Savic Veselinovic, M. | bioRxiv Science

bioRxiv2024

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

Global change is accelerating biological invasions, making it crucial to understand how species adapt in new environments to improve management strategies. Genomic data provide valuable insights into adaptation through Genotype-Environment Association (GEA) studies, which identify genes and biological processes tied to invasion success, and through geometric Genomic Offset (gGO) statistics, which estimate genetic (mal)adaptation to new environments. Here, we investigate genetic adaptation in the invasive pest Drosophila suzukii using novel genomic resources and statistical methods. We use a new chromosome-level genome assembly and data from 37 populations, combining publicly available and newly generated pooled and individual sequencing data, analyzed with an enhanced version of BayPass software, tailored for such hybrid datasets. First, we identify genomic regions showing genetic differentiation between native and invasive populations. Then, using a GEA with 29 environmental covariates, we estimate the gGO between the source environments and the invaded areas, shedding light on the potential adaptive challenges D. suzukii faced during previous invasions. In addition, we estimate gGO for geographical areas not yet invaded to predict future invasion risks, and identify regions from which preadapted populations may originate. Our results reveal numerous genomic regions associated with the invasive status from genome scans. However, when considering broader patterns of adaptation to specific environmental variables through gGO analyses, we find that D. suzukii populations likely faced only limited adaptive challenges across their major invasion range, while certain uninvaded regions still remain at high risk of future invasion. Our study offers significant insights into D. suzukii adaptation and provides a practical population genomics framework to predict biological invasions, applicable to various species.

evolutionary biology↗

bioRxiv2021

Drosophila Evolution over Space and Time (DEST) - A New Population Genomics Resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last 20 years. A major challenge is the integration of these disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution and population structure of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 population samples from over 100 locations in >20 countries on four continents based on a combination of 121 unpublished and 150 previously published genomic datasets. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.

genomics↗