QTL Mapping of Adult Plant Resistance to Stripe Rust in a Doubled Haploid Wheat Population
Bibliographic record
Abstract
Stripe rust caused by Puccinia striiformis Westend. f. sp. tritici. is a major bread wheat disease worldwide with yield losses of up to 100% under severe disease pressure. The deployment of resistant cultivars with adult plant resistance to the disease provides a long-term solution to stripe rust of wheat. An advanced line from the International Winter Wheat Improvement Program (IWWIP) 130675 (Avd/Vee#1//1-27-6275/Cf 1770/3/MV171-C-17466) showed a high level of adult plant resistance to stripe rust in the field. To identify the adult plant resistance genes in this elite line, a mapping population of 190 doubled haploid (DH) lines was developed from a cross between line 130675 and the universal stripe rust-susceptible variety Avocet S. The DH population was evaluated at precision wheat stripe rust phenotyping platform, in Izmir during 2019, 2020, and 2021 cropping seasons under artificial inoculations. Composite interval mapping (CIM) identified two stable QTLs QYr.rcrrc-3B.1, and QYr.rcrrc-3B.2, which were detected in multiple years. In addition to these two QTLs, five more QTLs, QYr.rcrrc-1B, QYr.rcrrc-2A, QYr.rcrrc-3A, QYr.rcrrc-5A, and QYr.rcrrc-7D, were identified, which were specific to the cropping year (environment). All QTLs were derived from the resistant parent, except QYr.rcrrc-3A. The significant QTLs explained 3.4–20.6% of the phenotypic variance. SNP markers flanking the QTL regions can be amenable to marker-assisted selection. The best DH lines with high yield, end-use quality, and stripe rust resistance can be used for further selection for improved germplasm. SNP markers flanking the QTL regions can aid in identifying such lines.
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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 | 0.001 |
| 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".