<i>Leptosphaeria maculans</i> AvrLm9: a new player in the game of hide and seek with AvrLm4‐7
Bibliographic record
Abstract
Blackleg disease of Brassica napus caused by Leptosphaeria maculans (Lm) is largely controlled by the deployment of race-specific resistance (R) genes. However, selection pressure exerted by R genes causes Lm to adapt and give rise to new virulent strains through mutation and deletion of effector genes. Therefore, a knowledge of effector gene function is necessary for the effective management of the disease. Here, we report the cloning of Lm effector AvrLm9 which is recognized by the resistance gene Rlm9 in B. napus cultivar Goéland. AvrLm9 was mapped to scaffold 7 of the Lm genome, co-segregating with the previously reported AvrLm5 (previously known as AvrLmJ1). Comparison of AvrLm5 alleles amongst the 37 re-sequenced Lm isolates and transgenic complementation identified a single point mutation correlating with the AvrLm9 phenotype. Therefore, we renamed this gene as AvrLm5-9 to reflect the dual specificity of this locus. Avrlm5-9 transgenic isolates were avirulent when inoculated on the B. napus cultivar Goéland. The expression of AvrLm5-9 during infection was monitored by RNA sequencing. The recognition of AvrLm5-9 by Rlm9 is masked in the presence of AvrLm4-7, another Lm effector. AvrLm5-9 and AvrLm4-7 do not interact, and AvrLm5-9 is expressed in the presence of AvrLm4-7. AvrLm5-9 is the second Lm effector for which host recognition is masked by AvrLm4-7. An understanding of this complex interaction will provide new opportunities for the engineering of broad-spectrum recognition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".