Genetics of ecological divergence during speciation

Abstract

Ecological differences often evolve early in speciation as divergent natural selection drives adaptation to distinct ecological niches, leading ultimately to reproductive isolation. Although this process is a major generator of biodiversity, its genetic basis is still poorly understood. Here we investigate the genetic architecture of niche differentiation in a sympatric species pair of threespine stickleback fish by mapping the environment-dependent effects of phenotypic traits on hybrid feeding and performance under semi-natural conditions. We show that multiple, unlinked loci act largely additively to determine position along the major niche axis separating these recently diverged species. We also find that functional mismatch between phenotypic traits reduces the growth of some stickleback hybrids beyond that expected from an intermediate phenotype, suggesting a role for epistasis between the underlying genes. This functional mismatch might lead to hybrid incompatibilities that are analogous to those underlying intrinsic reproductive isolation but depend on the ecological context.

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Figure 1: Niche use and body size.
Figure 2: Trait variation among F2 hybrid groups.
Figure 3: Genetic architecture of niche divergence.

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Acknowledgements

We thank J. Perez for counting gill rakers; C. Sather for performing lab work for SNP genotyping; and K. Broman, G. Coop, I. Goodliffe, A. Greenwood, P. Wainwright, M. White and M. Wund for constructive comments. Stable isotopes were analysed at the University of California, Davis, Stable Isotope Facility. Funding was provided by grants from the US National Institutes of Health (F32 GM086125 to M.E.A., R01 GM089733 to C.L.P. and D.S., and P50 HG002568 to C.L.P. and D.M.K.), the Natural Sciences and Engineering Research Council of Canada (to D.S.) and the Canada Foundation for Innovation (to D.S.).

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Contributions

M.E.A., C.L.P. and D.S. designed, planned and oversaw the project. M.E.A. made the crosses, set up the experimental pond and coordinated all field and laboratory research. M.E.A., K.B.M., S.K., N.B. and S.B. conducted fieldwork and stable-isotope analysis. M.D.M. measured functional morphological traits. B.M. and M.E.A. measured and analysed gut contents. S.K., D.S. and M.E.A. performed landmark-based morphometric analyses. M.E.A. analysed relationships between all traits and trophic variation. F.C.J., Y.F.C. and D.M.K. designed the SNP genotyping array. M.E.A., G.L.C., C.L.P and D.S. analysed SNP genotypes. D.S. determined the genealogy of the mapping population on the basis of SNP genotypes. M.E.A., C.L.P. and D.S. performed linkage and QTL analysis. M.E.A., C.L.P. and D.S. tested the genetic architecture of niche divergence. M.E.A., C.L.P., D.S., M.D.M., B.M. and G.L.C. interpreted the results. M.E.A. wrote the paper with input from C.L.P. and D.S., who are co-senior authors. All other authors provided editorial comments and approved the final version of the manuscript.

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Correspondence to Matthew E. Arnegard.

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Extended data figures and tables

Extended Data Figure 1 Experimental pond used in the study.

a, Photograph of pond no. 4 at the experimental pond facility of the University of British Columbia (Vancouver, British Columbia, Canada), taken in autumn 2008, during the collection of F2 juveniles. b, Diagram of the pond profile. See Supplementary Discussion for details on pond history before this study.

Extended Data Figure 2 Feeding patterns in relation to isotope signatures.

Plots show relationships between ingested prey counts from all available F2 hybrids (n = 99) and stable-isotope data. a, Loess-smoothed surface (span = 0.75, second-degree polynomials) of predicted chironomid counts plotted on original isotope axes (δ13C, δ15N). As with all other count data plotted here, counts were transformed as ln (chironomids + 1) and mapped according to the coloured scale. PC1 (black arrow) and PC2 (white) are based on the entire isotope distribution (Fig. 1a). Individuals are plotted as points according to the presence (crosses) or absence (filled circles) of calanoid copepods in their digestive tracts. bg, Linear or logistic regression, accordingly, of ingested prey count or presence/absence data (transformed as above) on the different axes through isotope space. b, Chironomid count against δ13C, linear regression, slope estimate = 0.415, R2 = 0.199, F1,97 = 24.1, P = 3.70 × 10−6. c, Chironomid presence against niche score, logistic regression, slope coefficient = 0.504, z = 2.23, P = 0.0255. d, Collembola presence against diet deviation score, logistic regression, slope coefficient = 1.25, z = 4.26, P = 2.03 × 10−5. e, Calanoid copepod count against δ15N, linear regression, slope estimate = 0.492, R2 = 0.0608, F1,97 = 6.28, P = 0.0139. f, Calanoid copepod presence against niche score, logistic regression, slope coefficient = −0.463, z = −1.84, P = 0.0651. g, Calanoid copepod presence against diet deviation score, logistic regression, slope coefficient = −0.958, z = −2.67, P = 0.00766. Source data

Extended Data Figure 3 Linkage map showing QTLs for all traits.

All G. aculeatus chromosomes are represented by LGs in the complete linkage map for this study (LGs and chromosomes use the same numbering29; LGs with no mapped QTLs are omitted here). Map distances are indicated with a scale at the left of each LG in centimorgans (cM). Coloured bars (at the right) are 1.5-LOD confidence intervals for QTL position (red bars, component traits of niche use; blue bars, other traits; Supplementary Table 3 provides LOD scores, map positions of LOD peaks, and effect sizes). The given SNP identifiers (IDs) are only for reference to Supplementary Table 4, which provides published SNP data30. For clarity, every other ID is omitted for SNP 066–098, even though these markers are present in the map. Markers closest to candidate QTLs for genetic model comparisons are highlighted: red text, nearest to candidate QTLs for niche score; green boxes, diet deviation score. Numbered traits are the x and y coordinates of morphometric landmarks (indicated on the fish photo): 1, posterior midpoint caudal peduncle; 2, anterior insertion anal fin at first soft ray; 3, posteroventral corner ectocoracoid; 4, posterodorsal corner ectocoracoid; 5, anteriormost corner ectocoracoid; 6, anteroventral corner opercle; 7, posterodorsal corner opercle; 8, dorsal edge opercle–hyomandibular boundary; 9, dorsalmost extent preopercle; 10, posteroventral corner preopercle; 11, anteriormost extent preopercle along ventral silhouette; 12, posteroventral extent maxilla; 13, anterodorsal extent maxilla; 14, suture between nasal and frontal bones along dorsal silhouette; 15, anterior margin orbit; 16, posterior margin orbit; 17, ventral margin orbit (landmarks 15–17 placed in line with vertical or horizontal midpoint of eye); 18, posterior extent supraoccipital along dorsal silhouette; 19, anterior insertion dorsal fin at first soft ray. Source data

Extended Data Figure 4 Shape variation among F2 hybrid groups.

Each overlaid pair of wireframe diagrams compares the mean body shape of individuals in one of three groups of F2 hybrids (B, L or A; shown in dark blue) with the relative mean shape of a reference group consisting of all other F2 hybrids (group membership shown in Fig. 1a). Using data for 19 Procrustes-superimposed and unbent landmarks (Extended Data Fig. 3), the wireframe diagrams were produced and plotted in MorphoJ v.1.04a, on the basis of discriminant function analysis (Supplementary Discussion). The shape differences represented here are magnified eightfold for easier visual comparison. Group sample sizes: n = 91 (B), n = 92 (L), n = 93 (A), n = 335 (reference group). See Supplementary Discussion for a detailed description of patterns of variation in several specific features of shape that can be interpreted from these data. Source data

Extended Data Figure 5 Variation of additional traits among F2 hybrid groups.

Means ( ± 1 s.e.m.) of F2 hybrids in groups B, L and A (Fig. 1a) are shown for the following traits (using raw data for long gill rakers and size-corrected data for the other traits): a, number of long gill rakers (ANOVA, F2,279 = 1.756, P = 0.175); b, residual anterior epaxial muscle height (F2,246 = 5.219, P = 0.00603); c, residual anterior epaxial muscle width (F2,246 = 4.223, P = 0.0157); d, residual neurocranium outlever length (F2,246 = 13.36, P = 3.10 × 10−6); e, residual buccal cavity length (F2,246 = 12.26, P = 8.42 × 10−6); f, residual gape (F2,246 = 7.974, P = 4.41 × 10−4). Numbers in parentheses are values of n. Traits are illustrated in Fig. 2e–g. The data conformed reasonably well to parametric statistical assumptions; ANOVA was therefore used to test trait variation among categories. Source data

Extended Data Figure 6 Relationships between F2 hybrid functional morphology and niche score.

For key functional morphological traits known to differ between wild Paxton benthics and limnetics, trait data from all available F2 hybrids are plotted against niche score and fitted with linear regression (raw data for gill raker counts; size-corrected data for other traits): a, number of long gill rakers (R2 = 0.0146; F1,629 = 9.32; P = 0.00236); b, number of short gill rakers (R2 = 0.0253; F1,629 = 16.30; P = 6.06 × 10−5); c, residual anterior epaxial muscle height (R2 = 0.0125; F1,552 = 7.00; P = 0.00804); d, residual anterior epaxial muscle width (R2 = 0.0189; F1,552 = 10.61; P = 0.00119); e, residual upper jaw protrusion length (R2 = 0.0580; F1,552 = 34.00; P = 9.40 × 10−9); f, residual lower jaw-opening inlever length (R2 = 0.0660; F1,615 = 43.43; P = 9.45 × 10−11). Traits are illustrated in Fig. 2e–g. Directions of benthic–limnetic divergence in Paxton Lake (arrows at left of plots, here and in Fig. 2a–d) are based on previously published studies16,18,19, combined with validating counts of long and short gill rakers for this study (data not shown). Source data

Extended Data Table 1 Goodness-of-fit tests for genomic distribution of QTLs
Extended Data Table 2 MQM model of only main effects of 14 candidate morphological QTLs on niche score
Extended Data Table 3 Full MQM model of main QTL effects and effects of pairwise QTL interactions on niche score

Supplementary information

Supplementary Information

This file contains Supplementary Tables 1-4, a Supplementary Discussion and Supplementary References. (PDF 1680 kb)

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Arnegard, M., McGee, M., Matthews, B. et al. Genetics of ecological divergence during speciation. Nature 511, 307–311 (2014). https://doi.org/10.1038/nature13301

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