Phylogenetic tree interpretation

Constructing phylogenetic trees

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Summary ...

 

Contents

   

Further reading and resources

Software

Ronquist et al. (2012) MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 61:539-42. (pmid: 22357727)

[ PubMed ] [ DOI ] Abstract 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.

Tamura et al. (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28:2731-9. (pmid: 21546353)

[ PubMed ] [ DOI ] Abstract Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.

Gene tree/Species tree reconciliation

Wu et al. (2013) TreeFix: statistically informed gene tree error correction using species trees. Syst Biol 62:110-20. (pmid: 22949484)

[ PubMed ] [ DOI ] Abstract Accurate gene tree reconstruction is a fundamental problem in phylogenetics, with many important applications. However, sequence data alone often lack enough information to confidently support one gene tree topology over many competing alternatives. Here, we present a novel framework for combining sequence data and species tree information, and we describe an implementation of this framework in TreeFix, a new phylogenetic program for improving gene tree reconstructions. Given a gene tree (preferably computed using a maximum-likelihood phylogenetic program), TreeFix finds a "statistically equivalent" gene tree that minimizes a species tree-based cost function. We have applied TreeFix to 2 clades of 12 Drosophila and 16 fungal genomes, as well as to simulated phylogenies and show that it dramatically improves reconstructions compared with current state-of-the-art programs. Given its accuracy, speed, and simplicity, TreeFix should be applicable to a wide range of analyses and have many important implications for future investigations of gene evolution. The source code and a sample data set are available at http://compbio.mit.edu/treefix.

Vilella et al. (2009) EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates. Genome Res 19:327-35. (pmid: 19029536)

[ PubMed ] [ DOI ] Abstract We have developed a comprehensive gene orientated phylogenetic resource, EnsemblCompara GeneTrees, based on a computational pipeline to handle clustering, multiple alignment, and tree generation, including the handling of large gene families. We developed two novel non-sequence-based metrics of gene tree correctness and benchmarked a number of tree methods. The TreeBeST method from TreeFam shows the best performance in our hands. We also compared this phylogenetic approach to clustering approaches for ortholog prediction, showing a large increase in coverage using the phylogenetic approach. All data are made available in a number of formats and will be kept up to date with the Ensembl project.

Degnan & Rosenberg (2009) Gene tree discordance, phylogenetic inference and the multispecies coalescent. Trends Ecol Evol (Amst.) 24:332-40. (pmid: 19307040)

[ PubMed ] [ DOI ] Abstract The field of phylogenetics is entering a new era in which trees of historical relationships between species are increasingly inferred from multilocus and genomic data. A major challenge for incorporating such large amounts of data into inference of species trees is that conflicting genealogical histories often exist in different genes throughout the genome. Recent advances in genealogical modeling suggest that resolving close species relationships is not quite as simple as applying more data to the problem. Here we discuss the complexities of genealogical discordance and review the issues that new methods for multilocus species tree inference will need to address to account successfully for naturally occurring genomic variability in evolutionary histories.

Practice

Ensembl Orthology pipeline