Alterations affecting the status of robustness and health can bring about physiological changes including hematological parameters in pigs. To identify quantitative trait loci (QTL) associated with 8 hematological phenotypes (one leukocyte trait, six erythrocyte traits, and one platelet trait), we performed a genome-wide association study using the Porcine SNP 60K BeadChip in an intercross population between Landrace and Korean native pigs. A total of 36,740 SNPs from 816 F2 offspring were analysed for each blood related traits after filtering by quality control. Data were analysed genome-wide rapid association using the mixed model and regression (GRAMMAR) approach. A total of 257 significant SNPs (P<1.36x10-6) on SSC3, 6, 8, 13, and 17 were detected for blood related traits in this study. Interestingly, the genomic region between 17.9 and 130 Mb on SSC8 was found to be significantly associated with RBC, MCV, and MCH. Our results include 5 significant SNPs within five candidate genes (KIT, IL15, TXK, ARAP2, and ERG) for hematopoiesis. Further validation of these identified SNPs could give valuable information for understanding the variation of hematological traits in swine.

품종 육종의 주요 목표중 수량의 증가를 위한 요인들을 선발하는 것이 중요하며, 콩에서 수량을 결정하는 요인들중에서는 협수와 립수가 중요한 요인으로 알려져 있다. 따라서 본 연구는 큰올콩과 익산10호를 교배하여 얻은 F10세대의 RIL 계통을 이용하여 수량에 관여하는 요인중 주당협수와 주당립수 및 협당립수를 조절하는 QTL을 분석하였다. 주당협수는 염색체 5번( LG A1), 6번(LG C2), 8번(LG A2)과 9번(LG K) 및 18번(LG G)에서 5개의 독립된 QTL이 탐지되었으며, 주당립수는 염색체 1번(LGD1a+Q), 6번(LG C2), 9번(LG K), 13번 (LG F)과 17번(LG D2) 및 18번(LG G)에서 6개의 독립된 QTL이 탐지되었다. 협당립수는 2개의 독립된 QTL이 염색체 11번(LG B1)과 19번(LG L)에서 탐지되었는 데 염색체 19번(LG L)에서 탐지된 QTL은 전체 변이의 19.3%를 설명하는 주요 QTL이었다. 한편 주당협수와 주당립수는 염색체 6번(LG C2)과 9번(LG K) 및 18번(LG G)에서 공통된 QTL이 탐지되었다.

Molecular genetic markers were genotyped used to detect chromosomal regions which contain economically important traits such as growth traits in pigs. Three generation resource population was constructed from a cross between the Korean native boars and Landrace sows. A total of 193 F2 animals from intercross of F1 were produced. Phenotypic data on 7 traits, birth weight, body weight at 3, 5, 12, 30 weeks of age, live empty weight were collected for F2 animals. Animals including grandparents (F0), parents (F1), offspring (F2) were genotyped for 194 microsatellite markers covering from chromosome 1 to 18. Quantitative trait locus analyses were performed using interval mapping by regression under line-cross model. To characterize presence of imprinting, genetic full model in which dominance, additive and imprinting effect were included was fitted in this analysis. Significance thresholds were determined by permutation test. Using imprinting full model, four QTL with expression of imprinted effect were detected at 5% chromosome-wide significance level for growth traits on chromosome 1, 5, 7, 13, 14, and 16.

Seed dormancy is an important adaptive mechanism to protect seeds under the unfavorable environments. Unlike to wild type species, the seed dormancy trait of cultivated crops has been weakened by breeding programs during the domestication period. Weak seed dormancy often causes preharvest sprouting (PHS) problem in many cereal crops that result in significant economic loss. The seed dormancy is a quantitative trait loci (QTL) controlled by multiple genetic and environmental factors. So far, many QTLs for seed dormancy have been identified from rice and wheat as well as in the model plant Arabidopsis. Unveiling of QTL genes and complex mechanisms underlying seed dormancy is accelerated by the rapid progress of crop genomics. In the present study, we reviewed current status of research progress on the seed dormancy QTLs and correlated genes in Arabidopsis and cereal crops.

Radish, Raphanus sativus(2n = 18), belonging to the brassicaceae family, is herbaceous plant with 1-2 years life cycle. It is cultivated worldwide for producing leafy and root vegetables. Although an economically important crop, the genetics of yield and quality traits, disease resistance are not well-studies. The major purpose of this project is development of molecular breeding technology in radish. In this project, quantitative trait loci (QTL) for Fusarium wilt resistance of radish were analyzed. To identify QTL, genetic linkage map of radish was constructed using F2 mapping population derived from a cross between two inbred lines, “DB01” (resistant) and “DB05” (susceptible). A total 319 markers have been mapped into nine linkage groups, covering 639.3cM with an average distance of 2cM between loci. QTL mapping detected 2 loci conferring Fusarium wilt resistance. Two QTLs were located on LG3 and LG7, respectively. The QTL of LG3, flanked by EAGGMCT6 and WALK500 marker, exhibited a LOD value ranging from 2.3 to 8.7, and the R2 (Phenotypic variations) ranging from 28 to 48% in four tests. This QTL was named qYR1. The QTL of LG7, flanked by EACCMCAC-202 and DCJ14-390 marker, exhibited a LOD value ranging from 6.2 to 10.6, and the R2 ranging from 42 to 55% in four tests. This QTL was named qYR2. The results of the QTL analysis may be useful in marker-assisted selection (MAS) of Fusarium wilt resistant radish cultivars.

Low temperature is a major abiotic stress that adversely affects rice production in rice cultivation regions of the world. Low temperature during the rice growing season, can inhibit growth and development at any development stage, from germination to grain filling. Among the rice growth stage, reproductive stage was known as the most sensitive to low temperature, causing sterile grain and lead yield loss. However, low temperature during the grain filling stage also, may cause delay and incomplete grain maturation. In this study QTL analysis were performed to identify the QTLs associated with percent of grain filling under low temperature condition during the grain filling stage. A 139 RIL derived from a cross between ‘Milyang23’ (Tong-il, cold susceptible) and ‘Gihobyeo’(Japonica, cold tolerance) were exposed to air and water of 17℃ at the same time for 14 days during the grain filling stage. One significant QTL associated to percent of grain filling was detected on chromosome 7. This QTL could explain 14.7% of the phenotypic variance for percent of grain filling. We have the plan to confirm the detected QTL through further study.

Seed weight (SW), often expressed as 100-seed weight (HSW), is an important yield component in soybean and has been found to show positive correlation with seed yield. It is shown to behave as a quantitative trait controlled by many loci that are largely unclear. In this study, we represent the identification of chromosomal regions controlling the seed weight in soybean. We used a Recombinant Inbred Line (RIL) population, consisting of 188 lines derived from a cross of a wild soybean PI483463 (HSW: 0.85g) and a cultivated soybean cultivar Hutcheson (HSW: 14.05g) to identify the chromosomal regions controlling the SW trait. The population, along with parental samples and check, William82 (HSW: 21.2g) was grown for four years and phenotype data was recorded postharvest. A total of 535 SNP and 16 SSR markers, polymorphic between the parents were employed to genotype the RILs using Golden gate assay to develop the linkage map. Whole genome QTL scanning identified a total of 17 QTLs, spanning 10 chromosomes for the 100-seed weight. All these QTLs explained phenotypic variation (PV) in the range of 3.77 to 12.33%. Of the 17 QTLs, 2 QTLs qSWA1-1 and qSWD2-1, found to be the consistent QTLs, expressing in all the four environments. The QTL qSWD2-1 explained highest contribution to the total PV with 10.04 -12.23 %. The remaining 15 QTLs were identified in at least one environment with PV ranging up to 10.39%. The findings from this study will provide useful information to understand the genetic and molecular basis of SW and facilitate further genomic research leading to the yield improvements in soybean.

High grain yield is one of the most important traits for improvement in rice breeding program. Much attention has been given to the genetic bases of spikelets per panicle (SPP) and grain weight (GW) because of their imporftance in rice yield. In this study, IL28, near isogenic line (NIL) developed by introgressing chromosomal segments from Moroberekan into Ilpumbyeo, showed significant increase in number of spikelets per panicle and 1,000 grain weight compare to the recurrent parent Ilpumbyeo. Quantitative trait locus (QTL) analysis in 1150 F2 plants derived from a cross between IL28 and Ilpumbyeo, indicated that both qspp6 and qgw6 were located in the interval RM3430 – RM20580. To map the QTL more precisely, substitution mapping of qspp6 and qgw6 using F4 lines was conducted. As a result of substitution mapping with fifty F4 lines, qspp6 was mapped to an 429kb interval between RM20521 and RM20562 while qgw6 was mapped to a 267kb interval between RM20562 and RM20572 based on the japonica genome sequence. This result seems to indicate that qspp6 and qgw6 are two different genes. It is notable that these QTL, qspp6 and qgw6 are independence from undesirable height and flowering time. Moreover, there was no negative correlation between qspp6 and qgw6 when two genes are pyramided in the genetic background of Ilpumbyeo. SSR markers tightly linked to the qspp6 and qgw6 will facilitate cloning of the gene underlying these QTLs as well as marker assisted selection for variation in SPP and TGW in an applied breeding program.

Spikelets per panicle (SPP) is one of the most important traits associated with rice yield. In this study, IL28, a near isogenic line (NIL) developed by introgressing chromosomal segments from ‘Moroberekan’ into ‘Ilpumbyeo’ showed significantly higher number of spikelets per panicle than the recurrent parent, ‘Ilpumbyeo’. Quantitative trait locus (QTL) analysis in 243 F2 plants derived from a cross between IL28 and Ilpumbyeo indicated that a QTL for spikelets per panicle, qSPP6 was located in the interval RM3430 - RM20580. The Moroberekan allele increased SPP. The fact that QTLs for panicle length and the number of secondary branches were mapped in the same interval as qSPP6 appears to indicate that this locus was associated with panicle structure. To map the QTL more precisely, substitution mapping of qSPP6 using F3 lines was conducted. Substitution mapping with 41 F3 lines further narrowed the interval containing not only qSPP6 for spikelets per panicle but also qNDW6 for node width to about 680-kb between markers RM20521 and RM20572 based on Nipponbare genome sequence. The locus, qSPP6 is of particular interest because of its independence from undesirable height and flowering time. SSR markers tightly linked to the qSPP6 will facilitate cloning of the gene underlying this QTL as well as marker assisted selection for variation in SPP in the breeding program.

The objective of this study were to identify QTLs for agronomic traits using a set of introgression lines carrying wild rice (Oryza rufipogon) segment in cultivated rice (ssp. japonica cv. Hwaseongbyeo). Ninety-six ILs were evaluated for seven agronomic traits, amylose and protein contents. The proportion of the recurrent genome in ILs ranged from 87.8 to 100%, with an average of 96.7%. The mean number of homozygous and heterozygous donor segments were 2 (ranging 0-7) and 1.7 (ranging 0-6), respectively, and the majority of these segments had size less than 10 cM. A total of 22 quantitative trait loci were identified for 9 traits and each QTL explained 7.2% to 56.6% of the phenotypic variance. Some QTLs were clustered in a few chromosomal regions. A first cluster was located near RM527 on chromosome 6 with QTLs for culm length, panicle length, days to heading, 1000-grain weight and protein content. Three ILs with high spikelets per panicle compared to the recurrent parent were selected to detect and fine map the wild segments responsible for this variation. The results will be discussed.

Spikelets per panicle is one of the most important trait associated with rice yield component. In this study, IL28, near isogenic line (NIL) developed by introgressing chromosomal segments from Moroberekan into Ilpumbyeo, showed significantly higher number of spikelets per panicle than the recurrent parent Ilpumbyeo. Quantitative trait locus (QTL) analysis in 243 F2 plants derived from a cross between IL28 and Ilpumbyeo, indicated that a QTL for spikelets per panicle, qspp6, located in the interval RM3430 – RM20580. The fact that QTLs for panicle length and secondary branch number were mapped in the same interval as that for qspp6 indicated that this locus was associated with panicle structure. To map the QTL more precisely, substitution mapping of qspp6 using F4 lines was conducted. As a result, substitution mapping with ten F4 lines further narrowed the interval containing qspp6 to about 429kb between marker RM20521 and RM20562 based on the japonica genome sequence. The locus, qspp6 is of particular interest because of its independence from undesirable height and flowering time. SSR markers tightly linked to the qspp6 will facilitate cloning of the gene underlying this QTL as well as marker assisted selection for variation in SPP in an applied breeding program.

The whitebacked planthopper (WBPH) is one of the most serious insect pests of rice. The nymphs and adults suck the phloem sap which causes reduced plant vigor, stunting, yellowing of leaves. We employed a mapping population composed of 113 doubled haploid lines (DHLs), derived from a cross between resistant cultivar ‘Cheongcheong’ and susceptible cultivar ‘Nagdong’, to identify the quantitative trait loci (QTL) associated with WBPH resistance. The DH population was evaluated for resistance to WBPH using seed box screening test. The WBPH resistance of each lines or plants was estimated when susceptible check ‘Nagdong’ was killed using 1-9 scale according to Standard Evaluation System for Rice (IRRI, 1988). A linkage map was constructed with 119 polymorphic microsatellite markers using the Joinmap 4 software program to adjust for segregation distortion. Transgressive segregation was observed on WBPH resistance. Two significant QTLs conferring resistance to WBPH, qwbph6.1 and qwbph6.2, were detected in the regions of RM588-RM276 and RM527-RM528 on chromosome 6 with LOD scores of 3.7 and 2.4, respectively. They collectively explained 55% of phenotypic variation. These two QTLs have large effects on WBPH resistance and may be useful for establishment of marker assisted selection (MAS) in the rice breeding programs.

본 연구에서는 자포니카형인 '낙동'과 통일형인 '삼강' 조합의 DH 집단을 이용하여 식미를 결정하는 특성 중 하나인 호응집성과 미립의 이화학적 특성인 천립중, 장폭비, 아밀로즈 함량, 단백질 함량, 지질 함량 및 전분 함량 간 상관관계를 검정하였다. 또한 호응집성의 QTL을 분석하고, 각 QTL에 속하는 DNA marker와 DH 집단의 호응집성 및 품종별 호응집성 간 관계를 분석하였다. '삼강/낙동' DH 집단의 호응집성 범위는 35~94 mm로 비교

본 연구는 최근 우리나라에서 급격하게 발생되고 있는 콩 불마름병에 대한 저항성 중간모본을 육성하고자 할 때 marker-assisted selection에 적용할 수 있는 저항성 근접 분자표지를 개발하고자 수행하였다. 1. 불마름병에 이병성인 큰올콩과 저항성인 신팔달콩의 RIL 116 계통에 대하여 콩 불마름병 균주 8ra에 대한 저항성과 연관된 QTL을 탐색한 결과 포장에서는 연관군 B2, D2, I와 K에서, 온실에서는 연관군 D2, C1과 F에서