Evolutionary Applications (May 2021)

Adaptive markers distinguish North and South Pacific Albacore amid low population differentiation

  • Felix Vaux,
  • Sandra Bohn,
  • John R. Hyde,
  • Kathleen G. O'Malley

DOI
https://doi.org/10.1111/eva.13202
Journal volume & issue
Vol. 14, no. 5
pp. 1343 – 1364

Abstract

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Abstract Albacore (Thunnus alalunga) support an economically valuable global fishery, but surprisingly little is known about the population structure of this highly migratory species. Physical tagging data suggest that Albacore from the North and South Pacific Ocean are separate stocks, but results from previous genetic studies did not support this two stock hypothesis. In addition, observed biological differences among juveniles suggest that there may be population substructure in the North Pacific. We used double‐digest restriction site‐associated DNA sequencing to assess population structure among 308 Albacore caught in 12 sample areas across the Pacific Ocean (10 North, 2 South). Since Albacore are highly migratory and spawning areas are unknown, sample groups were not assumed to be equivalent to populations and the genetic data were analyzed iteratively. We tested for putatively adaptive differences among groups and for genetic variation associated with sex. Results indicated that Albacore in the North and South Pacific can be distinguished using 84 putatively adaptive loci, but not using the remaining 12,788 presumed neutral sites. However, two individuals likely represent F1 hybrids between the North and South Pacific populations, and 43 Albacore potentially exhibit lower degrees of mixed ancestry. In addition, four or five cross‐hemisphere migrants were potentially identified. No genetic evidence was found for population substructure within the North Pacific, and no loci appeared to distinguish males from females. Potential functions for the putatively adaptive loci were identified, but an annotated Albacore genome is required for further exploration. Future research should try to locate spawning areas so that life history, demography, and genetic population structure can be linked and spatiotemporal patterns can be investigated.

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