• Genomics & Informatics
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• v.21 no.3
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• pp.28.1-28.13
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• 2023

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer's disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer's Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

• Genomics & Informatics
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• v.8 no.3
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• pp.159-163
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• 2010

Erythrocyte traits are heritable and indirect indicators of blood diseases caused by erythrocyte, but their genetic factors are largely unknown. So we performed genome-wide association study in 8,842 Korean individuals to identify genetic factors influencing erythrocyte traits. We identified 40 associations for three erythrocyte traits at genome-wide significance levels (p < $1{\times}10^{-6}$). We compared these associated loci with those reported in genome-wide association studies of European and Japanese. Our findings include previously identified loci(HBS1L-MYB, TMPRSS6, USP49 and CCND3) in other studies and novel associations (MRDS1/OFCC1, CSDE1, NRAS and 8 other loci). For example, SNP rs4895440 of HBS1L-MYB intergenic region on chromosome 6q23.3 is one of the most associations influencing erythrocyte traits (p=$8.33{\times}10^{-27}$).

• BMB Reports
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• v.45 no.5
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• pp.305-310
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• 2012

Allergic diseases such as asthma, allergic rhinitis, and atopic dermatitis are heterogeneous diseases characterized by multiple symptoms and phenotypes. Recent advancements in genetic study enabled us to identify disease associated genetic factors. Numerous genome-wide association studies (GWAS) have revealed multiple associated loci for allergic diseases. However, the majority of previous studies have been conducted in populations of European ancestry. Moreover, the associations of single nucleotide polymorphisms (SNPs) with allergic diseases have not been studied amongst the large-scale general Korean population. Herein, we performed the replication study to validate the previous variants, known to be associated with allergic diseases, in the Korean population. In this study, we categorized three allergic related phenotypes, one allergy and two asthma related phenotypes, based on self-reports of physician diagnosis and their symptoms from 8,842 samples. As a result, we found nominally significant associations of 6 SNPs with at least one allergic related phenotype in the Korean population.

• Genomics & Informatics
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• v.16 no.3
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• pp.59-64
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• 2018

Although pork quality traits are important commercially, genome-wide association studies (GWASs) have not well considered Landrace and Yorkshire pigs worldwide. Landrace and Yorkshire pigs are important pork-providing breeds. Although quantitative trait loci of pigs are well-developed, significant genes in GWASs of pigs in Korea must be studied. Through a GWAS using the PLINK program, study of the significant genes in Korean pigs was performed. We conducted a GWAS and surveyed the gene ontology (GO) terms associated with the backfat thickness (BF) trait of these pigs. We included the breed information (Yorkshire and Landrace pigs) as a covariate. The significant genes after false discovery rate (<0.01) correction were AFG1L, SCAI, RIMS1, and SPDEF. The major GO terms for the top 5% of genes were related to neuronal genes, cell morphogenesis and actin cytoskeleton organization. The neuronal genes were previously reported as being associated with backfat thickness. However, the genes in our results were novel, and they included ZNF280D, BAIAP2, LRTM2, GABRA5, PCDH15, HERC1, DTNBP1, SLIT2, TRAPPC9, NGFR, APBB2, RBPJ, and ABL2. These novel genes might have roles in important cellular and physiological functions related to BF accumulation. The genes related to cell morphogenesis were NOX4, MKLN1, ZNF280D, BAIAP2, DNAAF1, LRTM2, PCDH15, NGFR, RBPJ, MYH9, APBB2, DTNBP1, TRIM62, and SLIT2. The genes that belonged to actin cytoskeleton organization were MKLN1, BAIAP2, PCDH15, BCAS3, MYH9, DTNBP1, ABL2, ADD2, and SLIT2.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2231-2235
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• 2015

Genome-wide association studies (GWASs) of the entire genome provide a systematic approach for revealing novel genetic susceptibility loci for breast cancer. However, genetic association studies have hitherto been primarily conducted in women of European ancestry. Therefofre we here performed a pilot GWAS with a single nucleotide polymorphism (SNP) array 5.0 platform from $Affymetrix^{(R)}$ that contains 443,813 SNPs to search for new genetic risk factors in 89 breast cancer cases and 46 healthy women of Indonesian ancestry. The case-control association of the GWAS finding set was evaluated using PLINK. The strengths of allelic and genotypic associations were assessed using logistic regression analysis and reported as odds ratios (ORs) and P values; P values less than $1.00{\times}10^{-8}$ and $5.00{\times}10^{-5}$ were required for significant association and suggestive association, respectively. After analyzing 292,887 SNPs, we recognized 11 chromosome loci that possessed suggestive associations with breast cancer risk. Of these, however, there were only four chromosome loci with identified genes: chromosome 2p.12 with the CTNNA2 gene [Odds ratio (OR)=1.20, 95% confidence interval (CI)=1.13-1.33, $P=1.08{\times}10^{-7}$]; chromosome 18p11.2 with the SOGA2 gene (OR=1.32, 95%CI=1.17-1.44, $P=6.88{\times}10^{-6}$); chromosome 5q14.1 with the SSBP2 gene (OR=1.22, 95%CI=1.11-1.34, $P=4.00{\times}10^{-5}$); and chromosome 9q31.1 with the TEX10 gene (OR=1.24, 95%CI=1.12-1.35, $P=4.68{\times}10^{-5}$). This study identified 11 chromosome loci which exhibited suggestive associations with the risk of breast cancer among Indonesian women.

• Journal of Life Science
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• v.26 no.7
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• pp.855-867
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• 2016

The horse is relatively earlier domesticated animal species. Domesticated horses have been selected for their ability of racing, robustness, and disease-resistance. As a result, the thoroughbred horse genome has been condensed many genotypes related to exercise ability. In recent years, with the advent of NGS technologies, many studies were concentrated on finding superior genetic species in the horse genome in terms of genomics. Consequently, GWAS (Genome-wide Association study) is applied to horse genome, then genetic marker is revealed for superior racing ability. In addition, RNA-Seq is utilized as a method for analyze of whole transcript profiling in specific samples. By using this approach, specific gene expression patterns and transcript sequences can be revealed in various samples such as each individual, before and after exercise state, and each tissue. DNA methylation, a strong factor that regulate gene expression without the change of DNA sequence, have got a lot of attention. In horse genome, exercise- or individual-specific DNA methylation patterns were detected, and could be useful to develop selective marker of superior horses. MicroRNAs inhibit gene expression, and transposable elements accounted for half of the mammalian genome. These two elements are the crucial factors in functional genomics, and could be applied to the selection of superior horses. As the functional genomics and epigenomics advance, then these technologies introduced in this paper were applied to select superior horses. In this paper, the studies for selection of superior horses through genetic technologies, and development possibilities of these studies were discussed.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.1
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• pp.1-7
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• 2017

Objective: Three genome-wide association studies (GWAS) and a meta-analysis of GWAS were conducted to explore the genetic mechanisms underlying variation in pig teat number. Methods: We performed three GWAS and a meta-analysis for teat number on three pig populations, including a White Duroc${\times}$Erhualian $F_2$ resource population (n = 1,743), a Chinese Erhualian pig population (n = 320) and a Chinese Sutai pig population (n = 383). Results: We detected 24 single nucleotide polymorphisms (SNPs) that surpassed the genome-wide significant level on Sus Scrofa chromosomes (SSC) 1, 7, and 12 in the $F_2$ resource population, corresponding to four loci for pig teat number. We highlighted vertnin (VRTN) and lysine demethylase 6B (KDM6B) as two interesting candidate genes at the loci on SSC7 and SSC12. No significant associated SNPs were identified in the meta-analysis of GWAS. Conclusion: The results verified the complex genetic architecture of pig teat number. The causative variants for teat number may be different in the three populations

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.3
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• pp.309-319
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• 2017

Objective: Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods: This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results: We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion: This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1795-1801
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• 2018

Genome-Wide Association Study (GWAS) have been used to identify susceptibility genes for complex human diseases and many recent studies succeed to report common genetic factors for various diseases. Unfortunately, it is hard to understand all biological functions and mechanisms around the complex disease with GWAS only although the number of known associated genes with diseases is increased drastically because GWAS is a single locus based approach while not a gene but numerous factors may affect a disease associated pathways. PRaDA generates a combined report with genes, pathways and Gene Ontology (GO) using single nucleotide polymorphism (SNP) analysis output. The PRaDA reports not only directly associated pathways but also functionally related ones for identifying accumulated effects of low p-value SNPs. Through integrated information including indirect functional effects, user could have insights of overall disease mechanisms and markers.

• Genomics & Informatics
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• v.14 no.4
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• pp.160-165
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• 2016

Over the past decade, the detection of gene-gene interactions has become more and more popular in the field of genome-wide association studies (GWASs). The goal of the GWAS is to identify genetic susceptibility to complex diseases by assaying and analyzing hundreds of thousands of single-nucleotide polymorphisms. However, such tests are computationally demanding and methodologically challenging. Recently, a simple but powerful method, named "BOolean Operation-based Screening and Testing" (BOOST), was proposed for genome-wide gene-gene interaction analyses. BOOST was designed with a Boolean representation of genotype data and is approximately equivalent to the log-linear model. It is extremely fast, and genome-wide gene-gene interaction analyses can be completed within a few hours. However, BOOST can not adjust for covariate effects, and its type-1 error control is not correct. Thus, we considered two-step approaches for gene-gene interaction analyses. First, we selected gene-gene interactions with BOOST and applied logistic regression with covariate adjustments to select gene-gene interactions. We applied the two-step approach to type 2 diabetes (T2D) in the Korea Association Resource (KARE) cohort and identified some promising pairs of single-nucleotide polymorphisms associated with T2D.