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

• Asian-Australasian Journal of Animal Sciences
• /
• v.12 no.4
• /
• pp.511-514
• /
• 1999

Data pertaining to 1111 first lactation performance record of Karan Fries (Holstein-Friesian $\times$ Zebu) cows spread over a period of 21 years and sired by 72 bulls were used to examine the efficiency of sire indices for lactation milk production using auxiliary traits. First lactation length, first service period, first calving interval, first dry period and age at first calving were considered as auxiliary traits. The efficiency of this method was compared with simple daughter average index (D), contemporary comparison method (CC), least-square method (LSQ), simplified regressed least-squares method (SRLS) and best linear unbiased prediction (BLUP) for lactation milk production. The relative efficiency of sire evaluation methods using one auxiliary trait was lower (24.2-32.8%) in comparison to CC method, the most efficient method observed in this study. Use of two auxiliary traits at a time did not further improve the efficiency. The auxiliary sire indices discriminate better among bulls as the range of breeding values were higher in these methods in comparison to conventional sire evaluation methods. The rank correlation between breeding values estimated using auxiliary traits were high (0.77-0.78) with CC method. The rank correlation among auxiliary sire indices ranged from 0.98 to 0.99, indicating similar ranking of sire for breeding values of milk production in all the auxiliary sire indices.

• Asian-Australasian Journal of Animal Sciences
• /
• v.30 no.3
• /
• pp.309-319
• /
• 2017

Objective: Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods: This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results: We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion: This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

• Asian-Australasian Journal of Animal Sciences
• /
• v.32 no.8_spc
• /
• pp.1275-1283
• /
• 2019

Goats (Capra hircus) were domesticated during the late Neolithic, approximately 10,500 years ago, and humans exerted minor selection pressure until fairly recently. Probably the largest genetic change occurring over the millennia happened via natural selection and random genetic drift, the latter causing genes to be fixed in small and isolated populations. Recent human-influenced genetic changes have occurred through biometrics and genomics. For the most part, biometrics has concentrated upon the refining of estimates of heritabilities and genetic correlations. Heritabilities are instrumental in the calculation of estimated breeding values and genetic correlations are necessary in the construction of selection indices that account for changes in multiple traits under selection at one time. Early genomic studies focused upon microsatellite markers, which are short tandem repeats of nucleic acids and which are detected using polymerase chain reaction primers flanking the microsatellite. Microsatellite markers have been very important in parentage verification, which can impact genetic progress. Additionally, microsatellite markers have been a useful tool in assessing genetic diversity between and among breeds, which is important in the conservation of minor breeds. Single nucleotide polymorphisms are a new genomic tool that have refined classical BLUP methodology (biometric) to provide more accurate genomic estimated breeding values, provided a large reference population is available.

• Asian-Australasian Journal of Animal Sciences
• /
• v.31 no.5
• /
• pp.628-635
• /
• 2018

Objective: To determine the effects of genomic breeding values (GBV) and single nucleotide polymorphisms (SNP) on the total number of piglets born (TNB) in 3 pig breeds (Berkshire, Landrace, and Yorkshire). Methods: After collecting genomic information (Porcine SNP BeadChip) and phenotypic TNB records for each breed, the effects of GBV and SNP were estimated by using single step best linear unbiased prediction (ssBLUP) method. Results: The heritability estimates for TNB in Berkshire, Landrace, and Yorkshire breeds were 0.078, 0.107, and 0.121, respectively. The breeding value estimates for TNB in Berkshire, Landrace, and Yorkshire breeds were in the range of -1.34 to 1.47 heads, -1.79 to 1.87 heads, and -2.60 to 2.94 heads, respectively. Of sows having records for TNB, the reliability of breeding value for individuals with SNP information was higher than that for individuals without SNP information. Distributions of the SNP effects on TNB did not follow gamma distribution. Most SNP effects were near zero. Only a few SNPs had large effects. The numbers of SNPs with absolute value of more than 4 standard deviations in Berkshire, Landrace, and Yorkshire breeds were 11, 8, and 19, respectively. There was no SNP with absolute value of more than 5 standard deviations in Berkshire or Landrace. However, in Yorkshire, four SNPs (ASGA 0089457, ASGA0103374, ALGA0111816, and ALGA0098882) had absolute values of more than 5 standard deviations. Conclusion: There was no common SNP with large effect among breeds. This might be due to the large genetic composition differences and the small size of reference population. For the precise evaluation of genetic performance of individuals using a genomic selection method, it may be necessary to establish the appropriate size of reference population.

• Journal of Embryo Transfer
• /
• v.28 no.2
• /
• pp.79-85
• /
• 2013

The recent development in genetic assisted selection (combining traditional- and genome assisted selection method) and reproduction technologies will allow multiplying elite cow in Hanwoo small farm. This review describes the new context and corresponding needs for genome assisted selection schemes and how reproductive technologies can be incorporated to get more genetic gain for cow genetic improvement in Hanwoo. New improved massive phenotypes and pedigree information are being generated from commercial farm sector and these are allowing to do genetic evaluation using BLUP to get elite cows in Korea. Moreover cattle genome information can now be incorporated into breeding program. In this context, this review will discuss about combining the reproductive techniques (Multiple Ovulation Embryo Transfer; MOET) and genome assisted selection method to get more genetic gain in Hanwoo breeding program. Finally, how these technologies can be used for multiplication of elite cow in small farm was discussed.

• Asian-Australasian Journal of Animal Sciences
• /
• v.20 no.5
• /
• pp.622-626
• /
• 2007

Using multi-trait animal model BLUP, selection was conducted over seven generations for growth rate (DG), real-time ultrasound loin-eye muscle area (LEA), backfat thickness (BF), and intramuscular fat content (IMF) to develop a new line of purebred Duroc pigs with enhanced meat production and meat quality. This study was intended to investigate the relationship between restriction fragment length polymorphism (RFLP) of a heart fatty acid-binding protein (H-FABP) gene and intramuscular fat content (IMF) of this Duroc purebred population. The present experiment examined the RFLP of 499 slaughtered pigs. The DNA was separated from the blood or ear tissue of the pigs, which were slaughtered at 105 kg of body weight. Intramuscular fat content of the longissimus muscle was measured using chemical analysis. A significant difference was detected in the breeding value of IMF among the H-FABP PCR RFLP genotypes. The AA genotype has a significantly larger positive effect on the IMF breeding value than do the Aa and aa genotypes for the MspI RFLP. In addition, the DD genotype has a significantly greater positive effect on IMF breeding value than the Dd and dd genotypes for the HaeIII RFLP. For the HinfI RFLP, the hh genotype has a significantly larger positive effect on IMF breeding value than the HH genotype. Multiple regression analysis was performed using the IMF breeding values as the dependent variable and the three H-FABP genotypes as independent variables. Results revealed that the contribution of the genotypes to variation in IMF breeding values was approximately 40%. These results demonstrated that H-FABP RFLPs affect IMF in this Duroc population.

• Asian-Australasian Journal of Animal Sciences
• /
• v.15 no.5
• /
• pp.627-632
• /
• 2002

Genetic parameters for dairy performance traits were estimated, breeding values for the traits of all breeding sires and cows were predicted and the genetic trends were estimated using the breeding values in the Central Cattle Breeding Station (CCBS). A total of 3,801 records for Bangladeshi Local, 756 records for Red Sindhi and 959 records for Sahiwal covering the period from 1961 to 1997 were used in this analysis. Traits considered were total milk production per lactation (TLP), lactation length (LL) and daily milk yield (DMY). The genetic parameters were estimated by the REML using MTDFREML program. The breeding values were predicted by a best linear unbiased prediction (BLUP). In all sets of data, the genetic trends for the dairy performance traits were computed as averages of breeding values for cows born in the particular year. The estimates of heritability for TLP (0.26 and 0.27) and DMY (0.28 and 0.27) were moderate in Bangladeshi local and Red Sindhi breed, respectively. Furthermore, the heritability estimate for LL (0.24) was moderate in Red Sindhi. The estimates of heritabilities for all traits were low in Sahiwal. The repeatability estimate was high for TLP, moderate for LL and moderate to high for DMY. All variances estimated in Bangladeshi Local were low, comparing the respective values estimated in both Red Sindhi and Sahiwal. On the other hand, additive genetic variances for the three traits were estimated very low in Sahiwal. The genetic trends for the three dairy production traits have not been positive except for the recent trend in Bangladeshi Local.

• Asian-Australasian Journal of Animal Sciences
• /
• v.32 no.11
• /
• pp.1657-1663
• /
• 2019

Objective: A genome-based best linear unbiased prediction (GBLUP) method was applied to evaluate accuracies of genomic estimated breeding value (GEBV) of carcass and reproductive traits in Berkshire, Duroc and Yorkshire populations in Korean swine breeding farms. Methods: The data comprised a total of 1,870, 696, and 1,723 genotyped pigs belonging to Berkshire, Duroc and Yorkshire breeds, respectively. Reference populations for carcass traits consisted of 888 Berkshire, 466 Duroc, and 1,208 Yorkshire pigs, and those for reproductive traits comprised 210, 154, and 890 dams for the respective breeds. The carcass traits analyzed were backfat thickness (BFT) and carcass weight (CWT), and the reproductive traits were total number born (TNB) and number born alive (NBA). For each trait, GEBV accuracies were evaluated with a GEBV BLUP model and realized GEBVs. Results: The accuracies under the GBLUP model for BFT and CWT ranged from 0.33-0.72 and 0.33-0.63, respectively. For NBA and TNB, the model accuracies ranged 0.32 to 0.54 and 0.39 to 0.56, respectively. The realized accuracy estimates for BFT and CWT ranged 0.30 to 0.46 and 0.09 to 0.27, respectively, and 0.50 to 0.70 and 0.70 to 0.87 for NBA and TNB, respectively. For the carcass traits, the GEBV accuracies under the GBLUP model were higher than the realized GEBV accuracies across the breed populations, while for reproductive traits the realized accuracies were higher than the model based GEBV accuracies. Conclusion: The genomic prediction accuracy increased with reference population size and heritability of the trait. The GEBV accuracies were also influenced by GEBV estimation method, such that careful selection of animals based on the estimated GEBVs is needed. GEBV accuracy will increase with a larger sized reference population, which would be more beneficial for traits with low heritability such as reproductive traits.

• Asian-Australasian Journal of Animal Sciences
• /
• v.31 no.12
• /
• pp.1852-1862
• /
• 2018

Objective: The purpose of this study was to investigate a single step genome-wide association study (ssGWAS) for identifying genomic regions affecting reproductive traits in Landrace and Large White pigs. Methods: The traits included the number of pigs weaned per sow per year (PWSY), the number of litters per sow per year (LSY), pigs weaned per litters (PWL), born alive per litters (BAL), non-productive day (NPD) and wean to conception interval per litters (W2CL). A total of 321 animals (140 Landrace and 181 Large White pigs) were genotyped with the Illumina Porcine SNP 60k BeadChip, containing 61,177 single nucleotide polymorphisms (SNPs), while multiple traits single-step genomic BLUP method was used to calculate variances of 5 SNP windows for 11,048 Landrace and 13,985 Large White data records. Results: The outcome of ssGWAS on the reproductive traits identified twenty-five and twenty-two SNPs associated with reproductive traits in Landrace and Large White, respectively. Three known genes were identified to be candidate genes in Landrace pigs including retinol binding protein 7, and ubiquitination factor E4B genes for PWL, BAL, W2CL, and PWSY and one gene, solute carrier organic anion transporter family member 6A1, for LSY and NPD. Meanwhile, five genes were identified to be candidate genes in Large White, two of which, aldehyde dehydrogenase 1 family member A3 and leucine rich repeat kinase 1, associated with all of six reproduction traits and three genes; retrotransposon Gag like 4, transient receptor potential cation channel subfamily C member 5, and LHFPL tetraspan subfamily member 1 for five traits except W2CL. Conclusion: The genomic regions identified in this study provided a start-up point for marker assisted selection and estimating genomic breeding values for improving reproductive traits in commercial pig populations.