The transcriptional program controlled by the stem cell leukemia gene Scl/Tal1 during early embryonic hematopoietic development
Bibliographic record
Abstract
The basic helix-loop-helix transcription factor Scl/Tal1 controls the development and subsequent differentiation of hematopoietic stem cells (HSCs). However, because few Scl target genes have been validated to date, the underlying mechanisms have remained largely unknown. In this study, we have used ChIP-Seq technology (coupling chromatin immunoprecipitation with deep sequencing) to generate a genome-wide catalog of Scl-binding events in a stem/progenitor cell line, followed by validation using primary fetal liver cells and comprehensive transgenic mouse assays. Transgenic analysis provided in vivo validation of multiple new direct Scl target genes and allowed us to reconstruct an in vivo validated network consisting of 17 factors and their respective regulatory elements. By coupling ChIP-Seq in model cell lines with in vivo transgenic validation and sophisticated bioinformatic analysis, we have identified a widely applicable strategy for the reconstruction of stem cell regulatory networks in which biologic material is otherwise limiting. Moreover, in addition to revealing multiple previously unrecognized links to known HSC regulators, as well as novel links to genes not previously implicated in HSC function, comprehensive transgenic analysis of regulatory elements provided substantial new insights into the transcriptional control of several important hematopoietic regulators, including Cbfa2t3h/Eto2, Cebpe, Nfe2, Zfpm1/Fog1, Erg, Mafk, Gfi1b, and Myb.
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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".