Interaction of BES1 and LBD37 transcription factors modulates brassinosteroid-regulated root forging response under low nitrogen in arabidopsis
Bibliographic record
Abstract
Brassinosteriod (BR) plays important roles in regulation of plant growth, development and environmental responses. BR signaling regulates multiple biological processes through controlling the activity of BES1/BZR1 regulators. Apart from the roles in the promotion of plant growth, BR is also involved in regulation of the root foraging response under low nitrogen, however how BR signaling regulate this process remains unclear. Here we show that BES1 and LBD37 antagonistically regulate root foraging response under low nitrogen conditions. Both the transcriptional level and dephosphorylated level of BES1, is significant induced by low nitrogen, predominantly in root. Phenotypic analysis showed that BES1 gain-of-function mutant or BES1 overexpression transgenic plants exhibits progressive outgrowth of lateral root in response to low nitrogen and BES1 negatively regulates repressors of nitrate signaling pathway and positively regulates several key genes required for NO3- uptake and signaling. In contrast, BES1 knock-down mutant BES1-RNAi exhibited a dramatical reduction of lateral root elongation in response to low N. Furthermore, we identified a BES1 interacting protein, LBD37, which is a negative repressor of N availability signals. Our results showed that BES1 can inhibit LBD37 transcriptional repression on N-responsive genes. Our results thus demonstrated that BES1-LBD37 module acts critical nodes to integrate BR signaling and nitrogen signaling to modulate the root forging response at LN condition.
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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) | 0.002 | 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".