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      Genomic Islands in the Pathogenic Filamentous Fungus Aspergillus fumigatus

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      1 , 2 , 1 , 1 , 1 , 3 , 1 , 1 , 1 , 3 , 1 , 4 , 3 , 5 , 6 , 1 , 1 , 1 , 1 , 1 , 3 , 7 , 8 , 1 , 9 , 1 , 1 , 1 , 10 , 1 , 1 , 1 , 9 , 2 , 8 , 1 , 9 , 3 , 1 , 11 , *
      PLoS Genetics
      Public Library of Science

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          Abstract

          We present the genome sequences of a new clinical isolate of the important human pathogen, Aspergillus fumigatus, A1163, and two closely related but rarely pathogenic species, Neosartorya fischeri NRRL181 and Aspergillus clavatus NRRL1. Comparative genomic analysis of A1163 with the recently sequenced A. fumigatus isolate Af293 has identified core, variable and up to 2% unique genes in each genome. While the core genes are 99.8% identical at the nucleotide level, identity for variable genes can be as low 40%. The most divergent loci appear to contain heterokaryon incompatibility ( het) genes associated with fungal programmed cell death such as developmental regulator rosA. Cross-species comparison has revealed that 8.5%, 13.5% and 12.6%, respectively, of A. fumigatus, N. fischeri and A. clavatus genes are species-specific. These genes are significantly smaller in size than core genes, contain fewer exons and exhibit a subtelomeric bias. Most of them cluster together in 13 chromosomal islands, which are enriched for pseudogenes, transposons and other repetitive elements. At least 20% of A. fumigatus-specific genes appear to be functional and involved in carbohydrate and chitin catabolism, transport, detoxification, secondary metabolism and other functions that may facilitate the adaptation to heterogeneous environments such as soil or a mammalian host. Contrary to what was suggested previously, their origin cannot be attributed to horizontal gene transfer (HGT), but instead is likely to involve duplication, diversification and differential gene loss (DDL). The role of duplication in the origin of lineage-specific genes is further underlined by the discovery of genomic islands that seem to function as designated “gene dumps” and, perhaps, simultaneously, as “gene factories”.

          Author Summary

          Aspergillus is an extremely diverse genus of filamentous ascomycetous fungi (molds) found ubiquitously in soil and decomposing vegetation. Being supreme opportunists, aspergilli have adapted to overcome various chemical, physical, and biological stresses found in heterogeneous environments. While most species in the genus are saprophytes, a surprising number are able to infect wounded plants and animals. Remarkably, the allergic human host also responds abnormally to the aspergilli with lung and sinus disease. The advent of immunosuppressive agents and other medical advances have created a large worldwide pool of human hosts susceptible to some Aspergillus species, including the world's most harmful mold and the causative agent of invasive aspergillosis, Aspergillus fumigatus. In this study, we have used the power of comparative genomics to gain insight into genetic mechanisms that may contribute to the metabolic versatility and pathogenicity of this important human pathogen. Comparison of the genomes of two A. fumigatus clinical isolates and two closely related, but rarely pathogenic species showed that their genomes contain several large isolate- and species-specific chromosomal islands. The metabolic capabilities encoded by these highly labile regions are likely to contribute to their rapid adaptation to heterogeneous environments such as soil or a living host.

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          Most cited references60

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          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.
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            Sequencing and comparison of yeast species to identify genes and regulatory elements.

            Identifying the functional elements encoded in a genome is one of the principal challenges in modern biology. Comparative genomics should offer a powerful, general approach. Here, we present a comparative analysis of the yeast Saccharomyces cerevisiae based on high-quality draft sequences of three related species (S. paradoxus, S. mikatae and S. bayanus). We first aligned the genomes and characterized their evolution, defining the regions and mechanisms of change. We then developed methods for direct identification of genes and regulatory motifs. The gene analysis yielded a major revision to the yeast gene catalogue, affecting approximately 15% of all genes and reducing the total count by about 500 genes. The motif analysis automatically identified 72 genome-wide elements, including most known regulatory motifs and numerous new motifs. We inferred a putative function for most of these motifs, and provided insights into their combinatorial interactions. The results have implications for genome analysis of diverse organisms, including the human.
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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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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plge
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                April 2008
                April 2008
                11 April 2008
                : 4
                : 4
                : e1000046
                Affiliations
                [1 ]The J. Craig Venter Institute, Rockville, Maryland, United States of America
                [2 ]Department of Genetics, Smurfit Institute, University of Dublin, Trinity College, Dublin, Ireland
                [3 ]School of Medicine and Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
                [4 ]Department of Biology, McGill University, Montreal, Quebec, Canada
                [5 ]Agricultural Research Service, United States Department of Agriculture, Department of Plant Sciences, University of Arizona, Tucson, Arizona, United States of America
                [6 ]School of Biology, University of Nottingham, Nottingham, United Kingdom
                [7 ]Institute for Research in Immunology and Cancer, Department of Computer Science and Operations Research, Universite de Montreal, Montreal, Canada
                [8 ]Departamento de Ciencias Farmaceuticas, Faculdade de Ciencias Farmaceuticas de Ribeirao Preto, Universidade de Sao Paulo, Sao Paulo, Brazil
                [9 ]Merck & Co., Inc., Whitehouse Station, New Jersey, United States of America
                [10 ]Department of Molecular Biology and Biotechnology, The University of Sheffield, Sheffield, United Kingdom
                [11 ]Department of Biochemistry and Molecular Biology, The George Washington University School of Medicine, Washington DC, United States of America
                Department of Energy Joint Genome Institute, United States of America
                Author notes

                Conceived and designed the experiments: DD WN. Performed the experiments: MA AA HB PC RK IM. Analyzed the data: NF NK VJ RM PA MA JC JS JB SA PB PC PD AE KG BH JI SL JO TR CR JS GS GT BW PY KW GG JW BJ DD. Contributed reagents/materials/analysis tools: JC JS JB SA AE CF BH JO GS JV OW. Wrote the paper: NF NK DD WN.

                Article
                07-PLGE-RA-0725R3
                10.1371/journal.pgen.1000046
                2289846
                18404212
                168a750a-a986-454c-b535-3464135c302e
                Fedorova et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 31 August 2007
                : 4 March 2008
                Page count
                Pages: 13
                Categories
                Research Article
                Computational Biology/Comparative Sequence Analysis
                Computational Biology/Genomics
                Computational Biology/Macromolecular Sequence Analysis
                Computational Biology/Molecular Genetics
                Computational Biology/Population Genetics
                Genetics and Genomics/Bioinformatics
                Genetics and Genomics/Comparative Genomics
                Genetics and Genomics/Genome Projects
                Genetics and Genomics/Genomics
                Genetics and Genomics/Microbial Evolution and Genomics

                Genetics
                Genetics

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