• Microbiology and Biotechnology Letters
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• v.32 no.4
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• pp.356-361
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• 2004

The ethionine resisconferring gene (ERCI) was constitutively expressed under the control of the alcohol dehydrogenase gene promoter (ADClp) and introduced into the chromosomes of an industrial polyploid strain of Saccharocerevisiae by using the 8-sequences of the Tyl retrotransposon as the recombination site. 8-Integrative cassette devoid of bacterial DNA sequences containing the ampicillin resistance gene was constructed that had the aureobasidin A resistance gene (AURl-C) as the selection marker and ERCl gene. The ERCl gene was also employed as the selection marker in the 8-integrative cassette lacking the A URl-C gene. Industrial Saccerevisiae transformed with these integrative cassettes exhibited strong resistance to DL-ethioncompared with nontransformants.

• Journal of Plant Biotechnology
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• v.3 no.3
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• pp.113-121
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• 2001

The use of a marker gene in a transformation process aims to give a selective advantage to the transformed cells, allowing them to grow faster and better, and to kill the non-transformed cells. In general, the selective gene is introduced into plant genome along with the genes of interest. In some cases, the marker gene can be the gene of interest that will confer an agronomic characteristic, such as herbicide resistance. In this review we list and discuss the use of the most common selective marker genes on plant transformation and the effects of their respective selective agents. These genes could be divided in categories according their mode of action: genes that confer resistance to antibiotics and herbicides; and genes for positive selection. The contention of the marker gene flow through chloroplast transformation is further discussed. Moreover, strategies to recover marker-free transgenic plants, involving multi-auto-transformation (MAT), co-transformation, site specific recombination and intragenomic relocation of transgenes through transposable elements, are also reviewed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.83-92
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• 2004

Gene expression profile is numerical data of gene expression level from organism measured on the microarray. Generally, each specific tissue indicates different expression levels in related genes, so that we can classify cancer with gene expression profile. Because not all the genes are related to classification, it is needed to select related genes that is called feature selection. This paper proposes a new gene selection method using forward selection method in regression analysis. This method reduces redundant information in the selected genes to have more efficient classification. We used k-nearest neighbor as a classifier and tested with colon cancer dataset. The results are compared with Pearson's coefficient and Spearman's coefficient methods and the proposed method showed better performance. It showed 90.3% accuracy in classification. The method also successfully applied to lymphoma cancer dataset.

• Biotechnology and Bioprocess Engineering:BBE
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• v.5 no.1
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• pp.1-6
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• 2000

For the rapid selection of higher recombinant hirudin producing strain in a methylotrophic yeast Hansenula polymorpha, a multiple gene integration and dose-dependent selection vector, based on a telomere-associated ARS and a bacterial aminoglycoside 3-phosphotransferase (aph) gene, was adopted. Two hirudin expression cassettes (HV1 and HV2) were constructed using the MOX promoter of H. polymorpha and the mating factor $\alpha$ secretion signal of S. cerevisiae. Multiple integrants of a transforming vector containing hirudin expression cassettes were easily selected by using an antibiotic, G418. Hirudin expression level and integrated plasmid copy number of the tested transformants increased with increasing the concentration of G418 used for selection. The expression level of HV1 was consistently higher than that of HV2 under the similar conditions, suggesting that the gene context might be quite important for the high-level gene expression in H. polymorpha. The highest hirudin producing strain selected in this study produced over 96 mg/L of biologically active hirudin in a 500-mL flask and 165 mg/L in a 5-L fermentor.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.259-261
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• 2005

수천개의 Gene Expression Measurement를 생성해 내는 DNA Microarray 연구는 조직과 세포의 표본으로부터 진단에 유용한 Gene Expression 정보를 모으게 된다. 이런 종류의 Data를 분석하기 위하여 SVM(Support Vector Machine)을 사용한 새로운 방법이 연구되어왔다. 본 논문에서는 Gene Expression Data에 대한 고유벡터(Eigen Vector)를 이용하여 SVM의 성능을 향상시키고 질병진단에 유용한 Gene을 찾아 내는 알고리즘을 기술한다. 고유벡터를 통하여 Gene을 선택적으로 SVM Learning에 참가 시키고 분류의 결과를 통하여 추가된 Gene이 질병 진단에 미치는 영향력을 알아냄으로써 질병에 대한 Gene 역할을 파악 하는데 활용할 수 있다.

• Reproductive and Developmental Biology
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• v.38 no.2
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• pp.71-77
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• 2014

The specific genetic modification in porcine somatic cells by gene targeting has been very difficult because of low efficiency of homologous recombination. To improve gene targeting, we designed three kinds of knock-out vectors with ${\alpha}1,3$-galactosyltransferase gene (${\alpha}1,3$-GT gene), DT-A/pGT5'/neo/pGT3', DT-A/NLS/pGT5'/neo/pGT3' and pGT5'/neo/ pGT3'/NLS. The knock-out vectors consisted of a 4.8-kb fragment as the 5' recombination arm (pGT5') and a 1.9-kb fragment as the 3' recombination arm (pGT3'). We used the neomycin resistance gene (neo) as a positive selectable marker and the diphtheria toxin A (DT-A) gene as a negative selectable marker. These vectors have a neo gene insertion in exon 9 for inactivation of ${\alpha}1,3$-GT locus. DT-A/pGT5'/neo/pGT3' vector contain only positive-negative selection marker with conventional targeting vector. DT-A/NLS/pGT5'/neo/pGT3' vector contain positive-negative selection marker and NLS sequences in upstream of 5' recombination arm which enhances nuclear transport of foreign DNA into bovine somatic cells. pGT5'/neo/pGT3'/NLS vector contain only positive selection marker and NLS sequence in downstream of 3' recombination arm, not contain negative selectable marker. For transfection, linearzed vectors were introduced into porcine ear fibroblasts by electroporation. After 48 hours, the transfected cells were selected with $300{\mu}g/ml$ G418 during 12 day. The G418-resistant colonies were picked, of which 5 colonies were positive for ${\alpha}1,3$-GT gene disruption in 3' PCR and southern blot screening. Three knock-out somatic cells were obtained from DT-A/NLS/ pGT5'/neo/pGT3' knock-out vector. Thus, these data indicate that gene targeting vector using nuclear localization signal and negative selection marker improve targeting efficiency in porcine somatic cells.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.234-234
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• 2022

Gene-editing is currently one of the most popular technologies in recent years. Development of the new crop using the gene editing have advantage of improved accuracy and efficiency compared with conventional breeding. Soybean (Glycine max L.) is one of the most important crops worldwide used as food and forage. We tried to establish a system for breeding improvement of soybean through gene-editing technology. For the gene-editing system of soybean, i) selection of efficiency gRNA of targeted gene, ii) efficient genetic transformation of the selected gRNA, iii) selection of trans-clean mutant is essential. First of all, we investigated the selection conditions of gRNA with high editing efficiency of targeted gene using isolated protoplast of soybean. Furthermore, we performed the Agrobacterium-mediated genetic transformation of various soybean cultivars. We identified the tissue culture ability in 23 soybean cultivars for genetic transformation of soybean. The six cultivars with high tissue culture ability were selected and confirmed the transgenic plants in four cultivars. Finally, we established a speed-breeding system as a powerful tool for the fast selection of trans-clean mutants from transgenic plants. Our laboratory will provide the valuable system for improvement of soybean by the gene-editing technology.

• Molecules and Cells
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• v.21 no.3
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• pp.376-380
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• 2006

Gene expression is regulated in large part at the level of transcription under the control of sequence-specific transcriptional regulatory proteins. Therefore, the ability to affect gene expression at will using sequencespecific artificial transcription factors would provide researchers with a powerful tool for biotechnology research and drug discovery. Previously, we isolated 56 novel sequence-specific DNA-binding domains from the human genome by in vivo selection. We hypothesized that these domains might be more useful for regulating gene expression in higher eukaryotic cells than those selected in vitro using phage display. However, an unpredictable factor, termed the "context effect", is associated with the construction of novel zinc finger transcription factors--- DNA-binding proteins that bind specifically to 9-base pair target sequences. In this study, we directly selected active artificial zinc finger proteins from a zinc finger protein library. Direct in vivo selection of constituents of a zinc finger protein library may be an efficient method for isolating multi-finger DNA binding proteins while avoiding the context effect.

• Journal of Crop Science and Biotechnology
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• v.11 no.4
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• pp.233-236
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• 2008

A positive selectable marker system was adapted for transformation of mature embryo-derived calli of Indica rice (Oryza sativa L.) utilizing the PMI gene encoding for phosphomannose-isomerase that converts mannose-6-phosphate to fructose-6-phosphate. The transformed cells grew on medium supplemented with 3% mannose as carbon source and calli were selected on media containing various concentrations of mannose. Molecular analyses showed that the transformed plants contained the PMI gene. The results indicate that the mannose selection system can be used for Agrobacterium-mediated transformation of mature embryo in rice to substitute the use of conventional selectable markers in genetic transformation.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.598-600
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• 2001

DNA chip technology enables us to monitor thousands of gene expressions per sample simultaneously. Typically, DNA microarray data has at least several thousands of variables (genes) wish relatively smal1 number of samples. Thus feature (gene) selection by dimensionality reduction is necessary for efficient data analysis. In this paper we employ the partial least squares (PLS) method for gene selection and the principal component analysis (PCA) method for classification. The useful behavior of the PLS is verified by computer simulations.