Metabolic and transcriptional regulatory mechanisms underlying the anoxic adaptation of rice coleoptile
Bibliographic record
Abstract
The ability of rice to germinate under anoxia by extending the coleoptile is a highly unusual characteristic and a key feature underpinning the ability of rice seeds to establish in such a stressful environment. The process has been a focal point for research for many years. However, the molecular mechanisms underlying the anoxic growth of the coleoptile still remain largely unknown. To unravel the key regulatory mechanisms of rice germination under anoxic stress, we combined in silico modelling with gene expression data analysis. Our initial modelling analysis via random flux sampling revealed numerous changes in rice primary metabolism in the absence of oxygen. In particular, several reactions associated with sucrose metabolism and fermentation showed a significant increase in flux levels, whereas reaction fluxes across oxidative phosphorylation, the tricarboxylic acid cycle and the pentose phosphate pathway were down-regulated. The subsequent comparative analysis of the differences in calculated fluxes with previously published gene expression data under air and anoxia identified at least 37 reactions from rice central metabolism that are transcriptionally regulated. Additionally, cis-regulatory content analyses of these transcriptionally controlled enzymes indicate a regulatory role for transcription factors such as MYB, bZIP, ERF and ZnF in transcriptional control of genes that are up-regulated during rice germination and coleoptile elongation under anoxia.
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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) | 0.000 | 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 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".