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Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes
The objective of this study was to compare the accuracies of genomic prediction for milk yield, fat yield, and protein yield from Philippine dairy buffaloes using genomic best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP) with the accuracies based on pedigree BLUP (pBLUP). To al...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8581257/ https://www.ncbi.nlm.nih.gov/pubmed/34777455 http://dx.doi.org/10.3389/fgene.2021.682576 |
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author | Herrera, Jesus Rommel V. Flores, Ester B. Duijvesteijn, Naomi Moghaddar, Nasir van der Werf, Julius H. |
author_facet | Herrera, Jesus Rommel V. Flores, Ester B. Duijvesteijn, Naomi Moghaddar, Nasir van der Werf, Julius H. |
author_sort | Herrera, Jesus Rommel V. |
collection | PubMed |
description | The objective of this study was to compare the accuracies of genomic prediction for milk yield, fat yield, and protein yield from Philippine dairy buffaloes using genomic best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP) with the accuracies based on pedigree BLUP (pBLUP). To also assess the bias of the prediction, the regression coefficient (slope) of the adjusted phenotypes on the predicted breeding values (BVs) was also calculated. Two data sets were analyzed. The GENO data consisting of all female buffaloes that have both phenotypes and genotypes (n = 904 with 1,773,305-days lactation records) were analyzed using pBLUP and GBLUP. The ALL data, consisting of the GENO data plus females with phenotypes but not genotyped (n = 1,975 with 3,821,305-days lactation records), were analyzed using pBLUP and ssGBLUP. Animals were genotyped with the Affymetrix 90k buffalo genotyping array. After quality control, 60,827 single-nucleotide polymorphisms were used for downward analysis. A pedigree file containing 2,642 animals was used for pBLUP and ssGBLUP. Accuracy of prediction was calculated as the correlation between the predicted BVs of the test set and adjusted phenotypes, which were corrected for fixed effects, divided by the square root of the heritability of the trait, corrected for the number of lactations used in the test set. To assess the bias of the prediction, the regression coefficient (slope) of the adjusted phenotypes on the predicted BVs was also calculated. Results showed that genomic methods (GBLUP and ssGBLUP) provide more accurate predictions compared to pBLUP. Average GBLUP and ssGBLUP accuracies were 0.24 and 0.29, respectively, whereas average pBLUP accuracies (for GENO and ALL data) were 0.21 and 0.22, respectively. Slopes of the two genomic methods were also closer to one, indicating lesser bias, compared to pBLUP. Average GBLUP and ssGBLUP slopes were 0.89 and 0.84, respectively, whereas the average pBLUP (for GENO and ALL data) slopes were 0.80 and 0.54, respectively. |
format | Online Article Text |
id | pubmed-8581257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85812572021-11-12 Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes Herrera, Jesus Rommel V. Flores, Ester B. Duijvesteijn, Naomi Moghaddar, Nasir van der Werf, Julius H. Front Genet Genetics The objective of this study was to compare the accuracies of genomic prediction for milk yield, fat yield, and protein yield from Philippine dairy buffaloes using genomic best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP) with the accuracies based on pedigree BLUP (pBLUP). To also assess the bias of the prediction, the regression coefficient (slope) of the adjusted phenotypes on the predicted breeding values (BVs) was also calculated. Two data sets were analyzed. The GENO data consisting of all female buffaloes that have both phenotypes and genotypes (n = 904 with 1,773,305-days lactation records) were analyzed using pBLUP and GBLUP. The ALL data, consisting of the GENO data plus females with phenotypes but not genotyped (n = 1,975 with 3,821,305-days lactation records), were analyzed using pBLUP and ssGBLUP. Animals were genotyped with the Affymetrix 90k buffalo genotyping array. After quality control, 60,827 single-nucleotide polymorphisms were used for downward analysis. A pedigree file containing 2,642 animals was used for pBLUP and ssGBLUP. Accuracy of prediction was calculated as the correlation between the predicted BVs of the test set and adjusted phenotypes, which were corrected for fixed effects, divided by the square root of the heritability of the trait, corrected for the number of lactations used in the test set. To assess the bias of the prediction, the regression coefficient (slope) of the adjusted phenotypes on the predicted BVs was also calculated. Results showed that genomic methods (GBLUP and ssGBLUP) provide more accurate predictions compared to pBLUP. Average GBLUP and ssGBLUP accuracies were 0.24 and 0.29, respectively, whereas average pBLUP accuracies (for GENO and ALL data) were 0.21 and 0.22, respectively. Slopes of the two genomic methods were also closer to one, indicating lesser bias, compared to pBLUP. Average GBLUP and ssGBLUP slopes were 0.89 and 0.84, respectively, whereas the average pBLUP (for GENO and ALL data) slopes were 0.80 and 0.54, respectively. Frontiers Media S.A. 2021-10-28 /pmc/articles/PMC8581257/ /pubmed/34777455 http://dx.doi.org/10.3389/fgene.2021.682576 Text en Copyright © 2021 Herrera, Flores, Duijvesteijn, Moghaddar and van der Werf. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Herrera, Jesus Rommel V. Flores, Ester B. Duijvesteijn, Naomi Moghaddar, Nasir van der Werf, Julius H. Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes |
title | Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes |
title_full | Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes |
title_fullStr | Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes |
title_full_unstemmed | Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes |
title_short | Accuracy of Genomic Prediction for Milk Production Traits in Philippine Dairy Buffaloes |
title_sort | accuracy of genomic prediction for milk production traits in philippine dairy buffaloes |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8581257/ https://www.ncbi.nlm.nih.gov/pubmed/34777455 http://dx.doi.org/10.3389/fgene.2021.682576 |
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