• Genomics & Informatics
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• v.10 no.3
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• pp.194-199
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• 2012

In addition to single-nucleotide polymorphisms (SNP), copy number variation (CNV) is a major component of human genetic diversity. Among many whole-genome analysis platforms, SNP arrays have been commonly used for genomewide CNV discovery. Recently, a number of CNV defining algorithms from SNP genotyping data have been developed; however, due to the fundamental limitation of SNP genotyping data for the measurement of signal intensity, there are still concerns regarding the possibility of false discovery or low sensitivity for detecting CNVs. In this study, we aimed to verify the effect of combining multiple CNV calling algorithms and set up the most reliable pipeline for CNV calling with Affymetrix Genomewide SNP 5.0 data. For this purpose, we selected the 3 most commonly used algorithms for CNV segmentation from SNP genotyping data, PennCNV, QuantiSNP; and BirdSuite. After defining the CNV loci using the 3 different algorithms, we assessed how many of them overlapped with each other, and we also validated the CNVs by genomic quantitative PCR. Through this analysis, we proposed that for reliable CNV-based genomewide association study using SNP array data, CNV calls must be performed with at least 3 different algorithms and that the CNVs consistently called from more than 2 algorithms must be used for association analysis, because they are more reliable than the CNVs called from a single algorithm. Our result will be helpful to set up the CNV analysis protocols for Affymetrix Genomewide SNP 5.0 genotyping data.

• Genomics & Informatics
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• v.8 no.3
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• pp.103-107
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• 2010

The imputation of untyped SNPs enables researchers to validate association findings across SNP arrays and also enables them to test a large number of SNPs to reveal the fine structure of the association peak, facilitating interpretation of the results and the location of causal polymorphisms. In this study, we applied the imputation method to a genomewide association study and recapitulated the previously associated gene loci of blood pressure traits in Korean cohorts. A total of 1,827,004 SNPs were imputed by the IMPUTE program, and we conducted a genomewide association study for systolic and diastolic blood pressure. While no SNPs passed the Bonferroni correction p-value (p=$2.74{\times}10^{-8}$ for 1,827,004 SNPs), 12 novel loci for systolic blood pressure and 16 novel loci for diastolic blood pressure were detected by imputed SNPs, with $10^{-5}$ < p-value < $10^{-4}$. Moreover, 7 regions (ATP2B1, 10p15.1, ARHGEF12, ALX4, LIPC, 7q31.1, and TCF7L2) out of 14 genetic loci that were previously reported revealed that the imputed SNPs had lower p-values than those of genotyped SNPs. Moreover, a nonsynonymous SNP in the CSMD1 gene, one of the 14 genes, was found to be associated with systolic blood pressure (p<0.05). These results suggest that the imputation method can facilitate the discovery of novel SNPs as well as enhance the fine structure of the association peak in the loci.

• Genomics & Informatics
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• v.8 no.3
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• pp.108-115
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• 2010

Hypertension is the most prevalent disease worldwide and is itself a risk factor for cerebral, cardiac, and renal diseases. The inconsistency of candidate genes suggested by previous genomewide association studies (GWASs) may be due to not only differences in study design and genetic or environmental background but also the difference in the power of analysis between continuous traits and discrete traits. We analyzed 352,228 single nucleotide polymorphisms (SNPs) in 8842 unrelated Koreans obtained from Ansan and Ansung cohorts. We performed a series of GWA analyses using three different phenotype models; young hypertensive cases (278 subjects) versus elderly normotensive controls (680 subjects); the upper 25% (2211 hypertensive cases) versus the lower 25% of the SBP distribution (2211 hypotensive controls); and finally SBP and DBP as continuous traits (8842 subjects). The numbers of young hypertensive cases and elderly normotensive controls were not large enough to achieve genomewide significance. The model comparing the upper 25% subjects to the lower 25% of subjects showed a power that was approximate to that of QTL analysis. Two neighboring SNPs of the ATP2B1 gene, rs17249754 (SBP, p=$2.53^{-10}$; DBP, p=$1.28{\times}10^{-8}$) and rs7136259 (SBP, p=$1.30{\times}10^{-9}$; DBP, p=$6.41{\times}10^{-8}$), were associated with both SBP and DBP. Interestingly, a SNP of the RPL6 gene, rs11066280, revealed a significant genomewide association with SBP in men only (p=$3.85{\times}10^{-8}$), and four SNPs located near the MAN2A1 gene showed a strong association with DBP only in elderly men aged 60-70 years (e.g., rs6421827, p=$4.86{\times}10^{-8}$). However, we did not observe any gene variant attaining genomewide significance consistently in the three phenotype models except for the ATP2B1 gene variants. In general, the association signal with blood pressure was stronger in women than in men. Genes identified in GWASs are expected to open the way for prevention, early diagnosis, and personalized treatment of hypertension.

• The Korea Genome Conference
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• 2006.09a
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• pp.48-48
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• 2006

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.114-121
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• 2007

Power and sample size estimation is one of the crucially important steps in planning a genetic association study to achieve the ultimate goal, identifying candidate genes for disease susceptibility, by designing the study in such a way as to maximize the success possibility and minimize the cost. Here we review the optimal two-stage genotyping designs for genomewide association studies recently investigated by Wang et al(2006). We review two mathematical frameworks most commonly used to compute power in genetic association studies prior to the main study: Monte-Carlo and non-central chi-square estimates. Statistical powers are computed by these two approaches for case-control genotypic tests under one-stage direct association study design. Then we discuss how the linkage-disequilibrium strength affects power and sample size, and how to use empirically-derived distributions of important parameters for power calculations. We provide useful information on publicly available softwares developed to compute power and sample size for various study designs.

• Genomics & Informatics
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• v.10 no.1
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• pp.40-43
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• 2012

Recent genomewide association studies of large samples have identified genes that are associated with blood pressure. The Global Blood Pressure Genetics (Global BPgen) and Cohorts for Heart and Aging Research in Genome Epidemiology (CHARGE) consortiums identified 14 loci that govern blood pressure on a genomewide significance level, one of which is $CASZ1$ confirmed in both Europeans and Asians. $CASZ1$ is a zinc finger transcription factor that controls apoptosis and cell fate and suppresses neuroblastoma tumor growth by reprogramming gene expression, like a tumor suppressor. To validate the function of $CASZ1$ in blood pressure, we decreased $Casz1$ mRNA levels in mice by siRNA. $Casz1$ siRNA reduced mRNA levels by 59% in a mouse cell line. A polyethylenimine-mixed siRNA complex was injected into mouse tail veins, reducing $Casz1$ mRNA expression to 45% in the kidney. However, blood pressure in the treated mice was unaffected, despite a 55% reduction in $Casz1$ mRNA levels in the kidney on multiple siRNA injections daily. Even though $Casz1$ siRNA-treated mice did not experience any significant change in blood pressure, our study demonstrates the value of $in$ $vivo$ siRNA injection in analyzing the function of candidate genes identified by genomewide association studies.

• Genomics & Informatics
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• v.10 no.2
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• pp.106-109
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• 2012

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.

• Advances in Traditional Medicine
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• v.5 no.4
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• pp.251-261
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• 2005

Rheumatoid arthritis (RA) is an autoimmune/inflammatory disorder with a complex genetic component. RA is characterized by chronic inflammation of the synovial membrane in the joint, which leads to the progressive destruction of articular cartilage, ligament and bone. Several cytokines such as tumor necrosis $factor-{\alpha}\;TNF-{\alpha}\;and\;interleukin-1{\beta}\;(IL-1{\beta})$ and interleukin-6 (IL-6) have been implicated in the pathological mechanisms of synovial tissue proliferation, joint destruction and programmed cell death in rheumatoid joint. Genome wide screening of subjects suffering from autoimmune diseases especially arthritis revealed linkage to inflammatory molecules like $TNF-{\alpha},\;IL-1{\beta}$ and IL-6, inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), nuclear factor-kappaB $(NF-{\kappa}B)$ and human leucocyte antigen/major histocompatibility complex (HLA/MHC) locus. The status of the pharmacological mechanism of herbal drugs in the light of genome wide screening results has been discussed to reinforce the therapeutic potential and the pharmacological basis of the herbal drugs.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.11
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• pp.1521-1525
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• 2014

This study investigated heritability for bovine growth estimated with genomewide single nucleotide polymorphism (SNP) information obtained from a DNA microarray chip. Three hundred sixty seven Korean cattle were genotyped with the Illumina BovineSNP50 BeadChip, and 39,112 SNPs of 364 animals filtered by quality assurance were analyzed to estimate heritability of body weights at 6, 9, 12, 15, 18, 21, and 24 months of age. Restricted maximum likelihood estimate of heritability was obtained using covariance structure of genomic relationships among animals in a mixed model framework. Heritability estimates ranged from 0.58 to 0.76 for body weights at different ages. The heritability estimates using genomic information in this study were larger than those which had been estimated previously using pedigree information. The results revealed a trend that the heritability for body weight increased at a younger age (6 months). This suggests an early genetic evaluation for bovine growth using genomic information to increase genetic merits of animals.

• Genomics & Informatics
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• v.11 no.1
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• pp.55-57
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• 2013

Growing numbers of studies employ cell line-based systematic short interfering RNA (siRNA) screens to study gene functions and to identify drug targets. As multiple sources of variations that are unique to siRNA screens exist, there is a growing demand for a computational tool that generates normalized values and standardized scores. However, only a few tools have been available so far with limited usability. Here, we present siMacro, a fast and easy-to-use Microsoft Office Excel-based tool with a graphic user interface, designed to process single-condition or two-condition synthetic screen datasets. siMacro normalizes position and batch effects, censors outlier samples, and calculates Z-scores and robust Z-scores, with a spreadsheet output of >120,000 samples in under 1 minute.