• KOREAN JOURNAL OF CROP SCIENCE
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• 제49권5호
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• pp.423-428
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• 2004

Soybean seeds contain high amounts of isoflavones that display biological effects and isoflavone content of soybean seed can vary by year, environment, and genotype. Objective of this study was to identify quantitative trait loci that underlie isoflavone content in soybean seeds. The study involved 85 $F_2$ populations derived from Korean soybean cultivar 'Kwangkyo' and wild type soybean 'IT182305' for QTL analysis associated with isoflavone content. Isoflavone content of seeds was determined by HPLC. The genetic map of 33 linkage groups with 207 markers was constructed. The linkage map spanned 2,607.5 cM across all 33 linkage groups. The average linkage distance between pair of markers among all linkage groups was 12.6 cM in Kosambi map units. Isoflavone content in $F_2$ generations varied in a fashion that suggested a continuous, polygenic inheritance. Eleven markers (4 RAPD, 3 SSR, 4 AFLP) were significantly associated with isoflavone content. Only two markers, Satt419 and CTCGAG3 had F-tests that were significant at P<0.01 in $F_2$ generation for isoflavone content. Interval mapping using the $F_2$ data revealed only two putative QTLs for isoflavone content. The peak QTL region on linkage group 3, which was near OPAG03c, explained $14\%$ variation for isoflavone content. The peak QTL region on linkage group 5, which was located near OPN14 accounted for $35.3\%$ variation for isoflavone content. Using both Map-Maker-QTL $(LOD{\geq}2.0)$ and single-factor analysis $(P{\leq}0.05)$, one marker, CTCGAG3 in linkage group 3 was associated with QTLs for isoflavone content. This information would then be used in identification of QTLs for isoflavone content with precision

• Korean Journal of Poultry Science
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• 제40권3호
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• pp.223-234
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• 2013

Poultry industry is abounding day by day as it engrosses less cost of investment per bird as compared to large animals. Poultry have the most copious genomic tool box amongst domestic animals for the detection of quantitative trait loci (QTL) and marker assisted selection (MAS). Use of multiple markers and least square techniques for mapping of QTL affecting quality and production traits in poultry is in vogue. Examples of genetic tests that are available to or used in industry programs are documented and classified into causative mutations (direct markers), linked markers in population-wide linkage disequilibrium (LD) with the QTL (LD markers), and linked markers in population wide equilibrium with the QTL (LE markers). Development of genome-wide SNP assays, role of 42 K, 60 K (Illumina) and 600 K (Affymetrix$^{(R)}$ Axim$^{(R)}$) SNP chip with next generation sequencing for identification of single nucleotide polymorphism (SNP) has been documented. Hybridization based, PCR based, DNA chip and sequencing based are the major segments of DNA markers which help in conducting of MAS in poultry. Economic index-marker assisted selection (EI-MAS) provides platform for simultaneous selection for production traits while giving due weightage to their marginal economic values by calculating predicted breeding value, using information on DNA markers which are normally associated with relevant QTL. Understanding of linkage equilibrium, linkage dis-equilibrium, relation between the markers and gene of interest are quite important for success of MAS. This kind of selection is the most useful tool in enhancing disease resistance by identifying candidate genes to improve the immune response. The application of marker assisted selection in selection procedures would help in improvement of economic traits in poultry.

• Korean Journal of Breeding Science
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• 제41권3호
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• pp.236-243
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• 2009

This study was conducted to develop a japonica-type rice cultivar with brown planthopper (BPH) resistance using DNA markers. A doubled haploid (DH) population consisting of 120 pure-lines was established by anther culture of $F_1$ hybrids between 'Samgang', a Tongil type BPH resistance cultivar, and 'Nagdong', a japonica cultivar. To determine the map position of genes responsible for BPH resistance in rice, a genetic map was constructed based on 120 DH lines. A total of 162 molecular markers were classified into 12 linkage groups, covering 1,884 Kosami centimorgan (cM) with an average of 11.6 cM. Five QTLs (qBPR3, qBPR6, qBPR7, qBPR8, and qBPR12) associated with BPH resistance were identified and mapped on chromosomes 3, 6, 7, 8, and 12, respectively, using the genetic map constructed in this study. To analyze the relationship between BPH resistance and agronomic traits, a total of eight QTLs related to the agronomic traits were detected on 12 rice chromosomes. In an analysis of relationships, three QTLs (qBPR3, qBPR7, and qBPR8) showed a linkage with tested agronomic traits. A QTL (qBPR3) located on chromosome 3 (RM282-3023) was closely linked to culm length (qCL3). The QTL (qBPR8) for BPH resistance on the short arm of chromosome 8 also overlapped the region detected in culm length (qCL8).

• Korean Journal of Plant Resources
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• 제10권3호
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• pp.247-249
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• 1997

Seed protein and oil content is important trait in the soybean. Both seed protein and oil content in this plant species is inherited quantitatively. A 68-plant $F_2$ segregation population derived from a mating between Mercury and PI 467.468 was evaluated with random amplified polymorphic DNA (RAPD) markers to identify QTL related to seed protein and oil content. Marker OPB12 was found to be associated with differences in seed protein content. Four markers, OPA09b, OPM07b, OPC14, and OPN11b had highly significant effects on seed oil content. By interval mapping, the interval between marker OPK3c and OPQ1b on linkage group 13 contained a QTL that explained 25.7% variation for seed oil content.

• Korean Journal of Breeding Science
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• 제42권4호
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• pp.357-364
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• 2010

In a previous study, we mapped 12 QTLs for 1,000 grain weight (TGW) in the 172 $BC_2F_2$ lines derived from a cross between Oryza sativa ssp. Japonica cv. Hwaseongbyeo and O. rufipogon. These QTLs explained 5.4 - 11.4% of the phenotypic variance for TGW. Marker-aided selection combined with backcrosses was employed to develop QTL-NILs for each QTL. $BC_2F_2$ lines with each target QTL were backcrossed to Hwaseongbyeo twice and then allowed to self to produce $BC_4F_5$ populations. SSR markers linked to TGW were employed to select QTL-NILs with the respective target QTL. Six QTL-NILs with the recurrent parent, Hwaseongbyeo were evaluated for nine traits for three years from 2007 and 2009. Differences were observed between each of the 6 QTL-NILs and Hwaseongbyeo in TGW. In addition to TGW, these QTL-NILs displayed differences in other agronomic traits possibly indicating a tight linkage of genes controlling these traits. The direction of the QTL for TGW in 6 QTL-NILs was consistent as in the $BC_2F_2$ lines from the same cross. Difference in TGW between each of the QTL-NILs and Hwaseongbyeo was associated with the difference in one or two grain shape traits; grain length, grain width, and grain thickness. SSR markers linked to the QTL for TGW will facilitate selection of the grain shape character in a breeding program to diversify grain shape and provide the foundation for map-based gene isolation. Also, the QTL-NILs developed in this report and the progenies from crosses between the QTL-NILs will be useful in clarifying epistatic interactions among QTLs for TGW.

• KOREAN JOURNAL OF CROP SCIENCE
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• 제45권4호
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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.

• KOREAN JOURNAL OF CROP SCIENCE
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• 제42권6호
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• pp.712-721
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• 1997

The objectives of this study were; (1) to identify and localize QTLs for resistance to soybean cyst nematode(SCN) race 5 on RAPD map, (2) to idntify the magnitude and mode of inheritance for each QTL, and (3) to identify the best combinations of QTLs for resistance to SCN race 5. Based on the univariate regression analysis, we detected 26 markers(22 RAPD and 4 RFLP) which showed significant association(P<0.05) with resistance to SCN race 5. From MAPMAKER /QTL analysis, we identified two regions (LGC-20 and Group 2) for resistance to SCN race 5. The QTL that was localized at 8.0 cM from pK418C on LGC-20 showed a recessive mode of inheritance and the QTL that was localized between W03 and E02$^3$ on Group 2 showed a dominant mode of inheritance. Two pairs of flanking markers (E02$^3$ and W03, pK418C and pK418E$_1$) and one unlinked RAPD marker, G10$^1$ were used for multiple regression analysis. Marker combination which was composed of 4 markers, E02$^3$, G10$^1$, W03, and pK418E$_1$, explained the highest amount of phenotypic variation by SCN (35.2％). Further research for the identification of QTLs for resistance to SCN race 5 to explain larger portion of phenotypic variation is needed.

• The Plant Pathology Journal
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• 제18권5호
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• pp.266-270
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• 2002

Inbred lines of Chinese cabbage KU-101 (resistant line against Plasmodiophora brassicae race race 6) and CS-113 (susceptible line) were crossed and their progeny lines F$_1$, BC$_1$F$_1$, F$_2$, and F$_3$ were produced for the construction of the genetic linkage map of R brassicae race 6-resistant Brassica campestris ssp. pekinensis genome. Restriction fragment length polymorphism (RFLP) was applied to compare between parents and their f$_2$ progenies with a total of 192 probes and 5 restriction enzymes. The constructed RFLP map covered 1,104 cM with a mean distance between genetic marker of 8.0 cM, and produced 10 linkage groups having 121 genetic loci. The loci of P. brassicae race 6 (CR6)-resistant Brassica genome were determined by interval mapping of quan-titative trait loci (QTL), which resulted from bioassay using the same race of the fungi in P3 population. Resistant loci were estimated in numbers 1 (Gl) and 3 (G3) linkage groups. In the regression test, Gl had a value of4.8 logarithm of odd (LOD) score, while C3 had values of 4.2-7.2. Given these results, the location of the CR6-resistant loci within the Brassica genome map can now be addressed.

• Asian-Australasian Journal of Animal Sciences
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• 제24권12호
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• pp.1651-1659
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• 2011

This study was conducted to detect quantitative trait loci (QTL) for thirteen growth and meat quality traits in pigs by combing QTL experimental populations. Two F2 reference populations that were sired by Korea native pig (KNP) and dammed by Landrace (LN) or Yorkshire (YK) were generated to construct linkage maps using 123 genetic markers (mostly microsatellites) and to perform QTL analysis on porcine chromosomes (SSCs) 1, 2, 3, 6, 7, 8, 9, 11, 13, 14, and 15. A set of line-cross models was applied to detect QTL, and a series of lack-of-fit tests between the models was used to characterize inheritance mode of QTL. A total of 23, 11 and 19 QTL were detected at 5% chromosome-wise level for the data sets of KNP${\times}$LN, KNP${\times}$YK cross and joint sets of the two cross populations, respectively. With the joint data, two Mendelian expressed QTL for live weight and cooking loss were detected on SSC3 and SSC15 at 1% chromosome-wise level, respectively. Another Mendelian expressed QTL was detected for CIE a on SSC7 at 5% genome-wise level. Our results suggest that QTL analysis by combining data from two QTL populations increase power for QTL detection, which could provide more accurate genetic information in subsequent marker-assisted selection.

• Proceedings of the Korean Society of Crop Science Conference
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.146-146
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• 2017

The pod shattering or dehiscence is essential for the propagation of pod-bearing plant species in the wild, but it causes significant yield losses during harvest of domesticated crop plants. Identifying novel molecular makers, which are linked to seed-shattering genes, is needed to employ the molecular marker-assisted selection for efficiently developing shattering-resistant soybean varieties. In this study, a genetic linkage map was constructed using 115 recombinant inbred lines (RILs) developed from crosses between the pod shattering susceptible variety, Keunol, and resistant variety, Sinpaldal. A 180 K Axiom(R) SoyaSNPs data and pod shattering data from two environments in 2001 and 2015 were used to identify quantitative trait loci (QTL) for pod shattering. A major QTL was identified between two flanking single nucleotide polymorphism (SNP) markers, AX-90320801 and AX-90306327 on chromosome 16 with 1.3 cM interval, 857 kb of physical range. In sequence, genotype distribution analysis was conducted using extreme phenotype RILs. This could narrow down the QTL down to 153 kb on the physical map and was designated as qPDH1-KS with 6 annotated gene models. All exons within qPDH1-KS were sequenced and the 6 polymorphic SNPs affecting the amino acid sequence were identified. To develop universally available molecular markers, 38 Korean soybean cultivars were investigated by the association study using the 6 identified SNPs. Only two SNPswere strongly associated with the pod shattering. These two identified SNPs will help to identify the pod shattering responsible gene and to develop pod shattering-resistant soybean plants using marker-assisted selection.