<scp><i>SLG2</i></scp> specifically regulates grain width through <scp><i>WOX11</i></scp>‐mediated cell expansion control in rice
Bibliographic record
Abstract
Grain size is specified by three dimensions of length, width and thickness, and slender grain is a desirable quality trait in rice. Up to now, many grain size regulators have been identified. However, most of these molecules show influence on multi-dimensions of grain development, and only a few of them function specifically in grain width, a key factor determining grain yield and appearance quality. In this study, we identify the SLG2 (SLENDER GUY2) gene that specifically regulates grain width by affecting cell expansion in the spikelet hulls. SLG2 encodes a WD40 domain containing protein, and our biochemical analyses show that SLG2 acts as a transcription activator of its interacting WOX family protein WOX11. We demonstrate that the SLG2-associated WOX11 binds directly to the promoter of OsEXPB7, one of the downstream cell expansion genes. We show that knockout of WOX11 results in plants with a slender grain phenotype similar to the slg2 mutant. We also present that finer grains with different widths could be produced by combining SLG2 with the grain width regulator GW8. Collectively, we uncover the crucial role of SLG2 in grain width control, and provide a promising route to design rice plants with better grain shape and quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".