Towards improved crop photosynthesis efficiency

Projecttitel: Towards improved crop photosynthesis efficiency: elucidation and validation of genes underlying Arabidopsis photosynthesis QTLs
Projectnummer: BBE-1701
Looptijd: 2017 – 2018
Budget publiek: € 289.000
Budget privaat: € 28.000
Projectleider: Mark Aarts
Betrokken partijen: HZPC, Meyer Potato, SES Van der Have, Wageningen University & Research

Photosynthesis is the foundation of plant productivity. More photosynthesis results in more growth and reproduction. Breeding for improved photosynthesis is notoriously difficult, mainly due to the dynamic character of the trait and the physiological and genetic complexity of the process. Recent developments in plant phenotyping have enabled accurate measurements of parameters based on chiorophyli fluorescence that serve as reliable measures of leaf photosynthetic properties. The operating quantum yield of photosystem II (PSII) is a particularly useful parameter that measures light-use efficiency of the photosynthetic apparatus. It is strongly correlated with the electron transport rate and thus a proxy for CO2 fixation. Improving PSII efficiency will be a crucial step in improving CO2 fixation and subsequently contribute to improved plant production. Especially for root, tuber or fruit crops, the Increased CO2 fixatlon, leading to increases sugar production, is an attractive trait to provide an increased potential for a higher harvest index. Since 2010, several quantltative genetic studies have been performed in the Laboratories of Genetics and Horticulture and Product Physiology of Wageningen University. These were mostly performed using the same set of 352 Arabidopsis thaliana natural accessions. With this defined set of genotypes, genome wide association studies (GWAS) were done and multiple quantitative trait loci (QTL) were identified. Different growth conditions were used, lncluding varlous stresses, such as low phosphate nutrition, low nitrate nutrition, tow temperatures, and high-lrradiance. This has resulted in a unique dataset of Arabidopsis photosynthetic responses and growth data and associated QTL. These QTLs have been identified during later phases of PhD research projects and owing to time limitations they have remained largely unexplored. Only a handful of QTLs have been followed up to the point where the causal genes and the effect of their natural altelic variance was understood. Obvious questions arise, such as the existence of common QTLs in all conditlons as well as for tolerance to different stresses classes. All datasets combined will provide a good basis to further understand the natural variation and genetic networks underlying photosynthetic traits and for future applicatlons of this knowledge for targeted breeding for improved photosynthesis efficiency in crops contributing to the bio based economy.