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eQTL mapping of candidate genes for flower colour as a model for genetical genomics in azalea
Book Contribution - Chapter
Flower colour in azalea is inherited as a semi-qualitative trait and is mainly determined by differences in anthocyanins and flavonols. A two-gene model is used to explain the phenotypic variation between white, brick red and carmine red colour: W in case the flower petals contain anthocyanins and Q if flavonols are present as co-pigments. However, the regulatory network behind this pathway is still unclear. To identify key driver genes of the molecular pathway involved, a genetical genomics approach was followed. Genetics was combined with gene expression profiling, resulting in eQTL mapping. So far, mainly micro-array data have been used for this, limiting the technique to large scale projects. Nevertheless, qPCR can be a good and cost–efficient alternative, as we will demonstrate for flower colour in azalea. A genetic map of 13 linkage groups was constructed using a crossing population segregating for flower colour (250 plants). Besides anonymous AFLP and SSR markers also a set of functional markers were used. EST-markers were developed for genes coding for key-enzymes in the flavonoid biosynthesis pathway. Myb-profiling (related to NBS-profiling), generated 15 dominant markers related to the Myb gene family. Regulatory genes of the flavonoid biosynthesis pathway were in such way available on the map. Flower colour was determined on the population using image analysis and QTL mapping of these data (derived RGB parameters and results of discriminant analysis) integrated the phenotype with the genetic data. Gene expression profiles of five genes coding for key enzymes of the flavonoid biosynthesis pathway were generated in the petals of a subset of the crossing population. Normalized relative quantities were subjected to Box-Cox transformation in order to get a Gaussian distribution prior to eQTL mapping. Gene expression data were combined in discriminant functions for the allelic status of locus W and Q; these were used for eQTL mapping as well (Kruskal-Wallis rank sum tests and Interval Mapping; MapQTL5). The statistical power to detect eQTLs depends largely on the population size; because of financial constraints a small critical population size is favored. A total of 70 plants was needed to assure sufficient power. Three genes of which the expression profile was measured could also be mapped as EST markers. No cis-acting eQTLs could be assigned to one of them, but dfr appears to be local-trans regulated. eQTLs for multiple genes are co-located with myb-markers, suggesting a combinatorial transcriptionally regulation of these genes. Interestingly, the discriminant function for the Q locus mapped at both the fls locus and at the Q-locus (responsible for carmine red colour). Indeed, fls leads to the production of co-pigments (flavonols), that are only visible in the presence of anthocyanins and differentiate between carmine red and red flowers. This clear correlation can be seen as a proof of concept and validates the precision of our qPCR results and their potential for eQTL mapping.
Book: Proceedings of the 19th EUCARPIA General Congress: Plant Breeding for Future Generations
Number of pages: 4