QTL mapping for adult plant field resistance to stripe rust in the AAC Cameron/P2711 spring wheat population
Bibliographic record
Abstract
Abstract Stripe rust, caused by Puccinia striiformis f. sp . tritici ( Pst ), is a devastating disease of wheat ( Triticum aestivum L.). Deployment of resistant wheat cultivars is one of the best strategies to mitigate disease‐associated risks. The genotype P2711 possesses effective stripe rust resistance under field conditions in western Canada, however, the genetic basis of this resistance is unknown. To identify resistance, a recombinant inbred line (RIL) population comprised of 252 RILs was developed from the cross AAC Cameron/P2711. This population was evaluated for stripe rust severity at the adult plant stage in Creston, BC (in 2018, 2019, and 2020) and Lethbridge, AB (in 2018 and 2020), and was genotyped using the wheat 90K iSelect single nucleotide polymorphism (SNP) assay. A high‐density genetic map comprised of 8,915 markers was constructed covering all the wheat chromosomes. Four resistance quantitative trait loci (QTLs) were contributed by P2711 and three from AAC Cameron. QYr.lrdc‐2A.1 , corresponding to the Yr17 gene, was the most stable QTL and detected in four out of five environments, whereas QYr.lrdc‐2B was the second most stable QTL. These two QTL along with QYr.lrdc‐5A showed a significant reduction in stripe rust severity when present together. Where most of the QTLs detected in both locations, QYr.lrdc‐1A.1 and QYr.lrdc‐1A.2 , both were detected only in Creston, BC. Stable QTLs on chromosome 2A, 2B, and 5A, and their closely associated markers identified in this study could be utilized in marker‐assisted selection for stripe rust resistant cultivar development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".