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Dryad

Data from: Unioverse: a phylogenomic resource for reconstructing the evolution of freshwater mussels (Bivalvia, Unionoida)

Cite this dataset

Pfeiffer, John M.; Breinholt, Jesse W.; Page, Larry M. (2019). Data from: Unioverse: a phylogenomic resource for reconstructing the evolution of freshwater mussels (Bivalvia, Unionoida) [Dataset]. Dryad. https://doi.org/10.5061/dryad.8575jr5

Abstract

Freshwater mussels (order Unionoida) are a diverse radiation of parasitic bivalves that require temporary larval encystment on vertebrate hosts to complete metamorphosis to their free-living phase. The freshwater mussel-fish symbiosis represents a useful relationship for understanding eco-evolutionary dynamics in freshwater ecosystems but the practicality of this promising model system is undermined by the absence of a stable freshwater mussel phylogeny. Inadequate character sampling is the primary analytical impediment obfuscating a coherent phylogeny of freshwater mussels, specifically the lack of nuclear molecular markers appropriate for reconstructing supraspecific relationships and testing macroevolutionary hypotheses. The objective of this study is to develop a phylogenomic resource, specifically an anchored hybrid enrichment probe set, capable of capturing hundreds of molecular markers from taxa distributed across the entirety of freshwater mussel biodiversity. Our freshwater mussel specific anchored hybrid enrichment probe set, called Unioverse, successfully captures hundreds of nuclear protein-coding loci from all major lineages of the Unionoida and will facilitate more data-rich and taxonomically inclusive reconstructions of freshwater mussel evolution. We demonstrate the utility of this resource at three disparate evolutionary scales by estimating a backbone phylogeny of the Bivalvia with a focus on the order Unionoida, reconstructing the subfamily-level relationships of the Unionidae, and recovering the systematic position of the phylogenetically unstable genus Plectomerus.

Usage notes

Funding

National Science Foundation, Award: DEB 1701901