RNAi-mediated suppression of isoprene emission in poplar transiently impacts phenolic metabolism under high temperature and high light intensities: a transcriptomic and metabolomic analysis
Bibliographic record
Abstract
In plants, isoprene plays a dual role: (a) as thermo-protective agent proposed to prevent degradation of enzymes/membrane structures involved in photosynthesis, and (b) as reactive molecule reducing abiotic oxidative stress. The present work addresses the question whether suppression of isoprene emission interferes with genome wide transcription rates and metabolite fluxes in grey poplar (Populus x canescens) throughout the growing season. Gene expression and metabolite profiles of isoprene emitting wild type plants and RNAi-mediated non-isoprene emitting poplars were compared by using poplar Affymetrix microarrays and non-targeted FT-ICR-MS (Fourier transform ion cyclotron resonance mass spectrometry). We observed a transcriptional down-regulation of genes encoding enzymes of phenylpropanoid regulatory and biosynthetic pathways, as well as distinct metabolic down-regulation of condensed tannins and anthocyanins, in non-isoprene emitting genotypes during July, when high temperature and light intensities possibly caused transient drought stress, as indicated by stomatal closure. Under these conditions leaves of non-isoprene emitting plants accumulated hydrogen peroxide (H(2)O(2)), a signaling molecule in stress response and negative regulator of anthocyanin biosynthesis. The absence of isoprene emission under high temperature and light stress resulted transiently in a new chemo(pheno)type with suppressed production of phenolic compounds. This may compromise inducible defenses and may render non-isoprene emitting poplars more susceptible to environmental stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".