• Animal Bioscience
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• 제34권4호
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• pp.516-524
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• 2021

Objective: The genetic evaluation of Santa Inês sheep was performed for resistance to gastrointestinal nematode infection (RGNI) and body size using different relationship matrices to assess the efficiency of including genomic information in the analyses. Methods: There were 1,637 animals in the pedigree and 500, 980, and 980 records of RGNI, thoracic depth (TD), and rump height (RH), respectively. The genomic data consisted of 42,748 SNPs and 388 samples genotyped with the OvineSNP50 BeadChip. The (co)variance components were estimated in single- and multi-trait analyses using the numerator relationship matrix (A) and the hybrid matrix H, which blends A with the genomic relationship matrix (G). The BLUP and single-step genomic BLUP methods were used. The accuracies of estimated breeding values and Spearman rank correlation were also used to assess the feasibility of incorporating genomic information in the analyses. Results: The heritability estimates ranged from 0.11±0.07, for TD (in single-trait analysis using the A matrix), to 0.38±0.08, for RH (using the H matrix in multi-trait analysis). The estimates of genetic correlation ranged from -0.65±0.31 to 0.59±0.19, using A, and from -0.42±0.30 to 0.57±0.16 using H. The gains in accuracy of estimated breeding values ranged from 2.22% to 75.00% with the inclusion of genomic information in the analyses. Conclusion: The inclusion of genomic information will benefit the direct selection for the traits in this study, especially RGNI and TD. More information is necessary to improve the understanding on the genetic relationship between resistance to nematode infection and body size in Santa Inês sheep. The genetic evaluation for the evaluated traits was more efficient when genomic information was included in the analyses.

• Asian-Australasian Journal of Animal Sciences
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• 제30권7호
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• pp.907-911
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• 2017

Objective: Intramuscular fat is one of the meat quality traits that is considered in the selection strategies for Hanwoo (Korean cattle). Different methods are used to estimate the breeding value of selection candidates. In the present work we focused on accuracy of different genotype relationship matrices as described by forni and pedigree based relationship matrix. Methods: The data set included a total of 778 animals that were genotyped for BovineSNP50 BeadChip. Among these 778 animals, 72 animals were sires for 706 reference animals and were used as a validation dataset. Single trait animal model (best linear unbiased prediction and genomic best linear unbiased prediction) was used to estimate the breeding values from genomic and pedigree information. Results: The diagonal elements for the pedigree based coefficients were slightly higher for the genomic relationship matrices (GRM) based coefficients while off diagonal elements were considerably low for GRM based coefficients. The accuracy of breeding value for the pedigree based relationship matrix (A) was 13% while for GRM (GOF, G05, and Yang) it was 0.37, 0.45, and 0.38, respectively. Conclusion: Accuracy of GRM was 1.5 times higher than A in this study. Therefore, genomic information will be more beneficial than pedigree information in the Hanwoo breeding program.

• Journal of Animal Science and Technology
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• 제52권5호
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• pp.357-366
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• 2010

한우의 유전체 전장의 정보를 Illumina BeadArray$^{TM}$ Bovine SNP50 assay를 이용하여 단일염기다형 현상을 조사한 결과, 유전적 다양성을 보이는 좌위가 약 32,567 좌위 이상에서 다양성을 보이고 있었으며 약 5,554 좌위에서 다양성이 조사되지 않았다. 이는 조사된 자료의 가계집단의 수가 크게 제한되었기 때문에 기인될 수 있으며 또 다른 원인으로는 한우 종축집단의 크기가 작을 수 있다는 현상을 반증한다고 사료된다. 유전분석의 기초가 되는 혈통기록에 의한 개체간 혈연관계를 유전체 정보에 의한 혈연관계와 비교하여 본 결과, 유전체 정보에 의한 혈연관계의 크기가 혈통기록에 의한 혈연관계보다 좀 더 정확하게 추정될 수 있다는 장점이 있으며 혈통기록상의 오류로 그릇된 혈연관계의 크기를 유전체 정보를 통하여 보완할 수 있다는 장점이 있다. 이러한 장점을 활용하면 유전체정보를 이용한 유전능력 평가의 정확성을 크게 향상시킬 수 있을 것으로 사료되었다.

• Genomics & Informatics
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• 제12권4호
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• pp.254-260
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• 2014

Best linear unbiased prediction (BLUP) has been used to estimate the fixed effects and random effects of complex traits. Traditionally, genomic relationship matrix-based (GRM) and random marker-based BLUP analyses are prevalent to estimate the genetic values of complex traits. We used three methods: GRM-based prediction (G-BLUP), random marker-based prediction using an identity matrix (so-called single-nucleotide polymorphism [SNP]-BLUP), and SNP-SNP variance-covariance matrix (so-called SNP-GBLUP). We used 35,675 SNPs and R package "rrBLUP" for the BLUP analysis. The SNP-SNP relationship matrix was calculated using the GRM and Sherman-Morrison-Woodbury lemma. The SNP-GBLUP result was very similar to G-BLUP in the prediction of genetic values. However, there were many discrepancies between SNP-BLUP and the other two BLUPs. SNP-GBLUP has the merit to be able to predict genetic values through SNP effects.

• 농업과학연구
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• 제48권4호
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• pp.681-691
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• 2021

The estimated breeding value (EBV) and accuracy of Hanwoo steer (Korean cattle) is an indicator that can predict the slaughter time in the future and carcass performance outcomes. Recently, studies using pedigrees and genotypes are being actively conducted to improve the accuracy of the EBV. In this study, the pedigree and genotype of 46 steers obtained from livestock farm A in Gyeongnam were used for a pedigree best linear unbiased prediction (PBLUP) and a genomic best linear unbiased prediction (GBLUP) to estimate and analyze the breeding value and accuracy of the carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS). PBLUP estimated the EBV and accuracy by constructing a numeric relationship matrix (NRM) from the 46 steers and reference population I (545,483 heads) with the pedigree and phenotype. GBLUP estimated genomic EBV (GEBV) and accuracy by constructing a genomic relationship matrix (GRM) from the 46 steers and reference population II (16,972 heads) with the genotype and phenotype. As a result, in the order of CWT, EMA, BFT, and MS, the accuracy levels of PBLUP were 0.531, 0.519, 0.524 and 0.530, while the accuracy outcomes of GBLUP were 0.799, 0.779, 0.768, and 0.810. The accuracy estimated by GBLUP was 50.1 - 53.1% higher than that estimated by PBLUP. GEBV estimated with the genotype is expected to show higher accuracy than the EBV calculated using only the pedigree and is thus expected to be used as basic data for genomic selection in the future.

• Journal of Animal Science and Technology
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• 제55권3호
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• pp.165-171
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• 2013

돼지 유전체 전장의 고밀도 단일염기다형 유전자형을 이용하여 혈연관계행렬을 구성하고 이를 이용하여 유전체 육종가를 추정하였다. 이상치를 제거한 랜드레이스 순종돈 448두의 40,706개 단일염기다형 유전자형 정보를 이용하였으며, G05, GMF, GOF, $GOF^*$ 및 GN의 5가지 방법을 이용하여 유전체 관계행렬을 구성하고 이를 이용하여 유전체 육종가를 추정하였다. GOF 방법에 의하여 계산된 혈연계수가 기존의 혈통정보를 이용한 혈연계수와 가장 작은 편차를 나타내고 평균소수대립유전자빈도를 이용하는 GMF 방법에서는 큰 차이가 나타나 대립유전자빈도 기준이 혈연계수의 평균이동을 유발함을 확인하였으며, $GOF^*$를 제외한 모든 방법에서 정규 분포형태의 멘델리안샘플링이 나타나는 것을 확인하였다. 등지방두께 평균과 90 kg 도달일령에 대한 육종가 추정 모형을 설정하고 유전체 관계행렬을 이용하여 유전모수와 육종가를 추정한 결과 혈통정보를 이용한 육종가와의 상관은 GOF 방법에서 가장 높게 나타났으며, 유전체 관계행렬의 척도(scale)에 베타함수를 이용한 $GOF^*$의 경우 모든 형질에서 유전분산이 크게 추정되어 분모부분을 구성하는 척도는 유전모수 추정치 영향하는 것을 확인하였다. 동일한 표현형 정보량을 이용할 경우 유전체관계행렬을 이용한 육종가 추정의 정확도가 혈통정보를 이용한 육종가보다 높게 나타났으며, 90 kg 도달일령보다는 등지방두께 평균에서 그 차이가 더 크게 나타났다. 집단 내 누적 표현형자료가 부족한 경우, 외래 유전자원이 도입되어 집단 내 혈연관계가 부족할 경우 또는 멘델리안 분포가 전혀 고려되지 않는 어린 동복자손의 육종가를 예측해야 하는 경우에 유전체 정보를 활용하면 유전능력 평가의 정확성을 크게 향상시킬 수 있을 것으로 사료된다.

• Asian-Australasian Journal of Animal Sciences
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• 제26권12호
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• pp.1672-1679
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• 2013

Linkage disequilibrium between markers or genetic variants underlying interesting traits affects many genomic methodologies. In many genomic methodologies, the effective population size ($N_e$) is important to assess the genetic diversity of animal populations. In this study, dairy cattle were genotyped using the Illumina BoviveHD Genotyping BeadChips for over 777,000 SNPs located across all autosomes, mitochondria and sex chromosomes, and 70,000 autosomal SNPs were selected randomly for the final analysis. We characterized more accurate linkage disequilibrium in a sample of 96 dairy cattle producing milk in Korea. Estimated linkage disequilibrium was relatively high between closely linked markers (>0.6 at 10 kb) and decreased with increasing distance. Using formulae that related the expected linkage disequilibrium to $N_e$, and assuming a constant actual population size, $N_e$ was estimated to be approximately 122 in this population. Historical $N_e$, calculated assuming linear population growth, was suggestive of a rapid increase $N_e$ over the past 10 generations, and increased slowly thereafter. Additionally, we corrected the genomic relationship structure per chromosome in calculating $r^2$ and estimated $N_e$. The observed $N_e$ based on $r^2$ corrected by genomics relationship structure can be rationalized using current knowledge of the history of the dairy cattle breeds producing milk in Korea.

• 한국축산식품학회지
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• 제27권3호
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• pp.357-362
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• 2007

Nine brand populations of Hanwoo cattle were characterized using 11 microsatellite DNA markers. The studied populations were: Ansung, Yangpyang, DaeGwanryeng, Palkongsangkangwoo, Hoengseong, Jangsu, Sumjinkang, Hadong, Nam-hae. The observed heterozygosity, expected heterozygosity, and polymorphism information content were calculated. Allele frequencies were calculated and used for the characterization of each brand population and to study their genetic relationships. Genetic distances were estimated using Nei's DA genetic distance and the resultant DA matrix was used in the construction of phylogenetic trees. The NJ tree showed that Ansung and Yangpyang, Sumjinkang and Jangsu, Namhae and Ha-Dong are closely related and are considered to have undergone genetic exchange within the same locale. This study will contribute to the local Hanwoo brand industry.

• 한국수정란이식학회지
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• 제31권3호
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• pp.243-247
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• 2016

Growth traits, such as body weight, directly influence productivity and economic efficiency in the swine industry. In this study, we estimate heritability for body weight traits usinginformation from pedigree and genome-wide single nucleotide polymorphism (SNP) chip data. Four body weight phenotypes were measured in 1,105 $F_2$ progeny from an intercross between Landrace and Jeju native black pigs. All experimental animals were subjected to genotypic analysis using PorcineSNP60K BeadChip platform, and 39,992 autosomal SNP markers filtered by quality control criteria were used to construct genomic relationship matrix for heritability estimation. Restricted maximum likelihood estimates of heritability were obtained using both genomic- and pedigree- relationship matrix in a linear mixed model. The heritability estimates using SNP information were smaller (0.36-0.55) than those which were estimated using pedigree information (0.62-0.97). To investigate effect of common environment, such as maternal effect, on heritability estimation, we included maternal effect as an additional random effect term in the linear mixed model analysis. We detected substantial proportions of phenotypic variance components were explained by maternal effect. And the heritability estimates using both pedigree and SNP information were decreased. Therefore, heritability estimates must be interpreted cautiously when there are obvious common environmental variance components.

• Animal Bioscience
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• 제36권7호
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• pp.1003-1009
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• 2023

Objective: The objective was to compare (pedigree-based) best linear unbiased prediction (BLUP), genomic BLUP (GBLUP), and single-step GBLUP (ssGBLUP) methods for genomic evaluation of growth traits in a Mexican Braunvieh cattle population. Methods: Birth (BW), weaning (WW), and yearling weight (YW) data of a Mexican Braunvieh cattle population were analyzed with BLUP, GBLUP, and ssGBLUP methods. These methods are differentiated by the additive genetic relationship matrix included in the model and the animals under evaluation. The predictive ability of the model was evaluated using random partitions of the data in training and testing sets, consistently predicting about 20% of genotyped animals on all occasions. For each partition, the Pearson correlation coefficient between adjusted phenotypes for fixed effects and non-genetic random effects and the estimated breeding values (EBV) were computed. Results: The random contemporary group (CG) effect explained about 50%, 45%, and 35% of the phenotypic variance in BW, WW, and YW, respectively. For the three methods, the CG effect explained the highest proportion of the phenotypic variances (except for YW-GBLUP). The heritability estimate obtained with GBLUP was the lowest for BW, while the highest heritability was obtained with BLUP. For WW, the highest heritability estimate was obtained with BLUP, the estimates obtained with GBLUP and ssGBLUP were similar. For YW, the heritability estimates obtained with GBLUP and BLUP were similar, and the lowest heritability was obtained with ssGBLUP. Pearson correlation coefficients between adjusted phenotypes for non-genetic effects and EBVs were the highest for BLUP, followed by ssBLUP and GBLUP. Conclusion: The successful implementation of genetic evaluations that include genotyped and non-genotyped animals in our study indicate a promising method for use in genetic improvement programs of Braunvieh cattle. Our findings showed that simultaneous evaluation of genotyped and non-genotyped animals improved prediction accuracy for growth traits even with a limited number of genotyped animals.