The <i>ABSCISIC ACID INSENSITIVE 3</i> (<i>ABI3</i>) gene is modulated by farnesylation and is involved in auxin signaling and lateral root development in <i>Arabidopsis</i>
Bibliographic record
Abstract
Genetic screens have identified a number of genes that regulate abscisic acid (ABA) responsiveness in Arabidopsis. Using a combination of suppressor screens and double mutant analysis, we have determined a genetic relationship for a number of these ABA response loci. Based on germination in the presence of exogenous ABA, the ABI1 and ABI2 phosphatases act at or upstream of the ERA1 farnesyl transferase and the ABI3 and ABI5 transcription factors act at or downstream of ERA1. In contrast with ABI3 and ABI5, the ABI4 transcription factor appears to act at or upstream of ERA1. Based on reporter gene constructs, the upstream regulation of ABI3 by ERA1 occurs at least partially at the level of transcription, suggesting that this lipid modification is required to attenuate ABI3 expression. Similar experiments also indicate that ABI3 is auxin inducible in lateral root primordia. Related to this, loss-of-function abi3 alleles show reduced lateral root responsiveness in the presence of auxin and an auxin transport inhibitor, and era1 mutants have increased numbers of lateral roots. These results suggest the possibility that genes identified through ABA responsive germination screens such as ERA1 and ABI3 have functions in auxin action 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) | 0.000 | 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 | 0.001 |
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".