Abscisic acid deficiency of developing pea embryos achieved by immunomodulation attenuates developmental phase transition and storage metabolism
Bibliographic record
Abstract
The transition of pea embryos from pre-storage to maturation is partially controlled by abscisic acid (ABA). Immunomodulation in pea embryos specifically reduces free ABA levels during transition stages. Such seeds are, therefore, suitable models for studying ABA deficiency by global transcript and metabolite analysis. Compared with the wild type, anti-ABA seeds are smaller, contain fewer globulins and show lower dry matter accumulation and delayed differentiation. Free sugars are decreased, indicating lower uptake and/or elevated mobilisation. Lower levels of trans-zeatins suggest that ABA reduction influences rates of cytokinin synthesis and/or its level of accumulation. Abscisic acid deficiency leads to a general downregulation of gene expression related to transcription and translation. At the transcriptional level, anti-ABA embryos reveal a wide-range repression of carbohydrate oxidation, downregulated sucrose mobilisation, glycolysis and the tricarboxylic acid cycle/Krebs cycle (TCA cycle). Genes related to starch, amino acid and storage protein biosynthesis are downregulated, indicating a general decrease in metabolic fluxes. We conclude that during embryo differentiation ABA triggers broad upregulation of gene activity and genetic reprogramming, involving regulated protein degradation via the ubiquitin/proteasome system. Abscisic acid deficiency affects gene expression associated with transport processes and stimulation of membrane energisation. Our study identified mediators and downstream signalling elements of ABA during embryo differentiation, such as the transcription factor FUSCA3, SnRK1 kinase and Ca(2+) signalling processes. This suggests that ABA interacts with SnRK1 complexes, thus connecting SnRK1, sugar and stress signalling with ABA. Certain protein kinases/phosphatases known to negatively respond to ABA are upregulated in the modulated line, whilst those which respond positively are downregulated, pointing to a highly coordinated response of the gene network to ABA levels.
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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".