The use of natural variation in Arabidopsis thaliana has led to the genetic analysis of a manifold of quantitative traits in the past two decades. Only recently, technological advancements enabled us to profoundly investigate the molecular circuitry underlying these traits. Using the progress made in transcriptomics, proteomics and metabolomics in combination with genetic analyses I have shown the extensive genetic control of natural variation in these entities. The variation observed in the molecular pathway from genotype to phenotype undoubtedly underpins much of the variation manifested in plant performance. However, many of the analyses described thus far were limited by the number of genotypes analysed and often included only extreme phenotypes.
To analyse a much larger part of the natural variation present within Arabidopsis a core set of 384 genotypically distinct accessions was selected recently. Single Feature Polymorphism (SFP) resequencing has been used to develop a complete high density haplotype map that will be the basis for genome wide association analysis of quantitative variation. Elaborating on my earlier work, I propose to use this set for a much more comprehensive genetic analysis of metabolic variation in Arabidopsis. Moreover, to gain insight in the molecular circuitry from gene to phenotype, this set will be profiled for variation in gene expression and CG methylation. For this, a long-term stay in the Borevitz lab is envisaged to collaborate with the world?s leading research groups in Arabidopsis association mapping. Collected data will be used to develop and test methods for fine scale quantitative trait locus (QTL) association scanning capitalizing on the high density haplotype map. QTLs identified will be analysed further to reveal the molecular genetic basis relying on the extensive functional genomic resources available in Arabidopsis. Follow-up experimentation will include analyses of spatial and temporal differences in genetic control and genotype x environment interactions. |
