The cellular function of ROP GTPase prenylation is important for multicellularity in the moss <i>Physcomitrium patens</i>
Bibliographic record
Abstract
A complete picture of how signaling pathways lead to multicellularity is largely unknown. Previously, we generated mutations in a protein prenylation enzyme, GGB, and showed that it is essential for maintaining multicellularity in the moss Physcomitrium patens. Here, we show that ROP GTPases act as downstream factors that are prenylated by GGB and themselves play an important role in the multicellularity of P. patens. We also show that the loss of multicellularity caused by the suppression of GGB or ROP GTPases is due to uncoordinated cell expansion, defects in cell wall integrity and the disturbance of the directional control of cell plate orientation. Expressing prenylatable ROP in the ggb mutant not only rescues multicellularity in protonemata but also results in development of gametophores. Although the prenylation of ROP is important for multicellularity, a higher threshold of active ROP is required for gametophore development. Thus, our results suggest that ROP activation via prenylation by GGB is a key process at both cell and tissue levels, facilitating the developmental transition from one dimension to two dimensions and to three dimensions in P. patens.
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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) | 0.000 | 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".