The three-dimensional architecture of Hox cluster silencing
Bibliographic record
Abstract
Spatial chromatin organization is emerging as an important mechanism to regulate the expression of genes. However, very little is known about genome architecture at high-resolution in vivo. Here, we mapped the three-dimensional organization of the human Hox clusters with chromosome conformation capture (3C) technology. We show that computational modeling of 3C data sets can identify candidate regulatory proteins of chromatin architecture and gene expression. Hox genes encode evolutionarily conserved master regulators of development which strict control has fascinated biologists for over 25 years. Proper transcriptional silencing is key to Hox function since premature expression can lead to developmental defects or human disease. We now show that the HoxA cluster is organized into multiple chromatin loops that are dependent on transcription activity. Long-range contacts were found in all four silent clusters but looping patterns were specific to each cluster. In contrast to the Drosophila homeotic bithorax complex (BX-C), we found that Polycomb proteins are only modestly required for human cluster looping and silencing. However, computational three-dimensional Hox cluster modeling identified the insulator-binding protein CTCF as a likely candidate mediating DNA loops in all clusters. Our data suggest that Hox cluster looping may represent an evolutionarily conserved structural mechanism of transcription regulation.
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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 | 0.001 | 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".