The relationship of drought-related gene expression in Arabidopsis thaliana to hormonal and environmental factors
Bibliographic record
Abstract
Almost 2000 drought-responsive genes were identified in Arabidopsis thaliana under progressive soil drought stress using whole-genome oligonucleotide microarrays. Most of the drought-regulated genes recovered to normal expression levels by 3 h after rewatering. It has previously been shown that the abscisic acid (ABA) analogue (+)-8'-acetylene-ABA (PBI425) hyperinduces many ABA-like changes in gene expression to reveal a more complete list of ABA-regulated genes, and it is demonstrated here that PBI425 produced a correspondingly increased drought tolerance. About two-thirds of drought-responsive genes (1310 out of 1969) were regulated by ABA and/or the ABA analogue PBI425. Analysis of promoter motifs suggests that many of the remaining drought-responsive genes may be affected by ABA signalling. Concentrations of endogenous ABA and its catabolites significantly increased under drought stress and either completely (ABA) or partially (ABA catabolites) recovered to normal levels by 3 h after rehydration. Detailed analyses of drought transcript profiles and in silico comparisons with other studies revealed that the ABA-dependent pathways are predominant in the drought stress responses. These comparisons also showed that other plant hormones including jasmonic acid, auxin, cytokinin, ethylene, brassinosteroids, and gibberellins also affected drought-related gene expression, of which the most significant was jasmonic acid. There is also extensive cross-talk between responses to drought and other environmental factors including light and biotic stresses. These analyses demonstrate that ABA-related stress responses are modulated by other environmental and developmental factors.
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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 | 0.000 |
| 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".