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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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Personal Genomics, Bioinformatics, and Variomics
Bhak, Jong ; Ghang, Ho ; Reja, Rohit ; Kim, Sang-Soo ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 161~165
DOI : 10.5808/GI.2008.6.4.161
In 2008 at least five complete genome sequences are available. It is known that there are over 15,000,000 genetic variants, called SNPs, in the dbSNP database. The cost of full genome sequencing in 2009 is claimed to be less than $5000 USD. The genomics era has arrived in 2008. This review introduces technologies, bioinformatics, genomics visions, and variomics projects. Variomics is the study of the total genetic variation in an individual and populations. Research on genetic variation is the most valuable among many genomics research branches. Genomics and variomics projects will change biology and the society so dramatically that biology will become an everyday technology like personal computers and the internet. 'BioRevolution' is the term that can adequately describe this change.
In Silico Functional Assessment of Sequence Variations: Predicting Phenotypic Functions of Novel Variations
Won, Hong-Hee ; Kim, Jong-Won ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 166~172
DOI : 10.5808/GI.2008.6.4.166
A multitude of protein-coding sequence variations (CVs) in the human genome have been revealed as a result of major initiatives, including the Human Variome Project, the 1000 Genomes Project, and the International Cancer Genome Consortium. This naturally has led to debate over how to accurately assess the functional consequences of CVs, because predicting the functional effects of CVs and their relevance to disease phenotypes is becoming increasingly important. This article surveys and compares variation databases and in silico prediction programs that assess the effects of CVs on protein function. We also introduce a combinatorial approach that uses machine learning algorithms to improve prediction performance.
Identification and Characterization of Human Genes Targeted by Natural Selection
Ryu, Ha-Jung ; Kim, Young-Joo ; Park, Young-Kyu ; Kim, Jae-Jung ; Park, Mi-Young ; Seo, Eul-Ju ; Yoo, Han-Wook ; Park, In-Sook ; Oh, Berm-Seok ; Lee, Jong-Keuk ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 173~180
DOI : 10.5808/GI.2008.6.4.173
The human genome has evolved as a consequence of evolutionary forces, such as natural selection. In this study, we investigated natural selection on the human genes by comparing the numbers of nonsynonymous (NS) and synonymous (S) mutations in individual genes. We initially collected all coding SNP data of all human genes from the public dbSNP. Among the human genes, we selected 3 different selection groups of genes: positively selected genes (NS/S
3), negatively selected genes (NS/S
1/3) and neutral selection genes (0.9
Polymorphisms in RAS Guanyl-releasing Protein 3 are Associated with Chronic Liver Disease and Hepatocellular Carcinoma in a Korean Population
Oh, Ah-Reum ; Lee, Seung-Ku ; Kim, Min-Ho ; Cheong, Jae-Youn ; Cho, Sung-Won ; Yang, Kap-Seok ; Kwack, Kyu-Bum ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 181~191
DOI : 10.5808/GI.2008.6.4.181
RAS guanyl-releasing protein 3 (RasGRP3), a member of the Ras subfamily of GTPases, functions as a guanosine triphosphate (GTP)/guanosine diphosphate (GDP)-regulated switch that cycles between inactive GDP- and active GTP-bound states during signal transduction. Various growth factors enhance hepatocellular carcinoma (HCC) proliferation via activation of the Ras/Raf-1/extracellular signal-regulated kinase (ERK) pathway, which depends on RasGRP3 activation. We investigated the relationship between polymorphisms in RasGRP3 and progression of hepatitis B virus (HBV)-infected HCC in a Korean population. Nineteen RasGRP3 SNPs were genotyped in 206 patients with chronic liver disease (CLD) and 86 patients with HCC. Our results revealed that the T allele of the rs7597095 SNP and the C allele of the rs7592762 SNP increased susceptibility to HCC (OR=1.55, p=0.04 and OR=1.81
0.03, respectively). Moreover, patients who possessed the haplotype (ht) 1 (A-T-C-G) or diplotype (dt) 1 (ht1/ht1) variations had increased susceptibility to HCC (OR=1.79
0.03). In addition, we identified an association between haplotype1 (ht1) and the age of HCC onset; the age of HCC onset are earlier in ht1 +/+ than ht1 +/- or ht1 -/- (HR=0.42
0.015). Thus, our data suggest that RasGRP3 SNPs are significantly associated with an increased risk of developing HCC.
Erythropoietin-producing Human Hepatocellular Carcinoma Receptor B1 Polymorphisms are Associated with HBV-infected Chronic Liver Disease and Hepatocellular Carcinoma in a Korean Population
Kim, Kyoung-Yeon ; Lee, Seung-Ku ; Kim, Min-Ho ; Cheong, Jae-Youn ; Cho, Sung-Won ; Yang, Kap-Seok ; Kwack, Kyu-Bum ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 192~201
DOI : 10.5808/GI.2008.6.4.192
Erythropoietin-producing human hepatocellular carcinoma receptor B1 (EPHB1) is a member of the Eph family of receptor tyrosine kinases that mediate vascular system development. Eph receptor overexpression has been observed in various cancers and is related to the malignant transformation, metastasis, and differentiation of cancers, including hepatocellular carcinoma (HCC). Eph receptors regulate cell migration and attachment to the extracellular matrix by modulating integrin activity. EphrinB1, the ligand of EPHB1, has been shown to regulate HCC carcinogenesis. Here, we sought to determine whether EPHB1 polymorphisms are associated with hepatitis B virus (HBV)-infected liver diseases, including chronic liver disease (CLD) and HCC. We genotyped 26 EPHB1 single nucleotide polymorphisms (SNPs) in 399 Korean CLD, HCC, and LD (CLD+HCC) cases and seroconverted controls (HBV clearance, CLE) using the GoldenGate assay. Two SNPs (rs6793828 and rs11717042) and 1 haplotype that were composed of these SNPs were associated with an increased risk for CLD, HCC, and LD (CLD+HCC) compared with CLE. Haplotypes that could be associated with HBV-infected liver diseases by affecting downstream signaling were located in the Eph tyrosine kinase domain of EPHB1. Therefore, we suggest that EPHB1 SNPs, haplotypes, and diplotypes may be genetic markers for the progression of HBV-associated acute hepatitis to CLD and HCC.
Biological Pathway Extension Using Microarray Gene Expression Data
Chung, Tae-Su ; Kim, Ji-Hun ; Kim, Kee-Won ; Kim, Ju-Han ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 202~209
DOI : 10.5808/GI.2008.6.4.202
Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.
Microarray Data Analysis of Perturbed Pathways in Breast Cancer Tissues
Kim, Chang-Sik ; Choi, Ji-Won ; Yoon, Suk-Joon ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 210~222
DOI : 10.5808/GI.2008.6.4.210
Due to the polygenic nature of cancer, it is believed that breast cancer is caused by the perturbation of multiple genes and their complex interactions, which contribute to the wide aspects of disease phenotypes. A systems biology approach for the identification of subnetworks of interconnected genes as functional modules is required to understand the complex nature of diseases such as breast cancer. In this study, we apply a 3-step strategy for the interpretation of microarray data, focusing on identifying significantly perturbed metabolic pathways rather than analyzing a large amount of overexpressed and underexpressed individual genes. The selected pathways are considered to be dysregulated functional modules that putatively contribute to the progression of disease. The subnetwork of protein-protein interactions for these dysregulated pathways are constructed for further detailed analysis. We evaluated the method by analyzing microarray datasets of breast cancer tissues; i.e., normal and invasive breast cancer tissues. Using the strategy of microarray analysis, we selected several significantly perturbed pathways that are implicated in the regulation of progression of breast cancers, including the extracellular matrix-receptor interaction pathway and the focal adhesion pathway. Moreover, these selected pathways include several known breast cancer-related genes. It is concluded from this study that the present strategy is capable of selecting interesting perturbed pathways that putatively play a role in the progression of breast cancer and provides an improved interpretability of networks of protein-protein interactions.
Computational Approach for the Analysis of Post-PKS Glycosylation Step
Kim, Ki-Bong ; Park, Kie-Jung ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 223~226
DOI : 10.5808/GI.2008.6.4.223
We introduce a computational approach for analysis of glycosylation in Post-PKS tailoring steps. It is a computational method to predict the deoxysugar biosynthesis unit pathway and the substrate specificity of glycosyltransferases involved in the glycosylation of polyketides. In this work, a directed and weighted graph is introduced to represent and predict the deoxysugar biosynthesis unit pathway. In addition, a homology based gene clustering method is used to predict the substrate specificity of glycosyltransferases. It is useful for the rational design of polyketide natural products, which leads to in silico drug discovery.
Computational Approach for Biosynthetic Engineering of Post-PKS Tailoring Enzymes
Kim, Ki-Bong ; Park, Kie-Jung ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 227~230
DOI : 10.5808/GI.2008.6.4.227
Compounds of polyketide origin possess a wealth of pharmacological effects, including antibacterial, antifungal, antiparasitic, anticancer and immunosuppressive activities. Many of these compounds and their semisynthetic derivatives are used today in the clinic. Most of the gene clusters encoding commercially important drugs have also been cloned and sequenced and their biosynthetic mechanisms studied in great detail. The area of biosynthetic engineering of the enzymes involved in polyketide biosynthesis has recently advanced and been transferred into the industrial arena. In this work, we introduce a computational system to provide the user with a wealth of information that can be utilized for biosynthetic engineering of enzymes involved in post-PKS tailoring steps. Post-PKS tailoring steps are necessary to add functional groups essential for the biological activity and are therefore important in polyketide biosynthesis.
Comparison of Normalization Methods for Defining Copy Number Variation Using Whole-genome SNP Genotyping Data
Kim, Ji-Hong ; Yim, Seon-Hee ; Jeong, Yong-Bok ; Jung, Seong-Hyun ; Xu, Hai-Dong ; Shin, Seung-Hun ; Chung, Yeun-Jun ;
Genomics & Informatics, volume 6, issue 4, 2008, Pages 231~234
DOI : 10.5808/GI.2008.6.4.231
Precise and reliable identification of CNV is still important to fully understand the effect of CNV on genetic diversity and background of complex diseases. SNP marker has been used frequently to detect CNVs, but the analysis of SNP chip data for identifying CNV has not been well established. We compared various normalization methods for CNV analysis and suggest optimal normalization procedure for reliable CNV call. Four normal Koreans and NA10851 HapMap male samples were genotyped using Affymetrix Genome-Wide Human SNP array 5.0. We evaluated the effect of median and quantile normalization to find the optimal normalization for CNV detection based on SNP array data. We also explored the effect of Robust Multichip Average (RMA) background correction for each normalization process. In total, the following 4 combinations of normalization were tried: 1) Median normalization without RMA background correction, 2) Quantile normalization without RMA background correction, 3) Median normalization with RMA background correction, and 4) Quantile normalization with RMA background correction. CNV was called using SW-ARRAY algorithm. We applied 4 different combinations of normalization and compared the effect using intensity ratio profile, box plot, and MA plot. When we applied median and quantile normalizations without RMA background correction, both methods showed similar normalization effect and the final CNV calls were also similar in terms of number and size. In both median and quantile normalizations, RMA backgroundcorrection resulted in widening the range of intensity ratio distribution, which may suggest that RMA background correction may help to detect more CNVs compared to no correction.