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RNASeq or double-stranded RNA based approaches allowed the reconstruction of a total of 9 full-length or near full-length genomes of the recently discovered grapevine virus T (GVT). In addition, datamining of publicly available grapevine RNASeq transcriptome data allowed the reconstruction of a further 14 GVT genomes from five grapevine sources. Together with four GVT sequences available in Genbank, these novel sequences were used to analyse GVT diversity. GVT shows a very limited amount of indels variation but a high level of nucleotide and aminoacid polymorphism. This level is comparable to that shown in the closely related grapevine rupestris stem pitting-associated virus (GRSPaV). Further analyses showed that GVT mostly evolves under conservative selection pressure and that recombination has contributed to its evolutionary history. Phylogenetic analyses allow to identify at least seven clearly separated groups of GVT isolates. Analysis of the only reported PCR GVT-specific detection primer pair indicates that it is likely to fail to amplify some GVT isolates. Taken together these results point at the distinctiveness of GVT but also at the many points it shares with GRSPaV. They constitute the first pan-genomic analysis of the diversity of this novel virus., Competing Interests: The authors have declared that no competing interests exist.

Perennial crops, such as fruit trees, are infected by many viruses, which are transmitted through vegetative propagation and grafting of infected plant material. Some of these pathogens cause severe crop losses and often reduce the productive life of the orchards. Detection and characterization of these agents in fruit trees is challenging, however, during the last years, the wide application of high-throughput sequencing (HTS) technologies has significantly facilitated this task. In this review, we present recent advances in the discovery, detection, and characterization of fruit tree viruses and virus-like agents accomplished by HTS approaches. A high number of new viruses have been described in the last 5 years, some of them exhibiting novel genomic features that have led to the proposal of the creation of new genera, and the revision of the current virus taxonomy status. Interestingly, several of the newly identified viruses belong to virus genera previously unknown to infect fruit tree species (e.g., Fabavirus , Luteovirus ) a fact that challenges our perspective of plant viruses in general. Finally, applied methodologies, including the use of different molecules as templates, as well as advantages and disadvantages and future directions of HTS in fruit tree virology are discussed.

A one-step multiplex real-time reverse transcription polymerase chain reaction (RT-qPCR) based on TaqMan probes was developed for the simultaneous detection of Apple mosaic virus (ApMV), Apple stem pitting virus (ASPV) and Apple stem grooving virus (ASGV) in total RNA of pome trees extracted with a CTAB method. The sensitivity of the method was established using in vitro synthesized viral transcripts serially diluted in RNA from healthy, virus-tested (negative) pome trees. The three viruses were simultaneously detected up to a 10-4 dilution of total RNA from a naturally triple-infected apple tree prepared in total RNA of healthy apple tissue. The newly developed RT-qPCR assay was at least one hundred times more sensitive than conventional single RT-PCRs. The assay was validated with 36 field samples for which nine triple and 11 double infections were detected. All viruses were detected simultaneously in composite samples at least up to the ratio of 1:150 triple-infected to healthy pear tissue, suggesting the assay has the capacity to examine rapidly a large number of samples in pome tree certification programs and surveys for virus presence.

The ability to provide a fast, inexpensive and reliable diagnostic for any given viral infection is a key parameter in efforts to fight and control these ubiquitous pathogens. The recent developments of high-throughput sequencing (also called Next Generation Sequencing - NGS) technologies and bioinformatics have drastically changed the research on viral pathogens. It is now raising a growing interest for virus diagnostics. This review provides a snapshot vision on the current use and impact of high throughput sequencing approaches in plant virus characterization. More specifically, this review highlights the potential of these new technologies and their interplay with current protocols in the future of molecular diagnostic of plant viruses. The current limitations that will need to be addressed for a wider adoption of high-throughput sequencing in plant virus diagnostics are thoroughly discussed., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Cucumber mosaic virus, Tomato spotted wilt virus, Tomato mosaic virus, Tomato chlorosis virus, Pepino mosaic virus, Torrado tomato virus and Tomato infectious chlorosis virus cause serious damage and significant economic losses in tomato crops worldwide. The early detection of these pathogens is essential for preventing the viruses from spreading and improving their control. In this study, a procedure based on two multiplex RT-PCRs was developed for the sensitive and reliable detection of these seven viruses. Serial dilutions of positive controls were analysed by this methodology, and the results were compared with those obtained by ELISA and singleplex versions of RT-PCR. The multiplex and singleplex RT-PCR assays were able to detect specific targets at the same dilution and were 100 times more sensitive than ELISA. The multiplex versions were able to detect composite samples containing different concentrations of specific targets at ratios from 1:1 to 1:1000. In addition, 45 symptomatic tomato samples collected in different tomato-growing areas of Sicily (Italy) were analysed by multiplex RT-PCR, singleplex RT-PCR and commercially available ELISA tests. Similar results were obtained using the RT-PCR techniques, with a higher sensitivity than ELISA, revealing a common occurrence of mixed infections and confirming the presence of these seven virus species in Italy., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Detection of harmful viruses and bacteria in plant material, vectors or natural reservoirs is essential to ensure safe and sustainable agriculture. The techniques available have evolved significantly in the last few years to achieve rapid and reliable detection of pathogens, extraction of the target from the sample being important for optimising detection. For viruses, sample preparation has been simplified by imprinting or squashing plant material or insect vectors onto membranes. To improve the sensitivity of techniques for bacterial detection, a prior enrichment step in liquid or solid medium is advised. Serological and molecular techniques are currently the most appropriate when high numbers of samples need to be analysed. Specific monoclonal and/or recombinant antibodies are available for many plant pathogens and have contributed to the specificity of serological detection. Molecular detection can be optimised through the automatic purification of nucleic acids from pathogens by columns or robotics. New variants of PCR, such as simple or multiplex nested PCR in a single closed tube, co-operative-PCR and real-time monitoring of amplicons or quantitative PCR, allow high sensitivity in the detection of one or several pathogens in a single assay. The latest development in the analysis of nucleic acids is micro-array technology, but it requires generic DNA/RNA extraction and pre-amplification methods to increase detection sensitivity. The advances in research that will result from the sequencing of many plant pathogen genomes, especially now in the era of proteomics, represent a new source of information for the future development of sensitive and specific detection techniques for these microorganisms.

A new and highly sensitive method for the amplification of viral RNA targets from plant material has been developed and patented. This technique called Co-operational amplification (Co-PCR) can be carried out easily in a simple tetraprimer reaction based on the simultaneous action of four primers. The reaction process consists of the simultaneous reverse transcription of two different fragments from the same target, one containing the other; the production of four amplicons by the combination of the two pair of primers, one pair external to other; and the co-operational action of amplicons for the production of the largest fragment. The technique was used successfully, both in metal block and capillary air thermal cyclers for the detection of plant RNA viruses (Cherry leaf roll virus, Strawberry latent ringspot virus, Cucumber mosaic virus, Plum pox virus and Citrus tristeza virus). The sensitivity observed is at least 100 times higher than that achieved with RT-PCR and similar to nested RT-PCR. Colorimetric detection was coupled with this methodology facilitating its introduction for routine indexing programs and for phytosanitary selection of virus-free plant material.

Grapevine (Vitis vinifera L.) is one of the most important crops in the world due to its economic and social impact. Like many other crops, grapevine is susceptible to different types of diseases caused by pathogenic microorganisms. Grapevine leafroll-associated virus 1 (GLRaV-1) is a virus associated with grapevine leafroll disease and it is considered at the national and European level as a pathogen that must be absent in propagative plant material. For this reason, the availability of specific, sensitive and reliable detection techniques to ascertain the sanitary status of the plants is of great importance. The objective of this research was the development of a new GLRaV-1 detection method based on a TaqMan quantitative real-time RT-PCR targeted to the coat protein genomic region and including a host internal control in a duplex reaction. To this end, three new GLRaV-1 full genomes were recovered by HTS and aligned with all sequences available in the databases. The method has been validated following EPPO standards and applied for the diagnosis of field plant material and transmission vectors. The new protocol designed has turned out to be highly sensitive as well as much more specific than the current available methods for the detection and absolute quantitation of GLRaV-1 viral titer. [ABSTRACT FROM AUTHOR]

Grapevine leafroll-associated virus 3 (GLRaV-3) has a worldwide distribution and is the most economically important virus that causes grapevine leafroll disease. Reliable, sensitive, and specific methods are required for the detection of the pathogen in order to assure the production of healthy plant material and control of the disease. Although different serological and nucleic acid-based methods have been developed for the detection of GLRaV-3, diagnostic parameters have not been established, and there is no gold standard method. Therefore, the main aim of this work was to determine the sensitivity, specificity, and likelihood ratios of three commonly used methods, including one serological test (double-antibody sandwich enzyme-linked immunosorbent assay [DAS-ELISA]) and two nucleic acid-based techniques (spot and conventional real-time reverse transcription-polymerase chain reaction [RT-PCR]). Latent class models using a Bayesian approach have been applied to determine diagnostic test parameters and to facilitate decision-making regarding diagnostic test selection. Statistical analysis has been based on the results of a total of 281 samples, which were collected during the dormant period from three different populations. The best-fit model out of the 49 implemented models revealed that DAS-ELISA was the most specific method (value = 0.99) and provided the highest degree of confidence in positive results. Conversely, conventional real-time RT-PCR was the most sensitive method (value = 0.98) and produced the highest degree of confidence in negative results. Furthermore, the estimation of likelihood ratios showed that in populations with low GLRaV-3 prevalence the most appropriate method could be DAS-ELISA, while conventional real-time RT-PCR could be the most appropriate method in medium or high prevalence populations. Combining both techniques significantly increases detection accuracy. The flexibility and power of Bayesian latent class models open new possibilities for the evaluation of diagnostic tests for plant viruses. [ABSTRACT FROM AUTHOR]

The ubiquitin proteasome is a rapid, adaptive mechanism for selective protein degradation, crucial for proper plant growth and development. The ubiquitin proteasome system (UPS) has also been shown to be an integral part of plant responses to stresses, including plant defence against pathogens. Recently, significant progress has been made in the understanding of the involvement of the UPS in the signalling and regulation of the interaction between plants and viruses. This review aims to discuss the current knowledge about the response of plant viral infection by the UPS and how the viruses counteract this system, or even use it for their own benefit. [ABSTRACT FROM AUTHOR]

Grapevine Roditis leaf discoloration-associated virus (GRLDaV) is an emerging grapevine pathogen included in the European and Mediterranean Plant Protection Organization (EPPO) alert list due to its ability to damage grapevine crops and cause production losses. This work aimed to develop a specific and reliable diagnostic tool that would contribute to preventing the spread of this pathogen. Therefore, a TaqMan real-time quantitative PCR was developed. The method was validated according to EPPO guidelines showing a high degree of analytical sensitivity, analytical specificity, selectivity, and repeatability and reproducibility. The sensitivity of this method is much higher than the sensitivity reached by previously reported methods even when tested in crude extracts, which could allow rapid testing by avoiding nucleic acid extraction steps. The method was also able to detect GRLDaV isolates from all the geographic origins reported so far, despite their high degree of genetic diversity. In addition, this new technique has been successfully applied for the quantitative detection of GRLDaV in plant material and two mealybug species, Planococcus citri and Pseudococcus viburni. In conclusion, the methodology developed herein represents a significant contribution to the diagnosis and control of this emerging pathogen in grapevine. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]