The <i><scp>B</scp>rassica napus</i> receptor‐like protein <scp>RLM</scp>2 is encoded by a second allele of the <i><scp>L</scp>ep<scp>R</scp>3</i>/<i><scp>R</scp>lm2</i> blackleg resistance locus
Bibliographic record
Abstract
Leucine-rich repeat receptor-like proteins (LRR-RLPs) are highly adaptable parts of the signalling apparatus for extracellular detection of plant pathogens. Resistance to blackleg disease of Brassica spp. caused by Leptosphaeria maculans is largely governed by host race-specific R-genes, including the LRR-RLP gene LepR3. The blackleg resistance gene Rlm2 was previously mapped to the same genetic interval as LepR3. In this study, the LepR3 locus of the Rlm2 Brassica napus line 'Glacier DH24287' was cloned, and B. napus transformants were analysed for recovery of the Rlm2 phenotype. Multiple B. napus, B. rapa and B. juncea lines were assessed for sequence variation at the locus. Rlm2 was found to be an allelic variant of the LepR3 LRR-RLP locus, conveying race-specific resistance to L. maculans isolates harbouring AvrLm2. Several defence-related LRR-RLPs have previously been shown to associate with the RLK SOBIR1 to facilitate defence signalling. Bimolecular fluorescence complementation (BiFC) and co-immunoprecipitation of RLM2-SOBIR1 studies revealed that RLM2 interacts with SOBIR1 of Arabidopsis thaliana when co-expressed in Nicotiana benthamiana. The interaction of RLM2 with AtSOBIR1 is suggestive of a conserved defence signalling pathway between B. napus and its close relative A. thaliana.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 0.002 |
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".