HyperTRIBE uncovers increased MUSASHI-2 RNA binding activity and differential regulation in leukemic stem cells
Bibliographic record
Abstract
The cell-context dependency for RNA binding proteins (RBPs) mediated control of stem cell fate remains to be defined. Here we adapt the HyperTRIBE method using an RBP fused to a Drosophila RNA editing enzyme (ADAR) to globally map the mRNA targets of the RBP MSI2 in mammalian adult normal and malignant stem cells. We reveal a unique MUSASHI-2 (MSI2) mRNA binding network in hematopoietic stem cells that changes during transition to multipotent progenitors. Additionally, we discover a significant increase in RNA binding activity of MSI2 in leukemic stem cells compared with normal hematopoietic stem and progenitor cells, resulting in selective regulation of MSI2's oncogenic targets. This provides a basis for MSI2 increased dependency in leukemia cells compared to normal cells. Moreover, our study provides a way to measure RBP function in rare cells and suggests that RBPs can achieve differential binding activity during cell state transition independent of gene expression.
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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 | 0.000 |
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".