Forward and reverse genetics to identify genes involved in the age‐related resistance response in <i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
SUMMARY Age-related resistance (ARR) occurs in numerous plant species, often resulting in increased disease resistance as plants mature. ARR in Arabidopsis to Pseudomonas syringae pv. tomato is associated with intercellular salicylic acid (SA) accumulation and the transition to flowering. Forward and reverse genetic screens were performed to identify genes required for ARR and to investigate the mechanism of the ARR response. Infiltration of SA into the intercellular space of the ARR-defective mutant iap1-1 (important for the ARR pathway) partially restored ARR function. Inter- and intracellular SA accumulation was reduced in the mutant iap1-1 compared with the wild-type, and the SA regulatory gene EDS1 was also required for ARR. Combining microarray analysis with reverse genetics using T-DNA insertion lines, four additional ARR genes were identified as contributing to ARR: two plant-specific transcription factors of the NAC family [ANAC055 (At3g15500) and ANAC092 (At5g39610)], a UDP-glucose glucosyltransferase [UGT85A1 (At1g22400)] and a cytidine deaminase [CDA1 (At2g19570)]. These four genes and IAP1 are also required for ARR to Hyaloperonospora parasitica. IAP1 encodes a key component of ARR that acts upstream of SA accumulation and possibly downstream of UGT85A1, CDA1 and the two NAC transcription factors (ANAC055, ANAC092).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".