We conducted a QTL analysis of agronomic traits using 117 BC3F5 and BC3F6 lines developed from a cross between Ilpumbyeo and Moroberekan. Genotypes of 117 BC3F5 lines were determined using 134 simple sequence repeat (SSR) markers. A total of 832 Moroberekan chromosome segments with 410 homozygous and 422 heterozygous, respectively, were detected, and the genetic distance of introgression segments ranged from 0.5 cm to 112.1 cm. A linkage map constructed using 134 SSR markers was employed to characterize quantitative trait loci (QTL). The 117 BC3F5 and BC3F6 lines were evaluated for seven agronomic traits at two locations in 2006 and 2007 and at one location in 2007. A total of 26 QTLs were identified for seven traits including days to heading, and the phenotypic variance explained by each QTL ranged from 9.2% to 24.2%. Moroberekan alleles contributed positive effects in the Ilpumbyeo background at eleven QTL loci including panicle length and spikelets per panicle. Five QTLs, two for days to heading and one each for culm length, panicle length and spikelets per panicle were consistently detected in every occasions indicating that these QTLs are stable. Among them, two QTLs, spp6 for spikelets per panicle and pl6 for paniclel length were localized in the similar region. Increase in spikelets per panicle at this locus might be due to the increase in panicle length, because both traits were associated with increase in spikelets per panicle and panicle length due to the presence of the Moroberekan allele. These Moroberekan QTLs might be useful in breeding programs to develop high-yielding cultivars.

Grain weight (GW) or grain size is the most important target not only as a major component of grain yield, but also associated with the cooking quality in rice breeding program. In a previous study, two loci for grain weight, gw8 and gw9, have been fine map to about 306.4kb and 37.4kb, respectively, in backcross populations derived from a cross between the Korean japonica cultivar Hwaseongbyeo and Oryza rufipigon (IRGC 105491). Both O.rufipogon alleles increased GW in the Hwaseongbyeo background despite the fact that O. rufipogon was the small-seeded parent. To test the effect of pyramiding the QTLs for grain weight, an F2 population consisted of 226 individuals was developed derived from the cross between the two QTLs (gw8 and gw9), and used MAS to select nearly isgenic lines for two QTLs and a pyramiding line. Molecular genotyping of F2 population revealed the existence of interaction between gw8 and gw9. Moreover, the interaction was also confirmed by phenotypic analysis of four QTL-NILs. The results suggest that epistasis interaction is important genetic basis in determining yield traits in rice.

Field resistance is defined as the resistance that allows effective control of a parasite under natural field condition and is durable when exposed to new races of that parasite. To identify the genes for field resistance against rice blast, quantitative trait loci (QTLs) conferring field resistance in japonica rice cultivars were detected and mapped using SSR markers. QTL analysis was carried out in 190 RILs population from the cross between Suweon365 (moderately resistance) and Chucheong (highly susceptible). Fourteen QTLs for nine blast races inoculated were detected on chromosomes 1, 2, 4, 5, 6, 7, 11 and 12. They explained from 6.4 to 39.7% of total phenotypic variation. Eight QTLs for blast nursery screening in 4 regions for three years were detected on chromosomes 1, 2, 4, 5, 11 and 12. The phenotypic variation was explained by each QTL ranged from 5.9 to 38.0%. Three BC2F5 backcrossed progeny lines were developed to transfer the QTLs into the susceptible cultivar Chucheong as a recurrent parent. A NIL4 containing two QTLs Qbl6.2 and Qbl7 for blast races showed the reaction 6 to 7 in blast nursery in 2007 and 2008, respectively. Two lines NIL143 and NIL93 containing Qbl11.2 and Qbl12.1 for QTLs related with field resistance, respectively, were 3 to 4 reactions in blast nursery.

Cold tolerance at every growing stage of rice(Oryza sativa L.) is one of the main determinations for the stable growth in temperature and high elevate area. In the current study, a 181 lines of BC population derived from a cross of Gayabyeo, a Tongil type sensitive to cold and Chhamrong a tolerant to cold were evaluated for cold tolerance with cold water irrigation(17℃) at seeding stage as well as low temperature germinate at 13℃, respectively. The resulting linkage map consists of 157 marker loci, covering all of 12 rice chromosomes and spanning 910cM(Haldane function) with an average interval of 76cM between markers. Three main-effect QTLs were identified. The comparison of the OTLs identified in this cold treatments resulted in an intriquing finding that each treatments were controlled by a major QTL. The QTL qCWI-4 on chromosome 4 was found to increase its additive effect to -0.84 as the cold water irrigate stress was given. In the meanwhile, the QTL qLTG-8 was detected with a LOD score of5.54, explaining up to 13% of the phenotypic variation controlled by Gayabyeo allele. In addition, the QTL qLTGV-3, controlled by Gayabyeo allele with a LOD score of 5.19 explaining about 12.5% of the variation was also identified. These results would favor our better understanding of the genetic control of cold tolerance in rice and be important for the development of rice cultivars with a broaden climatic adaptation.

Cold sensitivity has been shown to vary and the cold tolerance from vegetative to reproductive stage appears to be independent during the life cycle. In the current study, cold tolerance under high elevation rice growing area were evaluated using F4 generation of 181 lines derived from Gayabyeo*2/Chhamrong. Five main-effect QTLs related to days to heading, panicle exertion and spikelet fertility were identified. The QTL qDH-3 on chromosome 3 showed the peak LOD score of 6.3, explaining up to 16.5% of phenotypic variation with additive effect of -2.6. Moreover, the QTL qPE-3 and qSF-3 on chromosome 3 were coincided with the QTL qDH-3 showing an opposite allele effects. Thus, the region harboring marker RM523-RM14281 could be helpful for the selection of cold tolerance genotypes in marker assisted selection(MAS) of rice breeding program.

This study was carried out to identify the quantitative trait loci (QTLs) for traits related to cold tolerance using an introgression lines (ILs) derived from a cross between a japonica weedy rice and a Tongil-type rice. Among the 80 RILs, one line (CR1835) showing tolerance for cold tolerance related to traits such as panicle exsertion and discoloration in the cold water plot was selected and backcrossed to the recurrent parent, Milyang 23. This line possessed Hapcheonaengmi 3 segments on chromosomes 1, 5 and 11. By two backcrosses to Milyang 23 and selfing, a total of 88 BC3F5 progenies were developed. The 88 ILs were evaluated for traits related to agricultural performance in cold water and in control plots. Cold tolerance was measured as difference of the culm length, spikelet fertility between two plots and panicle exsertion in cold water plot. The 88 ILs showed decreased culm length and increased anthocyan content in cold water plot than in the control water plot.

In this study, a 141 BC3F4 lines from across between the O. sativa cv. Milyang23 as there current parent, and O. glaberrima as the donor parent was used to identify favorable QTL alleles from O. glaberrima for yield and yield components. To detect the introgressions, 198 microsatellite markers of known chromosomal position were used for the parental survey. Of the 178 markers, 128 (64.6%) showed polymorphism. Among them, 115 SSR markers were used to construct a genetic linkage map with average interval length of 12.7 cM based on the previous rice molecular genetic map. The mean number of O. glaberrima segments in the population was 1.84 ranging from 0 to 7. The average length of the segments was 16.6 cM and ranged from 0.5 to 232.5 cM. This population consisting of 141 lines was used to evaluate for six traits of agronomic importance and genotypes were determined for 141 BC3F5 using SSR markers. A total of 22 QTLs for 6 traits were detected on chromosomes 1, 2, 3, 4, 5, 6, 7 and 9. Phenotypic variance associated with each QTL ranged 9.5% ~ 58.2%. For 26 of the QTLs identified in this study, the O. glaberrima alleles contributed a desirable agronomic effect despite the over all undesirable characteristics of the wild phenotype. Favorable wild alleles were detected for culm length, panicle length, yield, panicles per plant and 1000-grain weight. When compared with previous studies involving interspecific crosses, it can be concluded that O. glaberrima is useful asa source of valuable alleles for rice improvement. There sults will be discussed.

This study was conducted to identify QTLs for some agronomic traits under two different N-fertilizer conditions. A recombinant inbred population (DT-RILs) between Dasanbyeo (a tongil type rice, derived from an indica × japonica cross and similar to indica in its genetic make-up) and TR22183 (a Chinese japonica variety), consisting of 166 F8 lines, was developed and used for mapping. A frame map of 1,409 cM containing 113 SSR and 103 STS markers with an average interval of 6.5 cM between adjacent marker loci was constructed using the DT-RILs. The DT-RILs were cultivated in ordinary N-fertilizer (N-P2O5-K2O=100-80-80 kg/ha) condition and low N-fertilizer (N-P2O5-K2O=50-80-80 kg/ha) condition in order to compare the different N-fertilizer effects. Grain yield was positively correlated with spikelet number in both conditions. Path analysis revealed that spikelet number is the most positive contributor to grain yield. Twenty-nine single QTLs (S-QTLs) and sixty-five pairs of epistatic loci (E-QTLs) were identified for days to heading, culm length, panicle length, panicle number, spikelet number, spikelet fertility, 1000-grains weight and grain yield in both N-fertilizer conditions. The phenotypic variance explained by these S-QTLs and E-QTLs ranged from 8.8% to 61.1% and from 10.0% to 55.6%, respectively. The total phenotypic variance explained by all the QTLs for each trait ranged from 15.4% to 92.3%.