• Asian-Australasian Journal of Animal Sciences
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• v.15 no.7
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• pp.938-943
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• 2002

This study was perfonned to detect polymorphisms of the two candidate genes, bovine BTN (Butyrophilin) and ST AT5a (Signal Transducers and Activators of Transcription) gene using 98 Holstein bulls' frozen semen, and to offer the basic information for QTL (Quantitative Trait Loci) analysis. Each BTN PCR product was digested with endonuclease restriction enzyme. The digested fragments of four BTN PCR products were observed as follows: 316,280, and 162 bp in BTN1, 568, 305 and 263 bp in BTN2, 576, 332, and 244 bp in BTN3, and 573, 291, and 282 bp in BTN4, respectively. The gene frequencies of A and B allele in four BTN loci were as follows: 0.8980 and 0.1020 in BTN1, 0.5510 and 0.4490 in BTN2, 0.8163 and 0.1837 in BTN3, and 0.8875 and 0.1122 in BTN4, respectively. And three genotypes (homotypel, heterotype, and homotype2) for STAT5a were observed by SSCP (single stranded conformational polymorphism) method and the genotype frequencies are 78.57%, 19.39%, and 2.04%, respectively. The PlC (Polymorphism Information Content) value and heterozygosity of four BTN loci were as follows: 0.1695 and 0.1870 in BTN1, 0.3713 and 0.4927 in BTN2, 0.2549 and 0.2999 in BTN3, and 0.1794 and 0.1992 in BTN4, respectively. Comparing with the reported data, PlC value of BTN2 might have the possibility to be useful marker. Other BTN loci indicated skewed allele distribution.

• BMB Reports
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• v.40 no.1
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• pp.95-99
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• 2007

Bovine coding region single nucleotide polymorphisms located proximal to quantitative trait loci were identified to facilitate bovine QTL fine mapping research. A total of 692,763 bovine SNPs was extracted from 39,432 UniGene clusters, and 53,446 candidate SNPs were found to be a depth >3. In order to validate the in silico SNPs experimentally, 186 animals representing 14 breeds and 100 mixed breeds were analyzed. Genotyping of 40 randomly selected candidate SNPs revealed that 43% of these SNPs ranged in frequency from 0.009 to 0.498. To identify non-synonymous SNPs and to correct for possible frameshift errors in the ESTs at the predicted SNP positions, we designed a program that determines coding regions by protein-sequence referencing, and identified 17,735 nsSNPs. The SNPs and bovine quantitative traits loci informations were integrated into a bovine SNP data: BcSNPdb (http://snugenome.snu.ac.kr/BtcSNP/). Currently there are 43 different kinds of quantitative traits available. Thus, these SNPs would serve as valuable resources for exploiting genomic variation that influence economically and agriculturally important traits in cows.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.657-668
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• 2004

Permutation test has been applied for the QTL(quantitative trait loci) analysis and we selected a major locus. K -means clustering analysis, for the major DNA Marker mining of ILSTS035 microsatellite loci in Hanwoo chromosome 6, has been described. Finally, bootstrap testing method has been adapted to calculate confidence intervals and for finding major DNA Markers.

• Journal of Animal Science and Technology
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• v.44 no.1
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• pp.31-38
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• 2002

Interval mapping using microsatellite markers was employed to detect quantitative trait loci (QTL) in the experimental cross between Berkshire and Yorkshire pigs. In order to derive critical values (CV) for test statistics for declaring significance of QTL, permutation test (PT) of Churchill and Doerge method(1994) and the analytical method(LK) of Lander and Kruglyak(1995) were used by each trait and chromosome. 525 $F_2$ progeny phenotypes of five traits(carcass weight, loin eye area, marbling score, cholesterol content, last back fat thickness) and genotypes of 125 markers covering the genome were used. Data were analyzed by line cross regression interval mapping with an F-test every by 1cM. PT CV were based on 10,000 permutations. CV at genome-wise test were 10.5 for LK and ranged from 8.1 to 8.3 for PT, depending on the trait. CV, differed substantially between methods, led to different numbers of quantitative trait loci (QTL) to be detected. PT results in the least stringent CV compared at the same % level.

• Proceedings of the Korean Society of Crop Science Conference
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• 2000.04a
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• pp.378-379
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• 2000

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.167-167
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• 2023

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.175-184
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• 2007

LOD scores and a permutation test for detecting and locating quantitative trait loci (QTL) from the Hanwoo economic trait have been described and we selected a considerable major BMS1167 locus for further analysis. K-means clustering analysis, for the major DNA marker mining of BMS1167 microsatellite loci in Hanwoo chromosome17, has been tried and three cluster groups divide four traits. The three cluster groups are classified according to eight DNA marker bps. Finally, we employed the bootstrap test method to calculate confidence intervals using the resampling method to find major DNA markers. We conclude that the major marker of BMS1167 locus in Hanwoo chromosome17 is only DNA marker 100bp.

• Journal of Crop Science and Biotechnology
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• v.11 no.1
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• pp.7-12
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• 2008

Quantitative trait loci, a genetic concept for explaining the inheritance of non-Mendelian traits in 1940s, have been realized as particular fragments of chromosome even unique genes in most crops in 21st century. However, only very a small portion of QTL has been screened out by geneticists comparing to a great number of genes underneath the quantitative traits. These identified QTL even have been seldom used into breeding program because crop breeders may not find the QTL in their breeding populations in their field station. Several key points will be proposed to meet the challenges of QTL analysis today: a fine mapping population and the related reference genetic map, QTL evaluation in multiple environments, recognizing real QTL with small genetic effect, map integration.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.5
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• pp.617-623
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• 2008

A fine-mapping method exploiting linkage disequilibrium was used to detect quantitative trait loci (QTL) on the X chromosome affecting milk production, body conformation and productivity traits. The pedigree comprised 22 paternal half-sib families of Black-and-White Holstein bulls in the Netherlands in a grand-daughter design for a total of 955 sons. Twenty-five microsatellite markers were genotyped to construct a linkage map on the chromosome X spanning 170 Haldane cM with an average inter-marker distance of 7.1 cM. A covariance matrix including elements about identical-by-descent probabilities between haplotypes regarding QTL allele effects was incorporated into the animal model, and a restricted maximum-likelihood method was applied for the presence of QTL using the LDVCM program. Significance thresholds were obtained by permuting haplotypes to phenotypes and by using a false discovery rate procedure. Seven QTL responsible for conformation types (teat length, rump width, rear leg set, angularity and fore udder attachment), behavior (temperament) and a mixture of production and health (durable prestation) were detected at the suggestive level. Some QTL affecting teat length, rump width, durable prestation and rear leg set had small numbers of haplotype clusters, which may indicate good classification of alleles for causal genes or markers that are tightly associated with the causal mutation. However, higher maker density is required to better refine the QTL position and to better characterize functionally distinct haplotypes which will provide information to find causal genes for the traits.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.11
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• pp.1536-1544
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• 2013

A least squares regression interval mapping model was derived to detect quantitative trait loci (QTL) with a unique mode of genomic imprinting, polar overdominance (POD), under a breed cross design model in outbred mammals. Tests to differentiate POD QTL from Mendelian, paternal or maternal expression QTL were also developed. To evaluate the power of the POD models and to determine the ability to differentiate POD from non-POD QTL, phenotypic data, marker data and a biallelic QTL were simulated on 512 F2 offspring. When tests for Mendelian versus parent-of-origin expression were performed, most POD QTL were classified as partially imprinted QTL. The application of the series of POD tests showed that more than 90% and 80% of medium and small POD QTL were declared as POD type. However, when breed-origin alleles were segregating in the grand parental breeds, the proportion of declared POD QTL decreased, which was more pronounced in a mating design with a small number of parents ($F_0$ and $F_1$). Non-POD QTL, i.e. with Mendelian or parent-of-origin expression (complete imprinting) inheritance, were well classified (>90%) as non-POD QTL, except for QTL with small effects and paternal or maternal expression in the design with a small number of parents, for which spurious POD QTL were declared.