Comparative population genomics unveils candidate genes for athletic performance in Hanoverians
Bibliographic record
Abstract
Equine athletes have a genetic heritage that has been evolved for millions of years, which provides an opportunity to study the genetics of locomotion pattern and performance in mammals. The Hanoverian, a breed originating in Germany, is arguably among the most athletic of horse breeds, as well as possessing a balanced character and beautiful appearance. Here, we compared the whole genomes of Hanoverian with three other horse breeds (Akhal-Teke, Franches-Montagnes, and Standardbred), using the fixation index (Fst) and cross-population composite likelihood ratio (XP-CLR) methods for testing the multi-locus allele frequency differentiation between populations. We identified 299 and 485 positively selected genes using the Fst and XP-CLR methods, respectively. Further functional analyses showed that the ACTA1 gene is potentially involved in athletic performance in the Hanoverian breed, consistent with its role observed in human population. In addition, three other loci on chromosomes 1 and 20 were identified to be potentially involved in equine physical performance. The selected candidate genes identified in this study may be useful in current breeding efforts to develop improved breeds in regard to athletic performance.
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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 | 0.001 | 0.001 |
| 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".