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Data from: Multiplexed shotgun genotyping resolves species relationships within the North American genus Penstemon


Wessinger, Carolyn A. et al. (2017), Data from: Multiplexed shotgun genotyping resolves species relationships within the North American genus Penstemon, Dryad, Dataset,


Premise of the study: Evolutionary radiations provide opportunities to examine large-scale patterns in diversification and character evolution, yet are often recalcitrant to phylogenetic resolution due to rapid speciation events. The plant genus Penstemon has been difficult to resolve using Sanger sequence-based markers, leading to the hypothesis that it represents a recent North American radiation. The present study demonstrates the utility of multiplexed shotgun genotyping (MSG), a style of Restriction site-associated DNA sequencing (RADseq), to infer phylogenetic relationships within a subset of species in this genus and provide insight into evolutionary patterns. Methods: We sampled genomic DNA, primarily from herbarium material, and subjected it to MSG library preparation and Illumina sequencing. The resultant sequencing reads were clustered into homologous loci, aligned, and concatenated into data matrices that differed according to clustering similarity and amount of missing data. We performed phylogenetic analyses on these matrices using maximum likelihood (RAxML) and a species tree approach (SVDquartets). Key results: MSG data provide a highly resolved estimate of species relationships within Penstemon. While most species relationships were highly supported, the position of certain taxa remains ambiguous, suggesting that increased taxonomic sampling or additional methodologies may be required. The data confirm that evolutionary shifts from hymenopteran- to hummingbird-adapted flowers have occurred independently many times. Conclusions: This study demonstrates that phylogenomic approaches yielding thousands of variable sites can greatly improve species-level resolution of recent and rapid radiations. Similar to other studies, we found that less conservative similarity and missing data thresholds resulted in more highly supported topologies.

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