Chromatin loops are an ancestral hallmark of the animal regulatory genome
Bibliographic record
Abstract
Abstract In bilaterian animals, gene regulation is shaped by a combination of linear and spatial regulatory information. Regulatory elements along the genome are integrated into gene regulatory landscapes through chromatin compartmentalization 1,2 , insulation of neighbouring genomic regions 3,4 and chromatin looping that brings together distal cis -regulatory sequences 5 . However, the evolution of these regulatory features is unknown because the three-dimensional genome architecture of most animal lineages remains unexplored 6,7 . To trace the evolutionary origins of animal genome regulation, here we characterized the physical organization of the genome in non-bilaterian animals (sponges, ctenophores, placozoans and cnidarians) 8,9 and their closest unicellular relatives (ichthyosporeans, filastereans and choanoflagellates) 10 by combining high-resolution chromosome conformation capture 11,12 with epigenomic marks and gene expression data. Our comparative analysis showed that chromatin looping is a conserved feature of genome architecture in ctenophores, placozoans and cnidarians. These sequence-determined distal contacts involve both promoter–enhancer and promoter–promoter interactions. By contrast, chromatin loops are absent in the unicellular relatives of animals. Our findings indicate that spatial genome regulation emerged early in animal evolution. This evolutionary innovation introduced regulatory complexity, ultimately facilitating the diversification of animal developmental programmes and cell type repertoires.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".