• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.295-308
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• 2015

We have experienced a substantial improvement in and cost-drop for genotyping that enables genetic epidemiological studies with large-scale genetic data. Genome-wide association studies have identified more than ten thousand causal variants. Many statistical methods based on linear mixed models have been developed for various goals such as estimating heritability and identifying disease susceptibility locus. Empirical results also repeatedly stress the importance of linear mixed models. Therefore, we review the statistical methods related with to linear mixed models and illustrate the meaning of their estimates.

• BMB Reports
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• v.45 no.1
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• pp.47-50
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• 2012

The International HapMap Project and the Human Genome Diversity Project (HGDP) provide plentiful resources on human genome information to the public. However, this kind of information is limited because of the small sample size in both databases. A Genome-Wide Association Study has been conducted with 8,842 Korean subjects as a part of the Korea Association Resource (KARE) project. In an effort to build a publicly available browsing system for genome data resulted from large scale KARE GWAS, we developed the KARE browser. This browser provides users with a large amount of single nucleotide polymorphisms (SNPs) information comprising 1.5 million SNPs from population-based cohorts of 8,842 samples. KAREBrowser was based on the generic genome browser (GBrowse), a web-based application tool developed for users to navigate and visualize the genomic features and annotations in an interactive manner. All SNP information and related functions are available at the web site http://ksnp.cdc. go.kr/karebrowser/.

• Proceedings of the Korean Society of Crop Science Conference
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• 2020.06a
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• pp.120-120
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• 2020

Based on the simple sequence repeat (SSR) marker, a Korean wheat core collection were established with 616 wheat accessions. Among them, the SNP genotyping for the entire genome was performed using DNA chip array to clarify the whole genome SNP profiles. Consequently, a total of 35,143 SNPs were found and we re-established a mini-core collection with 247 accessions. Population diversity and phylogenetic analysis revealed genetic diversity and relationships from the mini core set. In addition, genome-wide association study (GWAS) was performed on 19 phenotypic traits; ear type, awn length, culm length, ear length, awn color, seed coat color, culm color, ear color, loading, leaf length, leaf width, seeding stand, cold damage, weight, auricle, plant type, heading stage, maturation period, upright habit, and degree of flag leaf. The GWAS was performed using the fixed and random model circulating probability unification (FarmCPU), which identified 14 to 258 SNP loci related to 19 phenotypic traits. Our study indicates that this Korean wheat mini-core collection is a set of germplasm useful for basic and applied research with the aim of understanding and exploiting the genetic diversity of Korean wheat varieties.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.7
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• pp.938-943
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• 2016

Development of body hair is an important physiological and cellular process that leads to better adaption in tropical environments for dairy cattle. Various studies suggested a major gene and, more recently, associated genes for hairy locus in dairy cattle. Main aim of this study was to i) employ a variant of the discordant sib pair model, in which half sibs from the same sires are randomly sampled using their affection statues, ii) use various single marker regression approaches, and iii) use whole genome regression approaches to dissect genetic architecture of the hairy gene in the cattle. Whole and single genome regression approaches detected strong genomic signals from Chromosome 23. Although there is a major gene effect on hairy phenotype sourced from chromosome 23: whole genome regression approach also suggested polygenic component related with other parts of the genome. Such a result could not be obtained by any of the single marker approaches.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.3
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• pp.328-333
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• 2015

A genome wide association study was conducted using estimated breeding value (EBV) for milk production traits from 1st to 4th lactation. Significant single nucleotide polymorphism (SNP) markers were selected for each trait and the differences were compared by lactation. DNA samples were taken from 456 animals with EBV which are Holstein proven bulls whose semen is being sold or the daughters of old proven bulls whose semen is no longer being sold in Korea. High density genome wide SNP genotype was investigated and the significance of markers associated with traits was tested using the breeding value estimated by a multiple lactation model as a dependent variant. As the result of significance comparisons by lactations, several differences were found between the first lactation and subsequent lactations (from second to 4th lactation). A similar trend was noted in mean deviation and correlation of the estimated effects by lactation. Since there was a difference in the genes associated with EBV for each trait between first and subsequent lactations, a multi-lactation model in which lactation is considered as a different trait is genetically useful. Also, significant markers in all lactations and common markers for different traits were detected, which can be used as markers for quantitative trait loci exploration and marker assisted selection in milk production traits.

• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.407-420
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• 2022

Chicken dominates meat consumption because it is low in fat and high in protein and has less or no religious and cultural barriers. Recently, meat quality traits have become the focus of the poultry industry more than ever. Currently, poultry farming is focusing on meat quality to satisfy meat consumer preferences, which are mostly based on high-quality proteins and a low proportion of saturated fatty acids. Meat quality traits are polygenic traits controlled by many genes. Thus, it is difficult to improve these traits using the conventional selection method because of their low to moderate heritability. These traits include pH, colour, drop loss, tenderness, intramuscular fat (IMF), water-holding capacity, flavour, and many others. Genome-wide association studies (GWAS) are an efficient genomic tool that identifies the genomic regions and potential candidate genes related to meat quality traits. Due to their impact on the economy, meat quality traits are used as selection criteria in breeding programs. Various genes and markers related to meat quality traits in chickens have been identified. In chickens, GWAS have been successfully done for intramuscular fat (IMF) content, ultimate pH (pHu) and meat and skin colour. Moreover, GWAS have identified 7, 4, 4 and 6 potential candidate genes for IMF, pHu, meat colour and skin colour, respectively. Therefore, the current review summarizes the significant genes identified by genome-wide association studies for meat quality traits in chickens.

• BMB Reports
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• v.45 no.1
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• pp.44-46
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• 2012

Recent advances in high-throughput genotyping technologies have enabled us to conduct a genome-wide association study (GWAS) on a large cohort. However, analyzing millions of single nucleotide polymorphisms (SNPs) is still a difficult task for researchers conducting a GWAS. Several difficulties such as compatibilities and dependencies are often encountered by researchers using analytical tools, during the installation of software. This is a huge obstacle to any research institute without computing facilities and specialists. Therefore, a proper research environment is an urgent need for researchers working on GWAS. We developed BioSMACK to provide a research environment for GWAS that requires no configuration and is easy to use. BioSMACK is based on the Ubuntu Live CD that offers a complete Linux-based operating system environment without installation. Moreover, we provide users with a GWAS manual consisting of a series of guidelines for GWAS and useful examples. BioSMACK is freely available at http://ksnp.cdc.go.kr/biosmack.

• Genomics & Informatics
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• v.10 no.2
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• pp.123-127
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• 2012

Gene set analysis (GSA) is useful in interpreting a genome-wide association study (GWAS) result in terms of biological mechanism. We compared the performance of two different GSA implementations that accept GWAS p-values of single nucleotide polymorphisms (SNPs) or gene-by-gene summaries thereof, GSA-SNP and i-GSEA4GWAS, under the same settings of inputs and parameters. GSA runs were made with two sets of p-values from a Korean type 2 diabetes mellitus GWAS study: 259,188 and 1,152,947 SNPs of the original and imputed genotype datasets, respectively. When Gene Ontology terms were used as gene sets, i-GSEA4GWAS produced 283 and 1,070 hits for the unimputed and imputed datasets, respectively. On the other hand, GSA-SNP reported 94 and 38 hits, respectively, for both datasets. Similar, but to a lesser degree, trends were observed with Kyoto Encyclopedia of Genes and Genomes (KEGG) gene sets as well. The huge number of hits by i-GSEA4GWAS for the imputed dataset was probably an artifact due to the scaling step in the algorithm. The decrease in hits by GSA-SNP for the imputed dataset may be due to the fact that it relies on Z-statistics, which is sensitive to variations in the background level of associations. Judicious evaluation of the GSA outcomes, perhaps based on multiple programs, is recommended.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.17
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• pp.7443-7447
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• 2014

Aim: Little is known about the genetic associations with Basal cell carcinoma (BCC) risk in non-Caucasian populations, in which BCC is rare, as in Korea. We here conducted a pilot genome-wide association study (GWAS) in 12 patients and 48 standard controls. Method: A total of 263,511 SNPs were analyzed with the Illumina HumanOmni1 Quad v1.0 DNA Analysis BeadChip for cases and Korean HapMap 570K for controls. Results: SNP-based analyses, based on the allele genetic model with adjustment for sex and age showed suggestive associations with BCC risk for 6 SNPs with a P-value (P < 0.0005). However, these associations were not statistically significant after Bonferroni correction: rs1040503, rs2216491, rs13407683, rs4751072, rs9891263, and rs1368474. In addition, results from gene-based analyses showed suggestive associations with BCC risk for 33 candidate genes with a P-value (P <0.0005). Consistent with previous GWAS and replication studies in Caucasian populations, PADI6, RHOU and SLC45A2 were identified as having null associations with BCC (P > 0.05), likely due to the smaller sample size. Conclusions: Although this was a small-scale negative study, to our knowledge, we have conducted the first GWAS for BCC risk in an Asian population. Further large studies in non-Caucasian populations are required to achieve statistical significance and confirm these findings.

• Korean Journal of Agricultural Science
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• v.45 no.2
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• pp.238-247
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• 2018

The overall consumption of meat is increasing as the level of national income increases. The end weight is a trait closely associated with dressed meat. Genome-wide association study (GWAS) is an effective method of analyzing genetic variation and gene identification associated with a number of natural alternative traits because it can detect variations. So this paper did a GWAS analysis to identity the location on the genome related to the end weight in purebred landrace pigs and to explore the relevant candidate gene. This study identified a significant single nucleotide poly morphism (SNP) marker in chromosome 6 (ASGA0029422, $p=1.22{\times}10^{-6}$). Adhesion G protein-coupled receptor L2 (ADGRL2) was found to be the candidate gene at the identified SNP marker location. ADGRL2 genes have been found to be associated with cell development in relation to the external and internal environment of a cell. In addition, genotype and statistical analyses were done on nine variations on the exon of ADGRL2. The results show that the SNP marker (ASGA0029422, $p=1.32{\times}10^{-6}$) was significant, but the significance of the nine variations on the ADGRL2 exon was not verified. However, by performing further experiments and functional studies on other SNPs showing possible genetic ADGRL-Exon mutations, objects with high associations of high-end weights can be selected.