Three-step transcriptional priming that drives the commitment of multipotent progenitors toward B cells
Bibliographic record
Abstract
Stem cell fate is orchestrated by core transcription factors (TFs) and epigenetic modifications. Although regulatory genes that control cell type specification are identified, the transcriptional circuit and the cross-talk among regulatory factors during cell fate decisions remain poorly understood. To identify the “time-lapse” TF networks during B-lineage commitment, we used multipotent progenitors harboring a tamoxifen-inducible form of Id3, an in vitro system in which virtually all cells became B cells within 6 d by simply withdrawing 4-hydroxytamoxifen (4-OHT). Transcriptome and epigenome analysis at multiple time points revealed that ∼10%–30% of differentially expressed genes were virtually controlled by the core TFs, including E2A, EBF1, and PAX5. Strikingly, we found unexpected transcriptional priming before the onset of the key TF program. Inhibition of the immediate early genes such as Nr4a2, Klf4, and Egr1 severely impaired the generation of B cells. Integration of multiple data sets, including transcriptome, protein interactome, and epigenome profiles, identified three representative transcriptional circuits. Single-cell RNA sequencing (RNA-seq) analysis of lymphoid progenitors in bone marrow strongly supported the three-step TF network model during specification of multipotent progenitors toward B-cell lineage in vivo. Thus, our findings will provide a blueprint for studying the normal and neoplastic development of B lymphocytes.
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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) | 0.001 | 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".