Analysis Of Qtlforyield And Related Traits Using Founder Inbred Lines In Maize

QTL mapping for important agronomic traits in maize is basic work to marker assistant selection (MAS). In this study, the F_2:3 population derived from an elite hybrid Zhengdan958 (Zheng58×Chang7-2) was used to detect the inheritance of yields and their related traits in maize. The partants, F1 and the F_2:3 population were evaluated in five environment. QTL mapping for nine yield traits and three flowering related traits, including Ear Length, Ear diameter, Row Number, Kernels per Row, Cod Diameter, Ear Weight, Kernel Weight per Ear, Rate of Kernel Production, 500 Kernel Weight, and days to tasseling, days to silking, days to anthesis were firstly analyzed by Composite Interval Mapping (CIM) method. Also, using Network 2.0 software with Mixed Linear Model (MCIM), main genetic effect including epistasis and epistatic×environment interactions were analyze. Compared with the single locus QTL and the interaction effects of QTL-by-environment (QE), These results will do great help in fine mapping QTL associated with yield characters and in marker-assisted selection in maize breeding. The main results were summarized as following:1.A genetic linkage map containing 180 SSR polymorphic markers was constructed using 225 F₂ population derieved from the F1 (Zheng58×Chang7-2) , which spanned a total of 1 978.7 cM with an average space between two makers of 11.0 cM. Compared with the IBM map from MaizeGDB website, the order of the markers on ten chromosomes were similar. Among these SSR markers, 22 (12.22%) markers showed the genetic segregation distortion (P<0.05 and P<0.01). The molecular genotypes deriving from parent Zheng58 were 8.98%-33.78%, the average homozygous genotypes of Zheng58 was 23.47%; the molecular genotypes of Chang 7-2 were 10.67%-34.67%, and the average genotypes of Chang 7-2 was 23.53%; the molecular genotypes of F1 were 20.00%-57.78%, and the average genotypes of F1 was 47.71%. The genotypes of the two parents at the marker loci followed 1:2:1 theoretical ratio, so the F_2:3 population was a random one and was fit for QTL analysis.2.Under five environment, Nine yield traits and three flowering traits were evaluated among family lines as well as the two parents. Transgressive segregation was observed for all traits in F_2:3 population, Normal distribution was observed for all traits; The yield relate trait and flowering related traits were significant correlation; the results of analysis of variance (ANOVA) showed significant difference with the lines, the environments, the lines and environment interaction in most of the traits. 3.111 QTLs were detected for 9 yield related traits under five environments. Contribution of single QTL to phenotypic variation varied from 3.39% to 31.15%, there were 14 QTLs showing more than 10% of phenotypic variation; 7 major QTLs for EL (qEL3-1 and qEL4), ED (qED3), RN (qRN3), KR (qKR5), CD (qCD5-1) and HKW (qHKW1-1) were common detected under five different environments and in the combined analysis, with higher contributions and stability, and could be used as stable QTL for further fine mapping and MAS. Moreover, Many QTLs were detected with the umc1703-umc1590, bnlg1325-umc2369 and bnlg420-umc1209, umc1800-umc2304, umc1257-phi031 marker confidence intervals on chromosome 1, 3, 5 and 6, respectively. Partially dominance and additive effect played an important part in the inheritance of yield-related traits.4.Digenic interactions were also detected for yield and the related traits. Twenty pairs of epistasis QTLs were identified in most of the traits except Cod Diameter, all epistasis QTLs have additive×additive, additive×dominance and dditive×dominance effect, the contribution of epistasis varied from 0.04% to 2.41%. Among the Digenic interaction effects, two pairs of interaction for kernel weight and kernel product percent, respectively, showed significant interaction effects with environments, which account for 0.33%-0.91% phenotype variation. Single locus among most of epistatic QTL was not significant, which had little effects on trait variation. It is important to consider different genotypes and the environment in the breeding.5.52 QTLs were detected for 3 flowering related traits under five environments. Contribution of single QTL to phenotypic variation varied from 4.28% to 19.59%, 17 QTLs explained more than 10% of phenotype variation; There major QTLs for TE (qTE5-2), AN (qAN1-2) and SE (qSE3-1) were stable under four different environments and in combined analysis. Moreover, Many pleitropic QTLs were also detected at 1.05-1.07 bin(qTE1-1,qTE1-2,qAN1-2,qAN1-3,qAN1-4,qSE1-2,qSE1-3), 3.05-3.06 bin(qTE3-1,qAN3-1,qSE3-1)and 5.08 bin(qTE5-1,qAN5-6,qSE5-2).6.Digenic interactions were detected for flowering related traits. Totally four pairs of epistasis QTLs were detected for days to tasseling and days to silking, and not detected epistatic QTL for days to anthesis, the type of epistasis QTL included additive×additive, additive×dominance and dominance×dominance effects, the contribution of epistasis varied from 0.02% to 0.13%.