Joon Ki Hong

This study estimated genetic parameters and genetic trends for production (days to 105 kg, DAYS105; backfat thickness, BFT) and reproductive traits (total number born, TNB; number born alive, NBA) in Korean Landrace and Yorkshire pigs using data collected from 2000 to 2024. Heritabilities for production traits were moderate to high (0.43-0.52), whereas those for reproductive traits were low (0.08-0.12). A negative genetic correlation (-0.15 to -0.18) was observed between DAYS105 and BFT, suggesting a genetic antagonism where selection for faster growth could lead to increased backfat thickness. Analysis of genetic trends over the 25 year period revealed substantial genetic progress, characterized by a continuous reduction in DAYS105 and an increase in litter size traits (TNB and NBA) for both breeds. The Yorkshire population showed higher accuracy in estimated breeding values compared to Landrace, attributed to its larger reference population size. These results highlight the confirmed effectiveness of the national breeding program and suggest the need for a balanced selection index considering unfavorable correlations, as well as the expansion of reference populations for further genetic improvement in maternal pig lines.

This study investigated the relationships between fatty acid composition and meat quality traits in Hanwoo steers for genetic improvement. A total of 872 Hanwoo steers, raised under standardized feeding conditions, were evaluated at 24 months of age as part of the 2023–2024 national progeny testing program. Key traits analyzed included marbling score, crude fat content, shear force, and tissue texture. Fatty acid profiles comprised saturated fatty acids (myristic, palmitic, and stearic), monounsaturated fatty acids (oleic, palmitoleic, eicosenoic, and vaccenic), and polyunsaturated fatty acids (linoleic, γ-linolenic, linolenic, arachidonic, and docosatetraenoic). Kendall's tau-b correlation and path analysis were conducted to evaluate their relationships with meat quality traits. Higher marbling scores were associated with higher crude fat content and lower shear force and texture scores. Oleic, palmitic, and stearic acids accounted for 45.81±2.73%, 29.31±1.90%, and 11.14±1.50% of total fatty acids, respectively. Oleic acid was correlated with lower shear force and texture values, suggesting a positive role in meat tenderness. Arachidonic acid was negatively associated with marbling score (-0.57) and crude fat (-0.65), but positively associated with shear force (0.49) and texture (0.41), indicating leaner but less tender meat. The direct effect of crude fat on marbling score showed a path coefficient of 0.52. These results indicate that oleic acid may be a key factor for enhancing marbling and tenderness, while arachidonic acid may contribute to balancing fat deposition and texture in Hanwoo beef.

This study investigated copy number variations (CNVs) in 2112 pigs from five populations: Korean Duroc (DUC), Korean Native Pig (KNP), and their crossbred offspring (F₁, F₂, and WRH). CNVs were detected using PennCNV and QuantiSNP, with CNVRuler identifying 698 CNV regions (CNVRs), covering 109 Mb (4.83%) of the porcine genome. Comparison with previous CNV studies on swine revealed CNVR overlap rates ranging from 31.12% (French Yorkshire) to 81.27% (Xiang), and 9.06% newly identified CNVRs. DUC showed the most CNVRs (n = 384), followed by WRH (n = 225). Meanwhile, F₁ and F₂ exhibited far fewer CNVRs (five and seven, respectively). Functional enrichment analysis highlighted various genes overlapping with the CNVRs, including 1236 genes in DUC and 572 genes in WRH, linked to biological processes. The quantitative trait loci (QTLs), overlapping with CNVRs, exhibited particular overlapping with traits such as average daily gain (4.24% of QTLs in DUC, 4.51% of QTLs in WRH). In contrast, KNP, F₁, and F₂ populations exhibited a higher frequency of CNVRs containing QTLs overlapped with drip loss. These findings indicate that WRH may inherit growth traits from DUC. This study provides a better understanding of CNVs in the pigs, which can potentially be used in improving genetic merits of pig populations.

Objective: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP).Methods: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip.Results: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits.Conclusion: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

Average daily gain (ADG) is an important growth trait in the pig industry. The direct genetic effect (DGE) has been studied mainly to assess the association between genetic information and economic traits. The social genetic effect (SGE) has been shown to affect ADG simultaneously with the DGE because of group housing systems. We conducted this study to elucidate the genetic characteristics and relationships of the DGE and SGE of purebred Korean Duroc and crossbred pigs by single-step genomic best linear unbiased prediction and a genome-wide association study. We used the genotype, phenotype, and pedigree data of 1779, 6022, and 7904 animals, respectively. Total heritabilities on ADG were 0.19 ± 0.04 and 0.39 ± 0.08 for purebred and crossbred pigs, respectively. The genetic correlation was the greatest (0.77 ± 0.12) between the SGE of purebred and DGE of crossbred pigs. We found candidate genes located in the quantitative trait loci (QTLs) for the SGE that were associated with behavior and neurodegenerative diseases, and candidate genes in the QTLs for DGE that were related to body mass, size of muscle fiber, and muscle hypertrophy. These results suggest that the genomic selection of purebred animals could be applied for crossbred performance.

본 연구의 목적은 국내 돼지의 다리건강에 대한 유전적 특성을 구명하고 종돈장에서 활용 가능한 형질을 발굴하는 것이다. 검정이 완료된 총 41,918 두(요크셔 29,980 두, 랜드레이스 11,938 두)를 활용하였으며 전체 공시축 중에 요크셔 2,515 두, 랜드레이스 703 두로 총 3,218 두의 개체에 대해 다리형태 외모를 조사하였다. 90kg도달일령(일), 등지방두께(mm), 기립자세(점), 무릎관절(점), 발목(점), 발톱(점) 및 종합외모(점)의 총 7개 형질에 대해 선형-임계(linear-threshold) 모델로 형질별 유전력과 형질 간의 유전상관을 추정하였다. 90kg도달일령(일), 등지방두께(mm) 및 무릎관절은 중도의 유전력(0.2-0.5)으로 추정되었으며, 나머지 형질은 저도의 유전력(0.2 미만)으로 추정되었다. 유전상관에서 종합외모와 발목의 유전상관이 0.89±0.04로 가장 높았다. 다리형태 형질에서 기립자세, 무릎관절 및 발목은 사이의 유전상관은 양의 상관(0.29-0.40)으로 서로 유기적인 관계를 형성하였다. 다리형태 형질 중 무릎관절과 발목 형질의 유전력은 각각 0.23과 0.14로 다른형질보다 더 높은 개량 효과를 기대할 수 있었다. 또한 이 두 형질은 유전상관에서 다른 생산성 형질과 상충성이 낮거나 중립적인 장점이 있었다. 따라서 돼지의 다리건강 개선을 위해 무릎관절과 발목의 외모가 국내개량에서 주요한 지표가 될 수 있다고 사료된다.

Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.

Objective: The objective of this study was to estimate the genetic correlation (rpc) of growth performance between purebred (Duroc and Korean native) and synthetic (WooriHeukDon) pigs using a single-step method.Methods: Phenotypes of 15,902 pigs with genotyped data from 1,792 pigs from a nucleus farm were used for this study. We estimated the rpc of several performance traits between WooriHeukDon and purebred pigs: day of target weight (DAY), backfat thickness (BF), feed conversion rate (FCR), and residual feed intake (RFI). The variances and covariances of the studied traits were estimated by an animal multi-trait model that applied the Bayesian inference.Results: rpc within traits was lower than 0.1 for DAY and BF, but high for FCR and RFI; in particular, rpc for RFI between Duroc and WooriHeukDon pigs was nearly 1. Comparison between different traits revealed that RFI in Duroc pigs was associated with different traits in WooriHeukDon pigs. However, the most of rpc between different traits were estimated with low or with high standard deviation.Conclusion: The results indicated that there were substantial differences in rpc of traits in the synthetic WooriHeukDon pigs, which could be caused by these pigs having a more complex origin than other crossbred pigs. RFI was strongly correlated between Duroc and WooriHeukDon pigs, and these breeds might have similar single nucleotide polymorphism effects that control RFI. RFI is more essential for metabolism than other growth traits and these metabolic characteristics in purebred pigs, such as nutrient utilization, could significantly affect those in synthetic pigs. The findings of this study can be used to elucidate the genetic architecture of crossbred pigs and help develop new breeds with target traits.

Background Woori-Heukdon (KWH) is a Korean synthetic pig breed generated using Chookjin-Duroc (KCD), Chookjin-Chamdon (KCC), and their crossbreds. Currently, there is a severe lack of studies investigating the Korean breed populations including wild boars (KWB) throughout the genome. Objective This study was performed to investigate the genetic characteristics of Korean pig populations at the genome-wide level. Methods Using the SNP dataset derived from genotyped and downloaded datasets using the Illumina PorcineSNP60K BeadChip, we compared the genomes of 532 individuals derived from 23 pig breeds to assess the genetic diversity, inbreeding coefficient, genetic differentiation, and population structure. Results KWB showed the lowest average expected heterozygosity (H_E = 0.1904), while KWH showed the highest genetic diversity (H_E = 0.02859) among Korean populations. We verified that the genetic composition of KWH, showing USD of 74.8% and KCC of 25.2% in ADMIXTURE analysis. In population structure analyses, KCC was consistently shown to be separated from other pig populations. In addition, we observed gene flow from Western pigs to a part of Chinese populations. Conclusion This study showed that Korean native pigs, KCC have genetic differences in comparison with Chinese and Western pigs; despite some historical records and recent genetic studies, we could not find any clear evidence that KCC was significantly influenced by Chinese or Western breeds in this study. We also verified the theoretical genomic composition of KWH at the molecular level in structure analyses. To our knowledge, this is the first genomic study to investigate the genomic characteristics of KWH and KCC.