• Animal Bioscience
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• 제34권4호
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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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• 제37권1호
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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.

• 원예과학기술지
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• 제28권4호
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• pp.627-637
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• 2010

최근 들어 우리나라에서 토마토 소비가 급증하고 있으며 많은 토마토 품종이 시장에서 거래되고 있다. 그러나 토마토 품종 육성에 이용되는 부모 계통의 유전적 다양성이 낮아 형태적인 특성에 의한 토마토 품종의 구분은 매우 어려운 현실이다. 이에 따라 토마토의 품종을 구별해 낼 수 있는 분자표지의 개발이 필요한 실정이다. 본 연구에서는 SNP를 탐색하고 토마토 품종 구분을 위한 SNP 마커를 개발하였다. SNP분자표지는 고추 유전체 서열로부터 파생된 COS II 분자표지와 인트론 기반 분자표지를 기반으로 선발되었으며, HRM분석을 통해 다형성을 테스트 하였다. 전체 628개의 프라이머 조합 가운데 PCR을 통해 크기가 500bp 이하의 단일 밴드가 증폭된 417개의 프라이머 조합을 선발하였다. 417개의 프라이머 조합을 이용해 4개의 토마토 계통을 대상으로 HRM 분석을 실시하였으며, 다형성을 보인 70개의 프라이머 조합을 선발하였다. 70개의 프라이머 조합을 이용하여 32개의 토마토 품종을 대상으로 HRM 분석을 실시하였다. HRM분석을 통해 총 11개의 SNP 분자표지가 선발되었으며, 이 분자표지를 이용해 시판중인 32개의 토마토 품종을 모두 구분할 수 있었다.

• Journal of Animal Science and Technology
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• 제51권5호
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• pp.353-360
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• 2009

14개의 microsatellite (MS) marker를 사용 할 경우 무작위 교배 집단(PI) 가정 하에 $3.43{\times}10^{-27}$의 판별율을 보여 60 개의 single nucleotide polymorphism (SNP) marker에 비해 약 1,000배의 높은 판별 효과를 나타내는 것으로 파악되었다. 그러나, 60개의 SNP marker의 경우 반형매 교배 집단($PI_{half-sibs}$)으로 가정할 경우 $4.69{\times}10^{-20}$과 전형매 교배 집단($PI_{sibs}$)으로 가정 할 경우 $8.02{\times}10^{-12}$으로 14개의 MS marker에 비해 약 10배와 10,000배의 높은 판별 효과를 나타내는 것으로 추정되었다. 이러한 결과는 무작위 교배집단에서는 사용된 marker의 전체 대립유전자수(MS : SNP = 146 : 120)에 의하여 판별효율이 결정되는 반면, 혈연관계가 높은 반형매와 전형매 집단에서는 비슷한 총 대립유전자수일 경우 marker의 수(MS : SNP = 14 : 60)가 많은 경우가 더 높은 판별율을 보이는 것으로 나타났다. 한육우의 경우 소수의 보증 종모우를 이용해 인공수정을 통해 형성 된 거대한 반형매 집단으로 가정하였을 경우 MS와 SNP marker의 판별율은 10배 정도의 차이로 큰 차이를 보이지 않을 것으로 예견되나, likelihood rato를 이용 하는 inclusion 방법에 의하여 부모를 동시에 찾을 확률은 MS marker가 1,000 배 정도 더 효율적인 것으로 나타났다. SNP marker의 장점인 변이의 안정성, 유전자형 분석의 자동화 및 대용량화 등을 한육우의 동일성 검사에 활용하기 위해서는 분석비용 절감 방안과 분석방법 및 장비의 국산화 등 실용 및 상용화적 측면에서의 연구개발이 필요하다고 사료된다.

• Genomics & Informatics
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• 제10권3호
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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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• 제29권4호
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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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• 제32권9호
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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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• 제28권7호
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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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• 제53권1호
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• pp.15-22
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• 2011

자돈의 생시 체중은 자돈의 이유 체중 및 생존율에도 크게 영향을 미친다. 또한 출하 시까지 돼지의 성장률 뿐만아니라 출하 일령 단축 및 출하 체중과도 밀접한 연관성이 있는 것으로 알려져 있다. 본 연구는 돼지 7번 염색체의 PGK 2 (phosphoglycerate kinase 2) 유전자의 promoter 영역 및 transcription 영역에 해당하는 DNA 염기서열을 유전체 구조분석을 통해 20개의 SNP (Single Nucleotide Polymorpism)를 발굴하였고, 발굴된 SNP 중 PGK 2 유전자의 전사 조절 영역 내 g.122 T>G 다형을 재래돼지와 Landrace를 이용한 $F_2$ 집단 268두 자돈의 성장 형질과의 연관성 분석을 실시한 결과, 생시 체중(p<0.01) 및 3주령 체중(p<0.001)에서 통계적으로 고도의 유의적 연관성이 있음을 확인 할 수 있었다. 따라서 본 연구를 통하여 확인된 PGK 2 유전자의 promoter 영역 내 성장 형질 관련 SNP는 건강한 자돈 및 종돈을 조기 선발하기 위한 유전자 marker로 활용 가능성을 제시하였다.

• Asian-Australasian Journal of Animal Sciences
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• 제29권3호
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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.