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

High-throughput sequencing (HTS) technologies have become indispensable tools assistingplant virus diagnostics and research thanks to their ability to detect any plant virus in a samplewithout prior knowledge. As HTS technologies are heavily relying on bioinformatics analysis of thehuge amount of generated sequences, it is of utmost importance that researchers can rely on efficientand reliable bioinformatic tools and can understand the principles, advantages, and disadvantagesof the tools used. Here, we present a critical overview of the steps involved in HTS as employed forplant virus detection and virome characterization. We start from sample preparation and nucleicacid extraction as appropriate to the chosen HTS strategy, which is followed by basic data analysisrequirements, an extensive overview of the in-depth data processing options, and taxonomic classificationof viral sequences detected. By presenting the bioinformatic tools and a detailed overviewof 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 inHTS plant virome projects.