Phosphorylation mediated regulation of RNA splicing in plants
Bibliographic record
Abstract
For the past two decades, the study of alternative splicing (AS) and its involvement in plant development and stress response has grown in popularity. Only recently however, has the focus shifted to the study of how AS regulation (or lack-thereof) affects downstream mRNA and protein landscapes and how these AS regulatory events impact plant development and stress tolerance. In humans, protein phosphorylation represents one of the predominant mechanisms by which AS is regulated and thus the protein kinases governing these phosphorylation events are of interest for further study. Large-scale phosphoproteomic studies in plants have consistently found that RNA splicing-related proteins are extensively phosphorylated, however, the signaling pathways involved in AS regulation have not been resolved. In this mini-review, we summarize our current knowledge of the three major splicing-related protein kinase families in plants that are suggested to mediate AS phospho-regulation and draw comparisons to their metazoan orthologs. We also summarize and contextualize the phosphorylation events identified as occurring on splicing-related protein families to illustrate the high degree to which splicing-related proteins are modified, placing a new focus on elucidating the impacts of AS at the protein and PTM-level.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".