Transgenic, non‐isoprene emitting poplars don’t like it hot
Bibliographic record
Abstract
The physiological role of isoprene emission in plants is a matter of much debate. One of the most widely propagated hypotheses suggests a function of isoprene in the protection of leaf physiological processes against thermal and oxidative stress. To test this hypothesis, we developed transgenic Grey poplar (Populusxcanescens) plants in which gene expression of isoprene synthase (ISPS) was either silenced by RNA interference (RNAi) or upregulated by over-expression of the ISPS gene. Despite increased ISPS mRNA levels, we did not observe consistent increases in isoprene emission in the over-expressing lines, indicating post-transcriptional control of ISPS by co-suppression. In the RNAi lines, levels of isoprene emission were effectively suppressed to virtually zero. Transgenic plants were subjected to temperature stress with three transient heat phases of 38-40 degrees C, each followed by phases of recovery at 30 degrees C. Parallel measurements of gas exchange, chlorophyll fluorescence and isoprene emission provided new insights into the physiological link between isoprene and enhanced temperature tolerance. Transgenic non-isoprene-emitting poplars showed reduced rates of net assimilation and photosynthetic electron transport during heat stress, but not in the absence of stress. The decrease in the efficiency of photochemistry was inversely correlated with the increase in heat dissipation of absorbed light energy, measured as NPQ (non-photochemical quenching). Isoprene-repressed poplars also displayed an increased formation of the xanthophyll cycle pigment zeaxanthin in the absence of stress, which can cause increased NPQ or may indicate an increased requirement for antioxidants. In conclusion, using a molecular genetic approach, we show that down-regulation of isoprene emission affects thermotolerance of photosynthesis and induces increased energy dissipation by NPQ pathways.
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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) | 0.002 | 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".