Combining data in phylogenetic analysis

Systematists have access to multiple sources of character information in phylogenetic analysis. For example, it is not unusual to have nucleotide sequences from several different genes, or to have molecular and morphological data. How should diverse data be analyzed in phylogenetic analysis? Several methods have been proposed for the treatment of partitioned data: the total evidence, separate analysis, and conditional combination approaches. Here, we review some of the advantages and disadvantages of the different approaches, with special concentration on which methods help us to discern the evolutionary process and provide the most accurate estimates of phylogeny.     

Signal, noise, and reliability in molecular phylogenetic analyses.

DNA sequences and other molecular data compared among organisms may contain phylogenetic signal, or they may be randomized with respect to phylogenetic history. Some method is needed to distinguish phylogenetic signal from random noise to avoid analysis of data that have been randomized with respect to the historical relationships of the taxa being compared. We analyzed 8,000 random data matrices consisting of 10-500 binary or four-state characters and 5-25 taxa to study several options for detecting signal in systematic data bases. Analysis of random data often yields a single most-parsimonious tree, especially if the number of characters examined is large and the number of taxa examined is small (both often true in molecular studies). The most-parsimonious tree inferred from random data may also be considerably shorter than the second-best alternative. The distribution of tree lengths of all tree topologies (or a random sample thereof) provides a sensitive measure of phylogenetic signal: data matrices with phylogenetic signal produce tree-length distributions that are strongly skewed to the left, whereas those composed of random noise are closer to symmetrical. In simulations of phylogeny with varying rates of mutation (up to levels that produce random variation among taxa), the skewness of tree-length distributions is closely related to the success of parsimony in finding the true phylogeny. Tables of critical values of a skewness test statistic, g1, are provided for binary and four-state characters for 10-500 characters and 5-25 taxa. These tables can be used in a rapid and efficient test for significant structure in data matrices for phylogenetic analysis.     

Detecting correlation between characters in a comparative analysis with uncertain phylogeny

Abstract.— The importance of accommodating the phylogenetic history of a group when performing a comparative analysis is now widely recognized. The typical approaches either assume the tree is known without error, or they base inferences on a collection of well-supported trees or on a collection of trees generated under a stochastic model of cladogenesis. However, these approaches do not adequately account for the uncertainty of phylogenetic trees in a comparative analysis, especially when data relevant to the phylogeny of a group are available. Here, we develop a method for performing comparative analyses that is based on an extension of Felsenstein's independent contrasts method. Uncertainties in the phylogeny, branch lengths, and other parameters are accommodated by averaging over all possible trees, weighting each by the probability that the tree is correct. We do this in a Bayesian framework and use Markov chain Monte Carlo to perform the high-dimensional summations and integrations required by the analysis. We illustrate the method using comparative characters sampled from Anolis lizards.     

Testing a covariotide model of DNA substitution

The concomitantly variable codons hypothesis of DNA substitution argues that at any time only a fraction of the codons in a gene are capable of accepting a mutation. However, as mutations are fixed at some positions in a gene, the sites that are potentially variable also change because of changed functional constraints. This hypothesis has been termed the "covarion" hypothesis or when the model is applied to nucleotides, the "covariotide" hypothesis. The covarion-covariotide model has proven to be remarkably difficult to test. Here I examine a covariotide hypothesis for 11 genes using a likelihood ratio test. I show that in nine of the genes examined a covariotide model provides a better explanation of the data than a model that does not allow constraints to change over time.     

Potential applications and pitfalls of Bayesian inference of phylogeny

Only recently has Bayesian inference of phylogeny been proposed. The method is now a practical alternative to the other methods; indeed, the method appears to possess advantages over the other methods in terms of ability to use complex models of evolution, ease of interpretation of the results, and computational efficiency. However, the method should be used cautiously. The results of a Bayesian analysis should be examined with respect to the sensitivity of the results to the priors used and the reliability of the Markov chain Monte Carlo approximation of the probabilities of trees.     

Quantifying the impact of dependent evolution among sites in phylogenetic inference

Nearly all commonly used methods of phylogenetic inference assume that characters in an alignment evolve independently of one another. This assumption is attractive for simplicity and computational tractability but is not biologically reasonable for RNAs and proteins that have secondary and tertiary structures. Here, we simulate RNA and protein-coding DNA sequence data under a general model of dependence in order to assess the robustness of traditional methods of phylogenetic inference to violation of the assumption of independence among sites. We find that the accuracy of independence-assuming methods is reduced by the dependence among sites; for proteins this reduction is relatively mild, but for RNA this reduction may be substantial. We introduce the concept of effective sequence length and its utility for considering information content in phylogenetics.     

Cellular stability of Rho-GTPases glucosylated by Clostridium difficile toxin B

Mono-glucosylation of Rho, Rac, and Cdc42 by Clostridium difficile toxin B (TcdB) induces changes of actin dynamics and apoptosis. When fibroblasts were treated with TcdB, an apparent decrease of the cellular Rac1 level was observed when applying anti-Rac1(Mab 102). This decrease was not based on degradation as inhibition of the proteasome by lactacystin did not stabilise cellular Rac1 levels. The application of anti-Rac1 (Mab 23A8) showed that the cellular Rac1 level slightly increased in TcdB-treated fibroblasts; thus, the apparent loss of cellular Rac1 was not due to degradation but due to impaired recognition of glucosylated Rac1 by anti-Rac1 (Mab 102). In contrast, recognition of RhoA by anti-RhoA (Mab 26C4) and Cdc42 by anti-Cdc42 (Mab 44) was not altered by glucosylation; a transient decrease of cellular RhoA and Cdc42 in TcdB-treated fibroblasts was indeed due to proteasomal degradation, as inhibition of the proteasome by lactacystin stabilised both cellular RhoA and Cdc42 levels. The finding that the apparent decrease of Rac1 reflects Rac1 glucosylation offers a valuable tool to determine Rac1 glucosylation.     

MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d(N)/d(S) rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.