SDG102, a H3K36-Methyltransferase-Encoding Gene, Plays Pleiotropic Roles in Growth and Development of Maize (Zea mays L.)
Bibliographic record
Abstract
Although histone lysine methylation has been studied in thale cress (Arabidopsis thaliana (L.) Heynh.) and rice (Oryza sativa L.) in recent years, its function in maize (Zea mays L.) remains poorly characterized. To better understand the function of histone lysine methylation in maize, SDG102, a H3 lysine 36 (H3K36) methylase, was chosen for functional characterization using overexpressed and knockout transgenic plants. SDG102-deficiency in maize caused multiple phenotypes including yellow leaves in seedlings, late-flowering, and increased adult plant height, while the overexpression of SDG102 led to reduced adult plant height. The key flowering genes, ZCN8/ZCN7 and MADS4/MADA67, were downregulated in SDG102-deficient plants. Chromatin immunoprecipitation (ChIP) experiments showed that H3 lysine 36 trimethylation (H3K36me3) levels were reduced at these loci. Perturbation of SDG102 expression caused the misexpression of multiple genes. Interestingly, the overexpression or knockout of SDG102 also led to genome-wide decreases and increases in the H3K36me3 levels, respectively. Together, our results suggest that SDG102 is a methyltransferase that catalyzes the trimethylation of H3K36 of many genes across the maize genome, which are involved in multiple biological processes including those controlling flowering time.
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 | 0.000 |
| 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".