PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.

https://www.zora.uzh.ch/id/eprint/155669/1/ZORA_NL_155669.pdf

New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0

Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets—either with respect to the number of taxa or base pairs—can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBS- and RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources. (Maximum likelihood; phylogenetic inference; rapid bootstrap; RAxML; support values.)

/pdf/a-rapid-bootstrap-algorithm-for-the-raxml-web-servers-53psp6fxvq.pdf

A Rapid Bootstrap Algorithm for the RAxML Web Servers

Tunicates or urochordates (appendicularians, salps and sea squirts), cephalochordates (lancelets) and vertebrates (including lamprey and hagfish) constitute the three extant groups of chordate animals. Traditionally, cephalochordates are considered as the closest living relatives of vertebrates, with tunicates representing the earliest chordate lineage. This view is mainly justified by overall morphological similarities and an apparently increased complexity in cephalochordates and vertebrates relative to tunicates. Despite their critical importance for understanding the origins of vertebrates, phylogenetic studies of chordate relationships have provided equivocal results. Taking advantage of the genome sequencing of the appendicularian Oikopleura dioica, we assembled a phylogenomic data set of 146 nuclear genes (33,800 unambiguously aligned amino acids) from 14 deuterostomes and 24 other slowly evolving species as an outgroup. Here we show that phylogenetic analyses of this data set provide compelling evidence that tunicates, and not cephalochordates, represent the closest living relatives of vertebrates. Chordate monophyly remains uncertain because cephalochordates, albeit with a non-significant statistical support, surprisingly grouped with echinoderms, a hypothesis that needs to be tested with additional data. This new phylogenetic scheme prompts a reappraisal of both morphological and palaeontological data and has important implications for the interpretation of developmental and genomic studies in which tunicates and cephalochordates are used as model animals.

/pdf/tunicates-and-not-cephalochordates-are-the-closest-living-kqlihy7de7.pdf

Tunicates and not cephalochordates are the closest living relatives of vertebrates

In phylogenomics the analysis of concatenated gene alignments, the so-called supermatrix, is commonly accompanied by the assumption of partition models. Under such models each gene, or more generally partition, is allowed to evolve under its own evolutionary model. Although partition models provide a more comprehensive analysis of supermatrices, missing data may hamper the tree search algorithms due to the existence of phylogenetic (partial) terraces. Here, we introduce the phylogenetic terrace aware (PTA) data structure for the efficient analysis under partition models. In the presence of missing data PTA exploits (partial) terraces and induced partition trees to save computation time. We show that an implementation of PTA in IQ-TREE leads to a substantial speedup of up to 4.5 and 8 times compared with the standard IQ-TREE and RAxML implementations, respectively. PTA is generally applicable to all types of partition models and common topological rearrangements thus can be employed by all phylogenomic inference software.

/pdf/terrace-aware-data-structure-for-phylogenomic-inference-from-1uhmj47jh4.pdf

Terrace Aware Data Structure for Phylogenomic Inference from Supermatrices

The spider mite Tetranychus urticae is a cosmopolitan agricultural pest with an extensive host plant range and an extreme record of pesticide resistance. Here we present the completely sequenced and annotated spider mite genome, representing the first complete chelicerate genome. At 90 megabases T. urticae has the smallest sequenced arthropod genome. Compared with other arthropods, the spider mite genome shows unique changes in the hormonal environment and organization of the Hox complex, and also reveals evolutionary innovation of silk production. We find strong signatures of polyphagy and detoxification in gene families associated with feeding on different hosts and in new gene families acquired by lateral gene transfer. Deep transcriptome analysis of mites feeding on different plants shows how this pest responds to a changing host environment. The T. urticae genome thus offers new insights into arthropod evolution and plant-herbivore interactions, and provides unique opportunities for developing novel plant protection strategies.

/pdf/the-genome-of-tetranychus-urticae-reveals-herbivorous-pest-33lyctw5ja.pdf

The genome of Tetranychus urticae reveals herbivorous pest adaptations

Most analysis programs for inferring molecular phylogenies are difficult to use, in particular for researchers with little programming experience

/pdf/treefinder-a-powerful-graphical-analysis-environment-for-11dy77qik9.pdf

Jobb G

Papers

TREEFINDER: a powerful graphical analysis environment for molecular phylogenetics