Genome-wide analysis of endogenous abscisic acid-mediated transcription in dry and imbibed seeds of Arabidopsis using tiling arrays
Bibliographic record
Abstract
The phytohormone abscisic acid (ABA) plays important roles in the induction and maintenance of seed dormancy. Although application of exogenous ABA inhibits germination, the effects of exogenous ABA on ABA-mediated gene transcription differ from those of endogenous ABA. To understand how endogenous ABA regulates the transcriptomes in seeds, we performed comprehensive expression analyses using whole-genome Affymetrix tiling arrays in two ABA metabolism mutants - an ABA-deficient mutant (aba2) and an ABA over-accumulation mutant (cyp707a1a2a3 triple mutant). Hierarchical clustering and principal components analyses showed that differences in endogenous ABA levels do not influence global expression of stored mRNA in dry seeds. However, the transcriptome after seed imbibition was related to endogenous ABA levels in both types of mutant. Endogenous ABA-regulated genes expressed in imbibed seeds included those encoding key ABA signaling factors and gibberellin-related components. In addition, cohorts of ABA-upregulated genes partially resembled those of dormant genes, whereas ABA-downregulated genes were partially overlapped with after-ripening-regulated genes. Bioinformatic analyses revealed that 6105 novel genes [non-Arabidopsis Genome Initiative (AGI) transcriptional units (TUs)] were expressed from unannotated regions. Interestingly, approximately 97% of non-AGI TUs possibly encoded hypothetical non-protein-coding RNAs, including a large number of antisense RNAs. In dry and imbibed seeds, global expression profiles of non-AGI TUs were similar to those of AGI genes. For both non-AGI TUs and AGI code genes, we identified those that were regulated differently in embryo and endosperm tissues. Our results suggest that transcription in Arabidopsis seeds is more complex and dynamic than previously thought.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".