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      Transposable element-assisted evolution and adaptation to host plant within the Leptosphaeria maculans- Leptosphaeria biglobosa species complex of fungal pathogens

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          Abstract

          Background

          Many plant-pathogenic fungi have a tendency towards genome size expansion, mostly driven by increasing content of transposable elements (TEs). Through comparative and evolutionary genomics, five members of the Leptosphaeria maculans- Leptosphaeria biglobosa species complex (class Dothideomycetes, order Pleosporales), having different host ranges and pathogenic abilities towards cruciferous plants, were studied to infer the role of TEs on genome shaping, speciation, and on the rise of better adapted pathogens.

          Results

          L. maculans ‘brassicae’, the most damaging species on oilseed rape, is the only member of the species complex to have a TE-invaded genome (32.5%) compared to the other members genomes (<4%). These TEs had an impact at the structural level by creating large TE-rich regions and are suspected to have been instrumental in chromosomal rearrangements possibly leading to speciation. TEs, associated with species-specific genes involved in disease process, also possibly had an incidence on evolution of pathogenicity by promoting translocations of effector genes to highly dynamic regions and thus tuning the regulation of effector gene expression in planta.

          Conclusions

          Invasion of L. maculans ‘brassicae’ genome by TEs followed by bursts of TE activity allowed this species to evolve and to better adapt to its host, making this genome species a peculiarity within its own species complex as well as in the Pleosporales lineage.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1471-2164-15-891) contains supplementary material, which is available to authorized users.

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          Most cited references80

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          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.
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            Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis.

            Ustilago maydis is a ubiquitous pathogen of maize and a well-established model organism for the study of plant-microbe interactions. This basidiomycete fungus does not use aggressive virulence strategies to kill its host. U. maydis belongs to the group of biotrophic parasites (the smuts) that depend on living tissue for proliferation and development. Here we report the genome sequence for a member of this economically important group of biotrophic fungi. The 20.5-million-base U. maydis genome assembly contains 6,902 predicted protein-encoding genes and lacks pathogenicity signatures found in the genomes of aggressive pathogenic fungi, for example a battery of cell-wall-degrading enzymes. However, we detected unexpected genomic features responsible for the pathogenicity of this organism. Specifically, we found 12 clusters of genes encoding small secreted proteins with unknown function. A significant fraction of these genes exists in small gene families. Expression analysis showed that most of the genes contained in these clusters are regulated together and induced in infected tissue. Deletion of individual clusters altered the virulence of U. maydis in five cases, ranging from a complete lack of symptoms to hypervirulence. Despite years of research into the mechanism of pathogenicity in U. maydis, no 'true' virulence factors had been previously identified. Thus, the discovery of the secreted protein gene clusters and the functional demonstration of their decisive role in the infection process illuminate previously unknown mechanisms of pathogenicity operating in biotrophic fungi. Genomic analysis is, similarly, likely to open up new avenues for the discovery of virulence determinants in other pathogens.
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              Genome expansion and gene loss in powdery mildew fungi reveal tradeoffs in extreme parasitism.

              Powdery mildews are phytopathogens whose growth and reproduction are entirely dependent on living plant cells. The molecular basis of this life-style, obligate biotrophy, remains unknown. We present the genome analysis of barley powdery mildew, Blumeria graminis f.sp. hordei (Blumeria), as well as a comparison with the analysis of two powdery mildews pathogenic on dicotyledonous plants. These genomes display massive retrotransposon proliferation, genome-size expansion, and gene losses. The missing genes encode enzymes of primary and secondary metabolism, carbohydrate-active enzymes, and transporters, probably reflecting their redundancy in an exclusively biotrophic life-style. Among the 248 candidate effectors of pathogenesis identified in the Blumeria genome, very few (less than 10) define a core set conserved in all three mildews, suggesting that most effectors represent species-specific adaptations.
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                Author and article information

                Contributors
                jonathan.grandaubert@gmail.com
                rohan.lowe@unimelb.edu.au
                jessica.soyer@versailles.inra.fr
                schoch2@ncbi.nlm.nih.gov
                apvdw2@unimelb.edu.au
                fudal@versailles.inra.fr
                robberts@ncbi.nlm.nih.gov
                nicolas.lapalu@versailles.inra.fr
                Matthew.Links@agr.gc.ca
                benedicte.ollivier@versailles.inra.fr
                juliette.linglin@versailles.inra.fr
                vbarbe@genoscope.cns.fr
                mangenot@genoscope.cns.fr
                cruaud@genoscope.cns.fr
                Hossein.Borhan@agr.gc.ca
                bhowlett@unimelb.edu.au
                mhb@versailles.inra.fr
                rouxel@versailles.inra.fr
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                12 October 2014
                12 October 2014
                2014
                : 15
                : 1
                : 891
                Affiliations
                [ ]INRA-Bioger, UR1290, Avenue Lucien Brétignières, BP 01, 78850 Thiverval-Grignon, France
                [ ]School of Botany, The University of Melbourne, Melbourne, Victoria 3010 Australia
                [ ]NIH/NLM/NCBI, 45 Center Drive, MSC 6510, Bethesda, Maryland 20892-6510 USA
                [ ]INRA-Bioger, URGI Route de St Cyr, 78026 Versailles Cedex, France
                [ ]Agriculture and Agri-Food Canada/Agriculture et Agroalimentaire Canada, Saskatoon Research Centre, 107 Science Place, Saskatoon, SK S7N OX2 Canada
                [ ]Department of Computer, University of Saskatchewan, 110 Science Place, Saskatoon, SK S7N 5C9 Canada
                [ ]GENOSCOPE, Centre National de Séquençage, Institut de Génomique CEA/DSV, 2, rue Gaston Crémieux, CP 5706, 91057 Evry Cedex, France
                Article
                6595
                10.1186/1471-2164-15-891
                4210507
                25306241
                730dcdce-4e9e-498a-a854-2bbf177acaca
                © Grandaubert et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 March 2014
                : 26 September 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Genetics
                comparative genomics,fungal plant pathogen,transposable elements,effector genes,speciation,adaptation to host

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