SOX9 reprograms endothelial cells by altering the chromatin landscape
Bibliographic record
Abstract
The transcription factor SOX9 is activated at the onset of endothelial-to-mesenchymal transition (EndMT) during embryonic development and in pathological conditions. Its roles in regulating these processes, however, are not clear. Using human umbilical vein endothelial cells (HUVECs) as an EndMT model, we show that SOX9 expression alone is sufficient to activate mesenchymal genes and steer endothelial cells towards a mesenchymal fate. By genome-wide mapping of the chromatin landscape, we show that SOX9 displays features of a pioneer transcription factor, such as opening of chromatin and leading to deposition of active histone modifications at silent chromatin regions, guided by SOX dimer motifs and H2A.Z enrichment. We further observe highly transient and dynamic SOX9 binding, possibly promoted through its eviction by histone phosphorylation. However, while SOX9 binding is dynamic, changes in the chromatin landscape and cell fate induced by SOX9 are persistent. Finally, our analysis of single-cell chromatin accessibility indicates that SOX9 opens chromatin to drive EndMT in atherosclerotic lesions in vivo. This study provides new insight into key molecular functions of SOX9 and mechanisms of EndMT and highlights the crucial developmental role of SOX9 and relevance to human disease.
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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".