Virus detection by high-throughput sequencing of small RNAs: large scale performance testing of sequence analysis strategies
2019
Massart, Sébastien | Chiumenti, Michela | de Jonghe, Kris | Glover, Rachel | Haegeman, Annelies | Koloniuk, Igor | Komínek, Petr | Kreuze, Jan | Kutnjak, Denis | Lotos, Leonidas | Maclot, François | Maliogka, Varvara | Maree, Hans J. | Olivier, Thibaut | Olmos, Antonio | Pooggin, Mikhail M. | Reynard, Jean-Sébastien | Ruiz-Garcia, Ana B. | Safarova, Dana | Schneeberger, Pierre H. H. | Sela, Noa | Turco, Silvia | Vainio, Eeva J. | Varallyay, Eva | Verdin, Eric | Westenberg, Marcel | Brostaux, Yves | Candresse, Thierry | Université de Liège = University of Liège = Universiteit van Luik = Universität Lüttich (ULiège) | National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR) | Plant Sciences Unit ; Research Institute for Agricultural, Fisheries and Food (ILVO) | Fera Science Limited | Biology Centre of the Czech Academy of Sciences (BIOLOGY CENTRE CAS) ; Czech Academy of Sciences [Prague] (CAS) | Crop research institute | International Potato Center [Lima] (CIP) ; International Potato Center = Centre International de la Pomme de terre (CIP) ; Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR) | Department of Biotechnology and Systems Biology ; National Institute of Biology [Ljubljana] (NIB) | Aristotle University of Thessaloniki | Agricultural Research Council [Pretoria, South Africa] (ARC) | Life Sciences Department ; Centre wallon de Recherches Agronomiques [Belgique] = Walloon Agricultural Research Centre [Belgium] (CRA-W) | Instituto Valenciano de Investigaciones Agrarias - Institut Valencià d'Investigacions Agraries - Valencian Institute for agricultural Research (IVIA) | Biologie et Génétique des Interactions Plante-Parasite (UMR BGPI) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Department of Environmental Sciences ; University of California [Los Angeles] (UCLA) ; University of California (UC)-University of California (UC) | Agroscope | Palacky University Olomouc | Université de Bâle = University of Basel = Basel Universität (Unibas) | Agricultural Research Organization | Department of Environmental Sciences, Botany ; Zurich Basel Plant Science Center ; Universität Zürich [Zürich] = University of Zurich (UZH)-Université de Bâle = University of Basel = Basel Universität (Unibas)-Universität Zürich [Zürich] = University of Zurich (UZH)-Université de Bâle = University of Basel = Basel Universität (Unibas) | Natural Resources Institute Finland (LUKE) | National Agricultural Research and Innovation Center (NARIC) | Unité de Pathologie Végétale (PV) ; Institut National de la Recherche Agronomique (INRA) | National Plant Protection Organization (NPPO) | Biologie du fruit et pathologie (BFP) ; Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1 (UB) | European Project: 232250,EC:FP7:SME,FP7-SME-2008-1,DIVAS(2009)
UMR BFP - Equipe Virologie
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Mostrar más [+] Menos [-]Inglés. Recent 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.
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