• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1836-1843
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• 2019

Objective: Social genetic effects (SGE) are an important genetic component for growth, group productivity, and welfare in pigs. The present study was conducted to evaluate i) the feasibility of the single-step genomic best linear unbiased prediction (ssGBLUP) approach with the inclusion of SGE in the model in pigs, and ii) the changes in the contribution of heritable SGE to the phenotypic variance with different scaling ${\omega}$ constants for genomic relationships. Methods: The dataset included performance tested growth rate records (average daily gain) from 13,166 and 21,762 pigs Landrace (LR) and Yorkshire (YS), respectively. A total of 1,041 (LR) and 964 (YS) pigs were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel. With the BLUPF90 software package, genetic parameters were estimated using a modified animal model for competitive traits. Giving a fixed weight to pedigree relationships (${\tau}:1$), several weights (${\omega}_{xx}$, 0.1 to 1.0; with a 0.1 interval) were scaled with the genomic relationship for best model fit with Akaike information criterion (AIC). Results: The genetic variances and total heritability estimates ($T^2$) were mostly higher with ssGBLUP than in the pedigree-based analysis. The model AIC value increased with any level of ${\omega}$ other than 0.6 and 0.5 in LR and YS, respectively, indicating the worse fit of those models. The theoretical accuracies of direct and social breeding value were increased by decreasing ${\omega}$ in both breeds, indicating the better accuracy of ${\omega}_{0.1}$ models. Therefore, the optimal values of ${\omega}$ to minimize AIC and to increase theoretical accuracy were 0.6 in LR and 0.5 in YS. Conclusion: In conclusion, single-step ssGBLUP model fitting SGE showed significant improvement in accuracy compared with the pedigree-based analysis method; therefore, it could be implemented in a pig population for genomic selection based on SGE, especially in South Korean populations, with appropriate further adjustment of tuning parameters for relationship matrices.

• Information Systems Review
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• v.23 no.3
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• pp.97-125
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• 2021

Blockchain is a core technology to solve personal information leakage and data management issues, which are limitations of existing Genomic Sequencing services. Due to continuous cost reduction and deregulation, the market size of Genomic Sequencing has been increasing, also the potential of services is expected to increase when Blockchain's security and connectivity are combined. We created our research model by combining the Technology Acceptance Model (TAM) and the Innovation Resistance Theory also analyzed the factors affecting the acceptance intention and innovation resistance of the Blockchain Based Genomic Sequencing Information Platform. A survey was conducted on 150 potential users of Blockchain and Genomic Sequencing services. The analysis was conducted by setting the four Blockchain variables: Security, transparency, availability, and diversity). Also, we set the Perceived Usefulness, Perceived risk, and Perceived Complexity for Technology Acceptance and Innovation Resistance variables and analyzed the effect of the characteristics of the Blockchain on acceptance intention and innovation resistance through these variables. Through this analysis, key variables that need to be considered important to reduce resistance and increase acceptance intention could be identified. This study presents innovation factors that should be considered in companies preparing a new Blockchain Based Genomic Sequencing Information Platform.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.12
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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.

• Research in Plant Disease
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• v.12 no.1
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• pp.62-64
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• 2006

July in 2005, we collected infected maize plant that showing stripe dwarf disease on maize leaf in Jeonbuk provinces including Gochang-gun and conducted genomic dsRNA extraction and RT-PCR. Genomic dsRNA was extracted directly in infected maize plant and electrophoresis in agarose gel. We confirmed 10 segments of genomic dsRNA. We conducted RT-PCR by genomic dsRNA and specific primer of S7, S8 and S10. As a result, specific band of expected size was confirmed respectively. In the results of dsRNA and RT-PCR analysis, we confirmed Rice black-streaked dwarf fijivirus (RBSDV) from naturally infected maize plant. Occurrence of RBSDV of maize plant was dealt 22 ha's damage in maize field. The occurrence rate was 80% in a lot of places of disease.

• Journal of Animal Reproduction and Biotechnology
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• v.38 no.1
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• pp.32-37
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• 2023

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.

• Animal Bioscience
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• v.37 no.3
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• pp.461-470
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• 2024

Objective: The objective of this study was to investigate the genetic diversity, population structure and whole-genome selection signatures of Luxi cattle to reveal its genomic characteristics in terms of meat and carcass traits, skeletal muscle development, body size, and other traits. Methods: To further analyze the genomic characteristics of Luxi cattle, this study sequenced the whole-genome of 16 individuals from the core conservation farm in Shandong region, and collected 174 published genomes of cattle for conjoint analysis. Furthermore, three different statistics (pi, F_st, and XP-EHH) were used to detect potential positive selection signatures related to selection in Luxi cattle. Moreover, gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were performed to reveal the potential biological function of candidate genes harbored in selected regions. Results: The results showed that Luxi cattle had high genomic diversity and low inbreeding levels. Using three complementary methods (pi, F_st, and XP-EHH) to detect the signatures of selection in the Luxi cattle genome, there were 2,941, 2,221 and 1,304 potentially selected genes identified, respectively. Furthermore, there were 45 genes annotated in common overlapping genomic regions covered 0.723 Mb, including PLAG1 zinc finger (PLAG1), dedicator of cytokinesis 3 (DOCK3), ephrin A2 (EFNA2), DAZ associated protein 1 (DAZAP1), Ral GTPase activating protein catalytic subunit alpha 1 (RALGAPA1), mediator complex subunit 13 (MED13), and decaprenyl diphosphate synthase subunit 2 (PDSS2), most of which were enriched in pathways related to muscle growth and differentiation and immunity. Conclusion: In this study, we provided a series of genes associated with important economic traits were found in positive selection regions, and a scientific basis for the scientific conservation and genetic improvement of Luxi cattle.

• Genomics & Informatics
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• v.7 no.3
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• pp.152-158
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• 2009

Although the genetic basis for bone mineral density (BMD) has been studied by many groups so far, genes responsible for this complex trait has not been completely revealed. In order to localize quantitative trait loci (QTLs) for BMD variation in Asian population, the study was designed using a group of Mongolian population, a genetically closed population with a homogeneous lifestyle. BMD was measured at the left and right wrists and ankles using DEXA in 1,082 participants from 142 families. Genotyping of 13 polymorphic microsatellite markers on chromosome 13 (average spacing 8-9 cM) and two-point and multipoint linkage analysis were performed. In two-point linkage analysis, we identified two markers, D13S175 (6.03 cM) and D13S265 (68.73 cM) that had LOD scores greater than 1 for left ankle (LOD=2.09, LOD=1.49, respectively). We also found a marker D13S175 (6.03 cM) with a high LOD for left wrist (LOD=1.49) and the markers D13S265 (68.73 cM) and D13S217 (17.21 cM) for the right wrist (LOD= 1.82, LOD= 1.62, respectively). Among these significant marker regions, only two regions at 17 cM (13p11) and 65 cM (13q21) for the right wrist overlapped with major QTLs reported in following multipoint linkage analysis (LOD= 1.7549, LOD=1.4462, respectively). This study provides the possible evidence of the presence of QTLs affecting right wrist BMD in Mongolian populations on 13p11 and 13q21. Modest evidence was also found for genes affecting left ankle and left wrist BMD on 13p13.

• The Korea Journal of Herbology
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• v.21 no.3
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• pp.91-95
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• 2006

Objectives : This study was performed to determine if an antler could be identified as one of the Cervus species by phylogenetic analysis, which was used to assess genetic authentication. Methods : The DNAs of an antler were extracted, amplified by PCR, and sequenced. The DNAs of an antler were identified by Phylogenetic analysis. Phylogenetic analysis was made using MEGA software (Molecular Evolutionary Genetics Analysis, 3.1) Results : By phylogenetic analysis an antler was identified as Cervus elaphus nelsoni not as Cervus elaphus sibericus. This work showed that authentication can efficiently be performed by phylogenetic analysis. Conclusion : These results suggest that phylogenetic analysis might be able to provide the authentication of Cervus species.

• Genomics & Informatics
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• v.17 no.4
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• pp.41.1-41.12
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• 2019

Survival analysis mainly deals with the time to event, including death, onset of disease, and bankruptcy. The common characteristic of survival analysis is that it contains "censored" data, in which the time to event cannot be completely observed, but instead represents the lower bound of the time to event. Only the occurrence of either time to event or censoring time is observed. Many traditional statistical methods have been effectively used for analyzing survival data with censored observations. However, with the development of high-throughput technologies for producing "omics" data, more advanced statistical methods, such as regularization, should be required to construct the predictive survival model with high-dimensional genomic data. Furthermore, machine learning approaches have been adapted for survival analysis, to fit nonlinear and complex interaction effects between predictors, and achieve more accurate prediction of individual survival probability. Presently, since most clinicians and medical researchers can easily assess statistical programs for analyzing survival data, a review article is helpful for understanding statistical methods used in survival analysis. We review traditional survival methods and regularization methods, with various penalty functions, for the analysis of high-dimensional genomics, and describe machine learning techniques that have been adapted to survival analysis.

• Korean Journal of Agricultural Science
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• v.44 no.4
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• pp.495-503
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• 2017

Genotyping-by-sequencing (GBS) is an outstanding technology for genotyping and single nucleotide polymorphism (SNP) discovery compared to next generation sequencing (NGS) because it can save time when analyzing large-scale samples and carries a low cost per sample. Recently, studies using GBS have been conducted on major crops and, to a greater extent, on fruit crops. However, many researchers have some problems due to low GBS efficiency resulting from low quality GBS libraries. To overcome this limitation, we developed an efficient GBS library construction method that regulates important conditions such as restriction enzymes (RE) digestion and a PCR procedure for grapevine. For RE digestion, DNA samples are digested with ApeKI (3.6U) at $75^{\circ}C$ for 5 hours and adapters are ligated to the ends of gDNA products. To produce suitable PCR fragments for sequencing, we modified the PCR amplification conditions; temperature cycling consisted of $72^{\circ}C$ (5 min), $98^{\circ}C$ (30 s), followed by 16 cycles of $98^{\circ}C$ (30 s), $65^{\circ}C$ (30 s), $72^{\circ}C$ (20 s) with a final extension step. As a result, we had obtained optimal library construct sizes (200 to 400 bp) for GBS analysis. Furthermore, it not only increased the mapping efficiency by approximately 10.17% compared to the previous method, but also produced mapped reads which were distributed equally on the19 chromosomes in the grape genome. Therefore, we suggest that this system can be used for various fruit crops and is expected to increase the efficiency of various genomic analysis performed.