• 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.

• Journal of Life Science
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• v.26 no.7
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• pp.855-867
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• 2016

The horse is relatively earlier domesticated animal species. Domesticated horses have been selected for their ability of racing, robustness, and disease-resistance. As a result, the thoroughbred horse genome has been condensed many genotypes related to exercise ability. In recent years, with the advent of NGS technologies, many studies were concentrated on finding superior genetic species in the horse genome in terms of genomics. Consequently, GWAS (Genome-wide Association study) is applied to horse genome, then genetic marker is revealed for superior racing ability. In addition, RNA-Seq is utilized as a method for analyze of whole transcript profiling in specific samples. By using this approach, specific gene expression patterns and transcript sequences can be revealed in various samples such as each individual, before and after exercise state, and each tissue. DNA methylation, a strong factor that regulate gene expression without the change of DNA sequence, have got a lot of attention. In horse genome, exercise- or individual-specific DNA methylation patterns were detected, and could be useful to develop selective marker of superior horses. MicroRNAs inhibit gene expression, and transposable elements accounted for half of the mammalian genome. These two elements are the crucial factors in functional genomics, and could be applied to the selection of superior horses. As the functional genomics and epigenomics advance, then these technologies introduced in this paper were applied to select superior horses. In this paper, the studies for selection of superior horses through genetic technologies, and development possibilities of these studies were discussed.

• Journal of Genetic Medicine
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• v.14 no.1
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• pp.8-17
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• 2017

Purpose: Pulse wave velocity (PWV) is an indicator of arterial stiffness, and is considered a marker of vascular damage. However, a genome-wide association study analyzing single nucleotide polymorphisms (SNPs) associated with brachial-ankle PWV (baPWV) has not been conducted in healthy populations. We performed this study to identify SNPs associated with baPWV in healthy populations in Korea. Materials and Methods: Genomic SNPs data for 2,407 individuals from three sites were analyzed as part of the Korean Genomic Epidemiologic Study. Without replication samples, we performed multivariable analysis as a post hoc analysis to verify the findings in site adjusted analysis. Healthy subjects aged between 40 and 70 years without self-reported history or diagnosis of hypertension, diabetes, hyperlipidemia, heart disease, cerebrovascular disease and cancer were included. We excluded subjects with a creatinine level >1.4 mg/dL (men) and 1.2 mg/dL (women). Results: In the site-adjusted association analysis, significant associations (P<$5{\times}10^{-8}$) with baPWV were detected for only 5 SNPs with low minor allele frequency. In multivariable analysis adjusted by age, sex, height, body mass index, mean arterial pressure, site, smoking, alcohol, and exercise, 11 SNPs were found to be associated (P<$5{\times}10^{-8}$) with baPWV. The 5 SNPs (P<$5{\times}10^{-8}$) linked to three genes (OPCML, PRR35 and RAB40C) were common between site-adjusted analysis and multivariable analysis. However, meta-analysis of the result from three sites for the 11 SNPs showed no significant associations. Conclusion: Using the recent standard for genome-wide association study, we did not find any evidence of significant association signals with baPWV.

• Animal Bioscience
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• v.36 no.4
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• pp.570-583
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• 2023

Objective: Fibroblast growth factors (FGFs) play critical roles in embryo development, and immune responses to infectious diseases. In this study, to investigate the roles of FGFs, we performed genome-wide identification, expression, and functional analyses of FGF family members in chickens. Methods: Chicken FGFs genes were identified and analyzed by using bioinformatics approach. Expression profiles and Hierarchical cluster analysis of the FGFs genes in different chicken tissues were obtained from the genome-wide RNA-seq. Results: A total of 20 FGF genes were identified in the chicken genome, which were classified into seven distinct groups (A-F) in the phylogenetic tree. Gene structure analysis revealed that members of the same clade had the same or similar exon-intron structure. Chromosome mapping suggested that FGF genes were widely dispersed across the chicken genome and were located on chromosomes 1, 4-6, 9-10, 13, 15, 28, and Z. In addition, the interactions among FGF proteins and between FGFs and mitogen-activated protein kinase (MAPK) proteins are limited, indicating that the remaining functions of FGF proteins should be further investigated in chickens. Kyoto encyclopedia of genes and genomes pathway analysis showed that FGF gene interacts with MAPK genes and are involved in stimulating signaling pathway and regulating immune responses. Furthermore, this study identified 15 differentially expressed genes (DEG) in 21 different growth stages during early chicken embryo development. RNA-sequencing data identified the DEG of FGFs on 1- and 3-days post infection in two indigenous Ri chicken lines infected with the highly pathogenic avian influenza virus H5N1 (HPAIV). Finally, all the genes examined through quantitative real-time polymerase chain reaction and RNA-Seq analyses showed similar responses to HPAIV infection in indigenous Ri chicken lines (R² = 0.92-0.95, p<0.01). Conclusion: This study provides significant insights into the potential functions of FGFs in chickens, including the regulation of MAPK signaling pathways and the immune response of chickens to HPAIV infections.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.3
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• pp.327-334
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• 2018

Objective: The objective of the present study was to validate genes and genomic regions associated with carcass weight using a low-density single nucleotide polymorphism (SNP) Chip in Hanwoo cattle breed. Methods: Commercial Hanwoo steers (n = 220) were genotyped with 20K GeneSeek genomic profiler BeadChip. After applying the quality control of criteria of a call rate ${\geq}90%$ and minor allele frequency (MAF) ${\geq}0.01$, a total of 15,235 autosomal SNPs were left for genome-wide association (GWA) analysis. The GWA tests were performed using single-locus mixed linear model. Age at slaughter was fitted as fixed effect and sire included as a covariate. The level of genome-wide significance was set at $3.28{\times}10^{-6}$ (0.05/15,235), corresponding to Bonferroni correction for 15,235 multiple independent tests. Results: By employing EMMAX approach which is based on a mixed linear model and accounts for population stratification and relatedness, we identified 17 and 16 loci significantly (p<0.001) associated with carcass weight for the additive and dominant models, respectively. The second most significant (p = 0.000049) SNP (ARS-BFGL-NGS-28234) on bovine chromosome 4 (BTA4) at 21 Mb had an allele substitution effect of 43.45 kg. Some of the identified regions on BTA2, 6, 14, 22, and 24 were previously reported to be associated with quantitative trait loci for carcass weight in several beef cattle breeds. Conclusion: This is the first genome-wide association study using SNP chips on commercial Hanwoo steers, and some of the loci newly identified in this study may help to better DNA markers that determine increased beef production in commercial Hanwoo cattle. Further studies using a larger sample size will allow confirmation of the candidates identified in this study.

• Journal of Microbiology and Biotechnology
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• v.13 no.2
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• pp.317-320
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• 2003

Genome-wide systematic deletion mutants were generated using a PCR-based targeted mutagenesis of Schizosacchaaromyces pombe. In a drug-sensitivity assay using thiabendazole(TBZ), an inhibitor of microtubule assembly, a heterozygous nda2 mutant ($nda2^+/nda2^-$), deleting one copy of nda2 encoding the microtubule subunit alpha1 demonstrated a distinct sensitivity to TBZ, indicating TBZ-induced haploinsufficiency. This result suggests that profiling drug-induced haploinsufficiency can be exploited to identify target genes for drugs and discover new drugs.

• Molecules and Cells
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• v.38 no.6
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• pp.475-481
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• 2015

Programmable nucleases, which include zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and RNA-guided engineered nucleases (RGENs) repurposed from the type II clustered, regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) system are now widely used for genome editing in higher eukaryotic cells and whole organisms, revolutionising almost every discipline in biological research, medicine, and biotechnology. All of these nucleases, however, induce off-target mutations at sites homologous in sequence with on-target sites, limiting their utility in many applications including gene or cell therapy. In this review, we compare methods for detecting nuclease off-target mutations. We also review methods for profiling genome-wide off-target effects and discuss how to reduce or avoid off-target mutations.

• Journal of Genetic Medicine
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• v.12 no.2
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• pp.61-65
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• 2015

Whole genome sequencing (WGS)-based noninvasive prenatal test (NIPT) is the first method applied in the clinical setting out of various NIPT techniques. Several companies, such as Sequenom, BGI, and Illumina offer WGS-based NIPT, each with different technical and bioinformatic approaches. Sequenom, BGI, and Illumina utilize z-, t-, and L-scores, as well as normalized chromosome values, respectively, for trisomy detection. Their outstanding performance has been demonstrated in clinical studies of more than 100,000 pregnancies. The sensitivity and specificity for detection of trisomies 13, 18, and 21 were above 98%, as reported by all three companies. Unlike other techniques, WGS-based NIPT can detect other trisomies as well as clinically significant segmental duplications/deletions within a chromosome, which could expand the scope of NIPT. Incorrect results could be due to low fetal fraction, fetoplacental mosaicism, confined placental mosaicism or maternal copy number variation (CNV). Among those, maternal CNV is a significant contributor of false positive results and therefore genome wide scanning plays an important role in preventing the occurrence of false positives. In this article, the bioinformatic techniques and clinical performance of three major companies are comprehensively reviewed.

• 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.