Transcriptional programs regulating seed dormancy and its release by after‐ripening in common wheat (<i>Triticum aestivum</i> L.)
Bibliographic record
Abstract
Seed dormancy is an important agronomic trait in wheat (Trticum aestivum). Seeds can be released from a physiologically dormant state by after-ripening. To understand the molecular mechanisms underlying the role of after-ripening in conferring developmental switches from dormancy to germination in wheat seeds, we performed comparative transcriptomic analyses between dormant (D) and after-ripened (AR) seeds in both dry and imbibed states. Transcriptional activation of genes represented by a core of 22 and 435 probesets was evident in the dry and imbibed states of D seeds, respectively. Furthermore, two-way ANOVA analysis identified 36 probesets as specifically regulated by dormancy. These data suggest that biological functions associated with these genes are involved in the maintenance of seed dormancy. Expression of genes encoding protein synthesis/activity inhibitors was significantly repressed during after-ripening, leading to dormancy decay. Imbibing AR seeds led to transcriptional activation of distinct biological processes, including those related to DNA replication, nitrogen metabolism, cytoplasmic membrane-bound vesicle, jasmonate biosynthesis and cell wall modification. These after-ripening-mediated transcriptional programs appear to be regulated by epigenetic mechanisms. Clustering of our microarray data produced 16 gene clusters; dormancy-specific probesets and abscisic acid (ABA)-responsive elements were significantly overrepresented in two clusters, indicating the linkage of dormancy in wheat with that of seed sensitivity to ABA. The role of ABA signalling in regulating wheat seed dormancy was further supported by the down-regulation of ABA response-related probesets in AR seeds and absence of differential expression of ABA metabolic genes between D and AR seeds.
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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".