A Primer on the Analysis of High-Throughput Sequencing Data for Detection of Plant Viruses

Author:

Kutnjak DenisORCID,Tamisier LucieORCID,Adams Ian,Boonham Neil,Candresse ThierryORCID,Chiumenti MichelaORCID,De Jonghe KrisORCID,Kreuze Jan F.ORCID,Lefebvre MarieORCID,Silva GonçaloORCID,Malapi-Wight MarthaORCID,Margaria Paolo,Mavrič Pleško Irena,McGreig Sam,Miozzi LauraORCID,Remenant Benoit,Reynard Jean-SebastienORCID,Rollin Johan,Rott Mike,Schumpp Olivier,Massart Sébastien,Haegeman AnneliesORCID

Abstract

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.

Funder

FOD Volksgezondheid, Veiligheid van de Voedselketen en Leefmilieu

Javna Agencija za Raziskovalno Dejavnost RS

Consortium of International Agricultural Research Centers

Bill and Melinda Gates Foundation

Euphresco

Publisher

MDPI AG

Subject

Virology,Microbiology (medical),Microbiology

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