Inheritance, Stability Analysis and QTL Mapping of Yield Related Traits in Soybean
|School||Chinese Academy of Agricultural Sciences|
|Course||Crop Genetics and Breeding|
|Keywords||Soybean genetic linkage map QTL mapping yield related traits Shukla’s stability variance|
High-yield and steady-yield is always the main goal of soybean breeding, but yield traits are genetic complex quantitative traits which are vulnerable to the environmental impact, phenotypic selection efficiency is not high enough to limit the yield traits’genetic improvement. With the development of molecular marker technology, it is possible to improve soybean yield traits at molecular level, but the precondition is to discover the quantitative trait loci （QTL） closely related to the yield traits.Presently, the researches on mapping QTLs associated with soybean yield related traits tend to conduct multi-environment field trials, while studies on stability of yield related traits stay at the traditional quantitative genetic analysis level. Therefore, it is necessary to conduct researches on stability of yield related traits and their quantitative characters. In this study, a recombinant inbred lines （RIL） population derived from the Zhongdou 29 and Zhongdou 32 cross was used, and new developed inheritance models and molecular marker technology were used to study the above aspects. The main results were as follows:A mixed major gene plus polygene inheritance model was used to perform the genetic analysis of twelve yield related traits in the RIL population under four environments. The joint segregation analysis results showed that: For number of nodes on main stem（NM） and number of long-branch per plant（NLB）, the best fitting genetic models were polygene model; For number of short-branch per plant（NSB）, the best fitting model was two or three major genes plus ploygenes model; For plant height（PH）, number of one-seed pods（OP）, number of three-seed pods（TP）, number of four-seed pods（FP）, number of pods（NP）, number of seeds per plant（NS）, number of seeds per pod（NSP）, all of the best fitting models were two major genes plus polygenes; For number of double-seed pods（DP）, the best fitting model was three major genes plus polygenes. At the same time, the 1st order parameters and the 2nd order parameters of the genetic models for the yield related traits were estimated, the results showed that PH, NM, NLB and NSB were mainly controlled by polygenes, while OP, DP, TP, FP, NP, NS and NSP were mainly controlled by major genes.Based on the RIL population consisting of 255 lines, a genetic linkage map of soybean genome was constructed, which consisted of 27 linkage groups with 131 simple sequence repeat （SSR） markers, 96 amplified fragment length polymorphism （AFLP） markers, 14 sequence-related amplified polymorphism （SRAP） markers and 2 classical markers. The map covered 1310.88 cM and the average distance between markers was 5.77 cM. Twenty-six linkage groups （LG） of the map fit the“Consensus Linkage Map”well both in the order of arrangement and the distances of the SSR markers. A total of 154 QTLs for 16 yield related traits under 6 different environments were identified by using the composite interval mapping （CIM） method. One QTL, qPH-15-1, mapped in the interval of EA2MC8-2～Satt554 on LG F, together with five QTL, qDP-19-1, qTP-19-1, qFP-19-1, qNSP-19-1 and qSW-19-1, mapped in the interval of LS～Sat268 on LG I, were detected in at least five environments and explained most of the variation. Compared to the results in inheritance analysis, it was found that QTL analysis always detected more major genes than those of model analysis.Shukla’s stability variance of the RIL population and the parents under six different environments were estimated for the stability of soybean yield traits. Using CIM method, nineteen QTLs associated with stability of yield related traits were detected and located on seven linkage groups. Among which, two QTLs related to PH stability were located on LG F and LG G; two QTLs associated with NLB stability were mapped in different marker intervals on LG N; three QTLs contributed to NB stability were identified on LGG and LG O; five QTLs related to TP stability were located on LG C2, LG I and LG G; two QTLs associated to FP stability were mapped on LG F and LG I; one QTL contributed to NP stability was identified on LG G; four QTLs related to weight of 100-seeds（SW） stability were located on LG E, LG I and LG O. The marker interval LS～Sat268 on LG I clustered three QTLs associated with TP, FP, SW stability and three major QTLs related to TP, FP, SW, the possible reason might be that the major effect QTLs for TP, FP and SW played important roles in the stability of yield related traits.In this study, the construction of soybean molecular linkage map established the foundation for the follow-up QTL mapping of the relevant traits, the primary QTL mapping of yield related traits provided basis for the further fine mapping of major QTLs and molecular marker-assisted breeding of the related traits. At the same time, mapping of QTLs associated with the stability of soybean yield related traits provided a new approach and methodology for soybean steady-yielding breeding. The genetic information about soybean yield related traits would provide important theoretical guide the high-yield and steady-yield soybean breeding.