DELLA1-Mediated Gibberellin Signaling Regulates Cytokinin-Dependent Symbiotic Nodulation
Bibliographic record
Abstract
In legume plants, low-nitrogen soils promote symbiotic interactions with rhizobial bacteria, leading to the formation of nitrogen-fixing root nodules. Among critical signals regulating this developmental process are bacterial Nod Factors (NFs) and several plant hormones, including cytokinins (CKs) and gibberellins (GAs). Here, we show in Medicago truncatula that GA signaling mediated by DELLA1 decreases the amount of bioactive CKs in roots and negatively impacts the Cytokinin Response1 (CRE1)-dependent NF activation of a subset of CK-signaling genes as well as of the CK-regulated Nodulation Signaling Pathway2 and Ethylene Response Factor Required for Nodulation1 early nodulation genes. Consistently, a dominant-active DELLA1 protein can partially rescue the reduced nodulation of the cre1 mutant and triggers the formation of nodule-like structures when expressed in the root cortex or in the root epidermis. This suggests a model where the DELLA1-mediated GA signaling interplays with the CRE1-dependent CK pathway to regulate early nodulation in response to both NF and CK signals critical for this symbiotic interaction.
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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".