Transcription‐linked kinases that regulate histone lysine methylation states
Bibliographic record
Abstract
Histone lysine methylation is linked to transcriptional regulation and the control of epigenetic inheritance. Importantly, lysine residues can be mono‐, di‐, or trimethylated and it is thought that each methylation state may impart a unique biological function as suggested by the histone code hypothesis. Yet whether distinct lysine methylation states are under selective control is not known. To address this issue, we have used the methylation of histone H3 at K4 in budding yeast as a model to screen for factors that selectively regulate K4 methylation. In one screen, we uncovered the Bur1/2 cyclin‐dependent protein kinase as a specific regulator of K4 trimethylation. These studies also revealed that Bur1 regulates H2B monoubiquitylation, which was in good agreement with synthetic genetic array and transcription microarray analyses that revealed the Bur1 kinase to be functionally similar to the PAF, Rad6 and Set1 complexes. In a separate screen, we uncovered the RNA polymerase II CTD kinase Ctk1 as a specific regulator of K4 monomethylation. Surprisingly, we find K4 monomethylation occurs preferentially over the transcribed regions of genes and that the loss of K4 monomethylation in CTK1 deletion cells correlates with the spreading of K4 trimethylation from the 5′ end of genes to the 3′ end. These results uncover new roles for several transcription‐linked kinases and suggest that the different K4 methylation states play important, but distinct, roles in transcriptional regulation.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".