SDG712, a Putative H3K9-Specific Methyltransferase Encoding Gene, Delays Flowering through Repressing the Expression of Florigen Genes in Rice
Bibliographic record
Abstract
SET domain group (SDG) proteins have been identified to be involved in histone modification and participate in diverse biological processes. Rice contains 41 SDG genes, however, most of which have not been functionally characterized. Here, we report the identification and functional investigation of rice SDG712 gene. Phylogenic analysis revealed that SDG712 belongs to the H3K9-specific SDG subclade. SDG712 is highly expressed in leaves during reproductive growth stage with obvious circadian rhythmic pattern. Mutation of SDG712 promotes rice flowering, while overexpression of SDG712 delays rice flowering. Gene expression analysis suggested that SDG712 acts downstream of Hd1, while acts upstream of Ehd1, Hd3a and RFT1. Subcellular localization assay demonstrated that SDG712 is localized in the nucleus. Chromatin immunoprecipitation (ChIP) assay showed that the H3K9me2 levels at Hd3a and RFT1 loci were increased in SDG712 overexpression transgenic plants, indicating that SDG712 may mediate the H3K9 di-methylation on these loci to repress rice flowering. Taken together, our findings demonstrated that SDG712 is a negative flowering regulatory gene in rice, and it delays flowering through repressing key flowering regulator gene Ehd1 and the florigen genes Hd3a and RFT1.
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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".