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

CRISPR-Cas assisted diagnostics of plant viruses and challenges

Plant viruses threaten global food security by infecting commercial crops, highlighting the critical need for efficient virus detection to enable timely preventive measures. Current techniques rely on polymerase chain reaction (PCR) for viral genome amplification and require laboratory conditions. This review explores the applications of CRISPR-Cas assisted diagnostic tools, specifically CRISPR-Cas12a and CRISPR-Cas13a/d systems for plant virus detection and analysis. The CRISPR-Cas12a system can detect viral DNA/RNA amplicons and can be coupled with PCR or isothermal amplification, allowing multiplexed detection in plants with mixed infections. Recent studies have eliminated the need for expensive RNA purification, streamlining the process by providing a visible readout through lateral flow strips. The CRISPR-Cas13a/d system can directly detect viral RNA with minimal preamplification, offering a proportional readout to the viral load. These approaches enable rapid viral diagnostics within 30 min of leaf harvest, making them valuable for onsite field applications. Timely identification of diseases associated with pathogens is crucial for effective treatment; yet developing rapid, specific, sensitive, and cost-effective diagnostic technologies remains challenging. The current gold standard, PCR technology, has drawbacks such as lengthy operational cycles, high costs, and demanding requirements. Here we update the technical advancements of CRISPR-Cas in viral detection, providing insights into future developments, versatile applications, and potential clinical translation. There is a need for approaches enabling field plant viral nucleic acid detection with high sensitivity, specificity, affordability, and portability. Despite challenges, CRISPR-Cas-mediated pathogen diagnostic solutions hold robust capabilities, paving the way for ideal diagnostic tools. Alternative applications in virus research are also explored, acknowledging the technology's limitations and challenges.

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.

Exploring the viral landscape of saffron through metatranscriptomic analysis

Saffron (Crocus sativus L.), a historically significant crop valued for its nutraceutical properties, has been poorly explored from a phytosanitary perspective. This study conducted a thorough examination of viruses affecting saffron samples from Spanish cultivars, using high-throughput sequencing alongside a systematic survey of transcriptomic datasets from Crocus sativus at the Sequence Read Archive. Our analysis unveiled a broad diversity and abundance, identifying 17 viruses across the 52 analyzed libraries, some of which were highly prevalent. This includes known saffron-infecting viruses and previously unreported ones. In addition, we discovered 7 novel viruses from the Alphaflexiviridae, Betaflexiviridae, Potyviridae, Solemoviridae, and Geminiviridae families, with some present in libraries from various locations. These findings indicate that the saffron-associated virome is more complex than previously reported, emphasizing the potential of phytosanitary analysis to enhance saffron productivity.

Occurrence, distribution, and genetic diversity of faba bean viruses in China

With worldwide cultivation, the faba bean (Vicia faba L.) stands as one of the most vital cool-season legume crops, serving as a major component of food security. China leads global faba bean production in terms of both total planting area and yield, with major production hubs in Yunnan, Sichuan, Jiangsu, and Gansu provinces. The faba bean viruses have caused serious yield losses in these production areas, but previous researches have not comprehensively investigated this issue. In this study, we collected 287 faba bean samples over three consecutive years from eight provinces/municipalities of China. We employed small RNA sequencing, RT-PCR, DNA sequencing, and phylogenetic analysis to detect the presence of viruses and examine their incidence, distribution, and genetic diversity. We identified a total of nine distinct viruses: bean yellow mosaic virus (BYMV, Potyvirus), milk vetch dwarf virus (MDV, Nanovirus), vicia cryptic virus (VCV, Alphapartitivirus), bean common mosaic virus (BCMV, Potyvirus), beet western yellows virus (BWYV, Polerovirus), broad bean wilt virus (BBWV, Fabavirus), soybean mosaic virus (SMV, Potyvirus), pea seed-borne mosaic virus (PSbMV, Potyvirus), and cucumber mosaic virus (CMV, Cucumovirus). BYMV was the predominant virus found during our sampling, followed by MDV and VCV. This study marks the first reported detection of BCMV in Chinese faba bean fields. Except for several isolates from Gansu and Yunnan provinces, our sequence analysis revealed that the majority of BYMV isolates contain highly conserved nucleotide sequences of coat protein (CP). Amino acid sequence alignment indicates that there is a conserved NAG motif at the N-terminal region of BYMV CP, which is considered important for aphid transmission. Our findings not only highlight the presence and diversity of pathogenic viruses in Chinese faba bean production, but also provide target pathogens for future antiviral resource screening and a basis for antiviral breeding.

Long-Read Sequencing Genome Assembly of Ceratocystis fimbriata Enables Development of Molecular Diagnostics for Sweetpotato Black Rot

Ceratocystis fimbriata is a destructive fungal pathogen of sweetpotato (Ipomoea batatas) that leads to losses at all stages of sweetpotato production. Accurate detection of C. fimbriata would allow for more efficient deployment of management tactics in sweetpotato production. To develop a diagnostic assay, a hybrid genome assembly of C. fimbriata isolate AS236 was generated. The resulting 31.7-MB assembly was near-chromosome level, with 18 contigs, 6,481 predicted genes, and a BUSCO completion score of 98.4% when compared with the fungus-specific lineage database. Additional Illumina DNA reads from C. manginecans, C. platani, and a second C. fimbriata isolate (C1421) were then mapped to the assembled genome using BOWTIE2 and counted using HTSeq, which identified 148 genes present only within C. fimbriata as molecular diagnostic candidates; 6 single-copy and 35 highly multi-copy (>40 BLAST hits), as determined through a self-BLAST-P alignment. Primers for PCR were designed in the 200-bp flanking region of the first exon for each candidate, and the candidates were validated against a diverse DNA panel containing Ceratocystis species, sweetpotato pathogens, and plants. After validation, two diagnostic candidates amplified only C. fimbriata DNA and were considered to be highly specific to the species. These genetic markers will serve as valuable diagnostic tools with multiple applications including the detection of C. fimbriata in seed, soil, and wash water in sweetpotato production.

Diagnosis and Characterization of Plant Viruses Using HTS to Support Virus Management and Tomato Breeding

Viral diseases pose a significant threat to tomato crops (Solanum lycopersicum L.), one of the world's most economically important vegetable crops. The limited genetic diversity of cultivated tomatoes contributes to their high susceptibility to viral infections. To address this challenge, tomato breeding programs must harness the genetic resources found in native populations and wild relatives. Breeding efforts may aim to develop broad-spectrum resistance against the virome. To identify the viruses naturally infecting 19 advanced lines, derived from native tomatoes, high-throughput sequencing (HTS) of small RNAs and confirmation with PCR and RT-PCR were used. Single and mixed infections with tomato mosaic virus (ToMV), tomato golden mosaic virus (ToGMoV), and pepper huasteco yellow vein virus (PHYVV) were detected. The complete consensus genomes of three variants of Mexican ToMV isolates were reconstructed, potentially forming a new ToMV clade with a distinct 3' UTR. The absence of reported mutations associated with resistance-breaking to ToMV suggests that the Tm-1, Tm-2, and Tm-22 genes could theoretically be used to confer resistance. However, the high mutation rates and a 63 nucleotide insertion in the 3' UTR, as well as amino acid mutations in the ORFs encoding 126 KDa, 183 KDa, and MP of Mexican ToMV isolates, suggest that it is necessary to evaluate the capacity of these variants to overcome Tm-1, Tm-2, and Tm-22 resistance genes. This evaluation, along with the characterization of advanced lines using molecular markers linked to these resistant genes, will be addressed in future studies as part of the breeding strategy. This study emphasizes the importance of using HTS for accurate identification and characterization of plant viruses that naturally infect tomato germplasm based on the consensus genome sequences. This study provides crucial insights to select appropriate disease management strategies and resistance genes and guide breeding efforts toward the development of virus-resistant tomato varieties.

Novel Betanucleorhabdoviruses Infecting Elderberry (Sambucus nigra L.): Genome Characterization and Genetic Variability

The genus Betanucleorhabdovirus includes plant viruses with negative sense, non-segmented, single-stranded RNA genomes. Here, we characterized putative novel betanucleorhabdoviruses infecting a medically important plant, elderberry. Total RNA was purified from the leaves of several plants, ribodepleted and sequenced using the Illumina platform. Sequence data analysis led to the identification of thirteen contigs of approximately 13.5 kb, showing a genome structure (3'-N-P-P3-M-G-L-5') typical of plant rhabdoviruses. The detected isolates showed 69.4 to 98.9% pairwise nucleotide identity and had the highest identity among known viruses (64.7-65.9%) with tomato betanucleorhabdovirus 2. A detailed similarity analysis and a phylogenetic analysis allowed us to discriminate the elderberry isolates into five groups, each meeting the sequence-based ICTV demarcation criterion in the Betanucleorhabdovirus genus (lower than 75% identity for the complete genome). Hence, the detected viruses appear to represent five novel, closely related betanucleorhabdoviruses, tentatively named Sambucus betanucleorhabdovirus 1 to 5.

Deciphering the virome of Chunkung (Cnidium officinale) showing dwarfism-like symptoms via a high-throughput sequencing analysis

BACKGROUND

Viruses have notable effects on agroecosystems, wherein they can adversely affect plant health and cause problems (e.g., increased biosecurity risks and economic losses). However, our knowledge of their diversity and interactions with specific host plants in ecosystems remains limited. To enhance our understanding of the roles that viruses play in agroecosystems, comprehensive analyses of the viromes of a wide range of plants are essential. High-throughput sequencing (HTS) techniques are useful for conducting impartial and unbiased investigations of plant viromes, ultimately forming a basis for generating further biological and ecological insights. This study was conducted to thoroughly characterize the viral community dynamics in individual plants.

RESULTS

An HTS-based virome analysis in conjunction with proximity sampling and a tripartite network analysis were performed to investigate the viral diversity in chunkung (Cnidium officinale) plants. We identified 61 distinct chunkung plant-associated viruses (27 DNA and 34 RNA viruses) from 21 known genera and 6 unclassified genera in 14 known viral families. Notably, 12 persistent viruses (7 DNA and 5 RNA viruses) were exclusive to dwarfed chunkung plants. The detection of viruses from the families Partitiviridae, Picobirnaviridae, and Spinareoviridae only in the dwarfed plants suggested that they may contribute to the observed dwarfism. The co-infection of chunkung by multiple viruses is indicative of a dynamic and interactive viral ecosystem with significant sequence variability and evidence of recombination.

CONCLUSIONS

We revealed the viral community involved in chunkung. Our findings suggest that chunkung serves as a significant reservoir for a variety of plant viruses. Moreover, the co-infection rate of individual plants was unexpectedly high. Future research will need to elucidate the mechanisms enabling several dozen viruses to co-exist in chunkung. Nevertheless, the important insights into the chunkung virome generated in this study may be relevant to developing effective plant viral disease management and control strategies.

Validation of High-Throughput Sequencing (HTS) for Routine Detection of Citrus Viruses and Viroids

The management of plant diseases relies on the accurate identification of pathogens that requires a robust and validated tool in terms of specificity, sensitivity, repeatability, and reproducibility. High-throughput sequencing (HTS) has become the method of choice for virus detection when either a complete viral status of a plant is required in a single assay or if an unknown viral agent is expected. To ensure that the most accurate diagnosis is made from an HTS data analysis, a standardized protocol per pathosystem is required. This chapter presents a detailed protocol for the detection of viruses and viroids infecting citrus using HTS. The protocol describes all the steps from sample processing, nucleic acid extraction, and bioinformatic analyses validated to be an efficient method for detection in this pathosystem. The protocol also includes a section on citrus tristeza virus (CTV) genotype differentiation using HTS data.

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 .

Benchmarking of virome metagenomic analysis approaches using a large, 60+ members, viral synthetic community

IMPORTANCE

We report here efforts to benchmark performance of two widespread approaches for virome analysis, which target either virion-associated nucleic acids (VANA) or highly purified double-stranded RNAs (dsRNAs). This was achieved using synthetic communities of varying complexity levels, up to a highly complex community of 72 viral agents (115 viral molecules) comprising isolates from 21 families and 61 genera of plant viruses. The results obtained confirm that the dsRNA-based approach provides a more complete representation of the RNA virome, in particular, for high complexity ones. However, for viromes of low to medium complexity, VANA appears a reasonable alternative and would be the preferred choice if analysis of DNA viruses is of importance. Several parameters impacting performance were identified as well as a direct relationship between the completeness of virome description and sample sequencing depth. The strategy, results, and tools used here should prove useful in a range of virome analysis efforts.

Cont-ID: detection of sample cross-contamination in viral metagenomic data

BACKGROUND

High-throughput sequencing (HTS) technologies completed by the bioinformatic analysis of the generated data are becoming an important detection technique for virus diagnostics. They have the potential to replace or complement the current PCR-based methods thanks to their improved inclusivity and analytical sensitivity, as well as their overall good repeatability and reproducibility. Cross-contamination is a well-known phenomenon in molecular diagnostics and corresponds to the exchange of genetic material between samples. Cross-contamination management was a key drawback during the development of PCR-based detection and is now adequately monitored in routine diagnostics. HTS technologies are facing similar difficulties due to their very high analytical sensitivity. As a single viral read could be detected in millions of sequencing reads, it is mandatory to fix a detection threshold that will be informed by estimated cross-contamination. Cross-contamination monitoring should therefore be a priority when detecting viruses by HTS technologies.

RESULTS

We present Cont-ID, a bioinformatic tool designed to check for cross-contamination by analysing the relative abundance of virus sequencing reads identified in sequence metagenomic datasets and their duplication between samples. It can be applied when the samples in a sequencing batch have been processed in parallel in the laboratory and with at least one specific external control called Alien control. Using 273 real datasets, including 68 virus species from different hosts (fruit tree, plant, human) and several library preparation protocols (Ribodepleted total RNA, small RNA and double-stranded RNA), we demonstrated that Cont-ID classifies with high accuracy (91%) viral species detection into (true) infection or (cross) contamination. This classification raises confidence in the detection and facilitates the downstream interpretation and confirmation of the results by prioritising the virus detections that should be confirmed.

CONCLUSIONS

Cross-contamination between samples when detecting viruses using HTS (Illumina technology) can be monitored and highlighted by Cont-ID (provided an alien control is present). Cont-ID is based on a flexible methodology relying on the output of bioinformatics analyses of the sequencing reads and considering the contamination pattern specific to each batch of samples. The Cont-ID method is adaptable so that each laboratory can optimise it before its validation and routine use.

Complete Genome Characterization of Penicillimonavirus gammaplasmoparae, a Bipartite Member of the Family Mymonaviridae

In this study, we identified Plasmopara-viticola-lesion-associated mononegaambi virus 3 (recently classified as Penicillimonavirus gammaplasmoparae), a fungi-associated mymonavirus, in grapevine plants showing an unusual upward curling symptomatology on the leaves and premature decline. Mymonaviridae is a family comprising nine genera of negative-sense single-stranded RNA viruses infecting filamentous fungi, although few of them have been associated with oomycetes, plants, and insects. Although the first mymonavirus genome description was reported a decade ago, the genome organization of several genera in the family, including the genus Penicillimonavirus, has remained unclear to date. We have determined the complete genome of P. gammaplasmoparae, which represents the first complete genomic sequence for this genus. Moreover, we provide strong evidence that P. gammaplasmoparae genome is bipartite and comprises two RNA molecules of around 6150 and 4560 nt. Our results indicate that the grapevine powdery mildew pathogen, Erysiphe necator, was also present in the analyzed plants and suggest P. gammaplasmoparae could be infecting this fungus. However, whether the fungus and/or the mycovirus are associated with the symptomatology that initially prompted these efforts remains to be determined.

In Silico Virome Analysis of Chinese Narcissus Transcriptomes Reveals Diverse Virus Species and Genetic Diversity at Different Flower Development Stages

Viromes of Chinese narcissus flowers were explored using transcriptome data from 20 samples collected at different flower development stages. Quality controlled raw data underwent de novo assembly, resulting in 5893 viral contigs that matched the seven virus species. The most abundant viruses were narcissus common latent virus (NCLV), narcissus yellow stripe virus (NYSV), and narcissus mottling-associated virus (NMaV). As flower development stages advanced, white tepal plants showed an increase in the proportion of viral reads, while the variation in viral proportion among yellow tepal plants was relatively small. Narcissus degeneration virus (NDV) dominated the white tepal samples, whereas NDV and NYSV prevailed in the yellow tepal samples. Potyviruses, particularly NDV, are the primary infectious viruses. De novo assembly generated viral contigs for five viruses, yielding complete genomes for NCLV, NDV, narcissus late season yellow virus (NLSYV), and NYSV. Phylogenetic analysis revealed genetic diversity, with distinct NCLV, NMaV, NDV, NLSYV, and NYSV groups. This study provides valuable insights into the viromes and genetic diversity of viruses in Chinese narcissus flowers.

Molecular and Biological Characterization of Novel and Known Family Secoviridae Members Infecting Lettuce

High-throughput sequencing of two lettuces showing virus-like symptoms in France provided evidence of infection by members of the family Secoviridae. One plant (JG1) had a complex mixed infection that involved, among others, a novel waikavirus (lettuce waikavirus 1) and two isolates of a sequivirus related to lettuce mottle virus (LeMoV). The second lettuce plant (JG2) was singly infected by LeMoV. Complete genomic sequences were obtained for all four isolates and, in addition, near complete genome sequences were obtained for other LeMoV or LeMoV-related isolates (from French cultivated and wild lettuces and from a Brazilian cultivated lettuce) and for two isolates of another family Asteraceae-infecting sequivirus, dandelion yellow mosaic virus (DaYMV). Analysis of these genomic sequences allows the proposal of tentative genome organization for the various viruses and clarification of their phylogenetic relationships. Sequence and host range comparisons point to significant differences between the two sequivirus isolates identified in the JG1 plant and LeMoV isolates from France and Brazil, suggesting they belong to a novel species for which the name lettuce star mosaic virus is proposed.

High-Throughput Sequencing of Grapevine in Mexico Reveals a High Incidence of Viruses including a New Member of the Genus Enamovirus

This is the first viral metagenomic analysis of grapevine conducted in Mexico. During the summer of 2021, 48 plants displaying virus-like symptoms were sampled in Queretaro, an important grapevine-producing area of Mexico, and analyzed for the presence of viruses via high-throughput sequencing (HTS). The results of HTS were verified by real-time RT-PCR following a standardized testing scheme (Protocol 2010). Fourteen different viruses were identified, including grapevine asteroid mosaic-associated virus (GAMaV), grapevine Cabernet Sauvignon reovirus (GCSV), grapevine fanleaf virus (GFLV), grapevine fleck virus (GFkV), grapevine Pinot gris virus (GPGV), grapevine red globe virus (GRGV), grapevine rupestris stem pitting-associated virus (GRSPaV), grapevine rupestris vein feathering virus (GRVFV), grapevine Syrah virus 1 (GSyV-1), grapevine virus B (GVB), and grapevine leafroll-associated viruses 1, 2, 3, 4 (GLRaV1, 2, 3, 4). Additionally, divergent variants of GLRaV4 and GFkV, and a novel Enamovirus-like virus were discovered. This is the first report of GAMaV, GCSV, GLRaV4, GPGV, GRGV, GRVFV, and GSyV-1 infecting grapevines in Mexico; the impact of these pathogens on production is unknown.

Managing the deluge of newly discovered plant viruses and viroids: an optimized scientific and regulatory framework for their characterization and risk analysis

The advances in high-throughput sequencing (HTS) technologies and bioinformatic tools have provided new opportunities for virus and viroid discovery and diagnostics. Hence, new sequences of viral origin are being discovered and published at a previously unseen rate. Therefore, a collective effort was undertaken to write and propose a framework for prioritizing the biological characterization steps needed after discovering a new plant virus to evaluate its impact at different levels. Even though the proposed approach was widely used, a revision of these guidelines was prepared to consider virus discovery and characterization trends and integrate novel approaches and tools recently published or under development. This updated framework is more adapted to the current rate of virus discovery and provides an improved prioritization for filling knowledge and data gaps. It consists of four distinct steps adapted to include a multi-stakeholder feedback loop. Key improvements include better prioritization and organization of the various steps, earlier data sharing among researchers and involved stakeholders, public database screening, and exploitation of genomic information to predict biological properties.

Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests

High-throughput sequencing (HTS), more specifically RNA sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus databases. In this way, they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data, as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected samples (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their sample(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.

Managing Viral Emerging Infectious Diseases via Current and Future Molecular Diagnostics

Emerging viral infectious diseases have been a constant threat to global public health in recent times. In managing these diseases, molecular diagnostics has played a critical role. Molecular diagnostics involves the use of various technologies to detect the genetic material of various pathogens, including viruses, in clinical samples. One of the most commonly used molecular diagnostics technologies for detecting viruses is polymerase chain reaction (PCR). PCR amplifies specific regions of the viral genetic material in a sample, making it easier to detect and identify viruses. PCR is particularly useful for detecting viruses that are present in low concentrations in clinical samples, such as blood or saliva. Another technology that is becoming increasingly popular for viral diagnostics is next-generation sequencing (NGS). NGS can sequence the entire genome of a virus present in a clinical sample, providing a wealth of information about the virus, including its genetic makeup, virulence factors, and potential to cause an outbreak. NGS can also help identify mutations and discover new pathogens that could affect the efficacy of antiviral drugs and vaccines. In addition to PCR and NGS, there are other molecular diagnostics technologies that are being developed to manage emerging viral infectious diseases. One of these is CRISPR-Cas, a genome editing technology that can be used to detect and cut specific regions of viral genetic material. CRISPR-Cas can be used to develop highly specific and sensitive viral diagnostic tests, as well as to develop new antiviral therapies. In conclusion, molecular diagnostics tools are critical for managing emerging viral infectious diseases. PCR and NGS are currently the most commonly used technologies for viral diagnostics, but new technologies such as CRISPR-Cas are emerging. These technologies can help identify viral outbreaks early, track the spread of viruses, and develop effective antiviral therapies and vaccines.

Surveillance for Avocado Sunblotch Viroid Utilizing the European Honey Bee (Apis mellifera)

Avocado is one of the world's fastest growing tropical fruit industries, and the pathogen avocado sunblotch viroid (ASBVd) is a major threat to both production and access to international export markets. ASBVd is seed transmissible, with infection possible via either the male (pollen) or female gametes. Surveillance for ASBVd across commercial orchards is a major logistical task, particularly when aiming to meet the stringent standards of evidence required for a declaration of pest freedom. As with many fruit crops, insect pollination is important for high avocado yields, and honey bee (Apis mellifera) hives are typically moved into orchards for paid pollination services. Exploiting the foraging behavior of honey bees can provide a complementary strategy to traditional surveillance methods. High-throughput sequencing (HTS) of bee samples for plant viruses shows promise, but this surveillance method has not yet been tested for viroids or in a targeted plant biosecurity context. Here, we tested samples of bees and pollen collected from pollination hives in two ASBVd orchard locations, one in Australia, where only four trees in a block were known to be infected, and a second in South Africa, where the estimated incidence of infection was 10%. Using real-time RT-PCR and HTS (total RNA-seq and small RNA-seq), we demonstrated that ASBVd can be confidently detected in bees and pollen samples from hives within 100 m of infected trees. The potential for using this approach in ASBVd surveillance for improved orchard management and supporting market access is discussed.

Plant Protection against Viruses: An Integrated Review of Plant Immunity Agents

Plant viruses are an important class of pathogens that seriously affect plant growth and harm crop production. Viruses are simple in structure but complex in mutation and have thus always posed a continuous threat to agricultural development. Low resistance and eco-friendliness are important features of green pesticides. Plant immunity agents can enhance the resilience of the immune system by activating plants to regulate their metabolism. Therefore, plant immune agents are of great importance in pesticide science. In this paper, we review plant immunity agents, such as ningnanmycin, vanisulfane, dufulin, cytosinpeptidemycin, and oligosaccharins, and their antiviral molecular mechanisms and discuss the antiviral applications and development of plant immunity agents. Plant immunity agents can trigger defense responses and confer disease resistance to plants, and the development trends and application prospects of plant immunity agents in plant protection are analyzed in depth.

A Novel and Highly Inclusive Quantitative Real-Time RT-PCR Method for the Broad and Efficient Detection of Grapevine Leafroll-Associated Virus 1

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.

Plant Viruses of Agricultural Importance: Current and Future Perspectives of Virus Disease Management Strategies

Plant viruses cause significant losses in agricultural crops worldwide, affecting the yield and quality of agricultural products. The emergence of novel viruses or variants through genetic evolution and spillover from reservoir host species, changes in agricultural practices, mixed infections with disease synergism, and impacts from global warming pose continuous challenges for the management of epidemics resulting from emerging plant virus diseases. This review describes some of the most devastating virus diseases plus select virus diseases with regional importance in agriculturally important crops that have caused significant yield losses. The lack of curative measures for plant virus infections prompts the use of risk-reducing measures for managing plant virus diseases. These measures include exclusion, avoidance, and eradication techniques, along with vector management practices. The use of sensitive, high throughput, and user-friendly diagnostic methods is crucial for defining preventive and management strategies against plant viruses. The advent of next-generation sequencing technologies has great potential for detecting unknown viruses in quarantine samples. The deployment of genetic resistance in crop plants is an effective and desirable method of managing virus diseases. Several dominant and recessive resistance genes have been used to manage virus diseases in crops. Recently, RNA-based technologies such as dsRNA- and siRNA-based RNA interference, microRNA, and CRISPR/Cas9 provide transgenic and nontransgenic approaches for developing virus-resistant crop plants. Importantly, the topical application of dsRNA, hairpin RNA, and artificial microRNA and trans-active siRNA molecules on plants has the potential to develop GMO-free virus disease management methods. However, the long-term efficacy and acceptance of these new technologies, especially transgenic methods, remain to be established.

Defective RNA Particles of Plant Viruses-Origin, Structure and Role in Pathogenesis

The genomes of RNA viruses may be monopartite or multipartite, and sub-genomic particles such as defective RNAs (D RNAs) or satellite RNAs (satRNAs) can be associated with some of them. D RNAs are small, deletion mutants of a virus that have lost essential functions for independent replication, encapsidation and/or movement. D RNAs are common elements associated with human and animal viruses, and they have been described for numerous plant viruses so far. Over 30 years of studies on D RNAs allow for some general conclusions to be drawn. First, the essential condition for D RNA formation is prolonged passaging of the virus at a high cellular multiplicity of infection (MOI) in one host. Second, recombination plays crucial roles in D RNA formation. Moreover, during virus propagation, D RNAs evolve, and the composition of the particle depends on, e.g., host plant, virus isolate or number of passages. Defective RNAs are often engaged in transient interactions with full-length viruses-they can modulate accumulation, infection dynamics and virulence, and are widely used, i.e., as a tool for research on cis-acting elements crucial for viral replication. Nevertheless, many questions regarding the generation and role of D RNAs in pathogenesis remain open. In this review, we summarise the knowledge about D RNAs of plant viruses obtained so far.

High-throughput detection of a large set of viruses and viroids of pome and stone fruit trees by multiplex PCR-based amplicon sequencing

A comprehensive diagnostic method of known plant viruses and viroids is necessary to provide an accurate phytosanitary status of fruit trees. However, most widely used detection methods have a small limit on either the number of targeted viruses/viroids or the number of samples to be evaluated at a time, hampering the ability to rapidly scale up the test capacity. Here we report that by combining the power of high multiplexing PCR (499 primer pairs) of small amplicons (120-135bp), targeting 27 viruses and 7 viroids of fruit trees, followed by a single high-throughput sequencing (HTS) run, we accurately diagnosed the viruses and viroids on as many as 123 pome and stone fruit tree samples. We compared the accuracy, sensitivity, and reproducibility of this approach and contrast it with other detection methods including HTS of total RNA (RNA-Seq) and individual RT-qPCR for every fruit tree virus or viroid under the study. We argue that this robust and high-throughput cost-effective diagnostic tool will enhance the viral/viroid knowledge of fruit trees while increasing the capacity for large scale diagnostics. This approach can also be adopted for the detection of multiple viruses and viroids in other crops.

Weed Hosts Represent an Important Reservoir of Turnip Yellows Virus and a Possible Source of Virus Introduction into Oilseed Rape Crop

Turnip yellows virus (TuYV) is one of the most important pathogens of oilseed rape worldwide. The virus has a large host range including many crop species (e.g., oilseed rape, pea, chickpea) and weeds from more than twenty plant families. Other than oilseed rape, we detected TuYV in many commonly grown weed species that share the fields and vegetation period together with canola crops in Czech and Slovak Republics. TuYV was detected by reverse-transcription polymerase chain reaction (RT-PCR) in at least 26 species including main crop hosts (oilseed rape), intercrops and weeds such as Amaranthus retroflexus, Atriplex patula (Amaranthaceae), Arctium lappa, Lactuca serriola, Taraxacum officinale, Tripleurospermum inodorum (Asteraceae), Phacelia tanacetifolia (Boraginaceae), Brassica napus, Capsella bursa-pastoris, Descurainia Sophia, Raphanus raphanistrum, Sinapis alba, Sisymbrium officinale, Thlaspi arvense (Brassicaceae), Silene alba, Stellaria media (Caryophyllaceae), Euphorbia helioscopia (Euphorbiaceae), Geranium rotundifolium (Geraniaceae), Lamium purpureum (Lamiaceae), Fumaria officinalis, Papaver rhoeas (Papaveraceae), Veronica persica (Plantaginaceae syn. Scrophulariaceae), Fallopia convolvulus (Polygonaceae), Solanum nigrum (Solanaceae), Urtica dioica (Urticaceae) and Viola arvensis (Violaceae). The detection of TuYV was further confirmed by RT-qPCR as well as Sanger sequencing of the PCR fragments. We discovered four new weed species as hosts of TuYV such as T. inodorum, S. alba, G. rotundifolium and E. helioscopia, representing their three respective plant families. The readthrough domain (RTD) gene sequence analysis of the Czech and Slovak TuYV isolates from oilseed rape and weed species showed similar within-group nucleotide divergence (7.1% and 5.6%, respectively) and the absence of geographical- or host-based phylogenetic clustering. The high-throughput sequencing of the P. rhoeas sample enabled the obtention of a nearly complete genome of TuYV and revealed the mixed infection of TuYV with turnip mosaic virus and cucumber mosaic virus. Our results thus show that weed species are an important TuYV reservoir and play a significant role in the spread and incidence of the disease in field crops such as oilseed rape.

Identification and complete genome sequencing of a divergent olive virus T isolate and an olive leaf yellowing-associated virus isolate naturally infecting olive trees in Greece

Several new full genome sequences of olive viruses came to light recently via high-throughput sequencing (HTS) analysis. In this study, total RNA HTS analysis of two Greek olive trees revealed the presence of an olive virus T (OlVT) isolate and an olive leaf yellowing-associated virus (OLYaV) isolate. The full viral genome of OlVT isolate (50Ch) is composed of 6862 nucleotides encoding for three proteins (replicase, movement protein, and capsid protein) with typical betaflexiviruses' genomic features. However, both sequence and phylogenetic data analysis exhibited high levels of variability between 50Ch and the previously characterized OlVT isolates. In addition, the almost full genome of the Greek OLYaV isolate (OL2) was obtained, which is composed of 16,693 nucleotides encoding for 11 open reading frames (ORFs) and shares common genomic features with the recently characterized OLYaV isolates from Spain and Brazil. Sequence and phylogenetic analysis revealed high similarity between these three isolates. Due to problems encountered with the detection of both viruses, new nested RT-PCR assays were developed and applied. In addition, recombination events were observed in OlVT isolates (50Ch GR-168), thus highlighting the potential role of this mechanism in the evolution of the virus. This study is adding further knowledge to the limited information available about these recently characterized olive infecting viral pathogens and highlights their widespread distribution in Greece, one of the most important olive producing countries of the world.

Viral metatranscriptomic approach to study the diversity of virus(es) associated with Common Bean (Phaseolus vulgaris L.) in the North-Western Himalayan region of India

Plant viruses are a major threat to legume production worldwide. In recent years, new virus strains have emerged with increasing frequencies in various legume cropping systems, which demands the development of cutting-edge virus surveillance techniques. In this study, we surveyed the common bean fields of Kashmir valley for virus infection using a total of 140 symptomatic and non-symptomatic leaf samples collected from different locations. The genetic diversity of viruses was examined by high-throughput sequencing (HTS) with three viruses being identified, namely, Bean Common Mosaic Virus (BCMV), Bean Common Mosaic Necrosis Virus (BCMNV), and Clover Yellow Vein Virus (ClYVV). BCMNV and ClYVV are new reports from India. De novo assembly of transcriptome constructed near-complete genomes of these viruses. RT-PCR results confirmed the presence of these viruses with an emerge incidence of 56. 4% for BCMV, 27.1% for BCMNV and 16.4 for ClYVV in the valley. Several samples were found to contain multiple virus infections with BCMV being the most predominant. Recombination events were detected in the genomes of BCMV and ClYVV, but not BCMNV. Phylogenetic and pairwise identity matrix evidence suggests viral import from multiple countries. Our results demonstrate that HTS followed by multiplex PCR assay is a simple, rapid, and reliable approach for simultaneous diagnosis of plant viruses.

Reproducibility and Sensitivity of High-Throughput Sequencing (HTS)-Based Detection of Citrus Tristeza Virus and Three Citrus Viroids

The credibility of a pathogen detection assay is measured using specific parameters including repeatability, specificity, sensitivity, and reproducibility. The use of high-throughput sequencing (HTS) as a routine detection assay for viruses and viroids in citrus was previously evaluated and, in this study, the reproducibility and sensitivity of the HTS assay were assessed. To evaluate the reproducibility of HTS, the same plants assayed in a previous study were sampled again, one year later, and assessed in triplicate using the same analyses to construct the virome profile. The sensitivity of the HTS assay was compared to routinely used RT-PCR assays in a time course experiment, to compensate for natural pathogen accumulation in plants over time. The HTS pipeline applied in this study produced reproducible and comparable results to standard RT-PCR assays for the detection of CTV and three viroid species in citrus. Even though the limit of detection of HTS can be influenced by pathogen concentration, sample processing method and sequencing depth, detection with HTS was found to be either equivalent or more sensitive than RT-PCR in this study.

Nanopore sequencing technology and its application in plant virus diagnostics

Plant viruses threaten crop yield and quality; thus, efficient and accurate pathogen diagnostics are critical for crop disease management and control. Recent advances in sequencing technology have revolutionized plant virus research. Metagenomics sequencing technology, represented by next-generation sequencing (NGS), has greatly enhanced the development of virus diagnostics research because of its high sensitivity, high throughput and non-sequence dependence. However, NGS-based virus identification protocols are limited by their high cost, labor intensiveness, and bulky equipment. In recent years, Oxford Nanopore Technologies and advances in third-generation sequencing technology have enabled direct, real-time sequencing of long DNA or RNA reads. Oxford Nanopore Technologies exhibit versatility in plant virus detection through their portable sequencers and flexible data analyses, thus are wildly used in plant virus surveillance, identification of new viruses, viral genome assembly, and evolution research. In this review, we discuss the applications of nanopore sequencing in plant virus diagnostics, as well as their limitations.

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.

Occurrence, Genetic Variability of Tomato Yellow Ring Orthotospovirus Population and the Development of Reverse Transcription Loop-Mediated Isothermal Amplification Assay for Its Rapid Detection

Tomato-infecting viruses have been considered as a serious threat to tomato crops in Poland. Therefore, during 2014–2021, 234 tomato samples delivered directly by greenhouse tomato growers to Plant Disease Clinic of IPP-NRI were tested. Eight virus species: pepino mosaic virus (PepMV), tomato yellow ring orthotospovirus (TYRV), tomato spotted wilt orthotospovirus (TSWV), potato virus Y (PVY), cucumber mosaic virus (CMV), tomato black ring virus (TBRV) and tomato mosaic virus (ToMV) were detected in single or mixed infection in 89 samples. The presence of TYRV was established for the first time in Poland in 2014. Since then, its presence has been observed in single and mixed infection with TSWV and CMV. Here, we analysed the genetic variability of TYRV population based on complete nucleocapsid (N) protein gene sequence of 55 TYRV isolates. Maximum-likelihood reconstruction revealed the presence of three distinct, well-supported phylogroups. Moreover, the effect of host species on virus diversity was confirmed. Therefore, RT-LAMP assay was developed for the rapid and efficient detection of TYRV isolates that can be implemented in field and greenhouse conditions.

Viromes of Hungarian Peach Trees Identified by High-Throughput Sequencing of Small RNAs

Peach trees can be infected with viruses and viroids. As we do not have efficient plant protection methods against these pathogens, the prevention of infection is crucial. Fruit trees are maintained by vegetative propagation. Planting material such as certified mother trees and rootstocks should be free from viruses and viroids, and this status has to be regularly checked to prevent infections. We surveyed certified peach trees for the presence of viruses and viroids using small RNA high-throughput sequencing (HTS), an unbiased virus diagnostic method. The results of the bioinformatic analysis of HTS were validated by other molecular methods including RT-PCR, Northern blot hybridization and loop-mediated isothermal amplification (LAMP). We found the presence of plum pox virus and peach latent mosaic viroid (PLMVd) in the vector-free isolator houses, whose presence should be regularly tested. Moreover, we detected frequent infection with recently described viruses such as nectarine stem pitting-associated virus and peach-associated luteovirus (PaLV). During the survey, PLMVd and PaLV were detected for the first time in Hungary. The analysis of the presenting virus variants and possible sources of infection suggests that the source of the viral infection could be the infected propagating material. Our study emphasizes the importance of using sensitive and trustworthy diagnostic techniques to be able to detect viral infections and successfully prevent their spread by propagation material.

Survey of Viruses Infecting Tomato, Cucumber and Mung Bean in Tajikistan

Viral diseases are major constraints to tomato, cucumber and mung bean production in most areas where these crops are grown. To identify the viruses on the crops in Tajikistan, a field survey was conducted in 2019. Samples of cucumber, mung bean and tomato with virus-like symptoms were collected and the viruses present were diagnosed by RT-PCR and PCR. Across all the samples, a very high proportion of the samples were infected with viruses from the genera Cucumovirus and Potyvirus. Cucumber mosaic virus (CMV; Cucumovirus) was very common in the collected samples of the three crops. As for Potyvirus, Potato virus Y (PVY) was detected in the collected tomato samples, Zucchini yellow mosaic virus (ZYMV) was identified in the collected cucumber samples, and Bean common mosaic virus (BCMV) was detected in 53% of the mung bean samples. Over 68% of the collected samples were infected with two or more viruses, suggesting that mixed infections are common for the three crops. Due to the results that the most identified viruses for the three crops are transmitted by aphids, the management of aphids is extremely important for the production of tomato, cucumber and mung bean in Tajikistan.

Diverse Novel Viruses Coinfecting the Tropical Ornamental Plant Polyscias balfouriana in China

The viromic profile of Polyscias balfouriana cv. Marginata, a perennial woody and ornamental plant, was determined using ribosomal RNA-depleted total RNA (rRNA-depleted totRNA) sequencing. Five viruses (i.e., polyscias mosaic virus, PoMV; one potential novel rhabdovirus; and three novel viruses of Betaflexiviridae and Closteroviridae) were detected and prevalence-surveyed in Hainan province, China. The genomes of polyscias capillovirus 1 (PCaV-1) and polyscias citrivirus 1 (PCiV-1) of family Betaflexiviridae were completed, and the genomes of polyscias crinivirus 1 (PCrV-1) of Closteroviridae were nearly completed lacking the 5′ and 3′ termini. PCaV-1 shares 68% genome nucleotide (nt) identity and 66% replicase (Rep) amino acid (aa) identity with homologues in apple stem grooving virus (ASGV). PCiV-1 shares 65% genome nt identity and 64% Rep aa identity with homologs in citrus leaf blotch virus (CLBV). Meeting the species demarcation criteria, PCaV-1 and PCiV-1 were considered to be new species in genera Capillovirus and Citrivirus, respectively. PCrV-1 shares high genome nt identity (62%), heat shock protein 70-like protein (HSP70h) and RNA-dependent RNA polymerase (RdRp) aa identity (78−80%) with homologues in tomato chlorosis virus (ToCV). We tentatively consider PCrV-1 to be an unclassified member of the Crinivirus genus. PoMV, PCaV-1, PCiV-1, and PCrV-1 are the prevalent viruses with >73% occurrence in the Xinglong Tropical Botanical Garden, Hainan, China.

VirHunter: A Deep Learning-Based Method for Detection of Novel RNA Viruses in Plant Sequencing Data

High-throughput sequencing has provided the capacity of broad virus detection for both known and unknown viruses in a variety of hosts and habitats. It has been successfully applied for novel virus discovery in many agricultural crops, leading to the current drive to apply this technology routinely for plant health diagnostics. For this, efficient and precise methods for sequencing-based virus detection and discovery are essential. However, both existing alignment-based methods relying on reference databases and even more recent machine learning approaches are not efficient enough in detecting unknown viruses in RNAseq datasets of plant viromes. We present VirHunter, a deep learning convolutional neural network approach, to detect novel and known viruses in assemblies of sequencing datasets. While our method is generally applicable to a variety of viruses, here, we trained and evaluated it specifically for RNA viruses by reinforcing the coding sequences' content in the training dataset. Trained on the NCBI plant viruses data for three different host species (peach, grapevine, and sugar beet), VirHunter outperformed the state-of-the-art method, DeepVirFinder, for the detection of novel viruses, both in the synthetic leave-out setting and on the 12 newly acquired RNAseq datasets. Compared with the traditional tBLASTx approach, VirHunter has consistently exhibited better results in the majority of leave-out experiments. In conclusion, we have shown that VirHunter can be used to streamline the analyses of plant HTS-acquired viromes and is particularly well suited for the detection of novel viral contigs, in RNAseq datasets.

Virus invasions of the New Zealand flora

More than 200 plant viruses and many of their invertebrate vectors have invaded New Zealand (NZ) in the last two centuries. All of these invaders are associated with introduced agricultural, horticultural and/or weed species. At least 16 of the viruses have invaded the native flora, including some rare and critically endangered species. Patterns are emerging: aphid transmitted viruses which are able to infect species from a number of families are prominent. For example, cucumber mosaic virus infects native species from seven families. There are also examples of viruses with more restricted host ranges invading individual families, particularly the native grasses. The yellow dwarf viruses have escaped from cereals and pasture into native grasses. Some of the species are also native to Australia and the Pacific Islands and the review and its literature should be of interest to those working further afield. Prospects for controlling or mitigating the effects of the viruses in agricultural systems have limited application in the native flora but they are relevant to propagation and rescue strategies. Biosecurity measures are not only the first line of defence against threats to agriculture but also to the conservation estate. The protection of native floras from virus invasion is another justification for the control measures and legislative procedures already in place to protect agriculture. High throughput sequencing to detect all viruses at the border, and genetic engineering and RNAi technologies to mitigate the effects of invasions are promising developments for the protection of the native flora.

An Advanced One-Step RT-LAMP for Rapid Detection of Little cherry virus 2 Combined with High-Throughput Sequence-Based Phylogenomics Reveal Divergent Flowering Cherry Isolates

Little cherry virus 2 (LChV-2, genus Ampelovirus) is considered to be the main causal agent of the economically damaging little cherry disease, which can only be controlled by removal of infected trees. The widespread viral disease of sweet cherry (Prunus avium L.) is affecting the survival of long-standing orchards in North America and Europe, hence the dire need for an early and accurate diagnosis to establish a sound disease control strategy. The endemic presence of LChV-2 is mainly confirmed using laborious time-consuming reverse-transcription (RT-PCR). A rapid reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay targeting a conserved region of the coat protein was developed and compared with conventional RT-PCR for the specific detection of LChV-2. This affordable assay, combined with a simple RNA extraction, deploys desirable characteristics such as higher ability for faster (<15 min), more analytically sensitive (100-fold), and robust broad-range diagnosis of LChV-2 isolates from sweet cherry, ornamental flowering cherry displaying heterogenous viral etiology and, for the first time, newly identified potential insect vectors. Moreover, use of Sanger and total RNA high-throughput sequencing as complementary metaviromics approaches confirmed the LChV-2 RT-LAMP detection of divergent LChV-2 isolates in new hosts and the relationship of their whole-genome was exhaustively inferred using maximum-likelihood phylogenomics. This entails unprecedented critical understanding of a novel evolutionary clade further expanding LChV-2 viral diversity. In conclusion, this highly effective diagnostic platform facilitates strategical support for early in-field testing to reliably prevent dissemination of new LChV-2 outbreaks from propagative plant stocks or newly postulated insect vectors. Validated results and major advantages are herein thoroughly discussed, in light of the knowledge required to increase the potential accuracy of future diagnostics and the essential epidemiological considerations to proactively safeguard cherries and Prunus horticultural crop systems from little cherry disease.

Highly divergent isolates of chrysanthemum virus B and chrysanthemum virus R infecting chrysanthemum in Russia

BACKGROUND

Chrysanthemum is a popular ornamental and medicinal plant that suffers from many viruses and viroids. Among them, chrysanthemum virus B (CVB, genus Carlavirus, family Betaflexiviridae) is widespread in all chrysanthemum-growing regions. Another carlavirus, chrysanthemum virus R (CVR), has been recently discovered in China. Information about chrysanthemum viruses in Russia is very scarce. The objective of this work was to study the prevalence and genetic diversity of CVB and CVR in Russia.

METHODS

We surveyed the chrysanthemum (Chrysanthemum morifolium Ramat.) germplasm collection in the Nikita Botanical Gardens, Yalta, Russia. To detect CVB and CVR, we used RT-PCR with virus-specific primers. To reveal the complete genome sequences of CVB and CVR isolates, metatransciptomic analysis of the cultivars Ribonette, Fiji Yellow, and Golden Standard plants, naturally co-infected with CVB and CVR, was performed using Illumina high-throughput sequencing. The recombination detection tool (RDP4) was employed to search for recombination in assembled genomes.

RESULTS

A total of 90 plants of 23 local and introduced chrysanthemum cultivars were surveyed. From these, 58 and 43% plants tested positive for CVB and CVR, respectively. RNA-Seq analysis confirmed the presence of CVB and CVR, and revealed tomato aspermy virus in each of the three transcriptomes. Six near complete genomes of CVB and CVR were assembled from the RNA-Seq reads. The CVR isolate X21 from the cultivar Golden Standard was 92% identical to the Chinese isolate BJ. In contrast, genomes of the CVR isolates X6 and X13 (from the cultivars Ribonette and Fiji Yellow, respectively), were only 76% to 77% identical to the X21 and BJ, and shared 95% identity to one another and appear to represent a divergent group of the CVR. Two distantly related CVB isolates, GS1 and GS2, were found in a plant of the cultivar Golden Standard. Their genomes shared from 82% to 87% identity to each other and the CVB genome from the cultivar Fiji Yellow (isolate FY), as well as to CVB isolates from Japan and China. A recombination event of 3,720 nucleotides long was predicted in the replicase gene of the FY genome. It was supported by seven algorithms implemented in RDP4 with statistically significant P-values. The inferred major parent was the Indian isolate Uttar Pradesh (AM765837), and minor parent was unknown.

CONCLUSION

We found a wide distribution of CVB and CVR in the chrysanthemum germplasm collection of the Nikita Botanical Gardens, which is the largest in Russia. Six near complete genomes of CVR and CVB isolates from Russia were assembled and characterized for the first time. This is the first report of CVR in Russia and outside of China thus expanding the information on the geographical distribution of the virus. Highly divergent CVB and CVR isolates have been identified that contributes the better understanding the genetic diversity of these viruses.

Integrating High throughput Sequencing into Survey Design Reveals Turnip Yellows Virus and Soybean Dwarf Virus in Pea (Pisum Sativum) in the United Kingdom

There is only limited knowledge of the presence and incidence of viruses in peas within the United Kingdom, therefore high-throughput sequencing (HTS) in combination with a bulk sampling strategy and targeted testing was used to determine the virome in cultivated pea crops. Bulks of 120 leaves collected from twenty fields from around the UK were initially tested by HTS, and presence and incidence of virus was then determined using specific real-time reverse-transcription PCR assays by testing smaller mixed-bulk size samples. This study presents the first finding of turnip yellows virus (TuYV) in peas in the UK and the first finding of soybean dwarf virus (SbDV) in the UK. While TuYV was not previously known to be present in UK peas, it was found in 13 of the 20 sites tested and was present at incidences up to 100%. Pea enation mosaic virus-1, pea enation mosaic virus-2, pea seed-borne mosaic virus, bean yellow mosaic virus, pea enation mosaic virus satellite RNA and turnip yellows virus associated RNA were also identified by HTS. Additionally, a subset of bulked samples were re-sequenced at greater depth to ascertain whether the relatively low depth of sequencing had missed any infections. In each case the same viruses were identified as had been identified using the lower sequencing depth. Sequencing of an isolate of pea seed-borne mosaic virus from 2007 also revealed the presence of TuYV and SbDV, showing that both viruses have been present in the UK for at least a decade, and represents the earliest whole genome of SbDV from Europe. This study demonstrates the potential of HTS to be used as a surveillance tool, or for crop-specific field survey, using a bulk sampling strategy combined with HTS and targeted diagnostics to indicate both presence and incidence of viruses in a crop.

Evaluation of sensitivity and specificity in RNA-Seq-based detection of grapevine viral pathogens

Virus detection is a crucial step for the implementation of clean stock programs that preserve healthy crop species. Viral infections in grapevine, a vegetatively propagated perennial crop, cannot be eradicated from the vineyards by the application of agrochemicals and must be curtailed at the stage of nursery production during the propagation of planting material. Viral detection is routinely performed using enzyme-linked immunosorbent assays (ELISA) or Reverse Transcription-quantitative Polymerase Chain Reactions (RT-qPCR). High throughput sequencing (HTS) approaches have the potential to detect all viral pathogens in a plant specimen. However, to date, no published HTS-based study has used threshold selection based on ROC curves for discriminating positive from negative samples. To fill this gap, we assessed the specificity and sensitivity of different sequencing and bioinformatics approaches for nine common viruses, which were tested in the same specimens using ELISA and/or RT-qPCR. The normalized detection thresholds giving the best results were 19.28 Fragments Per Kilobase of transcript per Million mapped reads (FPKM) for alignment-based total RNA-Seq approaches, 386 Reads Per Million mapped reads (RPM) for metagenomics-based total RNA-Seq, 1572 FPKM for alignment-based small RNA-Seq analysis and 0.97 % of contigs for de novo analysis of small RNA-Seq data. Validation of the proposed thresholds using independent specimens collected over time from the same stocks and other specimens collected from nearby stocks that had derived from the same propagating material showed that HTS approaches are accurate, with RNA-Seq approaches showing better performance than small RNA-Seq.

Interlaboratory Comparison Study on Ribodepleted Total RNA High-Throughput Sequencing for Plant Virus Diagnostics and Bioinformatic Competence

High-throughput sequencing (HTS) technologies and bioinformatic analyses are of growing interest to be used as a routine diagnostic tool in the field of plant viruses. The reliability of HTS workflows from sample preparation to data analysis and results interpretation for plant virus detection and identification must be evaluated (verified and validated) to approve this tool for diagnostics. Many different extraction methods, library preparation protocols, and sequence and bioinformatic pipelines are available for virus sequence detection. To assess the performance of plant virology diagnostic laboratories in using the HTS of ribosomal RNA depleted total RNA (ribodepleted totRNA) as a diagnostic tool, we carried out an interlaboratory comparison study in which eight participants were required to use the same samples, (RNA) extraction kit, ribosomal RNA depletion kit, and commercial sequencing provider, but also their own bioinformatics pipeline, for analysis. The accuracy of virus detection ranged from 65% to 100%. The false-positive detection rate was very low and was related to the misinterpretation of results as well as to possible cross-contaminations in the lab or sequencing provider. The bioinformatic pipeline used by each laboratory influenced the correct detection of the viruses of this study. The main difficulty was the detection of a novel virus as its sequence was not available in a publicly accessible database at the time. The raw data were reanalysed using Virtool to assess its ability for virus detection. All virus sequences were detected using Virtool in the different pools. This study revealed that the ribodepletion target enrichment for sample preparation is a reliable approach for the detection of plant viruses with different genomes. A significant level of virology expertise is needed to correctly interpret the results. It is also important to improve and complete the reference data.

HTS-Based Diagnostics of Sugarcane Viruses: Seasonal Variation and Its Implications for Accurate Detection

Rapid global germplasm trade has increased concern about the spread of plant pathogens and pests across borders that could become established, affecting agriculture and environment systems. Viral pathogens are of particular concern due to their difficulty to control once established. A comprehensive diagnostic platform that accurately detects both known and unknown virus species, as well as unreported variants, is playing a pivotal role across plant germplasm quarantine programs. Here we propose the addition of high-throughput sequencing (HTS) from total RNA to the routine quarantine diagnostic workflow of sugarcane viruses. We evaluated the impact of sequencing depth needed for the HTS-based identification of seven regulated sugarcane RNA/DNA viruses across two different growing seasons (spring and fall). Our HTS analysis revealed that viral normalized read counts (RPKM) was up to 23-times higher in spring than in the fall season for six out of the seven viruses. Random read subsampling analyses suggested that the minimum number of reads required for reliable detection of RNA viruses was 0.5 million, with a viral genome coverage of at least 92%. Using an HTS-based total RNA metagenomics approach, we identified all targeted viruses independent of the time of the year, highlighting that higher sequencing depth is needed for the identification of DNA viruses.

High-Throughput Sequencing of Small RNAs for the Sanitary Certification of Viruses in Grapevine

Biological indexing is the method generally recognized for the certification of propagative grapevines in many countries, and it is mandatory in the European Union. It consists of the evaluation of the plant material after grafting on indicators that are inspected for symptom development. This is a lengthy process that requires well-trained workers, testing field, etc. Alternative diagnostic methods such as serology and RT-qPCR have been discarded for certification because of their intrinsic drawbacks. In turn, high-throughput sequencing (HTS) of plant RNA has been proposed as a plausible alternative to bioassay, but before it is accepted, different aspects of this process must be evaluated. We have compared the HTS of small RNAs with bioassays and other diagnostic methods from a set of 40 grapevine plants submitted for certification. The results allowed the authors the identification of numerous grapevine viruses in the samples, as well as different variants. Besides, relationships between symptom expression and viromes were investigated, in particular leafroll-associated viruses. We compared HTS results using analytical and bioinformatics approaches in order to define minimum acceptable quality standards for certification schemes, resulting in a pipeline proposal. Finally, the comparison between HTS and bioassay resulted favorable for the former in terms of reliability, cost, and timing.

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.

TASPERT: Target-Specific Reverse Transcript Pools to Improve HTS Plant Virus Diagnostics

High-throughput sequencing (HTS) is becoming the new norm of diagnostics in plant quarantine settings. HTS can be used to detect, in theory, all pathogens present in any given sample. The technique’s success depends on various factors, including methods for sample management/preparation and suitable bioinformatic analysis. The Limit of Detection (LoD) of HTS for plant diagnostic tests can be higher than that of PCR, increasing the risk of false negatives in the case of low titer of the target pathogen. Several solutions have been suggested, particularly for RNA viruses, including rRNA depletion of the host, dsRNA, and siRNA extractions, which increase the relative pathogen titer in a metagenomic sample. However, these solutions are costly and time-consuming. Here we present a faster and cost-effective alternative method with lower HTS-LoD similar to or lower than PCR. The technique is called TArget-SPecific Reverse Transcript (TASPERT) pool. It relies on pathogen-specific reverse primers, targeting all RNA viruses of interest, pooled and used in double-stranded cDNA synthesis. These reverse primers enrich the sample for only pathogens of interest. Evidence on how TASPERT is significantly superior to oligodT, random 6-mer, and 20-mer in generating metagenomic libraries containing the pathogen of interest is presented in this proof of concept.

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.