<i>WRR4,</i> a broad‐spectrum TIR‐NB‐LRR gene from <i>Arabidopsis thaliana</i> that confers white rust resistance in transgenic oilseed brassica crops
Bibliographic record
Abstract
White blister rust caused by Albugo candida (Pers.) Kuntze is a common and often devastating disease of oilseed and vegetable brassica crops worldwide. Physiological races of the parasite have been described, including races 2, 7 and 9 from Brassica juncea, B. rapa and B. oleracea, respectively, and race 4 from Capsella bursa-pastoris (the type host). A gene named WRR4 has been characterized recently from polygenic resistance in the wild brassica relative Arabidopsis thaliana (accession Columbia) that confers broad-spectrum white rust resistance (WRR) to all four of the above Al. candida races. This gene encodes a TIR-NB-LRR (Toll-like/interleukin-1 receptor-nucleotide binding-leucine-rich repeat) protein which, as with other known functional members in this subclass of intracellular receptor-like proteins, requires the expression of the lipase-like defence regulator, enhanced disease susceptibility 1 (EDS1). Thus, we used RNA interference-mediated suppression of EDS1 in a white rust-resistant breeding line of B. napus (transformed with a construct designed from the A. thaliana EDS1 gene) to determine whether defence signalling via EDS1 is functionally intact in this oilseed brassica. The eds1-suppressed lines were fully susceptible following inoculation with either race 2 or 7 isolates of Al. candida. We then transformed white rust-susceptible cultivars of B. juncea (susceptible to race 2) and B. napus (susceptible to race 7) with the WRR4 gene from A. thaliana. The WRR4-transformed lines were resistant to the corresponding Al. candida race for each host species. The combined data indicate that WRR4 could potentially provide a novel source of white rust resistance in oilseed and vegetable brassica crops.
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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) | 0.002 | 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".