• Journal of Physiology & Pathology in Korean Medicine
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• v.24 no.3
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• pp.504-511
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• 2010

Diabetes is a disease that contains a high concentration of glucose in blood and due to defects in either insulin secretion or insulin action. Although the distinctive causes and factors of diabetes have not been clarified, the genetic factors are suggested as a main susceptibility until now. SNP (Single Nucleotide Polymorphism), as the most common genetic variation, has an influence on personal susceptibility for diseases. A nonsynonymous SNP, which changes the amino acid of the protein and its function, is especially important. Therefore, this study hypothesized that there are associations between specific SNPs of the targeted genes. Transcription factor 7-like 2 (TCF7L2) and fat mass and obesity associated (FTO) genes were selected as target genes from the results of genome-wide association and other related research studies. Second, four nonsynonymous SNPs (three in TCF7L2 and one in FTO gene) were selected as target SNPs by using public database of NCBI (National Center for Biotechnology Information). The recruited personnel was classified into three subgroups of diabetes, impaired fasting glucose (IFG) and normal groups. The individual genotypes of each group were analyzed by resequencing. None of genetic variations at four targeted SNP sites was revealed in all samples of this study. However, this study found two new SNPs that were not reported in TCF7L2 gene. One is synonymous SNP, which is heterozygous of C/T and no amino acid change of asparagine/asparagines, was located at c1641 and found in one normal person. Another is nonsynonymous SNP, which is heterozygous of G/A, was located at c1501 and found in two samples. This new discovered nonsynonymous SNP induce the amino acid change from alanine to threonine. Moreover, this new nonsynonymous SNP was found among two persons, one of whom was a diabetes patient and the other one was a person at boundary between IFG and normal, suggesting that this variant might be associated with IFG or diabetes. Even if there is a limitation of sample number for statistical power, this study has an importance due to the discovery of new SNPs. In the future study, a large sample number of diabetes cohort will be needed to investigate the frequency and association with new discovered SNP.

• Korean Journal of Plant Resources
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• v.32 no.4
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• pp.303-311
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• 2019

Various colors of fruit skin and flesh are the most popular commercial criteria for peach classification. In order to breed new red-fleshed peach cultivar, many cross seedlings and generations should be maintained. Therefore it is necessary to develop early selection markers to screen seedlings with target traits to increase breeding efficiency. For the comparison of transcription profiles in peach cultivars differing in flesh color expression, two cDNA libraries were constructed. Differences in gene expression between red-fleshed peach cultivar, 'Josanghyeoldo' and white-fleshed peach cultivar, 'Mibaekdo' were analyzed by next-generation sequencing (NGS). Expressed sequence tag (EST) of clones from the two cultivars were selected for nucleotide sequence determination and homology searches. Putative single nucleotide polymorphisms (SNP) were screened from peach EST contigs by high resolution melting (HRM) analysis displayed specific difference between 8 red-fleshed peach cultivars and 24 white-fleshed peach cultivars. All 72 pairs of SNPs were discriminated and the HRM profiles of amplicons were established. In the study reported here, the development of SNP markers for distinguishing between red and white fleshed peach cultivars by HRM analysis offers the opportunity to use DNA markers. This SNP marker could be useful for peach marker assisted breeding and provide a good reference for relevant research on molecular mechanisms of color variation in peach cultivars.

• Genomics & Informatics
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• v.6 no.3
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• pp.153-156
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• 2008

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.

• Genomics & Informatics
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• v.6 no.2
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• pp.91-94
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• 2008

Single nucleotide polymorphisms (SNPs) are the most abundant form of human genetic variation and are a resource for mapping complex genetic traits. A genome is covered by millions of these markers, and researchers are able to compare which SNPs predominate in people who have a certain disease. The International HapMap Project, launched in October, 2002, motivated us to start the Korean HapMap Project in order to support Korean HapMap infrastructure development and to accelerate the finding of genes that affect health, disease, and individual responses to medications and environmental factors. A Korean SNP and haplotype database system was developed through the Korean HapMap Project to provide Korean researchers with useful data-mining information about disease-associated biomarkers for studies on complex diseases, such as diabetes, cancer, and stroke. Also, we have developed a series of software programs for association studies as well as the comparison and analysis of Korean HapMap data with other populations, such as European, Chinese, Japanese, and African populations. The developed software includes HapMapSNPAnalyzer, SNPflank, HWE Test, FESD, D2GSNP, SNP@Domain, KMSD, KFOD, KFRG, and SNP@WEB. We developed a disease-related SNP retrieval system, in which OMIM, GeneCards, and MeSH information were integrated and analyzed for medical research scientists. The kHapMap Browser system that we developed and integrated provides haplotype retrieval and comparative study tools of human ethnicities for comprehensive disease association studies (http://www.khapmap.org). It is expected that researchers may be able to retrieve useful information from the kHapMap Browser to find useful biomarkers and genes in complex disease association studies and use these biomarkers and genes to study and develop new drugs for personalized medicine.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.508-518
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• 2019

Objective: This research aimed to determine biological pathways and protein-protein interaction (PPI) networks for 305-d milk yield (MY), 305-d fat yield (FY), and age at first calving (AFC) in the Thai multibreed dairy population. Methods: Genotypic information contained 75,776 imputed and actual single nucleotide polymorphisms (SNP) from 2,661 animals. Single-step genomic best linear unbiased predictions were utilized to estimate SNP genetic variances for MY, FY, and AFC. Fixed effects included herd-year-season, breed regression and heterosis regression effects. Random effects were animal additive genetic and residual. Individual SNP explaining at least 0.001% of the genetic variance for each trait were used to identify nearby genes in the National Center for Biotechnology Information database. Pathway enrichment analysis was performed. The PPI of genes were identified and visualized of the PPI network. Results: Identified genes were involved in 16 enriched pathways related to MY, FY, and AFC. Most genes had two or more connections with other genes in the PPI network. Genes associated with MY, FY, and AFC based on the biological pathways and PPI were primarily involved in cellular processes. The percent of the genetic variance explained by genes in enriched pathways (303) was 2.63% for MY, 2.59% for FY, and 2.49% for AFC. Genes in the PPI network (265) explained 2.28% of the genetic variance for MY, 2.26% for FY, and 2.12% for AFC. Conclusion: These sets of SNP associated with genes in the set enriched pathways and the PPI network could be used as genomic selection targets in the Thai multibreed dairy population. This study should be continued both in this and other populations subject to a variety of environmental conditions because predicted SNP values will likely differ across populations subject to different environmental conditions and changes over time.

• Journal of Plant Biotechnology
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• v.5 no.4
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• pp.193-195
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• 2003

A major goal of agricultural biotechnology is the discovery of genes or genetic loci which are associated with characteristics beneficial to crop production. This knowledge of genetic loci may then be applied to improve crop breeding. Agriculturally important genes may also benefit crop production through transgenic technologies. Recent years have seen an application of high throughput technologies to agricultural biotechnology leading to the production of large amounts of genomic data. The challenge today is the effective structuring of this data to permit researchers to search, filter and importantly, make robust associations within a wide variety of datasets. At the Plant Biotechnology Centre, Primary Industries Research Victoria in Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data to aid its application to agricultural biotechnology resear-ch. These tools include a sequence database, ASTRA, for the processing and annotation of expressed sequence tag data. Tools have also been developed for the discovery of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) molecular markers from large sequence datasets. Application of these tools to Brassica research has assisted in the production of genetic and comparative physical maps as well as candidate gene discovery for a range of agronomically important traits.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.12
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• pp.1689-1695
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• 2008

Leptin, the hormone product of the obese gene, is secreted predominately from white adipose tissue and regulates feed intake, energy metabolism and body composition. It has been considered a candidate gene for performance, carcass and meat quality traits in beef cattle. The objective of this study was to identify SNPs in the promoter region of the leptin gene and to evaluate the possible association of the SNP genotypes with carcass and meat quality traits in Korean cattle. We identified a total of 25 SNPs in the promoter region (1,208-3,049 bp upstream from the transcription start site) of the leptin gene, eleven (g.1508C>G, g.1540G>A, g.1545G>A, g.1551C>T, g.1746T>G, g.1798ins(G), g.1932del(T), g.1933del(T), g.1934del(T), g.1993C>T and g.2033C>T) of which have not been reported previously. Their sequences were deposited in GenBank database with accession number DQ202319. Genotyping of the SNPs located at positions g.2418C>G and g.2423G>A within the promoter region was performed by direct sequencing and PCR-SSCP method to investigate the effects of SNP genotypes on carcass and meat quality traits in Korean cattle. The SNP and SSCP genotypes from the two mutations of the leptin promoter were shown to be associated with the BF trait. The average BF value of animals with heterozygous SNP genotype was significantly greater than that of animals with the homozygous SNP genotypes for the g.2418C>G and g.2423G>A SNPs (p<0.05). Analysis of the combined genotype effect in both SNPs showed that animals with the AC SSCP genotype had higher BF value than animals with BB or AA SSCP genotypes (p<0.05). These results suggest that SNP of the leptin promoter region may be useful markers for selection of economic traits in Korean cattle.

• Journal of Korean Neurosurgical Society
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• v.57 no.6
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• pp.422-427
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• 2015

Moyamoya disease (MMD) is a chronic, progressive, cerebrovascular occlusive disorder that displays various clinical features and results in cerebral infarct or hemorrhagic stroke. Specific genes associated with the disease have not yet been identified, making identification of at-risk patients difficult before clinical manifestation. Familial MMD is not uncommon, with as many as 15% of MMD patients having a family history of the disease, suggesting a genetic etiology. Studies of single nucleotide polymorphisms (SNPs) in MMD have mostly focused on mechanical stress on vessels, endothelium, and the relationship to atherosclerosis. In this review, we discuss SNPs studies targeting the genetic etiology of MMD. Genetic analyses in familial MMD and genome-wide association studies represent promising strategies for elucidating the pathophysiology of this condition. This review also discusses future research directions, not only to offer new insights into the origin of MMD, but also to enhance our understanding of the genetic aspects of MMD. There have been several SNP studies of MMD. Current SNP studies suggest a genetic contribution to MMD, but further reliable and replicable data are needed. A large cohort or family-based design would be important. Modern SNP studies of MMD depend on novel genetic, experimental, and database methods that will hopefully hasten the arrival of a consensus conclusion.

• Genomics & Informatics
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• v.10 no.1
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• pp.65-67
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• 2012

We have discovered copy number variations (CNVs) in 3,578 Korean individuals with the Affymetrix Genome-Wide SNP array 5.0, and 4,003 copy number variation regions (CNVRs) were defined in a previous study. To explore the details of the variants easily in related studies, we built a database, cataloging the CNVs and related information. This system helps researchers browsing these variants with gene and structure variant annotations. Users can easily find specific regions with search options and verify them from system-integrated genome browsers with annotations.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.10a
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• pp.269-269
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• 2017