In the global climate change scenario, heatstress together with other abiotic stresses will remain an importantdeterminant of future food security. Wheat (Triticum aestivum L.) is the third most important crop, feeding about one third of the world population. Being a crop of temperate climate, wheat is sensitive to heat stress, particularly at the reproductive phase.

Heat tolerance is a complex trait. In the present study, a combined approach of physiological phenotyping and quantitative genetics was used to dissect the complex nature of heat tolerance into photosynthesis related traits- with a top-to-bottom (forward) approach:

Tier 1: Phenotyping: As a starting point,the quantification of heat tolerance was done by the chlorophyll fluorescence parameter, F_v/F_m, as a measure of maximum quantum efficiency of PSII photochemistry after heat stress treatment (40°C for 72h). This way the naturally existing variation amongst 1274 wheat cultivars was phenotyped repeatedly at increasing severity of heat stress, eventually leading to the selection of 41 cultivars extreme for F_v/F_m.

Tier 2: Validation: Since F_v/F_m is a measured parameter and represents only a single component of PSII functionality, therefore, its physiological relevance in terms of overall plant performance was validated under moderate heat stress (36°C for a week) mimicking natural heat waves. Interestingly, the wheat cultivars previously selected for high F_v/F_m also showed higher net photosynthesis,chlorophyll content, stomatal conductance and transpiration rate, suggesting that the tolerant cultivars had better evaporative cooling and stay green characteristics under heat stress. Further, cultivar Fv/Fm and dry matter content also showed a significant positive correlation.

Tier 3: Linking phenotypic differences to QTLs: Genotyping and linkage analysis of molecular markers was carried out to analyze quantitative trait loci (QTLs) in three bi-parental segregating populations derived from the parents contrasting for F_v/F_m. Three QTLs each explaining about 12-16% of the phenotypic variation were mapped at a resolution of around 20 cM on the hexaploid wheat genome.

Conclusion: With a combined forward approach of physiological phenotyping and genetic analysis it was possible to identify and link small phenotypic differences for a key physiological process in the photosynthesis to QTLs. Future works may reveal how important these identified QTLs are in terms of improving heat tolerance in wheat- in search of genes towards improving photosynthetic efficiency under heat stress.