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Challenges of using qPCR for eQTL mapping

Book Contribution - Chapter

Flower colour is inherited as a semi-qualitative trait in azalea 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 molecular pathways involved in complex phenotypes, a genetical genomics approach can be followed. Genetics is combined with gene expression profiling, resulting in eQTL mapping. So far, only micro-array data have been used for this expression profiling, limiting the technique to large scale projects. Nevertheless, qPCR can be a good and cost –efficient alternative, as we demonstrated 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 four genes coding for key-enzymes in the flavonoid biosynthesis pathway. Myb-profiling, a sequence directed technique similar to NBS-profiling, generated in this crossing population fifteen dominant markers functionally related to the Myb gene family. Regulatory genes of the flavonoid biosynthesis pathway were as such available on the map. Flower colour was determined on the population using image analysis and QTL mapping of these data 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 20 flowers of the crossing population. Normalized data were subjected to Box-Cox transformation in order to get a Gaussian distribution prior to QTL mapping. Both Kruskal-Wallis rank sum tests and Interval Mapping were used (MapQTL5). The statistical power to detect eQTLs depends largely on the population size. Because of financial constraints a small critical population size is favored. However, when using only 20 plants, no eQTLs were above the detection limit; with 50 plants results were acceptable for the Kruskal-Wallis analysis, but this was not sufficient for Interval Mapping. Hence, we were obliged to analyze a total of 70 plants to get good results. Analysis were spread over different runs and the limited availability of RNA from petals prevented a standard inter-run calibration. Therefore, the average expression of each gene in every run was chosen as a good alternative for this purpose.

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. Interesting to see is that the expression of fls is mapped at the Q-locus (responsible for carmine 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 proves the precision of our qPCR results and their potential for eQTL mapping.
Book: Advances in Genomics symposium 2010
Pages: 22
Number of pages: 1
Publication year:2010