Development of molecular markers linked to the <i>Leptosphaeria maculans</i> resistance gene <i>Rlm6</i> and inheritance of <scp>SCAR</scp> and <scp>CAPS</scp> markers in <i>Brassica napus</i> × <i>Brassica juncea</i> interspecific hybrids
Bibliographic record
Abstract
Abstract Leptosphaeria maculans causes blackleg disease on Brassica napus, an economically important oilseed crop. Brassica juncea has high resistance to blackleg and is a source for the development of resistant B. napus varieties. To transfer the Rlm6 resistance gene from B. juncea into B. napus, an interspecific cross between B. napus “Topas DH16516” and B. juncea “Forge” was produced, followed by the development of F2 and F3 generations. Sequence characterized amplified region (SCAR) and cleaved amplified polymorphic sequence (CAPS) markers linked to the L. maculans resistance gene Rlm6 were developed. Segregation of SCAR and CAPS markers linked to Rlm6 were confirmed by genotyping of F2 and F3 progeny. Segregation of CAPS markers and phenotypes for blackleg disease severity in F2 plants had a Mendelian ratio of 3:1 in resistant vs. susceptible plants, respectively, supporting the assumption that genetic control of resistance was by a single dominant gene. The molecular markers developed in this study, which show linkage with the L. maculans resistance gene Rlm6, would facilitate marker‐assisted backcross breeding in a variety development programme.
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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 | 0.001 |
| 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".