Genome-wide RAD sequence data provide unprecedented resolution of species boundaries and relationships in the Lake Victoria cichlid adaptive radiation.

Although population genomic studies using next generation sequencing (NGS) data are becoming increasingly common, studies focusing on phylogenetic inference using these data are in their infancy. Here, we use NGS data generated from reduced representation genomic libraries of restriction-site-associated DNA (RAD) markers to infer phylogenetic relationships among 16 species of cichlid fishes from a single rocky island community within Lake Victoria's cichlid adaptive radiation. Previous attempts at sequence-based phylogenetic analyses in Victoria cichlids have shown extensive sharing of genetic variation among species and no resolution of species or higher-level relationships. These patterns have generally been attributed to the very recent origin (<15,000 years) of the radiation, and ongoing hybridization between species. We show that as we increase the amount of sequence data used in phylogenetic analyses, we produce phylogenetic trees with unprecedented resolution for this group. In trees derived from our largest data supermatrices (3 to >5.8 million base pairs in width), species are reciprocally monophyletic with high bootstrap support, and the majority of internal branches on the tree have high support. Given the difficulty of the phylogenetic problem that the Lake Victoria cichlid adaptive radiation represents, these results are striking. The strict interpretation of the topologies we present here warrants caution because many questions remain about phylogenetic inference with very large genomic data set and because we can with the current analysis not distinguish between effects of shared ancestry and post-speciation gene flow. However, these results provide the first conclusive evidence for the monophyly of species in the Lake Victoria cichlid radiation and demonstrate the power that NGS data sets hold to resolve even the most difficult of phylogenetic challenges.