A historic Prunus salicina accession (Ptitsin #10), maintained for decades at the Canadian Food Inspection Agency, consistently produced gummosis, bark splitting, and dieback on indicator cultivars despite testing negative for all known Prunus viruses. High throughput sequencing of symptomatic and asymptomatic graft inoculated trees identified a previously undescribed virus. Genome analysis revealed three open reading frames characteristic of family Caulimoviridae and conserved domains including coat protein, aspartic protease, reverse transcriptase, and RNase H. Phylogenetic analysis placed the virus within genus Badnavirus, group 1, subgroup 1b with less than 80% amino acid identity in the RT/RNase H region relative to closest relatives Green Sichuan pepper vein clearing associated virus, Badnavirus venazanthoxyli, Grapevine vein clearing virus and Badnavirus venavitis, which support its designation as a novel species. Tentatively named prunus gummosis bark splitting virus, Badnavirus prunumosis, this newly discovered virus is graft transmissible, induces severe symptoms in certain cultivars, and remains latent in others. Prunus gummosis bark splitting virus to our knowledge represents the first documented badnavirus infecting Prunus, underscoring the importance of long term surveillance in germplasm collections.

Commercially cultivated Prunus species are commonly grown in adjacent or mixed orchards and can be infected with unique or commonly shared viruses. Apple (Malus domestica), another member of the Rosacea and distantly related to Prunus, can share the same growing regions and common pathogens. Pollen can be a major route for virus transmission, and analysis of the pollen virome in tree fruit orchards can provide insights into these virus pathogen complexes from mixed production sites. Commercial honey bee (Apis mellifera) pollination is essential for improved fruit sets and yields in tree fruit production systems. To better understand the pollen-associated virome in tree fruits, metagenomics-based detection of plant viruses was employed on bee and pollen samples collected at four time points during the peak bloom period of apricot, cherry, peach, and apple trees at one orchard site. Twenty-one unique viruses were detected in samples collected during tree fruit blooms, including prune dwarf virus (PDV) and prunus necrotic ringspot virus (PNRSV) (Genus Ilarvirus, family Bromoviridae), Secoviridae family members tomato ringspot virus (genus Nepovirus), tobacco ringspot virus (genus Nepovirus), prunus virus F (genus Fabavirus), and Betaflexiviridae family member cherry virus A (CVA; genus Capillovirus). Viruses were also identified in composite leaf and flower samples to compare the pollen virome with the virome associated with vegetative tissues. At all four time points, a greater diversity of viruses was detected in the bee and pollen samples. Finally, the nucleotide sequence diversity of the coat protein regions of CVA, PDV, and PNRSV was profiled from this site, demonstrating a wide range of sequence diversity in pollen samples from this site. These results demonstrate the benefits of area-wide monitoring through bee pollination activities and provide new insights into the diversity of viruses in tree fruit pollination ecosystems.

Plant viral infections cause significant economic losses, totalling $350 billion USD in 2021. With no treatment for virus-infected plants, accurate and efficient diagnosis is crucial to preventing and controlling these diseases. High-throughput sequencing (HTS) enables cost-efficient identification of known and unknown viruses. However, existing diagnostic pipelines face challenges. First, many methods depend on subjectively chosen parameter values, undermining their robustness across various data sources. Second, artifacts (e.g. false peaks) in the mapped sequence data can lead to incorrect diagnostic results. While some methods require manual or subjective verification to address these artifacts, others overlook them entirely, affecting the overall method performance and leading to imprecise or labour-intensive outcomes. To address these challenges, we introduce IIMI, a new automated analysis pipeline using machine learning to diagnose infections from 1583 plant viruses with HTS data. It adopts a data-driven approach for parameter selection, reducing subjectivity, and automatically filters out regions affected by artifacts, thus improving accuracy. Testing with in-house and published data shows IIMI's superiority over existing methods. Besides a prediction model, IIMI also provides resources on plant virus genomes, including annotations of regions prone to artifacts. The method is available as an R package (iimi) on CRAN and will integrate with the web application www.virtool.ca, enhancing accessibility and user convenience.

The extraction of double stranded (ds) RNA is a common enrichment method for the study, characterization, and detection of RNA viruses. In addition to RNA viruses, viroids, and some DNA viruses, can also be detected from dsRNA enriched extracts which makes it an attractive method for detecting a wide range of viruses when coupled with HTS. Several dsRNA enrichment strategies have been developed. The oldest utilizes the selective binding properties of dsRNA to cellulose. More recent methods are based on the application of anti-dsRNA antibodies and viral proteins with a specific affinity for dsRNA. All three methods have been used together with HTS for plant virus detection and study. To our knowledge, this is the first comparative study of three alternative dsRNA enrichment methods for virus and viroid detection through HTS using virus-infected, and healthy grapevine test plants. Extracts were performed in triplicate using methods based on, the anti-dsRNA antibody mAb rJ2 (Millipore Sigma Canada Ltd, Oakville, ON, Canada), the B2 dsRNA binding protein, and ReliaPrep™ Resin (Promega Corporation, Madison, WI, USA). The results show that the workflows for all three methods are effectively comparable, apart from purification steps related to antibody and binding protein construct. Both the cellulose resin and dsRNA binding protein construct methods provide highly enriched dsRNA extracts suitable for HTS with the B2 method providing a 36× and the ReliaPrep™ Resin a 163× increase in dsRNA enrichment compared to the mAb rJ2 antibody. The overall consistency and cost effectiveness of the ReliaPrep™ cellulose resin-based method and the potentially simpler adaptation to robotics made it the method of choice for future transfer to a semi-automated workflow.

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.

Monitoring the environment for pollution, pesticides, and pathogens is crucial for protecting human, agriculture, and overall ecosystem health. Diverse strategies ranging from physical sensors to sentinel species have been used for environmental monitoring. The European honey bee, Apis mellifera, is a globally managed pollinator that can serve as a continuous biomonitoring species. During foraging, honey bees are exposed to contaminants and pathogens and carry them to their hives where they can be detected and quantified. Although individual bees are vulnerable to environmental stressors, the honey bee colony as a whole is more resilient and can accumulate contaminants or respond to them without collapsing. This allows for long-term monitoring of the colony to map contaminants in a geographical area and study ecotoxicology gradients over space and time. In this paper, we review demonstrated and proposed uses of honey bees for environmental monitoring. We focus our discussion on heavy metals, air pollutants, pesticides, and plant pathogens that can be detected in bees and their hive materials including honey, wax, and stored pollen. We present the use of gene expression, microbiome profiling, and other high-throughput methodologies to study dose-dependent exposure and increase detection sensitivity; for example, stored pollen analysis with next generation sequencing can reveal the presence of plant viruses, fungi, and invasive species earlier than traditional detection methods. Finally, we discuss opportunities for using honey bees to monitor emerging threats such as climate change and antimicrobial resistance. This narrative review highlights the versatility and potential utility of the European honey bee as a biomonitoring species for ecosystem health.

Apple rubbery wood is a disease of apple found around the world, often associated with Apple flat limb disease, and regulated in many countries. Despite its long history in apple cultivation, the disease's causal agent has remained elusive. In this study, next-generation sequencing (NGS) was used to identify and characterize several related novel viral agents from apple rubbery wood-infected plants, which have been named Apple rubbery wood virus (ARWV) 1 and 2. Additional specimens with apple rubbery wood disease tested positive by polymerase chain reaction with primers designed to ARWV 1 and 2 genomic RNA segments. In an NGS-based screening of over 100 Malus and 100 Prunus specimens from a collection of virus-infected trees, only one Malus specimen was found to be infected with ARWV not known to be infected with the disease, which strongly suggests that ARWV is not commonly found in Malus spp. or other fruit trees. The two viruses are most closely related to members of the order Bunyavirales. Three RNA segments (large, medium, and small) were characterized and the viruses likely represent a new genus under the family Phenuiviridae, with a suggested name of Rubodvirus (Rubbery wood virus).

Cherry virus A (CVA) is a ubiquitous graft-transmissible virus that mainly infects Prunus spp. Next-generation sequencing was applied to 39 tree fruit specimens infected with CVA, and 75 full and 16 partial-length CVA genome sequences were assembled. Phylogenetic analysis of these and 11 previously sequenced CVA genomes resulted in six major clusters with no observable relationship between the host and the assembled genome sequences. Recombination analysis detected four recombinants. Consistent single-nucleotide polymorphism (SNP) patterns were observed between the 75 full-length genomes and their sequence clouds, which supports a quasispecies model for CVA evolution.

Genes acquired via HGT in other cyst and root-knot nematodes also found in the genome of G. rostochiensis. (XLSX 21 kb)

The majority of plant viruses contain RNA genomes. Detection of viral RNA genomes in infected plant material by next generation sequencing (NGS) is possible through the extraction and sequencing of total RNA, total RNA devoid of ribosomal RNA, small RNA interference (RNAi) molecules, or double stranded RNA (dsRNA). Plants do not typically produce high molecular weight dsRNA, therefore the presence of dsRNA makes it an attractive target for plant virus diagnostics. The sensitivity of NGS as a diagnostic method demands an effective dsRNA protocol that is both representative of the sample and minimizes sample cross contamination. We have developed a modified dsRNA extraction protocol that is more efficient compared to traditional protocols, requiring reduced amounts of starting material, that is less prone to sample cross contamination. This was accomplished by using bead based homogenization of plant material in closed, disposable 50ml tubes. To assess the quality of extraction, we also developed an internal control by designing a real-time (quantitative) PCR (qPCR) assay that targets endornaviruses present in Phaseolus vulgaris cultivar Black Turtle Soup (BTS).

Background: The yellow potato cyst nematode, Globodera rostochiensis, is a devastating plant pathogen of global economic importance. This biotrophic parasite secretes effectors from pharyngeal glands, some of which were acquired by horizontal gene transfer, to manipulate host processes and promote parasitism. G. rostochiensis is classified into pathotypes with different plant resistance-breaking phenotypes.Results: We generate a high quality genome assembly for G. rostochiensis pathotype Ro1, identify putative effectors and horizontal gene transfer events, map gene expression through the life cycle focusing on key parasitic transitions and sequence the genomes of eight populations including four additional pathotypes to identify variation. Horizontal gene transfer contributes 3.5 % of the predicted genes, of which approximately 8.5 % are deployed as effectors. Over one-third of all effector genes are clustered in 21 putative 'effector islands' in the genome. We identify a dorsal gland promoter element motif (termed DOG Box) present upstream in representatives from 26 out of 28 dorsal gland effector families, and predict a putative effector superset associated with this motif. We validate gland cell expression in two novel genes by in situ hybridisation and catalogue dorsal gland promoter element-containing effectors from available cyst nematode genomes. Comparison of effector diversity between pathotypes highlights correlation with plant resistance-breaking.Conclusions: These G. rostochiensis genome resources will facilitate major advances in understanding nematode plant-parasitism. Dorsal gland promoter element-containing effectors are at the front line of the evolutionary arms race between plant and parasite and the ability to predict gland cell expression a priori promises rapid advances in understanding their roles and mechanisms of action.

The genome sequence of tomato ringspot virus (ToRSV, a subgroup C nepovirus) is currently available for one raspberry isolate. In this study, we describe the complete genome sequence of three additional isolates from raspberry (Rasp1-2014), grapevine (GYV-2014) and prunus (13C280). The degree of nucleotide sequence identity shared between RNA1 and RNA2 in the 5′-terminal 900 nucleotides and 3′ untranslated region varied from 98-99 % (13C280, GYV-2014) to 80 % (Rasp1-2014). Phylogenetic studies revealed distinct origins for Rasp1-2014 RNA1 and RNA2, suggesting reassortment. Two recombination events were also identified in the 3′ UTR and 5′-terminal region of RNA1.

Summary Pinewood nematode, Bursaphelenchus xylophilus, is an inhabitant of native pine species of North America, where its presence in trees is non‐pathogenic. By contrast, the introduction of this nematode to forests overseas has devastated some pine stands and is recognized as a pest of phytosanitary concern by some countries' National Plant Protection Organizations. The ability to detect B. xylophilus in internationally traded wood products is crucial to reduce the spread of this organism. Current molecular techniques for the detection of B. xylophilus rely on the presence of genomic DNA and thus will detect both living and dead nematodes without differentiation. The detection of dead nematodes could lead to unnecessary trade disruption. Therefore, accurate techniques for the detection of and differentiation between live and dead B. xylophilus are critical. We have developed an endpoint RT ‐ PCR assay and a SYBR Green 1 real‐time RT‐PCR assay, both of which selectively identify living pinewood nematode by detecting the presence of H sp70 mRNA as a viability marker. Both of these assays may help overcome or resolve disputes involving the detection of pinewood nematode at the port of entry and can also be used to evaluate the efficiency of wood treatment procedures.

Springer-Verlag 2011 Abstract The complete nucleotide sequence of an Albanian isolate of grapevine leafroll-associated virus 7 (GLRaV-7-Alb) was determined. The viral genome con- sists 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 Closteroviri- dae. 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

A single-colour microarray hybridization system was designed and evaluated for the detection of viruses infecting grapevine. Total RNA (≥0.5μg) from infected plants was converted to cDNA and labelled with Cy3 using two different strategies. While amine-modified and labelled cDNA was adequate for the detection of nepoviruses, the 3DNA technique, a post-hybridization detection method that uses intensely fluorescent dendrimer reagents, was required for the detection of closteroviruses in infected plants. Threshold detection levels were based on the ratio between viral specific and 18S rRNA positive control signal intensities. Oligonucleotides between 27 and 75 nucleotides in length were evaluated and compared. Viruses detected include eight nepoviruses, two vitiviruses, and one each of closterovirus, foveavirus, ampelovirus, maculavirus and sadwavirus. Results of this work demonstrate the potential of microarray technique to detect viral pathogens without sequence bias amplification of template RNA.

Two Canadian isolates of the potato cyst nematode (PCN), Globodera rostochiensis pathotype Ro1, were evaluated for their ability to replicate on several species of nightshade. Nightshade is commonly found in potato-growing fields and can potentially act as an alternative host, thereby interfering with eradication/control measures for PCN. Accessions of Solanum carolinense, S. americanum, S. dulcamara, S. ptychanthum, S. rostratum, S. sarrachoides, S. sisymbriifolium, S physalifolium, S. triflorum, S. villosum and S. nigrum, were evaluated. Of these, most accessions were resistant to PCN with the following exceptions. The Newfoundland (NFLD) isolate of G. rostochiensis could replicate on S. villosum and S. dulcamara. In contrast, the British Columbian (BC) G. rostochiensis isolate was found to replicate on S. dulcamara but not S. villosum. Furthermore, two of 17 S. nigrum accessions were hosts to PCN from NFLD but not BC; however, both of these accessions may not be true S. nigrum samples but S. nigrum/S. villosum hybrids.

The potato cyst nematode (PCN). Globodera rostochiensis, has been present in Central Saanich on Vancouver Island for at least 45 years. Eradication/control efforts have been ongoing, with regulations enacted in the early 1980s restricting the planting of host crops and movement of soil. Surveys monitoring for cyst populations have been minimal since the regulations have been in place with only one limited study in the early 1990s. In this report, a survey of eight fields was undertaken, chosen as the most likely sites that may still harbor viable PCN cysts. Conventional sampling/detection methods were considered inadequate for the detection of very low cyst populations, and an innovative bioassay was developed to improve detection while minimizing costs and labor. Viable cysts were recovered from two fields, both with past quarantine infractions. Fields with no known infractions were found free of viable cysts. Lack of viable cysts found in fields with no infractions suggests that the quarantine restrictions in place since the early 1980s have been effective in reducing or eliminating PCN from these fields. Further systematic and comprehensive retesting of all fields within the quarantine zone is now required, which could lead to the reduction or lifting of some quarantine restrictions.