• Journal of Animal Science and Technology
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• 제65권6호
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• pp.1194-1204
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• 2023

Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome-wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b^*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%-4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b^*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.

• Genomics & Informatics
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• 제21권3호
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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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• 제10권2호
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• pp.106-109
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• 2012

Pulse rate is known to be related to diverse phenotypes, such as cardiovascular diseases, lifespan, arrhythmia, hypertension, lipids, diabetes, and menopause. We have reported two genomewide significant genetic loci responsible for the variation in pulse rate as a part of the Korea Association Resource (KARE) project, the genomewide association study (GWAS) that was conducted with 352,228 single nucleoride polymorphisms typed in 8,842 subjects in the Korean population. GJA1 was implied as a functionally causal gene for pulse rate from the KARE study, but lacked evidence of replication. To re-evaluate the association of a locus near GJA1 with pulse rate, we looked up this signal in another GWAS conducted in a Health Examinee-shared cohort of 3,703 samples. Not only we were able to confirm two pulse rate loci (1q32.2a near CD46 and 6q22.13c near LOCL644502) identified in the KARE GWAS, we also replicated a locus (6q22.31c) near GJA1 by the lookup in the Health Examinee GWAS. Considering that the GJA1-encoded protein is a major component of cardiac gap junctions, a functional study might be necessary to validate its genuine molecular biological role in the synchronized contraction of the heart.

• Animal Bioscience
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• 제37권5호
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• pp.807-816
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• 2024

Objective: This study aims to identify the significant regions and candidate genes of growth-related traits (adjusted backfat thickness [ABF], average daily gain [ADG], and days to 90 kg [DAYS90]) in Korean commercial GGP pig (Duroc, Landrace, and Yorkshire) populations. Methods: A genome-wide association study (GWAS) was performed using single-nucleotide polymorphism (SNP) markers for imputation to Illumina PorcineSNP60. The BayesB method was applied to calculate thresholds for the significance of SNP markers. The identified windows were considered significant if they explained ≥1% genetic variance. Results: A total of 28 window regions were related to genetic growth effects. Bayesian GWAS revealed 28 significant genetic regions including 52 informative SNPs associated with growth traits (ABF, ADG, DAYS90) in Duroc, Landrace, and Yorkshire pigs, with genetic variance ranging from 1.00% to 5.46%. Additionally, 14 candidate genes with previous functional validation were identified for these traits. Conclusion: The identified SNPs within these regions hold potential value for future marker-assisted or genomic selection in pig breeding programs. Consequently, they contribute to an improved understanding of genetic architecture and our ability to genetically enhance pigs. SNPs within the identified regions could prove valuable for future marker-assisted or genomic selection in pig breeding programs.

• 대한의생명과학회지
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• 제30권2호
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• pp.86-95
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• 2024

Sleep varies from individual to individual and is essential for maintaining good health, making it important for the health of individuals and societies. Sleep duration is influenced by both genetic and environmental factors, and sleep duration has been reported to be associated with obesity, metabolic syndrome, diabetes, and cardiovascular disease. In this study, we identified SNPs associated with sleep duration from the genome-wide association study (GWAS) catalog and compared them with the Korean Association Resource (KARE) cohort to find SNPs associated with sleep duration in Koreans and to identify the genes involved. The results showed that rs1553132, a SNP in the GRM5 gene, was identified as an SNP associated with sleep duration in both the GWAS catalog and the KARE cohort, and rs1504096 was the first SNP found to be associated with sleep duration in Koreans. It was found that having a minor allele tended to increase sleep duration. These results confirm the reproducibility of the association between sleep duration and the GRM5 gene in Koreans and provide a basis for using the associated SNPs as genetic determinants of sleep duration.

• 농업과학연구
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• 제49권3호
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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.

• Genomics & Informatics
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• 제15권4호
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• pp.178-182
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• 2017

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

• Asian Pacific Journal of Cancer Prevention
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• 제15권17호
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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.

• Genomics & Informatics
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• 제9권2호
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• pp.59-63
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• 2011

Obesity provokes many serious human diseases, including various cardiovascular diseases and diabetes. Body mass index (BMI) is a highly heritable trait that is broadly used to diagnose obesity. To identify genetic loci associated with obesity in Asians, we conducted a genome-wide association study (GWAS) of a population of Korean adults (n=6,742, age 40~60 years) and detected six BMI risk loci (TNR, FAM124B, RGS12, NFE2L3, MC4R and FTO) having p< $1{\times}10^{-5}$. However, in the replication study, only melanocortin 4 receptor gene (MC4R) (rs9946888, p=$4.58{\times}10^{-7}$) was replicated with marginal significance (p<0.05) in the second cohort (n=5,102, age 40~60 years). This study indicates that each locus associated with BMI has very weak genetic effect.

• Journal of Preventive Medicine and Public Health
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• 제42권6호
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• pp.356-359
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• 2009

In the more than 100 genome wide association studies (GWAS) conducted in the past 5 years, more than 250 genetic loci contributing to more than 40 common diseases and traits have been identified. Whilst many genes have been linked to a trait, both their individual and combined effects are small and unable to explain earlier estimates of heritability. Given the rapid changes in disease incidence that cannot be accounted for by changes in diagnostic practises, there is need to have well characterized exposure information in addition to genomic data for the study of gene-environment interactions. The case-control and cohort study designs are most suited for studying associations between risk factors and occurrence of an outcome. However, the case control study design is subject to several biases and hence the preferred choice of the prospective cohort study design in investigating geneenvironment interactions. A major limitation of utilising the prospective cohort study design is the long duration of follow-up of participants to accumulate adequate outcome data. The GWAS paradigm is a timely reminder for traditional epidemiologists who often perform one- or few-at-a-time hypothesis-testing studies with the main hallmarks of GWAS being the agnostic approach and the massive dataset derived through large-scale international collaborations.