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alpha-4 is an essential gene and is a dominant antiapoptotic factor in various tissues that is a regulatory subunit for type 2A protein phosphatases. A multiplexed phosphorylation site screen revealed that knockdown of alpha-4 by small interfering RNA (siRNA) increased p38 mitogen-activated protein kinase (MAPK) and c-Jun phosphorylation without changes in JNK or ERK. FLAG-alpha-4 coprecipitated hemagglutinin-MEK3 plus endogenous protein phosphatase 2A (PP2A) and selectively enhanced dephosphorylation of Thr193, but not Ser189, in the activation loop of MEK3. Overexpression of alpha-4 suppressed p38 MAPK activation in response to tumor necrosis factor alpha (TNF-alpha). The alpha-4 dominant-negative domain (DND) (residues 220 to 340) associated with MEK3, but not PP2A, and its overexpression sensitized cells to activation of p38 MAPK by TNF-alpha and interleukin-1beta, but not by ansiomycin or sorbitol. The response was diminished by nocodazole or by siRNA knockdown of the Opitz syndrome protein Mid1 that binds alpha-4 to microtubules. Interference by alpha-4 DND or alpha-4 siRNA increased caspase 3/7 activation in response to TNF-alpha. Growth of transformed cells in soft agar was enhanced by alpha-4 and suppressed by alpha-4 DND. The results show that alpha-4 targets PP2A activity to MEK3 to suppress p38 MAPK activation by cytokines, thereby inhibiting apoptosis and anoikis.
Mol Cell Biol 2007 Jun
PMID:Cytokine activation of p38 mitogen-activated protein kinase and apoptosis is opposed by alpha-4 targeting of protein phosphatase 2A for site-specific dephosphorylation of MEK3. 1743 31

PAML, currently in version 4, is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). The programs may be used to compare and test phylogenetic trees, but their main strengths lie in the rich repertoire of evolutionary models implemented, which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses. Uses of the programs include estimation of synonymous and nonsynonymous rates (d(N) and d(S)) between two protein-coding DNA sequences, inference of positive Darwinian selection through phylogenetic comparison of protein-coding genes, reconstruction of ancestral genes and proteins for molecular restoration studies of extinct life forms, combined analysis of heterogeneous data sets from multiple gene loci, and estimation of species divergence times incorporating uncertainties in fossil calibrations. This note discusses some of the major applications of the package, which includes example data sets to demonstrate their use. The package is written in ANSI C, and runs under Windows, Mac OSX, and UNIX systems. It is available at -- (http://abacus.gene.ucl.ac.uk/software/paml.html).
Mol Biol Evol 2007 Aug
PMID:PAML 4: phylogenetic analysis by maximum likelihood. 1748 13

jModelTest is a new program for the statistical selection of models of nucleotide substitution based on "Phyml" (Guindon and Gascuel 2003. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 52:696-704.). It implements 5 different selection strategies, including "hierarchical and dynamical likelihood ratio tests," the "Akaike information criterion," the "Bayesian information criterion," and a "decision-theoretic performance-based" approach. This program also calculates the relative importance and model-averaged estimates of substitution parameters, including a model-averaged estimate of the phylogeny. jModelTest is written in Java and runs under Mac OSX, Windows, and Unix systems with a Java Runtime Environment installed. The program, including documentation, can be freely downloaded from the software section at http://darwin.uvigo.es.
Mol Biol Evol 2008 Jul
PMID:jModelTest: phylogenetic model averaging. 1839 19

jModelTest is a bioinformatic tool for choosing among different models of nucleotide substitution. The program implements five different model selection strategies, including hierarchical and dynamical likelihood ratio tests (hLRT and dLRT), Akaike and Bayesian information criteria (AIC and BIC), and a performance-based decision theory method (DT). The output includes estimates of model selection uncertainty, parameter importance, and model-averaged parameter estimates, including model-averaged phylogenies. jModelTest is a Java program that runs under Mac OSX, Windows, and Unix systems with a Java Run Environment installed, and it can be freely downloaded from (http://darwin.uvigo.es).
Methods Mol Biol 2009
PMID:Selection of models of DNA evolution with jModelTest. 1937 41

The analysis of genetic marker data is increasingly being conducted in the context of the spatial arrangement of strata (e.g. populations) necessitating a more flexible set of analysis tools. GeneticStudio consists of four interacting programs: (i) Geno a spreadsheet-like interface for the analysis of spatially explicit marker-based genetic variation; (ii) Graph software for the analysis of Population Graph and network topologies, (iii) Manteller, a general purpose for matrix analysis program; and (iv) SNPFinder, a program for identifying single nucleotide polymorphisms. The GeneticStudio suite is available as source code as well as binaries for OSX and Windows and is distributed under the GNU General Public License.
Mol Ecol Resour 2009 Jan
PMID:GeneticStudio: a suite of programs for spatial analysis of genetic-marker data. 2156 74

In phylogenetic analyses of molecular sequence data, partitioning involves estimating independent models of molecular evolution for different sets of sites in a sequence alignment. Choosing an appropriate partitioning scheme is an important step in most analyses because it can affect the accuracy of phylogenetic reconstruction. Despite this, partitioning schemes are often chosen without explicit statistical justification. Here, we describe two new objective methods for the combined selection of best-fit partitioning schemes and nucleotide substitution models. These methods allow millions of partitioning schemes to be compared in realistic time frames and so permit the objective selection of partitioning schemes even for large multilocus DNA data sets. We demonstrate that these methods significantly outperform previous approaches, including both the ad hoc selection of partitioning schemes (e.g., partitioning by gene or codon position) and a recently proposed hierarchical clustering method. We have implemented these methods in an open-source program, PartitionFinder. This program allows users to select partitioning schemes and substitution models using a range of information-theoretic metrics (e.g., the Bayesian information criterion, akaike information criterion [AIC], and corrected AIC). We hope that PartitionFinder will encourage the objective selection of partitioning schemes and thus lead to improvements in phylogenetic analyses. PartitionFinder is written in Python and runs under Mac OSX 10.4 and above. The program, source code, and a detailed manual are freely available from www.robertlanfear.com/partitionfinder.
Mol Biol Evol 2012 Jun
PMID:Partitionfinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses. 2231 68

Open-source software (OSS) encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, OSS comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multiple times for different languages, it is possible to share components by bridging computer languages and Bio* projects, such as BioPerl, Biopython, BioRuby, BioJava, and R/Bioconductor. In this chapter, we compare the two principal approaches for sharing software between different programming languages: either by remote procedure call (RPC) or by sharing a local call stack. RPC provides a language-independent protocol over a network interface; examples are RSOAP and Rserve. The local call stack provides a between-language mapping not over the network interface, but directly in computer memory; examples are R bindings, RPy, and languages sharing the Java Virtual Machine stack. This functionality provides strategies for sharing of software between Bio* projects, which can be exploited more often. Here, we present cross-language examples for sequence translation, and measure throughput of the different options. We compare calling into R through native R, RSOAP, Rserve, and RPy interfaces, with the performance of native BioPerl, Biopython, BioJava, and BioRuby implementations, and with call stack bindings to BioJava and the European Molecular Biology Open Software Suite. In general, call stack approaches outperform native Bio* implementations and these, in turn, outperform RPC-based approaches. To test and compare strategies, we provide a downloadable BioNode image with all examples, tools, and libraries included. The BioNode image can be run on VirtualBox-supported operating systems, including Windows, OSX, and Linux.
Methods Mol Biol 2012
PMID:Sharing programming resources between Bio* projects through remote procedure call and native call stack strategies. 2239 73

Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis of multiple hypotheses and scenarios takes too long on a single desktop computer. In this chapter, we discuss techniques for scaling computations through parallelization of calculations, after giving a quick overview of advanced programming techniques. Unfortunately, parallel programming is difficult and requires special software design. The alternative, especially attractive for legacy software, is to introduce poor man's parallelization by running whole programs in parallel as separate processes, using job schedulers. Such pipelines are often deployed on bioinformatics computer clusters. Recent advances in PC virtualization have made it possible to run a full computer operating system, with all of its installed software, on top of another operating system, inside a "box," or virtual machine (VM). Such a VM can flexibly be deployed on multiple computers, in a local network, e.g., on existing desktop PCs, and even in the Cloud, to create a "virtual" computer cluster. Many bioinformatics applications in evolutionary biology can be run in parallel, running processes in one or more VMs. Here, we show how a ready-made bioinformatics VM image, named BioNode, effectively creates a computing cluster, and pipeline, in a few steps. This allows researchers to scale-up computations from their desktop, using available hardware, anytime it is required. BioNode is based on Debian Linux and can run on networked PCs and in the Cloud. Over 200 bioinformatics and statistical software packages, of interest to evolutionary biology, are included, such as PAML, Muscle, MAFFT, MrBayes, and BLAST. Most of these software packages are maintained through the Debian Med project. In addition, BioNode contains convenient configuration scripts for parallelizing bioinformatics software. Where Debian Med encourages packaging free and open source bioinformatics software through one central project, BioNode encourages creating free and open source VM images, for multiple targets, through one central project. BioNode can be deployed on Windows, OSX, Linux, and in the Cloud. Next to the downloadable BioNode images, we provide tutorials online, which empower bioinformaticians to install and run BioNode in different environments, as well as information for future initiatives, on creating and building such images.
Methods Mol Biol 2012
PMID:Scalable computing for evolutionary genomics. 2239 74

The study of de novo point mutations (new germline mutations arising from the gametes of the parents) remained largely static until the arrival of next-generation sequencing technologies, which made both whole-exome sequencing (WES) and whole-genome sequencing (WGS) feasible in practical terms. Single nucleotide polymorphism genotyping arrays have been used to identify de novo copy-number variants in a number of common neurodevelopmental conditions such as schizophrenia and autism. By contrast, as point mutations and microlesions occurring de novo are refractory to analysis by these microarray-based methods, little was known about either their frequency or impact upon neurodevelopmental disease, until the advent of WES. De novo point mutations have recently been implicated in schizophrenia, autism and mental retardation through the WES of case-parent trios. Taken together, these findings strengthen the hypothesis that the occurrence of de novo mutations could account for the high prevalence of such diseases that are associated with a marked reduction in fecundity. De novo point mutations are also known to be responsible for many sporadic cases of rare dominant mendelian disorders such as Kabuki syndrome, Schinzel-Giedion syndrome and Bohring-Opitz syndrome. These disorders share a common feature in that they are all characterized by intellectual disability. In summary, recent WES studies of neurodevelopmental and neuropsychiatric disease have provided new insights into the role of de novo mutations in these disorders. Our knowledge of de novo mutations is likely to be further accelerated by WGS. However, the collection of case-parent trios will be a prerequisite for such studies. This review aims to discuss recent developments in the study of de novo mutations made possible by technological advances in DNA sequencing.
Mol Psychiatry 2013 Feb
PMID:A new paradigm emerges from the study of de novo mutations in the context of neurodevelopmental disease. 2264 Nov 81

In proteomics, complex mixtures of proteins are separated (usually by chromatography or electrophoresis) and identified by mass spectrometry. We have created 2DE Tandem MS, a computer program designed for use in the biochemistry, proteomics, or bioinformatics classroom. It contains two simulations-2D electrophoresis and tandem mass spectrometry. The two simulations are integrated together and are designed to teach the concept of proteome analysis of prokaryotic and eukaryotic organisms. 2DE-Tandem MS can be used as a freestanding simulation, or in conjunction with a wet lab, to introduce proteomics in the undergraduate classroom. 2DE Tandem MS is a free program available on Sourceforge at https://sourceforge.net/projects/jbf/. It was developed using Java Swing and functions in Mac OSX, Windows, and Linux, ensuring that every student sees a consistent and informative graphical user interface no matter the computer platform they choose. Java must be installed on the host computer to run 2DE Tandem MS. Example classroom exercises are provided in the Supporting Information.
Biochem Mol Biol Educ
PMID:Simulation of two dimensional electrophoresis and tandem mass spectrometry for teaching proteomics. 2316 29


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