Transcriptomics of cytokinin and auxin metabolism and signaling genes during seed maturation in dormant and non-dormant wheat genotypes
Bibliographic record
Abstract
To gain insights into the roles of cytokinin (CK) and auxin in regulating dormancy during seed maturation in wheat, we examined changes in the levels of CK and indole-3-acetic acid (IAA) and expression patterns of their metabolism and signaling genes in embryonic and endospermic tissues of dormant and non-dormant genotypes. Seed maturation was associated with a decrease in the levels of isopentenyladenine in both tissues mainly via repression of the CK biosynthetic TaLOG genes. Differential embryonic trans-zeatin content and expression patterns of the CK related genes including TacZOG, TaGLU and TaARR12 between maturing seeds of the two genotypes implicate CK in the control of seed dormancy induction and maintenance. Seed maturation induced a decrease of IAA level in both tissues irrespective of genotype, and this appeared to be mediated by repression of specific IAA biosynthesis, transport and IAA-conjugate hydrolysis genes. The differential embryonic IAA content and expression pattern of the IAA biosynthetic gene TaAO during the early stage of seed maturation between the two genotypes imply the role of IAA in dormancy induction. It appears from our data that the expression of specific auxin signaling genes including TaRUB, TaAXR and TaARF mediate the role of auxin signaling in dormancy induction and maintenance during seed maturation in wheat.
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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".