Selection on ancestral genetic variation fuels repeated ecotype formation in bottlenose dolphins
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Studying repeated adaptation can provide insights into the mechanisms allowing species to adapt to novel environments. Here, we investigate repeated evolution driven by habitat specialization in the common bottlenose dolphin. Parapatric pelagic and coastal ecotypes of common bottlenose dolphins have repeatedly formed across the oceans. Analyzing whole genomes of 57 individuals, we find that ecotype evolution involved a complex reticulated evolutionary history. We find parallel linked selection acted upon ancient alleles in geographically distant coastal populations, which were present as standing genetic variation in the pelagic populations. Candidate loci evolving under parallel linked selection were found in ancient tracts, suggesting recurrent bouts of selection through time. Therefore, despite the constraints of small effective population size and long generation time on the efficacy of selection, repeated adaptation in long-lived social species can be driven by a combination of ecological opportunities and selection acting on ancestral standing genetic variation.
| Originalsprog | Engelsk |
|---|---|
| Artikelnummer | eabg1245 |
| Tidsskrift | Science Advances |
| Vol/bind | 7 |
| Udgave nummer | 44 |
| Antal sider | 14 |
| ISSN | 2375-2548 |
| DOI | |
| Status | Udgivet - 2021 |
Bibliografisk note
Funding Information:
Funding for sequencing was provided by the Total Foundation awarded to M.L., the University of Groningen awarded to M.C.F., and the Marine Alliance for Science and Technology for Scotland and The Russell Trust awarded to O.E.G. M.L. was supported by a Fyssen Fellowship, Total Foundation, Systematics Research Fund, Godfrey Hewitt mobility award from the European Society for Evolutionary Biology (ESEB), People's Trust for Endangered Species, Lerner-Gray Grants for Marine Research from the American Museum of Natural History, and the University of St Andrews. M.G. was funded through a Swiss National Science Foundation grant (31003A_173062) to D.W. A.D.F. was supported by European Union's Horizon 2020 research and innovation program under the Marie Sk?odowska-Curie grant agreement no. 663830. Bioinformatics and computational biology analyses were supported by the University of St Andrews Bioinformatics Unit, which is funded by a Wellcome Trust ISSF award (grant 105621/Z/14/Z).
Publisher Copyright:
Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).
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