Resolving Discrepancy between Nucleotides and Amino Acids in Deep-Level Arthropod Phylogenomics: Differentiating Serine Codons in 21-Amino-Acid Models

BACKGROUND: In a previous study of higher-level arthropod phylogeny, analyses of nucleotide sequences from 62 protein-coding nuclear genes for 80 panarthopod species yielded significantly higher bootstrap support for selected nodes than did amino acids. This study investigates the cause of that discrepancy. METHODOLOGY/PRINCIPAL FINIDINGS: The hypothesis is tested that failure to distinguish the serine residues encoded by two disjunct clusters of codons (TCN, AGY) in amino acid analyses leads to this discrepancy. In one test, the two clusters of serine codons (Ser1, Ser2) are conceptually translated as separate amino acids. Analysis of the resulting 21-amino-acid data matrix shows striking increases in bootstrap support, in some cases matching that in nucleotide analyses. In a second approach, nucleotide and 20-amino-acid data sets are artificially altered through targeted deletions, modifications, and replacements, revealing the pivotal contributions of distinct Ser1 and Ser2 codons. We confirm that previous methods of coding nonsynonymous nucleotide change are robust and computationally efficient by introducing two new degeneracy coding methods. We demonstrate for degeneracy coding that neither compositional heterogeneity at the level of nucleotides nor codon usage bias between Ser1 and Ser2 clusters of codons (or their separately coded amino acids) is a major source of non-phylogenetic signal. CONCLUSIONS: The incongruity in support between amino-acid and nucleotide analyses of the forementioned arthropod data set is resolved by showing that “standard” 20-amino-acid analyses yield lower node support specifically when serine provides crucial signal. Separate coding of Ser1 and Ser2 residues yields support commensurate with that found by degenerated nucleotides, without introducing phylogenetic artifacts. While exclusion of all serine data leads to reduced support for serine-sensitive nodes, these nodes are still recovered in the ML topology, indicating that the enhanced signal from Ser1 and Ser2 is not qualitatively different from that of the other amino acids.This study was supported by grants from the National Science Foundation, U.S.A. (grant numbers 0531626, 1042845 and 0120635). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Model Parameterization, Prior Distributions, and the General Time-Reversible Model in Bayesian Phylogenetics

This is an electronic version of an article published in Systematic Biology [Zwickl, Derrick J. and Mark T. Holder. Model parameterization, prior distributions and the general time-reversible model in Bayesian phylogenetics. Systematic Biology, 53:877{888, 2004.] Systematic Biology is available online at informaworld http://dx.doi.org/10.1080/10635150490522584.Bayesian phylogenetic methods require the selection of prior probability distributions for all parameters of the model of evolution. These distributions allow one to incorporate prior information into a Bayesian analysis, but even in the absence of meaningful prior information, a prior distribution must be chosen. In such situations, researchers typically seek to choose a prior that will have little effect on the posterior estimates produced by an analysis, allowing the data to dominate. Sometimes a prior that is uniform (assigning equal prior probability density to all points within some range) is chosen for this purpose. In reality, the appropriate prior depends on the parameterization chosen for the model of evolution, a choice that is largely arbitrary. There is an extensive Bayesian literature on appropriate prior choice, and it has long been appreciated that there are parameterizations for which uniform priors can have a strong influence on posterior estimates. We here discuss the relationship between model parameterization and prior specification, using the general time-reversible model of nucleotide evolution as an example. We present Bayesian analyses of 10 simulated data sets obtained using a variety of prior distributions and parameterizations of the general time-reversible model. Uniform priors can produce biased parameter estimates under realistic conditions, and a variety of alternative priors avoid this bias

BEAGLE: An Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software

BEAGLE: An Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.This work was supported by the National Science Foundation [grant numbers DBI-0755048, DEB-0732920, DEB-1036448, DMS-0931642, EF-0331495, EF-0905606, EF-0949453]; the National Institutes of Health [grant numbers R01-HG006139, R01-GM037841, R01-GM078985, R01-GM086887, R01-NS063897]; the Biotechnology and Biological Sciences Research Council [grant number BB/H011285/1]; the Wellcome Trust [grant number WT092807MA]; and Google Summer of Code

The 2006 NESCent Phyloinformatics Hackathon: A Field Report

In December, 2006, a group of 26 software developers from some of the most widely used life science programming toolkits and phylogenetic software projects converged on Durham, North Carolina, for a Phyloinformatics Hackathon, an intense five-day collaborative software coding event sponsored by the National Evolutionary Synthesis Center (NESCent). The goal was to help researchers to integrate multiple phylogenetic software tools into automated workflows. Participants addressed deficiencies in interoperability between programs by implementing “glue code” and improving support for phylogenetic data exchange standards (particularly NEXUS) across the toolkits. The work was guided by use-cases compiled in advance by both developers and users, and the code was documented as it was developed. The resulting software is freely available for both users and developers through incorporation into the distributions of several widely-used open-source toolkits. We explain the motivation for the hackathon, how it was organized, and discuss some of the outcomes and lessons learned. We conclude that hackathons are an effective mode of solving problems in software interoperability and usability, and are underutilized in scientific software development

The 2006 NESCent Phyloinformatics Hackathon: A Field Report

In December, 2006, a group of 26 software developers from some of the most widely used life science programming toolkits and phylogenetic software projects converged on Durham, North Carolina, for a Phyloinformatics Hackathon, an intense five-day collaborative software coding event sponsored by the National Evolutionary Synthesis Center (NESCent). The goal was to help researchers to integrate multiple phylogenetic software tools into automated workflows. Participants addressed deficiencies in interoperability between programs by implementing “glue code” and improving support for phylogenetic data exchange standards (particularly NEXUS) across the toolkits. The work was guided by use-cases compiled in advance by both developers and users, and the code was documented as it was developed. The resulting software is freely available for both users and developers through incorporation into the distributions of several widely-used open-source toolkits. We explain the motivation for the hackathon, how it was organized, and discuss some of the outcomes and lessons learned. We conclude that hackathons are an effective mode of solving problems in software interoperability and usability, and are underutilized in scientific software development

Ecological Guild Evolution and the Discovery of the World's Smallest Vertebrate

Living vertebrates vary drastically in body size, yet few taxa reach the extremely minute size of some frogs and teleost fish. Here we describe two new species of diminutive terrestrial frogs from the megadiverse hotspot island of New Guinea, one of which represents the smallest known vertebrate species, attaining an average body size of only 7.7 mm. Both new species are members of the recently described genus Paedophryne, the four species of which are all among the ten smallest known frog species, making Paedophryne the most diminutive genus of anurans. This discovery highlights intriguing ecological similarities among the numerous independent origins of diminutive anurans, suggesting that minute frogs are not mere oddities, but represent a previously unrecognized ecological guild