Leveraging the genome sequences of two Arabidopsis relatives for evolutionary and ecological genomics

Lead Research Organisation: John Innes Centre
Department Name: Contracts Office

Abstract

The impending completion of the genome sequences from Arabidopsis lyrata and Capsella rubella, both of which are closely related to the well-studied model Arabidopsis thaliana opens up unique opportunitites for ecological and evolutionary genomics. One strategically relevant question is for example what distinguishes species with a limited geographical distribution from highly invasive ones. The genus Capsella provides a model for addressing this issue, as it contains the obligate outbreeder C. grandiflora, which is only found in Greece, the Balkans and Northern Italy, and the selfer C. rubella with an essentially global distribution. In addition, individuals of the two species also differ in other ecologically important characters, such as flowering time or flower morphology. As it is still possible to obtain fertile hybrids between the two species, the genetic basis of these differences can be analyzed by quantitative genetic studies, and cloning of the causal genes underlying quantitative trait loci (QTL) will be greatly facilitated by the C. rubella genome sequence. The aim of this project is therefore to establish and genotype populations of recombinant inbred lines (RILs) and near isogenic lines (NILs) between C. grandiflora and C. rubella as a resource for evolutionary genetics. For the RILs, F2 individuals from an interspecific cross will be propagated through six additional generations by single seed descent. The resulting inbred lines will be genotyped using PCR-based polymorphic markers, which will be established in parallel to the propagation of the lines. These markers will also be used for marker-assisted introgression of individual C. grandiflora genome segments into a C. rubella background through repeated backcrossing, in order to generate a set of NILs. Both of these populations will form the basis for future QTL mapping and cloning projects to identify the genetic basis for quantitative variation in ecologically relevant traits.

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