The increasingly available plant genome information reveals evidence that gene copy number expansion and subsequent copy number variation (CNV) lie at the basis of plant adaptation to adverse environmental conditions. Such CNV appears to be highly dynamic, already apparent upon only a few generations of selection. Rapid evolution of plant adaptation traits will be very attractive to apply in plant breeding. In this project, we will investigate the role of CNV in the evolution of plant adaptations to environment and the traces it leaves in plant genomes. To this end we will develop novel, sensitive CNV analysis tools based on next-generation whole genome (re)sequencing (WGS) data from available crop and wild plant diversity panels. The key challenge is to reliably detect CNV on (very) low coverage datasets, to link this CNV to observed phenotypes, and to detect recurrent CNV by integrating measurements across populations. In addition, we will experimentally evolve Arabidopsis thaliana under two severely adverse abiotic conditions (high salt and high Zn exposure) and apply the developed CNV analysis tools on WGS data of evolved lines. Overall, the project will provide detailed information on newly generated (Arabidopsis) as well as standing CNV (diversity panels), which will be used to determine the frequency and distribution of de novo CNVs and the genome sequence requirements for CNV. This will help understand the mechanisms permitting extensive CNV to occur and will allow us to find ways to exploit it for rapid improvement of crop stress tolerance through plant breeding.