Conventional detection of viruses and virus-like diseases of plants is accomplished using a combination of molecular, serological, and biological indexing. These are the primary tools used by plant virologists to monitor and ensure trees are free of known viral pathogens. The biological indexing assay, or bioassay, is considered to be the “gold standard” as it is the only method of the three that can detect new, uncharacterized, or poorly characterized viral disease agents. Unfortunately, this method is also the most labor intensive and can take up to three years to complete. Next generation sequencing (NGS) is a technology with rapidly expanding possibilities including potential applications for the detection of plant viruses. In this study, comparisons are made between tree fruit testing by conventional and NGS methods, to demonstrate the efficacy of NGS. A comparison of 178 infected trees, many infected with several viral pathogens, demonstrated that conventional and NGS were equally capable of detecting known viruses and viroids. Comparable results were obtained for 170 of 178 of the specimens. Of the remaining eight specimens, some discrepancies were observed between viruses detected by the two methods, representing less than 5% of the specimens. NGS was further demonstrated to be equal or superior for the detection of new or poorly characterized viruses when compared with a conventional bioassay. These results validated both the effectiveness of conventional virus testing methods and the use of NGS as an additional or alternative method for plant virus detection.
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.
The complete nucleotide sequence of an Albanian isolate of grapevine leafroll-associated virus 7 (GLRaV-7-Alb) was determined. The viral genome consists of 16,404 nucleotides and has nine open reading frames (ORFs) that potentially encode proteins, most of which are typical for members of the family Closteroviridae. Only the 25-kDa (ORF8) and 27-kDa (ORF9) proteins had no apparent similarity to other viral proteins in the sequence databases. The genome structure of GLRaV-7-Alb closely resembles that of little cherry virus 1 and cordyline virus 1. In phylogenetic trees constructed with HSP70h sequences, these three viruses cluster together in a clade next to that comprising members of the genus Crinivirus, to which they are more closely related than to the clostero- and ampeloviruses. The molecular properties of these three viruses differ sufficiently from those of members of the three extant genera of the family Closteroviridae to warrant their classification in a novel genus.
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