• Proceedings of the KSAR Conference
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• 2003.06a
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• pp.55-55
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• 2003

The random insertion of useful gene in genome has been a common method to produce transgenic animals. This method is inefficient for induction of high levels gene expression in transgenic animals. To improve this limit, we tried to develop the system which target the gene at the specific genomic region. Thus, in our experiment, the vector system to target the human thrombopoietin (TPO) gene was developed. Targeting vector including TPO, neo and DT genes was transfrcted into bovine embryonic fibroblasts (bEF) or bovine ear skin fibroblasts (bESF). First of all, we determined concentration of the geneticin (G418) for selection of transfected cell lines. Our results showed that 1200 and 900 $\mu\textrm{g}$/ml of G418 were the most proper for selection of transfscted bEF and bESF cells. In this study, lipofectamine was used as a transfection reagent. Thus, the proper ratio of DNA:lipofectamine for transfection was also required to elevate targeting efficiency in primary mammalian cells. Our result indicates that the most proper ratios of DNA:lipofectamine were 4:2 and 1:2 in bEF and bESF cells. According to the optimized these conditions, single colonies were picked following transfection and were analyzed by PCR. More than 90% of the single colonies have TPO gene. However, there were no colonies with targeted TPO at the specific genomic region. Therefore, further experiments to select the specifically targeted colonies and to find more efficient methods such as reducing selection time and shortening a size of TPO gene are required.

• BMB Reports
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• v.51 no.1
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• pp.1-2
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• 2018

Positive selection on a new beneficial mutation generates a characteristic pattern of DNA sequence polymorphism when it reaches an intermediate allele frequency. On genome sequences of African Drosophila melanogaster, we detected such signatures of selection at 37 candidate loci and identified "sweeping haplotypes (SHs)" that are increasing or have increased rapidly in frequency due to hitchhiking. Based on geographic distribution of SH frequencies, we could infer whether selective sweeps occurred starting from de novo beneficial mutants under simple constant selective pressure. Single SHs were identified at more than half of loci. However, at many other loci, we observed multiple independent SHs, implying soft selective sweeps due to a high beneficial mutation rate or parallel evolution across space. Interestingly, SH frequencies were intermediate across multiple populations at about a quarter of the loci despite relatively low migration rates inferred between African populations. This invokes a certain form of frequency-dependent selection such as heterozygote advantage. At one locus, we observed a complex pattern of multiple independent that was compatible with recurrent frequency-dependent positive selection on new variants. In conclusion, genomic patterns of positive selection are very diverse, with equal contributions of hard and soft sweeps and a surprisingly large proportion of frequency-dependent selection in D. melanogaster populations.

• Korean Journal of Plant Tissue Culture
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• v.25 no.1
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• pp.45-50
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• 1998

Hypocotyl explants of flowering cabbage were precultured on MS medium without kanamycin and then cocultured with Agrobacterium tumefaciens LBA4404;;pGA875 harboring insect resistantce proteinase inhibitor II(PI-II) gene in MS liquid medium adjusted pH 5.5 for 72hr. These explants were transferred to MS medium containing 20 mg/L kanamycin, 500 mg/L carbenicillin, and 1 mg/L BA. The explants were subsequently subcultured every 2 weeks. After 4 weeks of subculture, kanamycin-resistant shoots were obtained from selection medium. Leaves of putative transformants survived on MS selection medium containing 30 mg/L kanamycin. Incoporation of the PI-II gene into flowering cabbage was confirmed by PCR analysis of genomic DNA. Southern blot analysis showed that ECL-labeled probe for PI-II gene was hybridized to the expected amplified genomic DNA fragment of about 500 by from transgenic flowering cabbage.

• Animal Bioscience
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• v.37 no.5
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• pp.807-816
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• 2024

Objective: This study aims to identify the significant regions and candidate genes of growth-related traits (adjusted backfat thickness [ABF], average daily gain [ADG], and days to 90 kg [DAYS90]) in Korean commercial GGP pig (Duroc, Landrace, and Yorkshire) populations. Methods: A genome-wide association study (GWAS) was performed using single-nucleotide polymorphism (SNP) markers for imputation to Illumina PorcineSNP60. The BayesB method was applied to calculate thresholds for the significance of SNP markers. The identified windows were considered significant if they explained ≥1% genetic variance. Results: A total of 28 window regions were related to genetic growth effects. Bayesian GWAS revealed 28 significant genetic regions including 52 informative SNPs associated with growth traits (ABF, ADG, DAYS90) in Duroc, Landrace, and Yorkshire pigs, with genetic variance ranging from 1.00% to 5.46%. Additionally, 14 candidate genes with previous functional validation were identified for these traits. Conclusion: The identified SNPs within these regions hold potential value for future marker-assisted or genomic selection in pig breeding programs. Consequently, they contribute to an improved understanding of genetic architecture and our ability to genetically enhance pigs. SNPs within the identified regions could prove valuable for future marker-assisted or genomic selection in pig breeding programs.

• Journal of Life Science
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• v.32 no.4
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• pp.279-284
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• 2022

This study was conducted to establish a genetic evaluation system applicable to general farms for improving cows raised on farms. The analysis used Best Linear Unbiased Prediction (BLUP) and Genomic Best Linear Unbiased Prediction (GBLUP) for 619 cows raised in Gyeonggi-do Province and compared and analyzed the accuracy of the estimated breeding value according to four traits (carcass weight, loineye muscle area, back fat thickness, and marbling). In the case of the GBLUP method, the size of the reference population was divided into different four groups and analyzed. The analysis results confirmed that the accuracy of the breeding value of each trait increased as the size of the GBLUP reference population increased. Comparing the accuracy of the breeding values estimated using the BLUP and GBLUP methods, it was confirmed that when the breeding values were estimated using the GBLUP method, they increased by 0.10, 0.09, 0.09, and 0.11 for carcass weight, eye muscle area, back fat thickness, and marbling scores, respectively. Applying the GBLUP method to the evaluation and selection of cows can enable precise and accurate individual selection, while increasing the size of the reference population can make even more accurate individual selection possible, thus increasing selection efficiency.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1117-1128
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• 2016

In genetic association studies with high-dimensional genomic data, regularization procedures based on penalized likelihood are often applied to identify genes or genetic regions associated with diseases or traits. A network-based regularization procedure can utilize biological network information (such as genetic pathways and signaling pathways in genetic association studies) with an outstanding selection performance over other regularization procedures such as lasso and elastic-net. However, network-based regularization has a limitation because cannot be applied to high-dimension genomic data with a group structure. In this article, we propose to combine data dimension reduction techniques such as principal component analysis and a partial least square into network-based regularization for the analysis of high-dimensional genomic data with a group structure. The selection performance of the proposed method was evaluated by extensive simulation studies. The proposed method was also applied to real DNA methylation data generated from Illumina Innium HumanMethylation27K BeadChip, where methylation beta values of around 20,000 CpG sites over 12,770 genes were compared between 123 ovarian cancer patients and 152 healthy controls. This analysis was also able to indicate a few cancer-related genes.

• IMMUNE NETWORK
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• v.2 no.4
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• pp.233-241
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• 2002

Background: Monoclonal antibodies (mAb) of rodent origin are produced with ease by hybridoma fusion technique, and have been successfully used as therapeutic reagents for humans after humanization by genetic engineering. However, utilization of these antibodies for therapeutic purpose has been limited by the fact that they act as immunogens in human body causing undesired side effects. So far, there have been several attempts to produce human mAbs for effective in vivo diagnostic or therapeutic reagents including the use of humanized xenomouse that is generated by mating knockout mice which lost Ig heavy and light chain genes by homologous recombination and transgenic mice having both human Ig heavy and light gene loci in their genome. Methods: Genomic DNA fragments of mouse Ig heavy and light chain were obtained from a mouse brain ${\lambda}$ genomic library by PCR screening and cloned into a targeting vector with ultimate goal of generating Ig knockout mouse. Results: Through PCR screening of the genomic library, three heavy chain and three light chain Ig gene fragments were identified, and restriction map of one of the heavy chain gene fragments was determined. Then heavy chain Ig gene fragments were subcloned into a targeting vector. The resulting construct was introduced into embryonic stem cells. Antibiotic selection of transfected cells is under the progress. Conclusion: Generation of xenomouse is particularly important in medical biotechnology. However, this goal is not easily achieved due to the technical difficulties as well as huge financial expenses. Although we are in the early stage of a long-term project, our results, at least, partially contribute the successful generation of humanized xenomouse in Korea.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

• Journal of Aquaculture
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• v.18 no.2
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• pp.130-132
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• 2005

Genomics research has two ultimate applied goals: to Isolate and clone genes of economic importance for bio-technology and gene-assisted selection (GAS), and to locate and use markers for marker-assisted selection (MAS) in selective breeding programs. To this end, we have identified linked markers for feed conversion efficiency growth rate, and disease resistance to enteric septicemia of catfish (ESC). Three microsatellite markers Ip266, Ip384, and Ip607 were identified to be linked to feed conversion efficiency. Similarly one marker each was identified to be linked to growth rate (Ip607) and disease resistance to ESC (Ip477). Ip607 marker linked to both growth rate and feed conversion efficiency, indicating that the QTL for both growth rate and feed conversion efficiency may either be the same or located in the same chromosomal region in the catfish genome. On phenotypic evaluation, certain traits such as growth rate can be accurately evaluated by body weight evaluation while other traits such as disease resistance can be quite complex. The linked DNA markers will be highly useful for MAS programs and for directing further efforts of genomic mapping for important quantitative traits.

• Journal of Animal Science and Technology
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• v.53 no.1
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• pp.1-6
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• 2011

This simulation study was performed to investigate the accuracy of the estimated breeding value by using genomic information (GEBV) by way of Bayesian framework. Genomic information by way of single nucleotide polymorphism (SNP) from a chromosome with length of 100cM were simulated with different marker distance (0.1cM, 0.5cM), heritabilities (0.1, 0.5) and half sibs families (20 heads, 4 heads). For generating the simulated population in which animals were inferred to genomic polymorphism, we assumed that the number of quantitative trait loci (QTL) were equal with the number of no effect markers. The positions of markers and QTLs were located with even and scatter distances, respectively. The accuracies of estimated breeding values by way of indicating correlations between true and estimated breeding values were compared on several cases of marker distances, heritabilities and family sizes. The accuracies of breeding values on animals only having genomic information were 0.87 and 0.81 in marker distances of 0.1cM and 0.5cM, respectively. These accuracies were shown to be influenced by heritabilities (0.87 at $h^2$ =0.10, 0.94 at $h^2$ =0.50). According to half sibs' family size, these accuracies were 0.87 and 0.84 in family size of 20 and 4, respectively. As half sibs family size is high, accuracy of breeding appeared high. Based on the results of this study it is concluded that the amount of marker information, heritability and family size would influence the accuracy of the estimated breeding values in genomic selection methodology for animal breeding.