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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Genomics & Informatics
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Korea Genome Organization
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Volume & Issues
Volume 6, Issue 4 - Dec 2008
Volume 6, Issue 3 - Sep 2008
Volume 6, Issue 2 - Jun 2008
Volume 6, Issue 1 - Mar 2008
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Protein Tyrosine Phosphatase N1 Gene Variants Associated with Type 2 Diabetes Mellitus and Its Related Phenotypes in the Korean Population
Hong, Kyung-Won ; Jin, Hyun-Seok ; Lim, Ji-Eun ; Ryu, Ha-Jung ; Ahn, Youn-Jhin ; Lee, Jong-Young ; Han, Bok-Ghee ; Shin, Hyoung-Doo ; Cho, Nam-Han ; Shin, Chol ; Woo, Jeong-Taek ; Park, Hun-Kuk ; Oh, Berm-Seok ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 99~109
DOI : 10.5808/GI.2008.6.3.099
Protein phosphorylation at tyrosine residues is a key regulatory event that modulates insulin signal transduction. We studied the PTPN1 gene with regard to susceptibility to Korean type 2 diabetes mellitus (T2DM) and its related quantitative traits. A total of seven SNPs [g.36171G>A (rs941798), g.58166G>A (rs3787343), g.58208A>G (rs2909270), g.64840C>T (rs754118), g.69560C>G (rs6020612), g.69866G>A (rs718050), and g.69934T>G (rs3787343)] were selected based on frequency (>0.05), linkage disequilibrium (LD) status, and haplotype tagging status. We studied the seven SNPs in 483 unrelated patients with type 2 diabetes (age:
years, onset age:
years; 206 men, 277 women) and 1138 nondiabetic control subjects (age:
; 516 men, 622 women). The SNP rs941798 had protective effects against T2DM with an odds ratio of 0.726 (C.I.
) and p-value=0.034, but none of the remaining six SNPs was associated with T2DM. Also, rs941798 was associated with blood pressure, HDL cholesterol, insulin sensitivity. rs941798 also has been associated with T2DM in previous reports of Caucasian-American and Hispanic-American populations. This is the first report that shows an association between PTPN1 and T2DM in the Korean as well as Asian population.
Association between Prostaglandin-endoperoxide Synthase 2 (PTGS2) Polymorphisms and Blood Pressure in Korean Population
Jin, Hyun-Seok ; Hong, Kyung-Won ; Lim, Ji-Eun ; Han, Hye-Ree ; Lee, Jong-Young ; Park, Hun-Kuk ; Oh, Berm-Seok ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 110~116
DOI : 10.5808/GI.2008.6.3.110
Blood pressure refers to the force exerted by circulating blood on the walls of blood vessels, and chronical elevation of blood pressure is known as hypertension. Although hypertension is affected by genetic and environmental factors, the genetic background of hypertension is not fully understood. One of the candidate genetic factors, Prostaglandin-endoperoxide synthase 2 (PTGS2), is a membrane-bound enzyme, catalyzing the conversion of arachidonic acid to prostaglandin, and recently SNPs of PTGS2 gene was associated with hypertension in Japanese population. Therefore the association of PTGS2 polymorphisms was investigated with blood pressure in healthy Korean subjects, 470 unrelated individuals randomly selected from Ansung and Ansan cohorts. The 25 SNPs of PTGS2 gene were identified by the sequencing analysis of 24 Korean samples. Among identified polymorphisms, three SNPs (rs689466, -1329A>G; rs5275, +6365T>C; rs4648308, +8806G> A) were selected for further association analysis, and rs689466 located in promoter region was associated with blood pressure as well as triglyceride level in the blood. By in silico analysis, rs689466 locates in v-Myb transcription factor binding site, and the v-Myb site disappears when the SNP is changed from A to G nucleotide. Individuals with A/G and G/G genotype in rs689466 have higher blood pressure than those with A/A genotype, and the regression p-value is 0.008 for systolic and 0.004 for diastolic blood pressure. In summary, the PTGS2 polymorphism (rs689466) is associated with blood pressure in Asian populations based on this and Japanese studies, shedding light on it as a genetic risk marker of hypertension.
Gene Expression Profiling in C57BL/6 Mice Treated with the Anorectic Drugs Sibutramine and Phendimetrazine and Their Mechanistic Implications
Ko, Moon-Jeong ; Choi, Hyo-Sung ; Ahn, Joon-Ik ; Kim, So-Young ; Jeong, Ho-Sang ; Chung, Hye-Joo ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 117~125
DOI : 10.5808/GI.2008.6.3.117
Recently, obesity has become a worldwide public health concern and the use of anorectic drugs has drastically increased. In this study, sibutramine and phendimetrazine, representative marketed anorectics, were repeatedly administered per os on a daily basis into C57BL/6 mice and the effects of these drugs on food intakes, body weight changes and gene expression profiles were monitored for up to following 7 days. Methamphetamine, which has a potent anorectic effect, was used as a positive control. Anorectic effects were sustained only for two days by phendimetrazine or methamphetamine, but for six days by sibutramine. The modulations of gene expressions in the hypothalamus and the striatum were investigated using microarrays on day 2 and day 7 post-administration, which corresponded to the anorectic period and a return of appetite respectively, for all three drugs tested. Differences in overall gene expression profiles in the stratum on day 2 for sibutramine and phendimetrazine seems to reflect difference between the two in terms of the onsets of drug tolerance. According to microarray findings, the Ankrd26 gene appears to have an important anorectic role, whereas the up-regulation of the olfaction system appeared to be involved in the drug tolerance of anorectics. The microarray data presented in this study demonstrates the usefulness of gene expression analysis for gathering information on the efficacy and safety of anorectic drugs.
CGHscape: A Software Framework for the Detection and Visualization of Copy Number Alterations
Jeong, Yong-Bok ; Kim, Tae-Min ; Chung, Yeun-Jun ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 126~129
DOI : 10.5808/GI.2008.6.3.126
The robust identification and comprehensive profiling of copy number alterations (CNAs) is highly challenging. The amount of data obtained from high-throughput technologies such as array-based comparative genomic hybridization is often too large and it is required to develop a comprehensive and versatile tool for the detection and visualization of CNAs in a genome-wide scale. With this respective, we introduce a software framework, CGHscape that was originally developed to explore the CNAs for the study of copy number variation (CNV) or tumor biology. As a standalone program, CGHscape can be easily installed and run in Microsoft Windows platform. With a user-friendly interface, CGHscape provides a method for data smoothing to cope with the intrinsic noise of array data and CNA detection based on SW-ARRAY algorithm. The analysis results can be demonstrated as log2 plots for individual chromosomes or genomic distribution of identified CNAs. With extended applicability, CGHscape can be used for the initial screening and visualization of CNAs facilitating the cataloguing and characterizing chromosomal alterations of a cohort of samples.
Haplotype Phylogeny of a 200kb Region in the Human Chromosome X Terminal Band (q28)
Kim, Sang-Soo ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 130~135
DOI : 10.5808/GI.2008.6.3.130
The haplotypes of a 200 kb region in the human chromosome X terminal band (q28) were analyzed using the International HapMap Project Phasell data, which had been collected for three analysis panels (YRI, CEU, and CHB＋JPT). When multiple linkage disequilibrium blocks were encountered for a panel, the neighboring haplotypes that had crossover rate of 5% or more in the panel were combined to generate 'haploid' configurations. This resulted in 8, 7, and 5 'haploid' configurations for the panels of YRI, CEU, and CHB＋JPT, respectively. The multiple sequence alignment of these 'haploids' was used for the calculation of allele-sharing distances and the subsequent principal coordinate analysis. Two 'haploids' in CEU and CHB＋JPT were hypothesized as 'parental' in light of the observations that the successive recombinants of these haploids can model two other haploids in CEU and CHB＋JPT, and that their configurations were consistent with those in YRI. This study demonstrates the utility of haplotype phylogeny in understanding population evolution.
Disease Prediction Using Ranks of Gene Expressions
Kim, Ki-Yeol ; Ki, Dong-Hyuk ; Chung, Hyun-Cheol ; Rha, Sun-Young ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 136~141
A large number of studies have been performed to identify biomarkers that will allow efficient detection and determination of the precise status of a patient’s disease. The use of microarrays to assess biomarker status is expected to improve prediction accuracies, because a whole-genome approach is used. Despite their potential, however, patient samples can differ with respect to biomarker status when analyzed on different platforms, making it more difficult to make accurate predictions, because bias may exist between any two different experimental conditions. Because of this difficulty in experimental standardization of microarray data, it is currently difficult to utilize microarray-based gene sets in the clinic. To address this problem, we propose a method that predicts disease status using gene expression data that are transformed by their ranks, a concept that is easily applied to two datasets that are obtained using different experimental platforms. NCI and colon cancer datasets, which were assessed using both Affymetrix and cDNA microarray platforms, were used for method validation. Our results demonstrate that the proposed method is able to achieve good predictive performance for datasets that are obtained under different experimental conditions.
Structural Bioinformatics Analysis of Disease-related Mutations
Park, Seong-Jin ; Oh, Sang-Ho ; Park, Dae-Ui ; Bhak, Jong ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 142~146
DOI : 10.5808/GI.2008.6.3.142
In order to understand the protein functions that are related to disease, it is important to detect the correlation between amino acid mutations and disease. Many mutation studies about disease-related proteins have been carried out through molecular biology techniques, such as vector design, protein engineering, and protein crystallization. However, experimental protein mutation studies are time-consuming, be it in vivo or in vitro. We therefore performed a bioinformatic analysis of known disease-related mutations and their protein structure changes in order to analyze the correlation between mutation and disease. For this study, we selected 111 diseases that were related to 175 proteins from the PDB database and 710 mutations that were found in the protein structures. The mutations were acquired from the Human Gene Mutation Database (HGMD). We selected point mutations, excluding only insertions or deletions, for detecting structural changes. To detect a structural change by mutation, we analyzed not only the structural properties (distance of pocket and mutation, pocket size, surface size, and stability), but also the physico-chemical properties (weight, instability, isoelectric point (IEP), and GRAVY score) for the 710 mutations. We detected that the distance between the pocket and disease-related mutation lay within
(98.5%, 700 proteins). We found that there was no significant correlation between structural stability and disease-causing mutations or between hydrophobicity changes and critical mutations. For large-scale mutational analysis of disease-causing mutations, our bioinformatics approach, using 710 structural mutations, called "Structural Mutatomics," can help researchers to detect disease-specific mutations and to understand the biological functions of disease-related proteins.
Parsing KEGG XML Files to Find Shared and Duplicate Compounds Contained in Metabolic Pathway Maps: A Graph-Theoretical Perspective
Kang, Sung-Hui ; Jang, Myung-Ha ; Whang, Ji-Young ; Park, Hyun-Seok ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 147~152
DOI : 10.5808/GI.2008.6.3.147
The basic graph layout technique, one of many visualization techniques, deals with the problem of positioning vertices in a way to maximize some measure of desirability in a graph. The technique is becoming critically important for further development of the field of systems biology. However, applying the appropriate automatic graph layout techniques to the genomic scale flow of metabolism requires an understanding of the characteristics and patterns of duplicate and shared vertices, which is crucial for bioinformatics software developers. In this paper, we provide the results of parsing KEGG XML files from a graph-theoretical perspective, for future research in the area of automatic layout techniques in biological pathway domains.
StrokeBase: A Database of Cerebrovascular Disease-related Candidate Genes
Kim, Young-Uk ; Kim, Il-Hyun ; Bang, Ok-Sun ; Kim, Young-Joo ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 153~156
DOI : 10.5808/GI.2008.6.3.153
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.
A Simple and Fast Web Alignment Tool for Large Amount of Sequence Data
Lee, Yong-Seok ; Oh, Jeong-Su ;
Genomics & Informatics, volume 6, issue 3, 2008, Pages 157~159
DOI : 10.5808/GI.2008.6.3.157
Multiple sequence alignment (MSA) is the most important step for many of biological sequence analyses, homology search, and protein structural assignments. However, large amount of data make biologists difficult to perform MSA analyses and it requires much computational time to align many sequences. Here, we have developed a simple and fast web alignment tool for aligning, editing, and visualizing large amount of sequence data. We used a cluster server installed ClustalW-MPI using web services and message passing interface (MPI). It also enables users to edit multiple sequence alignments for manual editing and to download the input data and results such as alignments and phylogenetic tree.