N-terminally truncated helper NLR <i>NRG1C</i> antagonizes immunity mediated by its full-length neighbors <i>NRG1A</i> and <i>NRG1B</i>
Bibliographic record
Abstract
Abstract Both animals and plants utilize nucleotide-binding leucine-rich repeat immune receptors (NLRs) to perceive the presence of pathogen-derived molecules and induce immune responses. NLR genes are far more abundant and diverse in higher plants. Interestingly, truncated NLRs, which lack one or more of the canonical domains, are also commonly encoded in plant genomes. However, little is known about their functions, especially regarding the N-terminally truncated ones. Here, we show that Arabidopsis thaliana ( A. thaliana ) N-terminally truncated helper NLR gene NRG1C ( N REQUIREMENT GENE 1 ) is highly induced upon pathogen infection and in autoimmune mutants. The immune response and cell death conferred by some TIR (Toll/interleukin-1 receptor)-type NLRs (TNLs) are compromised in the NRG1C overexpression lines. Detailed genetic analysis revealed that NRG1C antagonizes the immunity mediated by its full-length neighbors NRG1A and NRG1B . Biochemical tests indicate that NRG1C possibly interferes with the EDS1-SAG101 complex, which likely signals together with NRG1A/1B. Interestingly, Brassicaceae NRG1Cs are functionally exchangeable, and the Nicotiana benthamiana ( N. benthamiana ) N-terminally truncated helper NLR NRG2 antagonizes NRG1 in tobacco. Together, our study uncovers an unexpected negative role of N-terminally truncated helper NLRs in different plants.
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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".