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Footprints of worldwide adaptation in structured populations of D. melanogaster through the expanded DEST 2.0 genomic resource
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All sequences are available on the SRA (https://www.ncbi.nlm.nih.gov/sra) at PRJNA993612. Code is available in GitHub at: https://github.com/DEST-bio/DESTv2_data_paper. All outputs from the DEST 2.0 pipeline can be found at https://dest.bio. Supplementary datasets can be found in Zenodo at https://doi.org/10.5281/zenodo.13731977.. Large scale genomic resources can place genetic variation into an ecologically informed context. To advance our understanding of the population genetics of the fruit fly Drosophila melanogaster , we present an expanded release of the community-generated population genomics resource Drosophila Evolution over Space and Time (DEST 2.0; https://dest.bio/). This release includes 530 high-quality pooled libraries from flies collected across six continents over more than a decade (2009-2021), most at multiple time points per year; 211 of these libraries are sequenced and shared here for the first time. We used this enhanced resource to elucidate several aspects of the species' demographic history and identify novel signs of adaptation across spatial and temporal dimensions. We showed that patterns of secondary contact, originally characterized in North America, are replicated in South America and Australia. We also found that the spatial genetic structure of populations is stable over time, but that drift due to seasonal contractions of population size causes populations to diverge over time. We identified signals of adaptation that vary between continents in genomic regions associated with xenobiotic resistance, consistent with independent adaptation to common pesticides. Moreover, by analyzing samples collected during spring and fall across Europe, we provide new evidence for seasonal adaptation related to loci associated with pathogen response. Furthermore, we have also released an updated version of the DEST genome browser. This is a useful tool for studying spatio-temporal patterns of genetic variation in this classic model system.
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