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Human activities are accelerating rates of biological invasions and climate-driven range expansions globally, yet we understand little of how genomic processes facilitate the invasion process. Although most of the literature has focused on underlying phenotypic correlates of invasiveness, advances in genomic technologies are showing a strong link between genomic variation and invasion success. Here, we consider the ability of genomic tools and technologies to (i) inform mechanistic understanding of biological invasions and (ii) solve real-world issues in predicting and managing biological invasions. For both, we examine the current state of the field and discuss how genomics can be leveraged in the future. In addition, we make recommendations pertinent to broader research issues, such as data sovereignty, metadata standards, collaboration, and science communication best practices that will require concerted efforts from the global invasion genomics community. 

Abstract White clover (Trifolium repens L.; Fabaceae) is an important forage and cover crop in agricultural pastures around the world and is increasingly used in evolutionary ecology and genetics to understand the genetic basis of adaptation. Historically, improvements in white clover breeding practices and assessments of genetic variation in nature have been hampered by a lack of high-quality genomic resources for this species, owing in part to its high heterozygosity and allotetraploid hybrid origin. Here, we use PacBio HiFi and chromosome conformation capture (Omni-C) technologies to generate a chromosome-level, haplotype-resolved genome assembly for white clover totaling 998 Mbp (scaffold N50 = 59.3 Mbp) and 1 Gbp (scaffold N50 = 58.6 Mbp) for haplotypes 1 and 2, respectively, with each haplotype arranged into 16 chromosomes (8 per subgenome). We additionally provide a functionally annotated haploid mapping assembly (968 Mbp, scaffold N50 = 59.9 Mbp), which drastically improves on the existing reference assembly in both contiguity and assembly accuracy. We annotated 78,174 protein-coding genes, resulting in protein BUSCO completeness scores of 99.6% and 99.3% against the embryophyta_odb10 and fabales_odb10 lineage datasets, respectively.