• Journal of Korean Society of Forest Science
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• v.95 no.4
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• pp.483-494
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• 2006

We conducted QTL mapping for 6-year growths of open-pollinated half-sib progenies from a selected clone 7-1037 in Pinus taeda. With an AFLP marker analysis on haploid DNA samples from the megagametophytes of the open-pollinated seeds, we constructed 20 framework maps spanning a total of 1,869 cM in total length and 18.5 cM in an average interval length between markers. Composite interval mapping reveals that one QTL explains 5.9% of the total phenotypic variation of height, and three QTLs account for 3.9~5.6% of the variation of diameter at breast height (DBH). There are no correlations between the QTLs. The genetic effects of the QTLs are 39.6 cm in height and 7.20~9.41 mm in DBH, respectively, The average effects of gene substitution of the markers closely linked with the QTLs are 44.3 cm in height and 8.38~11.81 m in DBH. Under an assumption that the within-family heritability for the growth traits of loblolly pine is less than 0.2, the QTLs account for 26.8% of the additive genetic variance of the progenies. In terms of relative selection efficiency, the individual selection based on QTL markers could be 5 times as high as phenotypic selection. The results in this study indicate that the QTL mapping method with open-pollinated half-sib family could be more practical and applicable to the conventional seed orchard-based selection work than other mapping methods with a single full-sib family, in particular from the viewpoint that it can provide crucial information for within-family individual selection such as breeding value.

• Asian Journal of Turfgrass Science
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• v.22 no.1
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• pp.85-100
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• 2008

Gray leaf spot (GLS) is a serious fungal disease caused by Pyricularia oryzae Cavara, recently reported on the important turf and forage species, perennial ryegrass (Lolium perenneL.). This fungus also causes rice blast, which is usually controlled by host resistance, but durability of resistance is a problem. Few instances of GLS resistance have been reported in perennial ryegrass. However, two major QTL for GLS resistance have been detected on linkage groups 3 and 6 in an Italian x perennial ryegrass mapping population. To confirm that those QTL are still detectable in the next generation and can function in a different genetic background, a resistant segregant from this population has been crossed with an unrelated susceptible perennial clone, to form a new mapping population segregating for GLS resistance. QTL analysis has been performed in the new population, using two different ryegrass field isolates and RAPD, RFLP, and SSR marker-based linkage maps for each parent. Results indicate the previously identified QTL on linkage group 3 is still significant in the new population, with LOD and percent of phenotypic variance explained ranging from 2.0 to 3.5 and 5% to 10%, respectively. Also two QTL were detected in the susceptible parent, with similar LOD and phenotypic variance explained. Although the linkage group 6 QTL was not detected, the major QTL on linkage group 3 appears to beconfirmed. These results will add to our understanding of the genetic architecture of GLS resistance in ryegrass, which will facilitate its use in perennial ryegrass breeding programs.

• Journal of Life Science
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• v.16 no.6
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• pp.949-954
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• 2006

Soybean [Glycine max (L.) Merr.] is an important crop, accounting for 48% of the world market in oil crops. Improvement of the quality and quantity of soybean seed constituents is one of the most important objectives in soybean breeding. Protein content and seed size are important properties to determine the quality of tofu and soy sprouts respectively. The objective of this study was to identify quantitative trait loci (QTLs) that control seed weight, protein and oil content in soybean. The 117 $F_{2:10}$ recombinant inbred lines (RlL) developed from a cross of 'Keunolkong' and 'Shinpaldalkong' were used. Narrow-sense heritability estimates based on a plot mean on seed weight, protein and oil content were 0.8, 0.78 and 0.71, respectively. Four independent QTLs for seed weight were identified from linkage group (LG) F, I and K. Five QTL for protein content were located on LG D1b, E, H, I and L. Oil content was related with six QTLs located on LG D1b, E, G, I, J and N. Protein and oil content have three common QTLs on LG D1b, E and I. Thus, we identified major loci improving soybean seed quality.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.7
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• pp.932-937
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• 2002

A partial genome scan using porcine microsatellites was carried out to detect quantitative trait loci (QTL) for backfat thickness (BFT) in a pig reference population. This population carried QTL on chromosomes 1, 13 and 18. The QTL on chromosome 1 was located between marker loci S0113 and SW1301. The QTL corresponded to very low density lipoprotein receptor gene (VLDLR) in location and in biological effects, suggesting that VLDLR might be a candidate gene. The QTL found on chromosome 13 was found between marker loci SWR1941 and SW864, but significance for the marker-trait association was inconsistent by using data with different generations. The QTL on chromosome 18 was discovered between markers S0062 and S0117, and it was in proximity of the regions where IGFBP3 and GHRHR were located. The porcine obese gene might be also a candidate gene for the QTL on chromosome 18. In order to understand genetic architecture of BFT better, fine mapping and positional comparative candidate gene analyses are necessary.

• Korean Journal of Breeding Science
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• v.41 no.4
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• pp.429-436
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• 2009

We conducted a QTL analysis of grain quality traits using 117 $BC_3F_4$ and $BC_3F_5$ lines developed from a cross between Ilpumbyeo and Moroberekan. Genotypes of 117 $BC_3F_5$ lines were determined using 134 simple sequence repeat (SSR) markers. A linkage map constructed using 134 SSR markers was employed to characterize quantitative trait loci (QTL). The 117 $BC_3F_4$ and $BC_3F_5$ lines were evaluated for eleven grain quality traits in 2005 and 2006. A total of 18 QTLs were identified for eleven traits, and the phenotypic variance explained by each QTL ranged from 9.9% to 35.2%. Moroberekan alleles contributed positive effects in the Ilpumbyeo background at two QTL loci for 1,000 grain weight. Four QTLs, two for chalky rice and one each for 1,000 grain weight and head rice were consistently detected in two consecutive years indicating that these QTLs are stable. Clusters of QTLs were observed in three chromosome regions. One cluster harboring five QTLs including head rice and brown rice ratio near SSR markers RM190 and RM314 was detected on chromosome 6. Another cluster harboring grain weight and white belly was detected on chromosome 2. Increase in white belly at this locus might be due to the increase in grain weight due to the presence of the Moroberekan allele. The Moroberekan alleles at two QTL loci, gw3 and gw4 associated with increased grain weight might be useful in breeding programs to develop high-yielding cultivars.

• Proceedings of the Korea Society of Poultry Science Conference
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• 2003.11a
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• pp.135-137
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• 2003

The analyses of relationship between specific genes and economic traits were performed on the basis of the genetic characterization of Korean native chicken in this study. Three generation reference pedigree was established from the several lines of Korean native chicken and cornish breed for the linkage analysis and many economic traits were collected for QTL(quantitative trait loci) detection. The experimental design were planed to detect QTLs of meat quality and laying performance from those two distinctive breeds.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.43 no.4
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• pp.199-204
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• 1998

This study was conducted to investigate the chromosomal locations and effects of quantitative trait loci (QTL) associated with chemical properties of rice (Oryza sativa L.). One hundred sixty four recombinant inbred lines (MGRILs) of $F_{11}$ were derived from the cross between Milyang 23, Tongil type, and Gihobyeo, japonica type. They were evaluated for 7 traits of chemical property in rice. Transgressive segregation was observed for all traits examined. Eight significant QTLs were detected (LOD$\geq$2.0) for five traits, including two QTLs for amylose content, two QTLs for potassium content, one QTL for ratio of magnesium to potassium, one QTL for fat content and two QTLs for ash content. Phenotypic variation explained by each QTL ranged from 7.2% to 14.4%. However, no significant QTL was detected for magnesium and protein contents. In amylose content and ash content M alleles originated from Milyang 23 were responsible for increasing these traits and J alleles originated from Gihobyeo also responsible for increasing these traits. Pleiotropic effects of single QTLs on different traits are observed.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.6
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• pp.772-779
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• 2005

The objectives of this study were to examine problems with using F$_1$ data by simulation, association of marker loci and QTL from crosses of inbred parental lines and to enumerate the preliminary characterization of genetic superiority within inbred parental lines. In this study, the association between markers for QTL used as covariates and estimates of variance components due to effects of lines was investigated through computer simulation. The effects of size of population to develop inbred lines and initial frequencies and magnitudes of effects of QTL were also considered. Results show that estimates of variance components due to line effects are influenced by including marker information as covariates in the model for analysis. Estimates of line variance were increased by adding marker information into the analysis, because negative covariances between effects associated with the markers and the remaining effects associated with other loci existed. However, the fit of the model as indicated by the log likelihood improved by adding more markers as covariates into the analysis. Marker assisted selection will be beneficial when markers explain unexplained genetic difference during selection procedure. Markers can be used to identify QTLs affecting traits, and to select for favorable QTL alleles. To efficiently use genetic markers, location of markers at the genome must be identified. The estimates of variance due to effects of with and without marker information used as covariates in the analysis were investigated. The estimates of line variances were always increased when markers were included as covariates for the model because a negative covariance were existed.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.12
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• pp.1665-1669
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• 2001

A QTL was localized near S0120 on porcine chromosome 18. The QTL was significant (p<0.05) for average daily gain (ADG) of body weight and backfat thickness (BFT). The estimates of additive and dominance effects for the QTL were 0.0135 kg/day (p<0.001) and 0.0138 kg/day (p>0.5) for ADG and 1.6115 mm (p<0.001) and 0.9281 mm (p>0.05) for BFT. The location of this QTL coincided with a few growth hormone pathway genes. This study suggested that a QTL allele probably resulted from a mutation responsible for physiological lipase deficiency favoring obesity. This QTL might be important to obesity as well as growth in pigs.

• Plant Biotechnology Reports
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• v.4 no.1
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• pp.61-73
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• 2010

Quantitative trait loci (QTL) associated with six physical traits of cooked rice and seven chemical properties of rice grain were identified using a recombinant inbred (RI) population of rice evaluated over 3 years at the National Honam Agricultural Research Institute in Korea. The RI population consisted of 164 lines derived from a cross between Milyang23 and Gihobyeo, and the genetic map consisted of 414 molecular markers. A total of 49 QTL were identified for the 13 physico-chemical properties using composite interval mapping. Of these, 13 QTL were identified for 2 or more years, while 36 were detected in only 1 year. Five QTL were identified over all 3 years and will be useful for marker-assisted improvement of rice grain quality in Korea. The two QTL with the highest LOD scores, adhesiveness1.2 and potassium content7.1, provide a valuable starting point for positional cloning of genes underlying these QTL.