Identification of consensus homozygous regions and their associations with growth and feed efficiency traits in American mink
Bibliographic record
Abstract
The recent chromosome-based genome assembly and the newly developed 70K single nucleotide polymorphism (SNP) array for American mink (Neogale vison) facilitate the identification of genetic variants underlying complex traits in this species. The objective of this study was to evaluate the association between consensus runs of homozygosity (ROH) with growth and feed efficiency traits in American mink. A subsample of two mink populations (n = 2,986) were genotyped using the Affymetrix Mink 70K SNP array. The identified ROH segments were included simultaneously, concatenated into consensus regions, and the ROH-based association studies were carried out with linear mixed models considering a genomic relationship matrix for 11 growth and feed efficiency traits implemented in ASReml-R version 4. In total, 298,313 ROH were identified across all individuals, with an average length and coverage of 4.16 Mb and 414.8 Mb, respectively. After merging ROH segments, 196 consensus ROH regions were detected and used for genome-wide ROH-based association analysis. Thirteen consensus ROH regions were significantly (P < 0.01) associated with growth and feed efficiency traits. Several candidate genes within the significant regions are known for their involvement in growth and body size development, including MEF2A, ADAMTS17, POU3F2, and TYRO3. In addition, we found ten consensus ROH regions, defined as ROH islands, with frequencies over 80% of the population. These islands harbored 12 annotated genes, some of which were related to immune system processes such as DTX3L, PARP9, PARP14, CD86, and HCLS1. This is the first study to explore the associations between homozygous regions with growth and feed efficiency traits in American mink. Our findings shed the light on the effects of homozygosity in the mink genome on growth and feed efficiency traits, that can be utilized in developing a sustainable breeding program for 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) | 0.001 | 0.001 |
| 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) | 0.002 | 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".