Mapping and identification of molecular markers for the Pc96 gene conferring resistance to crown rust in oat
Bibliographic record
Abstract
Oat crown rust caused by Puccinia coronata Cda f. sp. avenae Erikss (Pca), is a major constraint to oat (Avena sativa L.) production in many parts of the globe, with host resistance applied as a common strategy to curb crown rust epidemics. Combining multiple sources of crown rust resistance (for example, Pc genes conferring seedling resistance) in a single genetic background can be expedited by marker-assisted selection using molecular markers that are tightly linked with resistance loci. Pc96 is a race-specific crown rust resistance gene originating from cultivated oat that has been deployed in North American oat breeding programs. SNP markers linked with Pc96 were identified using multiple interval mapping with 899 polymorphic SNPs in a recombinant inbred line population developed from a cross between the oat crown rust differential known to carry Pc96 and the differential line carrying Pc54. A single resistance locus was identified on chromosome 7D between 60.4 and 91.6 cM with a peak LOD at 87.3 cM. The resistance locus and linked SNPs were validated in two additional biparental populations, Ajay x Pc96 and Pc96 x Kasztan. Genotype state at a combination of two linked SNPs predicted the absence of Pc96 in a broad group of germplasm with 5% miss-classification. SNPs that are closely linked to the gene may be beneficial as PCR-based molecular markers in marker-assisted selection.
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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 | 0.001 |
| 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".