Abstract
For this study, the DNA of 8,413 animals collected by various methods from Hanwoo farms nationwide was extracted. The Axiom Bovine 60k version 3(Affymetrix Inc., 2006) SNP panel was used to generate genomic information. Quality Control to increase the accuracy of genomic analysis removed SNPs whose SNPs were on the sex chromosome or whose position on the chromosome was not identified. A total of 64,973 SNP markers were used to remove markers with an SNP call rate of 95% or less, a Minor Allele Frequency(MAF) of 0.01 or less, and a Chi-square value of more than 95% measured for the Hardy-Weinberg Equilibrium(HWE). Among the 8,413 animals with genomic information, duplicate animals, pedigree errors, and animals that did not match dependent variables were removed, and 6,616 references with genomic information were used for analysis. KPN used in the analysis was extracted using semen, and steer performed DNA extraction using tissue samples provided by the Korea Institute for Animal Products Quality Evaluation and the cow collected tail hairs and used them for analysis. As for the pedigree data, five generation pedigree data connected to 6,616 animals were collected from the Korea Animal Improvement Association, and a total of 5,153,168 pedigree data were used for the analysis. The carcass traits data were used for analysis on the remaining 2,376,865 animals after pre-removal of missing and abnormal values among 5,153,168 animals with carcass traits data. Four traits used in the analysis were considered Carcass Weight(CW), Eye Muscle Area(EMA), Backfat Thickness(BF), and Marbling Score(MS). It was estimated using the MiX99(Lidauer, 2015) program to estimate GEBV using ssGBLUP, and reliability estimated was performed using SNP BLUP REL, a self developed reliability estimated Fortran program. The genetic parameters used were the results of Son(2020), and the GEBV of Hanwoo carcass traits was estimated to show the distribution for each trait to determine the normality of GEBV, and to determine whether it was approximated to the normal distribution. EBV estimated by the BLUP method was analyzed as 13.90, 3.78, -0.17, and 0.63, respectively, in CW, EMA, BF, MS in Hanwoo cows. KPN showed 22.51, 6.33, -0.58, and 0.93, which were higher than that of cows, and 16.03, 5.29, -0.83, and 0.84, respectively. GEBV estimated by the single step method was analyzed as 3.32, 1.36, -1.04, and 0.13, respectively, in CW, EMA, BF, and MS in Hanwoo cows. KPN was estimated to be 11.96, 4.14, -1.47, 0.48, Steer was estimated to be 6.16, 3.20, -1.74, 0.44, and the difference between GEBV and EBV analyzed CW was –10.33, EMA was –2.23, BF was –0.89, and MS was –0.45, and GEBV was relatively lower than EBV. The GEBV of Hanwoo cows, steers and KPN was relatively lower than the estimated breeding value by the BLUP method. The reason for this result was that the proportion of pedigree data is higher than that of genomic data in the process of making H matrix due to the small number of genomic data, so it is estimated that the EBV estimate of the BLUP method using pedigree data is higher. The reliability analysis results of EBV estimated in 6,616 animals with genomic data were 0.48, 0.51, 0.51, and 0.59, respectively, in cows CW, EMA, BF, and MS, and the estimated EBV reliability of KPN was estimated to be 0.92, 0.92, 0.93 and 0.94, which was 40% higher on average. In addition, the GEBV reliability estimated by the single step GBLUP method, the cow CW was 0.66, EMA was 0.68, BF was 0.70 and MS was 0.77, and the KPN was 0.93. 0.93, 0.94, and 0.96. In the case of Hanwoo cows, it was confirmed that the reliability of GEBV increased by 17-19% on average than that of EBV, and in the case of KPN, the reliability of GEBV was slightly higher. It was found that KPNs containing a lot of carcass trait data of progeny had high reliability in EBV and GEBV, and cows with less carcass trait data of progeny than KPN had higher reliability using GEBV than EBV.
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