Two independent approaches converge to the cloning of a new <i>Leptosphaeria maculans</i> avirulence effector gene, <i>AvrLmS-Lep2</i>
Bibliographic record
Abstract
Summary Leptosphaeria maculans , the causal agent of blackleg disease, interacts with Brassica napus (oilseed rape, canola) in a gene-for-gene manner. The avirulence genes AvrLmS and AvrLep2 were described to be perceived by the resistance genes RlmS and LepR2 , respectively, present in the cultivar Surpass 400. Here we report cloning of AvrLmS and AvrLep2 using two independent methods. AvrLmS was cloned using combined in vitro crossing between avirulent and virulent isolates with sequencing of DNA bulks from avirulent or virulent progeny (Bulked-Segregant-Sequencing) to rapidly identify one candidate avirulence gene present in the effector repertoire of L. maculans. AvrLep2 was cloned using a bi-parental cross of avirulent and virulent L. maculans isolates and a classical map-based cloning approach. Taking these two approaches independently, we found that AvrLmS and AvrLep2 are the same gene. Complementation of virulent isolates with this gene confirmed its role in inducing resistance on Surpass 400 and Topas- LepR2 . The gene renamed AvrLmS-Lep2 encodes for a small cysteine-rich protein of unknown function with an N-terminal secretory signal peptide, which are common features of the majority of effectors from extracellular fungal plant pathogens. The AvrLmS-Lep2 / LepR2 interaction phenotype was found to vary from a typical hypersensitive response to intermediate resistance sometimes at the edge of, or evolving toward, susceptibility depending on the inoculation conditions. AvrLmS-Lep2 was nevertheless sufficient to significantly reduce the stem lesion size on plant genotypes with LepR2 , indicating the potential efficiency of this resistance to control the disease in the field.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".