The Major Quality Traits Analysis And QTL Detection Of Hexaploid Wheat In Southwest China

As one of the most important grain crop, common wheat (Triticum aestivum L.) is the main food of35%of population of the world. People pay more attention to the quality of wheat foods as living standards have improved. So, improvement of wheat’s nutritional quality becomes an important objective in wheat molecular breeding programs. Through the methods of molecular quantitative genetics, we can enhance the power of molecular marker-assisted breeding and the progress of wheat quality improvement. In this research, major quality traits analysis and QTL detection are firstly carried out on the RIL R97×R146; then the protein content in kernel and leaves, Glutamine synthetase activity in leaves of RIL R131×R142are analysed by conditioned QTL mapping methods. The main results are as follows.(1) Because of great genetic variation of wheat populations and diversity of genetic linkage map, it is difficult to draw lessons from the multiple QTL analyzing results. In the research, we have constructed a high-density consensus map with two high density genetic map, which have Chinese cultivated wheat genetic background, and a consensus map data. It contains617SSR markers (Xwmc, Xgwm and Xbarc) and covers1881.1cM. The high-density consensus map will be a new tool for multiple QTL results analysis and moleculer marker-assisted breeding.(2) The detection of dough rheology characteristics is laborious, time-consuming and need much flours. Our research shows that gluten index is significantly positively correlated with dough rheology characteristics (Farinogram Quality Number, dough development and stabilization time) and the correlation coefficients is0.201(P<0.05), 0.678(P<0.01)and0.48(P<0.01), respectively. So gluten index can be a rapid determination method for dough rheology characteristics detection in the early generation materials selection of wheat quality breeding.(3) It has been reported that high quality wheat is divided into quality type and quantity type. In the research, we find that quality traits (gluten index, Farinogram Quality Number) are significantly or high significantly negatively correlated with quantity traits (gluten content, protein content). It means that high quality wheat tends to have low gluten and protein content. Apparently, wheat quality and associated quantity traits are always in a dynamic state of equilibrium.(4) Protein content is an important qulity trait in wheat breeding. We have detected one major QTL (Q.GPC-6B) for protein content in RIL R97XR146. Q.GPC-6B is linked to marker Xwmc419-6B, which can steadily express in multi-environment. Others researches also detect QTLs for protein content in the similar genetic locus. So, there may be one QTL/genes cluster for protein content in the genetic locus which links to xwmc419-6B on chromosome6B.(5) Pentosans are important albeit quantitatively minor constituents of wheat grain. They are significant anti-nutrient factor and have important impact on end-use quality of cereal grain. In this study, we believe that water-soluble pentosan is the major component in pentosans which associate with amyloplast membranes. The association of water-soluble pentosan with amyloplast membranes could modulate the adhesion of starch-protein matrix and therefore has an impact on grain hard index.(6) In the grain hard index (HI) analysis, we find that distribution of the RIL population is bimodal. Using our classification criterion, we classify58RIL lines as high HI and43RIL lines as low HI. The results indicate that there is a single Mendalian genetic factor in this population for grain hard index as the segregation pattern for HI is1:1(χ2=1.66). At the same time, we also find a major QTL Q.HI.scau-7D (LOD>10、R2>32%). This QTL may be the Mendalian genetic factor in this population.(7) Because of temporal spatial expression of QTL, dynamic QTL analysis can accurately detect the QTL in the different development periods of wheat. So, the protein content of kernel and leaves, the Glutamine synthetase activity of leaves are firstly analysed and detected by conditioned QTL mapping method. We have detected four QTL with higher percentage of phenotypic variation. They are Q.GPC-1B.1(LOD=5.2, R2=16.6%), Q.LPC-2B.1(LOD=4.3, R2=28.2), Q.LPC-1B.2(LOD=8.1, R2=32.2%) and Q.GS-1B.1(LOD=3.8, R2=29.4%). We also detecte two QTL (Q.GPC-1B.3and Q.LPC-1B.3) for protein content of kernel and leaves between Xwmc419x and Xwmc44at T6(4.30|4.25).