QTL Mapping For Heat Tolerance Traits In Winter Wheat

With the global climate warming, heat stress has become one of the main threats during the grouting period, resulting in decreased grain yield and quality in wheat. Here, the RIL population derived from two varieties, Lumai 21 and Shannong 0431, that differ significantly of the agronomic traits was used to construct the genetic linkage map via both STS and SSR markers. The phenotypic data were obtained from two years of the artificial high temperature stress. The filling stage of chlorophyll content(SPAD value), normalized difference vegetation index(NDVI), canopy temperature(CT) and the thermal index of yield related characters were investigated for QTL mapping. The main results of this study are as follows.(1)For SPAD value, five QTLs were stably detected on Chromosome 2B, Chromosome 4A and Chromosome 4B, which can explain 53.8% of the total phenotypic variation. The QTL QChl.sdau-2B located on Chromosome 2B could be the major QTL, which can explain 21.0% of the phenotypic variation. The additive effect of this locus was 3.4, and the additive effect came from the male parent Lumai 21. The QTLs QChl.sdau-4A.1 and QChl.sdau-4A.2 located on Chromosome 4A could explain 8.0% and 7.1% of the phenotypic variation, respectively. The additive effects came from the female parent Shannong 0431. Another two QTLs QChl.sdau-4B.1 and QChl.sdau-4B.2 were detected on Chromosome 4B, and they could also explain 8.0% and 7.1% of the phenotypic variation, respectively. The additive effects came from the male parent Lumai 21.(2)For NDVI, two QTLs were stably identified. They were located on Chromosome 4B and Chromosome 7A, respectively, and they can explain 17.0% of the total phenotypic variation. QNDVI.sdau-4B could explain 9.2% of the phenotypic variation, and the additive effect came from Lumai 21. QNDVI.sdau-7A could explain 7.8% of the phenotypic variation, and the additive effect came from Lumai 21 as well.(3)Only one stable QTL was detected for CT, which was located on Chromosome 4A. This QTL could explain 8.3% of the phenotypic variation, and its additive effect was 6.4 derived from Lumai 21.(4)Five QTLs were identified for the thermal stable index of shoot dry weight, which were located on Chromosome 2D, Chromosome 3B and Chromosome 6B. These QTLs could explain 47.1% of the total phenotypic variation. One QTL, named as QBio.sdau-2D, which was located on Chromosome 2D, could explain 10.4% of the phenotypic variation. The additive effect of QBio.sdau-2D was derived from Shannong 0431. Three QTLs, QBio.sdau-3B.1, QBio.sdau-3B.2 and QBio.sdau-3B.3, were identified on Chromosome 3B. They could account for 9.9%, 9.9% and 10.2% of the phenotypic variation, respectively, and all of them came from Shannong 0431. And another QTL QQBio.sdau-6B which could explain 8.8% of the phenotypic variation, was located on Chromosome 6B. The additive effect came from Lumai 21.(5)For the thermal stable index of thousand grain weight, two QTLs were detected. They were both located on Chromosome 3A, which could explain 20.5% of the total phenotypic variation. QTGW.sdau-3A.1 and QTGW.sdau-3A.2 came from Lumai 21, and they can explain 12.7% and 7.8% of the phenotypic variation, respectively.(6)Two QTLs which were located on Chromosome 2D were detected for the thermal stable index of yield. They could account for 20.7% of the phenotypic variation. The two QTLs, QYld.sdau-2D.1 and QYld.sdau-2D.2, were both came from Lumai 21, and could explain 10.9% and 9.8% of the phenotypic variation, respectively.In summary, we detected 17 QTLs accounted for heat stress resistance in winter wheat. Among them, five, two, one, five, two, and two QTLs were identified for SPAD, NDVI, CT, shoot dry weight, thousand grain weight, and yield, respectively. These QTLs were located on Chromosome 2B, Chromosome 2D, Chromosome 3A, Chromosome 3B, Chromosome 4A, Chromosome 4B, Chromosome 6B and Chromosome 7A.