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RAD-Seq Reveals Patterns of Additive Polygenic Variation Caused by Spatially-Varying Selection in the American Eel
Charles Babin1, Pierre-Alexandre Gagnaire2, Scott A Pavey3
1IBIS (Institut de biologie intégrative et des systèmes), Département de biologie, Université Laval, Québec, Canada.
Abstract:
The American Eel (Anguilla rostrata) has an exceptional life cycle characterized by panmictic reproduction at the species scale, random dispersal, and selection in a highly heterogeneous habitat extending from subtropical to subarctic latitudes. The genetic consequences of spatially-varying selection in this species have been investigated for decades, revealing subtle clines in allele frequency at a few loci that contrast with complete panmixia on the vast majority of the genome. Because reproduction homogenizes allele frequencies every generation, sampling size, and genomic coverage are critical to reach sufficient power to detect selected loci in this context. Here, we used a total of 710 individuals from 12 sites and 12,098 high-quality single nucleotide polymorphisms to re-evaluate the extent to which local selection affects the spatial distribution of genetic diversity in this species. We used environmental association methods to identify markers under spatially-varying selection, which indicated that selection affects ∼1.5% of the genome. We then evaluated the extent to which candidate markers collectively vary with environmental factors using additive polygenic scores. We found significant correlations between polygenic scores and latitude, longitude and temperature which are consistent with polygenic selection acting against maladapted genotypes in different habitats occupied by eels throughout their range of distribution. Gene functions associated with outlier markers were significantly enriched for the insulin signaling pathway, indicating that the trade-offs inherent to occupying such a large distribution range involve the regulation of metabolism. Overall, this study highlights the potential of the additive polygenic scores approach in detecting selective effects in a complex environment.
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