MOS2 has redundant function with its homolog MOS2H and is required for proper splicing of<i>SNC1</i>
Bibliographic record
Abstract
Plant immunity is essential for plant survival and resistance (R) proteins serve essential roles in pathogen detection and defense signal initiation. A gain-of-function mutation in SNC1, a TIR-type R gene, results in a characteristic autoimmune phenotype in Arabidopsis. From a forward genetic suppressor screen using snc1, MOS2 (MODIFIER of snc1), which encodes an RNA-binding protein, was identified. When MOS2 function is lost, the autoimmunity caused by snc1 is abolished and basal resistance against virulent pathogens is attenuated. Recently, it was shown that mos2 mutants also have defects in miRNA processing. However, it is not known how the role of MOS2 in miRNA production is related to the suppression of snc1-mediated autoimmunity. Here, we show that MOS2 contributes to proper splicing of SNC1 transcript, agreeing with its potential association with the MOS4-associated complex (MAC). In addition, although mutant plants carrying a mutation in the MOS2 homolog MOS2H are wild-type like, the double mutant mos2 mos2h is lethal. These data suggest that MOS2 and MOS2H have unequally redundant functions. Overall, MOS2 and MOS2H probably have diverse functions in both alternative splicing and miRNA processing.
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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 | 0.000 |
| 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".