The Use of High-Throughput Sequencing for the Study and Diagnosis of Plant Viruses and Viroids in Pollen

Viruses cause epidemics on all major crops of agronomic importance, and a timely and accurate identification is essential for control. High throughput sequencing (HTS) is a technology that allows the identification of all viruses without prior knowledge on the targeted pathogens. In this paper, we used HTS technique for the detection and identification of different viral species occurring in single and mixed infections in plants in Poland. We analysed various host plants representing different families. Within the 20 tested samples, we identified a total of 13 different virus species, including those whose presence has not been reported in Poland before: clover yellow mosaic virus (ClYMV) and melandrium yellow fleck virus (MYFV). Due to this new finding, the obtained sequences were compared with others retrieved from GenBank. In addition, cucurbit aphid-borne yellows virus (CABYV) was also detected, and due to the recent occurrence of this virus in Poland, a phylogenetic analysis of these new isolates was performed. The analysis revealed that CABYV population is highly diverse and the Polish isolates of CABYV belong to two different phylogenetic groups. Our results showed that HTS-based technology is a valuable diagnostic tool for the identification of different virus species originating from variable hosts, and can provide rapid information about the spectrum of plant viruses previously not detected in a region.

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Applications of Next Generation High Throughput Sequencing Technologies in Characterization, Discovery and Molecular Interaction of Plant Viruses

Indian Journal of Virology ◽

10.1007/s13337-013-0133-4 ◽

2013 ◽

Vol 24 (2) ◽

pp. 157-165 ◽

Cited By ~ 26

Author(s):

K. Prabha ◽

V. K. Baranwal ◽

R. K. Jain

Keyword(s):

High Throughput ◽

Molecular Interaction ◽

High Throughput Sequencing ◽

Plant Viruses ◽

Next Generation ◽

Sequencing Technologies

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Assessment of Common Soybean-Infecting Viruses in Ohio, USA, Through Multi-site Sampling and High-Throughput Sequencing

Plant Health Progress ◽

10.1094/php-rs-16-0018 ◽

2016 ◽

Vol 17 (2) ◽

pp. 133-140 ◽

Cited By ~ 1

Author(s):

Junping Han ◽

Leslie L. Domier ◽

Bryan J. Cassone ◽

Anne Dorrance ◽

Feng Qu

Keyword(s):

Mosaic Virus ◽

High Throughput ◽

High Throughput Sequencing ◽

Virus Disease ◽

Soybean Mosaic Virus ◽

Alfalfa Mosaic Virus ◽

Plant Viruses ◽

Yellow Mosaic Virus ◽

Tobacco Streak Virus ◽

Streak Virus

Multi-site sampling was conducted during 2011 and 2012 to assess the scope of virus disease problems of soybean in Ohio, USA. A total of 259 samples were collected from 80 soybean fields distributed in 42 Ohio counties, accounting for more than 90% of major soybean-growing counties in Ohio. A high-throughput RNA-Seq approach was adopted to identify all viruses in the samples that share sufficient sequence similarities with known plant viruses. To minimize sequencing costs, total RNA extracted from up to 20 samples were first pooled to make up regional pools, resulting in eight regional pools per year in both 2011 and 2012. These regional pools were further pooled into two yearly master pools of RNA, and sequenced using the Illumina's HiSeq2000 platform. Bioinformatic analyses of sequence reads led to the identification of signature sequences of nine different viruses. The originating locations of these viruses were then mapped with PCR or RT-PCR. This study confirmed the widespread distribution of Bean pod mottle virus, Soybean vein necrosis virus, Tobacco ringspot virus, and Tobacco streak virus in Ohio. It additionally revealed occasional association of Alfalfa mosaic virus, Bean yellow mosaic virus, Clover yellow vein virus, Soybean mosaic virus, and Soybean Putnam virus with Ohio soybean. This is the first statewide survey of soybean viruses in Ohio, and provides the much-needed baseline information for management of virus diseases of soybean. Accepted for publication 20 May 2016. Published 10 June 2016.

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Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies

Phytopathology ◽

10.1094/phyto-02-18-0067-r ◽

2019 ◽

Vol 109 (3) ◽

pp. 488-497 ◽

Cited By ~ 29

Author(s):

Sebastien Massart ◽

Michela Chiumenti ◽

Kris De Jonghe ◽

Rachel Glover ◽

Annelies Haegeman ◽

...

Keyword(s):

High Throughput ◽

Large Scale ◽

High Throughput Sequencing ◽

Performance Test ◽

Virus Detection ◽

Performance Testing ◽

Plant Viruses ◽

Reference Sequence ◽

Bioinformatics Pipeline ◽

Double Blind

Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported but little attention has been paid thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large-scale performance test using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false-positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty in detecting viral agents when they are novel or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases, and (iv) the significant level of scientific expertise needed when interpreting pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.

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Recent Advances on Detection and Characterization of Fruit Tree Viruses Using High-Throughput Sequencing Technologies

Viruses ◽

10.3390/v10080436 ◽

2018 ◽

Vol 10 (8) ◽

pp. 436 ◽

Cited By ~ 30

Author(s):

Varvara Maliogka ◽

Angelantonio Minafra ◽

Pasquale Saldarelli ◽

Ana Ruiz-García ◽

Miroslav Glasa ◽

...

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Infected Plant ◽

Fruit Trees ◽

Plant Viruses ◽

Fruit Tree ◽

Advantages And Disadvantages ◽

Sequencing Technologies ◽

Recent Advances

Perennial crops, such as fruit trees, are infected by many viruses, which are transmitted through vegetative propagation and grafting of infected plant material. Some of these pathogens cause severe crop losses and often reduce the productive life of the orchards. Detection and characterization of these agents in fruit trees is challenging, however, during the last years, the wide application of high-throughput sequencing (HTS) technologies has significantly facilitated this task. In this review, we present recent advances in the discovery, detection, and characterization of fruit tree viruses and virus-like agents accomplished by HTS approaches. A high number of new viruses have been described in the last 5 years, some of them exhibiting novel genomic features that have led to the proposal of the creation of new genera, and the revision of the current virus taxonomy status. Interestingly, several of the newly identified viruses belong to virus genera previously unknown to infect fruit tree species (e.g., Fabavirus, Luteovirus) a fact that challenges our perspective of plant viruses in general. Finally, applied methodologies, including the use of different molecules as templates, as well as advantages and disadvantages and future directions of HTS in fruit tree virology are discussed.

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

Viruses ◽

10.3390/v13061130 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1130

Author(s):

Nourolah Soltani ◽

Kristian A. Stevens ◽

Vicki Klaassen ◽

Min-Sook Hwang ◽

Deborah A. Golino ◽

...

Keyword(s):

High Throughput ◽

High Throughput Sequencing ◽

Plant Viruses ◽

Molecular Diagnostic ◽

Virus Species ◽

Certification Programs ◽

Performance Specifications ◽

Virus Diagnostics ◽

Diagnostic Research ◽

And Performance

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.

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

Pathogens ◽

10.3390/pathogens10091174 ◽

2021 ◽

Vol 10 (9) ◽

pp. 1174

Author(s):

Yahya Z. A. Gaafar ◽

Marcel Westenberg ◽

Marleen Botermans ◽

Krizbai László ◽

Kris De Jonghe ◽

...

Keyword(s):

Sample Preparation ◽

High Throughput ◽

Ribosomal Rna ◽

Diagnostic Tool ◽

Plant Virus ◽

High Throughput Sequencing ◽

Interlaboratory Comparison ◽

Virus Detection ◽

Plant Viruses ◽

Comparison Study

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

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

Microorganisms ◽

10.3390/microorganisms9040841 ◽

2021 ◽

Vol 9 (4) ◽

pp. 841

Author(s):

Denis Kutnjak ◽

Lucie Tamisier ◽

Ian Adams ◽

Neil Boonham ◽

Thierry Candresse ◽

...

Keyword(s):

Data Analysis ◽

High Throughput ◽

Plant Virus ◽

High Throughput Sequencing ◽

Plant Viruses ◽

Acid Extraction ◽

Sequencing Data ◽

Bioinformatic Tools ◽

Advantages And Disadvantages ◽

Plant Virus Detection

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

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