The genetic consequences of spatially varying selection in the panmictic American eel (Anguilla rostrata)

Abstract

Our understanding of the genetic basis of local adaptation has recently benefited from the increased power to identify functional variants associated with environmental variables at the genome scale. However, it often remains challenging to determine whether locally adaptive alleles are actively maintained at intermediate frequencies by spatially varying selection. Here, we evaluate the extent to which this particular type of balancing selection explains the retention of adaptive genetic variation in the extreme situation of perfect panmixia, using the American eel (Anguilla rostrata) as a model. We first conducted a genome scan between two samples from opposite ends of a latitudinal environmental gradient using 454 sequencing of individually tagged cDNA libraries. Candidate SNPs were then genotyped in 992 individuals from 16 sampling sites at different life stages of the same cohort (including larvae from the Sargasso Sea, glass eels, and 1-year-old individuals) as well as in glass eels of the following cohort. Evidence for spatially varying selection was found at 13 loci showing correlations between allele frequencies and environmental variables across the entire species range. Simulations under a multiple-niche Levene's model using estimated relative fitness values among genotypes rarely predicted a stable polymorphic equilibrium at these loci. Our results suggest that some genetic-by-environment interactions detected in our study arise during the progress toward fixation of a globally advantageous allele with spatially variable effects on fitness.

Figure 1

Correlation between river mouth temperature and allele frequencies at locus ACP. Logistic regression is based on all three continental categories. (A) Allele frequencies in the GLASS8 category are represented by solid squares, OYO9 by circles with light shading, and GLASS9 by triangles with dark shading. (B) Sliding-window analysis of the coefficient of determination (R²) between allele frequencies at locus ACP in the GLASS8 category and the values predicted using river mouth temperature data. For each day within a 3-month period centered on the sampling date (which also corresponded approximately to the date of arrival at river mouths), surface temperature was taken as the mean value across the 10 previous days.

Figure 2

Synthetic multilocus spatial variation component in the 2008 glass eels. The spatial component analysis was based on genetic variation at the eight loci significantly associated with explanatory variables in the GLASS8 category. The 16 sampling sites are represented on the map by squares colored according to each locality’s lagged score on the first principal component, as indicated in the inset. Sea-surface temperatures averaged across the whole sampling period (from January 8 to July 16, 2008) are represented on the same color scale for indication (purple, 0.2°; red, 27.3°). The plot on the right shows the shape of the synthetic multilocus cline, as well as the decomposition of the product of the variance and the spatial autocorrelation into positive, null, and negative components (top right corner). The clinal structure corresponds to the highly positive eigenvalue in red.