved group. Bayesian inference trees recovered Acrossus as the sister group of the remaining Iberian Aphodiini, followed by Colobopterus erraticus and the rest of the Iberian Aphodiini, but this latter branch was unresolved. The general lack of statistical support for the inferred phylogenetic relationships at terminal nodes using both maximum parsimony and Bayesian inference suggests that variation in morphological characters useful for phylogenetic inference in the present study is small, perhaps as a consequence of a radiation event occurring at the origin of the tribe. A probable evolutionary pattern for Aphodiini is proposed which infers six groups, namely Acrossian, Ammoecian, Oxyomian, Aphodian s.str., Colobopteran and Aphodian s.l. clades.     

Properties of Markov Chain Monte Carlo Performance across Many Empirical Alignments

Nearly all current Bayesian phylogenetic applications rely on Markov chain Monte Carlo (MCMC) methods to approximate the posterior distribution for trees and other parameters of the model. These approximations are only reliable if Markov chains adequately converge and sample from the joint posterior distribution. Although several studies of phylogenetic MCMC convergence exist, these have focused on simulated data sets or select empirical examples. Therefore, much that is considered common knowledge about MCMC in empirical systems derives from a relatively small family of analyses under ideal conditions. To address this, we present an overview of commonly applied phylogenetic MCMC diagnostics and an assessment of patterns of these diagnostics across more than 18,000 empirical analyses. Many analyses appeared to perform well and failures in convergence were most likely to be detected using the average standard deviation of split frequencies, a diagnostic that compares topologies among independent chains. Different diagnostics yielded different information about failed convergence, demonstrating that multiple diagnostics must be employed to reliably detect problems. The number of taxa and average branch lengths in analyses have clear impacts on MCMC performance, with more taxa and shorter branches leading to more difficult convergence. We show that the usage of models that include both Γ-distributed among-site rate variation and a proportion of invariable sites is not broadly problematic for MCMC convergence but is also unnecessary. Changes to heating and the usage of model-averaged substitution models can both offer improved convergence in some cases, but neither are a panacea.     

Phylogenetic inference using non‐redundant coding of dependent characters versus alternative approaches for protein‐coding genes

Contemporary molecular phylogenetic analyses often encompass a broad range of taxonomic diversity while maintaining high levels of sampling within each major taxon. To help maximize phylogenetic signal in such studies, one may analyse multiple levels of characters simultaneously. We test the performance of both the original and the modified versions of non‐redundant coding of dependent characters (NRCDC) relative to commonly applied alternative character‐sampling strategies using codon‐based simulations under a range of conditions. Both original and modified NRCDC generally outperformed other character‐sampling strategies that only sampled characters at one level (nucleotides or amino acids) over a broader range of simulation parameters than any of the alternative character‐sampling strategies with respect to both overall success of resolution and averaged overall success of resolution in the parsimony‐based analyses. Based on theoretical considerations and the results of our simulations, we encourage application and further testing of modified NRCDC in parsimony‐based molecular phylogenetic analyses that sample exons of protein‐coding genes. We expect that modified NRCDC will generally increase both accuracy and branch‐support over commonly applied alternative character‐sampling strategies when analysed using the same phylogenetic inference method, particularly in studies that sample both closely and distantly related taxa with clades representing both ancient and recent divergences. © The Willi Hennig Society 2010.     

The enigmatic monotypic crab plover Dromas ardeola is closely related to pratincoles and coursers (Aves, Charadriiformes, Glareolidae)

The phylogenetic placement of the monotypic crab plover Dromasardeola (Aves, Charadriiformes) remains controversial. Phylogenetic analysis of anatomical and behavioral traits using phenetic and cladistic methods of tree inference have resulted in conflicting tree topologies, suggesting a close association of Dromas to members of different suborders and lineages within Charadriiformes. Here, we revisited the issue by applying Bayesian and parsimony methods of tree inference to 2,012 anatomical and 5,183 molecular characters to a set of 22 shorebird genera (including Turnix). Our results suggest that Bayesian analysis of anatomical characters does not resolve the phylogenetic relationship of shorebirds with strong statistical support. In contrast, Bayesian and parsimony tree inference from molecular data provided much stronger support for the phylogenetic relationships within shorebirds, and support a sister relationship of Dromas to Glareolidae (pratincoles and coursers), in agreement with previously published DNA-DNA hybridization studies.     

Out of South America: phylogeny of non‐biting midges in the genus Labrundinia suggests multiple dispersal events to Central and North America

Non‐biting midges of the genus Labrundinia (Chironomidae: Tanypodinae) are minute dipterans with immature stages living in a variety of unpolluted water bodies, from small streams and ponds to lakes and bays. Extensively recorded in ecological studies, the genus comprises 39 species, all except one described from areas outside the Palearctic region. Internal structure among Labrundinia species was postulated by S. S. Roback, who recognized four species groups based on morphological characters of immature stages. We examined phylogenetic relationships among known Labrundinia species using partial DNA sequences of the nuclear protein‐coding gene CAD and morphological characters. Both analyses with Bayesian inference and parsimony methods recovered the monophyly of Labrundinia, strongly supported by five morphological synapomorphies. Internal relationships within the genus partly supported Roback's species groups with the addition of later described species. Biogeographical inferences were obtained by applying Bayesian binary MCMC (BBM) analysis and favoured a scenario where Labrundinia had its initial diversification in the Neotropical region and that current presence in the Nearctic region and southern South America is due to subsequent dispersal.     

Modeling compositional heterogeneity

Compositional heterogeneity among lineages can compromise phylogenetic analyses, because models in common use assume compositionally homogeneous data. Models that can accommodate compositional heterogeneity with few extra parameters are described here, and used in two examples where the true tree is known with confidence. It is shown using likelihood ratio tests that adequate modeling of compositional heterogeneity can be achieved with few composition parameters, that the data may not need to be modelled with separate composition parameters for each branch in the tree. Tree searching and placement of composition vectors on the tree are done in a Bayesian framework using Markov chain Monte Carlo (MCMC) methods. Assessment of fit of the model to the data is made in both maximum likelihood (ML) and Bayesian frameworks. In an ML framework, overall model fit is assessed using the Goldman-Cox test, and the fit of the composition implied by a (possibly heterogeneous) model to the composition of the data is assessed using a novel tree-and model-based composition fit test. In a Bayesian framework, overall model fit and composition fit are assessed using posterior predictive simulation. It is shown that when composition is not accommodated, then the model does not fit, and incorrect trees are found; but when composition is accommodated, the model then fits, and the known correct phylogenies are obtained.