QTL Analysis Of Quality And Yield Related Traits In Soybean

Soybean is rich in protein and fat. For breeders, the main objective is to improve yield and quality of soybean. The objective of this study was to identify QTLs governing soybean quality and yield related traits. Two recombinant inbred lines (RILs) were mapped by SSR markers, One is 137RIL, developed from a cross of JiDou 12×JiHuang13. The other is 138RIL, developed from a cross of JiDou 12×Ji nf58. Twelve Traits were researched in this study, including Plant height, First pod height, Protein content, Oil content, Branches, Nod number, Effective pod, Sterile pod, Seed weight per plant, Seed number per plant. The results are as follows:1. Genetic map constructingIn 137RIL, 150 Polymorphic SSR markers were identified from a total of 457 SSR markers. And 73 SSR markers were mapped. The resulting genetic linkage map covered 849.9cM, including 20 linkage groups. In 138RIL, a total of 457 SSR markers were screened and 120 polymorphic SSR markers were identified. 77 SSR were used to construct map, as a result, 53 SSR markers were mapped in the RIL138, forming 16 linkage groups, covering 514.7cM of the soybean genome.2. QTL mappingA total of thirty-nine QTLs for 12 traits of the two populations were identified in two years and three places, the phenotypic variance they can explained ranging from 6%~37%. Sixteen QTLs could be detected in different environments.Among them, The Plant Height QTL located in 117.77—121.27cM of C2 LG and The Oil QTL located in satt229—satt373 of L LG are same as previous reports.Eighteen QTLs were identified in 137RIL. Among them, five QTLs could be identified in different environments. The QTL associated with Plant height, which was identified in different environments, accounted for 12%~17% of the phenotypic variance. The First pod height QTL detected in different environments can explain 9%~12% of the phenotypic variance. The QTL for Seed weight per plant which was identified in different environments can explain 7%~10% of the phenotypic variance.The Oil QTL detected in different environments can explain 8~11% of the phenotypic variance.Twenty-one QTLs were detected in the RIL138. Eleven QTLs for Plant height, Branch, First pod height, Oil content, Nod number, Effective pod, Seed weight per plant could be detected in different environments. The phenotypic variance them explained raning from 7%~27%.In two RILs, QTLs of three traits detected is in nearly locies of the same likage group(<10cM),The phenotypic variance them explained raning from 7%~20%.