| Maize is the most important crop of food and fodder, how to increase the output of maize was a major target of corn breeding. In order to achieve the target, breeder take breeding density-tolerance maize varieties as primary breeding direction and emphasize the importance of plant type breeding to improve light energy utilization and coordinate contradiction between group and individual. Therefore, the objective of this study are to mapping and analysis genetic effect for plant architectures and yield components based on a genome-wide simple sequence repeat (SSR) genotyping and on the plant and yield traits at three different environment, using an F2:3 families which constructed deriving from the typical compact plant type inbreed line Yu82 and the typical spreading plant type inbreed line Yu 87-1. Distorted cites main distributed 2, 4, 5, 6, 7, 9 and 10 chromosome. In which, a big distorted regions was detected on the seventh chromosome, it covered bin (7.00-7.03) regions. distorted cites main distributed 2, 4, 5, 6, 7, 9 and 10 chromosome. In which, a big distorted regions was detected on the seventh chromosome, it covered bin (7.00-7.03) regions.The major results are as follows.1. A genetic linkage map containing 191 SSR markers was constructed based on an F2 population with 254 individuals.The map spanned a total of 1827.6 cM with an average interval of 9.52 cM.For the study of 191 markers, there are 170 sites alleles frequency in accordance with the rate of 1: 2: 1 and a total of 21 markers (11.00%) showed a distorted segregation. In which 8 markers (occupy 38.08%) deviation heterozygote, 7 markers (occupy 33.33%) deviation Yu 82 , 6 markers(occupy 33.33%) deviation Yu 87-1 .From the distribution of2. With the composite interval mapping method, 163 QTL were detected for 8 plant architectures and 6 yield related traits based on a field mapping population cinsisting of 254 F2:3 families at three environment. The contribution to phenotypic variation for a single QTL varied from 2.61%-34.21%. In which, QTLs were detected above contribution rate 10% in many circumstance. They included: qLL3a and qLL5 related leaf length were detected which respectively located markers umc1030- umc2127 and umc1679-bnlg1879; qLA1 and qLA3a related leaf angle were detected which respectively located markers umc2383-bnlg1484 and bnlg1297-bnlg1017; qLOV1b and qLOV2a related leaf orientation value were detected which respectively located markers umc2096-umc2217 and bnlg1297-bnlg1017; qPH3a, qPH4 and qPH5b related plant height were detected which respectively located markers umc1030-umc2127, bnlg1126-umc1550 and bnlg1879-bnlg278;qEH1a related ear height was detected which located markers umc2383-bmc2238. in addition, qLW1b and qLW4 related leaf width, qLOV3 related leaf orientation value, qEH3a related ear height were detected in many circumstance whose contribution rate close to 10%.3. Gene actions of QTL were different among the different traits. Additive effects, partial dominance effects, dominance effects and overdominance effects were all detected. Among QTL for the plant architectures, 25.84% of QTL showed the additive gene effects, 54.35% of QTL showed the partial dominance effects, 11.88% of QTL showed overdominance effects. For yield related traits, 27.42% of QTL showed the additive gene effects, 54.84% of QTL showed the partial dominance effects, 8.06% of QTL showed dominance effects and 9.68% of QTL showed overdominance effects. Therefore, the partial dominance and the additive effects were the main genetic basis for the plant architectures and the yield related traits.4. The analysis for the main effect QTL showed: QTL×environment interaction (QEI) were not significant. It implied that the main effect QTL related the plant architectures and yield related traits were less affected by environment. A total of 12 pairs QTL with the significant digenic interaction were detected for plant architectures and yield related traits. All 4 possible digenic interaction types (AA, AD/DA and DD) were observed. All epistasis were found between two loci, which showed non-significant effects and explained few phenotypic variation. It implied that epistasis for the genetic of plant architectures and yield related traits occupy a certain proportion, but play a smaller role.5. The QTL for plant architectures concentrated on some overlap regions of the maize genome. For example, there are two most important genetic regions were simultaneously detected on chromosome 1 flanked with bin 1.02 and 1.03 which include qLA1, qLOV1b and qEH1a. Furthermore, chromosome 3 flanked with bin 3.03 and 3.04 which include qLL3a, qLOV3, qPH3a, qEH3a and qIH3. It indicated that concentrated distribution of QTL is relation to correlation of different traits between phenotype and genetic. These QTLs which controlled the different characters were adjacent to each other, to their advantage can be in favour of multi-effect.
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