Linkage mapping of genes controlling resistance to white rust (<i>Albugo candida</i>) in<i>Brassica rapa</i>(syn.<i>campestris</i>) and comparative mapping to<i>Brassica napus</i>and<i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
Genes for resistance to white rust (Albugo candida) in oilseed Brassica rapa were mapped using a recombinant inbred (RI) population and a genetic linkage map consisting of 144 restriction fragment length polymorphism (RFLP) markers and 3 phenotypic markers. Young seedlings were evaluated by inoculating cotyledons with A. candida race 2 (AC2) and race 7 (AC7) and scoring the interaction phenotype (IP) on a 0-9 scale. The IP of each line was nearly identical for the two races and the population showed bimodal distributions, suggesting that a single major gene (or tightly linked genes) controlled resistance to the two races. The IP scores were converted to categorical resistant and susceptible scores, and these data were used to map a single Mendelian gene controlling resistance to both races on linkage group 4 where resistance to race 2 had been mapped previously. A quantitative trait loci (QTL) mapping approach using the IP scores detected the same major resistance locus for both races, plus a second minor QTL effect for AC2 on linkage group 2. These results indicate that either a dominant allele at a single locus (Acal) or two tightly linked loci control seedling resistance to both races of white rust in the biennial turnip rape cultivar Per. The map positions of white rust resistance genes in B. rapa and Brassica napus were compared and the results indicate where additional loci that have not been mapped may be located. Alignment of these maps to the physical map of the Arabidopsis genome identified regions to target for comparative fine mapping using this model organism.
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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) | 0.001 | 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 | 0.000 |
| 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".