Autoimmunity conferred by chs3-2D relies on CSA1, its adjacent TNL-encoding neighbour
Bibliographic record
Abstract
Plant innate immunity depends on the function of a large number of intracellular immune receptor proteins, the majority of which are structurally similar to mammalian nucleotide-binding oligomerization domain (NOD)-like receptor (NLR) proteins. CHILLING SENSITIVE 3 (CHS3) encodes an atypical Toll/Interleukin 1 Receptor (TIR)-type NLR protein with an additional Lin-11, Isl-1 and Mec-3 (LIM) domain at its C-terminus. The gain-of-function mutant allele chs3-2D exhibits severe dwarfism and constitutively activated defense responses, including enhanced resistance to virulent pathogens, high defence marker gene expression, and salicylic acid accumulation. To search for novel regulators involved in CHS3-mediated immune signaling, we conducted suppressor screens in the chs3-2D and chs3-2D pad4-1 genetic backgrounds. Alleles of sag101 and eds1-90 were isolated as complete suppressors of chs3-2D, and alleles of sgt1b were isolated as partial suppressors of chs3-2D pad4-1. These mutants suggest that SAG101, EDS1-90, and SGT1b are all positive regulators of CHS3-mediated defense signaling. Additionally, the TIR-type NLR-encoding CSA1 locus located genomically adjacent to CHS3 was found to be fully required for chs3-2D-mediated autoimmunity. CSA1 is located 3.9 kb upstream of CHS3 and is transcribed in the opposite direction. Altogether, these data illustrate the distinct genetic requirements for CHS3-mediated defense signaling.
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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".