N <sup>6</sup> -methyladenosine mRNA marking promotes selective translation of regulons required for human erythropoiesis
Bibliographic record
Abstract
Abstract Many of the regulatory features governing erythrocyte specification, maturation, and associated disorders remain enigmatic. To identify new regulators of erythropoiesis, we performed a functional genomic screen for genes affecting expression of the erythroid marker CD235a/GYPA. Among validating hits were genes coding for the N 6 -methyladenosine (m 6 A) mRNA methyltransferase (MTase) complex, including, METTL14 , METTL3 , and WTAP . We found that m 6 A MTase activity promotes erythroid gene expression programs and lineage specification through selective translation of >200 m 6 A marked mRNAs, including those coding for SETD methyltransferase, ribosome, and polyA RNA binding proteins. Remarkably, loss of m 6 A marks resulted in dramatic loss of H3K4me3 across key erythroid-specific KLF1 transcriptional targets (e.g., Heme biosynthesis genes). Further, each m 6 A MTase subunit and a subset of their mRNAs targets, including BRD7 , CXXC1 , PABPC1 , PABPC4 , STK40 , and TADA2B , were required for erythroid specification. Thus, m 6 A mRNA marks promote the translation of a network of genes required for human erythropoiesis.
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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) | 0.002 | 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".