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

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.

Keywords: Greenland; adaptive divergence; climate change; contemporary evolution; genetic monitoring; marine fish; population structure; temporal change.

Figure 1

Approximate sampling locations in Greenland and Iceland (main map) shown in relation to the reference sample from Canada (blue dot on the inset map). Dots shifted left represent historical samples while dots shifted right represent contemporary samples. Samples are named by three-letter codes to indicate the location followed by two digits to indicate the sampling year (see Table 1; note the mixed origin of OWE10). For all samples except CAN08, the colors of the dots represent the blends of sample mean coordinates on the first two discriminant functions recoded as signal intensities of red and green, respectively (see text and Fig. 2a).

Figure 2

Scatterplots of the mean sample coordinates on the first and second (A) and the first and third (B) discriminant functions (DF) from the discriminant analysis of principal components (DAPC) based on the four inferred clusters. Contemporary sample names are plotted in white and historical sample names in gray. The background shading of the plot area illustrates the blended color gradient resulting from recoding coordinates on the first and second DF to intensity of red and green, respectively (see text).

Figure 3

Plot of the posterior membership probabilities of each individual to the Iceland inshore (yellow), East (red), West (green), and Nuuk (brown) clusters, respectively. Each vertical line represents an individual and is divided into color segments proportional to its posterior membership probability to each of the geographic clusters derived from the discriminant analysis of principal components (DAPC) including only the ‘pure’ samples (see text). The order of individuals within samples is random, but samples are ordered according to hydrographic distance from the easternmost sample.

Figure 4

Matrix of results from the bayescan spatial outlier tests in pairwise comparisons of the clusters. Each cell shows the q-value for each locus being under selection plotted against genome position (ordered by linkage groups LGs). Loci above the horizontal lines (representing q = 0.05) are considered significant outliers and loci that were also outliers in the Arlequin analysis are marked by filled symbols. Circles represent loci with known position within LGs, whereas triangles denote loci that were anchored to an LG but with unknown position within the LG. Loci in LG1, 2, and 7 are highlighted in blue, purple, and red, respectively, whereas the remaining LGs are plotted in alternating shades of gray and loci that could not be anchored to the linkage map are plotted in black.

Figure 5

Examples of temporal outlier detection results in DAB (A) and KAP (B). Each dot represents a locus, illustrating its temporal differentiation (F_temp, y-axis) against its heterozygosity (x-axis). The lines represent the 95% (gray) and the 99% (black) confidence envelopes of the simulated neutral distribution.