Cis-regulatory architecture and functions of a gene desert controlling pleiotropic expression and cardiac pacemaker development
Bibliographic record
Abstract
Abstract Gene deserts are extensive genomic regions spanning more than 500 kilobases and enriched near developmental genes. Despite their proposed critical roles in development, the enhancer architecture, and biological functions of most gene deserts in mammalian genomes remain unknown. The Shox2 transcription factor is a key regulator of cardiac pacemaker differentiation and at the genomic level is flanked by a centromeric gene desert harboring a multitude of predicted cis-regulatory modules (CRMs). Using CRISPR-Cas9 we demonstrate a requirement of this gene desert for pleiotropic expression and embryonic survival through full control of Shox2 in the sinoatrial node (SAN). To decode the underlying chromatin architecture and CRM logic, we performed region-specific chromatin conformation capture, epigenomic analysis and transgenic in vivo reporter assays. While the Shox2 regulatory landscape was found partitioned into largely tissue-invariant chromatin loops, we identified a surprising cardiac-specific contact domain within the gene desert. Subsequent transgenic analysis revealed clustering of non-cardiac enhancers with activities in limb, craniofacial or neuronal populations in this domain, pointing to a potential tissue-specific 3D-mechanism for enhancer attenuation. In addition, SAN-chromatin assessment and H3K27ac profiling from human fetal cardiac compartments enabled the identification of a unique cardiac enhancer located outside of the contact domain and essential for robust Shox2 levels during cardiac pacemaker development. In summary, our results serve as a blueprint to investigate gene desert function in context to cardiac defects and identify the Shox2 gene desert as a robust cis-regulatory hub indispensable for pleiotropic patterning, cardiac pacemaker differentiation and embryonic survival. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Swiss National Science Foundation (SNSF),National Institutes of Health (NIH)
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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".