Multiple PLDs Required for High Salinity and Water Deficit Tolerance in Plants
Bibliographic record
Abstract
High salinity and drought have received much attention because they severely affect crop production worldwide. Analysis and comprehension of the plant's response to excessive salt and dehydration will aid in the development of stress-tolerant crop varieties. Signal transduction lies at the basis of the response to these stresses, and numerous signaling pathways have been implicated. Here, we provide further evidence for the involvement of phospholipase D (PLD) in the plant's response to high salinity and dehydration. A tomato (Lycopersicon esculentum) alpha-class PLD, LePLDalpha1, is transcriptionally up-regulated and activated in cell suspension cultures treated with salt. Gene silencing revealed that this PLD is indeed involved in the salt-induced phosphatidic acid production, but not exclusively. Genetically modified tomato plants with reduced LePLDalpha1 protein levels did not reveal altered salt tolerance. In Arabidopsis (Arabidopsis thaliana), both AtPLDalpha1 and AtPLDdelta were found to be activated in response to salt stress. Moreover, pldalpha1 and plddelta single and double knock-out mutants exhibited enhanced sensitivity to high salinity stress in a plate assay. Furthermore, we show that both PLDs are activated upon dehydration and the knock-out mutants are hypersensitive to hyperosmotic stress, displaying strongly reduced growth.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".