PU.1 Positively Regulates GATA-1 Expression in Mast Cells
Bibliographic record
Abstract
Coexpression of PU.1 and GATA-1 is required for proper specification of the mast cell lineage; however, in the myeloid and erythroid lineages, PU.1 and GATA-1 are functionally antagonistic. In this study, we report a transcriptional network in which PU.1 positively regulates GATA-1 expression in mast cell development. We isolated a variant mRNA isoform of GATA-1 in murine mast cells that is significantly upregulated during mast cell differentiation. This isoform contains an alternatively spliced first exon (IB) that is distinct from the first exon (IE) incorporated in the major erythroid mRNA transcript. In contrast to erythroid and megakaryocyte cells, in mast cells we show that PU.1 and GATA-2 predominantly occupy potential cis-regulatory elements in the IB exon region in vivo. Using reporter assays, we identify an enhancer flanking the IB exon that is activated by PU.1. Furthermore, we observe that in PU.1(-/-) fetal liver cells, low levels of the IE GATA-1 isoform is expressed, but the variant IB isoform is absent. Reintroduction of PU.1 restores variant IB isoform and upregulates total GATA-1 protein expression, which is concurrent with mast cell differentiation. Our results are consistent with a transcriptional hierarchy in which PU.1, possibly in concert with GATA-2, activates GATA-1 expression in mast cells in a pathway distinct from that seen in the erythroid and megakaryocytic lineages.
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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 | 0.001 |
| 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".