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.
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