Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology Abnormalities
Artificial insemination (AI) has been used globally as a routine technology in the swine production industry. However, genetic parameters and genomic prediction accuracy of semen traits have seldom been reported. In this study, we estimated genetic parameters and conducted genomic prediction for fiv...
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MDPI AG
2019-09-01
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| Online Access: | https://www.mdpi.com/2076-2615/9/10/710 |
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| author | Yunxiang Zhao Ning Gao Jian Cheng Saeed El-Ashram Lin Zhu Conglin Zhang Zhili Li |
| author_facet | Yunxiang Zhao Ning Gao Jian Cheng Saeed El-Ashram Lin Zhu Conglin Zhang Zhili Li |
| author_sort | Yunxiang Zhao |
| collection | DOAJ |
| description | Artificial insemination (AI) has been used globally as a routine technology in the swine production industry. However, genetic parameters and genomic prediction accuracy of semen traits have seldom been reported. In this study, we estimated genetic parameters and conducted genomic prediction for five types of sperm morphology abnormalities in a large Duroc boar population. The estimated heritability of the studied traits ranged from 0.029 to 0.295. In the random cross-validation scenario, the predictive ability ranged from 0.212 to 0.417 for genomic best linear unbiased prediction (GBLUP) and from 0.249 to 0.565 for single-step GBLUP (ssGBLUP). In the forward prediction scenario, the predictive ability ranged from 0.069 to 0.389 for GBLUP and from 0.085 to 0.483 for ssGBLUP. In conclusion, the studied sperm morphology abnormalities showed moderate to low heritability. Both GBLUP and ssGBLUP showed comparative predictive abilities of breeding values, and ssGBLUP outperformed GBLUP under many circumstances in respect to predictive ability. To our knowledge, this is the first time that the genetic parameters and genomic predictive ability of these traits were reported in such a large Duroc boar population. |
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| language | English |
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| publishDate | 2019-09-01 |
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| spelling | doaj.art-8bd7a3537dbc45a2b53b425e0edf76d12022-12-21T23:58:22ZengMDPI AGAnimals2076-26152019-09-0191071010.3390/ani9100710ani9100710Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology AbnormalitiesYunxiang Zhao0Ning Gao1Jian Cheng2Saeed El-Ashram3Lin Zhu4Conglin Zhang5Zhili Li6College of Life Science and Engineering, Foshan University, Foshan 528231, ChinaState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510006, ChinaAnimal Science Department, Iowa State University, Ames, IA 50011, USACollege of Life Science and Engineering, Foshan University, Foshan 528231, ChinaDepartment of pig breeding, Guangxi Yangxiang Agriculture and Husbandry Co., LTD, Guigang 537100, ChinaDepartment of pig breeding, Guangxi Yangxiang Agriculture and Husbandry Co., LTD, Guigang 537100, ChinaCollege of Life Science and Engineering, Foshan University, Foshan 528231, ChinaArtificial insemination (AI) has been used globally as a routine technology in the swine production industry. However, genetic parameters and genomic prediction accuracy of semen traits have seldom been reported. In this study, we estimated genetic parameters and conducted genomic prediction for five types of sperm morphology abnormalities in a large Duroc boar population. The estimated heritability of the studied traits ranged from 0.029 to 0.295. In the random cross-validation scenario, the predictive ability ranged from 0.212 to 0.417 for genomic best linear unbiased prediction (GBLUP) and from 0.249 to 0.565 for single-step GBLUP (ssGBLUP). In the forward prediction scenario, the predictive ability ranged from 0.069 to 0.389 for GBLUP and from 0.085 to 0.483 for ssGBLUP. In conclusion, the studied sperm morphology abnormalities showed moderate to low heritability. Both GBLUP and ssGBLUP showed comparative predictive abilities of breeding values, and ssGBLUP outperformed GBLUP under many circumstances in respect to predictive ability. To our knowledge, this is the first time that the genetic parameters and genomic predictive ability of these traits were reported in such a large Duroc boar population.https://www.mdpi.com/2076-2615/9/10/710Duroc boarsgenetic parametersgenomic predictionsingle-step GBLUPsperm morphology abnormalities |
| spellingShingle | Yunxiang Zhao Ning Gao Jian Cheng Saeed El-Ashram Lin Zhu Conglin Zhang Zhili Li Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology Abnormalities Animals Duroc boars genetic parameters genomic prediction single-step GBLUP sperm morphology abnormalities |
| title | Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology Abnormalities |
| title_full | Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology Abnormalities |
| title_fullStr | Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology Abnormalities |
| title_full_unstemmed | Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology Abnormalities |
| title_short | Genetic Parameter Estimation and Genomic Prediction of Duroc Boars’ Sperm Morphology Abnormalities |
| title_sort | genetic parameter estimation and genomic prediction of duroc boars sperm morphology abnormalities |
| topic | Duroc boars genetic parameters genomic prediction single-step GBLUP sperm morphology abnormalities |
| url | https://www.mdpi.com/2076-2615/9/10/710 |
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