Short communication: Genomic prediction based on unbiased estimation of the genomic relationship matrix in pigs
The traditional genomic relationship matrix (GRM) has shown to be a biased estimation of true kinship, which can affect subsequent genetic analyses. In this study, we employed an unbiased kinship (UKin) estimation method within the genomic best linear unbiased prediction framework to evaluate its pr...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Animal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1751731124003392 |
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| author | M.Y. Li L.Y. Shi D.E. MacHugh X.Q. Wang J.J. Tian L.G. Wang Y.J. Deng L.X. Wang F.P. Zhao |
| author_facet | M.Y. Li L.Y. Shi D.E. MacHugh X.Q. Wang J.J. Tian L.G. Wang Y.J. Deng L.X. Wang F.P. Zhao |
| author_sort | M.Y. Li |
| collection | DOAJ |
| description | The traditional genomic relationship matrix (GRM) has shown to be a biased estimation of true kinship, which can affect subsequent genetic analyses. In this study, we employed an unbiased kinship (UKin) estimation method within the genomic best linear unbiased prediction framework to evaluate its prediction performance on both a simulated dataset and a Large White pig dataset. The simulated dataset encompasses six traits, 900 quantitative trait loci, and 36 000 single nucleotide polymorphisms (SNPs). Two scenarios (small effect genes; major genes and small effect genes) and three heritabilities (0.1, 0.3 and 0.5) were considered. The Large White pig dataset includes two traits, 3 290 animals and 35 172 SNPs. The prediction performance of the Ukin method was compared with several other GRM construction methods, including VanRaden1 and 2 methods, Goudet method, and the runs of homozygosity (ROH) method. In the simulated dataset, VanRaden2 method and the UKin+VanRaden1 method achieved relatively higher prediction accuracies, averaging 0.561 and 0.558 for the six traits, respectively. Apart from the ROH method, all methods demonstrated similar levels of unbiasedness, around 1.10. In the Large White pig dataset, the accuracy of two traits hovered around 0.780, and the unbiasedness around 0.99, again with the ROH method as an exception. This study underscores the potential of the unbiased kinship estimation method in animal breeding. |
| format | Article |
| id | doaj-art-1b8272f22ffb424ca075df5e6af4bae5 |
| institution | Kabale University |
| issn | 1751-7311 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Animal |
| spelling | doaj-art-1b8272f22ffb424ca075df5e6af4bae52025-02-12T05:30:52ZengElsevierAnimal1751-73112025-02-01192101402Short communication: Genomic prediction based on unbiased estimation of the genomic relationship matrix in pigsM.Y. Li0L.Y. Shi1D.E. MacHugh2X.Q. Wang3J.J. Tian4L.G. Wang5Y.J. Deng6L.X. Wang7F.P. Zhao8State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, ChinaSchool of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, ChinaAnimal Genomics Laboratory, UCD School of Agriculture and Food Science, University College Dublin, Dublin D04 V1W8, IrelandState Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, ChinaState Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, ChinaState Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, ChinaAnimal Husbandry and Aquatic Affairs Centre of Xiangxi Autonomous Prefecture, Jishou, Hunan 416000, ChinaState Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, ChinaState Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; Corresponding author.The traditional genomic relationship matrix (GRM) has shown to be a biased estimation of true kinship, which can affect subsequent genetic analyses. In this study, we employed an unbiased kinship (UKin) estimation method within the genomic best linear unbiased prediction framework to evaluate its prediction performance on both a simulated dataset and a Large White pig dataset. The simulated dataset encompasses six traits, 900 quantitative trait loci, and 36 000 single nucleotide polymorphisms (SNPs). Two scenarios (small effect genes; major genes and small effect genes) and three heritabilities (0.1, 0.3 and 0.5) were considered. The Large White pig dataset includes two traits, 3 290 animals and 35 172 SNPs. The prediction performance of the Ukin method was compared with several other GRM construction methods, including VanRaden1 and 2 methods, Goudet method, and the runs of homozygosity (ROH) method. In the simulated dataset, VanRaden2 method and the UKin+VanRaden1 method achieved relatively higher prediction accuracies, averaging 0.561 and 0.558 for the six traits, respectively. Apart from the ROH method, all methods demonstrated similar levels of unbiasedness, around 1.10. In the Large White pig dataset, the accuracy of two traits hovered around 0.780, and the unbiasedness around 0.99, again with the ROH method as an exception. This study underscores the potential of the unbiased kinship estimation method in animal breeding.http://www.sciencedirect.com/science/article/pii/S1751731124003392Genomic best linear unbiased predictionGenomic selectionKinship matrixLarge White pigsSimulation study |
| spellingShingle | M.Y. Li L.Y. Shi D.E. MacHugh X.Q. Wang J.J. Tian L.G. Wang Y.J. Deng L.X. Wang F.P. Zhao Short communication: Genomic prediction based on unbiased estimation of the genomic relationship matrix in pigs Animal Genomic best linear unbiased prediction Genomic selection Kinship matrix Large White pigs Simulation study |
| title | Short communication: Genomic prediction based on unbiased estimation of the genomic relationship matrix in pigs |
| title_full | Short communication: Genomic prediction based on unbiased estimation of the genomic relationship matrix in pigs |
| title_fullStr | Short communication: Genomic prediction based on unbiased estimation of the genomic relationship matrix in pigs |
| title_full_unstemmed | Short communication: Genomic prediction based on unbiased estimation of the genomic relationship matrix in pigs |
| title_short | Short communication: Genomic prediction based on unbiased estimation of the genomic relationship matrix in pigs |
| title_sort | short communication genomic prediction based on unbiased estimation of the genomic relationship matrix in pigs |
| topic | Genomic best linear unbiased prediction Genomic selection Kinship matrix Large White pigs Simulation study |
| url | http://www.sciencedirect.com/science/article/pii/S1751731124003392 |
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