| Maize is one of the most important food crops in China. It plays a vital role in agricultural economy of China. Maize kernel starch viscosity traits and QTL mapping of those traits are very important in corn genetic improvement. This experiment chose maize inbred lines JB and Y53 to build a F2 population with 240 plants. The correlation among seven RVA viscosity traits was investigated. In order to map QTL that control kernel starch viscosity traits, we measured the RVA viscosity of starch grains per plant and adopted 1121 SSR markers to build a molecular linkage map. The results were showed as follows.(1) Seven starch viscosity characters, except the final viscosity and peak time, were found significant difference between the parents (JB and Y53). Phenotypic correlation analysis was conducted in F2 generation, and significant correlation existed among many traits. The very significant positive correlation was found among peak viscosity, trough viscosity and final viscosity. Pasting temperature and peak time also had highly significant positive correlation. Peak viscosity, trough viscosity and final viscosity were negatively correlated with pasting temperature and peak time. Breakdown and setback were positively correlated with peak viscosity, trough viscosity and final viscosity, but the breakdown was negatively correlated with pasting temperature and peak time at a significant level.(2) Two parent lines and their F1 progeny were used to analyze the polymorphism of 1121 SSR markers, and 184 polymorphism markers were detected, The polymorphism percentage was only 16.4%. The genetic linkage map was constructed by 154 SSR markers, which covered 1734.9cM of maize genome with an average distance of 11.3cM between every two markers.(3)No QTL was detected for peak time. 57 QTLs were detected for the other six maize kernel starch viscosity traits with an average of 9.5 each trait. Peak viscosity, final viscosity, breakdown and setback had the larger number of QTLs. The number was 10, 11, 13 and 12, respectively. Whereas trough viscosity and pasting temperature had a smaller number of QTLs. There were 6 QTLs each explained phenotypic variation more than 20%. They were qPV7-2, qFV7-2, qSB7-1, qSB7-2, qSB8-1 and qSB8-2. qFV7-2 had the largest contibution to phenotypic variation, reaching 31.80%.(4) Integrated the information of all the QTLs of 7 starch viscosity traits, we found seven QTLs hotspot regions, where more than 3 QTLs were involved. They were umc1200-umc1160 in the first chromosome,umc1961-mmc0111 in the second chromosome,umc1489-umc1286 in the third chromosome,bnlg1094-dupssr9 and umc2197 in the seventh chromosome, umc1974-bnlg1834 and umc1005 in the eighth chromosome. The number of QTLs in umc1974-bnlg1834 was 5, and involved all the starch viscosity traits except pasting temperature.(5) In the 57 QTLs related with RVA viscosity traits, 30 showed overdominance. The number of QTLs showed additive, partial dominance and complete dominance were 7, 13 and 7, respectively. There were 6 QTLs related with peak viscosity, 6 QTLs related with final viscosity, 6 QTLs related with breakdown and 9 QTLs related with setback showing overdominance. Therefore, the gene action of these four traits was overdominance. Whereas trough viscosity and pasting temperature mostly showed partial dominance.
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