Factors affecting the accuracy of genomic prediction in joint pig populations
•We evaluated key factors influencing joint breeding accuracy.•Each factor contributes to the accuracy of joint evaluation.•Casual variant effect size is the primary influencing factor.•There is a weak genetic correlation between two Duroc populations.•Multi-trait model is a promising method for joi...
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Published in | Animal (Cambridge, England) Vol. 17; no. 10; p. 100980 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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Elsevier B.V
01.10.2023
Elsevier |
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Abstract | •We evaluated key factors influencing joint breeding accuracy.•Each factor contributes to the accuracy of joint evaluation.•Casual variant effect size is the primary influencing factor.•There is a weak genetic correlation between two Duroc populations.•Multi-trait model is a promising method for joint evaluation.
Genomic prediction (GP) has greatly advanced animal and plant breeding over the past two decades. GP in joint populations is a feasible method to improve the accuracy of genomic estimated breeding values in small populations. However, there is still a need to understand the factors that influence GP in joint populations. This study used simulated data and real data from Duroc pig populations to examine the impact of linkage disequilibrium (LD), causal variants effect sizes (CVESs), and minor allele frequencies (MAF) of SNPs on the accuracy of genomic prediction in joint populations. Three prediction methods were used: genomic best linear unbiased prediction (GBLUP), single-step GBLUP and multi-trait GBLUP. Results from the simulated datasets showed that the accuracies of GP in joint populations were always higher than those in a single population when only LD inconsistencies existed. However, single-step GBLUP accuracy in joint populations decreased as the correlation of MAF between populations decreased, while the accuracy of GBLUP is consistently higher in joint populations than in a single population. As the correlation of CVES between populations decreased, the accuracy of both GBLUP and single-step GBLUP in joint populations declined. Analysis of real Duroc populations showed low genetic correlation, similar to the simulated relationship between the most distant populations. In most cases in Duroc populations, GP have higher accuracies in joint populations than in individual population. In conclusion, the consistency of CVES plays a more important role in multi-population GP. The genetic relatedness of the Duroc populations is so weak that the prediction accuracy of GP in joint populations is reduced in some traits. Multi-trait GBLUP is a competitive method for the joint breeding evaluation. |
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AbstractList | Genomic prediction (GP) has greatly advanced animal and plant breeding over the past two decades. GP in joint populations is a feasible method to improve the accuracy of genomic estimated breeding values in small populations. However, there is still a need to understand the factors that influence GP in joint populations. This study used simulated data and real data from Duroc pig populations to examine the impact of linkage disequilibrium (LD), causal variants effect sizes (CVESs), and minor allele frequencies (MAF) of SNPs on the accuracy of genomic prediction in joint populations. Three prediction methods were used: genomic best linear unbiased prediction (GBLUP), single-step GBLUP and multi-trait GBLUP. Results from the simulated datasets showed that the accuracies of GP in joint populations were always higher than those in a single population when only LD inconsistencies existed. However, single-step GBLUP accuracy in joint populations decreased as the correlation of MAF between populations decreased, while the accuracy of GBLUP is consistently higher in joint populations than in a single population. As the correlation of CVES between populations decreased, the accuracy of both GBLUP and single-step GBLUP in joint populations declined. Analysis of real Duroc populations showed low genetic correlation, similar to the simulated relationship between the most distant populations. In most cases in Duroc populations, GP have higher accuracies in joint populations than in individual population. In conclusion, the consistency of CVES plays a more important role in multi-population GP. The genetic relatedness of the Duroc populations is so weak that the prediction accuracy of GP in joint populations is reduced in some traits. Multi-trait GBLUP is a competitive method for the joint breeding evaluation. •We evaluated key factors influencing joint breeding accuracy.•Each factor contributes to the accuracy of joint evaluation.•Casual variant effect size is the primary influencing factor.•There is a weak genetic correlation between two Duroc populations.•Multi-trait model is a promising method for joint evaluation. Genomic prediction (GP) has greatly advanced animal and plant breeding over the past two decades. GP in joint populations is a feasible method to improve the accuracy of genomic estimated breeding values in small populations. However, there is still a need to understand the factors that influence GP in joint populations. This study used simulated data and real data from Duroc pig populations to examine the impact of linkage disequilibrium (LD), causal variants effect sizes (CVESs), and minor allele frequencies (MAF) of SNPs on the accuracy of genomic prediction in joint populations. Three prediction methods were used: genomic best linear unbiased prediction (GBLUP), single-step GBLUP and multi-trait GBLUP. Results from the simulated datasets showed that the accuracies of GP in joint populations were always higher than those in a single population when only LD inconsistencies existed. However, single-step GBLUP accuracy in joint populations decreased as the correlation of MAF between populations decreased, while the accuracy of GBLUP is consistently higher in joint populations than in a single population. As the correlation of CVES between populations decreased, the accuracy of both GBLUP and single-step GBLUP in joint populations declined. Analysis of real Duroc populations showed low genetic correlation, similar to the simulated relationship between the most distant populations. In most cases in Duroc populations, GP have higher accuracies in joint populations than in individual population. In conclusion, the consistency of CVES plays a more important role in multi-population GP. The genetic relatedness of the Duroc populations is so weak that the prediction accuracy of GP in joint populations is reduced in some traits. Multi-trait GBLUP is a competitive method for the joint breeding evaluation. |
ArticleNumber | 100980 |
Author | Zhao, Wei Zhang, Zhenyang Pan, Yuchun Wang, Zhen Zhang, Zhe Ma, Peipei Wang, Qishan |
Author_xml | – sequence: 1 givenname: Wei surname: Zhao fullname: Zhao, Wei organization: Department of Animal Science, School of Agriculture and Biology, Shanghai Jiaotong University, 800# Dongchuan Road, Shang, East 200240, China – sequence: 2 givenname: Zhenyang surname: Zhang fullname: Zhang, Zhenyang organization: Department of Animal Science, College of Animal Sciences, Zhejiang University, 866# Yuhangtang Road, Hangzhou, East 310058, China – sequence: 3 givenname: Zhen surname: Wang fullname: Wang, Zhen organization: Department of Animal Science, College of Animal Sciences, Zhejiang University, 866# Yuhangtang Road, Hangzhou, East 310058, China – sequence: 4 givenname: Peipei surname: Ma fullname: Ma, Peipei organization: Department of Animal Science, School of Agriculture and Biology, Shanghai Jiaotong University, 800# Dongchuan Road, Shang, East 200240, China – sequence: 5 givenname: Yuchun orcidid: 0000-0002-1163-5963 surname: Pan fullname: Pan, Yuchun organization: Department of Animal Science, College of Animal Sciences, Zhejiang University, 866# Yuhangtang Road, Hangzhou, East 310058, China – sequence: 6 givenname: Qishan surname: Wang fullname: Wang, Qishan organization: Department of Animal Science, College of Animal Sciences, Zhejiang University, 866# Yuhangtang Road, Hangzhou, East 310058, China – sequence: 7 givenname: Zhe surname: Zhang fullname: Zhang, Zhe email: zhe_zhang@zju.edu.cn organization: Department of Animal Science, College of Animal Sciences, Zhejiang University, 866# Yuhangtang Road, Hangzhou, East 310058, China |
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Snippet | •We evaluated key factors influencing joint breeding accuracy.•Each factor contributes to the accuracy of joint evaluation.•Casual variant effect size is the... Genomic prediction (GP) has greatly advanced animal and plant breeding over the past two decades. GP in joint populations is a feasible method to improve the... |
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Title | Factors affecting the accuracy of genomic prediction in joint pig populations |
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