Improving the accuracy of genomic prediction for meat quality traits using whole genome sequence data in pigs  

作　　者：Zhanwei Zhuang Jie Wu Yibin Qiu Donglin Ruan Rongrong Ding Cineng Xu Shenping Zhou Yuling Zhang Yiyi Liu Fucai Ma Jifei Yang Ying Sun Enqin Zheng Ming Yang Gengyuan Cai Jie Yang Zhenfang Wu 

机构地区：[1]College of Animal Science and National Engineering Research Center for Breeding Swine Industry,South China Agricultural University,Guangzhou 510642,China [2]Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding,Guangzhou 510642,China [3]College of Animal Science and Technology,Zhongkai University of Agriculture and Engineering,Guangzhou 510225,China [4]Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture,Yunfu 527400,China

出　　处：《Journal of Animal Science and Biotechnology》2023年第5期1880-1894,共15页畜牧与生物技术杂志（英文版）

基　　金：supported by a Technical Innovation of Crossbred in Swine and Breed High Fertility Lines Project(2022B0202090002);a Local Innovative and Research Teams Project of Guangdong Province(2019BT02N630);a Natural Science Foundation of Guangdong Province project(2018B030313011);Innovative Teams of Modern Agriculture and Industry Technology System of Guangdong Province(2022KJ26).

摘　　要：Background Pork quality can directly affect customer purchase tendency and meat quality traits have become valu-able in modern pork production.However,genetic improvement has been slow due to high phenotyping costs.In this study,whole genome sequence(WGS)data was used to evaluate the prediction accuracy of genomic best linear unbiased prediction(GBLUP)for meat quality in large-scale crossbred commercial pigs.Results We produced WGS data(18,695,907 SNPs and 2,106,902 INDELs exceed quality control)from 1,469 sequenced Duroc×(Landrace×Yorkshire)pigs and developed a reference panel for meat quality including meat color score,marbling score,L*(lightness),a*(redness),and b*(yellowness)of genomic prediction.The prediction accuracy was defined as the Pearson correlation coefficient between adjusted phenotypes and genomic estimated breeding values in the validation population.Using different marker density panels derived from WGS data,accuracy differed substantially among meat quality traits,varied from 0.08 to 0.47.Results showed that MultiBLUP outperform GBLUP and yielded accuracy increases ranging from 17.39%to 75%.We optimized the marker density and found medium-and high-density marker panels are beneficial for the estimation of heritability for meat quality.Moreover,we conducted genotype imputation from 50K chip to WGS level in the same population and found average concord-ance rate to exceed 95%and r^(2)=0.81.Conclusions Overall,estimation of heritability for meat quality traits can benefit from the use of WGS data.This study showed the superiority of using WGS data to genetically improve pork quality in genomic prediction.

关 键 词：Genomic prediction Meat quality PIGS Whole genome sequence 

分 类 号：S828[农业科学—畜牧学]