• Genomics & Informatics
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• 제14권4호
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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.

• Asian-Australasian Journal of Animal Sciences
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• 제31권8호
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• pp.1127-1133
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• 2018

Objective: Genome wide association study was conducted to identify and validate candidate genes associated with fatty acid composition of pork. Methods: A total of 480 purebreed Duroc pigs were genotyped using IlluminaPorcine60k bead chips while the association test was implemented following genome-wide rapid association using Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approach. Results: A total of 25, 29, and 16 single nucleotide polymorphisms (SNPs) were significantly associated with stearic (18:0), oleic (18:1) and saturated fatty acids (SFA), respectively. Genome wide significant variants were located on the same region of swine chromosome 14 (SSC14) that spanned from 120 to 124 Mb. Top SNP ALGA008191 was located at 5 kb near the stearoyl-CoA desaturase (SCD) gene. This gene is directly involved in desaturation of stearic acid into oleic acid. General relationship of significant SNPs showed high linkage disequilibrium thus genome-wide signals was attributed to SCD gene. However, understanding the role of other genes like elongation of very long chain fatty acids-3 (ELOVL3) located on this chromosomal segment might help in further understanding of metabolism and biosynthesis of fatty acids. Conclusion: Overall, this study provides evidence that validates SCD gene as strong candidate gene associated with fatty acid composition in Duroc pigs. Moreover, this study confirms significant SNPs near ELOVL3 gene.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.192-192
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• 2022

Sweetpotato is rich in starch, which is converted to sugar during storage due to enzymatic hydrolysis. The sugar content of sweetpotato is a component related to taste and storability. In this study, the sugar content (fructose, glucose, maltose, sucrose and total sugar content) of 94 genotypes was evaluated and the GWAS (Genome-Wide Association Study) was conducted to search for candidate genes for sugar content. The fructose and glucose content were 0.2 ~ 8.8 and 0.2 ~ 9.4 g/100g, respectively. The maltose, sucrose and total sugar content were 0.2 ~ 9.1,3.2 - 30.0 and 7.9 ~ 40.2 g/100g, respectively. The fructose and glucose showed a positive correlation (0.98). The 94 genotypes were genotyped with genotyping-by-sequencing (GBS) and aligned against the reference genome sequences of sweetpotato. The GBS libraries from 94 genotypes were sequenced on an Illumina HiSeqXten system, and 1,339,892 SNPs (Single Nucleotide Polymorphism) were generated. Filtering for < 60% missing rate and > 0.05 minor allele frequency resulted in a total of 44,255 SNPs used in GWAS. The GAPIT (Genome Association and Prediction Integrated Tool) was used to conduct based on the mean of sugar content with a Bonferroni-corrected chromosome-wide significance threshold with a -logio(P) of 5.95. The significant SNPs were obtained with fructose (seven), glucose (six), maltose (four) and sucrose (nine). There were several genes related to sugar content around the significant SNPs such as sugar transport protein 8-like, probable galactose-1 -phosphate uridyltransferase-like and beta-amylase. These results will contribute to understanding of sugar content and conversion in sweetpotato.

• 대한조현병학회지
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• 제23권2호
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• pp.65-70
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• 2020

Objectives: This study aimed to explore whether common genetic variants that confer the risk of schizophrenia have similar effects between Korean and European ancestries using the polygenic risk score (PRS) analysis. Methods: Study subjects included 713 Korean patients with schizophrenia and 497 healthy controls. The Korea Biobank array was used for genotyping. Summary statistics of the most recent genome-wide association study (GWAS) of the European population were used as baseline data to calculate PRS. Logistic regression was conducted to determine the association between calculated PRS of European patients with schizophrenia and clinical diagnosis of schizophrenia in the Korean population. Results: Schizophrenia PRS was significantly higher in patients with schizophrenia than in healthy controls. The PRS at the p-value threshold of 0.5 best explained the variance of schizophrenia (R²=0.028, p=4.4×10^-6). The association was significant after adjusting for age and sex (odds ratio=1.34, 95% confidence interval=1.19-1.51, p=1.1×10^-6). The pattern of the association remained similar across different p-value thresholds (0.01-1). Conclusion: Schizophrenia PRS calculated using the European GWAS data showed a significant association with the clinical diagnosis of schizophrenia in the Korean population. Results suggest overlapping genetic risk variants between the two populations.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.58-58
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• 2017

The advent of next generation sequencing technology has elicited plenty of sequencing data available in agriculturally relevant plant species. For most crop species, it is too expensive to obtain the whole genome sequence data with sufficient coverage. Thus, many approaches have been developed to bring down the cost of NGS. Genotyping-by-sequencing (GBS) is a cost-effective genotyping method for complex genetic populations. GBS can be used for the analysis of genomic selection (GS), genome-wide association study (GWAS) and constructing haplotype and genetic linkage maps in a variety of plant species. For efficiently dealing with plant GBS data, the TASSEL-GBS pipeline is one of the most popular choices for many researchers. TASSEL-GBS is JAVA based a software package to obtain genotyping data from raw GBS sequences. Here, we describe application of GBS and bioinformatics pipeline of TASSEL-GBS for analyzing plant genetics data.

• Asian-Australasian Journal of Animal Sciences
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• 제27권3호
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• pp.303-309
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• 2014

The increasing importance of meat quality has implications for animal breeding programs. Research has revealed much about the genetic background of pigs, and many studies have revealed the importance of various genetic factors. Since meat quality is a complex trait which is affected by many factors, consideration of the overall phenotype is very useful to study meat quality. For integrating the phenotypes, we used principle component analysis (PCA). The significant SNPs refer to results of the GRAMMAR method against PC1, PC2 and PC3 of 14 meat quality traits of 181 Duroc pigs. The Genome-wide association study (GWAS) found 26 potential SNPs affecting various meat quality traits. The loci identified are located in or near 23 genes. The SNPs associated with meat quality are in or near five genes (ANK1, BMP6, SHH, PIP4K2A, and FOXN2) and have been reported previously. Twenty-five of the significant SNPs also located in meat quality-related QTL regions, these result supported the QTL effect indirectly. Each single gene typically affects multiple traits. Therefore, it is a useful approach to use integrated traits for the various traits at the same time. This innovative approach using integrated traits could be applied on other GWAS of complex-traits including meat-quality, and the results will contribute to improving meat-quality of pork.

• Genomics & Informatics
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• 제16권3호
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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.

• 한국수산과학회지
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• 제56권4호
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• pp.411-418
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• 2023

Genome wide association studies (GWAS) identify genetic loci associated with quantitative traits in genomic selection. Although several studies have compared performance of various algorithms, no study compares them in olive flounder Paralichthys olivaceus. This study compared the GWAS results of four mixed linear model (MLM) algorithms and one Fixed and random model Circulating Probability Unification (FarmCPU) algorithm in olive flounder. Considering gender and genetic association matrices as fixed and random effects, the MLM had stable performance without inflation for λ_GC (genomic inflation factor) of -log₁₀P. The FarmCPU algorithm had some appropriate λ_GC of -log₁₀P, and an upward tail was identified in quantile-quantile plots. Therefore, the models were suitable for detecting genetic variants associated with olive flounder growth traits. Moreover, significant genotypes appeared several times at chromosome 22, around which quantitative trait loci are expected to exist. Finally, in both models, some of the most genetic variants were found in genes related to growth traits, confirming their reliability. These results will be helpful when applied to the genomic selection of olive flounder growth traits in the future.

• Asian-Australasian Journal of Animal Sciences
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• 제32권7호
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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.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.158-158
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• 2017

The purpose of this study was to identify the candidate genes involved in selenium content in brown rice. Rice (Oryza sativa L.) was important crop including diverse functional substance such as carbohydrate, protein, lysine and tocopherol, mineral. Especially, selenium as nutritionally important minerals, it was known to activate the immune system, antioxidant effect and inhibition of carcinogenesis. Also recommended daily requirements of the United States and the United Kingdom were 55 to 90 ug for selenium. Therefore, selenium content in brown rice of core-set were analyzed by using ICP-MS (Inductively Coupled Plasma Mass Spectrometer) and GWAS (Genome Wide Association Study) was conducted to search for candidate genes in this study. The new natural variants identified through haplotyping analysis would be useful to develop new rice varieties with improved storage ability of the valuable mineral through the future molecular breeding.