- Volume 28 Issue 11
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Genome-wide Association Study (GWAS) and Its Application for Improving the Genomic Estimated Breeding Values (GEBV) of the Berkshire Pork Quality Traits
- Lee, Young-Sup (Department of Natural Science, Interdisciplinary Program in Bioinformatics, Seoul National University) ;
- Jeong, Hyeonsoo (Department of Natural Science, Interdisciplinary Program in Bioinformatics, Seoul National University) ;
- Taye, Mengistie (Department of Agricultural Biotechnology, Animal Biotechnology, and Research Institute for Agriculture and Life Sciences, Seoul National University) ;
- Kim, Hyeon Jeong (C&K Genomics Inc.) ;
- Ka, Sojeong (Department of Agricultural Biotechnology, Animal Biotechnology, and Research Institute for Agriculture and Life Sciences, Seoul National University) ;
- Ryu, Youn-Chul (Division of Biotechnology, Sustainable Agriculture Research Institute, Jeju National University) ;
- Cho, Seoae (C&K Genomics Inc.)
- Received : 2015.03.31
- Accepted : 2015.06.24
- Published : 2015.11.01
The missing heritability has been a major problem in the analysis of best linear unbiased prediction (BLUP). We introduced the traditional genome-wide association study (GWAS) into the BLUP to improve the heritability estimation. We analyzed eight pork quality traits of the Berkshire breeds using GWAS and BLUP. GWAS detects the putative quantitative trait loci regions given traits. The single nucleotide polymorphisms (SNPs) were obtained using GWAS results with p value <0.01. BLUP analyzed with significant SNPs was much more accurate than that with total genotyped SNPs in terms of narrow-sense heritability. It implies that genomic estimated breeding values (GEBVs) of pork quality traits can be calculated by BLUP via GWAS. The GWAS model was the linear regression using PLINK and BLUP model was the G-BLUP and SNP-GBLUP. The SNP-GBLUP uses SNP-SNP relationship matrix. The BLUP analysis using preprocessing of GWAS can be one of the possible alternatives of solving the missing heritability problem and it can provide alternative BLUP method which can find more accurate GEBVs.
Best Linear Unbiased Prediction;Genome Wide Association Study;Missing Heritability Problem;Sherman-Morrison-Woodbury Lemma;Single Nucleotide Polymorphism-Genomic Best Linear Unbiased Prediction;Berkshire Pigs
Supported by : National Institute of Biological Resources (NIBR)
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