Identification of single-nucleotide polymorphisms linked to resistance gene<i>Pc68</i>to crown rust in cultivated oat
Bibliographic record
Abstract
A procedure is described for developing single-nucleotide polymorphism (SNP) markers linked to Pc68, a gene conferring resistance to crown rust [Puccinia coronata f. sp. avenae] in many oat (Avena sativa) cultivars currently grown in Canada. Three restriction-fragment length polymorphism (RFLP) markers, located close to the resistance gene Pg9 to stem rust [Puccinia graminis f. sp. avenae] through comparative mapping, were used as sources of DNA-sequence information for SNP identification, since Pc68 is tightly linked or allelic to Pg9. Specific primers designed from the RFLP-marker sequences were used to amplify the target genomic region from recombinant inbred lines with and without Pc68. Putative SNP sites were identified by means of comparative sequence alignment of the polymerase chain reaction (PCR) fragments and were validated by the single-base extension method, a non-gel-based assay for genotyping SNPs. The 774-bp PCR fragment amplified by primers derived from the RFLP marker cdo309 was a sequence-tagged site (STS) marker linked to Pc68, and only the SNPs derived from a region within the STS were linked to Pc68. These SNPs and STS cosegregated in two genetic populations. The map distance between these markers and Pc68 was 4.2 and 6.7 cM (centimorgans), depending on population. The SNP markers identified in the present study can distinguish plants homozygous for Pc68 from heterozygotes, a useful feature for eliminating heterozygous plants in early generations. As SNP markers for other resistance genes or other important traits become available, breeders can benefit from using the technology with high-throughput, automation, and multiplexing capabilities, such as single-base extension assay, in breeding applications, including resistance gene pyramiding.
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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 | 0.000 |
| 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".