• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.207-207
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• 2022

Eating and cooking quality (ECQ) is one of the most complex quantitative traits in rice. The understanding of genetic regulation of transcript expression levels attributing to phenotypic variation in ECQ traits is limited. We integrated whole-genome resequencing, transcriptome, and phenotypic variation data from 84 Japonica accessions to build a transcriptome-wide association study (TWAS) based regulatory network. All ECQ traits showed a large phenotypic variation and significant phenotypic correlations among the traits. TWAS analysis identified a total of 285 transcripts significantly associated with six ECQ traits. Genome-wide mapping of ECQ-associated transcripts revealed 66,905 quantitative expression traits (eQTLs), including 21,747 local eQTLs, and 45,158 trans-eQTLs, regulating the expression of 43 genes. The starch synthesis-related genes (SSRGs), starch synthase IV-1 (SSIV-1), starch branching enzyme 1 (SBE1), granule-bound starch synthase 2 (GBSS2), and ADP-glucose pyrophosphorylase small subunit 2a (OsAGPS2a) were found to have eQTLs regulating the expression of ECQ associated transcripts. Further, in co-expression analysis, 130 genes produced at least one network with 22 master regulators. In addition, we developed CRISPR/Cas9-edited glbl mutant lines that confirmed the role of alpha-globulin (glbl) in starch synthesis to validate the co-expression analysis. This study provided novel insights into the genetic regulation of ECQ traits, and transcripts associated with these traits were discovered that could be used in further rice breeding.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1558-1565
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• 2020

Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ²_g, the third 0.001×σ²_g, and the fourth to 0.01×σ²_g. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance Conclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

• Genomics & Informatics
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• v.21 no.4
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• pp.48.1-48.8
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• 2023

Liver cancer is the fourth leading cause of death worldwide. Well-known risk factors include hepatitis B virus and hepatitis C virus, along with exposure to aflatoxins, excessive alcohol consumption, obesity, and type 2 diabetes. Genomic variants play a crucial role in mediating the associations between these risk factors and liver cancer. However, the specific variants involved in this process remain under-explored. This study utilized a bioinformatics approach to identify genetic variants associated with liver cancer from various continents. Single-nucleotide polymorphisms associated with liver cancer were retrieved from the genome-wide association studies catalog. Prioritization was then performed using functional annotation with HaploReg v4.1 and the Ensembl database. The prevalence and allele frequencies of each variant were evaluated using Pearson correlation coefficients. Two variants, rs2294915 and rs2896019, encoded by the PNPLA3 gene, were found to be highly expressed in the liver tissue, as well as in the skin, cell-cultured fibroblasts, and adipose-subcutaneous tissue, all of which contribute to the risk of liver cancer. We further found that these two SNPs (rs2294915 and rs2896019) were positively correlated with the prevalence rate. Positive associations with the prevalence rate were more frequent in East Asian and African populations. We highlight the utility of this population-specific PNPLA3 genetic variant for genetic association studies and for the early prognosis and treatment of liver cancer. This study highlights the potential of integrating genomic databases with bioinformatic analysis to identify genetic variations involved in the pathogenesis of liver cancer. The genetic variants investigated in this study are likely to predispose to liver cancer and could affect its progression and aggressiveness. We recommend future research prioritizing the validation of these variations in clinical settings.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.202-202
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• 2022

Recently days, soybean production in paddy field is increasing, from 4,422 ha in 2016 to 10,658 ha in 2021 in Korea. It is easy for Phytophthora stem and root rot (PSR) occurring in paddy field condition, when it is poorly drained soils with a high clay content, and temporary flooding and ponding. Therefore PSR resistant soybean cultivar is required. The objective of this study is to identify QTL region and candidate genes relating to PSR resistance of the race in main soybean cultivation area in Korea. 210 soybean materials including cultivars and germplasm were used for inoculation and genome-wide association study (GWAS). Inoculation was conducted using stem-scar method with 2 replications in 2-year for the race 3053 from Kimje and 3617 from Andong. 210 materials were genotyped with Soya SNP 180K chip, and structure analysis and association mapping were conducted with QTLMAX V2. The results of inoculation showed that survival ratio ranged from 0% to 96.7% and mean 9.7% for 3053 and ranged from 0% to 100% and mean 7.6% for 3617. Structure analysis showed linkage disequillibrium (LD) was decayed below r²=0.5 at 335kb of SNP distance. Significant SNPs (LOD>7.0) were identified in Chr 1, 2, 3, 4, 5, 11, 14, 15 for 3053 and Chr 1, 2, 3, 7, 10, 14 for 3617. Especially, LD blocks (AX-90455181;15,056,628bp~AX-90475572;15,298,872bp) in Chr 2 for 3053 and 3067 were duplicated. 29 genes were identified on these genetic regions including Glyma.02gl47000 relating to ribosome recycling factor and defense response to fungus in Soybase.

• Genomics & Informatics
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• v.6 no.3
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• pp.153-156
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• 2008

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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.21-24
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• 2016

전장유전체 연관성 연구에서 상위성 탐색은 많은 단일염기다형성 수로 인해 계산이 어렵기 때문에 네트워크에서의 탐색을 이용한 방법이 사용되고 있다. 그러나 전장유전체 연관성 연구에서 단일염기다형성들의 상위성 네트워크의 구성 역시 큰 계산 비용을 필요로 한다. 본 논문에서는 단일염기다형성과 표현형의 상호정보량을 이용한 네트워크를 구성하는데 드는 시간을 줄이는 알고리즘을 제안한다. 또한 표본 크기별로 계산 시간을 실험해 보았으며, 기존의 방법과 비교해 실행 속도가 향상됨을 보였다.

• Biomedical Science Letters
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• v.26 no.3
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• pp.238-243
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• 2020

Tuberculosis is a global public health problem and manifests itself as a difference in the genetic susceptibility of the host, along with the properties of Mycobacterium tuberculosis (MTB). The single nucleotide polymorphisms (SNPs) and candidate genes proposed in the Genome-wide association study (GWAS) on tuberculosis in a recently published Chinese population were reported. In this study, we investigated whether the genetic polymorphism of candidate genes related to tuberculosis is reproduced when targeting Koreans. The CLCN6 (rs12404124, rs198391, rs535107), DOK7 (rs1203104, rs1203103) and HLA-DRA (rs1051336) gene polymorphisms showed statistically significant results. In addition, it was also found whether it acts as an expression quantitative trait loci (eQTL) that can influence gene expression. This study confirmed that the genetic polymorphism of the three genes (CLCN6, DOK7, HLA-DRA) affects the development of tuberculosis and will help to understand the genetic specificity of tuberculosis and the interaction between pathogens and hosts.

• Journal of Plant Biotechnology
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• v.45 no.1
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• pp.17-29
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• 2018

This study was conducted to investigate a morphological trait in 294 rice accessions including Korean breeding lines. We also carried out a genome-wide association study (GWAS) to detect significant single nucleotide polymorphism markers and candidate genes affecting major agronomic traits. A Manhattan plot analysis of GWAS using morphological traits showed that phenotypic and statistical significance was associated with a chromosome in each group. The significance of SNPs that were detected in this study was investigated by comparing them with those found previously studied QTL regions related to agronomic traits. As a result, SNP (S8-19815442), which is significant with regard to leaf angle, was located in the known QTL regions. To observe gene mutations related to leaf angle in a candidate gene, Os08g31950, its sequences were compared with sequences in previously selected rice varieties. In Os08g31950, a single nucleotide mutation occurred in one region. To compare relative RNA expression levels of candidate gene Os08g31950, obtained from GWAS analysis of 294 rice accessions and related to lateral leaf angle, we investigated relative levels by selecting 10 erect leaf angle varieties and 10 horizontal leaf angle varieties and examining real-time PCR. In Os08g31950, a high level of expression and various expression patterns were observed in all tissues. Also, Os08g31950 showed higher expression levels in the erect leaf angle variety group and higher expression rates in the leaf than in the root. The candidate gene detected through GWAS would be useful in developing new rice varieties with improved yield potential through future molecular breeding.

• Biomedical Science Letters
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• v.20 no.4
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• pp.221-226
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• 2014

High-density lipoprotein (HDL) cholesterol levels are associated with decreased risk of coronary artery disease. Several genome-wide association studies (GWAS) for HDL cholesterol levels have implicated Lipoprotein lipase (LPL) as possibly being causal. Herein, the association between single nucleotide polymorphism (SNP) rs10503669 in the LPL gene and HDL cholesterol levels and triglyceride levels was tested in the Korean population. A total of 994 subjects from Seoul City were included in a replication study with LPL SNP rs10503669. SNP rs10503669 in the LPL gene was associated with mean HDL cholesterol levels (effect per allele 3.13 mg/dL, P<0.0001) and triglyceride levels (effect per allele -18.0 mg/dL, P=0.0026). Subjects with the CA/AA genotype had a 0.42-fold (range 0.23~0.77-fold) lower risk of having abnormal HDL cholesterol levels (<40 mg/dL) than subjects with the CC genotype. When analyzed by gender, the association of LPL was stronger in men than in women. This study clearly demonstrates that genetic variants in LPL influence HDL cholesterol levels and triglyceride levels in Korean adults.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.913-921
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• 2019

Objective: The objectives of this study were to compare identified informative regions through two genome-wide association study (GWAS) approaches and determine the accuracy and bias of the direct genomic value (DGV) for milk production traits in Korean Holstein cattle, using two genomic prediction approaches: single-step genomic best linear unbiased prediction (ss-GBLUP) and Bayesian Bayes-B. Methods: Records on production traits such as adjusted 305-day milk (MY305), fat (FY305), and protein (PY305) yields were collected from 265,271 first parity cows. After quality control, 50,765 single-nucleotide polymorphic genotypes were available for analysis. In GWAS for ss-GBLUP (ssGWAS) and Bayes-B (BayesGWAS), the proportion of genetic variance for each 1-Mb genomic window was calculated and used to identify informative genomic regions. Accuracy of the DGV was estimated by a five-fold cross-validation with random clustering. As a measure of accuracy for DGV, we also assessed the correlation between DGV and deregressed-estimated breeding value (DEBV). The bias of DGV for each method was obtained by determining regression coefficients. Results: A total of nine and five significant windows (1 Mb) were identified for MY305 using ssGWAS and BayesGWAS, respectively. Using ssGWAS and BayesGWAS, we also detected multiple significant regions for FY305 (12 and 7) and PY305 (14 and 2), respectively. Both single-step DGV and Bayes DGV also showed somewhat moderate accuracy ranges for MY305 (0.32 to 0.34), FY305 (0.37 to 0.39), and PY305 (0.35 to 0.36) traits, respectively. The mean biases of DGVs determined using the single-step and Bayesian methods were $1.50{\pm}0.21$ and $1.18{\pm}0.26$ for MY305, $1.75{\pm}0.33$ and $1.14{\pm}0.20$ for FY305, and $1.59{\pm}0.20$ and $1.14{\pm}0.15$ for PY305, respectively. Conclusion: From the bias perspective, we believe that genomic selection based on the application of Bayesian approaches would be more suitable than application of ss-GBLUP in Korean Holstein populations.