Genetics of stripe rust resistance in a common wheat landrace Aus27492 and its transfer to modern wheat cultivars
Bibliographic record
Abstract
The development of resistant cultivars is a preferred way to manage the wheat rust pathogens. Successful breeding relies on the continuous discovery, characterization and deployment of genetically diverse resistance sources. This investigation covers the identification and characterization of the stripe rust (caused by Puccinia striiformis f. sp. tritici) resistance carried by a pre-Green Revolution wheat genotype, Aus27492, from France and its transfer to modern backgrounds. Genetic analysis of stripe rust resistance using an F3 population derived from the cross of Aus27492 with the susceptible parent ‘Avocet S’ indicated digenic inheritance of all stage resistance. The underlying genes were tentatively named YrAW6 and YrAW7 and these loci were located in the long arms of chromosomes 2B and 5A, respectively, through the Illumina iSelect 90 K Infinium SNP genotyping array-based bulked segregant analysis (BSA). While YrAW7 was shown to be the same as the previously described stripe rust resistance gene Yr34 based on pathotypic specificity, YrAW6 appears to represent a new locus. To take these results from the laboratory to farmers’ fields, derivatives of Aus27492 in the Australian wheat cultivars ‘Emu Rock’, ‘Mace’ and ‘Suntop’ were delivered to Australian wheat-breeding companies for use as donor sources.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".