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      Secretome analysis reveals effector candidates associated with broad host range necrotrophy in the fungal plant pathogen Sclerotinia sclerotiorum

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          Abstract

          Background

          The white mold fungus Sclerotinia sclerotiorum is a devastating necrotrophic plant pathogen with a remarkably broad host range. The interaction of necrotrophs with their hosts is more complex than initially thought, and still poorly understood.

          Results

          We combined bioinformatics approaches to determine the repertoire of S. sclerotiorum effector candidates and conducted detailed sequence and expression analyses on selected candidates. We identified 486  S. sclerotiorum secreted protein genes expressed in planta, many of which have no predicted enzymatic activity and may be involved in the interaction between the fungus and its hosts. We focused on those showing (i) protein domains and motifs found in known fungal effectors, (ii) signatures of positive selection, (iii) recent gene duplication, or (iv) being S. sclerotiorum-specific. We identified 78 effector candidates based on these properties. We analyzed the expression pattern of 16 representative effector candidate genes on four host plants and revealed diverse expression patterns.

          Conclusions

          These results reveal diverse predicted functions and expression patterns in the repertoire of S. sclerotiorum effector candidates. They will facilitate the functional analysis of fungal pathogenicity determinants and should prove useful in the search for plant quantitative disease resistance components active against the white mold.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1471-2164-15-336) contains supplementary material, which is available to authorized users.

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          Most cited references59

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          KaKs_Calculator 2.0: A Toolkit Incorporating Gamma-Series Methods and Sliding Window Strategies

          We present an integrated stand-alone software package named KaKs_Calculator 2.0 as an updated version. It incorporates 17 methods for the calculation of nonsynonymous and synonymous substitution rates; among them, we added our modified versions of several widely used methods as the gamma series including γ-NG, γ-LWL, γ-MLWL, γ-LPB, γ-MLPB, γ-YN and γ-MYN, which have been demonstrated to perform better under certain conditions than their original forms and are not implemented in the previous version. The package is readily used for the identification of positively selected sites based on a sliding window across the sequences of interests in 5’ to 3’ direction of protein-coding sequences, and have improved the overall performance on sequence analysis for evolution studies. A toolbox, including C++ and Java source code and executable files on both Windows and Linux platforms together with a user instruction, is downloadable from the website for academic purpose at https://sourceforge.net/projects/kakscalculator2/.
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            Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models.

            Q. Z. Yang (2000)
            Approximate methods for estimating the numbers of synonymous and nonsynonymous substitutions between two DNA sequences involve three steps: counting of synonymous and nonsynonymous sites in the two sequences, counting of synonymous and nonsynonymous differences between the two sequences, and correcting for multiple substitutions at the same site. We examine complexities involved in those steps and propose a new approximate method that takes into account two major features of DNA sequence evolution: transition/transversion rate bias and base/codon frequency bias. We compare the new method with maximum likelihood, as well as several other approximate methods, by examining infinitely long sequences, performing computer simulations, and analyzing a real data set. The results suggest that when there are transition/transversion rate biases and base/codon frequency biases, previously described approximate methods for estimating the nonsynonymous/synonymous rate ratio may involve serious biases, and the bias can be both positive and negative. The new method is, in general, superior to earlier approximate methods and may be useful for analyzing large data sets, although maximum likelihood appears to always be the method of choice.
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              InParanoid 7: new algorithms and tools for eukaryotic orthology analysis

              The InParanoid project gathers proteomes of completely sequenced eukaryotic species plus Escherichia coli and calculates pairwise ortholog relationships among them. The new release 7.0 of the database has grown by an order of magnitude over the previous version and now includes 100 species and their collective 1.3 million proteins organized into 42.7 million pairwise ortholog groups. The InParanoid algorithm itself has been revised and is now both more specific and sensitive. Based on results from our recent benchmarking of low-complexity filters in homology assignment, a two-pass BLAST approach was developed that makes use of high-precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows. We have also updated the InParanoid web site (http://InParanoid.sbc.su.se). Several features have been added, the response times have been improved and the site now sports a new, clearer look. As the number of ortholog databases has grown, it has become difficult to compare among these resources due to a lack of standardized source data and incompatible representations of ortholog relationships. To facilitate data exchange and comparisons among ortholog databases, we have developed and are making available two XML schemas: SeqXML for the input sequences and OrthoXML for the output ortholog clusters.
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                Author and article information

                Contributors
                guyonkoanna@yahoo.fr
                Claudine.balague@toulouse.inra.fr
                Dominique.roby@toulouse.inra.fr
                Sylvain.raffaele@toulouse.inra.fr
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                4 May 2014
                4 May 2014
                2014
                : 15
                : 1
                : 336
                Affiliations
                [ ]INRA, Laboratoire des Interactions Plantes-Microorganismes (LIPM), UMR441, F-31326 Castanet-Tolosan, France
                [ ]CNRS, Laboratoire des Interactions Plantes-Microorganismes (LIPM), UMR2594, F-31326 Castanet-Tolosan, France
                Article
                6074
                10.1186/1471-2164-15-336
                4039746
                24886033
                f569f0cf-c1fc-4c98-9294-b2eae16c0a17
                © Guyon 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
                : 3 February 2014
                : 27 April 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2014

                Genetics
                sclerotinia sclerotiorum. effectors,gene expression,secretome,necrotrophic fungal,pathogen,arabidopsis thaliana

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