| Yield is the most important trait in maize. High yield is the constant theme for maize research. Becides, selection from other agronomic traits is a same important way beyond the yield traits because agronomic traits have significant impacts on yield stability and adaptability. Since yield traits and the related agronomic traits are kinds of quantitative traits, research using conventional genetic methods is more difficult, which greatly limited the maize high yield breeding process. With the development of molecular biology, QTL mapping technique offers greatly tools for heredity relation research of complex quantitative traits in maize. In this study,270Fg families recombinant inbred lines derived from the cross178×9782as the mapping population were constructed, and the phenotypes of agronomic traits of families were identified in the year2011. At the same time, linkage map which consist of150SSR makers was constructed in the reseach and then QTLs of important agronomic traits were identified primarily by composite interval mapping (CIM) method. The main results are as follows:1. Florescence, plant morphological and yield correlated traits of RIL families were identified in the year2011in Wenjiang, and all17traits were analysed by statistic strategies. The results were as follows:The range of traits variation showed a significant transgressive segregation phenomenon and the coefficient of variation ranged between2.95%-49.63%. Yield traits showed significant correlation among yield traits, florescence and plant morphological traits, and to this RIL population, yield traits showed significant negative correlation with florescence, yield traits showed positive correlation with each other. The main yield traits such as kernel weight showed the most significant correlation with ear weight, kernel weight per row and row number per ear, the correlation coefficient were:0.954、0.841、0.639; The correlation coefficients of kernel weight with plant height, leaf number, ear height and total tassel branch number were:0.204,0.198,0.191and0.175. Kernel weight showed significant negative correlation with days to tasseling, days to silking and days to anthesis, the correlation coefficients were:-0.319,-0.374and-0.288.2. The linkage map containing150SSR makers was constructed in the research. In this map, the total distance was1440cM, and the average interval length was9.6cM between makers with biggest interval31.88cM. The number of makers on each chromosome was24,21,9,17,19,13,12,13,8,14with average interval length between markers on each chromosome10.44cM,9.09cM,7.03cM,9.42cM,8.66cM,10.19cM,10.98cM,10.76cM and9.6cM, respectively.3. A total of51QTLs associated with17agronomic traits were identified primarily. The detailed QTL information according to traits is listed as follows:(1) In the aspect of yield associate traits, the number of QTLs associated with100-kernel weight was2all on chromosome1. These QTLs accounted for5.54～7.91%of the phenotype variations. The number of QTLs associated with ear diameter was1on chromosome2, the QTL accounted for4.92%of the phenotype variations. The number of QTLs associated with kernel number per row was3on chromosome2,3,6, these QTLs accounted for4.13-8.03%of the phenotype variations. The number of QTLs associated with row number per ear was4on chromosome2,3,4,5. These QTLs accounted for6.14～7.63%of the phenotype variations. The number of QTLs associated with kernel weight was3on chromosome2,3,6. These QTLs accounted for4.62～15.57%of the phenotype variations. The number of QTLs associated with ear length was2on chromosome3,4. These QTLs accounted for4.30～5.95%of the phenotype variations. The number of QTLs associated with ear weight was3on chromosome2,3,6. These QTLs accounted for4.75～13.50%of the phenotype variations.(2) In the aspect of plant morphological traits, the number of QTLs associated with plant height was4on chromosome2,3,5,8. These QTLs accounted for11.19～15.21%of phenotype variations. The number of QTLs associated with ear height was6on chromosome2,3,5,6,8. These QTLs accounted for4.19～17.31%of the phenotype variations. The number of QTLs associated with total tassel length was3on chromosome3,5,10. These QTLs accounted for4.91～6.06%of the phenotype variations. The number of QTLs associated with tassel branch number was5on chromosome1,2,4,5,10. These QTLs accounted for4.26～19.30%of the phenotype variations. The number of QTLs associated with leaf number was4on chromosome3,4,7. These QTLs accounted for4.84～14.82%of the phenotype variations. The number of QTLs associated with ear leaf length was3on chromosome1,5,8. These QTLs accounted for4.12～22.47%of phenotype variations. The number of QTLs associated with ear leaf width was4on chromosome1,2,4,10. These QTLs accounted for4.36-9.70%of the phenotype variations.(3) In the aspect of florescence, the number of QTLs associated with days to teaseling was3on chromosome2,3,10. These QTLs together accounted for18.36%of the total phenotype variations. The number of QTL associated with day to silking was1on chromosome2. These QTLs accounted for10.09%of the phenotype variations. Chromosome1,2,3,5were the intensive QTL region in this study.4.15QTLs which accounted for high percentage of phenotype variations were detected in this research which were listed as follows:qKW3-1(Bin3.05, LOD=9.76, accounted for15.57%of the phenotype variations), qEW3-1(Bin3.05, LOD=8.35, accounted for13.50%of the phenotype variations), qPH2-1(Bin2.06-2.08, LOD=5.68, accounted for11.19%of the phenotype variations), qPH3-1(Bin3.03-3.04, LOD=8.53, accounted for15.21%of the phenotype variations), qPH5-1(Bin5.01-5.02,LOD=4.93, accounted for12.40%of the phenotype variations), qPH8-1(Bin8.06-8.08,LOD=4.26, accounted for13.92%of the phenotype variations), qEH2-1(Bin2.06-2.08, LOD=6.12, accounted for12.99%of the phenotype variations), qEH8-1(Bin8.06-8.08, LOD=5.49, accounted for17.31%of the phenotype variations), qTBNl-1(Binl.02-1.03, LOD=11.63, accounted for18.13%of the phenotype variations), qTBN2-1(Bin2.01-2.02, LOD=5.17, accounted for15.33%of the phenotype variations), qTBN5-1(Bin5.05-5.06, LOD=6.56, accounted for19.30%of the phenotype variations), qLN3-1(Bin3.05-3.06,LOD=4.51, accounted for14.82%of the phenotype variations), qELLl-1(Binl.03, LOD=10.81, accounted for22.47%of the phenotype variations), qELL5-1(Bin5.00-5.01, LOD=4.91, accounted for10.02%of the phenotype variations), qDS2-1(Bin2.02-2.03, LOD=5.17, accounted for10.09%of the phenotype variations). These QTLs may be main-effect QTLs which accounted for high percentage of phenotype variations, and could be studied further. |
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