Genome-wide Association Study to Identify Quantitative Trait Loci for Meat and Carcass Quality Traits in Berkshire

被引:15
|
作者
Iqbal, Asif [1 ]
Kim, You-Sam [1 ]
Kang, Jun-Mo [1 ]
Lee, Yun-Mi [1 ]
Rai, Rajani [1 ]
Jung, Jong-Hyun [2 ]
Oh, Dong-Yup [3 ]
Nam, Ki-Chang [4 ]
Lee, Hak-Kyo [5 ]
Kim, Jong-Joo [1 ]
机构
[1] Yeungnam Univ, Sch Biotechnol, Gyongsan 712749, South Korea
[2] Jung P&C Inst, Seoul 16950, South Korea
[3] Livestock Res Inst, Yeongju 750871, South Korea
[4] Sunchon Natl Univ, Dept Anim Sci & Technol, Sunchon 540950, South Korea
[5] Chonbuk Natl Univ, Dept Anim Biotechnol, Jeonju 561756, South Korea
来源
关键词
Genome Wide Association; Study; Berkshire; Quantitative Trait Loci; Single Nucleotide Polymorphism; Meat Quality; PIETRAIN RESOURCE POPULATION; BACKFAT THICKNESS; PIG BREEDS; LINKAGE; GENES; PORK; QTL; IDENTIFICATION; FATNESS; SCAN;
D O I
10.5713/ajas.15.0752
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Meat and carcass quality attributes are of crucial importance influencing consumer preference and profitability in the pork industry. A set of 400 Berkshire pigs were collected from Dasan breeding farm, Namwon, Chonbuk province, Korea that were born between 2012 and 2013. To perform genome wide association studies (GWAS), eleven meat and carcass quality traits were considered, including carcass weight, backfat thickness, pH value after 24 hours (pH24), Commission Internationale de l'Eclairage lightness in meat color (CIE L), redness in meat color (CIE a), yellowness in meat color (CIE b), filtering, drip loss, heat loss, shear force and marbling score. All of the 400 animals were genotyped with the Porcine 62K SNP BeadChips (Illumina Inc., USA). A SAS general linear model procedure (SAS version 9.2) was used to pre-adjust the animal phenotypes before GWAS with sire and sex effects as fixed effects and slaughter age as a covariate. After fitting the fixed and covariate factors in the model, the residuals of the phenotype regressed on additive effects of each single nucleotide polymorphism (SNP) under a linear regression model (PLINK version 1.07). The significant SNPs after permutation testing at a chromosome-wise level were subjected to stepwise regression analysis to determine the best set of SNP markers. A total of 55 significant (p<0.05) SNPs or quantitative trait loci (QTL) were detected on various chromosomes. The QTLs explained from 5.06% to 8.28% of the total phenotypic variation of the traits. Some QTLs with pleiotropic effect were also identified. A pair of significant QTL for pH24 was also found to affect both CIE L and drip loss percentage. The significant QTL after characterization of the functional candidate genes on the QTL or around the QTL region may be effectively and efficiently used in marker assisted selection to achieve enhanced genetic improvement of the trait considered.
引用
收藏
页码:1537 / 1544
页数:8
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