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

Denis Kutnjak, Lucie Tamisier, Ian Adams, Neil Boonham, Thierry Candresse, Michela Chiumenti, Kris De Jonghe, Jan Kreuze, Marie Lefebvre, Gonçalo Silva, Martha Malapi-Wight, Paolo Margaria, Irena Mavric-Plesko, Sam McGreig, Laura Miozzi, Benoit Remenant, Jean-Sébastien Reynard, Johan Rollin, Mike Rott, Olivier SchumppAnnelies Haegeman

Onderzoeksoutput: Bijdrage aan tijdschriftA1: Web of Science-artikelpeer review


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 thatresearchers 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.
Oorspronkelijke taalNederlands
Artikel nummer841
Pagina's (van-tot)1-31
Aantal pagina’s31
PublicatiestatusGepubliceerd - 14-apr-2021

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