• Journal of Animal Science and Technology
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• 제65권1호
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• pp.57-68
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• 2023

Flavor is an important sensory trait of chicken meat. The free amino acid (FAA) and nucleotide (NT) components of meat are major factors affecting meat flavor during the cooking process. As a genetic approach to improve meat flavor, we performed a genome-wide association study (GWAS) to identify the potential candidate genes related to the FAA and NT components of chicken breast meat. Measurements of FAA and NT components were recorded at the age of 10 weeks from 764 and 767 birds, respectively, using a White leghorn and Yeonsan ogye crossbred F2 chicken population. For genotyping, we used 60K Illumina single-nucleotide polymorphism (SNP) chips. We found a total of nine significant SNPs for five FAA traits (arginine, glycine, lysine, threonine content, and the essential FAAs and one NT trait (inosine content), and six significant genomic regions were identified, including three regions shared among the essential FAAs, arginine, and inosine content traits. A list of potential candidate genes in significant genomic regions was detected, including the KCNRG, KCNIP4, HOXA3, THSD7B, and MMUT genes. The essential FAAs had significant gene regions the same as arginine. The genes related to arginine content were involved in nitric oxide metabolism, while the inosine content was possibly affected by insulin activity. Moreover, the threonine content could be related to methylmalonyl-CoA mutase. The genes and SNPs identified in this study might be useful markers in chicken selection and breeding for chicken meat flavor.

• Genomics & Informatics
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• 제12권3호
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• pp.127-133
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• 2014

Gastritis is a major disease that has the potential to grow as gastric cancer. Gastric cancer is a very common cancer, and it is related to a very high mortality rate in Korea. This disease is known to have various reasons, including infection with Helicobacter pylori, dietary habits, tobacco, and alcohol. The incidence rate of gastritis has reported to differ between age, population, and gender. However, unlike other factors, there has been no analysis based on gender. So, we examined the high risk factors of gastritis in each gender in the Korean population by focusing on sex. We performed an analysis of 120 clinical characteristics and genome-wide association studies (GWAS) using 349,184 single-nucleotide polymorphisms from the results of Anseong and Ansan cohort study in the Korea Association Resource (KARE) project. As the result, we could not prove a strong relation with these factors and gastritis or gastric ulcer in the GWAS. However, we confirmed several already-known risk factors and also found some differences of clinical characteristics in each gender using logistic regression. As a result of the logistic regression, a relation with hyperlipidemia, coronary artery disease, myocardial infarction, hyperlipidemia therapy, hypotensive or antihypotensive drug, diastolic blood pressure, and gastritis was seen in males; the results of this study suggest that vascular disease has a potential association with gastritis in males.

• Genomics & Informatics
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• 제12권4호
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• pp.165-170
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• 2014

Genome-wide association (GWA) studies have found many important genetic variants that affect various traits. Since these studies are useful to investigate untyped but causal variants using linkage disequilibrium (LD), it would be useful to explore the haplotypes of single-nucleotide polymorphisms (SNPs) within the same LD block of significant associations based on high-density variants from population references. Here, we tried to make a haplotype catalog affecting body mass index (BMI) through an integrative analysis of previously published whole-genome next-generation sequencing (NGS) data of 7 representative Korean individuals and previously known Korean GWA signals. We selected 435 SNPs that were significantly associated with BMI from the GWA analysis and searched 53 LD ranges nearby those SNPs. With the NGS data, the haplotypes were phased within the LDs. A total of 44 possible haplotype blocks for Korean BMI were cataloged. Although the current result constitutes little data, this study provides new insights that may help to identify important haplotypes for traits and low variants nearby significant SNPs. Furthermore, we can build a more comprehensive catalog as a larger dataset becomes available.

• BMB Reports
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• 제45권5호
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• pp.305-310
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• 2012

Allergic diseases such as asthma, allergic rhinitis, and atopic dermatitis are heterogeneous diseases characterized by multiple symptoms and phenotypes. Recent advancements in genetic study enabled us to identify disease associated genetic factors. Numerous genome-wide association studies (GWAS) have revealed multiple associated loci for allergic diseases. However, the majority of previous studies have been conducted in populations of European ancestry. Moreover, the associations of single nucleotide polymorphisms (SNPs) with allergic diseases have not been studied amongst the large-scale general Korean population. Herein, we performed the replication study to validate the previous variants, known to be associated with allergic diseases, in the Korean population. In this study, we categorized three allergic related phenotypes, one allergy and two asthma related phenotypes, based on self-reports of physician diagnosis and their symptoms from 8,842 samples. As a result, we found nominally significant associations of 6 SNPs with at least one allergic related phenotype in the Korean population.

• Genomics & Informatics
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• 제8권3호
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• pp.131-137
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• 2010

Genome-wide association studies (GWASs) have greatly contributed to the identification of common variants responsible for numerous complex traits. There are, however, unavoidable limitations in detecting causal and/or rare variants for traits in this approach, which depends on an LD-based tagging SNP microarray chip. In an effort to detect potential casual and/or rare variants for complex traits, such as type 2 diabetes (T2D) and triglycerides (TGs), we conducted a targeted resequencing of loci identified by the Korea Association REsource (KARE) GWAS. The target regions for resequencing comprised whole exons, exon-intron boundaries, and regulatory regions of genes that appeared within 1 Mb of the GWA signal boundary. From 124 individuals selected in population-based cohorts, a total of 0.7 Mb target regions were captured by the NimbleGen sequence capture 385K array. Subsequent sequencing, carried out by the Roche 454 Genome Sequencer FLX, generated about 110,000 sequence reads per individual. Mapping of sequence reads to the human reference genome was performed using the SSAHA2 program. An average of 62.2% of total reads was mapped to targets with an average 22X-fold coverage. A total of 5,983 SNPs (average 846 SNPs per individual) were called and annotated by GATK software, with 96.5% accuracy that was estimated by comparison with Affymetrix 5.0 genotyped data in identical individuals. About 51% of total SNPs were singletons that can be considered possible rare variants in the population. Among SNPs that appeared in exons, which occupies about 20% of total SNPs, 304 nonsynonymous singletons were tested with Polyphen to predict the protein damage caused by mutation. In total, we were able to detect 9 and 6 potentially functional rare SNPs for T2D and triglycerides, respectively, evoking a further step of replication genotyping in independent populations to prove their bona fide relevance to traits.

• Genomics & Informatics
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• 제6권1호
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• pp.1-7
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• 2008

The widespread presence of large-scale genomic variations, termed copy number variation (CNVs), has been recently recognized in phenotypically normal individuals. Judging by the growing number of reports on CNVs, it is now evident that these variants contribute significantly to genetic diversity in the human genome. Like single nucleotide polymorphisms (SNPs), CNVs are expected to serve as potential biomarkers for disease susceptibility or drug responses. However, the technical and practical concerns still remain to be tackled. In this review, we examine the current status of CNV DBs and research, including the ongoing efforts of CNV screening in the human genome. We also discuss the characteristics of platforms that are available at the moment and suggest the potential of CNVs in clinical research and application.

• Genomics & Informatics
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• 제17권4호
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• pp.47.1-47.12
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• 2019

The achievements of genome-wide association studies have suggested ways to predict diseases, such as type 2 diabetes (T2D), using single-nucleotide polymorphisms (SNPs). Most T2D risk prediction models have used SNPs in combination with demographic variables. However, it is difficult to evaluate the pure additive contribution of genetic variants to classically used demographic models. Since prediction models include some heritable traits, such as body mass index, the contribution of SNPs using unmatched case-control samples may be underestimated. In this article, we propose a method that uses propensity score matching to avoid underestimation by matching case and control samples, thereby determining the pure additive contribution of SNPs. To illustrate the proposed propensity score matching method, we used SNP data from the Korea Association Resources project and reported SNPs from the genome-wide association study catalog. We selected various SNP sets via stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and the elastic-net (EN) algorithm. Using these SNP sets, we made predictions using SLR, LASSO, and EN as logistic regression modeling techniques. The accuracy of the predictions was compared in terms of area under the receiver operating characteristic curve (AUC). The contribution of SNPs to T2D was evaluated by the difference in the AUC between models using only demographic variables and models that included the SNPs. The largest difference among our models showed that the AUC of the model using genetic variants with demographic variables could be 0.107 higher than that of the corresponding model using only demographic variables.

• Genomics & Informatics
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• 제10권4호
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• pp.256-262
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• 2012

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene ($G{\times}G$) interactions. However, the biological interpretation of $G{\times}G$ interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified $G{\times}G$ interactions. The proposed network graph analysis consists of three steps. The first step is for performing $G{\times}G$ interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified $G{\times}G$ interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform $G{\times}G$ interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified $G{\times}G$ interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of $G{\times}G$ interactions.

• Asian-Australasian Journal of Animal Sciences
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• 제27권10호
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• pp.1406-1410
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• 2014

Age at first calving is an important trait for achieving earlier reproductive performance. To detect quantitative trait loci (QTL) for reproductive traits, a genome wide association study was conducted on the 96 Hanwoo cows that were born between 2008 and 2010 from 13 sires in a local farm (Juk-Am Hanwoo farm, Suncheon, Korea) and genotyped with the Illumina 50K bovine single nucleotide polymorphism (SNP) chips. Phenotypes were regressed on additive and dominance effects for each SNP using a simple linear regression model after the effects of birth-year-month and polygenes were considered. A forward regression procedure was applied to determine the best set of SNPs for age at first calving. A total of 15 QTL were detected at the comparison-wise 0.001 level. Two QTL with strong statistical evidence were found at 128.9 Mb and 111.1 Mb on bovine chromosomes (BTA) 2 and 7, respectively, each of which accounted for 22% of the phenotypic variance. Also, five significant SNPs were detected on BTAs 10, 16, 20, 26, and 29. Multiple QTL were found on BTAs 1, 2, 7, and 14. The significant QTLs may be applied via marker assisted selection to increase rate of genetic gain for the trait, after validation tests in other Hanwoo cow populations.

• 생명과학회지
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• 제26권7호
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• pp.855-867
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• 2016

말은 인류에 의해 상대적으로 일찍 가축화된 종 중 하나로써, 경주능력, 강건성 및 항병성 등과 같은 능력을 위해 인공적으로 선택되었다. 그 결과, 현재 경주마로 많이 쓰이고 있는 서러브레드의 게놈은 운동 능력에 특화된 유전자형을 많이 갖고 있다. 최근 NGS 기술의 도래와 함께 전장게놈을 대상으로 경주마의 우수한 유전형질을 찾는 연구가 유전체학의 관점에서 진행되고 있다. 그 결과 말의 게놈에 대해서도 GWAS (Genome-wide Association study)가 적용되고 있고, 우수 경주능력을 나타내는 유전자 마커가 발굴되고 있다. 아울러, 특정 샘플의 전장 전사체를 NGS 기법으로 분석할 수 있는 RNA-Seq 기법 역시 활용되고 있는데, 이를 통하여 각 개체별, 운동 전후, 한 개체의 조직별 특정 유전자의 발현 양상과 함께 전사체의 서열 등을 확인할 수 있다. DNA 서열의 변화 없이 유전자 발현을 조절하는 강력한 인자로써 DNA methylation이 주목받고 있다. 말의 게놈에 있어서도 운동 특이적 또는 개체 특이적 DNA methylation 패턴을 보여 주었고, 이는 우수 개체 선정을 위한 마커 개발에 좋은 단서를 제공해 줄 것이다. 유전자 발현을 억제하는 miRNA와, 포유동물의 유전체 내 절반 정도를 차지하고 있는 이동성 유전인자는 기능유전체 연구에 있어서 중요한 인자들이다. 이들은 인간의 게놈에서 많이 연구가 되어 왔으나, 말에서의 연구는 현재 미미한 실정이다. 하지만, 현재까지 말에서 되어 있는 위의 두 인자에 대한 연구 현황을 알아보고, 차후 우수 마 선별 연구에 적용될 가능성을 제시하였다. 기능유전체 및 후성유전체 분석 기법이 발전함에 따라 말에서도 본 연구에서 소개된 여러 가지 분석 기법이 적용되고, 우수한 경주마를 선정하는 데 많은 도움을 줄 것으로 기대하고 있다. 이에 현재까지의 우수한 경주마를 선택하기 위한 많은 연구들 및, 말 연구에 대한 앞으로의 발전 가능성에 대해 고찰하고 토의하였다.