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Spatiotemporal SNP analysis reveals pronounced biocomplexity at the northern range margin of Atlantic cod Gadus morhua.

Authors :
Therkildsen, Nina Overgaard
Hemmer-Hansen, Jakob
Hedeholm, Rasmus Berg
Wisz, Mary S.
Pampoulie, Christophe
Meldrup, Dorte
Bonanomi, Sara
Retzel, Anja
Olsen, Steffen Malskær
Eg Nielsen, Einar
Source :
Evolutionary Applications; Jun2013, Vol. 6 Issue 4, p690-705, 16p
Publication Year :
2013

Abstract

Accurate prediction of species distribution shifts in the face of climate change requires a sound understanding of population diversity and local adaptations. Previous modeling has suggested that global warming will lead to increased abundance of Atlantic cod (Gadus morhua) in the ocean around Greenland, but the dynamics of earlier abundance fluctuations are not well understood. We applied a retrospective spatiotemporal population genomics approach to examine the temporal stability of cod population structure in this region and to search for signatures of divergent selection over a 78-year period spanning major demographic changes. Analyzing >900 gene-associated single nucleotide polymorphisms in 847 individuals, we identified four genetically distinct groups that exhibited varying spatial distributions with considerable overlap and mixture. The genetic composition had remained stable over decades at some spawning grounds, whereas complete population replacement was evident at others. Observations of elevated differentiation in certain genomic regions are consistent with adaptive divergence between the groups, indicating that they may respond differently to environmental variation. Significantly increased temporal changes at a subset of loci also suggest that adaptation may be ongoing. These findings illustrate the power of spatiotemporal population genomics for revealing biocomplexity in both space and time and for informing future fisheries management and conservation efforts. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17524563
Volume :
6
Issue :
4
Database :
Complementary Index
Journal :
Evolutionary Applications
Publication Type :
Academic Journal
Accession number :
102204850
Full Text :
https://doi.org/10.1111/eva.12055