Constitutive down-regulation of SiSGR gene is related to green millet in Setaria italica
Bibliographic record
Abstract
Millet colour is an important index to evaluate the quality of dehulled foxtail millet ( Setaria italica (L.) Beauv.). Most varieties are yellow, due to the accumulation of carotenoids. However, there are some foxtail millet germplasms producing dark green millet. To elucidate the molecular mechanism of the chlorophyll retention phenotype, Daqinggu with green millet colour and Jingu 21 with yellow millet colour were selected as research material in this study. The total carotenoid level in dehulled millet of Daqinggu was about 0.024 mg/g, and 0.038 mg/g in Jingu 21. The transcript levels of carotenoid structural genes were investigated at three stages of grain development in both millet varieties. The expression levels of carotenoid biosysnthesis-related genes SiPSY3, SiPDS, SiZ-ISO, SiLCYB and SiCYP97C were significantly higher in Daqinggu than in Jingu 21, which was not consistent with the difference in the carotenoid levels between these two varieties. Interestingly, SiSGR , a homologue to the STAY-GREEN gene in Arabidopsis, tomato, and rice, was constitutively down-regulated during maturation in Daqinggu. In addition, the total chlorophyll content was consistently higher in Daqinggu than in Jingu21 during grain maturation. These evidences suggest that SiSGR is a key gene in regulating chlorophyll retention for dark green foxtail millet.
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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".