Genetic analysis of resistance to stripe rust in durum wheat (Triticum turgidum L. var. durum)
Bibliographic record
Abstract
Stripe rust, caused by the fungal pathogen Puccinia striiformis Westend. f. sp. tritici Eriks, is an important disease of bread wheat (Triticum aestivum L.) worldwide and there is an indication that it may also become a serious disease of durum wheat (T. turgidum L. var. durum). Therefore, we investigated the genetic architecture underlying resistance to stripe rust in adapted durum wheat germplasm. Wheat infection assays were conducted under controlled conditions in Canada and under field conditions in Mexico. Disease assessments were performed on a population of 155 doubled haploid (DH) lines derived from the cross of Kofa (susceptible) and W9262-260D3 (moderately resistant) and on a breeding panel that consisted of 92 diverse cultivars and breeding lines. Both populations were genotyped using the 90K single-nucleotide polymorphism (SNP) iSelect assay. In the DH population, QTL for stripe rust resistance were identified on chromosome 7B (LOD 6.87-11.47) and chromosome 5B (LOD 3.88-9.17). The QTL for stripe rust resistance on chromosome 7B was supported in the breeding panel. Both QTL were anchored to the genome sequence of wild emmer wheat, which identified gene candidates involved in disease resistance. Exome capture sequencing identified variation in the candidate genes between Kofa and W9262-260D3. These genetic insights will be useful in durum breeding to enhance resistance to stripe rust.
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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 | 0.000 |
| 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".