• Animal Bioscience
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• v.34 no.4
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• pp.482-488
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• 2021

Objective: This study was conducted to estimate effect of single nucleotide polymorphisms (SNP) on the estimated breeding value of Hungarian Grey (HG) bulls and to find markers associated with horn colour. Methods: Genotypes 136 HG animals were determined on Geneseek high-density Bovine SNP 150K BeadChip. A multi-locus mixed-model was applied for statistical analyses. Results: Six SNPs were identified to be associated (-log10P>10) with green and white horn. These loci are located on chromosome 1, 3, 9, 18, and 25. Seven loci (on chromosome 1, 3, 6, 9, 10, 28) showed considerable association (-log10P>10) with the estimated breeding value. Conclusion: Analysis provides markers for further research of horn colour and supplies markers to achieve more effective selection work regarding estimated breeding value of HG.

• 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.28 no.4
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• pp.627-637
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• 2010

The consumption of tomato has greatly increased recently in Korea, and a large number of tomato cultivars are commercially available in the market. However, identification of tomato cultivars by morphological traits is extremely difficult because of the narrow genetic diversity of breeding lines. Therefore, it is necessary to develop molecular markers for cultivar identification in tomato. In this study, we surveyed single nucleotide polymorphism (SNP), and developed SNP marker sets for tomato cultivar identification. SNP markers were developed based on conserved ortholog set II (COSII) and intron-based markers derived from pepper EST sequences, and marker polymorphism was tested using high-resolution melting (HRM) analysis. A total of 628 primer sets was tested, and 417 primer sets amplifying single bands were selected. Of the 417 primer sets, 70 primer sets showing HRM polymorphism among 4 inbred lines were selected. Eleven markers were selected from the 70 primer sets and subjected to cultivar identification analysis. Thirty two commercial tomato cultivars were successfully identified using the marker set.

• Journal of Animal Science and Technology
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• v.51 no.5
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• pp.353-360
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• 2009

When 14 microsatellite (MS) markers were applied in the identifying test for 480 Hanwoo, the discriminating power was estimated as $3.43{\times}10^{-27}$ based on the assumption of a random mating group (PI). This rate is 1,000 times higher than that of 60 single nucleotide polymorphism (SNP) markers. On the other hand, the power of the 60 SNP markers was estimated as $4.69{\times}10^{-20}$ and $8.02{\times}10^{-12}$ on the assumption of a half-sib mating group ($PI_{half-sibs}$) and a full-sib mating group ($PI_{sibs}$), respectively. These powers were 10 times and 10,000 times higher than those of the 14 MS markers. The results indicated that the total number of alleles (MS vs SNP = 146 vs 120) acted as a key factor for the discriminating power in a random mating population, and the total number of markers (MS vs SNP = 14 vs 60) was a dominant influence on the power in half-sib and full-sib populations. In the Hanwoo population, in which it was assumed that the entire population is the enormous half-sib group formed by the absolute genetic contribution of a few nuclear bulls, there will be only a 10 times difference in the discriminating power between the 14 MS markers and the 60 SNP makers. However, the probability of not excluding a candidate parent pair from the parentage of an arbitrary offspring, given that only the genotype of the offspring ($PNE_{pp}$) was 1,000 times higher as shown by the 14 MS markers than that by the 60 SNP markers. The strong points of SNP makers are the stability of the variation (low mutation rate) and automation of high-throughput genotyping. In order to apply these merits for the practical and constant Hanwoo identity test, research and development are required to set a cost-effective platform and produce a homemade apparatus for SNP genotyping.

• Genomics & Informatics
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• v.10 no.3
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• pp.194-199
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• 2012

In addition to single-nucleotide polymorphisms (SNP), copy number variation (CNV) is a major component of human genetic diversity. Among many whole-genome analysis platforms, SNP arrays have been commonly used for genomewide CNV discovery. Recently, a number of CNV defining algorithms from SNP genotyping data have been developed; however, due to the fundamental limitation of SNP genotyping data for the measurement of signal intensity, there are still concerns regarding the possibility of false discovery or low sensitivity for detecting CNVs. In this study, we aimed to verify the effect of combining multiple CNV calling algorithms and set up the most reliable pipeline for CNV calling with Affymetrix Genomewide SNP 5.0 data. For this purpose, we selected the 3 most commonly used algorithms for CNV segmentation from SNP genotyping data, PennCNV, QuantiSNP; and BirdSuite. After defining the CNV loci using the 3 different algorithms, we assessed how many of them overlapped with each other, and we also validated the CNVs by genomic quantitative PCR. Through this analysis, we proposed that for reliable CNV-based genomewide association study using SNP array data, CNV calls must be performed with at least 3 different algorithms and that the CNVs consistently called from more than 2 algorithms must be used for association analysis, because they are more reliable than the CNVs called from a single algorithm. Our result will be helpful to set up the CNV analysis protocols for Affymetrix Genomewide SNP 5.0 genotyping data.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.4
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• pp.464-470
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• 2016

The objective of this study was to investigate the accuracy of imputation from low density (LDC) to moderate density SNP chips (MDC) in a Thai Holstein-Other multibreed dairy cattle population. Dairy cattle with complete pedigree information (n = 1,244) from 145 dairy farms were genotyped with GeneSeek GGP20K (n = 570), GGP26K (n = 540) and GGP80K (n = 134) chips. After checking for single nucleotide polymorphism (SNP) quality, 17,779 SNP markers in common between the GGP20K, GGP26K, and GGP80K were used to represent MDC. Animals were divided into two groups, a reference group (n = 912) and a test group (n = 332). The SNP markers chosen for the test group were those located in positions corresponding to GeneSeek GGP9K (n = 7,652). The LDC to MDC genotype imputation was carried out using three different software packages, namely Beagle 3.3 (population-based algorithm), FImpute 2.2 (combined family- and population-based algorithms) and Findhap 4 (combined family- and population-based algorithms). Imputation accuracies within and across chromosomes were calculated as ratios of correctly imputed SNP markers to overall imputed SNP markers. Imputation accuracy for the three software packages ranged from 76.79% to 93.94%. FImpute had higher imputation accuracy (93.94%) than Findhap (84.64%) and Beagle (76.79%). Imputation accuracies were similar and consistent across chromosomes for FImpute, but not for Findhap and Beagle. Most chromosomes that showed either high (73%) or low (80%) imputation accuracies were the same chromosomes that had above and below average linkage disequilibrium (LD; defined here as the correlation between pairs of adjacent SNP within chromosomes less than or equal to 1 Mb apart). Results indicated that FImpute was more suitable than Findhap and Beagle for genotype imputation in this Thai multibreed population. Perhaps additional increments in imputation accuracy could be achieved by increasing the completeness of pedigree information.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.9
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• pp.1340-1348
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• 2019

Objective: The objectives were to compare variance components, genetic parameters, prediction accuracies, and genomic-polygenic estimated breeding value (EBV) rankings for milk yield (MY) and fat yield (FY) in the Thai multibreed dairy population using five single nucleotide polymorphism (SNP) sets from GeneSeek GGP80K chip. Methods: The dataset contained monthly MY and FY of 8,361 first-lactation cows from 810 farms. Variance components, genetic parameters, and EBV for five SNP sets from the GeneSeek GGP80K chip were obtained using a 2-trait single-step average-information restricted maximum likelihood procedure. The SNP sets were the complete SNP set (all available SNP; SNP100), top 75% set (SNP75), top 50% set (SNP50), top 25% set (SNP25), and top 5% set (SNP5). The 2-trait models included herd-year-season, heterozygosity and age at first calving as fixed effects, and animal additive genetic and residual as random effects. Results: The estimates of additive genetic variances for MY and FY from SNP subsets were mostly higher than those of the complete set. The SNP25 MY and FY heritability estimates (0.276 and 0.183) were higher than those from SNP75 (0.265 and 0.168), SNP50 (0.275 and 0.179), SNP5 (0.231 and 0.169), and SNP100 (0.251and 0.159). The SNP25 EBV accuracies for MY and FY (39.76% and 33.82%) were higher than for SNP75 (35.01% and 32.60%), SNP50 (39.64% and 33.38%), SNP5 (38.61% and 29.70%), and SNP100 (34.43% and 31.61%). All rank correlations between SNP100 and SNP subsets were above 0.98 for both traits, except for SNP100 and SNP5 (0.93 for MY; 0.92 for FY). Conclusion: The high SNP25 estimates of genetic variances, heritabilities, EBV accuracies, and rank correlations between SNP100 and SNP25 for MY and FY indicated that genotyping animals with SNP25 dedicated chip would be a suitable to maintain genotyping costs low while speeding up genetic progress for MY and FY in the Thai dairy population.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.936-942
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• 2015

The purpose of this study was to characterize genetic architecture of behavior patterns in Sapsaree dogs. The breed population (n=8,256) has been constructed since 1990 over 12 generations and managed at the Sapsaree Breeding Research Institute, Gyeongsan, Korea. Seven behavioral traits were investigated for 882 individuals. The traits were classified as a quantitative or a categorical group, and heritabilities ($h^2$) and variance components were estimated under the Animal model using ASREML 2.0 software program. In general, the $h^2$ estimates of the traits ranged between 0.00 and 0.16. Strong genetic ($r_G$) and phenotypic ($r_P$) correlations were observed between nerve stability, affability and adaptability, i.e. 0.9 to 0.94 and 0.46 to 0.68, respectively. To detect significant single nucleotide polymorphism (SNP) for the behavioral traits, a total of 134 and 60 samples were genotyped using the Illumina 22K CanineSNP20 and 170K CanineHD bead chips, respectively. Two datasets comprising 60 (Sap60) and 183 (Sap183) samples were analyzed, respectively, of which the latter was based on the SNPs that were embedded on both the 22K and 170K chips. To perform genome-wide association analysis, each SNP was considered with the residuals of each phenotype that were adjusted for sex and year of birth as fixed effects. A least squares based single marker regression analysis was followed by a stepwise regression procedure for the significant SNPs (p<0.01), to determine a best set of SNPs for each trait. A total of 41 SNPs were detected with the Sap183 samples for the behavior traits. The significant SNPs need to be verified using other samples, so as to be utilized to improve behavior traits via marker-assisted selection in the Sapsaree population.

• Journal of Animal Science and Technology
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• v.53 no.1
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• pp.15-22
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• 2011

The purpose of this study was to analyse of association between growth traits and single nucleotide polymorphisms (SNPs) polymorphism of phosphoglycerate kinase 2 (PGK 2) gene in pigs. The birth weight of piglet influences on weaning weight and survival rate that are import economic traits in pig industry. Also, these growth traits are representative factor to decrease a period getting to marketing weight as well as growth rate in pig. The PGK 2 is an isozyme that catalyzes the first ATP-generating step in the glycolytic pathwayand important enzyme related with energy metabolism. Twenty of SNPs were discoveredby genome structure analysis that compares the sequence on promoter and transcription region of PGK 2 gene in porcine chromosome 7. An association between PGK 2 SNPs and growth traits was analyzed in $F_2$ reciprocal-crossbred population between korean native pig (KNP) and Landrace. Association analysis indicated that polymorphism of the PGK 2 gene promoter region has significant effects on weight at birth (p<0.01) and weight at 3 weeks of age (p<0.0001). These results suggest that PGK 2 gene polymorphism was associated with energy metabolism and physiological function of growth in pig.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.3
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• pp.315-320
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• 2016

Porcine beta-defensin-1 (PBD-1) gene plays an important role in the innate immunity of pigs. The peptide encoded by this gene is an antimicrobial peptide that has direct activity against a wide range of microbes. This peptide is involved in the co-creation of an antimicrobial barrier in the oral cavity of pigs. The objective of the present study was to detect polymorphisms, if any, in exon-1 and exon-2 regions of PBD-1 gene in Large White Yorkshire (LWY) and native Ankamali pigs of Kerala, India. Blood samples were collected from 100 pigs and genomic DNA was isolated using phenol chloroform method. The quantity of DNA was assessed in a spectrophotometer and quality by gel electrophoresis. Exon-1 and exon-2 regions of PBD-1 gene were amplified by polymerase chain reaction (PCR) and the products were subjected to single strand conformation polymorphism (SSCP) analysis. Subsequent silver staining of the polyacrylamide gels revealed three unique SSCP banding patterns in each of the two exons. The presence of single nucleotide polymorphisms (SNPs) was confirmed by nucleotide sequencing of the PCR products. A novel SNP was found in the 5'-UTR region of exon-1 and a SNP was detected in the mature peptide coding region of exon-2. In exon-1, the pooled population frequencies of GG, GT, and TT genotypes were 0.67, 0.30, and 0.03, respectively. GG genotype was predominant in both the breeds whereas TT genotype was not detected in LWY breed. Similarly, in exon-2, the pooled population frequencies of AA, AG, and GG genotypes were 0.50, 0.27, and 0.23, respectively. AA genotype was predominant in LWY pigs whereas GG genotype was predominant in native pigs. These results suggest that there exists a considerable genetic variation at PBD-1 locus and further association studies may help in development of a PCR based genotyping test to select pigs with better immunity.