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      A Tale of Genome Compartmentalization: The Evolution of Virulence Clusters in Smut Fungi

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          Abstract

          Smut fungi are plant pathogens mostly parasitizing wild species of grasses as well as domesticated cereal crops. Genome analysis of several smut fungi including Ustilago maydis revealed a singular clustered organization of genes encoding secreted effectors. In U. maydis, many of these clusters have a role in virulence. Reconstructing the evolutionary history of clusters of effector genes is difficult because of their intrinsically fast evolution, which erodes the phylogenetic signal and homology relationships. Here, we describe the use of comparative evolutionary analyses of quality draft assemblies of genomes to study the mechanisms of this evolution. We report the genome sequence of a South African isolate of Sporisorium scitamineum, a smut fungus parasitizing sugar cane with a phylogenetic position intermediate to the two previously sequenced species U. maydis and Sporisorium reilianum. We show that the genome of S. scitamineum contains more and larger gene clusters encoding secreted effectors than any previously described species in this group. We trace back the origin of the clusters and find that their evolution is mainly driven by tandem gene duplication. In addition, transposable elements play a major role in the evolution of the clustered genes. Transposable elements are significantly associated with clusters of genes encoding fast evolving secreted effectors. This suggests that such clusters represent a case of genome compartmentalization that restrains the activity of transposable elements on genes under diversifying selection for which this activity is potentially beneficial, while protecting the rest of the genome from its deleterious effect.

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          The Bioperl toolkit: Perl modules for the life sciences.

          The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.
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            The generic genome browser: a building block for a model organism system database.

            The Generic Model Organism System Database Project (GMOD) seeks to develop reusable software components for model organism system databases. In this paper we describe the Generic Genome Browser (GBrowse), a Web-based application for displaying genomic annotations and other features. For the end user, features of the browser include the ability to scroll and zoom through arbitrary regions of a genome, to enter a region of the genome by searching for a landmark or performing a full text search of all features, and the ability to enable and disable tracks and change their relative order and appearance. The user can upload private annotations to view them in the context of the public ones, and publish those annotations to the community. For the data provider, features of the browser software include reliance on readily available open source components, simple installation, flexible configuration, and easy integration with other components of a model organism system Web site. GBrowse is freely available under an open source license. The software, its documentation, and support are available at http://www.gmod.org.
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              ASTRAL: genome-scale coalescent-based species tree estimation

              Motivation: Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions. Results: We present ASTRAL, a fast method for estimating species trees from multiple genes. ASTRAL is statistically consistent, can run on datasets with thousands of genes and has outstanding accuracy—improving on MP-EST and the population tree from BUCKy, two statistically consistent leading coalescent-based methods. ASTRAL is often more accurate than concatenation using maximum likelihood, except when ILS levels are low or there are too few gene trees. Availability and implementation: ASTRAL is available in open source form at https://github.com/smirarab/ASTRAL/. Datasets studied in this article are available at http://www.cs.utexas.edu/users/phylo/datasets/astral. Contact: warnow@illinois.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Genome Biol Evol
                Genome Biol Evol
                gbe
                gbe
                Genome Biology and Evolution
                Oxford University Press
                1759-6653
                March 2016
                12 February 2016
                12 February 2016
                : 8
                : 3
                : 681-704
                Affiliations
                [1 ]Department of Organismic Interactions, Max Planck Institute for Terrestrial Microbiology, Marburg, Germany
                [2 ]German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany
                Author notes

                3Present address: Department of Evolutionary Genetics Max Planck Institute for Evolutionary Biology, Plön, Germany

                4Present address: DOE Joint Genome Institute, Walnut Creek, California

                5Present address: Microbial Genetics, Institute of Applied Microbiology, Aachen Biology and Biotechnology, RWTH Aachen University, Germany

                Associate editor: Laura Rose

                Data deposition: This project has been deposited at European Nucleotide Archive, ENA under the accession PRJEB6265.

                Article
                evw026
                10.1093/gbe/evw026
                4824034
                26872771
                7f98be6b-b19e-4204-ba9f-7307273b6522
                © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 08 February 2016
                Page count
                Pages: 24
                Categories
                Research Article

                Genetics
                genome architecture,effector proteins,gene duplication,repeat sequences,selection interference,gene cluster

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