Molecular pathotyping platforms for the clubroot pathogen, Plasmodiophora brassicae
Bibliographic record
Abstract
Clubroot, caused by the soilborne pathogen Plasmodiophora brassicae, is a threat to cruciferous crops worldwide and an important disease of canola (Brassica napus L.) in Canada. At present, pathotypes of P. brassicae are distinguished phenotypically based on their virulence patterns on host differential sets, including the systems of Williams, Somé et al., the European Clubroot Differential set, and most recently, the Canadian Clubroot Differential and the Sinitic Clubroot Differential sets. While these are frequently used because of their simplicity of application, they are time-consuming, labor-intensive, and can lack sensitivity. Early and preventative pathotype detection is imperative to maximize productivity and promote sustainable crop production. The decreased turnaround time and increased specificity of molecular pathotyping will be valuable for the development of integrated clubroot management strategies, and interest in molecular approaches to complement phenotypic bioassays is increasing. In this study, two rapid and sensitive molecular P. brassicae pathotyping assays were developed, the first using RNase H2-dependent PCR (rhPCR) technology, and the second using a modified single base extension technique known as SNaPshot. Both assays clearly distinguished between pathotype clusters. The results correlated fully with whole genome sequencing data in silico for all 38 single-spore isolates of P. brassicae tested. Additional isolates from pathotyped clubroot galls and from samples in a single-blind test were also identified correctly. The rhPCR assay generated differentiating electrophoretic bands without non-specific amplification. The SNaPshot assay was able to detect down to a 10% relative allelic proportion in template (pathotype) mixtures with both single-spore and field isolates. Collectively, the results demonstrated that the rhPCR-based and single base extension assays developed in this study may be used as fast and reliable diagnostic tools to detect and distinguish between P. brassicae pathotype clusters. The ability to identify pathotypes in a rapid manner will aid in clubroot diagnosis and surveillance activities, complementing traditional bioassays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".