| Soybean [Glycine max (L.) Merr.] originating in China, is the major crop in the world. Soybean is also a major source of vegetable protein. Moreover, it has an irreplaceable role in ensuring national food security. Analyzing and mapping QTL of plant type traits of soybean have great significance for utilizing MAS breeding to improve yield and efficiency of breeding.In this study,427 lines of a recombinant inbred lines that derived from Kefeng 1×Nannong 1138-2 were used to conduct field experiment, and some soybean’s plant type traits, including plant height, number of main stem nodes, average node length, average length of the top five nodes, leaf width ratio were investigated. After obtaining phenotypic datas, we used the genetic map which has been constructed to map QTL of plant type traits, and 17 QTL were detected. Podding habit was divided by the leaf width ratio. The follows are results:1 Through mapping QTL of plant height, four QTL were detected, which were qPH06-1, qPH10-1, qPHll-1 and qPH12-1 respectively. Additive effects were 0.62,7.10,-6.31 and 3.75 respectively. Genetic contribution explaining phenotypic variance ratio were 8.55%,17.82%,9.13% and 3.34% respectively.In addition, qPH10-1 and qPH12-1 of controlling plant height was detected one pair interactions. Additive interaction effect was-1.64. Genetic contribution explaining phenotypic variance ratio was 0.89%.2 Through mapping QTL of number of main stem nodes and average node length, five QTL associated with number of main stem nodes were detected, which were qNMS06-1, qNMS08-1, qNMS10-1, qNMS11-1 and qNMS12-1 respectively. Additive effects were 0.76,-0.32,1.13,-1.15 and 1.02 respectively. Genetic contribution explaining phenotypic variance ratio were 6.73%,0.43%,17.11%,11.12% and 10.47% respectively. Two QTL associated with average node length were detected, which were qANL10-1 and qANL10-2. Additive effects were 0.15 and 0.09. Genetic contribution explaining phenotypic variance ratio were 5.54% and 1.9%.In addition, qNMS08-1 and qNMS10-1, qNMS10-1 and qNMS12-1, which control number of main stem nodes, were also detected two pairs of interaction effect. Additive interaction effects were 0.19 and-0.30 respectively. Genetic contribution explaining phenotypic variance ratio were 0.38% and 1.05% respectively.3 Through mapping QTL of average length of the top five nodes, three QTL were detected, which were qAFN01-1, qAFN04-1 and qAFN09-1 respectively. Additive effects were 0.55,0.71 and -0.68 respectively. Genetic contribution explaining phenotypic variance ratio were 3.49%,4.02% and 3.28% respectively.In addition, qAFN01-1 and qAFN09-1 of controlling average length of the top five nodes was detected one pair of interaction effect. Additive interaction effect was 0.62. Genetic contribution explaining phenotypic variance ratio was 2.86%.4 DT and SDT were divided by leaf width ratio 0.62, but this result didn’t conform to Liu Shunhu’s. With the chi-square analysis of DT and SDT, the result showed the actual value was not consistent with the theoretical value. And in mapping QTL of leaf width ratio, three QTLs were detected, which does not comply with DT and SDT with a pair of genes controlling.Therefore the results of this trial needs further research.5 In mapping QTL of plant height and number of main stem nodes,4 and 5 QTL were detected respectively. They were located at the same site of 6,10,11 and 12 chromosome, suggesting that there were some pleiotropic effects.Plant height, number of main stem nodes, average node length, average length of the top five nodes and leaf width ratio have an important influence on the formation of soybean production, so we can use the genes that were mapped to shape ideal plant traits to improve soybean production by MAS breeding. |
PDF Full Text Request