PSVII-8 Genome-Wide Association Studies for Feed Efficiency and Growth Traits in American Mink
Bibliographic record
Abstract
Abstract Feed efficiency (FE) traits contribute to the economic output of mink production systems as feed costs comprise the largest proportion of their variable expenses. However, the genetic architecture underlying FE-related traits is largely unknown in American mink. The objective of this study was to identify potential genetic variants and candidate genes associated with feed efficiency and growth traits, including body weight (BW), average daily gain (ADG), daily feed intake (DFI), feed conversion ratio (FCR), residual feed intake (RFI), residual gain (RG), residual intake and gain (RIG), and Kleiber ratio (KR). Genome-wide association studies (GWAS) were performed using deregressed estimated breeding values (DEBVs) of 1,255 to 2,160 individuals (as pseudophenotypes), genotyped with the Affymetrix Mink 70K single nucleotide polymorphisms (SNP) array. Association analyses were performed using the mixed linear model in GCTA software. A total of 36 SNPs located on 11 different chromosomes were significantly (FDR < 0.01) associated with eight feed efficiency and growth traits, among which nine SNPs had pleiotropic effects on at least two analyzed traits. The phenotypic variance (of DEBVs) explained by all significant SNPs for BW, ADG, DFI, FCR, RFI, RG, RIG, and KR, were 0.54%, 2.35%, 0.51%, 2.45%, 0.03%, 3.67%, 0.21%, and 2.60%, respectively. Furthermore, 191 genes were identified within 1-Mb windows around these significant SNPs. These regions included candidate genes such as FABP6, ADAMTS18, ADGRB3, GRM8, DSCAM, COL9A1, and CSRP2, previously associated with feed efficiency and growth traits in other livestock species. Gene ontology analyses revealed that these genes were involved in molecular functions such as ATPase activity and ATP binding, which provide the direct energy source for the body. To our knowledge, this is the first GWAS to identify genetic variants and biological mechanisms associated with FE and growth 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 | 0.000 | 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) | 0.003 | 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".