Genetic Dissection For Kernel Row Number And Other Key Agronomic Traits In The Specific Maize Germplasm Four-rowed Waxy Corn

Kernel row number and other Key agronomic traits are closely related to maize yield, thus thedissection of the genetic basis of these traits is of great importance to improve the maize yieldperformance. In this study, segregation populations were developed by reciprocally crossing the inbredline derived from “Four-rowed Waxy Corn” with Nong531to identify QTL for KRN and other keyagronomic traits. The reciprocally crossed F2:3populations were phenotyped in Beijing (BJ) and Henan(HN). Totally173polymorphic SSR primer pairs obtained from the maize genome database(http://www.maizegdb.org/) were used to genotype the lines and to construct linkage maps. QTL forKRN and other agronomic traits were detected with both ICIM (QTL IciMapping Version3.2Software)and CIM (QTL Network2.0Software).1. The KRN of Four-rowed Waxy Corn and Nong531were4.0and19.2, respectively, and the KRNof the reciprocally crossed F2:3families ranged from4.0to17.4. A total of twelve QTL for KRNphenotyped in the two environments were detected with ICIM, which were located on eightchromosomes except Chr.1and Chr.7. All alleles having negative effect on KRN were from Four-rowedWaxy Corn. A total of five major QTL were detected in both environments. qKRN2-1which was themost important QTL, explained18.48%of the phenotypic variance. The other four QTL, i.e. qKRN4-2,qKRN5-1, qKRN8-2and qKRN9-1, explained11.58%,13.55%,16.91%and9.66%of the phenotypicvariance, respectively. Meanwhile five QTL were detected with CIM, four of which were in accordancewith the major QTL detected with ICIM, i.e. qKRN2-1, qKRN4-2, qKRN8-2and qKRN9-1.Cumulatively, the five major QTL explained51.5%(BJ) and54.0%(HN) of the phenotypic variance inthe two environments with the GLM model, respectively. Correlation analysis showed that, in the twoenvironments, correlations between the estimated values of phenotypic variance and observed values inthe F2:3families were highly significant. In addition, two pairs of QTL located on three chromosomes(Chr.2, Chr.4and Chr.9) represented epistasis, explaining only a small part of the phenotypic variance(2.90%and1.80%, respectively).2. Days to tasseling, days to anthesis, days to silking, plant height, ear height and brace root tiernumber were significantly related to each other. Totally78QTL were detected for these traits via ICIMmethod, of which14、12、13、16、13、10were for the six agronomic traits respectively. Several majorQTL were related to multi-traits, which were distributed on bin1.11, bin3.04, bin4.03—4.05, bin4.07—4.09, bin6.01—6.02, bin9.02—9.03, bin10.03—10.04, explaining11%—32%of the phenotypicvariation, respectively. The two QTL located on bin9.02—9.03and bin10.03—10.04associated withall the six agronomic traits, explaining15%—22%and13—32%of the phenotypic variation,respectively. QTL could explain more phenotypic variation than epistasis and QE interaction, whilethere were epistasis and QE interaction.