Page 130 - PC2019 Program & Proceedings

PLANT CANADA 2019

S45. Diagnostic metagenomics in the context of molecular plant pathology
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Chen, W. ; S. Hambleton ; K. Seifert ; D. Radford ; C.A. Levesque
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1 Agriculture and Agri-Food Canada
2 Canadian Food Inspection Agency
To protect the food, agriculture and forestry sectors and the environment from biotic threats, effective
diagnostic tools to support accurate surveillance and risk assessments of pathogens and pests are of great
importance. High-throughput sequencing-based metagenomics (HTS) allows rapid, simultaneous
detection of genetic material of a broad spectrum of known and unknown pathogens and pests. The dense
ancillary information, e.g weather conditions and land use, associated with HTS data also allows
modeling and inference of factors affecting their dispersal and spread. However, to enable HTS
technologies as an effective diagnostic and decision-making tool, we must improve the identification
accuracy of short HTS reads at species or subspecies levels, which regulatory programs and
quarantine/trade regulations on pathogens and pests now emphasize. Caution must be taken when
reporting classification at high taxonomic resolutions using off-the-shelf bioinformatics tools and public
reference databases. We are introducing an improved bioinformatics solution for high-resolution
pathogen/pest identification from metagenomics data. This bioinformatics tool, named Automated
Oligonucleotide Design Pipeline (AODP, https://bitbucket.org/wenchen_aafc/aodp_v2.0_release),
implements a novel sequence matching algorithm for superior performance of HTS taxonomic
classification compared to other methods (e.g. BLAST, RDP classifier and USEARCH) [BMC
Bioinformatics 19(1):395]. The power of AODP coupled with curated and high-quality reference
databases to detect known, new and potentially invasive/transboundary pathogens in commodities and
agro-ecosystems has been tested using real data sets as test cases.

Wen Chen (wen.chen@canada.ca)

S46. Genome-enhanced detection and identification of regulated plant pathogens
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Bilodeau, G.J. ; E. Giroux ; N. Feau ; R.C. Hamelin
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1 Canadian Food Inspection Agency
2 University of British Columbia
Implementation of regulations to restrict the movement of plant pests on infected plant commodities rely
heavily on accurate plant disease diagnostics; which can be challenging for organisms that are difficult to
isolate and/or differentiate from closely-related, non-regulated species. Early detection of non-indigenous
fungi is the key to manage regulated and invasive species. High-throughput sequencing technologies can
process large numbers of samples and volumes of genomics data. We developed the Genome-Enhanced
Detection and Identification (GEDI) approach which consists in by mining and comparing the genomes of
pests and their closely-related pests to design species and lineage-specific molecular markers exploiting
the genetic differences. These markers can be translated into real-time PCR, SNP markers, and AmpliSeq
assays for the purpose of detecting and assessing the genetic diversity of pathogens in plant samples from
the species to the intra-lineage. Genetic information from environmental samples can be obtained thereby
allowing tracing the trajectory of plant diseases movement, i.e. population studies information linked with
metadata. Proof-of-concept of an integrated method and bioinformatics pipeline was used to design some
Fusarium and Phytophthora species, among others, organism-specific markers. Genomic approaches and
bioinformatics pipelines help to quickly develop molecular tools to facilitate detection and identification
of fungal pathogens

Guillaume Bilodeau (guillaume.bilodeau@canada.ca)

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