KUTNJAK, Denis; TAMISIER, Lucie; ADAMS, Ian; BOONHAM, Neil; CANDRESSE, Thierry; CHIUMENTI, Michela; DE JONGHE, Kris; KREUZE, Jan F.; LEFEBVRE, Marie; SILVA, Goncalo; MALAPI-WIGHT, Martha; MARGARIA, Paolo; MAVRIC PLESCO, Irena; MCGREIG, Sam; MIOZZI, Laura; REMENANT, Benoit; REYNARD, Jean Sebastien; ROLLIN, Johan; ROTT, Mike; SCHUMPP, Olivier; MASSART, Sébastien; HAEGEMAN, Annelies

doi:10.3390/microorganisms9040841

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KUTNJAK, Denis
National Institute of Biology [Ljubljana] [NIB]

TAMISIER, Lucie
Gembloux Agro-Bio Tech [Faculté universitaire des sciences agronomiques de Gembloux] [[FUSAGx]]

ADAMS, Ian
Fera Science Limited

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Ce document a été publié dans

Microorganisms. 2021-04-14, vol. 9, n° 4, p. 841

MDPI

Résumé en anglais

High-throughput sequencing (HTS) technologies have become indispensable tools assisting plant virus diagnostics and research thanks to their ability to detect any plant virus in a sample without prior knowledge. As HTS technologies are heavily relying on bioinformatics analysis of the huge amount of generated sequences, it is of utmost importance that researchers can rely on efficient and reliable bioinformatic tools and can understand the principles, advantages, and disadvantages of the tools used. Here, we present a critical overview of the steps involved in HTS as employed for plant virus detection and virome characterization. We start from sample preparation and nucleic acid extraction as appropriate to the chosen HTS strategy, which is followed by basic data analysis requirements, an extensive overview of the in-depth data processing options, and taxonomic classification of viral sequences detected. By presenting the bioinformatic tools and a detailed overview of the consecutive steps that can be used to implement a well-structured HTS data analysis in an easy and accessible way, this paper is targeted at both beginners and expert scientists engaging in HTS plant virome projects< Réduire

Mots clés

Pathologie Végétale

Virologie végétale

Santé des plantes

Mots clés en anglais

plant virus

high-throughput sequencing

bioinformatics

detection

discovery