Estimation of variance and genomic prediction using genotypes imputed from low-density marker subsets for carcass traits in Japanese black cattle

• Published in: Animal science journal 2016-09, Vol.87 (9), p.1106-1113
• Main Authors: Ogawa, Shinichiro, Matsuda, Hirokazu, Taniguchi, Yukio, Watanabe, Toshio, Sugimoto, Yoshikazu, Iwaisaki, Hiroaki
• Format: Article
• Language: English
• Subjects: Animals; Breeding; carcass trait; Cattle; Cattle - genetics; Cost-Benefit Analysis; Density; Food Quality; Gene polymorphism; Genes; Genetic diversity; Genetic variance; Genetic Variation; genomic prediction; Genomics; Genotype; Genotype & phenotype; genotype imputation; Genotypes; Genotyping Techniques - methods; Japanese Black cattle; Linear Models; Livestock breeding; Male; Mathematical analysis; Matrix methods; Meat - analysis; Meat - economics; Model accuracy; Nucleotides; Polymorphism; Polymorphism, Single Nucleotide - genetics; Predictive Value of Tests; Quantitative Trait, Heritable; Single-nucleotide polymorphism; variance component
• ISSN: 1344-3941; 1740-0929
• DOI: 10.1111/asj.12570

The influence of genotype imputation using low‐density single nucleotide polymorphism (SNP) marker subsets on the genomic relationship matrix (G matrix), genetic variance explained, and genomic prediction (GP) was investigated for carcass weight and marbling score in Japanese Black fattened steers, using genotype data of approximately 40,000 SNPs. Genotypes were imputed using equally spaced SNP subsets of different densities. Two different linear models were used. The first (model 1) incorporated one G matrix, while the second (model 2) used two different G matrices constructed using the selected and remaining SNPs. When using model 1, the estimated additive genetic variance was always larger when using all SNPs obtained via genotype imputation than when using only equally spaced SNP subsets. The correlations between the genomic estimated breeding values obtained using genotype imputation with at least 3,000 SNPs and those using all available SNPs without imputation were higher than 0.99 for both traits. While additive genetic variance was likely to be partitioned with model 2, it did not enhance the accuracy of GP compared with model 1. These results indicate that genotype imputation using an equally spaced low‐density panel of an appropriate size can be used to produce a cost‐effective, valid GP.