Dataset Information

Virus-viroid interactions: Citrus Tristeza Virus enhances the accumulation of Citrus Dwarfing Viroid in Mexican lime via virus-encoded silencing suppressors.

ABSTRACT: An assay to identify interactions between Citrus Dwarfing Viroid (CDVd) and Citrus Tristeza Virus (CTV) showed that viroid titer was enhanced by the coinfecting CTV in Mexican lime but not in etrog citron. Since CTV encodes three RNA silencing suppressors (RSSs), p23, p20 and p25, an assay using transgenic Mexican limes expressing each RSS revealed that p23 and, to a lesser extent, p25 recapitulated the effect observed with coinfections of CTV and CDVd.

SUBMITTER: Serra P

PROVIDER: S-EPMC3911637 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Publications

Virus-viroid interactions: Citrus Tristeza Virus enhances the accumulation of Citrus Dwarfing Viroid in Mexican lime via virus-encoded silencing suppressors.

Serra Pedro P Bani Hashemian Seyed M SM Fagoaga Carmen C Romero Juan J Ruiz-Ruiz Susana S Gorris Maria T MT Bertolini Edson E Duran-Vila Núria N

Journal of virology 20131113 2

An assay to identify interactions between Citrus Dwarfing Viroid (CDVd) and Citrus Tristeza Virus (CTV) showed that viroid titer was enhanced by the coinfecting CTV in Mexican lime but not in etrog citron. Since CTV encodes three RNA silencing suppressors (RSSs), p23, p20 and p25, an assay using transgenic Mexican limes expressing each RSS revealed that p23 and, to a lesser extent, p25 recapitulated the effect observed with coinfections of CTV and CDVd. ...[more]

PMID: 24227850

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Project description:Viral encoded RNA silencing suppressor proteins interfere with the host RNA silencing machinery, facilitating viral infection by evading host immunity. In plant hosts, the viral proteins have several basic science implications and biotechnology applications. However in silico identification of these proteins is limited by their high sequence diversity. In this study we developed supervised learning based classification models for plant viral RNA silencing suppressor proteins in plant viruses. We developed four classifiers based on supervised learning algorithms: J48, Random Forest, LibSVM and Naïve Bayes algorithms, with enriched model learning by correlation based feature selection. Structural and physicochemical features calculated for experimentally verified primary protein sequences were used to train the classifiers. The training features include amino acid composition; auto correlation coefficients; composition, transition, and distribution of various physicochemical properties; and pseudo amino acid composition. Performance analysis of predictive models based on 10 fold cross-validation and independent data testing revealed that the Random Forest based model was the best and achieved 86.11% overall accuracy and 86.22% balanced accuracy with a remarkably high area under the Receivers Operating Characteristic curve of 0.95 to predict viral RNA silencing suppressor proteins. The prediction models for plant viral RNA silencing suppressors can potentially aid identification of novel viral RNA silencing suppressors, which will provide valuable insights into the mechanism of RNA silencing and could be further explored as potential targets for designing novel antiviral therapeutics. Also, the key subset of identified optimal features may help in determining compositional patterns in the viral proteins which are important determinants for RNA silencing suppressor activities. The best prediction model developed in the study is available as a freely accessible web server pVsupPred at http://bioinfo.icgeb.res.in/pvsup/.

Dataset Information

Virus-viroid interactions: Citrus Tristeza Virus enhances the accumulation of Citrus Dwarfing Viroid in Mexican lime via virus-encoded silencing suppressors.

Publications

Virus-viroid interactions: Citrus Tristeza Virus enhances the accumulation of Citrus Dwarfing Viroid in Mexican lime via virus-encoded silencing suppressors.

Similar Datasets

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