Grapevine leafroll disease (GLD) is one of the most important grapevine viral diseases affecting grapevines worldwide. The impact on vine health, crop yield and quality is difficult to assess due to a high number of variables, but significant economic losses are consistently reported over the lifespan of a vineyard if intervention strategies are not implemented. Several viruses from the family Closteroviridae are associated with GLD. However, Grapevine leafroll-associated virus 3 (GLRaV-3), the type species for the genus Ampelovirus, is regarded as the most important causative agent. Here we provide a general overview on various aspects of GLRaV-3, with an emphasis on the latest advances in the characterization of the genome. The full genome of several isolates have recently been sequenced and annotated, revealing the existence of several genetic variants. The classification of these variants, based on their genome sequence, will be discussed and a guideline is presented to facilitate future comparative studies. The characterization of sgRNAs produced during the infection cycle of GLRaV-3 has given some insight into the replication strategy and the putative functionality of the ORFs. The latest nucleotide sequence based molecular diagnostic techniques were shown to be more sensitive than conventional serological assays and although ELISA is not as sensitive it remains valuable for high-throughput screening and complementary to molecular diagnostics. The application of next-generation sequencing is proving to be a valuable tool to study the complexity of viral infection as well as plant-pathogen interaction. Next-generation sequencing data can provide information regarding disease complexes, variants of viral species, and abundance of particular viruses. This information can be used to develop more accurate diagnostic assays. Reliable virus screening in support of robust grapevine certification programs remains the cornerstone of GLD management.

Application of HTS for Routine Plant Virus Diagnostics: State of the Art and Challenges

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.

Grapevine leafroll is the most complex and intriguing viral disease of grapevine (Vitis spp.). Several monopartite closteroviruses (family Closteroviridae) from grapevines have been molecularly characterized, yet their role in disease etiology is not completely resolved. Hence, these viruses are currently designated under the umbrella term of Grapevine leafroll–associated viruses (GLRaVs). This review examines our current understanding of the genetically divergent GLRaVs and highlights the emerging picture of several unique aspects of the leafroll disease pathosystem. A systems biology approach using contemporary technologies in molecular biology, -omics, and cell biology aids in exploring the comparative molecular biology of GLRaVs and deciphering the complex network of host-virus-vector interactions to bridge the gap between genomics and phenomics of leafroll disease. In addition, grapevine-infecting closteroviruses have a great potential as designer viruses to pursue functional genomics and for the rational design of novel disease intervention strategies in this agriculturally important perennial fruit crop.

The use of next-generation sequencing has become an established method for virus detection. Efficient study design for accurate detection relies on the optimal amount of data representing a significant portion of a virus genome. In this study, genome coverage at different sequencing depths was determined for a number of viruses, viroids, hosts and sequencing library types, using both read-mapping and de novo assembly-based approaches. The results highlighted the strength of ribo-depleted RNA and sRNA in obtaining saturated genome coverage with the least amount of data, while even though the poly(A)-selected RNA yielded virus-derived reads, it was insufficient to cover the complete genome of a non-polyadenylated virus. The ribo-depleted RNA data also outperformed the sRNA data in terms of the percentage of coverage that could be obtained particularly with the de novo assembled contigs. Our results suggest the use of ribo-depleted RNA in a de novo assembly-based approach for the detection of single-stranded RNA viruses. Furthermore, we suggest that sequencing one million reads will provide sufficient genome coverage specifically for closterovirus detection.