New insights into past and future invasion of Drosophila suzukii using novel genomic resources and statistical methods to combine individual and pool sequencing data

Climate change and globalization are accelerating biological invasions, highlighting the urgent need to understand adaptation mechanisms in invaded environments to improve management strategies. Genomic data can provide insights into the adaptation of invasive species through Genotype-Environment Association (GEA) studies, identifying genes and biological processes associated with invasion success, and more globally to estimate genetic (mal)adaptation to new environments by calculating Genomic Offset (GO) statistics. In this study, we investigate genetic adaptation in the invasive crop pest Drosophila suzukii using novel genomic resources and statistical methods. We rely on a new chromosome-level genome assembly and a dataset representing 36 populations, combining both publicly available and newly generated pooled and individual sequencing data, which are analyzed using an enhanced version of the B ay P ass software, tailored for such hybrid datasets. We identify a limited number of genomic regions associated with invasion success, supporting the hypothesis of a polygenic architecture of the underlying adaptive traits. Using a GEA incorporating 28 environmental covariates, we further estimate GO between source environments and invaded areas to gain insight into the adaptive challenges faced by D. suzukii during past invasions. Reciprocally, we estimate GO between putative source environments and geographic areas that have not yet been invaded to predict regions at risk for potential future invasions. Finally, we used GO calculation to identify high risk regions from which pre-adapted populations could likely originate. Our results suggest that the adaptive challenge for D. suzukii populations to invade their current major invasion range was limited. We also identified uninvaded regions (in Africa, South America, and Australia) as being at high risk of future invasion. While further sampling and more extensive individual sequencing could refine these conclusions, our study provides important insights into D. suzukii adaptation and offers a generic and operational population genomics framework for studying and predicting biological invasions that can be applied to diverse species.