Single-cell chromatin accessibility profiling reveals regulatory mechanisms and evolution in pig brains
Bibliographic record
Abstract
BACKGROUND: Pig brains serve as a valuable biomedical model for studying brain-related diseases due to their significant structural similarities to the human brain. Furthermore, the long-term domestication and artificial selection of domestic pigs have profoundly shaped their brains, making them an interesting subject for research. However, a comprehensive understanding of the regulatory mechanisms governing pig brain function and their impact on various phenotypes remains elusive due to the high degree of cellular heterogeneity present in the brain. RESULTS: In this study, we profiled 71,798 cells from domestic pig and wild boar cerebral cortex and cerebellum, identifying nine cell types, and integrated single-cell RNA sequencing data to explore cell type-specific regulatory landscapes and oligodendrocyte developmental trajectory. Furthermore, comparative analysis of each cell type between domestic pigs and wild boars indicated that oligodendrocyte progenitor cells may potentially exhibit a faster evolutionary rate. Finally, cross-species analysis suggested that, compared to humans, the proportion of sequence-conserved and functionally conserved regulatory elements in each cell type appears to be higher in pigs than in mice. Studies on the enrichment of genetic variants associated with 15 human diseases and complex traits in conserved regulatory elements across cell types indicated that immune-related diseases were more enriched in pigs, whereas neurological diseases were somewhat more enriched in mice. However, the enrichment of Alzheimer's disease-associated variants in pigs but not in mice suggests that pigs could be a more suitable model for this condition. CONCLUSIONS: Our research offers preliminary insights into the heterogeneity of pig brains and suggests the potential underlying regulatory mechanisms. Additionally, we explore the possible impact of nervous system differences on phenotypic changes, which could lay the groundwork for further biomedical studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".