Genome-wide association studies for growth and feed efficiency traits in American mink
Bibliographic record
Abstract
The objective of this study was to identify potential genetic variants and positional candidate genes associated with growth and feed efficiency traits in American mink. Genome-wide association studies (GWAS) were performed using deregressed estimated breeding values of 1037–1872 individuals (as pseudophenotypes), genotyped with the Affymetrix Mink 70K single nucleotide polymorphism (SNP) array. A total of 42 SNPs located on 11 different chromosomes were significantly (false discovery rate < 0.01) associated with six growth and feed efficiency traits. Furthermore, 153 genes were identified within 1-Mb windows flanking these significant SNPs. Several positional candidate genes such as TUBB, CDKN1A, SRSF3, GPRC6A, RFX6, and KPNA5 were previously associated with feed efficiency and growth traits in other livestock species. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that these genes were involved in lipid metabolism, hormone signaling and regulation, and muscle development. To our knowledge, this is the first GWAS to identify genetic variants and biological mechanisms associated with growth and feed efficiency traits in American mink. These findings provide a biological foundation for improving these traits using genomic selection programs to select more efficient mink.
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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 | 0.001 | 0.001 |
| 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".