• Journal of Animal Science and Technology
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• v.66 no.4
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• pp.702-716
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• 2024

The objective of this study was to identify genomic regions and candidate genes associated with productive traits using a total of 37,099 productive records and 6,683 single nucleotide polymorphism (SNP) data obtained from five Great-Grand-Parents (GGP) farms in Landrace. The estimated of heritabilities for days to 105 kg (AGE), average daily gain (ADG), backfat thickness (BF), and eye muscle area (EMA) were 0.49, 0.49, 0.56, and 0.23, respectively. We identified a genetic window that explained 2.05%-2.34% for each trait of the total genetic variance. We observed a clear partitioning of the four traits into two groups, and the most significant genomic region for AGE and ADG were located on the Sus scrofa chromosome (SSC) 1, while BF and EMA were located on SSC 2. We conducted Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), which revealed results in three biological processes, four cellular component, three molecular function, and six KEGG pathway. Significant SNPs can be used as markers for quantitative trait loci (QTL) investigation and genomic selection (GS) for productive traits in Landrace pig.

• Genomics & Informatics
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• v.14 no.2
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• pp.62-68
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• 2016

Osteoporosis is a medical condition of global concern, with increasing incidence in both sexes. Bone mineral density (BMD), a highly heritable trait, has been proven a useful diagnostic factor in predicting fracture. Because medical information is lacking about male osteoporotic genetics, we conducted a genome-wide association study of BMD in Korean men. With 1,176 participants, we analyzed 4,414,664 single nucleotide polymorphisms (SNPs) after genomic imputation, and identified five SNPs and three loci correlated with bone density and strength. Multivariate linear regression models were applied to adjust for age and body mass index interference. Rs17124500 ($p=6.42{\times}10^{-7}$), rs34594869 ($p=6.53{\times}10^{-7}$) and rs17124504 ($p=6.53{\times}10^{-7}$) in 14q31.3 and rs140155614 ($p=8.64{\times}10^{-7}$) in 15q25.1 were significantly associated with lumbar spine BMD (LS-BMD), while rs111822233 ($p=6.35{\times}10^{-7}$) was linked with the femur total BMD (FT-BMD). Additionally, we analyzed the relationship between BMD and five genes previously identified in Korean men. Rs61382873 (p = 0.0009) in LRP5, rs9567003 (p = 0.0033) in TNFSF11 and rs9935828 (p = 0.0248) in FOXL1 were observed for LS-BMD. Furthermore, rs33997547 (p = 0.0057) in ZBTB and rs1664496 (p = 0.0012) in MEF2C were found to influence FT-BMD and rs61769193 (p = 0.0114) in ZBTB to influence femur neck BMD. We identified five SNPs and three genomic regions, associated with BMD. The significance of our results lies in the discovery of new loci, while also affirming a previously significant locus, as potential osteoporotic factors in the Korean male population.

• Genomics & Informatics
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• v.16 no.4
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• pp.33.1-33.9
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• 2018

Recently, there have been many studies in medicine related to genetic analysis. Many genetic studies have been performed to find genes associated with complex diseases. To find out how genes are related to disease, we need to understand not only the simple relationship of genotypes but also the way they are related to phenotype. Multi-block data, which is a summation form of variable sets, is used for enhancing the analysis of the relationships of different blocks. By identifying relationships through a multi-block data form, we can understand the association between the blocks in comprehending the correlation between them. Several statistical analysis methods have been developed to understand the relationship between multi-block data. In this paper, we will use generalized canonical correlation methodology to analyze multi-block data from the Korean Association Resource project, which has a combination of single nucleotide polymorphism blocks, phenotype blocks, and disease blocks.

• Biomedical Science Letters
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• v.30 no.3
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• pp.173-180
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• 2024

Hypercholesterolemia, a form of hyperlipidemia, is a significant risk factor for cardiovascular diseases, often linked to genetic variations in the APOE gene, particularly the ε4 allele, which influences LDL cholesterol levels. This study aimed to examine the association between APOE gene variants and plasma sphingomyelin levels in Korean individuals with hypercholesterolemia, using a metabolite genome-wide association study (mGWAS) approach. Data from 7,031 participants in the Korean Genome and Epidemiology Study (KoGES) were analyzed. Genetic associations with cholesterol and sphingomyelin levels were evaluated through Exome chip analysis and metabolite profiling. Significant associations were identified between specific APOE variants (e.g., rs769449, rs4420638) and serum cholesterol levels. Additionally, certain SNPs were linked to variations in plasma sphingomyelin levels, suggesting a genetic influence on both lipid and sphingomyelin metabolism. The findings underscore the relevance of mGWAS in unraveling the genetic and metabolic pathways involved in hypercholesterolemia, offering potential biomarkers for disease risk and therapeutic targets.

• Genomics & Informatics
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• v.8 no.1
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• pp.19-27
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• 2010

To discover genetic markers for autism spectrum disorder (ASD), we previously applied genome-wide BAC array comparative genomic hybridization (array-CGH) to 28 autistic patients and 62 normal controls in Korean population, and identified that chromosomal losses on 8p23.1 and on 17p11.2 are significantly associated with autism. In this study, we developed an 8.5K ASD-specific BAC array covering 27 previously reported ASD-associated CNV loci including ours and examined whether the associations would be replicated in 8 ASD patient cell lines of four different ethnic groups and 10 Korean normal controls. As a result, a CNV-loss on 8p23.1 was found to be significantly more frequent in patients regardless of ethnicity (p<0.0001). This CNV region contains two coding genes, DEFA1 and DEFA3, which are members of DEFENSIN gene family. Two other CNVs on 17p11.2 and Xp22.31 were also distributed differently between ASDs and controls, but not significant (p=0.069 and 0.092, respectively). All the other loci did not show significant association. When these evidences are considered, the association between ASD and CNV of DEFENSIN gene seems worthy of further exploration to elucidate the pathogenesis of ASD. Validation studies with a larger sample size will be required to verify its biological implication.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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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.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.7
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• pp.833-847
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• 2010

In the past decade, there have been many advances in whole-genome sequencing in domestic animals, as well as the development of "next-generation" sequencing technologies and high-throughput genotyping platforms. Consequently, these advances have led to the creation of the high-density SNP array as a state-of-the-art tool for genetics and genomics analyses of domestic animals. The emergence and utilization of SNP arrays will have significant impacts not only on the scale, speed, and expense of SNP genotyping, but also on theoretical and applied studies of quantitative genetics, population genetics and molecular evolution. The most promising applications in agriculture could be genome-wide association studies (GWAS) and genomic selection for the improvement of economically important traits. However, some challenges still face these applications, such as incorporating linkage disequilibrium (LD) information from HapMap projects, data storage, and especially appropriate statistical analyses on the high-dimensional, structured genomics data. More efforts are still needed to make better use of the high-density SNP arrays in both academic studies and industrial applications.

• Genomics & Informatics
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• v.21 no.2
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• pp.26.1-26.9
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• 2023

Stevens-Johnson syndrome (SJS) produces a severe hypersensitivity reaction caused by Herpes simplex virus or mycoplasma infection, vaccination, systemic disease, or other agents. Several studies have investigated the genetic susceptibility involved in SJS. To provide further genetic insights into the pathogenesis of SJS, this study prioritized high-impact, SJS-associated pathogenic variants through integrating bioinformatic and population genetic data. First, we identified SJS-associated single nucleotide polymorphisms from the genome-wide association studies catalog, followed by genome annotation with HaploReg and variant validation with Ensembl. Subsequently, expression quantitative trait locus (eQTL) from GTEx identified human genetic variants with differential gene expression across human tissues. Our results indicate that two variants, namely rs2074494 and rs5010528, which are encoded by the HLA-C (human leukocyte antigen C) gene, were found to be differentially expressed in skin. The allele frequencies for rs2074494 and rs5010528 also appear to significantly differ across continents. We highlight the utility of these population-specific HLA-C genetic variants for genetic association studies, and aid in early prognosis and disease treatment of SJS.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.5
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• pp.638-642
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• 2017

Objective: This study aimed to validate the statistical evidence from the genome-wide association study (GWAS) as true-positive and to better understand the effects of the glycophorin C (GYPC) gene on serum hemoglobin traits. Methods: Our initial GWAS revealed the presence of two single nucleotide polymorphisms (SNPs) (ASGA0069038 and ALGA0084612) for the hemoglobin concentration trait (HGB) in the 2.48 Mb region of SSC15. From this target region, GYPC was selected as a promising gene that associated with serum HGB traits in pigs. SNPs within the GYPC gene were detected by sequencing. Thereafter, we performed association analysis of the variant with the serum hemoglobin level in three pig populations. Results: We identified one SNP (g.29625094 T>C) in exon 3 of the GYPC gene. Statistical analysis showed a significant association of the SNP with the serum hemoglobin level on day 20 (p<0.05). By quantitative real-time polymerase chain reaction, the GYPC gene was expressed in eight different tissues. Conclusion: These results might improve our understanding of GYPC function and provide evidence for its association with serum hemoglobin traits in the pig. These results also indicate that the GYPC gene might serve as a useful marker in pig breeding programs.

• Journal of Animal Science and Technology
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• v.63 no.1
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• pp.25-35
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• 2021

The purpose of this study is to estimate the single nucleotide polymorphism (SNP) effect for pH values affecting Berkshire meat quality. A total of 39,603 SNPs from 1,978 heads after quality control and 882 pH values were used estimate SNP effect by single step genomic best linear unbiased prediction (ssGBLUP) method. The average physical distance between adjacent SNP pairs was 61.7kbp and the number and proportion of SNPs whose minor allele frequency was below 10% were 9,573 and 24.2%, respectively. The average of observed heterozygosity and polymorphic information content was 0.32 ± 0.16 and 0.26 ± 0.11, respectively and the estimate for average linkage disequilibrium was 0.40. The heritability of pH45m and pH24h were 0.10 and 0.15 respectively. SNPs with an absolute value more than 4 standard deviations from the mean were selected as threshold markers, among the selected SNPs, protein-coding genes of pH45m and pH24h were detected in 6 and 4 SNPs, respectively. The distribution of coding genes were detected at pH45m and were detected at pH24h.