Identification of positive selection signatures in pigs by comparing linkage disequilibrium variances
Bibliographic record
Abstract
Selection affects the patterns of linkage disequilibrium (LD) around the site of a beneficial allele with an increase in LD among the hitchhiking alleles. Comparing the differences in regional LD between pig populations could help to identify putative genomic regions with potential adaptations for economic traits. In this study, using Illumina Porcine SNP60K BeadChip genotyping data from 207 Chinese indigenous, 117 South American village and 408 Large White pigs, we estimated the variation of genome-wide LD between populations using the varld program. The top 0.1% standardized VarLD scores were used as a criterion for all comparisons, and compared with LD blocks, a total of four selection signatures on Sus scrofa chromosome (SSC) 7, 9, 13 and 14 were identified in all populations. These signatures overlapped with quantitative trait loci for linoleic acid content, age at puberty, number of muscle fibers per unit area, hip structure and body weight traits in pigs. Among them, one of the signatures (56.5-56.6 Mb on SSC7) in Large White pigs harbored the ADAMTSL3 gene, which is known to affect body length. The findings of this study seem to point toward recent selection in different pig populations. Further investigations are encouraged to confirm the selection signatures detected by varld in the present study.
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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".