Transportin-SR Is Required for Proper Splicing of Resistance Genes and Plant Immunity
Bibliographic record
Abstract
Transportin-SR (TRN-SR) is a member of the importin-β super-family that functions as the nuclear import receptor for serine-arginine rich (SR) proteins, which play diverse roles in RNA metabolism. Here we report the identification and cloning of mos14 (modifier of snc1-1, 14), a mutation that suppresses the immune responses conditioned by the auto-activated Resistance (R) protein snc1 (suppressor of npr1-1, constitutive 1). MOS14 encodes a nuclear protein with high similarity to previously characterized TRN-SR proteins in animals. Yeast two-hybrid assays showed that MOS14 interacts with AtRAN1 via its N-terminus and SR proteins via its C-terminus. In mos14-1, localization of several SR proteins to the nucleus was impaired, confirming that MOS14 functions as a TRN-SR. The mos14-1 mutation results in altered splicing patterns of SNC1 and another R gene RPS4 and compromised resistance mediated by snc1 and RPS4, suggesting that nuclear import of SR proteins by MOS14 is required for proper splicing of these two R genes and is important for their functions in plant immunity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".