Rice Cytokinin GATA Transcription Factor1 Regulates Chloroplast Development and Plant Architecture
Bibliographic record
Abstract
Chloroplast biogenesis has been well documented in higher plants, yet the complex methods used to regulate chloroplast activity under fluctuating environmental conditions are not well understood. In rice (Oryza sativa), the CYTOKININ-RESPONSIVE GATA TRANSCRIPTION FACTOR1 (Cga1) shows increased expression following light, nitrogen, and cytokinin treatments, while darkness and gibberellin reduce expression. Strong overexpression of Cga1 produces dark green, semidwarf plants with reduced tillering, whereas RNA interference knockdown results in reduced chlorophyll and increased tillering. Coexpression, microarray, and real-time expression analyses demonstrate a correlation between Cga1 expression and the expression of important nucleus-encoded, chloroplast-localized genes. Constitutive Cga1 overexpression increases both chloroplast biogenesis and starch production but also results in delayed senescence and reduced grain filling. Growing the transgenic lines under different nitrogen regimes indicates potential agricultural applications for Cga1, including manipulation of biomass, chlorophyll/chloroplast content, and harvest index. These results indicate a conserved mechanism by which Cga1 regulates chloroplast development in higher plants.
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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".