0359 Understanding the genetic archticture of Hays Converter Cattle
Bibliographic record
Abstract
The Hays Converter (HC) was the first Canadian breed to be recognized in terms of the Canadian Livestock Pedigree Act and combines the genetics of the Hereford, Holstein and Brown Swiss breeds. Although, the improvement program has continued there is now a risk to its sustainability. The objective of this study is to utilize genomic tools to assess genetic diversity and inbreeding within the HC population. Historical samples for 265, 238, and 208 animals born between 1973 and 2015 have been genotyped for 19K (19,792 SNPs,), 6K (6829 SNPs) and Illumina BovineSNP50 (50K, 49,100 SNPs), respectively. A total of 49,100 SNPs across 29 autosomes that passed all quality control criteria were considered for imputation of the target populations with 19k (7496 SNPs) and with 6k (6253 SNPs) using FImpute. The actual and imputed genotypes were filtered for 702 animals and 41,734 SNPs across 29 autosomes passed quality control. Using only actual 50K genotypes of 208 animals, the genetic structure of the HC population was assessed in conjunction with individuals genotyped for Illumina BovineSNP50 from Angus (AN, n = 486), Hereford (HE, n = 591) and Holstein (HO, n = 32) breeds using principal component analysis (PCA). The genomic inbreeding coefficients for individuals within HC were estimated using pedigree information and 4 genomic methods. The genetic distances between animals within each population were calculated based on their genomic profile using Prevosti Distance. Although, the PCA indicated that the HC breed is genetically divergent from Holstein, Hereford and Angus, it was more closely related to Holstein cattle than the other breeds. Genomic inbreeding coefficients using imputed or actual genotypes indicated that the HC is inbred over years, particularly from 1993 till 2005. Thus, this indicates a smaller effective population size for the HC population at that time. The result from genetic distance and phylogeny of the HC population indicated existence of sub populations within the HC. In conclusion, the study showed an increase of inbreeding within HC breeds so that managing inbreeding and maximizing diversity is required to avoid inbreeding depression. The observed diversity will influence HC design for future mate allocation using genomic information.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".