Evaluation of Genomics for Detection of Plant Pathogens of Regulatory Concern

A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Genetics and Genomics".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 6661

Special Issue Editors


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Guest Editor
Canadian Food Inspection Agency, Ottawa Plant Laboratory, Ottawa, ON K2J 4S1, Canada
Interests: technologies for detection and identification of plant pests (fungi-oomycetes) of regulatory significance; fungal detection and genotyping; real-time PCR; genomic; metagenomic
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Guest Editor
National Reference Centre for Plant Health, Dutch National Plant Protection Organization, Geertjesweg 15, 6706 EA Wageningen, The Netherlands
Interests: molecular detection and identification of plant pathogens and pest species of regulatory concern; interlaboratory comparison studies; comparative genomics; metagenomics; identification of functional trait-based markers; population and genome dynamics for track and tracing; phylogeny; real-time (RT-)PCR; 1st, 2nd and 3rd generation sequencing; bioinformatics

Special Issue Information

Dear Colleagues,

Healthy plants are essential for life on Earth. They produce the oxygen we breathe and make up over 80% of the food we eat. Plant pathogens and pest species threaten food security and cause great economic losses, and when engaging with international trade, regulations have to be implemented restricting the introduction and spread of plant pests. These regulations rely heavily on accurate plant disease diagnostics, which can be challenging for organisms that are difficult to isolate and/or to differentiate from closely-related, non-regulated species. With the introduction of molecular tools, fast and reliable detection and identification tests for regulated pests became available. The early detection of non-indigenous plant pathogens is the key to managing regulated and invasive species.

With the introduction of whole genome shotgun sequencing techniques, new powerful tools have become available in diagnostic laboratories for regulatory plant health. No longer do diagnosticians have to rely on a single genetic locus, but now they have the power of an entire (meta)genome at their disposal. Genome sequencing with high throughput sequencing (HTS) technologies are capable of processing large numbers of samples and producing even larger volumes of genomics data. By mining the genome sequences of closely-related pests and comparing them to one another, it is possible to design molecular markers that can be used by diagnostics labs to distinguish them from one another. Moreover in virology, this is a way to identify (novel) plant pathogenic viruses from metagenomic samples. These approaches rely on exploiting the genetic differences between species for identification or population-level analyses in order to respond to questions in regulatory research. With the increasing use of HTS, more specific guidelines are developed for applications in regulatory plant health.

In this Special Issue, the following topics can be presented: the development and validation of generic and specific bioinformatic pipelines for regulated plant pests; the use of comparative genomics for novel assay design; genome-wide phylogenomic analyses to distinguish regulated from non-regulated organisms; and population-level studies for track-and-trace purposes. In addition, we invite authors to reflect on possible implications for the use of HTS in regulatory plant health for phytosanitary policies.

Dr. Guillaume J. Bilodeau
Dr. Bart T. L. H. Van De Vossenberg
Guest Editors

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Keywords

  • molecular detection and identification
  • regulated plant pathogens
  • HTS detection
  • genomics
  • metagenomics
  • comparative genomics
  • population dynamics

Published Papers (2 papers)

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Research

20 pages, 1801 KiB  
Article
Side-by-Side Comparison of Post-Entry Quarantine and High Throughput Sequencing Methods for Virus and Viroid Diagnosis
by Marie-Emilie A. Gauthier, Ruvini V. Lelwala, Candace E. Elliott, Craig Windell, Sonia Fiorito, Adrian Dinsdale, Mark Whattam, Julie Pattemore and Roberto A. Barrero
Biology 2022, 11(2), 263; https://0-doi-org.brum.beds.ac.uk/10.3390/biology11020263 - 08 Feb 2022
Cited by 11 | Viewed by 2974
Abstract
Rapid and safe access to new plant genetic stocks is crucial for primary plant industries to remain profitable, sustainable, and internationally competitive. Imported plant species may spend several years in Post Entry Quarantine (PEQ) facilities, undergoing pathogen testing which can impact the ability [...] Read more.
Rapid and safe access to new plant genetic stocks is crucial for primary plant industries to remain profitable, sustainable, and internationally competitive. Imported plant species may spend several years in Post Entry Quarantine (PEQ) facilities, undergoing pathogen testing which can impact the ability of plant industries to quickly adapt to new global market opportunities by accessing new varieties. Advances in high throughput sequencing (HTS) technologies provide new opportunities for a broad range of fields, including phytosanitary diagnostics. In this study, we compare the performance of two HTS methods (RNA-Seq and sRNA-Seq) with that of existing PEQ molecular assays in detecting and identifying viruses and viroids from various plant commodities. To analyze the data, we tested several bioinformatics tools which rely on different approaches, including direct-read, de novo, and reference-guided assembly. We implemented VirusReport, a new portable, scalable, and reproducible nextflow pipeline that analyses sRNA datasets to detect and identify viruses and viroids. We raise awareness of the need to evaluate cross-sample contamination when analyzing HTS data routinely and of using methods to mitigate index cross-talk. Overall, our results suggest that sRNA analyzed using VirReport provides opportunities to improve quarantine testing at PEQ by detecting all regulated exotic viruses from imported plants in a single assay. Full article
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16 pages, 523 KiB  
Article
Four In Silico Designed and Validated qPCR Assays to Detect and Discriminate Tilletia indica and T. walkeri, Individually or as a Complex
by Émilie D. Tremblay, Julie Carey, Guillaume J. Bilodeau and Sarah Hambleton
Biology 2021, 10(12), 1295; https://0-doi-org.brum.beds.ac.uk/10.3390/biology10121295 - 08 Dec 2021
Cited by 1 | Viewed by 2643
Abstract
Several fungi classified in the genus Tilletia are well-known to infect grass species including wheat (Triticum). Tilletia indica is a highly unwanted wheat pathogen causing Karnal bunt, subject to quarantine regulations in many countries. Historically, suspected Karnal bunt infections were identified [...] Read more.
Several fungi classified in the genus Tilletia are well-known to infect grass species including wheat (Triticum). Tilletia indica is a highly unwanted wheat pathogen causing Karnal bunt, subject to quarantine regulations in many countries. Historically, suspected Karnal bunt infections were identified by morphology, a labour-intensive process to rule out other tuberculate-spored species that may be found as contaminants in grain shipments, and the closely-related pathogen T. walkeri on ryegrass (Lolium). Molecular biology advances have brought numerous detection tools to discriminate Tilletia congeners (PCR, qPCR, etc.). While those tests may help to identify T. indica more rapidly, they share weaknesses of targeting insufficiently variable markers or lacking sensitivity in a zero-tolerance context. A recent approach used comparative genomics to identify unique regions within target species, and qPCR assays were designed in silico. This study validated four qPCR tests based on single-copy genomic regions and with highly sensitive limits of detection (~200 fg), two to detect T. indica and T. walkeri separately, and two newly designed, targeting both species as a complex. The assays were challenged with reference DNA of the targets, their close relatives, other crop pathogens, the wheat host, and environmental specimens, ensuring a high level of specificity for accurate discrimination. Full article
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