Jean-Sébastien Reynard

Recent advances in high-throughput sequencing technologies and bioinformatics have generated huge new opportunities for discovering and diagnosing plant viruses and viroids. Plant virology has undoubtedly benefited from these new methodologies, but at the same time, faces now substantial bottlenecks, namely the biological characterization of the newly discovered viruses and the analysis of their impact at the biosecurity, commercial, regulatory, and scientific levels. This paper proposes a scaled and progressive scientific framework for efficient biological characterization and risk assessment when a previously known or a new plant virus is detected by next generation sequencing (NGS) technologies. Four case studies are also presented to illustrate the need for such a framework, and to discuss the scenarios.

Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported but little attention has been paid thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large-scale performance test using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false-positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty in detecting viral agents when they are novel or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases, and (iv) the significant level of scientific expertise needed when interpreting pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.

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.

Grapevine red blotch virus (GRBV) is a recently described virus that infects grapevine. Little information is available on the possible occurrence and distribution outside North America. Therefore, we surveyed commercial vineyards from the three major grape-growing regions in Switzerland to determine the presence or absence of GRBV. In total, 3,062 vines were analyzed by polymerase chain reaction. None of the vines tested positive for GRBV, suggesting the absence of GRBV from Swiss vineyards. We also investigated whether GRBV was present in 653 grapevine accessions in the Agroscope grapevine virus collection at Nyon, including dominantly Swiss (457) but also international accessions. Only six referential accessions were infected by GRBV, all originating from the United States, whereas all others from 10 European and 8 non-European origins tested negative. High-throughput sequencing analysis of Zinfandel A2V13, in the collection since 1985, confirmed close similarity of GRBV isolate Z_A2V13 to American isolates according to genomes deposited in GenBank. Because the Zinfandel A2V13 reference was also maintained grafted on the leafroll virus indicator Vitis vinifera 'Gamay', we evaluated the effect of GRBV on viticultural performance over a 3-year period. Our results showed clear detrimental effects of GRBV on grapevine physiology (vine vigor, leaf chlorophyll content, and gas exchange) and fruit quality. These findings underscore the importance of implementation of GRBV testing worldwide in certification and quarantine programs to prevent the dissemination of this virus.

Leafroll viruses are among the most devastating pathogens in viticulture and are responsible for major economic losses in the wine industry. However, the molecular interactions underlying the effects on fruit quality deterioration are not well understood. The few molecular studies conducted on berries from infected vines, associated quality decreases with the repression of key genes in sugar transport and anthocyanin biosynthesis. Sampling protocols in these studies did however not account for berry heterogeneity and potential virus induced phenological shifts, which could have biased the molecular information. In the present study, we adopted an innovative individual berry sampling protocol to produce homogeneous batches for RNA extraction, thereby circumventing berry heterogeneity and compensating for virus induced phenological shifts. This way a characterization of the transcriptomic modulation by viral infections was possible and explain why our results differ significantly from previously reported repression of anthocyanin biosynthesis and sugar metabolism. The present study provides new insights into the berry transcriptome modulation by leafroll infection, highlighting the virus induced upregulation of plant innate immunity as well as an increased responsiveness of the early ripening berry to biotic stressors. The study furthermore emphasizes the importance of sampling protocols in physiological studies on grapevine berry metabolism.