The Arabidopsis <scp> <i>WRR4A</i> </scp> and <scp> <i>WRR4B</i> </scp> paralogous <scp>NLR</scp> proteins both confer recognition of multiple <i>Albugo candida</i> effectors
Bibliographic record
Abstract
Summary The oomycete Albugo candida causes white blister rust, an important disease of Brassica crops. Distinct races of A. candida are defined by their capacity to infect different host plant species. Each A. candida race encodes secreted proteins with a CX 2 CX 5 G (‘CCG’) motif that are polymorphic and show presence/absence variation, and are therefore candidate effectors . The White Rust Resistance 4 ( WRR4 ) locus in Arabidopsis thaliana accession Col‐0 contains three genes that encode intracellular nucleotide‐binding domain leucine‐rich repeat immune receptors. The Col‐0 alleles of WRR4A and WRR4B confer resistance to multiple A. candida races, although both WRR4A and WRR4B can be overcome by the Col‐0‐virulent race 4 isolate AcEx1. Comparison of CCG candidate effectors in avirulent and virulent races, and transient co‐expression of CCG effectors from four A. candida races in Nicotiana sp. or A. thaliana , revealed CCG effectors that trigger WRR4A‐ or WRR4B‐dependent hypersensitive responses. We found eight WRR4A‐recognised CCGs and four WRR4B‐recognised CCGs, the first recognised proteins from A. candida for which the cognate immune receptors in A. thaliana are known. This multiple recognition capacity potentially explains the broad‐spectrum resistance to several A. candida races conferred by WRR4 paralogues. We further show that of five tested CCGs, three confer enhanced disease susceptibility when expressed in planta , consistent with A. candida CCG proteins being effectors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".