Temporal Dynamics of Growth and Photosynthesis Suppression in Response to Jasmonate Signaling
Bibliographic record
Abstract
Biotic stress constrains plant productivity in natural and agricultural ecosystems. Repression of photosynthetic genes is a conserved plant response to biotic attack, but how this transcriptional reprogramming is linked to changes in photosynthesis and the transition from growth- to defense-oriented metabolism is poorly understood. Here, we used a combination of noninvasive chlorophyll fluorescence imaging technology and RNA sequencing to determine the effect of the defense hormone jasmonate (JA) on the growth, photosynthetic efficiency, and gene expression of Arabidopsis (Arabidopsis thaliana) rosette leaves. High temporal resolution was achieved through treatment with coronatine (COR), a high-affinity agonist of the JA receptor. We show that leaf growth is rapidly arrested after COR treatment and that this effect is tightly correlated with changes in the expression of genes involved in growth, photosynthesis, and defense. Rapid COR-induced expression of defense genes occurred concomitantly with the repression of photosynthetic genes but was not associated with a reduced quantum efficiency of photosystem II. These findings support the view that photosynthetic capacity is maintained during the period in which stress-induced JA signaling redirects metabolism from growth to defense. Chlorophyll fluorescence images captured in a multiscale time series, however, revealed a transient COR-induced decrease in quantum efficiency of photosystem II at dawn of the day after treatment. Physiological studies suggest that this response results from delayed stomatal opening at the night-day transition. These collective results establish a high-resolution temporal view of how a major stress response pathway modulates plant growth and photosynthesis and highlight the utility of chlorophyll fluorescence imaging for revealing transient stress-induced perturbations in photosynthetic performance.
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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".