• KOREAN JOURNAL OF CROP SCIENCE
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• v.45 no.4
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• pp.227-231
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• 2000

Small seed size is one of the major traits of soybean cultivars for sprouts with regard to high sprout yield. This study was conducted to identify quantitative trait loci (QTL) for seed size and weight in a set of F 6 seeds of 89 lines derived from a cross between 'Pureunkong', a soybean cultivar developed for sprouts and 'Jinpumkong 2', a soybean cultivar with no beany taste in seed due to the lack of lipoxygenases. The genetic map of 25 linkage groups with a total of 98 markers including RFLP, RAPD, SSR and classical markers was constructed from this F/sbu 5/-derived population and was used for QTL analysis. 'Pureunkong' was significantly smaller (P＜0.01) than 'Jinpumkong 2' in seed size and seed weight. Genetic variation was detected and transgressive segregation was common in the population for these traits. Seven DNA markers including opT14-1600 in LG A2, opF02-400 in LG B2, Satt100, opC09-700, opG04-730 and opQll-650 in LG C2, and opY07-1100 ＆ 1000 in LG(unknown) were significantly associated and accounted for 4.7 to 10.9% and 5.1 to 10.1 % of the phenotypic variation in seed size and seed weight, respectively. 'Pureunkong' alleles increased seed size and seed weight at the all four significant marker loci on the LG C2. These marker loci in LG C2 were closely linked and were presumed to be a single QTL. Overall, at least three independent QTLs from 3 linkage groups (A2, B2, and C2) were putatively involved in the control of seed size and seed weight.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.926-935
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• 2015

The efficiency of genome-wide association analysis (GWAS) depends on power of detection for quantitative trait loci (QTL) and precision for QTL mapping. In this study, three different strategies for GWAS were applied to detect QTL for carcass quality traits in the Korean cattle, Hanwoo; a linkage disequilibrium single locus regression method (LDRM), a combined linkage and linkage disequilibrium analysis (LDLA) and a $BayesC{\pi}$ approach. The phenotypes of 486 steers were collected for weaning weight (WWT), yearling weight (YWT), carcass weight (CWT), backfat thickness (BFT), longissimus dorsi muscle area, and marbling score (Marb). Also the genotype data for the steers and their sires were scored with the Illumina bovine 50K single nucleotide polymorphism (SNP) chips. For the two former GWAS methods, threshold values were set at false discovery rate <0.01 on a chromosome-wide level, while a cut-off threshold value was set in the latter model, such that the top five windows, each of which comprised 10 adjacent SNPs, were chosen with significant variation for the phenotype. Four major additive QTL from these three methods had high concordance found in 64.1 to 64.9Mb for Bos taurus autosome (BTA) 7 for WWT, 24.3 to 25.4Mb for BTA14 for CWT, 0.5 to 1.5Mb for BTA6 for BFT and 26.3 to 33.4Mb for BTA29 for BFT. Several candidate genes (i.e. glutamate receptor, ionotropic, ampa 1 [GRIA1], family with sequence similarity 110, member B [FAM110B], and thymocyte selection-associated high mobility group box [TOX]) may be identified close to these QTL. Our result suggests that the use of different linkage disequilibrium mapping approaches can provide more reliable chromosome regions to further pinpoint DNA makers or causative genes in these regions.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.5
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• pp.669-676
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• 2007

This study was conducted to detect quantitative trait loci (QTL) affecting growth and body composition in an $F_2$ reference population of Korean native pig and Landrace crossbreds. The three-generation mapping population was generated with 411 progeny from 38 $F_2$ full-sib families, and 133 genetic markers were used to produce a sex-average map of the 18 autosomes. The data set was analyzed using least squares Mendelian and parent-of-origin interval-mapping models. Lack-of-fit tests between the models were used to characterize QTL for mode of expressions. A total of 8 (39) QTL were detected at the 5% genome (chromosome)-wise level for the 17 analyzed traits. Of the 47 QTL detected, 21 QTL were classified as Mendelian expressed, 13 QTL as paternally expressed, 6 QTL as maternally expressed, and 7 QTL as partially expressed. Of the detected QTL at 5% genome-wise level, two QTL had Mendelian mode of inheritance on SSC6 and SSC9 for backfat thickness and bone weight, respectively, two QTL were maternally expressed for leather weight and front leg weight on SSC6 and SSC12, respectively, one QTL was paternally expressed for birth weight on SSC4, and three QTL were partially expressed for hot carcass weight and rear leg weight on SSC6, and bone weight on SSC13. Many of the Mendelian QTL had a dominant (complete or overdominant) mode of gene action, and only a few of the QTL were primarily additive, which reflects that heterosis for growth is appreciable in a cross between Korean native pig and Landrace. Our results indicate that alternate breed alleles of growth and body composition QTL are segregating between the two breeds, which could be utilized for genetic improvement of growth via marker-assisted selection.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.11
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• pp.1507-1510
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• 2012

Quantitative trait loci (QTL) associated with fat deposition traits in pigs are important gene positions in a chromosome that influence meat quality of pork. For QTL study, a three generation resource population was constructed from a cross between Korean native boars and Landrace sows. A total of 240 F2 animals from intercross of F1 were produced. 80 microsatellite markers covering chromosomes 1 to 10 were selected to genotype the resource population. Intervals between adjacent markers were approximately 19 cM. Linkage analysis was performed using CRIMAP software version 2.4 with a FIXED option to obtain the map distances. For QTL analysis, the public web-based software, QTL express (http://www.qtl.cap.ed.ac.uk) was used. Two significant and two suggestive QTL were identified on SSC 6, 7, and 8 as affecting body fat and IMF traits. For QTL affecting IMF, the most significant association was detected between marker sw71 and sw1881 on SSC 6, and a suggestive QTL was identified between sw268 and sw205 on SSC8. These QTL accounted for 26.58% and 12.31% of the phenotypic variance, respectively. A significant QTL affecting IMF was detected at position 105 cM between markers sw71 and sw1881 on SSC 6.

• Journal of Animal Science and Technology
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• v.55 no.2
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• pp.103-107
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• 2013

A crucial first step in the planning of any scientific experiment is to evaluate an appropriate sample size to permit sufficient statistical power to detect the desired effect. In this study, we investigated the optimal sample size of quantitative trait locus (QTL) linkage analysis for simple random sibship samples in pedigreed chicken populations, under the variance component framework implemented in the genetic power calculator program. Using the program, we could compute the statistical power required to achieve given sample sizes in variance component linkage analysis in random sibship data. For simplicity, an additive model was taken into account. Power calculations were performed to relate sample size to heritability attributable to a QTL. Under the various assumptions, comparative power curves indicated that the power to detect QTL with the variance component method is highly affected by a function of the effect size of QTL. Hence, more power can be achievable for QTL with a larger effect. In addition, a marked improvement in power could be obtained by increasing the sibship size. Thus, the use of chickens is advantageous regarding the sampling unit issue, since desirable sibship size can be easily obtained compared with other domestic species.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.8
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• pp.1134-1140
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• 2018

Objective: Fatty acid composition is one of the most important meat quality traits because it can contribute to functional, sensorial, and nutritional factors. In this study, quantitative trait locus (QTL) analyses for fatty acid composition traits were investigated in thigh and breast meat of Korean native chicken (KNC). Methods: In total, 18 fatty acid composition traits were investigated from each meat sample using 83 parents, and 595 $F_1$ chicks of 20 week old. Genotype assessment was performed using 171 informative DNA markers on 26 autosomes. The KNC linkage map was constructed by CRI-MAP software, which calculated genetic distances, with map orders between markers. The half-sib and full-sib QTL analyses were performed using GridQTL and SOLAR programs, respectively. Results: In total, 30 QTLs (12 in the thigh and 18 in the breast meat) were detected by the half-sib analysis and 7 QTLs (3 in the thigh and 4 in the breast meat) were identified by the full-sib analysis. Conclusion: With further verification of the QTL regions using additional markers and positional candidate gene studies, these results can provide valuable information for determining causative mutations affecting the fatty acid composition of KNC meat. Moreover, these findings may aid in the selection of birds with favorable fatty acid composition traits.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1826-1835
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• 2019

Objective: Testicular growth and development are strongly influenced by androgen. Although both testis weight and plasma testosterone level are inherited traits, the interrelationship between them is not fully established. Males of DDD/Sgn (DDD) mice are known to have extremely heavy testes and very high plasma testosterone level among inbred mouse strains. We dissected the genetic basis of testis weight and analyzed the potential influence of plasma testosterone level in DDD mice. Methods: Quantitative trait loci (QTL) mapping of testis weight was performed with or without considering the influence of plasma testosterone level in reciprocal $F_2$ intercross populations between DDD and C57BL/6J (B6) mice, thereby assessing the influence of testosterone on the effect of testis weight QTL. Candidate genes for testis weight QTL were investigated by next-generation sequencing analysis. Results: Four significant QTL were identified on chromosomes 1, 8, 14, and 17. The DDDderived allele was associated with increased testis weight. The $F_2$ mice were then divided into two groups according to the plasma testosterone level ($F_2$ mice with relatively "low" and "high" testosterone levels), and QTL scans were again performed. Although QTL on chromosome 1 was shared in both $F_2$ mice, QTL on chromosomes 8 and 17 were identified specifically in $F_2$ mice with relatively high testosterone levels. By whole-exome sequencing analysis, we identified one DDD-specific missense mutation Pro29Ser in alpha tubulin acetyltransferase 1 (Atat1). Conclusion: Most of the testis weight QTL expressed stronger phenotypic effect when they were placed on circumstance with high testosterone level. High testosterone influenced the QTL by enhancing the effect of DDD-derived allele and diminishing the effects of B6-derived allele. Since Pro29Ser was not identified in other inbred mouse strains, and since Pro29 in Atat1 has been strongly conserved among mammalian species, Atat1 is a plausible candidate for testis weight QTL on chromosome 17.

• Animal Bioscience
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• v.35 no.4
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• pp.511-516
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• 2022

Objective: A genomic region associated with a particular phenotype is called quantitative trait loci (QTL). To detect the optimal F₂ population size associated with QTLs in native chicken, we performed a simulation study on F₂ population derived from crosses between two different breeds. Methods: A total of 15 males and 150 females were randomly selected from the last generation of each F₁ population which was composed of different breed to create two different F₂ populations. The progenies produced from these selected individuals were simulated for six more generations. Their marker genotypes were simulated with a density of 50K at three different heritability levels for the traits such as 0.1, 0.3, and 0.5. Our study compared 100, 500, 1,000 reference population (RP) groups to each other with three different heritability levels. And a total of 35 QTLs were used, and their locations were randomly created. Results: With a RP size of 100, no QTL was detected to satisfy Bonferroni value at three different heritability levels. In a RP size of 500, two QTLs were detected when the heritability was 0.5. With a RP size of 1,000, 0.1 heritability was detected only one QTL, and 0.5 heritability detected five QTLs. To sum up, RP size and heritability play a key role in detecting QTLs in a QTL study. The larger RP size and greater heritability value, the higher the probability of detection of QTLs. Conclusion: Our study suggests that the use of a large RP and heritability can improve QTL detection in an F₂ chicken population.

• Genomics & Informatics
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• v.20 no.2
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• pp.17.1-17.11
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• 2022

Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.283-283
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• 2022

Abiotic stresses such as high/low temperature, drought, salinity, and submergence directly or indirectly influence the physiological status and molecular mechanisms of rice which badly affect yield. Especially, the low temperature causes harmful influences in the overall process of rice growth such as uneven germination and the establishment of seedlings, which has become one of the main limiting factors affecting rice production in the world. It is of great significance to find the candidate genes controlling low-temperature tolerance during seed germination and study their functions for breeding new rice cultivars with immense low-temperature tolerance during seed germination. In this study, 120 lines of Cheongcheong/Nagdong double haploid population were used for quantitative trait locus analysis of low-temperature germinability. The results showed significant difference in germination under low different temperature conditions. In total, 4 QTLs were detected on chromosome 3, 6, and 8. A total of 41 genes were identified from all the 4 QTLs, among them, 25 genes were selected by gene function annotation and further screened through quantitative real time polymerase chain reaction. Based on gene function annotation and level of expression under low-temperature, our study suggested OsGPq3 gene as a candidate gene controlling viviparous germination, ABA and GA signaling under low-temperature. This study will provide a theoretical basis for marker-assisted breeding.