From field to the genome. Application of 3rd generation sequencing to direct genotyping of canola pathogens
Term: 3 years, ending February 2024
Status: Complete
Researcher(s): Hossein Borhan, Tim Dumonceaux, AAFC; Stephen Strelkov, U of A
SaskCanola Investment: $155,250
Total Project Cost: $310,500
Funding Partners: ACPC
Grower Benefits
We applied target capture sequencing to canola root galls and soil samples from three fields in Alberta. Sequencing data showed that the clubroot pathogen pathotype 3H was present in two fields. A third field sample showed presence of new mutations in one of the target sequences indicating presence of clubroot pathotype 3H and potentially other pathotype that were not present in our clubroot sequence dataset. We also determined the genotype of blackleg races from three canola stems infected with blackleg and determined a mixture of blackleg species as well as other pathogenic fungi present in these samples.
Project Summary
A high-throughput and accurate pathogen genotyping method using target enrichment sequencing technology was developed and applied to plant and soil samples to determine the blackleg pathogen races present in canola stems and clubroot pathotypes present in root galls and soil samples from canola fields.
Knowledge of pathogen races is essential for the successful prevention of crop pathogens. Plant pathogen virulence genes, also known as effectors, can mutate rapidly and generate new pathogen races/pathotypes that overcome disease-resistant varieties. Detecting and tracking changes in the effector genes of pathogens is important for crop disease management. We applied next-generation sequencing technology to develop a high-throughput and accurate genotyping technique by targeted sequencing of clubroot and blackleg effector genes from plant and soil samples collected from canola fields. This technique enabled us to genotype clubroot and blackleg pathogens and identify several other fungal pathogens on the same samples.
Targeted sequencing of soil and canola tissues, infected with blackleg and clubroot pathogens, was achieved by designing sequencing probes with homology to the pathogen effector genes. Probes are short oligonucleotides (small DNA fragments) that have homology to the sequence of target genes. We designed probes against all known effector genes from the blackleg pathogen and 126 computationally predicted effector genes from the clubroot pathogen. These probes were used to capture and sequence the corresponding effector genes from DNA prepared from canola field samples. Sequences of targeted effector genes were used to determine the race structure of blackleg and clubroot pathogens.
Marker-assisted genotyping of pathogen races is a rapid and accurate method to determine the pathogen isolates in farmers’ fields and identify changes in the pathogen’s populations. We have previously provided PCR-based markers for the blackleg pathogen Leptosphaeria maculans (Lm). These markers were designed to determine the genotype of Lm isolates based on informative mutations in the sequence of known Lm virulence (effector) genes. PCR markers are practical and cost-effective. However, they could only detect known mutations, and any additional sequence mutations in the PCR primer binding sites renders the markers unusable. In addition, for pathogens such as Plasmodiophora brassicae (Pb), that causes clubroot disease of canola, the virulence (effector) genes that determine race specificity have not been discovered yet. A solution to this shortfall of PCR-based markers is targeted sequencing of pathogen effector genes. Unlike PCR markers, targeted sequencing not only identifies known mutations in the genes of interest but also detects new mutations. We were able to determine field races for blackleg and clubroot pathogens and identify several other pathogenic fungi by using sequence enrichment of known Lm effectors and predicted effectors from Pb. These techniques can be applied to target multiple genes and hundreds or even thousands of samples at once and provide accurate genotyping for many samples in one application.