Developmental and evolutionary comparative analysis of a regulatory landscape in mouse and chicken
Bibliographic record
Abstract
Modifications in gene regulation are driving forces in the evolution of organisms. Part of these changes involve cis-regulatory elements (CREs), which contact their target genes through higher-order chromatin structures. However, how such architectures and variations in CREs contribute to transcriptional evolvability remains elusive. We use Hoxd genes as a paradigm for the emergence of regulatory innovations, as many relevant enhancers are located in a regulatory landscape highly conserved in amniotes. Here, we analysed their regulation in murine vibrissae and chicken feather primordia, two skin appendages expressing different Hoxd gene subsets, and compared the regulation of these genes in these appendages with that in the elongation of the posterior trunk. In the two former structures, distinct subsets of Hoxd genes are contacted by different lineage-specific enhancers, probably as a result of using an ancestral chromatin topology as an evolutionary playground, whereas the gene regulation that occurs in the mouse and chicken embryonic trunk partially relies on conserved CREs. A high proportion of these non-coding sequences active in the trunk have functionally diverged between species, suggesting that transcriptional robustness is maintained, despite considerable divergence in enhancer sequences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".