Dynamics of Brassinosteroid Response Modulated by Negative Regulator LIC in Rice
Bibliographic record
Abstract
Brassinosteroids (BRs) regulate rice plant architecture, including leaf bending, which affects grain yield. Although BR signaling has been investigated in Arabidopsis thaliana, the components negatively regulating this pathway are less well understood. Here, we demonstrate that Oryza sativa LEAF and TILLER ANGLE INCREASED CONTROLLER (LIC) acts as an antagonistic transcription factor of BRASSINAZOLE-RESISTANT 1 (BZR1) to attenuate the BR signaling pathway. The gain-of-function mutant lic-1 and LIC-overexpressing lines showed erect leaves, similar to BZR1-depleted lines, which indicates the opposite roles of LIC and BZR1 in regulating leaf bending. Quantitative PCR revealed LIC transcription rapidly induced by BR treatment. Image analysis and immunoblotting showed that upon BR treatment LIC proteins translocate from the cytoplasm to the nucleus in a phosphorylation-dependent fashion. Phosphorylation assay in vitro revealed LIC phosphorylated by GSK3-like kinases. For negative feedback, LIC bound to the core element CTCGC in the BZR1 promoter on gel-shift and chromatin immunoprecipitation assay and repressed its transcription on transient transformation assay. LIC directly regulated target genes such as INCREASED LEAF INCLINATION 1 (ILI1) to oppose the action of BZR1. Repression of LIC in ILI1 transcription in protoplasts was partially rescued by BZR1. Phenotypic analysis of the crossed lines depleted in both LIC and BZR1 suggested that BZR1 functionally depends on LIC. Molecular and physiology assays revealed that LIC plays a dominant role at high BR levels, whereas BZR1 is dominant at low levels. Thus, LIC regulates rice leaf bending as an antagonistic transcription factor of BZR1. The phenotypes of lic-1 and LIC-overexpressing lines in erect leaves contribute to ideal plant architecture. Improving this phenotype may be a potential approach to molecular breeding for high yield in rice.
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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".