SDG714, a Histone H3K9 Methyltransferase, Is Involved in <i>Tos17</i> DNA Methylation and Transposition in Rice
Bibliographic record
Abstract
Although the role of H3K9 methylation in rice (Oryza sativa) is unclear, in Arabidopsis thaliana the loss of histone H3K9 methylation by mutation of Kryptonite [also known as SU(VAR)3-9 homolog] reduces genome-wide DNA methylation and increases the transcription of transposable elements. Here, we report that rice SDG714 (for SET Domain Group Protein714) encodes a histone H3K9-specific methyltransferase. The C terminus of SDG714 confers enzymatic activity and substrate specificity, whereas the N terminus localizes it in the nucleus. Loss-of-function mutants of SDG714 (SDG714IR transformants) generated by RNA interference display a mostly glabrous phenotype as a result of the lack of macro trichomes in glumes, leaves, and culms compared with control plants. These mutants also show decreased levels of CpG and CNG cytosine methylation as well as H3K9 methylation at the Tos17 locus, a copia-like retrotransposon widely used for the generation of rice mutants. Most interestingly, loss of function of SDG714 can enhance transcription and cause the transposition of Tos17. Together, these results suggest that histone H3K9 methylation mediated by SDG714 is involved in DNA methylation, the transposition of transposable elements, and genome stability in rice.
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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) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".