Background: Recently, the single-step genomic best linear unbiased prediction (ssGBLUP) method, which incorporates not only genomic information but also phenotypic information of pedigree, is under study. In this study, we performed a ssGBLUP analysis on a commercial Hanwoo population using phenotypic, genotypic, and pedigree data. Methods: The test population comprised Hanwoo 1,740 heads raised in four regions of Korea, while the reference population used Hanwoo 18,499 heads raised across the country and two-generation pedigree data. Analysis was performed using genotype data generated by the Hanwoo 50 K SNP beadchip. Results: The mean Genome estimated breeding values (GEBVs) estimated using the ssGBLUP methods for carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS) were 7.348, 1.515, -0.355, and 0.040, respectively, while the accuracy of each trait was 0.749, 0.733, 0.769, and 0.768, respectively. When the correlation analysis between the GEBVs as a result of this study and the actual slaughter performance was confirmed, CWT, EMA, BFT, and MS were reported to be 0.519, 0.435, 0.444, and 0.543, respectively. Conclusions: Our results suggest that the ssGBLUP method enables a more accurate evaluation because it conducts a genetic evaluation of an individual using not only genotype information but also phenotypic information of the pedigree. Individual evaluation using the ssGBLUP method is considered effective for enhancing the genetic ability of farms and enabling accurate and rapid improvements. It is considered that if more pedigree information of reference population is collected for analysis, genetic ability can be evaluated more accurately.

This study has evaluated the genomic estimated breeding value (GEBV) of the commercial Hanwoo population using the genomic best linear unbiased prediction (GBLUP) method and genomic information. Furthermore, it analyzed the accuracy and realized accuracy of the GEBV. 1,740 heads of the Hanwoo population which were analyzed using a single nucleotide polymorphism (SNP) Chip has selected as the test population. For carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS), the mean GEBVs estimated using the GBLUP method were 3.819, 0.740, -0.248, and 0.041, respectively and the accuracy of each trait was 0.743, 0.728, 0.737, and 0.765, respectively. The accuracy of the breeding value was affected by heritability. The accuracy was estimated to be low in EMA with low heritability and high in MS with high heritability. Realized accuracy values of 0.522, 0.404, 0.444, and 0.539 for CWT, EMA, BFT, and MS, respectively, showing the same pattern as the accuracy value. The results of this study suggest that the breeding value of each individual can be estimated with higher accuracy by estimating the GEBV using the genomic information of 18,499 reference populations. If this method is used and applied to individual selection in a commercial Hanwoo population, more precise and economical individual selection is possible. In addition, continuous verification of the GBLUP model and establishment of a reference population suitable for commercial Hanwoo populations in Korea will enable a more accurate evaluation of individuals.

본 연구에서는 한국에서 개발한 23개의 양송이 품종과 42개의 도입품종의 유전적 다양성과 집단 구조를 SSR 마커를 이용하여 분석하였다. 양송이 품종의 NA는 약 13, HO는 약 0.59, HE는 약 0.74, PIC값은 약 0.71 이었다. 양송이 품종은 군집분석에 의하여 3개의 Group으로 구분되 었고 다양한 국가의 품종으로 구성된 Group2의 다양성이 높았으며, 구조분석에 의하여 2개의 subpopulation으로 구분되었고, 품종의 수가 많은 Pop2의 다양성이 높았다. 한국의 양송이 품종들은 주로 Group 3에 분포하고, subpopulation 간 분포에는 큰 차이를 보이지 않았다. 본 연구의 결과는 양송이의 육종소재의 개발, 다양성 확보 등과 같은 품종의 개발과정에 이용될 수 있을 것이다.

본 연구는 한우의 경제형질 관련 유전적 표지인자(DNA marker) 개발을 목적으로 한우 도체형질과의 기능적 후보유전자로부터 검출된 10개의 유전마커(Single Nucleotide Polymorphism; SNP)에 대해서, 환경효과가 다양하게 포함되어 있는 상용축을 대상으로 마커효과를 검정하였다. 그 결과, 한우 후대 검정우에서 통계적 유의성이 인정되었던 다수의 SNP 좌위중 IP3R1 유전자에서 검출된 DNA 마커만 상용축의 근내지방도와 통계적 유의차를 보였으며, 이는 각 좌위마다의 환경 효과와의 보다 더 통계분석이 요구되는 것이며, 향후 근내지방도와 연관된 다수의 마커와 함께 혼합모델을 통하여 개체의 표현형 예측등에 활용이 가능할 것으로 사료된다.