SRFR1 Negatively Regulates Plant NB-LRR Resistance Protein Accumulation to Prevent Autoimmunity
Bibliographic record
Abstract
Plant defense responses need to be tightly regulated to prevent auto-immunity, which is detrimental to growth and development. To identify negative regulators of Resistance (R) protein-mediated resistance, we screened for mutants with constitutive defense responses in the npr1-1 background. Map-based cloning revealed that one of the mutant genes encodes a conserved TPR domain-containing protein previously known as SRFR1 (SUPPRESSOR OF rps4-RLD). The constitutive defense responses in the srfr1 mutants in Col-0 background are suppressed by mutations in SNC1, which encodes a TIR-NB-LRR (Toll Interleukin1 Receptor-Nucleotide Binding-Leu-Rich Repeat) R protein. Yeast two-hybrid screens identified SGT1a and SGT1b as interacting proteins of SRFR1. The interactions between SGT1 and SRFR1 were further confirmed by co-immunoprecipitation analysis. In srfr1 mutants, levels of multiple NB-LRR R proteins including SNC1, RPS2 and RPS4 are increased. Increased accumulation of SNC1 is also observed in the sgt1b mutant. Our data suggest that SRFR1 functions together with SGT1 to negatively regulate R protein accumulation, which is required for preventing auto-activation of plant immunity.
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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) | 0.001 | 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".