An abscisic acid‐sensitive checkpoint in lateral root development of <i>Arabidopsis</i>
Bibliographic record
Abstract
Lateral root (LR) formation displays considerable plasticity in response to developmental and environmental signals. The mechanism whereby plants incorporate diverse regulatory signals into the developmental programme of LRs remains to be elucidated. Current concepts of lateral root regulation focus on the role of auxin. In this study, we show that another plant hormone, abscisic acid (ABA), also plays a critical role in the regulation of this post-embryonic developmental event. In the presence of exogenous ABA, LR development is inhibited. This occurs at a specific developmental stage, i.e. immediately after the emergence of the LR primordium (LRP) from the parent root and prior to the activation of the LR meristem, and is reversible. Interestingly, this inhibition requires 10-fold less ABA than the inhibition of seed germination and is only slightly reduced in characterised abi mutants, suggesting that it may involve novel ABA signalling mechanisms. We also present several lines of evidence to support the conclusion that the ABA-induced lateral root inhibition is mediated by an auxin-independent pathway. First, the inhibition could not be rescued by either exogenous auxin application or elevated auxin synthesis. Secondly, a mutation in the ALF3 gene, which is believed to encode an important component in the auxin-dependent regulatory pathway for the post-emergence LR development, does not affect the sensitivity of LRs to ABA. Thirdly, ABA and the alf3-1 mutation do not act at the same developmental point. To summarise, these results demonstrate a novel ABA-sensitive, auxin-independent checkpoint for lateral root development in Arabidopsis at the post-emergence stage. In addition, we also present data indicating that regulation of this developmental checkpoint may require novel ABA signalling mechanisms and that ABA suppresses auxin response in the LRPs.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".