N6-methyladenosine RNA modification regulates embryonic neural stem cell self-renewal through histone modifications
Bibliographic record
Abstract
Internal N6-methyladenosine (m6A) modification is widespread in messenger RNAs (mRNAs) and is catalyzed by heterodimers of methyltransferase-like protein 3 (Mettl3) and Mettl14. To understand the role of m6A in development, we deleted Mettl14 in embryonic neural stem cells (NSCs) in a mouse model. Phenotypically, NSCs lacking Mettl14 displayed markedly decreased proliferation and premature differentiation, suggesting that m6A modification enhances NSC self-renewal. Decreases in the NSC pool led to a decreased number of late-born neurons during cortical neurogenesis. Mechanistically, we discovered a genome-wide increase in specific histone modifications in Mettl14 knockout versus control NSCs. These changes correlated with altered gene expression and observed cellular phenotypes, suggesting functional significance of altered histone modifications in knockout cells. Finally, we found that m6A regulates histone modification in part by destabilizing transcripts that encode histone-modifying enzymes. Our results suggest an essential role for m6A in development and reveal m6A-regulated histone modifications as a previously unknown mechanism of gene regulation in mammalian cells. Using a genetic approach, Wang et al. demonstrate an essential function for m6A mRNA modification in promoting neural stem cell proliferation and reveal interactions between m6A and histone modification as a novel gene regulatory mechanism.
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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 | 0.000 | 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".