Population genomics of American mink using genotype data
Bibliographic record
Abstract
Understanding the genetic structure of the target population is critically important to develop an efficient genomic selection program in domestic animals. In this study, 2,973 American mink of six color types from two farms (Canadian Centre for Fur Animal Research (CCFAR), Truro, NS and Millbank Fur Farm (MFF), Rockwood, ON) were genotyped with the Affymetrix Mink 70K panel to compute their linkage disequilibrium (LD) patterns, effective population size ( Ne ), genetic diversity, genetic distances, and population differentiation and structure. The LD pattern represented by average r 2 , decreased to <0.2 when the inter-marker interval reached larger than 350 kb and 650 kb for CCFAR and MFF, respectively, and suggested at least 7,700 and 4,200 single nucleotide polymorphisms (SNPs) be used to obtain adequate accuracy for genomic selection programs in CCFAR and MFF respectively. The Ne for five generations ago was estimated to be 76 and 91 respectively. Our results from genetic distance and diversity analyses showed that American mink of the various color types had a close genetic relationship and low genetic diversity, with most of the genetic variation occurring within rather than between color types. Three ancestral genetic groups was considered the most appropriate number to delineate the genetic structure of these populations. Black (in both CCFAR and MFF) and pastel color types had their own ancestral clusters, while demi, mahogany, and stardust color types were admixed with the three ancestral genetic groups. This study provided essential information to utilize the first medium-density SNP panel for American mink in their genomic studies.
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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".