• Asian Pacific Journal of Cancer Prevention
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• v.13 no.2
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• pp.621-623
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• 2012

To estimate the genetic susceptibility for childhood lymphoma, we conducted an association study for 23 cases and 148 controls. Total 1536 tag single nucleotide polymorphisms (SNPs) were selected in 138 candidate gene regions related to immune responses, apoptosis, the cell cycle, and DNA repair. Twelve SNPs were significantly associated with the risk of lymphoma ($P_{trend}$ <0.05) in six genes ($IL1RN$, $IL2$, $IL12RB1$, $JAK3$, $TNFRSF13B$, and $XRCC3$). The most significant association was seen for $IL2$ variant rs2069762 ($OR_{TG+GG}$ vs. TT=3.43 (1.29-9.11), $P_{trend}$=0.002, min$P$=0.005). These findings suggest that common genetic variants in $IL2$ might play a role in the pathogenesis of childhood lymphoma.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.8
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• pp.1066-1073
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• 2017

Objective: Growth-related traits are important economic traits in the swine industry. However, the genetic mechanism of growth-related traits is little known. The aim of this study was to screen the candidate genes and molecular markers associated with body dimension and body weight traits in pigs. Methods: A genome-wide association study (GWAS) on body dimension and body weight traits was performed in a White $Duroc{\times}Erhualian$ $F_2$ intercross by the illumina PorcineSNP60K Beadchip. A mixed linear model was used to assess the association between single nucleotide polymorphisms (SNPs) and the phenotypes. Results: In total, 611 and 79 SNPs were identified significantly associated with body dimension traits and body weight respectively. All SNPs but 62 were located into 23 genomic regions (quantitative trait loci, QTLs) on 14 autosomal and X chromosomes in Sus scrofa Build 10.2 assembly. Out of the 23 QTLs with the suggestive significance level ($5{\times}10^{-4}$), three QTLs exceeded the genome-wide significance threshold ($1.15{\times}10^{-6}$). Except the one on Sus scrofa chromosome (SSC) 7 which was reported previously all the QTLs are novel. In addition, we identified 5 promising candidate genes, including cell division cycle 7 for abdominal circumference, pleiomorphic adenoma gene 1 and neuropeptides B/W receptor 1 for both body weight and cannon bone circumference on SSC4, phosphoenolpyruvate carboxykinase 1, and bone morphogenetic protein 7 for hip circumference on SSC17. Conclusion: The results have not only demonstrated a number of potential genes/loci associated with the growth-related traits in pigs, but also laid a foundation for studying the genes' role and further identifying causative variants underlying these loci.

• Korean Journal of Agricultural Science
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• v.31 no.2
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• pp.97-104
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• 2004

Myostatin is a transforming growth and differentiation factor-${\beta}$ family member that acts as a negative regulator of muscle growth. Previously, mutations in the myostatin gene were known to be related to double muscling phenotypes in cattle. Because myostatin gene is highly related to muscle mass, also meat quality, in cattle, we sequenced whole myostatin mRNA and investigated the SNPs (Single Nucleotide Polymorphisms) in Korean cattle (Hanwoo). The results indicated that Hanwoo had an SNP in nt2385 and this mutation can be a useful marker with further verifications. We also investigated expression patterns of the myostatin gene from various muscle tissues and organs. Northern blotting results indicated that myostatin expression was restricted in muscles with variable expression levels. The results presented here can be used as a valuable information for meat quality related traits and muscle mass in cattle.

• Food Science of Animal Resources
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• v.38 no.4
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• pp.703-710
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• 2018

Bromodomain-containing protein 2 (BRD2) is a nuclear serine/threonine kinase involved in transcriptional regulation. We investigated the expression and association of the BRD2 gene as a candidate gene for meat quality traits in Berkshire pigs. BRD2 mRNA was expressed at relatively high levels in muscle tissue. Statistical analysis revealed that the c.1709G>C polymorphism of the BRD2 gene was significantly associated with carcass weight, meat color ($a^*$, redness), protein content, cooking loss, water-holding capacity, carcass temperatures 4, 12 and 24 h postmortem, and the 24 h postmortem pH in 384 Berkshire pigs. Therefore, this polymorphism in the porcine BRD2 gene may be used as a candidate genetic marker to improve meat quality traits in pigs.

• Genomics & Informatics
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• v.17 no.4
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• pp.40.1-40.9
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• 2019

While studies aimed at detecting and analyzing indels or single nucleotide polymorphisms within human genomic sequences have been actively conducted, studies on detecting long insertions/deletions are not easy to orchestrate. For the last 10 years, the availability of long read data of human genomes from PacBio or Nanopore platforms has increased, which makes it easier to detect long insertions/deletions. However, because long read data have a critical disadvantage due to their relatively high cost, many next generation sequencing data are produced mainly by short read sequencing machines. Here, we constructed programs to detect so-called unmapped regions (UMRs, where no reads are mapped on the reference genome), scanned 40 Korean genomes to select UMR long deletion candidates, and compared the candidates with the long deletion break points within the genomes available from the 1000 Genomes Project (1KGP). An average of about 36,000 UMRs were found in the 40 Korean genomes tested, 284 UMRs were common across the 40 genomes, and a total of 37,943 UMRs were found. Compared with the 74,045 break points provided by the 1KGP, 30,698 UMRs overlapped. As the number of compared samples increased from 1 to 40, the number of UMRs that overlapped with the break points also increased. This eventually reached a peak of 80.9% of the total UMRs found in this study. As the total number of overlapped UMRs could probably grow to encompass 74,045 break points with the inclusion of more Korean genomes, this approach could be practically useful for studies on long deletions utilizing short read data.

• Genomics & Informatics
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• v.17 no.4
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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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• 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.

• Genomics & Informatics
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• v.14 no.4
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• pp.216-221
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• 2016

Osteoporotic fractures (OFs) are critical hard outcomes of osteoporosis and are characterized by decreased bone strength induced by low bone density and microarchitectural deterioration in bone tissue. Most OFs cause acute pain, hospitalization, immobilization, and slow recovery in patients and are associated with increased mortality. A variety of genetic studies have suggested associations of genetic variants with the risk of OF. Genome-wide association studies have reported various single-nucleotide polymorphisms and copy number variations (CNVs) in European and Asian populations. To identify CNV regions associated with OF risk, we conducted a genome-wide CNV study in a Korean population. We performed logistic regression analyses in 1,537 Korean subjects (299 OF cases and 1,238 healthy controls) and identified a total of 8 CNV regions significantly associated with OF (p < 0.05). Then, one CNV region located on chromosome 20q13.12 was selected for experimental validation. The selected CNV region was experimentally validated by quantitative polymerase chain reaction. The CNV region of chromosome 20q13.12 is positioned upstream of a family of long non-coding RNAs, LINC01260. Our findings could provide new information on the genetic factors associated with the risk of OF.

• Genomics & Informatics
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• v.14 no.4
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• pp.230-233
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• 2016

Linkage disequilibrium (LD) is the non-random association between the loci and it could give us a preliminary insight into the genetic history of the population. In the present study LD patterns and effective population size (Ne) of three Korean cattle breeds along with Chinese, Japanese and Mongolian cattle were compared using the bovine Illumina SNP50 panel. The effective population size (Ne) is the number of breeding individuals in a population and is particularly important as it determines the rate at which genetic variation is lost. The genotype data in our study comprised a total of 129 samples, varying from 4 to 39 samples. After quality control there were ~29,000 single nucleotide polymorphisms (SNPs) for which $r^2$ value was calculated. Average distance between SNP pairs was 1.14 Mb across all breeds. Average $r^2$ between adjacent SNP pairs ranged between was 0.1 for Yanbian to 0.3 for Qinchuan. Effective population size of the breeds based on $r^2$ varied from 16 in Hainan to 226 in Yanbian. Amongst the Korean native breeds effective population size of Brindle Hanwoo was the least with Ne = 59 and Brown Hanwoo was the highest with Ne = 83. The effective population size of the Korean cattle breeds has been decreasing alarmingly over the past generations. We suggest appropriate measures to be taken to prevent these local breeds in their native tracts.

• Tuberculosis and Respiratory Diseases
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• v.83 no.1
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• pp.1-13
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• 2020

For the past three decades, more than a thousand of genetic studies have been performed to find out the genetic variants responsible for the risk of asthma. Until now, all of the discovered single nucleotide polymorphisms have explained genetic effects less than initially expected. Thus, clarification of environmental factors has been brought up to overcome the 'missing' heritability. The most exciting solution is epigenesis because it intervenes at the junction between the genome and the environment. Epigenesis is an alteration of genetic expression without changes of DNA sequence caused by environmental factors such as nutrients, allergens, cigarette smoke, air pollutants, use of drugs and infectious agents during pre- and post-natal periods and even in adulthood. Three major forms of epigenesis are composed of DNA methylation, histone modifications, and specific microRNA. Recently, several studies have been published on epigenesis in asthma and allergy as a powerful tool for research of genetic heritability in asthma albeit epigenetic changes are at the starting point to obtain the data on specific phenotypes of asthma. In this presentation, we mainly review the potential role of DNA CpG methylation in the risk of asthma and its sub-phenotypes including nonsteroidal anti-inflammatory exacerbated respiratory diseases.