Identification of resistance loci against new pathotypes of Plasmodiophora brassicae in Brassica napus based on genome-wide association mapping
Bibliographic record
Abstract
Genetic resistance is a successful strategy for management of clubroot (Plasmodiophora brassicae) of brassica crops, but resistance can break down quickly. Identification of novel sources of resistance is especially important when new pathotypes arise. In the current study, the reaction of 177 accessions of Brassica napus to four new, virulent pathotypes of P. brassicae was assessed. Each accession was genotyped using genotyping by sequencing to identify and map novel sources of clubroot resistance using mixed linear model (MLM) analysis. The majority of accessions were highly susceptible (70-100 DSI), but a few accessions exhibited strong resistance (0-20 DSI) to pathotypes 5X (21 accessions), 3A (8), 2B (7), and 3D (15), based on the Canadian Clubroot Differential system. In total, 301,753 SNPs were mapped to 19 chromosomes. Population structure analysis indicated that the 177 accessions belong to seven major populations. SNPs were associated with resistance to each pathotype using MLM. In total, 13 important SNP loci were identified, with 9 SNPs mapped to the A-genome and 4 to the C-genome. The SNPs were associated with resistance to pathotypes 5X (2 SNPs), 3A (4), 2B (5) and 3D (6). A Blast search of 1.6 Mb upstream and downstream from each SNP identified 13 disease-resistance genes or domains. The distance between a SNP locus and the nearest resistance gene ranged from 0.04 to 0.74 Mb. The resistant lines and SNP markers identified in this study can be used to breed for resistance to the most prevalent new pathotypes of P. brassicae in Canada.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".