• Genomics & Informatics
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• v.14 no.4
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• pp.166-172
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• 2016

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.114-114
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• 2017

The aim of this research is to improve Korean lettuce varieties in terms of Fusarium wilt, bolting under hot weather and nutritional function applying genomics approaches. To find related gene/molecular markers, we selected 96 lettuce varieties which are popular in domestic fresh vegetable markets. To construct frame works of the genomic approaches, we exploited GBS(Genotyping by Sequencing) and found total 61,407 SNPs from lettuce whole genomes (MAF>0.02). We observed that Three SNPs array per 100kb of lettuce genome. Average LD decay is expected to expand up to 3.9M(million)bp. Thus, we concluded that about 104 SNPs exist within a LD, which is sufficient to use GWAS(Genome-wide Association Study) to explore the useful gene/molecular markers. In addition, we optimized mass screening method to evaluate disease resistance levels against Fusarium wilt and are testing the bolting sensitivity during summer growing season for those lettuce allele mining set.

• Tuberculosis and Respiratory Diseases
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• v.76 no.3
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• pp.105-113
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• 2014

From January 2012 up until March 2013, many articles with huge clinical importance in asthma were published based on large numbered clinical trials or meta-analysis. The main subjects of these studies were the new therapeutic plan based on the asthma phenotype or efficacy along with the safety issues regarding the current treatment guidelines. For efficacy and safety issues, inhaled corticosteroid tapering strategy or continued long-acting beta agonists use was the major concern. As new therapeutic trials, monoclonal antibodies or macrolide antibiotics based on inflammatory phenotypes have been under investigation, with promising preliminary results. There were other issues on the disease susceptibility or genetic background of asthma, particularly for the "severe asthma" phenotype. In the era of genome and pharmacogenetics, there have been extensive studies to identify susceptible candidate genes based on the results of genome wide association studies (GWAS). However, for severe asthma, which is where most of the mortality or medical costs develop, it is very unclear. Moreover, there have been some efforts to find important genetic information in order to predict the possible disease progression, but with few significant results up until now. In conclusion, there are new on-going aspects in the phenotypic classification of asthma and therapeutic strategy according to the phenotypic variations. With more pharmacogenomic information and clear identification of the "severe asthma" group even before disease progression from GWAS data, more adequate and individualized therapeutic strategy could be realized in the future.

• Genomics & Informatics
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• v.20 no.1
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• pp.9.1-9.6
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• 2022

Mendelian randomization (MR) uses genetic variation as a natural experiment to investigate the causal effects of modifiable risk factors (exposures) on outcomes. Two-sample Mendelian randomization (2SMR) is widely used to measure causal effects between exposures and outcomes via genome-wide association studies. 2SMR can increase statistical power by utilizing summary statistics from large consortia such as the UK Biobank. However, the first-order term approximation of standard error is commonly used when applying 2SMR. This approximation can underestimate the variance of causal effects in MR, which can lead to an increased false-positive rate. An alternative is to use the second-order approximation of the standard error, which can considerably correct for the deviation of the first-order approximation. In this study, we simulated MR to show the degree to which the first-order approximation underestimates the variance. We show that depending on the specific situation, the first-order approximation can underestimate the variance almost by half when compared to the true variance, whereas the second-order approximation is robust and accurate.

• Journal of Animal Science and Technology
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• v.64 no.5
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• pp.830-841
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• 2022

Genetic analysis has great potential as a tool to differentiate between different species and breeds of livestock. In this study, the optimal combinations of single nucleotide polymorphism (SNP) markers for discriminating the Yeonsan Ogye chicken (Gallus gallus domesticus) breed were identified using high-density 600K SNP array data. In 3,904 individuals from 198 chicken breeds, SNP markers specific to the target population were discovered through a case-control genome-wide association study (GWAS) and filtered out based on the linkage disequilibrium blocks. Significant SNP markers were selected by feature selection applying two machine learning algorithms: Random Forest (RF) and AdaBoost (AB). Using a machine learning approach, the 38 (RF) and 43 (AB) optimal SNP marker combinations for the Yeonsan Ogye chicken population demonstrated 100% accuracy. Hence, the GWAS and machine learning models used in this study can be efficiently utilized to identify the optimal combination of markers for discriminating target populations using multiple SNP markers.

• Genomics & Informatics
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• v.20 no.4
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• pp.48.1-48.7
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• 2022

Penalized regression has been widely used in genome-wide association studies for joint analyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficients from the model by shrinking them to zero. To handle group structures, such as genes and pathways, several modified Lasso penalties have been proposed, including group Lasso and sparse group Lasso. Group Lasso ensures sparsity at the level of pre-defined groups, eliminating unimportant groups. Sparse group Lasso performs group selection as in group Lasso, but also performs individual selection as in Lasso. While these sparse methods are useful in high-dimensional genetic studies, interpreting the results with many groups and coefficients is not straightforward. Lasso's results are often expressed as trace plots of regression coefficients. However, few studies have explored the systematic visualization of group information. In this study, we propose a multi-level polar Lasso (MP-Lasso) chart, which can effectively represent the results from group Lasso and sparse group Lasso analyses. An R package to draw MP-Lasso charts was developed. Through a real-world genetic data application, we demonstrated that our MP-Lasso chart package effectively visualizes the results of Lasso, group Lasso, and sparse group Lasso.

• Journal of Plant Biotechnology
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• v.43 no.3
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• pp.261-271
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• 2016

Citrus is an economically important fruit crop widely growing worldwide. However, citrus production largely depends on natural hybrid selection and bud sport mutation. Unique botanical features including long juvenility, polyembryony, and QTL that controls major agronomic traits can hinder the development of superior variety by conventional breeding. Diverse factors including drastic changes of citrus production environment due to global warming and changes in market trends require systematic molecular breeding program for early selection of elite candidates with target traits, sustainable production of high quality fruits, cultivar diversification, and cost-effective breeding. Since the construction of the first genetic linkage map using isozymes, citrus scientists have constructed linkage maps using various DNA-based markers and developed molecular markers related to biotic and abiotic stresses, polyembryony, fruit coloration, seedlessness, male sterility, acidless, morphology, fruit quality, seed number, yield, early fruit setting traits, and QTL mapping on genetic maps. Genes closely related to CTV resistance and flesh color have been cloned. SSR markers for identifying zygotic and nucellar individuals will contribute to cost-effective breeding. The two high quality citrus reference genomes recently released are being efficiently used for genomics-based molecular breeding such as construction of reference linkage/physical maps and comparative genome mapping. In the near future, the development of DNA molecular markers tightly linked to various agronomic traits and the cloning of useful and/or variant genes will be accelerated through comparative genome analysis using citrus core collection and genome-wide approaches such as genotyping-by-sequencing and genome wide association study.

• Animal Bioscience
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• v.35 no.9
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• pp.1303-1313
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• 2022

Objective: The current study aimed to perform whole-genome resequencing of Chinese indigenous Mongolian sheep breeds including Ujimqin, Sunit, and Wu Ranke sheep breeds (UJMQ, SNT, WRK) and deeply analyze genetic variation, population structure, domestication, and selection for domestication traits among these Mongolian sheep breeds. Methods: Blood samples were collected from a total of 60 individuals comprising 20 WRK, 20 UJMQ, and 20 SNT. For genome sequencing, about 1.5 ㎍ of genomic DNA was used for library construction with an insert size of about 350 bp. Pair-end sequencing were performed on Illumina NovaSeq platform, with the read length of 150 bp at each end. We then investigated the domestication and signatures of selection in these sheep breeds. Results: According to the population and demographic analyses, WRK and SNT populations were very similar, which were different from UJMQ populations. Genome wide association study identified 468 and 779 significant loci from SNT vs UJMQ, and UJMQ vs WRK, respectively. However, only 3 loci were identified from SNT vs WRK. Genomic comparison and selective sweep analysis among these sheep breeds suggested that genes associated with regulation of secretion, metabolic pathways including estrogen metabolism and amino acid metabolism, and neuron development have undergone strong selection during domestication. Conclusion: Our findings will facilitate the understanding of Chinese indigenous Mongolian sheep breeds domestication and selection for complex traits and provide a valuable genomic resource for future studies of sheep and other domestic animal breeding.

• Animal Bioscience
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• v.36 no.1
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• pp.29-42
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• 2023

Objective: Pigs, an ideal biomedical model for human diseases, suffer from about 50% early embryonic and fetal death, a major cause of fertility loss worldwide. However, identifying the causal variant remains a huge challenge. This study aimed to detect single nucleotide polymorphisms (SNPs) and candidate genes for the number of mummified (NM) piglets using the imputed whole-genome sequence (WGS) and validate the potential candidate genes. Methods: The imputed WGS was introduced from genotyping-by-sequencing (GBS) using a multi-breed reference population. We performed genome-wide association studies (GWAS) for NM piglets at birth from a Landrace pig populatiGWAS peak located on SSC11: 0.10 to 7.11 Mbp (Top SNP, SSC11:1,889,658 bp; p = 9.98E-13) was identified in cyclin dependent kinase on. A total of 300 Landrace pigs were genotyped by GBS. The whole-genome variants were imputed, and 4,252,858 SNPs were obtained. Various molecular experiments were conducted to determine how the genes affected NM in pigs. Results: A strong GWAS peak located on SSC11: 0.10 to 7.11 Mbp (Top SNP, SSC11:1,889,658 bp; p = 9.98E-13) was identified in cyclin dependent kinase 8 (CDK8) gene, which plays a crucial role in embryonic retardation and lethality. Based on the molecular experiments, we found that Y-box binding protein 1 (YBX1) was a crucial transcription factor for CDK8, which mediated the effect of CDK8 in the proliferation of porcine ovarian granulosa cells via transforming growth factor beta/small mother against decapentaplegic signaling pathway, and, as a consequence, affected embryo quality, indicating that this pathway may be contributing to mummified fetal in pigs. Conclusion: A powerful imputation-based association study was performed to identify genes associated with NM in pigs. CDK8 was suggested as a functional gene for the proliferation of porcine ovarian granulosa cells, but further studies are required to determine causative mutations and the effect of loci on NM in pigs.

• Journal of Animal Science and Technology
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• v.54 no.5
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• pp.323-329
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• 2012

Genome-wide association study was performed on data from 266 Hanwoo steers derived from 66 sires using bovine 10K mapping chip in Hanwoo (Korean cattle). SNPs were excluded from the analysis if they failed in over 5% of the genotypes, had median GC scores below 0.6, had GC scores under 0.6 in less than 90% of the samples, deviated in heterozygosity more than 3 standard deviations from the other SNPs and were out of Hardy-Weinberg equilibrium for a cut-off p-value of $1^{-15}$. Unmapped and SNPs on sex chromosomes were also excluded. A total of 4,522 SNPs were included in the analysis. To test an association between SNP and QTL, a single marker regression analysis was implemented in this study. SNP was assumed to be in LD with QTL in close proximity and the effect evaluated was additive effect (QTL allele substitution effect). The number of significant SNP at a threshold of P<0.001 was 3, 5, 5 and 4 loci for live weight at 6, 12, 18 and 24 months, respectively. For live weight at different ages, significant SNP were spread out across chromosome but some of significant SNP (rs29012453 and rs29012456 on BTA24) had shown highly significant effects. As for the distribution of size of SNP effects, few loci for live weight at different age had moderate effects (6~11%) but most of significant loci had small effects (2 to 5% of additive genetic variance) against total additive genetic variance. In conclusion, live weight at different age might be affected by few loci with moderate effect and many loci with small effects across genome in Hanwoo.