The SCL Transcription Factor Supports Erythroid Cell Survival and Differentiation Downstream of the Erythropoietin Receptor.
Bibliographic record
Abstract
Abstract Erythroid cell development critically depends on the SCL/Tal1 transcription factor and on erythropoietin signalling. In the present study, we have taken several approaches to show that the two genes operate within the same pathway to consolidate the erythroid lineage. Signaling through the erythropoietin receptor (EpoR) upregulates SCL protein levels in a clonal cell line (TF-1) in vitro, and in murine fetal liver cells in vivo, when Epor−/− cells were compared to those of wild type littermates at E12.5. In addition, we provide functional evidence for a linear pathway from EpoR to SCL that regulates erythropoiesis. Interfering with SCL induction or SCL function prevents the anti-apoptotic effect of Epo in TF-1 cells and conversely, ectopic SCL expression is sufficient to substitute for Epo to transiently maintain cell survival. In vivo, SCL gain of function complements the cellular defects in Epor−/− embryos to support cell survival and maturation during primitive and definitive erythropoiesis, as assessed by cellular and histological analyses of Epor−/− SCLtg embryos. Moreover, several erythroid specific genes that are decreased in Epor−/− embryos are rescued by the SCL transgene including glycophorinA, bH1 and bmaj globin, providing molecular confirmation of the functional and genetic interaction between Epor and SCL. Conversely, erythropoiesis becomes deficient in compound Epor+/−SCL+/− heterozygote mice, indicating that the genetic interaction between EpoR and SCL is synthetic. Finally, using EpoR mutants that harbour well defined signalling deficiencies, combined with gain and loss of function approaches for specific kinases, we identify MAPK as the major signal transduction pathway downstream of EpoR that upregulates SCL function, necessary for erythroid cell survival and differentiation. Taken together, our observations are consistent with the view that cytokines can influence cell fate by altering the dosage of lineage transcriptional regulators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".