Novel and Expanded Roles for MAPK Signaling in<i>Arabidopsis</i>Stomatal Cell Fate Revealed by Cell Type–Specific Manipulations
Bibliographic record
Abstract
Mitogen-activated protein kinase (MAPK) signaling networks regulate numerous eukaryotic biological processes. In Arabidopsis thaliana, signaling networks that contain MAPK kinases MKK4/5 and MAPKs MPK3/6 function in abiotic and biotic stress responses and regulate embryonic and stomatal development. However, how single MAPK modules direct specific output signals without cross-activating additional downstream processes is largely unknown. Studying relationships between MAPK components and downstream signaling outcomes is difficult because broad experimental manipulation of these networks is often lethal or associated with multiple phenotypes. Stomatal development in Arabidopsis follows a series of discrete, stereotyped divisions and cell state transitions. By expressing a panel of constitutively active MAPK kinase (MAPKK) variants in discrete stomatal lineage cell types, we identified a new inhibitory function of MKK4 and MKK5 in meristemoid self-renewal divisions. Furthermore, we established roles for MKK7 and MKK9 as both negative and (unexpectedly) positive regulators during the major stages of stomatal development. This has expanded the number of known MAPKKs that regulate stomatal development and allowed us to build plausible and testable subnetworks of signals. This in vivo cell type-specific assay can be adapted to study other protein families and thus may reveal insights into other complex signal transduction pathways in 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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".