SOX9 acts as a dynamic pioneer factor inducing stable changes in the chromatin landscape to reprogram endothelial cells
Bibliographic record
Abstract
Abstract The transcription factor SOX9 is expressed in multiple tissues during embryogenesis and directs developmental processes. SOX9 is activated upon endothelial-to-mesenchymal transition (EndMT) in the developing heart, but its role in regulating this process is less clear. Using human umbilical vein endothelial cells as an EndMT model, we show that SOX9 expression alone is sufficient to activate mesenchymal enhancers and steer endothelial cells towards a mesenchymal fate. By genome-wide mapping of the chromatin landscape, we show that SOX9 acts as a pioneer transcription factor, having the ability to open chromatin and lead to deposition of active histone marks at a specific subset of previously silent enhancers, guided by SOX motifs and H2A.Z enrichment. This leads to a switch in enhancer activity states resulting in activation of mesenchymal genes and concurrent suppression of endothelial genes to drive EndMT. Moreover, we show that SOX9 chromatin binding is dynamic, but induces stable changes in the chromatin landscape. Our data also show widespread SOX9 chromatin scanning in silent chromatin that is not associated with SOX motifs or H2A.Z enrichment. Our study highlights the crucial developmental role of SOX9 and provides new insight into key molecular functions of SOX9 in the chromatin landscape and mechanisms of EndMT. Graphical abstract
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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 | 0.001 | 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) | 0.041 | 0.005 |
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".