Reviewer #1 (Public Review): Arabidopsis SDG proteins mediate Polycomb removal and transcription-coupled H3K36 methylation for gene activation
Bibliographic record
Abstract
Polycomb Repressive Complex 2 (PRC2) recognizes Polycomb response elements (PREs) and catalyzes trimethylation of histone H3 on lysine 27 (H3K27me3) for gene silencing. This silencing is counteracted by H3K36 methylation for epigenetic activation of gene expression. Here, we show that the Arabidopsis thaliana H3K36 methyltransferases SET DOMAIN-CONTAINING PROTEIN 7 (SDG7) and SDG8 antagonize PRC2-mediated silencing and establish H3K36 methylation patterns with the general transcription machinery. The sdg7 sdg8 double mutant shows developmental defects and lower H3K36me2 and H3K36me3 levels. SDG7 preferentially binds near PREs, but SDG8 is recruited to H3K36 methylation peaks. The sdg7 sdg8 phenotypes are partially rescued by loss of Polycomb function. SDG7 overlaps with PRC2 and its recruiters on chromatin and evicts them from shared target genes when conditionally induced. SDG8 and RNA Polymerase II associate at SDG- and RNA POLYMERASE II ASSOCIATED FACTOR 1 complex-regulated targets for H3K36 methylation and transcription. These results suggest that SDG proteins evict PRC2 from PREs to prevent H3K27me3 deposition and activate target genes via transcription-coupled H3K36 methylation.
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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 | 0.015 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.012 | 0.005 |
| Insufficient payload (model declined to judge) | 0.136 | 0.087 |
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".