Accuracy of genomic prediction using mixed low-density marker panels

被引:2
|
作者
Hou, Lianjie [1 ]
Liang, Wenshuai [1 ]
Xu, Guli [1 ]
Huang, Bo [1 ]
Zhang, Xiquan [1 ]
Hu, Ching Yuan [2 ]
Wang, Chong [1 ]
机构
[1] South China Agr Univ, Coll Anim Sci, Guangdong Prov Key Lab Agroanim Genom & Mol Breed, Natl Engn Res Ctr Breeding Swine Ind, 483 Wushan Rd, Guangzhou 510642, Peoples R China
[2] Univ Hawaii Manoa, Coll Trop Agr & Human Resources, Dept Human Nutr Food & Anim Sci, AgSci, 1955 East West Rd,415J, Honolulu, HI 96822 USA
基金
中国博士后科学基金;
关键词
genomic selection; SNP imputation; low-density polymorphism panel; mixed low-density panel; SELECTION; POPULATION; STRATEGIES; IMPUTATION; VALUES;
D O I
10.1071/AN18503
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Low-density single-nucleotide polymorphism (LD-SNP) panel is one effective way to reduce the cost of genomic selection in animal breeding. The present study proposes a new type of LD-SNP panel called mixed low-density (MLD) panel, which considers SNPs with a substantial effect estimated by Bayes method B (BayesB) from many traits and evenly spaced distribution simultaneously. Simulated and real data were used to compare the imputation accuracy and genomic-selection accuracy of two types of LD-SNP panels. The result of genotyping imputation for simulated data showed that the number of quantitative trait loci (QTL) had limited influence on the imputation accuracy only for MLD panels. Evenly spaced (ELD) panel was not affected by QTL. For real data, ELD performed slightly better than did MLD when panel contained 500 and 1000 SNP. However, this advantage vanished quickly as the density increased. The result of genomic selection for simulated data using BayesB showed that MLD performed much better than did ELD when QTL was 100. For real data, MLD also outperformed ELD in growth and carcass traits when using BayesB. In conclusion, the MLD strategy is superior to ELD in genomic selection under most situations.
引用
收藏
页码:999 / 1007
页数:9
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