<scp>LAZY3</scp> interacts with <scp>LAZY2</scp> to regulate tiller angle by modulating shoot gravity perception in rice
Bibliographic record
Abstract
Starch biosynthesis in gravity-sensing tissues of rice shoot determines the magnitude of rice shoot gravitropism and thus tiller angle. However, the molecular mechanism underlying starch biosynthesis in rice gravity-sensing tissues is still unclear. We characterized a novel tiller angle gene LAZY3 (LA3) in rice through map-based cloning. Biochemical, molecular and genetic studies further demonstrated the essential roles of LA3 in gravity perception of rice shoot and tiller angle control. The shoot gravitropism and lateral auxin transport were defective in la3 mutant upon gravistimulation. We showed that LA3 encodes a chloroplast-localized tryptophan-rich protein associated with starch granules via Tryptophan-rich region (TRR) domain. Moreover, LA3 could interact with the starch biosynthesis regulator LA2, determining starch granule formation in shoot gravity-sensing tissues. LA3 and LA2 negatively regulate tiller angle in the same pathway acting upstream of LA1 to mediate asymmetric distribution of auxin. Our study defined LA3 as an indispensable factor of starch biosynthesis in rice gravity-sensing tissues that greatly broadens current understanding in the molecular mechanisms underlying the starch granule formation in gravity-sensing tissues, and provides new insights into the regulatory mechanism of shoot gravitropism and rice tiller angle.
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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 | 0.001 |
| 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".