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Virus detection by high-throughput sequencing of small RNAs: large scale performance testing of sequence analysis strategies

hal.structure.identifierUniversité de Liège
dc.contributor.authorMASSART, Sébastien
hal.structure.identifierNational Research Council of Italy | Consiglio Nazionale delle Ricerche [CNR]
dc.contributor.authorCHIUMENTI, Michela
hal.structure.identifierPlant Sciences Unit
dc.contributor.authorDE JONGHE, Kris
hal.structure.identifierFera Science Limited
dc.contributor.authorGLOVER, Rachel
hal.structure.identifierPlant Sciences Unit
dc.contributor.authorHAEGEMAN, Annelies
hal.structure.identifierBiology Centre of the Czech Academy of Sciences [BIOLOGY CENTRE CAS]
dc.contributor.authorKOLONIUK, Igor
hal.structure.identifierCrop research institute
dc.contributor.authorKOMÍNEK, Petr
hal.structure.identifierInternational Potato Center [Lima] [CIP]
dc.contributor.authorKREUZE, Jan
hal.structure.identifierDepartment of Biotechnology and Systems Biology
dc.contributor.authorKUTNJAK, Denis
hal.structure.identifierAristotle University of Thessaloniki
dc.contributor.authorLOTOS, Leonidas
hal.structure.identifierUniversité de Liège
dc.contributor.authorMACLOT, François
hal.structure.identifierAristotle University of Thessaloniki
dc.contributor.authorMALIOGKA, Varvara
hal.structure.identifierAgricultural Research Council [ARC]
dc.contributor.authorMAREE, Hans J.
hal.structure.identifierLife Sciences Department
dc.contributor.authorOLIVIER, Thibaut
hal.structure.identifierInstituto Valenciano de Investigaciones Agrarias - Institut Valencià d'Investigacions Agraries - Valencian Institute for agricultural Research [IVIA]
dc.contributor.authorOLMOS, Antonio
hal.structure.identifierBiologie et Génétique des Interactions Plante-Parasite [UMR BGPI]
hal.structure.identifierDepartment of Environmental Sciences
dc.contributor.authorPOOGGIN, Mikhail M.
hal.structure.identifierAgroscope
dc.contributor.authorREYNARD, Jean-Sébastien
hal.structure.identifierInstituto Valenciano de Investigaciones Agrarias - Institut Valencià d'Investigacions Agraries - Valencian Institute for agricultural Research [IVIA]
dc.contributor.authorRUIZ-GARCIA, Ana B.
hal.structure.identifierPalacky University Olomouc
dc.contributor.authorSAFAROVA, Dana
hal.structure.identifierUniversité de Bâle = University of Basel = Basel Universität [Unibas]
dc.contributor.authorSCHNEEBERGER, Pierre H. H.
hal.structure.identifierAgricultural Research Organization
dc.contributor.authorSELA, Noa
hal.structure.identifierDepartment of Environmental Sciences, Botany
dc.contributor.authorTURCO, Silvia
hal.structure.identifierNatural Resources Institute Finland [LUKE]
dc.contributor.authorVAINIO, Eeva J.
hal.structure.identifierNational Agricultural Research and Innovation Center [NARIC]
dc.contributor.authorVARALLYAY, Eva
hal.structure.identifierUnité de Pathologie Végétale [PV]
dc.contributor.authorVERDIN, Eric
hal.structure.identifierNational Plant Protection Organization [NPPO]
dc.contributor.authorWESTENBERG, Marcel
hal.structure.identifierUniversité de Liège
dc.contributor.authorBROSTAUX, Yves
hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorCANDRESSE, Thierry
dc.date.issued2019
dc.identifier.issn0031-949X
dc.description.abstractEnRecent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported, but little attention has been paid so far to their sensitivity and reliability for diagnostic purposes. We therefore compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large scale performance test ten datasets of 21-24 nt small (s)RNA sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty to detect viral agents when they are novel and/or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases and (iv) the significant level of scientific expertise needed when interpreting pipelines results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.
dc.language.isoen
dc.publisherAmerican Phytopathological Society
dc.subjectTechniques
dc.subjectVirology
dc.title.enVirus detection by high-throughput sequencing of small RNAs: large scale performance testing of sequence analysis strategies
dc.typeArticle de revue
dc.identifier.doi10.1094/PHYTO-02-18-0067-R
dc.subject.halSciences du Vivant [q-bio]/Biologie végétale/Phytopathologie et phytopharmacie
dc.subject.halSciences du Vivant [q-bio]/Microbiologie et Parasitologie/Virologie
dc.description.sponsorshipEuropeDiversification for Tobacco Growing Farms by the alternative crop Stevia rebaudiana Bertoni
bordeaux.journalPhytopathology
bordeaux.page488-497
bordeaux.volume109
bordeaux.issue3
bordeaux.peerReviewedoui
hal.identifierhal-02627121
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02627121v1
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