• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.321-330
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• 2023

The genetic diversity of three Hanwoo populations was analyzed using 11 microsatellite (MS) markers for the traceability of Hanwoo beef in this study. A total of 1,099 Hanwoo cattle from two populations (694 line-breeding and 405 general Hanwoo) at the Hanwoo Research Institute (HRI) of the National Institute of Animal Science and 1,171 Korean proven bulls (KPNs) were used for the analysis. Specific alleles of four markers (ETH10, INRA23, TGLA122, and TGLA227) were identified only in the line-breeding population, although at a low allele frequency (0.001 - 0.02). The genetic distance (Nei's D) between line-breeding Hanwoo and KPN was the greatest (0.064), whereas general Hanwoo and KPN were relatively close genetically (0.02); the distance between line-breeding and general Hanwoo was found to be 0.054. These results are expected because the HRI has performed closed breeding via selecting its line-breeding sires without utilizing KPN since 2009. Therefore, the line-breeding Hanwoo population of HRI show different genetic diversity from the KPN population, based on the 11 MS markers. The results of this study provide basic data for securing the genetic diversity of Hanwoo cattle and utilizing line-breeding Hanwoo cattle from the HRI.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.13-18
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• 2013

This study was conducted to estimate the Genomic Estimated Breeding Value (GEBV) using Genomic Best Linear Unbiased Prediction (GBLUP) method in Hanwoo (Korean native cattle) population. The result is expected to adapt genomic selection onto the national Hanwoo evaluation system. Carcass weight (CW), eye muscle area (EMA), backfat thickness (BT), and marbling score (MS) were investigated in 552 Hanwoo progeny-tested steers at Livestock Improvement Main Center. Animals were genotyped with Illumina BovineHD BeadChip (777K SNPs). For statistical analysis, Genetic Relationship Matrix (GRM) was formulated on the basis of genotypes and the accuracy of GEBV was estimated with 10-fold Cross-validation method. The accuracies estimated with cross-validation method were between 0.915~0.957. In 534 progeny-tested steers, the maximum difference of GEBV accuracy compared to conventional EBV for CW, EMA, BT, and MS traits were 9.56%, 5.78%, 5.78%, and 4.18% respectively. In 3,674 pedigree traced bulls, maximum increased difference of GEBV for CW, EMA, BT, and MS traits were increased as 13.54%, 6.50%, 6.50%, and 4.31% respectively. This showed that the implementation of genomic pre-selection for candidate calves to test on meat production traits could improve the genetic gain by increasing accuracy and reducing generation interval in Hanwoo genetic evaluation system to select proven bulls.

• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.399-403
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• 2013

This study was conducted to investigate the basic concept of multiple trait effective daughter contribution (MTEDC) for dairy cattle sires and calculate effective daughter contribution (EDC) by applying a five lactation multiple trait model using milk yield test records of daughters for the Multiple-trait Across Country Evaluation (MACE). Milk yield data and pedigree information of 301,551 cows that were the progeny of 2,046 Korean and imported dairy bulls were collected from the National Agricultural Cooperative Federation and used in this study. For MTEDC approximation, the reliability of the breeding value was separated based on parents average, own yield deviation and mate adjusted progeny contribution. EDC was then calculated by lactation using these reliabilities. The average number of recorded daughters per sire by lactations were 140.57, 94.24, 55.14, 29.20 and 14.06 from the first to fifth lactation, respectively. However, the average EDC per sire by lactation using the five lactation multiple trait model was 113.49, 89.28, 73.56, 54.02 and 35.08 from the first to fifth lactation, respectively, while the decrease of EDC in late lactations was comparably lower than the average number of recorded daughters per sire. These findings indicate that the availability of daughters without late lactation records is increased by genetic correlation using the multiple trait model. Owing to the relatedness between the EDC and reliability of the estimated breeding value for sire, understanding the MTEDC algorithm and continuous monitoring of EDC is required for correct MACE application of the five lactation multiple trait model.

• Journal of Life Science
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• v.22 no.3
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• pp.366-372
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• 2012

This study was conducted to estimate the extent of linkage disequilibrium (LD) and effective population size using whole genomic single nucleotide polymorphisms (SNP) genotyped by DNA chip in Hanwoo. Using the blood samples of 35 young bulls born from 2005 to 2008 and their progenies (N=253) in a Hanwoo nucleus population collected from Hanwoo Improvement Center, 51,582 SNPs were genotyped using Bovine SNP50 chips. A total of 40,851 SNPs were used in this study after elimination of SNPs with a missing genotyping rate of over 10 percent and monomorphic SNPs (10,730 SNPs). The total autosomal genome length, measured as the sum of the longest syntenic pairs of SNPs by chromosome, was 2,541.6 Mb (Mega base pairs). The average distances of all adjacent pairs by each BTA ranged from 0.55 to 0.74 cM. Decay of LD showed an exponential trend with physical distance. The means of LD ($r^2$) among syntenic SNP pairs were 0.136 at a range of 0-0.1 Mb in physical distance and 0.06 at a range of 0.1-0.2 Mb. When these results were used for Luo's formula, about 2,000 phenotypic records were found to be required to achieve power > 0.9 to detect 5% QTL in the population of Hanwoo. As a result of estimating effective population size by generation in Hanwoo, the estimated effective population size for the current status was 84 heads and the estimate of effective population size for 50 generations of ancestors was 1,150 heads. The average decreasing rates of effective population size by generation were 9.0% at about five generations and 17.3% at the current generation. The main cause of the rapid decrease in effective population size was considered to be the intensive use of a few prominent sires since the application of artificial insemination technology in Korea. To increase and/or sustain the effective population size, the selection of various proven bulls and mating systems that consider genetic diversity are needed.

• Journal of Animal Science and Technology
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• v.65 no.4
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• pp.720-734
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• 2023

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (M_e) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between M_e and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between M_e and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the M_e, the higher the accuracy of EBV.

• Journal of Animal Science and Technology
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• v.48 no.1
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• pp.15-20
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• 2006

The data used in the study were taken from the national dairy genetic evaluation of bulls from 1986 up to 2001. It was conducted to compare the phenotypic performance and genetic merits in terms of production traits, linear traits and selection indexes of four types of dairy semen (TypeⅠ:semen from Korean proven bull, Type Ⅱ:semen from proven bull imported by National Agricultural Cooperative Federation(NACF), Type Ⅲ:semen imported from USA, Type Ⅳ:semen imported from Canada) used in Korea. The result of national dairy genetic evaluation was used to compare genetic merits. Type Ⅲ was superior in the phenotypic performance of milk yield, milk fat and milk protein and was significantly different from Type Ⅰ. Types of semen were not significantly different in fat when semen from bull born after 1991 were compared. Likewise, types of semen were not significantly different in the genetic merit for milk yield, milk fat, milk protein and milk protein %. Moreso, for profit index (MFP) and Korean type production index (KTPI) it was not statistically different. However type Ⅰ was superior in milk fat % and was significantly different from other types. Type Ⅳ was superior in Final Score of conformation test (FS) and Udder Composite Index (UDC) and significantly different from Type Ⅰ. When semen from bull born after 1991 were compared, types of semen were not significantly different in milk yield and milk protein, although type I was superior in milk fat, milk fat %, milk protein % and MFP and was significantly different from others. Moreover type Ⅲ and type Ⅳ was superior in UDC and were significantly different from others.