Quarantine Regulations and the Impact of Modern Detection Methods

Comprehensive Metatranscriptomic Analysis of Plant Viruses in Imported Frozen Cherries and Blueberries

The possibility of new viruses emerging in various regions worldwide has increased due to a combination of factors, including climate change and the expansion of international trading. Plant viruses spread through various transmission routes, encompassing well-known avenues such as pollen, seeds, and insects. However, research on potential transmission routes beyond these known mechanisms has remained limited. To address this gap, this study employed metatranscriptomic analysis to ascertain the presence of plant viruses in imported frozen fruits, specifically cherries and blueberries. This analysis aimed to identify pathways through which plant viruses may be introduced into countries. Virome analysis revealed the presence of six species of plant viruses in frozen cherries and blueberries: cherry virus A (CVA), prunus necrotic ringspot virus (PNRSV), prune dwarf virus (PDV), prunus virus F (PrVF), blueberry shock virus (BlShV), and blueberry latent virus (BlLV). Identifying these potential transmission routes is crucial for effectively managing and preventing the spread of plant viruses and crop protection. This study highlights the importance of robust quality control measures and monitoring systems for frozen fruits, emphasizing the need for proactive measures to mitigate the risk associated with the potential spread of plant viruses.

Comparative Performance Evaluation of Double-Stranded RNA High-Throughput Sequencing for the Detection of Viral Infection in Temperate Fruit Crops

There is limited information on the compared performances of biological, serological. and molecular assays with high-throughput sequencing (HTS) for viral indexing in temperate fruit crops. Here, using a range of samples of predetermined virological status, we compared two performance criteria (inclusivity and analytical sensitivity) of enzyme-linked immunosorbent assay (ELISA), molecular hybridization, reverse transcription (RT)-PCR, and double-stranded RNA (dsRNA) HTS for the detection of a total of 14 viruses (10 genera) and four viroids (three genera). When undiluted samples from individual plants were used, ELISA had the lowest performance, with an overall detection rate of 68.7%, followed by RT-PCR (82.5%) and HTS (90.7%; 100% if considering only viruses). The lower performance of RT-PCR reflected the inability to amplify some isolates as a consequence of point mutations affecting primer-binding sites. In addition, HTS identified viruses that had not been identified by other assays in nearly two-thirds of the samples. Analysis of serial dilutions of fruit tree samples allowed comparison of analytical sensitivities for various viruses. ELISA showed the lowest analytical sensitivity, but RT-PCR showed higher analytical sensitivity than HTS for most of the samples. Overall, these results confirm the superiority of HTS over biological indexing in terms of speed and inclusivity and show that while the absolute analytical sensitivity of RT-PCR tends to be higher than that of HTS, PCR inclusivity is affected by viral genetic diversity. Taken together, these results make a strong case for the implementation of HTS-based approaches in fruit tree viral testing protocols supporting quarantine and certification programs.

An optical system to detect, surveil, and kill flying insect vectors of human and crop pathogens

Sustainable and effective means to control flying insect vectors are critically needed, especially with widespread insecticide resistance and global climate change. Understanding and controlling vectors requires accurate information about their movement and activity, which is often lacking. The Photonic Fence (PF) is an optical system that uses machine vision, infrared light, and lasers to identify, track, and interdict vectors in flight. The PF examines an insect's outline, flight speed, and other flight parameters and if these match those of a targeted vector species, then a low-power, retina-safe laser kills it. We report on proof-of-concept tests of a large, field-sized PF (30 mL × 3 mH) conducted with Aedes aegypti, a mosquito that transmits dangerous arboviruses, and Diaphorina citri, a psyllid which transmits the fatal huanglongbing disease of citrus. In tests with the laser engaged, < 1% and 3% of A. aegypti and D. citri, respectfully, were recovered versus a 38% and 19% recovery when the lacer was silenced. The PF tracked, but did not intercept the orchid bee, Euglossa dilemma. The system effectively intercepted flying vectors, but not bees, at a distance of 30 m, heralding the use of photonic energy, rather than chemicals, to control flying vectors.

Development of Rapid and Affordable Virus-Mimicking Artificial Positive Controls

A major bottleneck in the development of detection assays is the availability of positive controls. Their acquisition can be problematic, their maintenance is expensive, and without them, assays cannot be validated. Herein, we present a novel strategy for the development of virus-mimicking artificial positive controls (ViMAPCs). The time between design and application is less than 5 days, unlike alternatives which normally take several weeks to obtain and implement. The ViMAPCs provide a realistic representation of natural infection unlike alternatives and allow for an effortless recognition of laboratory-based contamination. The feasibility and adaptability of the strategy was evaluated using several RNA and DNA plant viruses. ViMAPCs can be used in diagnostics laboratories but also in the monitoring of pathogen outbreaks where rapid response is of utmost importance.

PhytoPipe: a phytosanitary pipeline for plant pathogen detection and diagnosis using RNA-seq data

BACKGROUND

Detection of exotic plant pathogens and preventing their entry and establishment are critical for the protection of agricultural systems while securing the global trading of agricultural commodities. High-throughput sequencing (HTS) has been applied successfully for plant pathogen discovery, leading to its current application in routine pathogen detection. However, the analysis of massive amounts of HTS data has become one of the major challenges for the use of HTS more broadly as a rapid diagnostics tool. Several bioinformatics pipelines have been developed to handle HTS data with a focus on plant virus and viroid detection. However, there is a need for an integrative tool that can simultaneously detect a wider range of other plant pathogens in HTS data, such as bacteria (including phytoplasmas), fungi, and oomycetes, and this tool should also be capable of generating a comprehensive report on the phytosanitary status of the diagnosed specimen.

RESULTS

We have developed an open-source bioinformatics pipeline called PhytoPipe (Phytosanitary Pipeline) to provide the plant pathology diagnostician community with a user-friendly tool that integrates analysis and visualization of HTS RNA-seq data. PhytoPipe includes quality control of reads, read classification, assembly-based annotation, and reference-based mapping. The final product of the analysis is a comprehensive report for easy interpretation of not only viruses and viroids but also bacteria (including phytoplasma), fungi, and oomycetes. PhytoPipe is implemented in Snakemake workflow with Python 3 and bash scripts in a Linux environment. The source code for PhytoPipe is freely available and distributed under a BSD-3 license.

CONCLUSIONS

PhytoPipe provides an integrative bioinformatics pipeline that can be used for the analysis of HTS RNA-seq data. PhytoPipe is easily installed on a Linux or Mac system and can be conveniently used with a Docker image, which includes all dependent packages and software related to analyses. It is publicly available on GitHub at https://github.com/healthyPlant/PhytoPipe and on Docker Hub at https://hub.docker.com/r/healthyplant/phytopipe .

Hybrid Autofluorescence and Optoacoustic Microscopy for the Label-Free, Early and Rapid Detection of Pathogenic Infections in Vegetative Tissues

Agriculture plays a pivotal role in food security and food security is challenged by pests and pathogens. Due to these challenges, the yields and quality of agricultural production are reduced and, in response, restrictions in the trade of plant products are applied. Governments have collaborated to establish robust phytosanitary measures, promote disease surveillance, and invest in research and development to mitigate the impact on food security. Classic as well as modernized tools for disease diagnosis and pathogen surveillance do exist, but most of these are time-consuming, laborious, or are less sensitive. To that end, we propose the innovative application of a hybrid imaging approach through the combination of confocal fluorescence and optoacoustic imaging microscopy. This has allowed us to non-destructively detect the physiological changes that occur in plant tissues as a result of a pathogen-induced interaction well before visual symptoms occur. When broccoli leaves were artificially infected with Xanthomonas campestris pv. campestris (Xcc), eventually causing an economically important bacterial disease, the induced optical absorption alterations could be detected at very early stages of infection. Therefore, this innovative microscopy approach was positively utilized to detect the disease caused by a plant pathogen, showing that it can also be employed to detect quarantine pathogens such as Xylella fastidiosa.

Area Wide Monitoring of Plant and Honey Bee (Apis mellifera) Viruses in Blueberry (Vaccinium corymbosum) Agroecosystems Facilitated by Honey Bee Pollination

Healthy agroecosystems are dependent on a complex web of factors and inter-species interactions. Flowers are hubs for pathogen transmission, including the horizontal or vertical transmission of plant-viruses and the horizontal transmission of bee-viruses. Pollination by the European honey bee (Apis mellifera) is critical for industrial fruit production, but bees can also vector viruses and other pathogens between individuals. Here, we utilized commercial honey bee pollination services in blueberry (Vaccinium corymbosum) farms for a metagenomics-based bee and plant virus monitoring system. Following RNA sequencing, viruses were identified by mapping reads to a reference sequence database through the bioinformatics portal Virtool. In total, 29 unique plant viral species were found at two blueberry farms in British Columbia (BC). Nine viruses were identified at one site in Ontario (ON), five of which were not identified in BC. Ilarviruses blueberry shock virus (BlShV) and prune dwarf virus (PDV) were the most frequently detected viruses in BC but absent in ON, while nepoviruses tomato ringspot virus and tobacco ringspot virus were common in ON but absent in BC. BlShV coat protein (CP) nucleotide sequences were nearly identical in all samples, while PDV CP sequences were more diverse, suggesting multiple strains of PDV circulating at this site. Ten bee-infecting viruses were identified, with black queen cell virus frequently detected in ON and BC. Area-wide bee-mediated pathogen monitoring can provide new insights into the diversity of viruses present in, and the health of, bee-pollination ecosystems. This approach can be limited by a short sampling season, biased towards pollen-transmitted viruses, and the plant material collected by bees can be very diverse. This can obscure the origin of some viruses, but bee-mediated virus monitoring can be an effective preliminary monitoring approach.

Molecular Analysis of the Global Population of Potato Virus S Redefines Its Phylogeny, and Has Crop Biosecurity Implications

In 2020, 264 samples were collected from potato fields in the Turkish provinces of Bolu, Afyon, Kayseri and Niğde. RT-PCR tests, with primers which amplified its coat protein (CP), detected potato virus S (PVS) in 35 samples. Complete CP sequences were obtained from 14 samples. Phylogenetic analysis using non-recombinant sequences of (i) the 14 CP's, another 8 from Tokat province and 73 others from GenBank; and (ii) 130 complete ORF, RdRp and TGB sequences from GenBank, found that they fitted within phylogroups, PVS^I, PVS^II or PVS^III. All Turkish CP sequences were in PVS^I, clustering within five subclades. Subclades 1 and 4 were in three to four provinces, whereas 2, 3 and 5 were in one province each. All four genome regions were under strong negative selection constraints (ω = 0.0603-0.1825). Considerable genetic variation existed amongst PVS^I and PVS^II isolates. Three neutrality test methods showed PVS^III remained balanced whilst PVS^I and PVS^II underwent population expansion. The high fixation index values assigned to all PVS^I, PVS^II and PVS^III comparisons supported subdivision into three phylogroups. As it spreads more readily by aphid and contact transmission, and may elicit more severe symptoms in potato, PVS^II spread constitutes a biosecurity threat for countries still free from it.

A Novel, Divergent Member of the Rhabdoviridae Family Infects Strawberry

Strawberry (Fragaria × ananassa) is the most important berry crop worldwide and viruses pose a constant threat to the industry. In this communication, we describe a novel virus in the family Rhabdoviridae referred to as strawberry virus 3 (StrV-3). The virus does not show significant homology when compared with recognized rhabdoviruses and, therefore, the establishment of a new genus should be considered. A triplex reverse-transcription PCR test was developed and successfully employed in a survey of the National Clonal Germplasm Repository Fragaria collection. A CRISPR-Cas-based protocol was also developed and shown to detect the virus in as little as 1 fg of total RNA, a protocol to be used in the detection of the virus in candidate G1 plants. The strawberry aphid (Chaetosiphon fragaefolii) was evaluated-alas, unsuccessfully-as a potential vector of the virus. This work broadens our understanding of the family Rhabdoviridae and assists in the quest of releasing plant material free of viruses.

Phytosanitary Rules for the Movement of Olive (Olea europaea L.) Propagation Material into the European Union (EU)

Phytosanitary legislation involves government laws that are essential to minimize the risk of the introduction and diffusion of pests, especially invasive non-native species, as a consequence of the international exchange of plant material, thus allowing us to safeguard agricultural production and biodiversity of a territory. These measures ensure compliance with adequate requirements relating to the absence of pests, especially of harmful quarantine organisms through inspections and diagnosis tests of the consignments to ascertain the presence of the pests concerned. They also regulate the eradication and containment measures that are implemented in the eventuality of an unintentional introduction of these organisms. In the present contribution, the current plant protection legislation for the exchange of plants or propagation material within the European Union or for export to foreign countries, represented by Regulation (EU) 2016/2031, has been reviewed, with a particular focus on the olive tree (Olea europaea L.). Furthermore, a brief summary of the main olive tree pests transmissible with the propagation material is also reported, indicating their current categorization with respect to the relative quarantine status.

A Step Towards Validation of High-Throughput Sequencing for the Identification of Plant Pathogenic Oomycetes

The advancement in high-throughput sequencing (HTS) technology allows the detection of pathogens without the need for isolation or template amplification. Plant regulatory agencies worldwide are adopting HTS as a prescreening tool for plant pathogens in imported plant germplasm. The technique is a multipronged process and, often, the bioinformatic analysis complicates detection. Previously, we developed E-probe diagnostic nucleic acid analysis (EDNA), a bioinformatic tool that detects pathogens in HTS data. EDNA uses custom databases of signature nucleic acid sequences (e-probes) to reduce computational effort and subjectivity when determining pathogen presence in a sample. E-probes of Pythium ultimum and Phytophthora ramorum were previously validated only using simulated HTS data. However, HTS samples generated from infected hosts or pure culture may vary in pathogen concentration, sequencing bias, and data quality, suggesting that each pathosystem requires further validation. Here, we used metagenomic and genomic HTS data generated from infected hosts and pure culture, respectively, to further validate and curate e-probes of Pythium ultimum and Phytophthora ramorum. E-probe length was found to be a determinant of diagnostic sensitivity and specificity; 80-nucleotide e-probes increased the diagnostic specificity to 100%. Curating e-probes to increase specificity affected diagnostic sensitivity only for 80-nucleotide Pythium ultimum e-probes. Comparing e-probes with alternative databases and bioinformatic tools in their speed and ability to find Pythium ultimum and Phytophthora ramorum demonstrated that, although pathogen sequence reads were detected by other methods, they were less specific and slower when compared with e-probes.

New-Generation Sequencing Technology in Diagnosis of Fungal Plant Pathogens: A Dream Comes True?

The fast and continued progress of high-throughput sequencing (HTS) and the drastic reduction of its costs have boosted new and unpredictable developments in the field of plant pathology. The cost of whole-genome sequencing, which, until few years ago, was prohibitive for many projects, is now so affordable that a new branch, phylogenomics, is being developed. Fungal taxonomy is being deeply influenced by genome comparison, too. It is now easier to discover new genes as potential targets for an accurate diagnosis of new or emerging pathogens, notably those of quarantine concern. Similarly, with the development of metabarcoding and metagenomics techniques, it is now possible to unravel complex diseases or answer crucial questions, such as "What's in my soil?", to a good approximation, including fungi, bacteria, nematodes, etc. The new technologies allow to redraw the approach for disease control strategies considering the pathogens within their environment and deciphering the complex interactions between microorganisms and the cultivated crops. This kind of analysis usually generates big data that need sophisticated bioinformatic tools (machine learning, artificial intelligence) for their management. Herein, examples of the use of new technologies for research in fungal diversity and diagnosis of some fungal pathogens are reported.

Implementation of GA-VirReport, a Web-Based Bioinformatics Toolkit for Post-Entry Quarantine Screening of Virus and Viroids in Plants

High-throughput sequencing (HTS) of host plant small RNA (sRNA) is a popular approach for plant virus and viroid detection. The major bottlenecks for implementing this approach in routine virus screening of plants in quarantine include lack of computational resources and/or expertise in command-line environments and limited availability of curated plant virus and viroid databases. We developed: (1) virus and viroid report web-based bioinformatics workflows on Galaxy Australia called GA-VirReport and GA-VirReport-Stats for detecting viruses and viroids from host plant sRNA extracts and (2) a curated higher plant virus and viroid database (PVirDB). We implemented sRNA sequencing with unique dual indexing on a set of plants with known viruses. Sequencing data were analyzed using GA-VirReport and PVirDB to validate these resources. We detected all known viruses in this pilot study with no cross-sample contamination. We then conducted a large-scale diagnosis of 105 imported plants processed at the post-entry quarantine facility (PEQ), Australia. We detected various pathogens in 14 imported plants and discovered that de novo assembly using 21–22 nt sRNA fraction and the megablast algorithm yielded better sensitivity and specificity. This study reports the successful, large-scale implementation of HTS and a user-friendly bioinformatics workflow for virus and viroid screening of imported plants at the PEQ.

Modelling cassava production and pest management under biotic and abiotic constraints

We summarise modelling studies of the most economically important cassava diseases and arthropods, highlighting research gaps where modelling can contribute to the better management of these in the areas of surveillance, control, and host-pest dynamics understanding the effects of climate change and future challenges in modelling. For over 30 years, experimental and theoretical studies have sought to better understand the epidemiology of cassava diseases and arthropods that affect production and lead to considerable yield loss, to detect and control them more effectively. In this review, we consider the contribution of modelling studies to that understanding. We summarise studies of the most economically important cassava pests, including cassava mosaic disease, cassava brown streak disease, the cassava mealybug, and the cassava green mite. We focus on conceptual models of system dynamics rather than statistical methods. Through our analysis we identified areas where modelling has contributed and areas where modelling can improve and further contribute. Firstly, we identify research challenges in the modelling developed for the surveillance, detection and control of cassava pests, and propose approaches to overcome these. We then look at the contributions that modelling has accomplished in the understanding of the interaction and dynamics of cassava and its' pests, highlighting success stories and areas where improvement is needed. Thirdly, we look at the possibility that novel modelling applications can achieve to provide insights into the impacts and uncertainties of climate change. Finally, we identify research gaps, challenges, and opportunities where modelling can develop and contribute for the management of cassava pests, highlighting the recent advances in understanding molecular mechanisms of plant defence.

Metatranscriptomic Analysis of Plant Viruses in Imported Pear and Kiwifruit Pollen

Pollen is a vector for viral transmission. Pollen-mediated viruses cause serious economic losses in the fruit industry. Despite the commercial importance of pollen-associated viruses, the diversity of such viruses is yet to be fully explored. In this study, we performed metatranscriptomic analyses using RNA sequencing to investigate the viral diversity in imported apple and kiwifruit pollen. We identified 665 virus-associated contigs, which corresponded to four different virus species. We identified one virus, the apple stem grooving virus, from pear pollen and three viruses, including citrus leaf blotch virus, cucumber mosaic virus, and lychnis mottle virus in kiwifruit pollen. The assembled viral genome sequences were analyzed to determine phylogenetic relationships. These findings will expand our knowledge of the virosphere in fruit pollen and lead to appropriate management of international pollen trade. However, the pathogenic mechanisms of pollen-associated viruses in fruit trees should be further investigated.

Side-by-Side Comparison of Post-Entry Quarantine and High Throughput Sequencing Methods for Virus and Viroid Diagnosis

Rapid and safe access to new plant genetic stocks is crucial for primary plant industries to remain profitable, sustainable, and internationally competitive. Imported plant species may spend several years in Post Entry Quarantine (PEQ) facilities, undergoing pathogen testing which can impact the ability of plant industries to quickly adapt to new global market opportunities by accessing new varieties. Advances in high throughput sequencing (HTS) technologies provide new opportunities for a broad range of fields, including phytosanitary diagnostics. In this study, we compare the performance of two HTS methods (RNA-Seq and sRNA-Seq) with that of existing PEQ molecular assays in detecting and identifying viruses and viroids from various plant commodities. To analyze the data, we tested several bioinformatics tools which rely on different approaches, including direct-read, de novo, and reference-guided assembly. We implemented VirusReport, a new portable, scalable, and reproducible nextflow pipeline that analyses sRNA datasets to detect and identify viruses and viroids. We raise awareness of the need to evaluate cross-sample contamination when analyzing HTS data routinely and of using methods to mitigate index cross-talk. Overall, our results suggest that sRNA analyzed using VirReport provides opportunities to improve quarantine testing at PEQ by detecting all regulated exotic viruses from imported plants in a single assay.

Comparison of High Throughput Sequencing to Standard Protocols for Virus Detection in Berry Crops

We completed a comprehensive study comparing virus detection between high throughput sequencing (HTS) and standard protocols in 30 berry selections (12 Fragaria, 10 Vaccinium, and eight Rubus) with known virus profiles. The study examined temporal detection of viruses at four sampling times encompassing two growing seasons. Within the standard protocols, reverse transcription (RT) PCR proved better than biological indexing. Detection of known viruses by HTS and RT-PCR nearly mirrored each other. HTS provided superior detection compared with RT-PCR on a wide spectrum of variants and discovery of novel viruses. More importantly, in most cases in which the two protocols showed parallel virus detection, 11 viruses in 16 selections were not consistently detected by both methods at all sampling points. Based on these data, we propose a testing requirement of four sampling times over two growing seasons for berry and potentially other crops, to ensure that no virus remains undetected independent of titer, distribution, or other virus-virus or virus-host interactions.

Population genetics of cycas necrotic stunt virus and the development of multiplex RT-PCR diagnostics

Cycas necrotic stunt virus (CNSV) has an extensive host range and is detected in an accelerated pace around the globe in several agricultural crops. One of the plant species affected is peony (Paeonia lactiflora Pall.). The virus is asymptomatic in most peony cultivars, but there have been reports of symptoms in others. It is thus important to study CNSV and its population structure to gain insights into its evolution and epidemiology. The outputs of this study, in addition to the in-depth analysis of the virus population structure, include the development of a multiplex RT-PCR detection protocol that can amplify all published CNSV isolate sequences; allowing for accurate, reliable detection of the virus and safeguarding its susceptible, clonally-propagated hosts.

Virus Diseases of Cereal and Oilseed Crops in Australia: Current Position and Future Challenges

This review summarizes research on virus diseases of cereals and oilseeds in Australia since the 1950s. All viruses known to infect the diverse range of cereal and oilseed crops grown in the continent's temperate, Mediterranean, subtropical and tropical cropping regions are included. Viruses that occur commonly and have potential to cause the greatest seed yield and quality losses are described in detail, focusing on their biology, epidemiology and management. These are: barley yellow dwarf virus, cereal yellow dwarf virus and wheat streak mosaic virus in wheat, barley, oats, triticale and rye; Johnsongrass mosaic virus in sorghum, maize, sweet corn and pearl millet; turnip yellows virus and turnip mosaic virus in canola and Indian mustard; tobacco streak virus in sunflower; and cotton bunchy top virus in cotton. The currently less important viruses covered number nine infecting nine cereal crops and 14 infecting eight oilseed crops (none recorded for rice or linseed). Brief background information on the scope of the Australian cereal and oilseed industries, virus epidemiology and management and yield loss quantification is provided. Major future threats to managing virus diseases effectively include damaging viruses and virus vector species spreading from elsewhere, the increasing spectrum of insecticide resistance in insect and mite vectors, resistance-breaking virus strains, changes in epidemiology, virus and vectors impacts arising from climate instability and extreme weather events, and insufficient industry awareness of virus diseases. The pressing need for more resources to focus on addressing these threats is emphasized and recommendations over future research priorities provided.

Application of Oxford Nanopore Technology to Plant Virus Detection

The adoption of Oxford Nanopore Technologies (ONT) sequencing as a tool in plant virology has been relatively slow despite its promise in more recent years to yield large quantities of long nucleotide sequences in real time without the need for prior amplification. The portability of the MinION and Flongle platforms combined with lowering costs and continued improvements in read accuracy make ONT an attractive method for both low- and high-scale virus diagnostics. Here, we provide a detailed step-by-step protocol using the ONT Flongle platform that we have developed for the routine application on a range of symptomatic post-entry quarantine and domestic surveillance plant samples. The aim of this methods paper is to highlight ONT’s feasibility as a valuable component to the diagnostician’s toolkit and to hopefully stimulate other laboratories towards the eventual goal of integrating high-throughput sequencing technologies as validated plant virus diagnostic methods in their own right.

Metagenomic Analysis of Marigold: Mixed Infection Including Two New Viruses

Marigold plants with symptoms of mosaic, crinkle, leaf curl and necrosis were observed and small RNA and ribo-depleted total RNA deep sequencing were conducted to identify the associated viruses. Broad bean wilt virus 2, cucumber mosaic virus, turnip mosaic virus, a new potyvirus tentatively named marigold mosaic virus (MMV) and a new partitivirus named as marigold cryptic virus (MCV) were finally identified. Complete genome sequence analysis showed MMV was 9811 nt in length, encoding a large polyprotein with highest aa sequence identity (57%) with the putative potyvirus polygonatumkingianum virus 1. Phylogenetic analysis with the definite potyviruses based on the polyprotein sequence showed MMV clustered closest to plum pox virus. The complete genome of MCV comprised of dsRNA1 (1583 bp) and dsRNA2 (1459 bp), encoding the RNA-dependent RNA polymerase (RdRp), and coat protein (CP), respectively. MCV RdRp shared the highest (75.7%) aa sequence identity with the unclassified partitivirus ambrosia cryptic virus 2, and 59.0%, 57.1%, 56.1%, 54.5% and 33.7% with the corresponding region of the definite delta-partitiviruses, pepper cryptic virus 2, beet cryptic virus 3, beet cryptic virus 2, pepper cryptic virus 1 and fig cryptic virus, respectively. Phylogenetic analysis based on the RdRp aa sequence showed MCV clustered into the delta-partitivirus group. These findings enriched our knowledge of viruses infecting marigold, but the association of the observed symptom and the identified viruses and the biological characterization of the new viruses should be further investigated.

Quality Assessment and Validation of High-Throughput Sequencing for Grapevine Virus Diagnostics

Development of High-Throughput Sequencing (HTS), also known as next generation sequencing, revolutionized diagnostic research of plant viruses. HTS outperforms bioassays and molecular diagnostic assays that are used to screen domestic and quarantine grapevine materials in data throughput, cost, scalability, and detection of novel and highly variant virus species. However, before HTS-based assays can be routinely used for plant virus diagnostics, performance specifications need to be developed and assessed. In this study, we selected 18 virus-infected grapevines as a test panel for measuring performance characteristics of an HTS-based diagnostic assay. Total nucleic acid (TNA) was extracted from petioles and dormant canes of individual samples and constructed libraries were run on Illumina NextSeq 500 instrument using a 75-bp single-end read platform. Sensitivity was 98% measured over 264 distinct virus and viroid infections with a false discovery rate (FDR) of approximately 1 in 5 positives. The results also showed that combining a spring petiole test with a fall cane test increased sensitivity to 100% for this TNA HTS assay. To evaluate extraction methodology, these results were compared to parallel dsRNA extractions. In addition, in a more detailed dilution study, the TNA HTS assay described here consistently performed well down to a dilution of 5%. In that range, sensitivity was 98% with a corresponding FDR of approximately 1 in 5. Repeatability and reproducibility were assessed at 99% and 93%, respectively. The protocol, criteria, and performance levels described here may help to standardize HTS for quality assurance and accreditation purposes in plant quarantine or certification programs.

The population structure of the secovirid lychnis mottle virus based on the RNA2 coding sequences

Lychnis mottle virus (LycMoV), family Secoviridae, is one of several viruses recently detected in peony. Given the high prevalence of the virus in the more than 300 samples tested, the population structure of the virus was studied using 48 isolates representing at least 20 cultivars and collected from major producing and propagating states in the United States. The homogeneity of the United States population, based on data from the RNA2 coding region, along with phylogenetic analyses of all publicly available sequences point to the dissemination of the virus through propagation material rather that active vector-mediated transmission.

Sixty Years from the First Disease Description, a Novel Badnavirus Associated with Chestnut Mosaic Disease

Although chestnut mosaic disease (ChMD) was described several decades ago, its etiology is still not clear. Using classical approaches and high-throughput sequencing (HTS) techniques, we identified a novel Badnavirus that is a strong etiological candidate for ChMD. Two disease sources from Italy and France were submitted to HTS-based viral indexing. Total RNAs were extracted, ribodepleted, and sequenced on an Illumina NextSeq500 (2 × 150 nt or 2 × 75 nt). In each source, we identified a single contig of ≈7.2 kb that corresponds to a complete circular viral genome and shares homologies with various badnaviruses. The genomes of the two isolates have an average nucleotide identity of 90.5%, with a typical badnaviral genome organization comprising three open reading frames. Phylogenetic analyses and sequence comparisons showed that this virus is a novel species; we propose the name Chestnut mosaic virus (ChMV). Using a newly developed molecular detection test, we systematically detected the virus in symptomatic graft-inoculated indicator plants (chestnut and American oak) as well in chestnut trees presenting typical ChMD symptoms in the field (100 and 87% in France and Italy surveys, respectively). Datamining of publicly available chestnut sequence read archive transcriptomic data allowed the reconstruction of two additional complete ChMV genomes from two Castanea mollissima sources from the United States as well as ChMV detection in C. dentata from the United States. Preliminary epidemiological studies performed in France and central eastern Italy showed that ChMV has a high incidence in some commercial orchards and low within-orchard genetic diversity.

Comparison of the Virome of Quarantined Sugarcane Varieties and the Virome of Grasses Growing near the Quarantine Station

Visacane is a sugarcane quarantine station located in the South of France, far away from sugarcane growing areas. Visacane imports up to 100 sugarcane varieties per year, using safe control and confinement measures of plants and their wastes to prevent any risk of pathogen spread outside of the facilities. Viruses hosted by the imported material are either known or unknown to cause disease in cultivated sugarcane. Poaceae viruses occurring in plants surrounding the quarantine glasshouse are currently unknown. These viruses could be considered as a source of new sugarcane infections and potentially cause new sugarcane diseases in cases of confinement barrier failure. The aim of this study was to compare the plant virome inside and outside of the quarantine station to identify potential confinement failures and risks of cross infections. Leaves from quarantined sugarcane varieties and from wild Poaceae growing near the quarantine were collected and processed by a metagenomics approach based on virion-associated nucleic acids extraction and library preparation for Illumina sequencing. While viruses belonging to the same virus genus or family were identified in the sugarcane quarantine and its surroundings, no virus species was detected in both environments. Based on the data obtained in this study, no virus movement between quarantined sugarcane and nearby grassland has occurred so far, and the confinement procedures of Visacane appear to be properly implemented.

High-Throughput Sequencing Indicates Novel Varicosavirus, Emaravirus, and Deltapartitivirus Infections in Vitis coignetiae

Vitis coignetiae samples were collected from several locations in the northern area of Japan, and virome analysis using a high-throughput sequencing technique was performed. The data indicated that some of the collected samples were in mixed infections by various RNA viruses. Among these viruses, three were identified as newly recognized species with support of sequence identity and phylogenetic analysis. The viruses have been provisionally named the Vitis varicosavirus, Vitis emaravirus, and Vitis crypticvirus, and were assigned to the genus Varicosavirus, Emaravirus, and Deltapartitivirus, respectively.

Comparison of qPCR and Metabarcoding Methods as Tools for the Detection of Airborne Inoculum of Forest Fungal Pathogens

Forest diseases caused by invasive fungal pathogens are becoming more common, sometimes with dramatic consequences to forest ecosystems. The development of early detection systems is necessary for efficient surveillance and to mitigate the impact of invasive pathogens. Windborne spores are an important pathway for introduction of fungal pathogens into new areas; the design of spore trapping devices adapted to forests, capable of collecting different types of spores, and aligned with development of efficient molecular methods for detection of the pathogen, should help forest managers anticipate new disease outbreaks. Two types of Rotorod samplers were evaluated for the collection of airborne inoculum of forest fungal pathogens with a range of spore sizes in five forest types. Detection was by specific quantitative PCR (qPCR) and by high-throughput sequencing (HTS) of amplified internal transcribed spacer sequences using a new bioinformatic pipeline, FungiSearch, developed for diagnostic purposes. Validation of the pipeline was conducted on mock communities of 10 fungal species belonging to different taxa. Although the sensitivity of the new HTS pipeline was lower than the specific qPCR, it was able to detect a wide variety of fungal pathogens. FungiSearch is easy to use, and the reference database is updatable, making the tool suitable for rapid identification of new pathogens. This new approach combining spore trapping and HTS detection is promising as a diagnostic tool for invasive fungal pathogens.

Improved multiplex TaqMan qPCR assay with universal internal control offers reliable and accurate detection of Clavibacter michiganensis

AIM

Clavibacter michiganensis (Cm) is a seed-borne plant pathogen that significantly reduces tomato production worldwide. Due to repeated outbreaks and rapid spread of the disease, seeds/transplants need to be certified free of the pathogen before planting. To this end, we developed a multiplex TaqMan qPCR assay that can accurately detect Cm in infected samples.

METHODS AND RESULTS

A specific region of Cm (clvG gene) was selected for primer design using comparative genomics approach. A fully synthetic universal internal control (UIC) was also designed to detect PCR inhibitors and false-negative results in qPCRs. The Cm primers can be used alone or in a triplex TaqMan qPCR assay with UIC and previously described Clavibacter primers. The assay was specific for Cm and detected up to 10 fg of Cm DNA in sensitivity and spiked assays. Addition of the UIC did not change the specificity or sensitivity of the multiplex TaqMan qPCR assay.

CONCLUSION

The triplex TaqMan qPCR provides a specific and sensitive diagnostic assay for Cm.

SIGNIFICANCE AND IMPACT OF THE STUDY

This assay can be used for biosecurity surveillance, routine diagnostics, estimating bacterial titres in infected material and for epidemiological studies. The UIC is fully synthetic, efficiently amplified and multiplex compatible with any other qPCR assay.

Virus Pathogens in Australian Vineyards with an Emphasis on Shiraz Disease

Grapevine viruses are found throughout the viticultural world and have detrimental effects on vine productivity and grape and wine quality. This report provides a comprehensive and up-to-date review on grapevine viruses in Australia with a focus on “Shiraz Disease” (SD) and its two major associated viruses, grapevine virus A (GVA) and grapevine leafroll-associated virus 3 (GLRaV-3). Sensitive grapevine cultivars like Shiraz infected with GVA alone or with a co-infection of a leafroll virus, primarily GLRaV-3, show symptoms of SD leading to significant yield and quality reductions in Australia and in South Africa. Symptom descriptors for SD will be outlined and a phylogenetic tree will be presented indicating the SD-associated isolates of GVA in both countries belong to the same clade. Virus transmission, which occurs through infected propagation material, grafting, and naturally vectored by mealybugs and scale insects, will be discussed. Laboratory and field-based indexing will also be discussed along with management strategies including rogueing and replanting certified stock that decrease the incidence and spread of SD. Finally, we present several cases of SD incidence in South Australian vineyards and their effects on vine productivity. We conclude by offering strategies for virus detection and management that can be adopted by viticulturists. Novel technologies such as high throughput sequencing and remote sensing for virus detection will be outlined.

Comparative analysis uncovers the limitations of current molecular detection methods for Fusarium oxysporum f. sp. cubense race 4 strains

Fusarium oxysporum f. sp. cubense Tropical Race 4 (Foc TR4) is threatening banana production worldwide. Despite quarantine efforts, the pathogen continues to spread; thus, early diagnosis plays an essential role for the proper execution of contingency plans. Here, we assess the accuracy of four PCR-based molecular methods described in the literature for the identification and detection of race 4 strains, including Subtropical (Foc STR4) and Tropical Race 4 causing Fusarium wilt of banana. We screened a total of 302 isolates using these four markers, and performed phylogenetic analyses, Vegetative Compatibility Group (VCG) testing, sequence comparison, and pathogenicity tests for selected isolates. Our results show that three out of the four markers tested are not reliable for identification of Foc STR4 and TR4, as DNA from isolates from Ecuador, pathogenic and nonpathogenic to banana, obtained from different banana cultivars, displayed cross-reaction with these methods; that is, false positives can occur during the diagnostic process for race 4. Phylogenetic analyses, VCG testing, sequence comparison, and pathogenicity tests suggest the presence of non-target F. oxysporum isolates that share genomic regions with pathogenic strains but lack true pathogenicity to banana. The findings of this work are of foremost importance for international regulatory agencies performing surveillance tests in pathogen-free areas using the current diagnostic methods. We suggest the use of a genetic locus possibly related to virulence, previously identified by T-DNA, and amplified with primers W2987F/ W2987R, for diagnosis of Foc TR4 as the most reliable alternative. We urge the adoption of a more holistic view in the study of F. oxysporum as a plant pathogen that considers the biology and diversity of the species for the development of better diagnostic tools.

Prospects and challenges of implementing DNA metabarcoding for high-throughput insect surveillance

Trap-based surveillance strategies are widely used for monitoring of invasive insect species, aiming to detect newly arrived exotic taxa as well as track the population levels of established or endemic pests. Where these surveillance traps have low specificity and capture non-target endemic species in excess of the target pests, the need for extensive specimen sorting and identification creates a major diagnostic bottleneck. While the recent development of standardized molecular diagnostics has partly alleviated this requirement, the single specimen per reaction nature of these methods does not readily scale to the sheer number of insects trapped in surveillance programmes. Consequently, target lists are often restricted to a few high-priority pests, allowing unanticipated species to avoid detection and potentially establish populations. DNA metabarcoding has recently emerged as a method for conducting simultaneous, multi-species identification of complex mixed communities and may lend itself ideally to rapid diagnostics of bulk insect trap samples. Moreover, the high-throughput nature of recent sequencing platforms could enable the multiplexing of hundreds of diverse trap samples on a single flow cell, thereby providing the means to dramatically scale up insect surveillance in terms of both the quantity of traps that can be processed concurrently and number of pest species that can be targeted. In this review of the metabarcoding literature, we explore how DNA metabarcoding could be tailored to the detection of invasive insects in a surveillance context and highlight the unique technical and regulatory challenges that must be considered when implementing high-throughput sequencing technologies into sensitive diagnostic applications.

Forewarned is forearmed: harmonized approaches for early detection of potentially invasive pests and pathogens in sentinel plantings

The number of invasive alien pest and pathogen species affecting ecosystem functioning, human health and economies has increased dramatically over the last decades. Discoveries of invasive pests and pathogens previously unknown to science or with unknown host associations yet damaging on novel hosts highlights the necessity of developing novel tools to predict their appearance in hitherto naïve environments. The use of sentinel plant systems is a promising tool to improve the detection of pests and pathogens before introduction and to provide valuable information for the development of preventative measures to minimize economic or environmental impacts. Though sentinel plantings have been established and studied during the last decade, there still remains a great need for guidance on which tools and protocols to put into practice in order to make assessments accurate and reliable. The sampling and diagnostic protocols chosen should enable as much information as possible about potential damaging agents and species identification. Consistency and comparison of results are based on the adoption of common procedures for sampling design and sample processing. In this paper, we suggest harmonized procedures that should be used in sentinel planting surveys for effective sampling and identification of potential pests and pathogens. We also review the benefits and limitations of various diagnostic methods for early detection in sentinel systems, and the feasibility of the results obtained supporting National Plant Protection Organizations in pest and commodity risk analysis.

High Throughput Sequencing For Plant Virus Detection and Discovery

Over the last decade, virologists have discovered an unprecedented number of viruses using high throughput sequencing (HTS), which led to the advancement of our knowledge on the diversity of viruses in nature, particularly unraveling the virome of many agricultural crops. However, these new virus discoveries have often widened the gaps in our understanding of virus biology; the forefront of which is the actual role of a new virus in disease, if any. Yet, when used critically in etiological studies, HTS is a powerful tool to establish disease causality between the virus and its host. Conversely, with globalization, movement of plant material is increasingly more common and often a point of dispute between countries. HTS could potentially resolve these issues given its capacity to detect and discover. Although many pipelines are available for plant virus discovery, all share a common backbone. A description of the process of plant virus detection and discovery from HTS data are presented, providing a summary of the different pipelines available for scientists' utility in their research.

Recent Advances on the Multiplex Molecular Detection of Plant Viruses and Viroids

Plant viruses are still one of the main contributors to economic losses in agriculture. It has been estimated that plant viruses can cause as much as 50 billion euros loss worldwide, per year. This situation may be worsened by recent climate change events and the associated changes in disease epidemiology. Reliable and early detection methods are still one of the main and most effective actions to develop control strategies for plant viral diseases. During the last years, considerable progress has been made to develop tools with high specificity and low detection limits for use in the detection of these plant pathogens. Time and cost reductions have been some of the main objectives pursued during the last few years as these increase their feasibility for routine use. Among other strategies, these objectives can be achieved by the simultaneous detection and (or) identification of several viruses in a single assay. Nucleic acid-based detection techniques are especially suitable for this purpose. Polyvalent detection has allowed the detection of multiple plant viruses at the genus level. Multiplexing RT polymerase chain reaction (PCR) has been optimized for the simultaneous detection of more than 10 plant viruses/viroids. In this short review, we provide an update on the progress made during the last decade on techniques such as multiplex PCR, polyvalent PCR, non-isotopic molecular hybridization techniques, real-time PCR, and array technologies to allow simultaneous detection of multiple plant viruses. Also, the potential and benefits of the powerful new technique of deep sequencing/next-generation sequencing are described.

High Risk Blueberry Viruses by Region in North America; Implications for Certification, Nurseries, and Fruit Production

There is limited information on the distribution of blueberry viruses in the U.S. or around the world other than where the viruses were first discovered and characterized. A survey for blueberry viruses was carried out in the U.S. in 2015⁻2017. Most blueberry viruses have been characterized to the point that sensitive diagnostic assays have been developed. These assays are based on ELISA or variations of PCR, which were employed here to determine the presence of blueberry viruses in major blueberry production and nursery areas of the U.S. The viruses included in this study were: blueberry fruit drop (BFDaV), blueberry latent (BlLV), blueberry leaf mottle (BLMoV), blueberry mosaic (BlMaV), blueberry red ringspot (BRRV), blueberry scorch (BlScV), blueberry shock (BlShV), blueberry shoestring (BlSSV), blueberry virus A (BVA), peach rosette mosaic (PRMV), tobacco ringspot (TRSV), and tomato ringspot (ToRSV). In the Pacific Northwest BlShV was the most widespread virus, with BlScV and ToRSV detected in a limited number of fields in Oregon and Washington, but BlScV was widespread in British Columbia. In the upper midwest, the nematode-borne (ToRSV, TRSV), aphid-transmitted (BlSSV and BVA) and pollen-borne (BLMoV) viruses were most widespread. In the northeast, TRSV, ToRSV, and BlScV, were detected most frequently. In the southeast, BRRV and BNRBV were the most widespread viruses. BlLV, a cryptic virus with no known symptoms or effect on plant growth or yield was present in all regions. There are other viruses present at low levels in each of the areas, but with the lower incidence they pose minimal threat to nursery systems or fruit production. These results indicate that there are hotspots for individual virus groups that normally coincide with the presence of the vectors. The information presented highlights the high risk viruses for nursery and fruit production each pose a different challenge for control.

Application of Next Generation Sequencing for Diagnostic Testing of Tree Fruit Viruses and Viroids

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.

Plant viruses and viroids in the United Kingdom: An analysis of first detections and novel discoveries from 1980 to 2014

This review covers 35 years (1980-2014) representing a period of changing land use and agricultural practices in the United Kingdom (UK), which have also witnessed a marked change in the availability and application of new diagnostic technologies. During this period there have been 53 first records of viruses and viroids, of which 36 were first UK findings and a further 17 previously undescribed viruses. Given the challenges in detection and diagnosis of plant viruses, the field of plant virology has been an early adopter of new diagnostic technologies and these data highlight the transition from a reliance on biological, morphological, and serological based identification to the increased application of nucleic acid based detection methods and latterly the emergence of Next-Generation Sequencing. This review presents a comprehensive record of these findings and an analysis of how the potential drivers of change such as commodity based research, trade, as well as the application of diagnostic technology, could have influenced the frequency and type of findings.

Generic Amplicon Deep Sequencing to Determine Ilarvirus Species Diversity in Australian Prunus

The distribution of Ilarvirus species populations amongst 61 Australian Prunus trees was determined by next generation sequencing (NGS) of amplicons generated using a genus-based generic RT-PCR targeting a conserved region of the Ilarvirus RNA2 component that encodes the RNA dependent RNA polymerase (RdRp) gene. Presence of Ilarvirus sequences in each positive sample was further validated by Sanger sequencing of cloned amplicons of regions of each of RNA1, RNA2 and/or RNA3 that were generated by species specific PCRs and by metagenomic NGS. Prunus necrotic ringspot virus (PNRSV) was the most frequently detected Ilarvirus, occurring in 48 of the 61 Ilarvirus-positive trees and Prune dwarf virus (PDV) and Apple mosaic virus (ApMV) were detected in three trees and one tree, respectively. American plum line pattern virus (APLPV) was detected in three trees and represents the first report of APLPV detection in Australia. Two novel and distinct groups of Ilarvirus-like RNA2 amplicon sequences were also identified in several trees by the generic amplicon NGS approach. The high read depth from the amplicon NGS of the generic PCR products allowed the detection of distinct RNA2 RdRp sequence variant populations of PNRSV, PDV, ApMV, APLPV and the two novel Ilarvirus-like sequences. Mixed infections of ilarviruses were also detected in seven Prunus trees. Sanger sequencing of specific RNA1, RNA2, and/or RNA3 genome segments of each virus and total nucleic acid metagenomics NGS confirmed the presence of PNRSV, PDV, ApMV and APLPV detected by RNA2 generic amplicon NGS. However, the two novel groups of Ilarvirus-like RNA2 amplicon sequences detected by the generic amplicon NGS could not be associated to the presence of sequence from RNA1 or RNA3 genome segments or full Ilarvirus genomes, and their origin is unclear. This work highlights the sensitivity of genus-specific amplicon NGS in detection of virus sequences and their distinct populations in multiple samples, and the need for a standardized approach to accurately determine what constitutes an active, viable virus infection after detection by molecular based methods.

Sequencing viral siRNAs to identify previously undescribed viruses and viroids in a panel of ornamental plant samples structured as a matrix of pools

Ornamental plants constitute a largely unknown and potentially important source of pathogens affecting not only ornamental plants, but also major crop species. We have carried out studies using high-throughput sequencing of 21-24 nt RNAs from potentially virus-infected ornamental plants, followed by assembly of sequence scaffolds, to identify the virus and viroid genomes present in a panel of 67 plant samples representing 46 species belonging to the main sectors of the ornamental plant industry (cut flowers, pot plants, bulbs). A pilot study demonstrated that samples could be pooled (5 samples per pool), and the overall process simplified without loss of detection of important known pathogens. In a full-scale study, pools of 5 samples were organized in a 5×5 matrix to facilitate attribution of a sequence to a precise sample directly from analysis of the matrix. In the total of 67 samples analyzed in the two studies, partial sequences suggesting the presence of 25 previously unknown viruses and viroids were detected, including all types of virus and viroid genomes, and also showed four cases of known viruses infecting previously undescribed hosts. Furthermore, two types of potential mis-assembly were analyzed, and were shown to not affect the conclusions regarding the presence of the pathogens identified, but show that mis-assembly can affect the results when the objective is determining complete bona fide viral genome sequences. These results clearly confirm that ornamental plants constitute a potential source of unknown viruses and viroids that could have a major impact on agriculture, and that sequencing siRNAs of potentially virus- or viroid-infected ornamental plants is an effective means for screening for the presence of potentially important pathogens.

A Framework for the Evaluation of Biosecurity, Commercial, Regulatory, and Scientific Impacts of Plant Viruses and Viroids Identified by NGS Technologies

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.