• 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.

• Journal of Life Science
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• v.25 no.8
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• pp.925-931
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• 2015

We performed a molecular marker-based analysis of quantitative trait loci (QTLs) for traits that determine the quality of the appearance of grains, using 120 doubled-haploid (DH) lines developed by another culture from the F1 cross between ‘Cheongcheong’ (Oryza sativa L. ssp. Indica) and ‘Nagdong’ (Oryza sativa L. ssp. Japonica). The traits studied included length, width, and thickness of the grains, as well as length-to-width ratio and 1,000-grain weight. The objective of this study was to determine the genetic control of these traits in order to formulate a strategy for improving the appearance of this hybrid. Within the DH population, five traits exhibited wide variation, with mean values occurring within the range of the two parents. Three QTLs were identified for grain length on chromosomes 2, 5, and 7. Three QTLs were mapped for grain width on chromosome 2: qGW2-1, qGW2-2, and qGW2-3. Six chromosomes were identified for the grain length-to-width ratio; four of these were on chromosome 2, whereas the other two were on chromosomes 7 and 12. One QTL influencing 1,000-grain weight was identified and located on chromosome 8. The results presented in the present study should facilitate rice-breeding, especially for improved hybrid-rice quality.

• Korean Journal of Breeding Science
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• v.41 no.4
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• pp.456-462
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• 2009

Bacterial pustule (BP), caused by Xanthomonas axonopodis pv. glycines, is prevalent disease in major soybean production areas. BP can reduce seed yield as well as seed quality. To identify the genomic region associated with the resistance to BP, QTL analysis was conducted using $F_{10}$ RIL (recombinant inbred lines) population, Keunolkong${\times}$Shinpaldalkong. Four QTLs for BP disease were identified on the linkage group B2, D2, I and K in field accounts for 36.4% of the phenotypic variation. Especially, QTL at near of Satt135 on LG D2 was identified in green house experiment explaining 20.9% of the phenotypic variation was found to be a major QTL conferring BP. One of these QTLs, Satt135 on the LG D2, was also identified in green house experiment. In both field and green house condition, the position of major QTL for BP was detected between Satt135 and Satt397 on the LG D2. The major QTL for BP may be used for minimizing soybean BP through effective marker-assisted selection (MAS).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.1
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• pp.85-92
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• 2008

An RIL population from a Shinpaldalkong2/GC83006 cross was employed to identify quantitative trait loci (QTL) associated with agronomic traits in soybean. The genetic map consisted of 127 loci which covered about 3,000cM and were assigned into 20 linkage groups. Phenotypic data were collected for the following traits; plant height, leaf area, flowering time, pubescence color, seed coat color and hilum color in 2005. Seed weight was evaluated using seeds collected in 2003 to 2005 at Suwon and in 2005 at Pyeongchang and Miryang sites. Three QTLs were associated with 100-seed weight in the combined analysis across three years. Among the three QTLs related to seed weight, all GC83006 alleles on LG O ($R^2\;=\;12.5$), LG A1 ($R^2\;=\;10.1$) and LG C2 ($R^2\;=\;11.5$) increased the seed weight. A QTL conditioning plant height was linked to markers including Satt134 (LG C2, $R^2\;=\;25.4$), and the GC83006 allele increased plant height at this QTL locus. For two QTLs related to leaf area, 1aM on LG M ($R^2\;=\;10.0$) and laL on LG L ($R^2\;=\;8.6$), the Shinpaldalkong2 alleles had positive effect to increase the leaf area. Satt134 on LG C2 ($R^2\;=\;41.0$) was associated with QTL for days to flowering. Satt134 (LG C2) showed a linkage to a gene for pubescence color. Satt363 (LG C2) and Satt354 (LG I) were linked to the hilum color gene, and Sat077 (LG D1a) was linked to the seed coat color. The QTL conditioning plant height was in the similar genomic location as the QTLs for days to flowering in this population, indicating pleiotropic effect of one gene or the tight linkage of several genes. These linked markers would be useful in marker assisted selection for these traits in a soybean breeding program.

• 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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2021.04a
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• pp.119-119
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• 2021

• Plant Biotechnology Reports
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• v.5 no.2
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• pp.135-146
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• 2011

The objective of the present research was to map QTLs associated with agronomic traits such as days from sowing to flowering, plant height, yield and leaf-related traits in a population of recombinant inbred lines (RILs) of sunflower (Helianthus annuus). Two field experiments were conducted with well-irrigated and partially irrigated conditions in randomized complete block design with three replications. A map with 304 AFLP and 191 SSR markers with a mean density of 1 marker per 3.7 cM was used to identify QTLs related to the studied traits. The difference among RILs was significant for all studied traits in both conditions. Three to seven QTLs were found for each studied trait in both conditions. The percentage of phenotypic variance ($R^2$) explained by QTLs ranged from 4 to 49%. Three to six QTLs were found for each yield-related trait in both conditions. The most important QTL for grain yield per plant on linkage group 13 (GYP-P-13-1) under partial-irrigated condition controls 49% of phenotypic variance ($R^2$). The most important QTL for 1,000-grain weight (TGW-P-11-1) was identified on linkage group 11. Favorable alleles for this QTL come from RHA266. The major QTL for days from sowing to flowering (DSF-P-14-1) were observed on linkage group 14 and explained 38% of the phenotypic variance. The positive alleles for this QTL come from RHA266. The major QTL for HD (HD-P-13-1) was also identified on linkage group 13 and explained 37% of the phenotypic variance. Both parents (PAC2 and RHA266) contributed to QTLs controlling leaf-related traits in both conditions. Common QTL for leaf area at flowering (LAF-P-12-1, LAF-W-12-1) was detected in linkage group 12. The results emphasise the importance of the role of linkage groups 2, 10 and 13 for studied traits. Genomic regions on the linkage groups 9 and 12 are specific for QTLs of leaf-related traits in sunflower.

• 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.

• Korean Journal of Plant Resources
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• v.30 no.2
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• pp.213-218
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• 2017

Rice is the staple food of at least half of the world's population. Due to global warming, the weather is difficult to forecast nowadays. Therefore, it is necessary to breed various breeding to respond to such changes in the environment. This study was conducted to analyze the QTL about plant form, culm length, ear number and ear length by using 120 lines by anther culture, a cross between the Indica variety Cheongcheong and Japonica variety Nagdong. DNA marker was selected on the QTLs gene, and the following results were obtained. CNDH (Cheongcheong Nagdong Doubled Haploid) lines frequency distribution table curves about culm length, ear number and ear length exhibited showed a continuous variation close to a normal distribution. QTL analysis result, on culm length qPlL1-1 and qPlL1-2 were detected on the chromosome 1 and qPlL5 was detected on the chromosome 5. However, on ear length qPL2, qPL3 and qPL10, were detected on the chromosome 2, 3 and 10, while on ear number qPN1-1 and qPN1-2 were detected on the chromosome 1, qPN9 was detected on the chromosome 9. The QTLs related to culm length was found to chromosomes 5 and LOD scores were 3.81. The QTLs related to ear length was found to chromosomes 2 and 3 LOD scores were 7.13 and 3.20. The QTLs related to ear number was found to chromosome 9 and LOD scores were 4.27. Twenty two (22) Japonica cultivars and 12 Indica cultivars were analyzed polymorphisms, using selected 9 markers from the result about plant form analysis. RM5311, RM555 and RM8111 about the culm length, the ear length and number of ear were selected on the standard of Cheongcheong and Nagdong. Each rate of concordances about the culm length, the ear length and number of ear are 44.11%, 41.17% and 44.11%.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.5
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• pp.613-620
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• 2012

Marbling from intramuscular fat is an important trait of meat quality and has an economic benefit for the beef industry. Quantitative trait loci (QTL) fine mapping was performed to identify the marbling trait in 266 Hanwoo steers using a 10K single nucleotide polymorphism panel with the combined linkage and linkage disequilibrium method. As a result, we found nine putative QTL regions for marbling: three on BTA6, two on BTA17, two on BTA22, and two on BTA29. We detected candidate genes for marbling within 1 cM of either side of the putative QTL regions. Additionally, to understand the functions of these candidate genes at the molecular level, we conducted a functional categorization using gene ontology and pathway analyses for those genes involved in lipid metabolism or fat deposition. In these putative QTL regions, we found 95 candidate genes for marbling. Using these candidate genes, we found five genes that had a direct interaction with the candidate genes. We also found SCARB1 as a putative candidate gene for marbling that involves fat deposition related to cholesterol transport.