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      Complete Genome Sequence of Sporisorium scitamineum and Biotrophic Interaction Transcriptome with Sugarcane

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          Abstract

          Sporisorium scitamineum is a biotrophic fungus responsible for the sugarcane smut, a worldwide spread disease. This study provides the complete sequence of individual chromosomes of S. scitamineum from telomere to telomere achieved by a combination of PacBio long reads and Illumina short reads sequence data, as well as a draft sequence of a second fungal strain. Comparative analysis to previous available sequences of another strain detected few polymorphisms among the three genomes. The novel complete sequence described herein allowed us to identify and annotate extended subtelomeric regions, repetitive elements and the mitochondrial DNA sequence. The genome comprises 19,979,571 bases, 6,677 genes encoding proteins, 111 tRNAs and 3 assembled copies of rDNA, out of our estimated number of copies as 130. Chromosomal reorganizations were detected when comparing to sequences of S. reilianum, the closest smut relative, potentially influenced by repeats of transposable elements. Repetitive elements may have also directed the linkage of the two mating-type loci. The fungal transcriptome profiling from in vitro and from interaction with sugarcane at two time points (early infection and whip emergence) revealed that 13.5% of the genes were differentially expressed in planta and particular to each developmental stage. Among them are plant cell wall degrading enzymes, proteases, lipases, chitin modification and lignin degradation enzymes, sugar transporters and transcriptional factors. The fungus also modulates transcription of genes related to surviving against reactive oxygen species and other toxic metabolites produced by the plant. Previously described effectors in smut/plant interactions were detected but some new candidates are proposed. Ten genomic islands harboring some of the candidate genes unique to S. scitamineum were expressed only in planta. RNAseq data was also used to reassure gene predictions.

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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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            Fungal effector proteins.

            It is accepted that most fungal avirulence genes encode virulence factors that are called effectors. Most fungal effectors are secreted, cysteine-rich proteins, and a role in virulence has been shown for a few of them, including Avr2 and Avr4 of Cladosporium fulvum, which inhibit plant cysteine proteases and protect chitin in fungal cell walls against plant chitinases, respectively. In resistant plants, effectors are directly or indirectly recognized by cognate resistance proteins that reside either inside the plant cell or on plasma membranes. Several secreted effectors function inside the host cell, but the uptake mechanism is not yet known. Variation observed among fungal effectors shows two types of selection that appear to relate to whether they interact directly or indirectly with their cognate resistance proteins. Direct interactions seem to favor point mutations in effector genes, leading to amino acid substitutions, whereas indirect interactions seem to favor jettison of effector genes.
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              PredGPI: a GPI-anchor predictor

              Background Several eukaryotic proteins associated to the extracellular leaflet of the plasma membrane carry a Glycosylphosphatidylinositol (GPI) anchor, which is linked to the C-terminal residue after a proteolytic cleavage occurring at the so called ω-site. Computational methods were developed to discriminate proteins that undergo this post-translational modification starting from their aminoacidic sequences. However more accurate methods are needed for a reliable annotation of whole proteomes. Results Here we present PredGPI, a prediction method that, by coupling a Hidden Markov Model (HMM) and a Support Vector Machine (SVM), is able to efficiently predict both the presence of the GPI-anchor and the position of the ω-site. PredGPI is trained on a non-redundant dataset of experimentally characterized GPI-anchored proteins whose annotation was carefully checked in the literature. Conclusion PredGPI outperforms all the other previously described methods and is able to correctly replicate the results of previously published high-throughput experiments. PredGPI reaches a lower rate of false positive predictions with respect to other available methods and it is therefore a costless, rapid and accurate method for screening whole proteomes.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2015
                12 June 2015
                : 10
                : 6
                : e0129318
                Affiliations
                [1 ]College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil
                [2 ]Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2
                [3 ]CSIRO Agriculture, Flagship, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD, 4067, Australia
                [4 ]Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, Australia
                [5 ]Centre for Comparative Genomics, Murdoch University, Perth, Australia
                [6 ]Centro Avançado da Pesquisa Tecnológica do Agronegócio de Cana—IAC/Apta Ribeirão Preto, São Paulo, Brazil
                [7 ]Mendelics Análise Genômica, Rua Cubatão 86, Cj. 1602, 04013-000, São Paulo, SP, Brazil
                Illinois Institute of Technology, UNITED STATES
                Author notes

                Competing Interests: Mendelics Analise Genômica provided support in the form of a salary for author JPK. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: CBMV JPK. Performed the experiments: ACP MCPK FRSN MCQ. Analyzed the data: LMT PDCS JB LPP GC KSA PJB JAF PMM GH AW JPK CBMV. Contributed reagents/materials/analysis tools: LLC SC. Wrote the paper: LMT PDCS JB LPP GC KSA GH JPK CBMV. Provided expertise and editing: JPK MLCV MCQ.

                ‡ These authors also contributed equally to this work.

                Article
                PONE-D-15-07959
                10.1371/journal.pone.0129318
                4466345
                26065709
                145a4485-3e82-46a4-a81d-6fb70affd85e
                Copyright @ 2015

                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
                : 24 February 2015
                : 8 May 2015
                Page count
                Figures: 6, Tables: 2, Pages: 31
                Funding
                The authors acknowledge the support of the Brazilian institution FAPESP: grant numbers 2008/52074-0 and 2010/05591-9 (C.B.M.-V.); fellowships to L.M.T (2014/17034-8); P.D.C.S (2013/25599-2); L.P.P (2013/15014-7); J.B. (2014/21802-0); A.C.P. (2012/09524-0); and NSERC Discovery Grant (G.H.). Mendelics Analise Genômica also provided support in the form of a salary for author JPK. These funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                The complete genome sequence of S. scitamineum SSC39B strain, including the mitochondrial DNA, are deposited at GenBank under the accession numbers CP010913 to CP010939 (assembly accession: ASM101084v1). RNAseq data are available at the NCBI Sequence Read Archive (SRA) under the accession number SRX884131. Sequences of BSES15 and BSES17 strains are available at the European Nucleotide Archive (ENA) under the accession number PRJEB5169.

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