43 Single and Multiple-breed Genomic Predictions for Conformation Traits of Canadian Dairy Goats

Abstract The use of multiple-breed models can increase the accuracy of estimated breeding values (EBV) when few phenotypes are available for a trait. However, pooling breeds is not always beneficial for genomic evaluations due to the low consistency of gametic phase between individual breeds. The ob...

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Bibliographic Details
Published in:Journal of animal science 2021-10, Vol.99 (Supplement_3), p.27-28
Main Authors: Massender, Erin, Brito, Luiz F, Maignel, Laurence, Oliveira, Hinayah R, Jafarikia, Mohsen, Baes, Christine F, Sullivan, Brian, Schenkel, Flavio S
Format: Article
Language:English
Subjects:
Accuracy
Animal models
Animals
Breeding
Conformation
Datasets
Genetic improvement
Genomics
Genotypes
Goats
Oral Presentations
Phenotypes
Predictions
Teats
Udder
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Summary:Abstract The use of multiple-breed models can increase the accuracy of estimated breeding values (EBV) when few phenotypes are available for a trait. However, pooling breeds is not always beneficial for genomic evaluations due to the low consistency of gametic phase between individual breeds. The objective of this study was to compare the expected gain in accuracy of single-step genomic breeding values (GEBV) for conformation traits of Canadian Alpine and Saanen goats predicted using single and multiple-breed models. The traits considered were body capacity, dairy character, feet and legs, fore udder, general appearance, rear udder, suspensory ligament, and teats, all recorded by trained classifiers, using a 1 to 9 scale. The full datasets included a total of 7,500 phenotypes for each trait (5,158 Alpine and 2,342 Saanen) and 1,707 50K genotypes (833 Alpine, 874 Saanen). Standard errors of prediction (SEP) were obtained for EBV and GEBV predicted using single-trait animal models on full or validation datasets. Breed difference was accounted for as a fixed effect in the multiple-breed models. Average theoretical accuracies were calculated from the SEP. For Saanen, with fewer records, expected accuracies of EBV and GEBV for the validation animals (selection candidates) were consistently higher for the multiple-breed models. Trait specific gains in theoretical accuracy of GEBV relative to EBV for the selection candidates ranged from 30 to 48% for Alpine and 41 to 61% for Saanen. Averaged across all traits, GEBV predicted from the full dataset were 32 to 38% more accurate than EBV for genotyped animals and the largest gains were found for does without conformation records (49 to 55%) and bucks without daughter records (56 to 82%). Overall, the implementation of genomic selection would substantially increase selection accuracy for young breeding candidates and, consequently, the rate of genetic improvement for conformation traits in Canadian dairy goats.
ISSN:0021-8812
1525-3163
DOI:10.1093/jas/skab235.046