Genomic signatures of divergent selection are associated with social behaviour for spinner dolphin ecotypes.

Understanding the genomic basis of adaptation is critical for understanding evolutionary processes and predicting how species will respond to environmental change. Spinner dolphins in the eastern tropical Pacific (ETP) present a unique system for studying adaptation. Within this large geographical region are four spinner dolphin ecotypes with weak neutral genetic divergence and no obvious barriers to gene flow, but strong spatial variation in morphology, behaviour and habitat. These ecotypes have large population sizes, which could reduce the effects of drift and facilitate selection. To identify genomic regions putatively under divergent selective pressures between ecotypes, we used genome scans with 8994 RADseq single nucleotide polymorphisms (SNPs) to identify population differentiation outliers and genotype-environment association outliers. Gene ontology enrichment analyses indicated that outlier SNPs from both types of analyses were associated with multiple genes involved in social behaviour and hippocampus development, including 15 genes associated with the human social disorder autism. Evidence for divergent selection on social behaviour is supported by previous evidence that these spinner dolphin ecotypes differ in mating systems and associated social behaviours. In particular, three of the ETP ecotypes probably have a polygynous mating system characterized by strong premating competition among males, whereas the fourth ecotype probably has a polygynandrous mating system characterized by strong postmating competition such as sperm competition. Our results provide evidence that selection for social behaviour may be an evolutionary force driving diversification of spinner dolphins in the ETP, potentially as a result of divergent sexual selection associated with different mating systems. Future studies should further investigate the potential adaptive role of the candidate genes identified here, and could probably find further signatures of selection using whole genome sequence data.