Current impact and future directions of high throughput sequencing in plant virus diagnostics

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.

Mixed infection of two mandariviruses identified by high-throughput sequencing in Kinnow mandarin and development of their specific detection using duplex RT-PCR

In the current study, high-throughput sequencing (HTS) was used to identify viruses associated with the Kinnow mandarin (Citrus reticulata) plants exhibiting yellow vein clearing, mottling, and chlorosis symptoms at experimental farm of ICAR-Indian Agricultural Research Institute, New Delhi, India. During November 2022, leaf samples of symptomatic and asymptomatic Kinnow mandarin trees were collected, subjected to HTS and one of the representative symptomatic samples was subjected to leaf-dip electron microscopy (EM). In the EM results, flexuous virus particles typical of mandarivirus were observed. Ribosomal RNA was depleted from total RNA of pooled samples and RNA sequencing was done using NovaSeq 6000. Host unaligned reads were de novo assembled into contigs, which were annotated through BLASTn using database of plant viruses/viroids reference genomes (NCBI). Results of assembled contigs revealed near-complete genomes of two mandariviruses, i.e., citrus yellow vein clearing virus (CYVCV) and citrus yellow mottle-associated virus (CiYMaV). The values of fragments per kilo base transcript length per million fragments mapped estimation indicated the dominance of CYVCV in HTS data and it was also confirmed through krona plot distribution of viruses in the pooled samples. A rapid and reliable duplex RT-PCR assay was also developed and standardized for the simultaneous detection of both CYVCV and CiYMaV in a pooled Kinnow mandarin sample. The developed duplex RT-PCR was then validated for the presence of these viruses in individual Kinnow mandarin samples. The specificity and sensitivity results confirmed that primers were highly specific to their targets and able to detect viruses up to 10-2 dilutions of RNA in standard and duplex RT-PCR. Therefore, the developed rapid duplex RT-PCR can be used for virus indexing and production of virus-free Kinnow mandarin plants for certification programs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04011-9.

A review on endophytic fungi: a potent reservoir of bioactive metabolites with special emphasis on blight disease management

Phytopathogenic microorganisms have caused blight diseases that present significant challenges to global agriculture. These diseases result in substantial crop losses and have a significant economic impact. Due to the limitations of conventional chemical treatments in effectively and sustainably managing these diseases, there is an increasing interest in exploring alternative and environmentally friendly approaches for disease control. Using endophytic fungi as biocontrol agents has become a promising strategy in recent years. Endophytic fungi live inside plant tissues, forming mutually beneficial relationships, and have been discovered to produce a wide range of bioactive metabolites. These metabolites demonstrate significant potential for fighting blight diseases and provide a plentiful source of new biopesticides. In this review, we delve into the potential of endophytic fungi as a means of biocontrol against blight diseases. We specifically highlight their significance as a source of biologically active compounds. The review explores different mechanisms used by endophytic fungi to suppress phytopathogens. These mechanisms include competing for nutrients, producing antifungal compounds, and triggering plant defense responses. Furthermore, this review discusses the challenges of using endophytic fungi as biocontrol agents in commercial applications. It emphasizes the importance of conducting thorough research to enhance their effectiveness and stability in real-world environments. Therefore, bioactive metabolites from endophytic fungi have considerable potential for sustainable and eco-friendly blight disease control. Additional research on endophytes and their metabolites will promote biotechnology solutions.

Next Generation Sequencing, and Development of a Pipeline as a Tool for the Detection and Discovery of Citrus Pathogens to Facilitate Safer Germplasm Exchange

Citrus is affected by many diseases, and hence, the movement of citrus propagative materials is highly regulated in the USA. Currently used regulatory pathogen detection methods include biological and laboratory-based technologies, which are time-consuming, expensive, and have many limitations. There is an urgent need to develop alternate, rapid, economical, and reliable testing methods for safe germplasm exchange. Citrus huanglongbing (HLB) has devastated citrus industries leading to an increased need for germplasm exchanges between citrus growing regions for evaluating many potentially valuable hybrids for both HLB resistance and multilocational performance. In the present study, Next-Generation Sequencing (NGS) methods were used to sequence the transcriptomes of 21 test samples, including 15 well-characterized pathogen-positive plants. A workflow was designed in the CLC Genomics Workbench software, v 21.0.5 for bioinformatics analysis of the sequence data for the detection of pathogens. NGS was rapid and found to be a valuable technique for the detection of viral and bacterial pathogens, and for the discovery of new citrus viruses, complementary to the existing array of biological and laboratory assays. Using NGS methods, we detected beet western yellows virus, a newly reported citrus virus, and a variant of the citrus yellow vein-associated virus associated with the "fatal yellows" disease.

Viromes of Plants Determined by High-Throughput Sequencing of Virus-Derived siRNAs

Plants growing in open airfields can be infected by several viruses even as a multiple infection. Virus infection in crops can lead to a serious damage to the harvest. In addition, virus presence in grapevine, fruit trees, and tuberous vegetables, propagated vegetatively affects the phytosanitary status of the propagation material (both the rootstock and the variety) having profound effect on the lifetime and health of the new plantations. The fast evolution of sequencing techniques provides a new opportunity for metagenomics-based viral diagnostics. Small interfering (si) RNAs produced by the RNA silencing-based host immune system during viral infection can be sequenced by high-throughput techniques and analyzed for the presence of viruses, revealing the presence of all known viral pathogens in the sample and therefore opening new avenues in virus diagnostics. This method is based on Illumina sequencing and bioinformatics analysis of virus-derived siRNAs in the host. Here we describe a protocol for this challenging technique step by step with notes, to ensure success for every user.

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 .

Novel plant-associated genomoviruses from the Brazilian Cerrado biome

The discovery rate of new plant viruses has increased due to studies involving high-throughput sequencing (HTS), particularly for single-stranded DNA viruses of the family Genomoviridae. We carried out an HTS-based survey of genomoviruses in a wide range of native and exotic trees grown in the Brazilian Cerrado biome, and the complete genome sequences of two novel members of the family Genomoviridae from two distinct genera were determined. Specific primers were designed to detect these genomoviruses in individual samples. A new gemykolovirus (Tecoma stans associated gemykolovirus) was detected in Tecoma stans, and a new gemykibivirus (Ouratea duparquetiana associated gemykibivirus) was detected in Ouratea duparquetiana. A gemykrogvirus related to Gila monster associated gemykrogvirus (80% pairwise identity) was also detected in foliar samples of Trembleya parviflora. Our pilot study paves the way for a better characterization of this diverse collection of genomoviruses as well as their interactions with the associated tree species.

Mixed infections with new emerging viruses associated with jujube mosaic disease

BACKGROUND

Jujube is an economically important fruit tree and native to China. Viral disease is a new threat to jujube production, and several new viruses have been identified infecting jujube plants. During our field survey, jujube mosaic disease was widely distributed in Beijing, but the associated causal agents are still unknown.

METHODS

Small RNA deep sequencing was conducted to identify the candidate viruses associated with jujube mosaic. Further complete genome sequences of the viruses were cloned, and the genomic characterization of each virus was analyzed. The field distribution of these viruses was further explored with PCR/RT-PCR detection of field samples.

RESULTS

Mixed infection of four viruses was identified in a plant sample with the symptom of mosaic and leaf twisting, including the previously reported jujube yellow mottle-associated virus (JYMaV), persimmon ampelovirus (PAmpV), a new badnavirus tentatively named jujube-associated badnavirus (JaBV), and a new secovirus tentatively named jujube-associated secovirus (JaSV). PAmpV-jujube was 14,093 nt in length with seven putative open reading frames (ORFs) and shared highest (79.4%) nucleotide (nt) sequence identity with PAmpV PBs3. Recombination analysis showed that PAmpV-jujube was a recombinant originating from plum bark necrosis stem pitting-associated virus isolates nanjing (KC590347) and bark (EF546442). JaBV was 6449 bp in length with conserved genomic organization typical of badnaviruses. The conserved RT and RNAse H region shared highest 67.6% nt sequence identity with jujube mosaic-associated virus, which was below the 80% nt sequence identity value used as the species demarcation threshold in Badnavirus. The genome of JaSV composed of two RNA molecules of 5878 and 3337 nts in length, excluding the polyA tails. Each genome segment contained one large ORF that shared homology and phylogenetic identity with members of the family Secoviridae. Field survey showed JYMaV and JaBV were widely distributed in jujube trees in Beijing.

CONCLUSION

Two new viruses were identified from jujube plants, and mixed infections of JYMaV and JaBV were common in jujube in Beijing.

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.

Investigating Variability in Viral Presence and Abundance across Soybean Seed Development Stages Using Transcriptome Analysis

Plant transcriptomes offer a valuable resource for studying viral communities (viromes). In this study, we explore how plant transcriptome data can be applied to virome research. We analyzed 40 soybean transcriptomes across different growth stages and identified six viruses: broad bean wilt virus 2 (BBWV2), brassica yellow virus (BrYV), beet western yellow virus (BWYV), cucumber mosaic virus (CMV), milk vetch dwarf virus (MDV), and soybean mosaic virus (SMV). SMV was the predominant virus in both Glycine max (GM) and Glycine soja (GS) cultivars. Our analysis confirmed its abundance in both, while BBWV2 and CMV were more prevalent in GS than GM. The viral proportions varied across developmental stages, peaking in open flowers. Comparing viral abundance measured by viral reads and fragments per kilobase of transcript per million (FPKM) values revealed insights. SMV showed similar FPKM values in GM and GS, but BBWV2 and CMV displayed higher FPKM proportions in GS. Notably, the differences in viral abundance between GM and GS were generally insignificant based on the FPKM values across developmental stages, except for the apical bud stage in four GM cultivars. We also detected MDV, a multi-segmented virus, in two GM samples, with variable proportions of its segments. In conclusion, our study demonstrates the potential of plant transcriptomes for virome research, highlighting their strengths and limitations.

Going beyond consensus genome sequences: An innovative SNP-based methodology reconstructs different Ugandan cassava brown streak virus haplotypes at a nationwide scale in Rwanda

Cassava Brown Streak Disease (CBSD), which is caused by cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), represents one of the most devastating threats to cassava production in Africa, including in Rwanda where a dramatic epidemic in 2014 dropped cassava yield from 3.3 million to 900,000 tonnes (1). Studying viral genetic diversity at the genome level is essential in disease management, as it can provide valuable information on the origin and dynamics of epidemic events. To fill the current lack of genome-based diversity studies of UCBSV, we performed a nationwide survey of cassava ipomovirus genomic sequences in Rwanda by high-throughput sequencing (HTS) of pools of plants sampled from 130 cassava fields in thirteen cassava-producing districts, spanning seven agro-ecological zones with contrasting climatic conditions and different cassava cultivars. HTS allowed the assembly of a nearly complete consensus genome of UCBSV in twelve districts. The phylogenetic analysis revealed high homology between UCBSV genome sequences, with a maximum of 0.8 per cent divergence between genomes at the nucleotide level. An in-depth investigation based on Single Nucleotide Polymorphisms (SNPs) was conducted to explore the genome diversity beyond the consensus sequences. First, to ensure the validity of the result, a panel of SNPs was confirmed by independent reverse transcription polymerase chain reaction (RT-PCR) and Sanger sequencing. Furthermore, the combination of fixation index (FST) calculation and Principal Component Analysis (PCA) based on SNP patterns identified three different UCBSV haplotypes geographically clustered. The haplotype 2 (H2) was restricted to the central regions, where the NAROCAS 1 cultivar is predominantly farmed. RT-PCR and Sanger sequencing of individual NAROCAS1 plants confirmed their association with H2. Haplotype 1 was widely spread, with a 100 per cent occurrence in the Eastern region, while Haplotype 3 was only found in the Western region. These haplotypes' associations with specific cultivars or regions would need further confirmation. Our results prove that a much more complex picture of genetic diversity can be deciphered beyond the consensus sequences, with practical implications on virus epidemiology, evolution, and disease management. Our methodology proposes a high-resolution analysis of genome diversity beyond the consensus between and within samples. It can be used at various scales, from individual plants to pooled samples of virus-infected plants. Our findings also showed how subtle genetic differences could be informative on the potential impact of agricultural practices, as the presence and frequency of a virus haplotype could be correlated with the dissemination and adoption of improved cultivars.

Infection Defects of RNA and DNA Viruses Induced by Antiviral RNA Interference

Immune recognition of viral genome-derived double-stranded RNA (dsRNA) molecules and their subsequent processing into small interfering RNAs (siRNAs) in plants, invertebrates, and mammals trigger specific antiviral immunity known as antiviral RNA interference (RNAi). Immune sensing of viral dsRNA is sequence-independent, and most regions of viral RNAs are targeted by virus-derived siRNAs which extensively overlap in sequence. Thus, the high mutation rates of viruses do not drive immune escape from antiviral RNAi, in contrast to other mechanisms involving specific virus recognition by host immune proteins such as antibodies and resistance (R) proteins in mammals and plants, respectively. Instead, viruses actively suppress antiviral RNAi at various key steps with a group of proteins known as viral suppressors of RNAi (VSRs). Some VSRs are so effective in virus counter-defense that potent inhibition of virus infection by antiviral RNAi is undetectable unless the cognate VSR is rendered nonexpressing or nonfunctional. Since viral proteins are often multifunctional, resistance phenotypes of antiviral RNAi are accurately defined by those infection defects of VSR-deletion mutant viruses that are efficiently rescued by host deficiency in antiviral RNAi. Here, we review and discuss in vivo infection defects of VSR-deficient RNA and DNA viruses resulting from the actions of host antiviral RNAi in model systems.

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.

Combining micro- and portable-XRF as a tool for fast identification of virus infections in plants: The case study of ASa-Virus in Fraxinus ornus L

Plant viruses can affect micro- and macro-nutrients homeostasis in woody plants, with fluctuation in the concentration of some elements at the leaf level due to the pathogen activity and/or the plant physiological response to the infection.Leaves of Fraxinus ornus L. (flowering ash) were sampled for three consecutive years in the city of Hamburg (Germany), from both trees showing the typical symptoms of the ash shoestring associated virus infection (ASaV+) and healthy trees (ASaV-). Such leaves were analyzed by μ-XRF, using both laboratory and synchrotron X-ray sources, and large differences between symptomatic and not symptomatic leaves were observed: ASaV+ samples showed uneven element distribution and regions of the lamina with severe depletions of P, S, and Ca. Differently, K appeared more concentrated. Thus, 139 leaflets sampled from various healthy and infected ash trees over the three-year period were analyzed for K and Ca concentration with a portable XRF instrument. We found that the K:Ca concentration ratio was always significantly higher in ASaV+ samples, and this trend was verified for all the samplings over the tree years. We conclude that the K:Ca ratio parameter has potential in the frame of trendsetting diagnostics and could be used, together with visual symptoms, for a rapid, non-destructive, on-site and cheap indirect ASaV detection.

Transgene Silencing, RNA Interference, and the Antiviral Defense Mechanism Directed by Small Interfering RNAs

One important discovery in plant pathology over recent decades is the natural antiviral defense mechanism mediated by RNA interference (RNAi). In antiviral RNAi, virus infection triggers Dicer processing of virus-specific double-stranded RNA into small interfering RNAs (siRNAs). Frequently, further amplified by host enzyme and cofactors, these virus-derived siRNAs direct specific virus clearance in an Argonaute protein-containing effector complex. The siRNAs derived from viruses and viroids accumulate to very high levels during infection. Because they overlap extensively in nucleotide sequence, this allows for deep sequencing and bioinformatics assembly of total small RNAs for rapid discovery and identification of viruses and viroids. Antiviral RNAi acts as the primary defense mechanism against both RNA and DNA viruses in plants, yet viruses still successfully infect plants. They do so because all currently recognized plant viruses combat the RNAi response by encoding at least one protein as a viral suppressor of RNAi (VSR) required for infection, even though plant viruses have small genome sizes with a limited coding capacity. This review article will recapitulate the key findings that have revealed the genetic pathway for the biogenesis and antiviral activity of viral siRNAs and the specific role of VSRs in infection by antiviral RNAi suppression. Moreover, early pioneering studies on transgene silencing, RNAi, and virus-plant/virus-virus interactions paved the road to the discovery of antiviral RNAi.

Translating virome analyses to support biosecurity, on-farm management, and crop breeding

Virome analysis via high-throughput sequencing (HTS) allows rapid and massive virus identification and diagnoses, expanding our focus from individual samples to the ecological distribution of viruses in agroecological landscapes. Decreases in sequencing costs combined with technological advances, such as automation and robotics, allow for efficient processing and analysis of numerous samples in plant disease clinics, tissue culture laboratories, and breeding programs. There are many opportunities for translating virome analysis to support plant health. For example, virome analysis can be employed in the development of biosecurity strategies and policies, including the implementation of virome risk assessments to support regulation and reduce the movement of infected plant material. A challenge is to identify which new viruses discovered through HTS require regulation and which can be allowed to move in germplasm and trade. On-farm management strategies can incorporate information from high-throughput surveillance, monitoring for new and known viruses across scales, to rapidly identify important agricultural viruses and understand their abundance and spread. Virome indexing programs can be used to generate clean germplasm and seed, crucial for the maintenance of seed system production and health, particularly in vegetatively propagated crops such as roots, tubers, and bananas. Virome analysis in breeding programs can provide insight into virus expression levels by generating relative abundance data, aiding in breeding cultivars resistant, or at least tolerant, to viruses. The integration of network analysis and machine learning techniques can facilitate designing and implementing management strategies, using novel forms of information to provide a scalable, replicable, and practical approach to developing management strategies for viromes. In the long run, these management strategies will be designed by generating sequence databases and building on the foundation of pre-existing knowledge about virus taxonomy, distribution, and host range. In conclusion, virome analysis will support the early adoption and implementation of integrated control strategies, impacting global markets, reducing the risk of introducing novel viruses, and limiting virus spread. The effective translation of virome analysis depends on capacity building to make benefits available globally.

Arabidopsis latent virus 1, a comovirus widely spread in Arabidopsis thaliana collections

Transcriptome studies of Illumina RNA-Seq datasets of different Arabidopsis thaliana natural accessions and T-DNA mutants revealed the presence of two virus-like RNA sequences which showed the typical two-segmented genome characteristics of a comovirus. This comovirus did not induce any visible symptoms in infected A. thaliana plants cultivated under standard laboratory conditions. Hence it was named Arabidopsis latent virus 1 (ArLV1). Virus infectivity in A. thaliana plants was confirmed by quantitative reverse transcription polymerase chain reaction, transmission electron microscopy and mechanical inoculation. Arabidopsis latent virus 1 can also mechanically infect Nicotiana benthamiana, causing distinct mosaic symptoms. A bioinformatics investigation of A. thaliana RNA-Seq repositories, including nearly 6500 Sequence Read Archives (SRAs) in the NCBI SRA database, revealed the presence of ArLV1 in 25% of all archived natural A. thaliana accessions and in 8.5% of all analyzed SRAs. Arabidopsis latent virus 1 could also be detected in A. thaliana plants collected from the wild. Arabidopsis latent virus 1 is highly seed-transmissible with up to 40% incidence on the progeny derived from infected A. thaliana plants. This has probably led to a worldwide distribution in the model plant A. thaliana with as yet unknown effects on plant performance in a substantial number of studies.

Identification of Seven Additional Genome Segments of Grapevine-Associated Jivivirus 1

Jiviruses are a group of recently described viruses characterized with a tripartite genome and having affinities with Virgaviridae (RNA1 and 2) and Flaviviridae (RNA3). Using a combination of high-throughput sequencing, datamining and RT-PCR approaches, we demonstrate here that in grapevine samples infected by grapevine-associated jivivirus 1 (GaJV-1) up to 7 additional molecules can be consistently detected with conserved 5' and 3' non-coding regions in common with the three previously identified GaJV-1 genomic RNAs. RNA4, RNA5, RNA6, RNA7, RNA8 and RNA10, together with a recombinant RNArec7-8, are all members of a family sharing a previously non recognized conserved protein domain, while RNA9 is part of a distinct family characterized by another conserved motif. Datamining of pecan (Carya illinoinensis) public transcriptomic data allowed the identification of two further jiviviruses and the identification of supplementary genomic RNAs with homologies to those of GaJV-1. Taken together, these results reshape our vision of the divided genome of jiviviruses and raise novel questions about the function(s) of the proteins encoded by jiviviruses supplementary RNAs.

Evolution and Phylogeny of Soybean Mosaic Virus Based on 143 Complete Genomes

Soybean mosaic virus (SMV) of the genus Potyvirus is an important virus in cultivated soybeans. Here, we obtained 7 SMV genomes from soybean germplasms using RNA sequencing and conducted a comprehensive evolutionary and phylogenetic study of 143 SMV genomes derived from 10 plant species and 12 countries. The phylogenetic tree we constructed using coding DNA sequences revealed the existence of nine clades of SMV isolates/strains. Recombination analysis revealed 76 recombinant events and 141 recombinants in total. Clades 1 and 3 contain the most common SMV pathotypes, including G1 through G7, which are distributed worldwide. Clade 2 includes several Chinese SMV pathotypes. The SMV isolates were further divided into two groups. The SMV isolates in the first group, including clades 8 and 9, were identified from Pinellia and Atractylodes species, whereas those in the second group (clades 1 through 7) were mostly found in cultivated soybeans. The SMV polyprotein undergoes positive selection, whereas most mature proteins, except for the P1 protein, undergo negative selection. The P1 protein of SMV isolates in group 1 may be highly correlated with host adaptation. This study provides strong evidence that recombination and plant hosts are powerful forces driving the genetic diversity of the SMV genome.

CRISPR/Cas technology: Opportunities for phytopathogenic viruses detection

Detection and monitoring of viruses are essential for healthy plants and prosperity. Recent development in CRISPR/Cas system in diagnosis has open an avenue well suited for pathogen detection. Variety of CRISPR associated proteins are being discovered, suggesting array of application and detection strategies in diagnosis. Phytopathogenic viruses are diverse with respect to their nucleic acid compositions, which presents a challenge in developing a single device applicable for almost all viruses. The review describes about the efficient use of CRISPR/Cas Technology in diagnosis, such as SHERLOCK, DETECTR and SATORI. These methods are different in their characteristic to identify specific nucleic acids and processing the detectable signals. These technologies are in their infancy and lot of scope is there to develop commercial kits. Plant tissue culture-based industries, climate control green houses, indoor cultivation facilities etc. has been considered as few examples. This review will be beneficial for researchers seeking to develop detection mechanism based on CRISPR/Cas technology. The outcome in the form of cost-effective detection of viruses will be boon for agro-based industries, which are facing challenges through virus contamination.

Phylogenetic and Phylodynamic Analyses of Soybean Mosaic Virus Using 305 Coat Protein Gene Sequences

Soybean mosaic virus (SMV) of the family Potyviridae is the most devastating virus that infects soybean plants. In this study, we obtained 83 SMV coat protein (CP) sequences from seven provinces in Korea using RT-PCR and Sanger sequencing. Phylogenetic and haplotype analyses revealed eight groups of 83 SMV isolates and a network of 50 SMV haplotypes in Korea. The phylogenetic tree using 305 SMV CP sequences available worldwide revealed 12 clades that were further divided into two groups according to the plant hosts. Recombination rarely occurred in the CP sequences, while negative selection was dominant in the SMV CP sequences. Genetic diversity analyses revealed that plant species had a greater impact on the genetic diversity of SMV CP sequences than geographical origin or location. SMV isolates identified from Pinellia species in China showed the highest genetic diversity. Phylodynamic analysis showed that the SMV isolates between the two Pinellia species diverged in the year 1248. Since the divergence of the first SMV isolate from Glycine max in 1486, major clades for SMV isolates infecting Glycine species seem to have diverged from 1791 to 1886. Taken together, we provide a comprehensive overview of the genetic diversity and divergence of SMV CP sequences.

Detection and discovery of plant viruses in soybean by metagenomic sequencing

BACKGROUND

Viruses negatively impact soybean production by causing diseases that affect yield and seed quality. Newly emerging or re-emerging viruses can also threaten soybean production because current control measures may not be effective against them. Furthermore, detection and characterization of new plant viruses requires major efforts when no sequence or antibody-based resources are available.

METHODS

In this study, soybean fields were scouted for virus-like disease symptoms during the 2016-2019 growing seasons. Total RNA was extracted from symptomatic soybean parts, cDNA libraries were prepared, and RNA sequencing was performed using high-throughput sequencing (HTS). A custom bioinformatic workflow was used to identify and assemble known and unknown virus genomes.

RESULTS

Several viruses were identified in single or mixed infections. Full- or nearly full-length genomes were generated for tobacco streak virus (TSV), alfalfa mosaic virus (AMV), tobacco ringspot virus (TRSV), soybean dwarf virus (SbDV), bean pod mottle virus (BPMV), soybean vein necrosis virus (SVNV), clover yellow vein virus (ClYVV), and a novel virus named soybean ilarvirus 1 (SIlV1). Two distinct ClYVV isolates were recovered, and their biological properties were investigated in Nicotiana benthamiana, broad bean, and soybean. In addition to infections by individual viruses, we also found that mixed viral infections in various combinations were quite common.

CONCLUSIONS

Taken together, the results of this study showed that HTS-based technology is a valuable diagnostic tool for the identification of several viruses in field-grown soybean and can provide rapid information about expected viruses as well as viruses that were previously not detected in soybean.

Viruses of Yams (Dioscorea spp.): Current Gaps in Knowledge and Future Research Directions to Improve Disease Management

Viruses are a major constraint for yam production worldwide. They hamper the conservation, movement, and exchange of yam germplasm and are a threat to food security in tropical and subtropical areas of Africa and the Pacific where yam is a staple food and a source of income. However, the biology and impact of yam viruses remains largely unknown. This review summarizes current knowledge on yam viruses and emphasizes gaps that exist in the knowledge of the biology of these viruses, their diagnosis, and their impact on production. It provides essential information to inform the implementation of more effective virus control strategies.

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.

Risk factors associated with cassava brown streak disease dissemination through seed pathways in Eastern D.R. Congo

Vegetatively propagated crops are particularly prone to disease dissemination through their seed systems. Strict phytosanitary measures are important to limit the impact of diseases as illustrated by the potato seed system in Europe. Cassava brown streak disease (CBSD) is a devastating disease caused by two viral species collectively named cassava brown streak viruses (CBSVs). CBSD can cause substantial root yield losses of up to 100% in the worst affected areas and is easily transmitted through stem cuttings. In Eastern and Central Africa, the epidemiology of CBSVs in the local socio-economical context of production remains poorly known while a better understanding would be an asset to properly manage the disease. This lack of information explains partially the limited efficiency of current regulatory schemes in increasing the availability of quality seed to smallholders and mitigating the spread of pests and diseases. This study surveyed the epidemiology of CBSVs in Uvira territory, Eastern D.R. Congo, and its drivers using a multivariate approach combining farmer's interview, field observation, sampling and molecular detection of CBSVs. Investigation on the epidemiology of CBSD revealed that three clusters in the study area could be identified using five most significant factors: (i) symptoms incidence, (ii) number of whiteflies, (iii) types of foliar symptoms, (iv) cutting's pathways and (v) plant age. Among the three clusters identified, one proved to be potentially interesting for seed multiplication activities since the disease pressure was the lowest. Through risk assessment, we also identified several key socio-economic determinants on disease epidemy: (i) factors related to farmer's knowledge and awareness (knowledge of cassava pests and diseases, knowledge of management practices, support from extension services and management strategies applied), (ii) factors related to the geographical location of farmer's fields (proximity to borders, proximity to town, distance to acquire cuttings), as well as (iii) the pathways used to acquire cuttings.

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.

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.

Metatranscriptomic Analysis of Plant Viruses in Imported Pear and Kiwifruit Pollen

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

Discovery and Genomic Function of a Novel Rice Dwarf-Associated Bunya-like Virus

Bunyaviruses cause diseases in vertebrates, arthropods, and plants. Here, we used high-throughput RNA-seq to identify a bunya-like virus in rice plants showing the dwarfing symptom, which was tentatively named rice dwarf-associated bunya-like virus (RDaBV). The RDaBV genome consists of L, M, and S segments. The L segment has 6562 nt, and encodes an RdRp with a conserved Bunya_RdRp super family domain. The M segment has 1667 nt and encodes a nonstructural protein (NS). The complementary strand of the 1120 nt S segment encodes a nucleocapsid protein (N), while its viral strand encodes a small nonstructural protein (NSs). The amino acid (aa) sequence identities of RdRp, NS, and N between RDaBV and viruses from the family Discoviridae were the highest. Surprisingly, the RDaBV NSs protein did not match any viral proteins. Phylogenetic analysis based on RdRp indicated that RDaBV is evolutionarily close to viruses in the family Discoviridae. The PVX-expressed system indicated that RDaBV N and NS may be symptom determinants of RDaBV. Our movement complementation and callose staining experiment results confirmed that RDaBV NSs is a viral movement protein in plants, while an agro-infiltration experiment found that RDaBV NS is an RNA silencing suppressor. Thus, we determined that RDaBV is a novel rice-infecting bunya-like virus.

From Metagenomics to Discovery of New Viral Species: Galium Leaf Distortion Virus, a Monopartite Begomovirus Endemic in Mexico

Begomoviruses (Family Geminiviridae) are a major group of emerging plant viruses worldwide. The knowledge of begomoviruses is mostly restricted to crop plant systems. Nevertheless, it has been described that non-cultivated plants are important reservoirs and vessels of viral evolution that leads to the emergence of new diseases. High-throughput sequencing (HTS) has provided a powerful tool for speeding up the understanding of molecular ecology and epidemiology of plant virome and for discovery of new viral species. In this study, by performing earlier metagenomics library data mining, followed by geminivirus-related signature single plant searching and RCA-based full-length viral genome cloning, and based on phylogenetic analysis, genomes of two isolates of a novel monopartite begomovirus species tentatively named Galium leaf distortion virus (GLDV), which infects non-cultivated endemic plant Galium mexicanum, were identified in Colima, Mexico. Analysis of the genetic structure of both isolates (GLDV-1 and GLDV-2) revealed that the GLDV genome displays a DNA-A-like structure shared with the new world (NW) bipartite begomoviruses. Nonetheless, phylogenetic analysis using representative members of the main begomovirus American clades for tree construction grouped both GLDV isolates in a clade of the monopartite NW begomovirus, Tomato leaf deformation virus (ToLDeV). A comparative analysis of viral replication regulatory elements showed that the GLDV-1 isolate possesses an array and sequence conservation of iterons typical of NW begomovirus infecting the Solanaceae and Fabaceae families. Interestingly, GLDV-2 showed iteron sequences described only in monopartite begomovirus from OW belonging to a sweepovirus clade that infects plants of the Convolvulaceae family. In addition, the rep iteron related-domain (IRD) of both isolates display FRVQ or FRIS amino acid sequences corresponding to NW and sweepobegomovirus clades for GMV-1 and GMV-2, respectively. Finally, the lack of the GLDV DNA-B segment (tested by molecular detection and biological assays using GLDV-1/2 infectious clones) confirmed the monopartite nature of GLDV. This is the first time that a monopartite begomovirus is described in Mexican ecosystems, and “in silico” geometagenomics analysis indicates that it is restricted to a specific region. These data revealed additional complexity in monopartite begomovirus genetics and geographic distribution and highlighted the importance of metagenomic approaches in understanding global virome ecology and evolution.

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.

Viruses Infecting Trees and Herbs That Produce Edible Fleshy Fruits with a Prominent Value in the Global Market: An Evolutionary Perspective

Trees and herbs that produce fruits represent the most valuable agricultural food commodities in the world. However, the yield of these crops is not fully achieved due to biotic factors such as bacteria, fungi, and viruses. Viruses are capable of causing alterations in plant growth and development, thereby impacting the yield of their hosts significantly. In this work, we first compiled the world's most comprehensive list of known edible fruits that fits our definition. Then, plant viruses infecting those trees and herbs that produce fruits with commercial importance in the global market were identified. The identified plant viruses belong to 30 families, most of them containing single-stranded RNA genomes. Importantly, we show the overall picture of the host range for some virus families following an evolutionary approach. Further, the current knowledge about plant-virus interactions, focusing on the main disorders they cause, as well as yield losses, is summarized. Additionally, since accurate diagnosis methods are of pivotal importance for viral diseases control, the current and emerging technologies for the detection of these plant pathogens are described. Finally, the most promising strategies employed to control viral diseases in the field are presented, focusing on solutions that are long-lasting.

Diagnosis of Viral Diseases Using Deep Sequencing and Metagenomics Analyses

Viruses are ubiquitous in nature and exist in a variety of habitats. The advancement in sequencing technologies has revolutionized the understanding of viral biodiversity associated with plant diseases. Deep sequencing combined with metagenomics is a powerful approach that has proven to be revolutionary in the last decade and involves the direct analysis of viral genomes present in a diseased tissue sample. This protocol describes the details of RNA extraction and purification from wild rice plant and their yield, RNA purity, and integrity assessment. As a final step, bioinformatics data analysis including demultiplexing, quality control, de novo transcriptome assembly, taxonomic allocation and read mapping following Illumina HiSeq small and total RNA sequencing are described. Furthermore, the total RNAs extraction protocol and an additional ribosomal rRNAs depletion step which are significantly important for viral genomes construction are provided.

High-Throughput Sequencing of Small RNAs for Diagnostics of Grapevine Viruses and Viroids in Russia

The use of high-throughput sequencing (HTS) technology has led to significant progress in the identification of many viruses and their genetic variants. In this study, we used the HTS platform to sequence small RNAs (sRNAs) of grapevine to study the virome. Isolation of RNA was performed using symptomatic grapevines collected from commercial vineyards in Krasnodar Krai in 2017-2018. To determine the viromes of vineyards, we used an integrated approach that included a bioinformatic analysis of the results of sRNA HTS and the molecular method RT-PCR, which made it possible to identify 13 viruses and 4 viroids. Grapevine leafroll-associated virus 4 (GLRaV-4), Grapevine Syrah Virus-1 (GSyV-1), Raspberry bushy dwarf virus (RBDV), Australian grapevine viroid (AGVd), and Grapevine yellow speckle viroid 2 (GYSVd-2) were identified for the first time in Russia. Out of 38 samples analyzed, 37 had mixed infections with 4-11 viruses, indicating a high viral load. Analysis of the obtained sequences of fragments of virus genomes made it possible to identify recombination events in GLRaV-1, GLRaV-2, GLRaV-3, GLRaV-4, GVT, GPGV, GRSPaV, GVA, and GFLV. The obtained results indicate a wide spread of the viruses and a high genetic diversity in the vineyards of Krasnodar Krai and emphasize the urgent need to develop and implement long-term strategies for the control of viral grapevine diseases.

Small RNA and Transcriptome Sequencing of a Symptomatic Peony Plant Reveals Mixed Infections with Novel Viruses

To identify the viruses in tree peony plants associated with the symptoms of yellowing, leaf rolling, stunted growth, and decline, high-throughput sequencing of small RNA and mRNA was conducted from a single symptomatic plant. Bioinformatic analyses and reconstruction of viral genomes indicated mixed viral infections involving cycas necrotic stunt virus, apple stem grooving virus, lychnis mottle virus, grapevine line pattern virus, and three new viruses designated as peony yellowing-associated citrivirus (PYaCV, Citrivirus in Betaflexiviridae), peony betaflexivirus 1 (PeV1, unclassified in Betaflexiviridae), and peony leafroll-associated virus (PLRaV, Ampelovirus in Closteroviridae). PYaCV was 8,666 nucleotides (nt) in length, comprising three open reading frames (ORFs), and shared 63.8 to 75.9% nt sequence identity with citrus leaf blotch virus (CLBV) isolates. However, the ORF encoding the replication-associated protein (REP) shared 57 and 52% sequence identities at the nt and amino acid (aa) level, respectively, with other reported CLBV isolates, which were below the criterion for species classification within the family Betaflexiviridae. Recombination analysis identified putative recombination sites in PYaCV, which originated from CLBV. PeV1, only identified from the transcriptome data, was 8,124 nt in length, with five ORFs encoding the REP (ORF1), triple gene block (ORF2 to 4) and coat protein (CP, ORF5). Phylogenetic analysis and sequence comparison showed that PeV1 clustered with an unassigned member, the garlic yellow mosaic-associated virus within the Betaflexiviridae family, into a separate clade. Partial genome sequence analysis of PLRaV (12,545 nt) showed it contained seven ORFs encoding the partial polyprotein 1a, the RNA-dependent RNA polymerase (RdRp), two small hydrophobic proteins p11 and p6, HSP70h, p55, and a CP duplicate, which shared low aa sequence identity with Closteroviridae family members. Phylogenetic analysis based on the aa sequences of RdRp or HSP70h indicated that PLRaV clustered with grapevine leafroll-associated virus 1 (GLRaV-1) and GLRaV-13 in the Ampelovirus genus. Field investigation confirmed the wide distribution of these viruses, causing mixed infections of peony plants in Beijing.

A Novel Rice Curl Dwarf-Associated Picornavirus Encodes a 3C Serine Protease Recognizing Uncommon EPT/S Cleavage Sites

Picornaviruses cause diseases in a wide range of vertebrates, invertebrates and plants. Here, a novel picornavirus was identified by RNA-seq technology from rice plants showing dwarfing and curling symptoms, and the name rice curl dwarf-associated virus (RCDaV) is tentatively proposed. The RCDaV genome consists of an 8,987 nt positive-stranded RNA molecule, excluding a poly(A) tail, that encodes two large polyproteins. Using in vitro cleavage assays, we have identified that the RCDaV 3C protease (3Cpro) as a serine protease recognizes the conserved EPT/S cleavage site which differs from the classic Q(E)/G(S) sites cleaved by most picornaviral 3C chymotrypsin-like cysteine proteases. Therefore, we comprehensively deciphered the RCDaV genome organization and showed that the two polyproteins of RCDaV can be cleaved into 12 mature proteins. We found that seven unclassified picornaviruses also encode a 3Cpro similar to RCDaV, and use the highly conserved EPT/S as the cleavage site. The precise genome organizations of these viruses were illustrated. Moreover, RCDaV and the seven unclassified picornaviruses share high sequence identities and similar genome organizations, and cluster into a distinct clade in the order Picornavirales. Our study provides valuable information for the understanding of picornaviral 3Cpros, deciphers the genome organization of a few relatively obscure picornaviruses, and lays the foundation for further pathogenesis research on these viruses.

Contribution of historical herbarium small RNAs to the reconstruction of a cassava mosaic geminivirus evolutionary history

Emerging viral diseases of plants are recognised as a growing threat to global food security. However, little is known about the evolutionary processes and ecological factors underlying the emergence and success of viruses that have caused past epidemics. With technological advances in the field of ancient genomics, it is now possible to sequence historical genomes to provide a better understanding of viral plant disease emergence and pathogen evolutionary history. In this context, herbarium specimens represent a valuable source of dated and preserved material. We report here the first historical genome of a crop pathogen DNA virus, a 90-year-old African cassava mosaic virus (ACMV), reconstructed from small RNA sequences bearing hallmarks of small interfering RNAs. Relative to tip-calibrated dating inferences using only modern data, those performed with the historical genome yielded both molecular evolution rate estimates that were significantly lower, and lineage divergence times that were significantly older. Crucially, divergence times estimated without the historical genome appeared in discordance with both historical disease reports and the existence of the historical genome itself. In conclusion, our study reports an updated time-frame for the history and evolution of ACMV and illustrates how the study of crop viral diseases could benefit from natural history collections.

Virus diversity in metagenomes of a lichen symbiosis (Umbilicaria phaea): complete viral genomes, putative hosts and elevational distributions

Viruses can play critical roles in symbioses by initiating horizontal gene transfer, affecting host phenotypes, or expanding their host's ecological niche. However, knowledge of viral diversity and distribution in symbiotic organisms remains elusive. Here we use deep-sequenced metagenomic DNA (PacBio Sequel II; two individuals), paired with a population genomics approach (Pool-seq; 11 populations, 550 individuals) to understand viral distributions in the lichen Umbilicaria phaea. We assess (i) viral diversity in lichen thalli, (ii) putative viral hosts (fungi, algae, bacteria) and (iii) viral distributions along two replicated elevation gradients. We identified five novel viruses, showing 28%-40% amino acid identity to known viruses. They tentatively belong to the families Caulimoviridae, Myoviridae, Podoviridae and Siphoviridae. Our analysis suggests that the Caulimovirus is associated with green algal photobionts (Trebouxia) of the lichen, and the remaining viruses with bacterial hosts. We did not detect viral sequences in the mycobiont. Caulimovirus abundance decreased with increasing elevation, a pattern reflected by a specific algal lineage hosting this virus. Bacteriophages showed population-specific patterns. Our work provides the first comprehensive insights into viruses associated with a lichen holobiont and suggests an interplay of viral hosts and environment in structuring viral distributions.

Detection of Four New Tomato Viruses in Serbia Using Post Hoc High-Throughput Sequencing Analysis of Samples From a Large-Scale Field Survey

Tomato production worldwide is affected by numerous plant virus species. The early and accurate detection of viruses is a critical step for disease control. However, the simultaneous detection of the most known tomato viruses can be difficult because of the high number and diversity of tomato-infecting viruses. Here, we have identified four new viruses in Serbia by applying target-independent small RNA high-throughput sequencing (HTS). HTS was applied on pools of samples and separate samples, in total comprising 30 tomato samples that exhibited (severe) virus-like symptoms and were collected in Serbia during three annual surveys (2011 to 2013). These samples had previously tested negative for the presence of 16 tomato viruses using targeted detection methods. Three divergent complete genome sequences of Physostegia chlorotic mottled virus were obtained from different localities, indicating for the first time that this virus is widespread in Serbia and might represent an emergent viral pathogen of tomato. The tomato torrado virus was detected at one locality with devastating yield losses. The southern tomato virus was detected at two localities, and the spinach latent virus was detected at one locality. In addition, we detected the presence of one already-known virus in Serbia, the tomato spotted wilt orthotospovirus. All the HTS results were subsequently confirmed by targeted detection methods. In this study, the successful application of post hoc HTS testing of a limited number of pooled samples resulted in the discovery of new viruses. Thus, our results encourage the use of HTS in research and diagnostic laboratories, including laboratories that have limited resources to resolve disease etiology.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Complete genome sequence of a new isolate of caper latent virus in caper

The genome of a new carlavirus isolate from asymptomatic wild Capparis spinosa L. plants in Sicily was sequenced via high-throughput sequencing (HTS) and 5'/3' RACE experiments. The complete genomic sequence was found to be 8,280 nt in length, excluding the poly(A) tail, and contained five putative open reading frames (ORFs). Molecular characterization revealed a close relationship to caper latent virus (CapLV), with 87% and 90% nucleotide sequence identity to available partial sequences of the ORFs encoding the replicase and coat protein of that virus. According to the molecular criteria for species demarcation, which is based on the ORF-1- and ORF-5-encoded proteins, the virus characterized in this study could be considered a variant of CapLV, and we have thus designated it as CapLV-W.

Spatial Virome Analysis of Zanthoxylum armatum Trees Affected With the Flower Yellowing Disease

Zanthoxylum armatum is an important woody crop with multiple applications in pharmaceutics, cosmetics, and food industries. With continuous increases in the plantation area, integrated pest management is required for scale production when diseases caused by biotic factors such as pests and pathogens have become new problems, one of which is the infectious flower yellowing disease (FYD). Here, isolates of a new illarvirus (3) and a new nepovirus-associated subviral satellite RNA (12) were identified in Z. armatum, in addition to 38 new isolates of four previously reported RNA viruses. Sequence variation can be observed in viral/subviral quasispecies and among predominant isolates from the same or different samples and geographic origins. Intriguingly, RNA sequencing of different diseased trees invariably showed an extraordinary pattern of particularly high reads accumulation of the green Sichuan pepper-nepovirus (GSPNeV) and the satellite RNA in symptomatic tissues. In addition, we also examined small RNAs of the satellite RNA, which show similar patterns to those of coinfecting viruses. This study provides further evidence to support association of the FYD with viral/subviral infections and deepens our understanding of the diversity and molecular characteristics of the viruses and satellite, as well as their interactions with the host.

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.

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

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

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

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

Virus Detection: A Review of the Current and Emerging Molecular and Immunological Methods

Viruses are ubiquitous in the environment. While many impart no deleterious effects on their hosts, several are major pathogens. This risk of pathogenicity, alongside the fact that many viruses can rapidly mutate highlights the need for suitable, rapid diagnostic measures. This review provides a critical analysis of widely used methods and examines their advantages and limitations. Currently, nucleic-acid detection and immunoassay methods are among the most popular means for quickly identifying viral infection directly from source. Nucleic acid-based detection generally offers high sensitivity, but can be time-consuming, costly, and require trained staff. The use of isothermal-based amplification systems for detection could aid in the reduction of results turnaround and equipment-associated costs, making them appealing for point-of-use applications, or when high volume/fast turnaround testing is required. Alternatively, immunoassays offer robustness and reduced costs. Furthermore, some immunoassay formats, such as those using lateral-flow technology, can generate results very rapidly. However, immunoassays typically cannot achieve comparable sensitivity to nucleic acid-based detection methods. Alongside these methods, the application of next-generation sequencing can provide highly specific results. In addition, the ability to sequence large numbers of viral genomes would provide researchers with enhanced information and assist in tracing infections.

A Primer on the Analysis of High-Throughput Sequencing Data for Detection of Plant Viruses

High-throughput sequencing (HTS) technologies have become indispensable tools assisting plant virus diagnostics and research thanks to their ability to detect any plant virus in a sample without prior knowledge. As HTS technologies are heavily relying on bioinformatics analysis of the huge amount of generated sequences, it is of utmost importance that researchers can rely on efficient and reliable bioinformatic tools and can understand the principles, advantages, and disadvantages of the tools used. Here, we present a critical overview of the steps involved in HTS as employed for plant virus detection and virome characterization. We start from sample preparation and nucleic acid extraction as appropriate to the chosen HTS strategy, which is followed by basic data analysis requirements, an extensive overview of the in-depth data processing options, and taxonomic classification of viral sequences detected. By presenting the bioinformatic tools and a detailed overview of the consecutive steps that can be used to implement a well-structured HTS data analysis in an easy and accessible way, this paper is targeted at both beginners and expert scientists engaging in HTS plant virome projects.

Current Developments and Challenges in Plant Viral Diagnostics: A Systematic Review

Plant viral diseases are the foremost threat to sustainable agriculture, leading to several billion dollars in losses every year. Many viruses infecting several crops have been described in the literature; however, new infectious viruses are emerging frequently through outbreaks. For the effective treatment and prevention of viral diseases, there is great demand for new techniques that can provide accurate identification on the causative agents. With the advancements in biochemical and molecular biology techniques, several diagnostic methods with improved sensitivity and specificity for the detection of prevalent and/or unknown plant viruses are being continuously developed. Currently, serological and nucleic acid methods are the most widely used for plant viral diagnosis. Nucleic acid-based techniques that amplify target DNA/RNA have been evolved with many variants. However, there is growing interest in developing techniques that can be based in real-time and thus facilitate in-field diagnosis. Next-generation sequencing (NGS)-based innovative methods have shown great potential to detect multiple viruses simultaneously; however, such techniques are in the preliminary stages in plant viral disease diagnostics. This review discusses the recent progress in the use of NGS-based techniques for the detection, diagnosis, and identification of plant viral diseases. New portable devices and technologies that could provide real-time analyses in a relatively short period of time are prime important for in-field diagnostics. Current development and application of such tools and techniques along with their potential limitations in plant virology are likewise discussed in detail.

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

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

Identification of Divergent Isolates of Banana Mild Mosaic Virus and Development of a New Diagnostic Primer to Improve Detection

Banana mild mosaic virus (BanMMV) (Betaflexiviridae, Quinvirinae, unassigned species) is a filamentous virus belonging to the Betaflexiviridae family. It infects Musa spp. with a very wide geographic distribution. The genome variability of plant viruses, including the members of the Betaflexiviridae family, makes their molecular detection by specific primers particularly challenging. During routine indexing of the Musa germplasm accessions, a discrepancy was observed between electron microscopy and immunocapture (IC) reverse transcription (RT) polymerase chain reaction (PCR) test results for one asymptomatic accession. Filamentous viral particles were observed while molecular tests failed to amplify any fragment. The accession underwent high-throughput sequencing and two complete genomes of BanMMV with 75.3% of identity were assembled. Based on these sequences and on the 54 coat protein sequences available from GenBank, a new forward primer, named BanMMV CP9, compatible with Poty1, an oligodT reverse primer already used in diagnostics, was designed. A retrospective analysis of 110 different germplasm accessions from diverse origins was conducted, comparing BanMMCP2 and BanMMV CP9 primers. Of these 110 accessions, 16 tested positive with both BanMMCP2 and BanMMV CP9, 3 were positive with only BanMMCP2 and 2 tested positive with only BanMMV CP9. Otherwise, 89 were negative with the two primers and free of flexuous virions. Sanger sequencing was performed from purified PCR products in order to confirm the amplification of the BanMMV sequence for the five accessions with contrasting results. It is highly recommended to use the two primers successively to improve the inclusiveness of the protocol.