Analysis Of QTL×Environment Interactions On Main Agronomic Traits In Rice

Molecular marker technology is one of the most important method in ricebreeding because of its increasing and widespread application. In recent years,molecular markers has been implicated to play an important role in the construction ofgenetic linkage map, analysis of genetic diversity, protection of genetic resources,gene cloning and molecular marker assisted breeding. The group of recombinantinbred lines (RIL) which was constructed by Dasanbyeo×TR22183was used asexperimental material and grown in several locations for several years. In this study,7agronomic traits were investigated including the heading stage, culm length, paniclelength, number of panicle per plant, number of spikelet per panicle, spikelet fertilityper panicle and grain weight. In addition, the molecular marker genetic linkage mapabout the agronomic traits of quantitative was constructed on the whole-genome.The main results were as follows:1. Analysis of phenotypic variation of RIL population in different environmentsSeven traits of RIL population had significant differences with each other，andthey had significant differences with parents in the same environment. The same traitalso showed some differences in different environment. The seven traits fitted forcontinuity of normal distribution in a population and complex correlativity presentedamong these different traits.2. The variance analysis of traits in RIL populationAmong7agronomic traits of RIL population，DTH，CL，PL，PN，SN，SF andGW showed significant genotype effects，environmental effects and effects of G×Einteraction.3. The construction of genetic linkage mapUsing the RIL population, we constructed a molecular genetic map containing56pairs of SSR markers and106pairs of STS markers. They covered1081.6cM of rice genome, and the average distance between2markers was6.68cM.4. QTL analysis of the agronomic traits in RIL populationUsing the composite interval mapping method, we analyzed the QTLs for7agronomic traits with phenotype data and molecular data.In total,32QTLs associated with the7agronomic traits were detected. TheseQTLs distributed in23intervals on12chromosomes, and could explain0.37%to18.98%genetic variations. Eighteen of32QTLs were the positive effects and theothers were the negative effects. The DTH, CL, PL, PN, SN, SF and GW respectivelydetected5,5,4,4,5,3and6QTLs, and most of them were distributed onchromosome1,7and8. Among them,5QTLs with SSR marker RM25,3QTLs withSTS marker S03145,2QTLs with SSR marker RM438, STS marker S01140andS07011were detected respectively across.Eighteen QTLs with epistatic effects in7agronomic traits were detected,6ofthem belong to PL. They could explain0.57%~4.55%genetic variations,9of themwere the positive effects and the others were the negative effects.Eight QTLs which interacted with environment were detected in7agronomictraits except heading stage. Three of them such as qSN8-1, qSF8-1and qSF11-4wereinteracted with several environments. The8QTLs could explain0.31%~2.29%genetic variations.Three QTLs with epistatic effects which interacted with environment weredetected, they were qEPN2and qESF1, qESF2which explained2.25%,0.46%and2.08%respectively.