ASIL1 is required for proper timing of seed filling in Arabidopsis
Bibliographic record
Abstract
In flowering plants, seed development and seed filling are intricate genetically programmed processes that correlate with changes in metabolite levels and that are spatially and temporally regulated by a complex signaling network mediated mainly by sugars and hormones. ASIL1, a member of the plant-specific trihelix family of DNA-binding transcription factors, was isolated based on its interaction with the GT-element of the Arabidopsis thaliana 2S albumin At2S3 promoter. Mutation of ASIL1 derepressed expression of a subset of embryonic genes resulting in accumulation of 2S albumin and embryo-specific lipids in leaves. It was recently reported that mutation of ASIL1 led to early embryo development in Arabidopsis. In this study, we demonstrated that ASIL1 acts as a temporal regulator of seed filling. In developing siliques, mutation of ASIL1 led to earlier expression of master regulatory genes LEC2, FUS3 and ABI3 as well as genes for seed storage reserves. Moreover, the 12S globulin accumulated to a much higher level in the developing seeds of asil1-1 compared to wild type. To our knowledge, this is the first evidence that ASIL1 not only functions as a negative regulator of embryonic traits in seedlings but also contributes to the maintenance of precise temporal control of seed filling. Thus, ASIL1 represents a novel component of the regulatory framework controlling embryonic gene expression in Arabidopsis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".