• Korean Journal of Agricultural Science
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• v.39 no.3
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• pp.357-364
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• 2012

Genomic breeding value (GEBV) has recently become available in the beef cattle industry. Genomic selection methods are exceptionally valuable for selecting traits, such as marbling, that are difficult to measure until later in life. One method to utilize information from sparse marker panels is the Bayesian model selection method with RJMCMC. The accuracy of prediction varies between a multiple SNP model with RJMCMC (0.47 to 0.73) and a least squares method (0.11 to 0.41) when using SNP information, while the accuracy of prediction increases in the multiple SNP (0.56 to 0.90) and least square methods (0.21 to 0.63) when including a polygenic effect. In the multiple SNP model with RJMCMC model selection method, the accuracy ($r^2$) of GEBV for marbling predicted based only on SNP effects was 0.47, while the $r^2$ of GEBV predicted by SNP plus polygenic effect was 0.56. The accuracies of GEBV predicted using only SNP information were 0.62, 0.68 and 0.73 for CWT, EMA and BF, respectively. However, when polygenic effects were included, the accuracies of GEBV were increased to 0.89, 0.90 and 0.89 for CWT, EMA and BF, respectively. Our data demonstrate that SNP information alone is missing genetic variation information that contributes to phenotypes for carcass traits, and that polygenic effects compensate genetic variation that whole genome SNP data do not explain. Overall, the multiple SNP model with the RJMCMC model selection method provides a better prediction of GEBV than does the least squares method (single marker regression).

• Food Science of Animal Resources
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• v.29 no.1
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• pp.108-113
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• 2009

Apolipoprotein E (APOE) is a plasma lipoprotein in mammals and plays an important role in the transport and metabolism of lipids such as phospholipids and triglycerides. Therefore, the APOE gene could be a candidate gene controlling lipid metabolism in beef cattle. This study was performed to identify single nucleotide polymorphisms (SNP) in the APOE gene and to investigate the effects of SNP genotype on the carcass traits such as meat quantity and quality in Korean cattle. For PCR amplification, pooled DNA made from unrelated 60 individuals was prepared and primer pairs were designed based on the cDNA sequence of exon 4 region of the bovine APOE gene. A SNP was identified at position 2034 (T/C substitution) of the exon 4 region in the APOE gene. PCR-RFLP procedure with restriction enzyme ACC I was developed for determining the SNP genotype for each of a total of 309 animals with pedigree information and performance records through the national progeny testing program. The frequencies of the genotypes TT, TC and CC were 10.9, 46.9 and 42.2%. Gene frequencies were 0.344 for T allele and 0.656 for C allele. The g.2034T>C SNP genotype showed a significant effect (p<0.05) on dressing percentage and meat color, respectively. Animals with the TT genotype showed higher dressing percentage than those with the CC genotype, and TT genotype had desirable meat color compared with CC genotype. These results suggest that the g.2034T>C SNP genotype of the APOE gene may be useful as a DNA marker for meat quantity index and dressing percentage in Korean cattle.

• Journal of Animal Science and Technology
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• v.63 no.6
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• pp.1232-1246
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• 2021

Recently, the cattle genome sequence has been completed, followed by developing a commercial single nucleotide polymorphism (SNP) chip panel in the animal genome industry. In order to increase statistical power for detecting quantitative trait locus (QTL), a number of animals should be genotyped. However, a high-density chip for many animals would be increasing the genotyping cost. Therefore, statistical inference of genotype imputation (low-density chip to high-density) will be useful in the animal industry. The purpose of this study is to investigate the effect of the reference population size and marker density on the imputation accuracy and to suggest the appropriate number of reference population sets for the imputation in Hanwoo cattle. A total of 3,821 Hanwoo cattle were divided into reference and validation populations. The reference sets consisted of 50k (38,916) marker data and different population sizes (500, 1,000, 1,500, 2,000, and 3,600). The validation sets consisted of four validation sets (Total 889) and the different marker density (5k [5,000], 10k [10,000], and 15k [15,000]). The accuracy of imputation was calculated by direct comparison of the true genotype and the imputed genotype. In conclusion, when the lowest marker density (5k) was used in the validation set, according to the reference population size, the imputation accuracy was 0.793 to 0.929. On the other hand, when the highest marker density (15k), according to the reference population size, the imputation accuracy was 0.904 to 0.967. Moreover, the reference population size should be more than 1,000 to obtain at least 88% imputation accuracy in Hanwoo cattle.

• Molecules and Cells
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• v.37 no.1
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• pp.36-42
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• 2014

The tomato (Solanum lycopersicum L.) is a model plant for genome research in Solanaceae, as well as for studying crop breeding. Genome-wide single nucleotide polymorphisms (SNPs) are a valuable resource in genetic research and breeding. However, to do discovery of genome-wide SNPs, most methods require expensive high-depth sequencing. Here, we describe a method for SNP calling using a modified version of SAMtools that improved its sensitivity. We analyzed 90 Gb of raw sequence data from next-generation sequencing of two resequencing and seven transcriptome data sets from several tomato accessions. Our study identified 4,812,432 non-redundant SNPs. Moreover, the workflow of SNP calling was improved by aligning the reference genome with its own raw data. Using this approach, 131,785 SNPs were discovered from transcriptome data of seven accessions. In addition, 4,680,647 SNPs were identified from the genome of S. pimpinellifolium, which are 60 times more than 71,637 of the PI212816 transcriptome. SNP distribution was compared between the whole genome and transcriptome of S. pimpinellifolium. Moreover, we surveyed the location of SNPs within genic and intergenic regions. Our results indicated that the sufficient genome-wide SNP markers and very sensitive SNP calling method allow for application of marker assisted breeding and genome-wide association studies.

• Horticultural Science & Technology
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• v.35 no.4
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• pp.465-479
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• 2017

Chili pepper (Capsicum annuum L.) is an economically important horticultural crop in Korea; however, various diseases, including Phytophthora root rot, anthracnose, powdery mildew, Cucumber mosaic virus (CMV), Pepper mild mottle virus (PMMoV), and Pepper mottle virus (PepMoV), severely affect their productivity and quality. Therefore, pepper varieties with resistance to multiple diseases are highly desired. In this study, we developed 20 SNP type assays for three pepper populations using Fluidigm nanofluidic dynamic arrays. A total of 4,608 data points can be produced with a 192.24 dynamic array consisting of 192 samples and 24 SNP markers. The assays were converted from previously developed sequence-tagged-site (STS) markers and included markers for resistance to Phytophthora root rot (M3-2 and M3-3), anthracnose (CcR9, CA09g12180, CA09g19170, CA12g17210, and CA12g19240), powdery mildew (Ltr4.1-40344, Ltr4.2-56301, and Ltr4.2-585119), bacterial spot (Bs2), CMV (Cmr1-2), PMMoV (L4), and PepMoV (pvr1 and pvr2-123457), as well as for capsaicinoids content (qcap3.1-40134, qcap6.1-299931, qcap6.1-589160, qdhc2.1-1335057, and qdhc2.2-43829). In addition, 11 assays were validated through a comparison with the corresponding data of the STS markers. Furthermore, we successfully applied the assays to commercial $F_1$ cultivars and to our breeding lines. These 20 SNP type assays will be very useful for developing new superior pepper varieties with resistance to multiple diseases and a higher content of capsaicinoids for increased pungency.

• Animal Bioscience
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• v.37 no.5
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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.

• Plant Breeding and Biotechnology
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• v.6 no.4
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• pp.434-443
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• 2018

Genotyping-by-sequencing (GBS) has been used as a viable single nucleotide polymorphism (SNP) validation method that provides reduced representation sequencing by using restriction endonucleases. Although GBS makes it possible to perform marker discovery and genotyping simultaneously with reasonable costs and a simple molecular biology workflow, the standard TASSEL-GBS pipeline was designed for homozygous groups, and genotyping of heterozygous groups is more complicated. To addresses this problem, we developed a GBS pipeline for heterozygous groups that called KNU-GBS pipeline, specifically for apple (Malus domestica). Using KNU-GBS pipeline, we constructed a genetic linkage map consisting of 1,053 SNP markers distributed over 17 linkage groups encompassing a total of 1350.1 cM. The novel GBS pipeline for heterozygous groups will be useful for marker-assisted breeding programs, and diverse heterozygous genome analyses.

• Horticultural Science & Technology
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• v.33 no.5
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• pp.722-729
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• 2015

Powdery mildew (PM) caused by Podosphaera aphanis is a major disease that can result in significant yield losses in strawberry (Fragaria ${\times}$ ananassa Duchesne). For preventing PM, pesticides are usually applied in strawberry. In this study, molecular markers were developed to increase breeding efficiency of PM-resistance cultivars by marker-assisted selection (MAS). An $F_2$ population derived from a cross between PM-resistance 'Seolhyang' and PM-susceptibility 'Akihime' was evaluated for disease resistance to PM and RAPD (random amplification of polymorphic DNA)-BSA (bulked segregant analysis). Among 200 RAPD primers tested, OPE10 primer amplified a 311bp-band present in with 331bp. Sequence alignment performed for searching polymorphisms and six single nucleotide polymorphism (SNP) were found in amplified regions. To develop polymorphic marker for distinguishing between resistant and susceptible, RAPD was converted to cleaved amplified polymorphic sequence (CAPS) marker. Among restriction enzymes associated with six SNPs, Eae I (Y/GGCCR) was successfully digested to 231bp in susceptible. The results suggest that the selected CAPS marker could be used for increasing efficiency of selecting powdery mildew resistant strawberry in breeding system.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.9
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• pp.1240-1244
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• 2006

The complete coding region sequence of the SRY gene in Chinese swamp buffalo was determined by PCR product sequencing. Comparison of swamp and river buffalo SRY gene sequences revealed a single nucleotide polymorphism (SNP, C/G) at the 202 bp site of the coding region. Further, a total of 124 male domestic buffaloes were genotyped at this SNP site using the PCR-SSCP method, and it was found that all Chinese indigenous swamp buffaloes had a guanine (G) at this site, while introduced river buffaloes and crossbred buffaloes showed a cytosine (C). Our findings suggested that this Y-linked SNP displayed type-specific alleles differentiating swamp and river buffaloes, and could be used as an effective marker to detect crossbreeding of swamp buffaloes with introduced river buffaloes in native buffalo populations, and thereby assess genetic diversity status and make proper conservation decisions for indigenous swamp buffaloes. In addition, this SNP can be potentially applied in the study of Asian water buffalo phylogeny from a male perspective.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.11
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• pp.1504-1513
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• 2011

It is important to identify genetic interactions related to human diseases or animal traits. Many linear statistical models have been reported but they did not consider genetic interactions. Genotype matrix mapping (GMM) has been developed to identify genetic interactions. This study uses the GMM method to detect superior SNP combinations of the CCDC158 gene that influences average daily gain, marbling score, cold carcass weight and longissimus muscle dorsi area traits in Hanwoo. We evaluated the statistical significance of the major SNP combinations selected by implementing the permutation test of the F-measure. The effect of g.34425+102 A>T (AA), g.8778G>A (GG) and g.4102+36T>G (GT) SNP combinations produced higher performance of average daily gain, marbling score, cold carcass weight and the longissimus muscle dorsi area traits than the effect of a single SNP. GMM is a fast and reliable method for multiple SNP analysis with potential application in marker-assisted selection. GMM may prospectively be used for genetic assessment of quantitative traits after further development.