Nested Association Mapping to Identify Stripe Rust Resistance in Spring Wheat
Bibliographic record
Abstract
Stripe rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss. (Pst), is one of the most devastating diseases affecting wheat (Triticum aestivum L.). It is one of the five ‘priority one’ diseases for which a minimum level of resistance is required when registering a wheat cultivar with desirable traits. Among all the available management approaches, genetic resistance is the most effective, easy-to-use, and environmentally friendly approach to combating stripe rust. Researchers are fighting a never-ending war against the ever-evolving dynamic population of the pathogen. Thus, the continuous identification of new sources of resistance is essential for breeding resistant wheat cultivars. In this study, we developed three nested association mapping (NAM) populations (n = 741, 575, and 1098), consisting of 16 RIL families. These populations were developed in the genetic background of susceptible wheat cultivars Avocet, Vesper, and Cardale by crossing with 6, 6, and 4 new, diverse, and resistant source lines, respectively. Comprehensive phenotypic evaluations of the NAM populations were conducted in multiple environments to quantify disease severity. Following phenotypic evaluation, all lines were genotyped using a wheat 7K SNP assay, generating a robust marker dataset for genetic analyses. Linkage maps for each RIL family were constructed, and these were further integrated into a consensus map to facilitate joint QTL mapping for each NAM population. Major QTL were defined as those explaining more than 20% of the phenotypic variance, whereas stable QTL were consistently detected across multiple environments. 34 major and stable QTL were identified from 16 RIL families using composite interval mapping (CIM). The most significant and stable QTL from individual families were QYr.lrdc-7B.2, QYr.lrdc-7D (RIL family 3: Avocet/P2382), QYr.lrdc-5D (RIL family 5: Avocet/P2432), QYr.lrdc-1A.1 (RIL family 8: Vesper/P2686), QYr.lrdc-7B.1, QYr.lrdc-7B.2 (RIL family 10: Vesper/P2688), QYr.lrdc-2B (RIL family 12: Vesper/P2265), and QYr.lrdc-2B (RIL family 16: Cardale/P2703), with the phenotypic variance explained (PVE) ranging from 31% to 62%. Joint mapping of NAM populations 1, 2, and 3 was carried out to identify 20, 21, and 14 QTL, respectively. In the individual family analyses, we were able to detect family-specific loci; however, the power was limited because each family only segregated for a subset of alleles. By combining all families into the NAM framework, we increased both mapping resolution and statistical power. Furthermore, several QTL were only revealed through joint mapping, demonstrating the added power of combining information across families. The overlapping chromosomal regions across multiple RIL families indicate genomic regions consistently contributing stripe rust resistance. These results show that NAM population is a powerful tool for dissecting complex traits and discovering new resistance alleles. The major-effect QTL and their linked molecular markers offer valuable resources for marker-assisted selection. Overall, the study provides a clear understanding of the genetic architecture of stripe rust resistance in wheat to accelerate the Canadian wheat breeding program.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".