Evolution of chloroplast retrograde signaling facilitates green plant adaptation to land
Bibliographic record
Abstract
Chloroplast retrograde signaling networks are vital for chloroplast biogenesis, operation, and signaling, including excess light and drought stress signaling. To date, retrograde signaling has been considered in the context of land plant adaptation, but not regarding the origin and evolution of signaling cascades linking chloroplast function to stomatal regulation. We show that key elements of the chloroplast retrograde signaling process, the nucleotide phosphatase (SAL1) and 3′-phosphoadenosine-5′-phosphate (PAP) metabolism, evolved in streptophyte algae—the algal ancestors of land plants. We discover an early evolution of SAL1-PAP chloroplast retrograde signaling in stomatal regulation based on conserved gene and protein structure, function, and enzyme activity and transit peptides of SAL1s in species including flowering plants, the fern Ceratopteris richardii , and the moss Physcomitrella patens . Moreover, we demonstrate that PAP regulates stomatal closure via secondary messengers and ion transport in guard cells of these diverse lineages. The origin of stomata facilitated gas exchange in the earliest land plants. Our findings suggest that the conquest of land by plants was enabled by rapid response to drought stress through the deployment of an ancestral SAL1-PAP signaling pathway, intersecting with the core abscisic acid signaling in stomatal guard cells.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".