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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » National Germplasm Resources Laboratory » Research » Publications at this Location » Publication #354652

Research Project: Characterizing and Detecting Pathogens to Ensure Safe Exchange of Plant Germplasm

Location: National Germplasm Resources Laboratory

Title: Using high throughput sequencing in plant virus diagnostics

item Mollov, Dimitre
item Grinstead, Sam

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/18/2018
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Plant viromes are defined by the assembly of viral nucleic acids, both DNA and RNA, associated with any plant sample or community of plants. Plant viral metagenomics is the genomic analysis of the plant virome. High throughput sequencing (HTS) is a metagenomics-based technique used to detect either individual particles or entire populations of viruses. This review considers both the benefits and pitfalls of HTS methods. HTS is beginning to supersede more traditionally used plant virus diagnostic methods such as biological indicators, ELISA, PCR, RT-PCR, and electron microscopy. The advantages of HTS are: extreme sensitivity, reliability, and the relative ease of obtaining a whole viral genome sequence. HTS has other applications for plant virology, including studying pathogen diversity, the discovery of new and uncharacterized viruses, and as a tool for virus surveys and large-scale epidemiological studies. An essential variable to consider is the nucleic acid (NA) (DNA or RNA, single or double stranded, size selection, with or without enrichment, etc.) template used in the downstream HTS workflow. These considerations provide several sequencing options: total NA and shotgun approach, double stranded RNA, virion purified NA, and small interfering RNAs. Using HTS for virus detection and characterization requires comprehensive computational efforts. Among many of the challenges with HTS data is the de novo assembly and accurate sequence mapping to known references or newly assembled contigs. HTS raw data reads consist of NA from viruses, prokaryotic and eukaryotic organisms. To identify and associate these reads with their true biological significance is a major challenge for the HTS approach. In many occasions reads and contigs are identified with very low identities (~20-40%) to viral taxa, and could suggest they represent an uncharacterized virus. However, it can also be a false alarm and such data needs to be carefully evaluated. In most cases a PCR-based approach and Sanger sequencing is necessary to validate HTS results. A single NA extract sent for HTS often yields a complete viral genome but one test has several potential bioinformatic outcomes: 1) a single sequence of the target; 2) multiple, positive target sequences; 3) fragmentary sequence of target; 4) no good assembly evident; 5) heavy contamination sample-to-sample: cross talk between samples and false positives. Another important challenge is the sensitivity of HTS. Processing and analyzing samples with low viral NA titer can lead to overlooking potential infections and result in a false negative detection. HTS has been gaining popularity and has aided in the discovery of numerous new viruses. However, there is a gap between HTS data and its biological meaning, which poses yet another challenge for satisfying Koch’s postulates. The application of HTS may even cause a methodological shift from disease etiology to metagenomics approaches, and creates ambiguity for plant quarantine regulations. Despite its current challenges HTS is very promising approach in plant virus diagnostics and virus characterization.