384
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Diverse Lifestyles and Strategies of Plant Pathogenesis Encoded in the Genomes of Eighteen Dothideomycetes Fungi

      research-article

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The class Dothideomycetes is one of the largest groups of fungi with a high level of ecological diversity including many plant pathogens infecting a broad range of hosts. Here, we compare genome features of 18 members of this class, including 6 necrotrophs, 9 (hemi)biotrophs and 3 saprotrophs, to analyze genome structure, evolution, and the diverse strategies of pathogenesis. The Dothideomycetes most likely evolved from a common ancestor more than 280 million years ago. The 18 genome sequences differ dramatically in size due to variation in repetitive content, but show much less variation in number of (core) genes. Gene order appears to have been rearranged mostly within chromosomal boundaries by multiple inversions, in extant genomes frequently demarcated by adjacent simple repeats. Several Dothideomycetes contain one or more gene-poor, transposable element (TE)-rich putatively dispensable chromosomes of unknown function. The 18 Dothideomycetes offer an extensive catalogue of genes involved in cellulose degradation, proteolysis, secondary metabolism, and cysteine-rich small secreted proteins. Ancestors of the two major orders of plant pathogens in the Dothideomycetes, the Capnodiales and Pleosporales, may have had different modes of pathogenesis, with the former having fewer of these genes than the latter. Many of these genes are enriched in proximity to transposable elements, suggesting faster evolution because of the effects of repeat induced point (RIP) mutations. A syntenic block of genes, including oxidoreductases, is conserved in most Dothideomycetes and upregulated during infection in L. maculans, suggesting a possible function in response to oxidative stress.

          Author Summary

          Dothideomycetes is the largest and most ecologically diverse class of fungi that includes many plant pathogens with high economic impact. Currently 18 genome sequences of Dothideomycetes are available, 14 of which are newly described in this paper and in several companion papers, allowing unprecedented resolution in comparative analyses. These 18 organisms have diverse lifestyles and strategies of plant pathogenesis. Three feed on dead organic matter only, six are necrotrophs (killing the host plant cells), one is a biotroph (forming an association with and thus feeding on the living cells of the host plant cells) and 8 are hemibiotrophs (having an initial biotrophic stage, and killing the host plant at a later stage). These various lifestyles are also reflected in the gene sets present in each group. For example, sets of genes involved in carbohydrate degradation and secondary metabolism are expanded in necrotrophs. Many genes involved in pathogenesis are located near repetitive sequences, which are believed to speed up their evolution. Blocks of genes with conserved gene order were identified. In addition to this we deduce that the mechanism for mesosynteny, a type of genome evolution particular to Dothideomycetes, is by intra-chromosomal inversions.

          Related collections

          Most cited references80

          • Record: found
          • Abstract: found
          • Article: not found

          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
            • Record: found
            • Abstract: found
            • Article: not found

            ProtTest: selection of best-fit models of protein evolution.

            Using an appropriate model of amino acid replacement is very important for the study of protein evolution and phylogenetic inference. We have built a tool for the selection of the best-fit model of evolution, among a set of candidate models, for a given protein sequence alignment. ProtTest is available under the GNU license from http://darwin.uvigo.es
              • Record: found
              • Abstract: found
              • Article: not found

              Ab initio gene finding in Drosophila genomic DNA.

              Ab initio gene identification in the genomic sequence of Drosophila melanogaster was obtained using (human gene predictor) and Fgenesh programs that have organism-specific parameters for human, Drosophila, plants, yeast, and nematode. We did not use information about cDNA/EST in most predictions to model a real situation for finding new genes because information about complete cDNA is often absent or based on very small partial fragments. We investigated the accuracy of gene prediction on different levels and designed several schemes to predict an unambiguous set of genes (annotation CGG1), a set of reliable exons (annotation CGG2), and the most complete set of exons (annotation CGG3). For 49 genes, protein products of which have clear homologs in protein databases, predictions were recomputed by Fgenesh+ program. The first annotation serves as the optimal computational description of new sequence to be presented in a database. Reliable exons from the second annotation serve as good candidates for selecting the PCR primers for experimental work for gene structure verification. Our results shows that we can identify approximately 90% of coding nucleotides with 20% false positives. At the exon level we accurately predicted 65% of exons and 89% including overlapping exons with 49% false positives. Optimizing accuracy of prediction, we designed a gene identification scheme using Fgenesh, which provided sensitivity (Sn) = 98% and specificity (Sp) = 86% at the base level, Sn = 81% (97% including overlapping exons) and Sp = 58% at the exon level and Sn = 72% and Sp = 39% at the gene level (estimating sensitivity on std1 set and specificity on std3 set). In general, these results showed that computational gene prediction can be a reliable tool for annotating new genomic sequences, giving accurate information on 90% of coding sequences with 14% false positives. However, exact gene prediction (especially at the gene level) needs additional improvement using gene prediction algorithms. The program was also tested for predicting genes of human Chromosome 22 (the last variant of Fgenesh can analyze the whole chromosome sequence). This analysis has demonstrated that the 88% of manually annotated exons in Chromosome 22 were among the ab initio predicted exons. The suite of gene identification programs is available through the WWW server of Computational Genomics Group at http://genomic.sanger.ac.uk/gf. html.

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, USA )
                1553-7366
                1553-7374
                December 2012
                December 2012
                6 December 2012
                : 8
                : 12
                : e1003037
                Affiliations
                [1 ]United States Department of Energy (DOE) Joint Genome Institute (JGI), Walnut Creek, California, United States of America
                [2 ]Faculty of Forestry, Forest Sciences Centre, University of British Columbia, Vancouver, British Columbia, Canada
                [3 ]Architecture et Fonction des Macromolécules Biologiques, Aix-Marseille Université, CNRS, Marseille, France
                [4 ]NIH/NLM/NCBI, Bethesda, Maryland, United States of America
                [5 ]Department of Biology, Technion - IIT, Haifa, Israel
                [6 ]Department of Plant Pathology & Plant-Microbe Biology, Cornell University, Ithaca, New York, United States of America
                [7 ]Bioinformatics Knowledge Unit, Technion - IIT, Haifa, Israel
                [8 ]Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon, United States of America
                [9 ]Institute of Molecular BioSciences, Massey University, Palmerston North, New Zealand
                [10 ]Natural Resources Canada, Ste-Foy, Quebec, Canada
                [11 ]Plant Research International, Wageningen, The Netherlands
                [12 ]Virginia Bioinformatics Institute & Department of Biological Sciences, Blacksburg, Virginia, United States of America
                [13 ]Division of Occupational & Environmental Health, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
                [14 ]Laboratory of Phytopathology, Wageningen University, Wageningen, The Netherlands
                [15 ]Department of Plant Pathology, North Dakota State University, Fargo, North Dakota, United States of America
                [16 ]United States Department of Agriculture, Agricultural Research Service, Purdue University, West Lafayette, Indiana, United States of America
                University of Melbourne, Australia
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: RAO REB LC SBG IVG RCH GHJK CL JAS JWS BGT PJGMDW SZ. Performed the experiments: RAO REB BJC BD NF FG BH BAH IK AAS CLS BGT CNH. Analyzed the data: RAO REB BJC BD NF FG BH BAH IK AAS CLS BGT ACC KL EAL. Contributed reagents/materials/analysis tools: KWB SL. Wrote the paper: RAO REB NF SBG IVG BH BAH CLS BGT ACC. Sequenced and assembled genome(s) and/or ESTs: KWB ACC BD CNH KL EAL SL. Annotated genome(s): CNH RAO.

                Article
                PPATHOGENS-D-12-00952
                10.1371/journal.ppat.1003037
                3516569
                23236275
                a9d68abf-cef5-4599-b04b-b4013c2c122f
                Copyright @ 2012

                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 29 February 2012
                : 30 September 2012
                Page count
                Pages: 26
                Funding
                The work done by U.S. Department of Energy Joint Genome Institute is supported by the Office of Science of the U.S. Department of Energy under contract number DE-AC02-05CH11231. This work was supported in part by USDA-ARS CRIS project 3602-22000-015-00D. CLS acknowledges support from the Intramural Research Program of the NIH, National Library of Medicine. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Genomics
                Comparative Genomics
                Functional Genomics
                Genome Evolution
                Genome Sequencing
                Microbiology
                Host-Pathogen Interaction
                Microbial Evolution
                Microbial Pathogens
                Mycology
                Pathogenesis

                Infectious disease & Microbiology
                Infectious disease & Microbiology

                Comments

                Comment on this article

                Related Documents Log