Genetics of ecological divergence during speciation

Journal name:
Nature
Volume:
511,
Pages:
307–311
Date published:
DOI:
doi:10.1038/nature13301
Received
Accepted
Published online

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.

At a glance

Figures

  1. Niche use and body size.
    Figure 1: Niche use and body size.

    a, Stable isotopes (δ13C and δ15N) for 625 F2 hybrids, showing contours of loess-smoothed body size. Individuals with extreme loess-predicted size are shown as black points (triangles point down, group B; triangles point up, group L; squares, group A; each contains 15% of individuals sampled from the pond; group L restricted to PC1<0.045 to preserve group distinctiveness). Other individuals are shown as grey circles. Arrows indicate principal components of isotope distribution (PC1, niche score; PC2, diet deviation score; origin, red cross). be, Counts of common food items (means±1 s.e.m.) in digestive tracts of group B, L and A individuals. b, Larval Chironomidae (benthic macroinvertebrate); c, Skistodiaptomus oregonensis (evasive calanoid copepod); d, Collembola (terrestrial origin, surface dwelling); e, Chydorus sp. (littoral cladoceran). Kruskal–Wallis tests for differences among groups: larval Chironomidae ( = 13.52, P = 0.001); S.oregonensis ( = 7.547, P = 0.023); Collembola ( = 18.67, P = 8.82×10−5); Chydorus sp. ( = 0.629, P = 0.730). Numbers in parentheses are values of n. f, Cubic splines48 of mean body size against niche score (predicted values ±2s.e.m.) estimated with the 20 largest F2 families (n = 438 individuals), 1,000 bootstrap replicates, and F2 family as a covariate (black, all individuals; orange, individuals with PC2<0).

  2. Trait variation among F2 hybrid groups.
    Figure 2: Trait variation among F2 hybrid groups.

    ad, Trait means (±1 s.e.m.) of F2 hybrids in categories B, L and A (Fig. 1a): a, number of short gill rakers (ANOVA, F2,279 = 5.396, P = 0.005); b, suction feeding index (F2,246 = 4.080, P = 0.018); c, residual lower jaw-opening inlever length (F2,275 = 20.36, P = 5.65×10−9); d, residual upper jaw protrusion length (F2,246 = 14.94, P = 7.54×10−7). Numbers in parentheses are values of n. Arrows indicate directions of benthic–limnetic divergence (vertical axes of b and c are inverted to facilitate visual comparisons). eg, Trait illustrations: e, gill rakers, functioning in prey retention16, 17; f, five components of suction feeding index18, 19; g, two oral jaw traits that influence efficiency of capturing evasive zooplankton19.

  3. Genetic architecture of niche divergence.
    Figure 3: Genetic architecture of niche divergence.

    a, Niche scores of F2 hybrids are predicted from the number of benthic alleles summed across 11 unlinked loci in the full MQM model (R2 = 0.081; F1,605 = 53.52; P = 8.18×10−13). Dashed lines are 95% confidence intervals of regression line (solid). b, Observed niche score compared with that predicted by the additive-only genetic model. c, Observed niche score compared with that predicted by the full genetic model: additive, dominance and epistatic effects. Statistics for b and c are provided in the text.

  4. Experimental pond used in the study.
    Extended Data Fig. 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.

  5. Feeding patterns in relation to isotope signatures.
    Extended Data Fig. 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.

  6. Linkage map showing QTLs for all traits.
    Extended Data Fig. 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 SNP066–098, 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.

  7. Shape variation among F2 hybrid groups.
    Extended Data Fig. 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.

  8. Variation of additional traits among F2 hybrid groups.
    Extended Data Fig. 5: Variation of additional traits among F2 hybrid groups.

    Means (±1s.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.

  9. Relationships between F2 hybrid functional morphology and niche score.
    Extended Data Fig. 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).

Tables

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

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Author information

Affiliations

  1. Fred Hutchinson Cancer Research Center, Human Biology and Basic Sciences Divisions, 1100 Fairview Avenue North, Seattle, Washington 98109, USA

    • Matthew E. Arnegard &
    • Catherine L. Peichel
  2. University of British Columbia, Biodiversity Research Centre and Zoology Department, 6270 University Boulevard, Vancouver, British Columbia V6T 1Z4, Canada

    • Matthew E. Arnegard,
    • Kerry B. Marchinko,
    • Gina L. Conte,
    • Sahriar Kabir,
    • Nicole Bedford &
    • Dolph Schluter
  3. University of California at Davis, Department of Evolution and Ecology, One Shields Avenue, Davis, California 95616, USA

    • Matthew D. McGee
  4. EAWAG, Department of Aquatic Ecology, Center for Ecology, Evolution, and Biogeochemistry, Seestrasse 79, 6047 Kastanienbaum, Switzerland

    • Blake Matthews
  5. Uppsala University, Department of Animal Ecology, Evolutionary Biology Centre (EBC), Norbyvägen 18D, SE-75236 Uppsala, Sweden

    • Sara Bergek
  6. Stanford University School of Medicine, Department of Developmental Biology and Howard Hughes Medical Institute, 279 Campus Drive, Stanford, California 94305, USA

    • Yingguang Frank Chan,
    • Felicity C. Jones &
    • David M. Kingsley
  7. Present address: Swedish University of Agricultural Sciences, Department of Aquatic Resources, Stångholmsvägen 2, SE-17893 Drottningholm, Sweden.

    • Sara Bergek

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.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

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Author details

Extended data figures and tables

Extended Data Figures

  1. Extended Data Figure 1: Experimental pond used in the study. (772 KB)

    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.

  2. Extended Data Figure 2: Feeding patterns in relation to isotope signatures. (307 KB)

    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.

  3. Extended Data Figure 3: Linkage map showing QTLs for all traits. (694 KB)

    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 SNP066–098, 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.

  4. Extended Data Figure 4: Shape variation among F2 hybrid groups. (389 KB)

    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.

  5. Extended Data Figure 5: Variation of additional traits among F2 hybrid groups. (99 KB)

    Means (±1s.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.

  6. Extended Data Figure 6: Relationships between F2 hybrid functional morphology and niche score. (353 KB)

    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).

Extended Data Tables

  1. Extended Data Table 1: Goodness-of-fit tests for genomic distribution of QTLs (158 KB)
  2. Extended Data Table 2: MQM model of only main effects of 14 candidate morphological QTLs on niche score (87 KB)
  3. Extended Data Table 3: Full MQM model of main QTL effects and effects of pairwise QTL interactions on niche score (159 KB)

Supplementary information

PDF files

  1. Supplementary Information (1.6 MB)

    This file contains Supplementary Tables 1-4, a Supplementary Discussion and Supplementary References.

Additional data