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Data from: Genome-wide analysis of allele frequency change in sunflower crop-wild hybrid populations evolving under natural conditions

Cite this dataset

Corbi, Jonathan et al. (2017). Data from: Genome-wide analysis of allele frequency change in sunflower crop-wild hybrid populations evolving under natural conditions [Dataset]. Dryad. https://doi.org/10.5061/dryad.mp32f

Abstract

Crop-wild hybridization occurs in numerous plant species, and could alter the genetic structure and evolutionary dynamics of wild populations. Studying crop-derived alleles in wild populations is also relevant to assessing/mitigating the risks associated with transgene escape. To date, crop-wild hybridization has generally been examined via short-term studies, typically within a single generation, focusing on few traits or genetic markers. Little is known about patterns of selection on crop-derived alleles over multiple generations, particularly at a genome-wide scale. Here, we documented patterns of natural selection in an experimental crop × wild sunflower population that was allowed to evolve under natural conditions for two generations at two locations. Allele frequencies at a genome-wide collection of SNPs were tracked across generations, and a common garden experiment was conducted to compare trait means between generations. These data allowed us to identify instances of selection on crop-derived alleles/traits and, in concert with QTL mapping results, test for congruence between our genotypic and phenotypic results. We found that natural selection overwhelmingly favors wild alleles and phenotypes. However, crop alleles in certain genomic regions can be favored, and these changes often occurred in parallel across locations. We did not, however, consistently observe close agreement between our genotypic and phenotypic results. For example, when a trait evolved towards the wild phenotype, wild QTL alleles associated with that trait did not consistently increase in frequency. We discuss these results in the context of crop allele introgression into wild populations and implications for the management of GM crops.

Usage notes

Funding

National Science Foundation, Award: IOS-1444522