bioRxivEvolutionary Biology
Population Genomics of Rapidly Invading Lionfish in the Caribbean Reveals Signals of Range Expansion in the Absence of Spatial Population Structure
Abstract
Range expansions driven by global change and species invasions are likely to have significant genomic, evolutionary, and ecological implications. During range expansions, strong genetic drift characterized by repeated founder events can result in decreased genetic diversity with increased distance from the center of the historic range, or the point of invasion. The invasion of the Indo-Pacific lionfish, Pterois volitans, into waters off the U.S. East Coast, Gulf of Mexico, and Caribbean Sea provides a natural system to study rapid range expansion in an invasive marine fish with high dispersal capabilities. We report results from 12,759 loci sequenced by restriction enzyme associated DNA sequencing for nine P. volitans populations in the invaded range, including Florida and other Caribbean sites, as well as mitochondrial control region D-loop data. Analyses revealed low to no spatially explicit metapopulation genetic structure in the study area, which is partly consistent with previous finding of little structure within ocean basins, but partly divergent from reports of between-basin structure. Genetic diversity, however, was not homogeneous across all sampled sites. Patterns of genetic diversity correlate with invasion pathway. Observed heterozygosity, averaged across all loci within a population, decreases with distance from Florida while expected heterozygosity is mostly constant throughout sampled populations, indicating population genetic disequilibrium correlated with distance from the point of invasion. Using an FST outlier analysis and a Bayesian environmental correlation analysis, we identified 256 and 616 loci, respectively, that could be experiencing selection or genetic drift. Of these, 24 loci were shared between the two methods.
- organism: non-human primate
- assay: whole-genome sequencing
- research focus: genome assembly
- approach: statistical model
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