H3.3 De Novo Mutations Alter Lysine 36 Methylation via Distinct Mechanisms
Bibliographic record
Abstract
Abstract Bryant-Li-Bhoj syndrome (BLBS) is caused by de novo mutations on histone H3.3 and is generally characterized by severe neurodevelopmental deficits. Oncogenic H3.3 amino acid substitutions were described over the past decade, but the molecular impact of BLBS mutations remained unstudied. The remarkable number and spread of the missense mutations led us to hypothesize that some converge on the same downstream effectors. We recently showed that H3.3G34R/V substitutions, seen in both cancer and BLBS, impair associations with the DNMT3A DNA methyltransferase. Our proteomic, enzymatic, and structural analyses now show that H3.3 BLBS mutations flanking glycine 34 have surprisingly stark effects on H3K36 methyltransferases, drastically altering H3K36 methyl states in cis and the binding of effector proteins with a PWWP domain, including DNMT3A/B. That confirms the existence of molecular commonalities amongst BLBS H3.3 point mutants while providing some of the first mechanistic insights into the syndrome.
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) | 0.000 | 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) | 0.002 | 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".