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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 10, Issue 4 - Dec 2012
Volume 10, Issue 3 - Sep 2012
Volume 10, Issue 2 - Jun 2012
Volume 10, Issue 1 - Mar 2012
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Perspectives of Integrative Cancer Genomics in Next Generation Sequencing Era
Kwon, So-Mee ; Cho, Hyun-Woo ; Choi, Ji-Hye ; Jee, Byul-A ; Jo, Yun-A ; Woo, Hyun-Goo ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 69~73
DOI : 10.5808/GI.2012.10.2.69
The explosive development of genomics technologies including microarrays and next generation sequencing (NGS) has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research.
Alternative Splicing and Its Impact as a Cancer Diagnostic Marker
Kim, Yun-Ji ; Kim, Heui-Soo ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 74~80
DOI : 10.5808/GI.2012.10.2.74
Most genes are processed by alternative splicing for gene expression, resulting in the complexity of the transcriptome in eukaryotes. It allows a limited number of genes to encode various proteins with intricate functions. Alternative splicing is regulated by genetic mutations in cis-regulatory factors and epigenetic events. Furthermore, splicing events occur differently according to cell type, developmental stage, and various diseases, including cancer. Genome instability and flexible proteomes by alternative splicing could affect cancer cells to grow and survive, leading to metastasis. Cancer cells that are transformed by aberrant and uncontrolled mechanisms could produce alternative splicing to maintain and spread them continuously. Splicing variants in various cancers represent crucial roles for tumorigenesis. Taken together, the identification of alternative spliced variants as biomarkers to distinguish between normal and cancer cells could cast light on tumorigenesis.
Identifying Copy Number Variants under Selection in Geographically Structured Populations Based on F-statistics
Song, Hae-Hiang ; Hu, Hae-Jin ; Seok, In-Hae ; Chung, Yeun-Jun ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 81~87
DOI : 10.5808/GI.2012.10.2.81
Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional
measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the
estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific
and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.
Interaction Effects of Lipoprotein Lipase Polymorphisms with Lifestyle on Lipid Levels in a Korean Population: A Cross-sectional Study
Pyun, Jung-A ; Kim, Sun-Shin ; Park, Kyung-Chae ; Baik, In-Kyung ; Cho, Nam-H. ; Koh, In-Song ; Lee, Jong-Young ; Cho, Yoon-Shin ; Kim, Young-Jin ; Go, Min-Jin ; Shim, Eu-Gene ; Kwack, Kyu-Bum ; Shin, Chol ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 88~98
DOI : 10.5808/GI.2012.10.2.88
Lipoprotein lipase (LPL) plays an essential role in the regulation of high-density lipoprotein cholesterol (HDLC) and triglyceride levels, which have been closely associated with cardiovascular diseases. Genetic studies in European have shown that LPL single-nucleotide polymorphisms (SNPs) are strongly associated with lipid levels. However, studies about the influence of interactions between LPL SNPs and lifestyle factors have not been sufficiently performed. Here, we examine if LPL polymorphisms, as well as their interaction with lifestyle factors, influence lipid concentrations in a Korean population. A two-stage association study was performed using genotype data for SNPs on the LPL gene, including the 3' flanking region from 7,536 (stage 1) and 3,703 (stage 2) individuals. The association study showed that 15 SNPs and 4 haplotypes were strongly associated with HDLC (lowest
) and triglyceride levels (lowest
). Interactions between LPL polymorphisms and lifestyle factors (lowest
) were also observed on lipid concentrations. These findings suggest that there are interaction effects of LPL polymorphisms with lifestyle variables, including energy intake, fat intake, smoking, and alcohol consumption, as well as effects of LPL polymorphisms themselves, on lipid concentrations in a Korean population.
Effect of Genetic Predisposition on Blood Lipid Traits Using Cumulative Risk Assessment in the Korean Population
Go, Min-Jin ; Hwang, Joo-Yeon ; Kim, Dong-Joon ; Lee, Hye-Ja ; Jang, Han-Byul ; Park, Kyung-Hee ; Song, Ji-Hyun ; Lee, Jong-Young ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 99~105
DOI : 10.5808/GI.2012.10.2.99
Dyslipidemia, mainly characterized by high triglyceride (TG) and low high-density lipoprotein cholesterol (HDL-C) levels, is an important etiological factor in the development of cardiovascular disease (CVD). Considering the relationship between childhood obesity and CVD risk, it would be worthwhile to evaluate whether previously identified lipid-related variants in adult subjects are associated with lipid variations in a childhood obesity study (n = 482). In an association analysis for 16 genome-wide association study (GWAS)-based candidate loci, we confirmed significant associations of a genetic predisposition to lipoprotein concentrations in a childhood obesity study. Having two loci (rs10503669 at LPL and rs16940212 at LIPC) that showed the strongest association with blood levels of TG and HDL-C, we calculated a genetic risk score (GRS), representing the sum of the risk alleles. It has been observed that increasing GRS is significantly associated with decreased HDL-C (effect size,
) compared to single nucleotide polymorphism combinations without two risk variants. In addition, a positive correlation was observed between allelic dosage score and risk allele (rs10503669 at LPL) on high TG levels (effect size,
). These two loci yielded consistent associations in our previous meta-analysis. Taken together, our findings demonstrate that the genetic architecture of circulating lipid levels (TG and HDL-C) overlap to a large extent in childhood as well as in adulthood. Post-GWAS functional characterization of these variants is further required to elucidate their pathophysiological roles and biological mechanisms.
Replication of the Association of the 6q22.31c Locus near GJA1 with Pulse Rate in the Korean Population
Kim, Nam-Hee ; Kim, Young-Jin ; Oh, Ji-Hee ; Cho, Yoon-Shin ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 106~109
DOI : 10.5808/GI.2012.10.2.106
Pulse rate is known to be related to diverse phenotypes, such as cardiovascular diseases, lifespan, arrhythmia, hypertension, lipids, diabetes, and menopause. We have reported two genomewide significant genetic loci responsible for the variation in pulse rate as a part of the Korea Association Resource (KARE) project, the genomewide association study (GWAS) that was conducted with 352,228 single nucleoride polymorphisms typed in 8,842 subjects in the Korean population. GJA1 was implied as a functionally causal gene for pulse rate from the KARE study, but lacked evidence of replication. To re-evaluate the association of a locus near GJA1 with pulse rate, we looked up this signal in another GWAS conducted in a Health Examinee-shared cohort of 3,703 samples. Not only we were able to confirm two pulse rate loci (1q32.2a near CD46 and 6q22.13c near LOCL644502) identified in the KARE GWAS, we also replicated a locus (6q22.31c) near GJA1 by the lookup in the Health Examinee GWAS. Considering that the GJA1-encoded protein is a major component of cardiac gap junctions, a functional study might be necessary to validate its genuine molecular biological role in the synchronized contraction of the heart.
Genetic Analysis of SCN5A in Korean Patients Associated with Atrioventricular Conduction Block
Park, Hyoung-Seob ; Kim, Yoon-Nyun ; Lee, Young-Soo ; Jung, Byung-Chun ; Lee, Sang-Hee ; Shin, Dong-Gu ; Cho, Yong-Keun ; Bae, Myung-Hwan ; Han, Sang-Mi ; Lee, Myung-Hoon ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 110~116
DOI : 10.5808/GI.2012.10.2.110
Recent several studies have shown that the genetic variation of SCN5A is related with atrioventricular conduction block (AVB); no study has yet been published in Koreans. Therefore, to determine the AVB-associated genetic variation in Korean patients, we investigated the genetic variation of SCN5A in Korean patients with AVB and compared with normal control subjects. We enrolled 113 patients with AVB and 80 normal controls with no cardiac symptoms. DNA was isolated from the peripheral blood, and all exons (exon 2-exon 28) except the untranslated region and exon-intron boundaries of the SCN5A gene were amplified by multiplex PCR and directly sequenced using an ABI PRISM 3100 Genetic Analyzer. When a variation was discovered in genomic DNA from AVB patients, we confirmed whether the same variation existed in the control genomic DNA. In the present study, a total of 7 genetic variations were detected in 113 AVB patients. Of the 7 variations, 5 (G87A-A29A, intervening sequence 9-3C>A, A1673G-H558R, G3578A-R1193Q, and T5457C-D1819D) have been reported in previous studies, and 2 (C48G-F16L and G3048A-T1016T) were novel variations that have not been reported. The 2 newly discovered variations were not found in the 80 normal controls. In addition, G298S, G514C, P1008S, G1406R, and D1595N, identified in other ethnic populations, were not detected in this study. We found 2 novel genetic variations in the SCN5A gene in Korean patients with AVB. However, further functional study might be needed.
Sample Size and Statistical Power Calculation in Genetic Association Studies
Hong, Eun-Pyo ; Park, Ji-Wan ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 117~122
DOI : 10.5808/GI.2012.10.2.117
A sample size with sufficient statistical power is critical to the success of genetic association studies to detect causal genes of human complex diseases. Genome-wide association studies require much larger sample sizes to achieve an adequate statistical power. We estimated the statistical power with increasing numbers of markers analyzed and compared the sample sizes that were required in case-control studies and case-parent studies. We computed the effective sample size and statistical power using Genetic Power Calculator. An analysis using a larger number of markers requires a larger sample size. Testing a single-nucleotide polymorphism (SNP) marker requires 248 cases, while testing 500,000 SNPs and 1 million markers requires 1,206 cases and 1,255 cases, respectively, under the assumption of an odds ratio of 2, 5% disease prevalence, 5% minor allele frequency, complete linkage disequilibrium (LD), 1:1 case/control ratio, and a 5% error rate in an allelic test. Under a dominant model, a smaller sample size is required to achieve 80% power than other genetic models. We found that a much lower sample size was required with a strong effect size, common SNP, and increased LD. In addition, studying a common disease in a case-control study of a 1:4 case-control ratio is one way to achieve higher statistical power. We also found that case-parent studies require more samples than case-control studies. Although we have not covered all plausible cases in study design, the estimates of sample size and statistical power computed under various assumptions in this study may be useful to determine the sample size in designing a population-based genetic association study.
Performance Comparison of Two Gene Set Analysis Methods for Genome-wide Association Study Results: GSA-SNP vs i-GSEA4GWAS
Kwon, Ji-Sun ; Kim, Ji-Hye ; Nam, Doug-U ; Kim, Sang-Soo ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 123~127
DOI : 10.5808/GI.2012.10.2.123
Gene set analysis (GSA) is useful in interpreting a genome-wide association study (GWAS) result in terms of biological mechanism. We compared the performance of two different GSA implementations that accept GWAS p-values of single nucleotide polymorphisms (SNPs) or gene-by-gene summaries thereof, GSA-SNP and i-GSEA4GWAS, under the same settings of inputs and parameters. GSA runs were made with two sets of p-values from a Korean type 2 diabetes mellitus GWAS study: 259,188 and 1,152,947 SNPs of the original and imputed genotype datasets, respectively. When Gene Ontology terms were used as gene sets, i-GSEA4GWAS produced 283 and 1,070 hits for the unimputed and imputed datasets, respectively. On the other hand, GSA-SNP reported 94 and 38 hits, respectively, for both datasets. Similar, but to a lesser degree, trends were observed with Kyoto Encyclopedia of Genes and Genomes (KEGG) gene sets as well. The huge number of hits by i-GSEA4GWAS for the imputed dataset was probably an artifact due to the scaling step in the algorithm. The decrease in hits by GSA-SNP for the imputed dataset may be due to the fact that it relies on Z-statistics, which is sensitive to variations in the background level of associations. Judicious evaluation of the GSA outcomes, perhaps based on multiple programs, is recommended.
Characteristics in Molecular Vibrational Frequency Patterns between Agonists and Antagonists of Histamine Receptors
Oh, S. June ;
Genomics & Informatics, volume 10, issue 2, 2012, Pages 128~132
DOI : 10.5808/GI.2012.10.2.128
To learn the differences between the structure-activity relationship and molecular vibration-activity relationship in the ligand-receptor interaction of the histamine receptor, 47 ligands of the histamine receptor were analyzed by structural similarity and molecular vibrational frequency patterns. The radial tree that was produced by clustering analysis of molecular vibrational frequency patterns shows its potential for the functional classification of histamine receptor ligands.