Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goats
ABSTRACT: Genomic evaluations are routine in most plant and livestock breeding programs but are used infrequently in dairy goat breeding schemes. In this context, the purpose of this study was to investigate the use of the single-step genomic BLUP method for predicting genomic breeding values for mi...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-03-01
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| Series: | Journal of Dairy Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0022030221011127 |
| _version_ | 1818114112887980032 |
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| author | Erin Massender Luiz F. Brito Laurence Maignel Hinayah R. Oliveira Mohsen Jafarikia Christine F. Baes Brian Sullivan Flavio S. Schenkel |
| author_facet | Erin Massender Luiz F. Brito Laurence Maignel Hinayah R. Oliveira Mohsen Jafarikia Christine F. Baes Brian Sullivan Flavio S. Schenkel |
| author_sort | Erin Massender |
| collection | DOAJ |
| description | ABSTRACT: Genomic evaluations are routine in most plant and livestock breeding programs but are used infrequently in dairy goat breeding schemes. In this context, the purpose of this study was to investigate the use of the single-step genomic BLUP method for predicting genomic breeding values for milk production traits (milk, protein, and fat yields; protein and fat percentages) in Canadian Alpine and Saanen dairy goats. There were 6,409 and 12,236 Alpine records and 3,434 and 5,008 Saanen records for each trait in first and later lactations, respectively, and a total of 1,707 genotyped animals (833 Alpine and 874 Saanen). Two validation approaches were used, forward validation (i.e., animals born after 2013 with an average estimated breeding value accuracy from the full data set ≥0.50) and forward cross-validation (i.e., subsets of all animals included in the forward validation were used in successive replications). The forward cross-validation approach resulted in similar validation accuracies (0.55 to 0.66 versus 0.54 to 0.61) and biases (−0.01 to –0.07 versus −0.03 to 0.11) to the forward validation when averaged across traits. Additionally, both single and multiple-breed analyses were compared, and similar average accuracies and biases were observed across traits. However, there was a small gain in accuracy from the use of multiple-breed models for the Saanen breed. A small gain in validation accuracy for genomically enhanced estimated breeding values (GEBV) relative to pedigree-based estimated breeding values (EBV) was observed across traits for the Alpine breed, but not for the Saanen breed, possibly due to limitations in the validation design, heritability of the traits evaluated, and size of the training populations. Trait-specific gains in theoretical accuracy of GEBV relative to EBV for the validation animals ranged from 17 to 31% in Alpine and 35 to 55% in Saanen, using the cross-validation approach. The GEBV predicted from the full data set were 12 to 16% more accurate than EBV for genotyped animals, but no gains were observed for nongenotyped animals. The largest gains were found for does without lactation records (35–41%) and bucks without daughter records (46–54%), and consequently, the implementation of genomic selection in the Canadian dairy goat population would be expected to increase selection accuracy for young breeding candidates. Overall, this study represents the first step toward implementation of genomic selection in Canadian dairy goat populations. |
| first_indexed | 2024-12-11T03:45:33Z |
| format | Article |
| id | doaj.art-8c64d884c12d47e596211934fea0ad47 |
| institution | Directory Open Access Journal |
| issn | 0022-0302 |
| language | English |
| last_indexed | 2024-12-11T03:45:33Z |
| publishDate | 2022-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Dairy Science |
| spelling | doaj.art-8c64d884c12d47e596211934fea0ad472022-12-22T01:22:03ZengElsevierJournal of Dairy Science0022-03022022-03-01105323932407Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goatsErin Massender0Luiz F. Brito1Laurence Maignel2Hinayah R. Oliveira3Mohsen Jafarikia4Christine F. Baes5Brian Sullivan6Flavio S. Schenkel7Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada, N1G 2W1; Corresponding authorCentre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada, N1G 2W1; Department of Animal Sciences, Purdue University, West Lafayette, IN 47907Canadian Centre for Swine Improvement Inc., Ottawa, ON, Canada, K1A 0C6Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada, N1G 2W1; Department of Animal Sciences, Purdue University, West Lafayette, IN 47907Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada, N1G 2W1; Canadian Centre for Swine Improvement Inc., Ottawa, ON, Canada, K1A 0C6Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada, N1G 2W1; Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001 Bern, SwitzerlandCanadian Centre for Swine Improvement Inc., Ottawa, ON, Canada, K1A 0C6Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada, N1G 2W1ABSTRACT: Genomic evaluations are routine in most plant and livestock breeding programs but are used infrequently in dairy goat breeding schemes. In this context, the purpose of this study was to investigate the use of the single-step genomic BLUP method for predicting genomic breeding values for milk production traits (milk, protein, and fat yields; protein and fat percentages) in Canadian Alpine and Saanen dairy goats. There were 6,409 and 12,236 Alpine records and 3,434 and 5,008 Saanen records for each trait in first and later lactations, respectively, and a total of 1,707 genotyped animals (833 Alpine and 874 Saanen). Two validation approaches were used, forward validation (i.e., animals born after 2013 with an average estimated breeding value accuracy from the full data set ≥0.50) and forward cross-validation (i.e., subsets of all animals included in the forward validation were used in successive replications). The forward cross-validation approach resulted in similar validation accuracies (0.55 to 0.66 versus 0.54 to 0.61) and biases (−0.01 to –0.07 versus −0.03 to 0.11) to the forward validation when averaged across traits. Additionally, both single and multiple-breed analyses were compared, and similar average accuracies and biases were observed across traits. However, there was a small gain in accuracy from the use of multiple-breed models for the Saanen breed. A small gain in validation accuracy for genomically enhanced estimated breeding values (GEBV) relative to pedigree-based estimated breeding values (EBV) was observed across traits for the Alpine breed, but not for the Saanen breed, possibly due to limitations in the validation design, heritability of the traits evaluated, and size of the training populations. Trait-specific gains in theoretical accuracy of GEBV relative to EBV for the validation animals ranged from 17 to 31% in Alpine and 35 to 55% in Saanen, using the cross-validation approach. The GEBV predicted from the full data set were 12 to 16% more accurate than EBV for genotyped animals, but no gains were observed for nongenotyped animals. The largest gains were found for does without lactation records (35–41%) and bucks without daughter records (46–54%), and consequently, the implementation of genomic selection in the Canadian dairy goat population would be expected to increase selection accuracy for young breeding candidates. Overall, this study represents the first step toward implementation of genomic selection in Canadian dairy goat populations.http://www.sciencedirect.com/science/article/pii/S0022030221011127dairy goatgenomic selectionmilk production traitsingle-step genomic predictionsingle-step genomic best linear unbiased prediction |
| spellingShingle | Erin Massender Luiz F. Brito Laurence Maignel Hinayah R. Oliveira Mohsen Jafarikia Christine F. Baes Brian Sullivan Flavio S. Schenkel Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goats Journal of Dairy Science dairy goat genomic selection milk production trait single-step genomic prediction single-step genomic best linear unbiased prediction |
| title | Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goats |
| title_full | Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goats |
| title_fullStr | Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goats |
| title_full_unstemmed | Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goats |
| title_short | Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goats |
| title_sort | single step genomic evaluation of milk production traits in canadian alpine and saanen dairy goats |
| topic | dairy goat genomic selection milk production trait single-step genomic prediction single-step genomic best linear unbiased prediction |
| url | http://www.sciencedirect.com/science/article/pii/S0022030221011127 |
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