Fontdevila Pareta Nuria, Khalili Maryam, Maachi Ayoub, Rivarez Mark Paul S, Rollin Johan, Salavert Ferran, Temple Coline, Aranda Miguel A, Boonham Neil, Botermans Marleen, Candresse Thierry, Fox Adrian, Hernando Yolanda, Kutnjak Denis, Marais Armelle, Petter Françoise, Ravnikar Maja, Selmi Ilhem, Tahzima Rachid, Trontin Charlotte, Wetzel Thierry, Massart Sebastien
Plant Pathology Laboratory, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
Univ. Bordeaux, INRAE, UMR BFP, Villenave d'Ornon, France.
Front Microbiol. 2023 May 30;14:1181562. doi: 10.3389/fmicb.2023.1181562. eCollection 2023.
The advances in high-throughput sequencing (HTS) technologies and bioinformatic tools have provided new opportunities for virus and viroid discovery and diagnostics. Hence, new sequences of viral origin are being discovered and published at a previously unseen rate. Therefore, a collective effort was undertaken to write and propose a framework for prioritizing the biological characterization steps needed after discovering a new plant virus to evaluate its impact at different levels. Even though the proposed approach was widely used, a revision of these guidelines was prepared to consider virus discovery and characterization trends and integrate novel approaches and tools recently published or under development. This updated framework is more adapted to the current rate of virus discovery and provides an improved prioritization for filling knowledge and data gaps. It consists of four distinct steps adapted to include a multi-stakeholder feedback loop. Key improvements include better prioritization and organization of the various steps, earlier data sharing among researchers and involved stakeholders, public database screening, and exploitation of genomic information to predict biological properties.
高通量测序(HTS)技术和生物信息学工具的进步为病毒和类病毒的发现及诊断提供了新机遇。因此,源自病毒的新序列正以前所未有的速度被发现和公布。为此,各方共同努力撰写并提出了一个框架,用于确定发现新植物病毒后所需生物特性鉴定步骤的优先顺序,以评估其在不同层面的影响。尽管所提议的方法被广泛使用,但仍对这些指南进行了修订,以考虑病毒发现和特性鉴定的趋势,并整合最近发表或正在开发的新方法和工具。这个更新后的框架更适应目前的病毒发现速度,并为填补知识和数据空白提供了更好的优先顺序安排。它由四个不同步骤组成,并纳入了多利益相关方反馈循环。主要改进包括对各个步骤进行更好的优先排序和组织、研究人员与相关利益方更早地共享数据、公共数据库筛选以及利用基因组信息预测生物学特性。