Hox in motion: tracking HoxA cluster conformation during differentiation
Bibliographic record
Abstract
Three-dimensional genome organization is an important higher order transcription regulation mechanism that can be studied with the chromosome conformation capture techniques. Here, we combined chromatin organization analysis by chromosome conformation capture-carbon copy, computational modeling and epigenomics to achieve the first integrated view, through time, of a connection between chromatin state and its architecture. We used this approach to examine the chromatin dynamics of the HoxA cluster in a human myeloid leukemia cell line at various stages of differentiation. We found that cellular differentiation involves a transient activation of the 5'-end HoxA genes coinciding with a loss of contacts throughout the cluster, and by specific silencing at the 3'-end with H3K27 methylation. The 3D modeling of the data revealed an extensive reorganization of the cluster between the two previously reported topologically associated domains in differentiated cells. Our results support a model whereby silencing by polycomb group proteins and reconfiguration of CTCF interactions at a topologically associated domain boundary participate in changing the HoxA cluster topology, which compartmentalizes the genes following differentiation.
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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".