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Mutation predicts 40 million years of fly wing evolution

Nature volume 548, pages 447–450 (2017)Cite this article

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Abstract

Mutation enables evolution, but the idea that adaptation is also shaped by mutational variation is controversial1,2,3,4. Simple evolutionary hypotheses predict such a relationship if the supply of mutations constrains evolution5,6, but it is not clear that constraints exist, and, even if they do, they may be overcome by long-term natural selection7. Quantification of the relationship between mutation and phenotypic divergence among species will help to resolve these issues. Here we use precise data on over 50,000 Drosophilid fly wings to demonstrate unexpectedly strong positive relationships between variation produced by mutation, standing genetic variation, and the rate of evolution over the last 40 million years. Our results are inconsistent with simple constraint hypotheses because the rate of evolution is very low relative to what both mutational and standing variation could allow. In principle, the constraint hypothesis could be rescued if the vast majority of mutations are so deleterious that they cannot contribute to evolution, but this also requires the implausible assumption that deleterious mutations have the same pattern of effects as potentially advantageous ones. Our evidence for a strong relationship between mutation and divergence in a slowly evolving structure challenges the existing models of mutation in evolution.

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Figure 1: Mean wing shapes of 112 Drosophilid species, plus five outgroup taxa.
Figure 2: Species scores on the two directions in shape phenotype space (canonical variables) that explain the most variance among species means.
Figure 3: Ellipses representing the variation around each landmark.
Figure 4: Relationships between variance in wing shape in M, G and R.

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References

  1. Arnold, S. J., Pfrender, M. E. & Jones, A. G. The adaptive landscape as a conceptual bridge between micro- and macroevolution. Genetica 112–113, 9–32 (2001)

    Article  PubMed  Google Scholar 

  2. Hansen, T. F. & Houle, D. in The Evolutionary Biology of Complex Phenotypes (eds M. Pigliucci & K. Preston) 130–150 (Oxford Univ. Press, 2004)

  3. Blows, M. W. & Hoffmann, A. A. A reassessment of genetic limits to evolutionary change. Ecology 86, 1371–1384 (2005)

    Article  Google Scholar 

  4. Futuyma, D. J. Evolutionary constraint and ecological consequences. Evolution 64, 1865–1884 (2010)

    Article  PubMed  Google Scholar 

  5. Lande, R. Quantitative genetic analysis of multivariate evolution applied to brain:body size allometry. Evolution 33, 402–416 (1979)

    Article  PubMed  Google Scholar 

  6. Wagner, G. P. & Altenberg, L. Perspective: complex adaptations and the evolution of evolvability. Evolution 50, 967–976 (1996)

    Article  PubMed  Google Scholar 

  7. Bolstad, G. H. et al. Genetic constraints predict evolutionary divergence in Dalechampia blossoms. Phil. Trans. R. Soc. Lond. B 369, 20130255 (2014)

    Article  Google Scholar 

  8. Hill, W. G. Rates of change in quantitative traits from fixation of new mutations. Proc. Natl Acad. Sci. USA 79, 142–145 (1982)

    Article  ADS  MathSciNet  CAS  PubMed  MATH  PubMed Central  Google Scholar 

  9. Houle, D., Morikawa, B. & Lynch, M. Comparing mutational variabilities. Genetics 143, 1467–1483 (1996)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Houle, D. & Fierst, J. Properties of spontaneous mutational variance and covariance for wing size and shape in Drosophila melanogaster. Evolution 67, 1116–1130 (2013)

    Article  PubMed  Google Scholar 

  11. Lynch, M., Latta, L., Hicks, J. & Giorgianni, M. Mutation, selection, and the maintenance of life-history variation in a natural population. Evolution 52, 727–733 (1998)

    Article  PubMed  Google Scholar 

  12. Houle, D. How should we explain variation in the genetic variance of traits? Genetica 102–103, 241–253 (1998)

    Article  PubMed  Google Scholar 

  13. Farhadifar, R., Ponciano, J. M., Andersen, E. C., Needleman, D. J. & Baer, C. F. Mutation is a sufficient and robust predictor of genetic variation for mitotic spindle traits in Caenorhabditis elegans. Genetics 203, 1859–1870 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  14. Schluter, D. Adaptive radiation along genetic lines of least resistance. Evolution 50, 1766–1774 (1996)

    Article  PubMed  Google Scholar 

  15. Hansen, T. F. & Martins, E. P. Translating between microevolutionary process and macroevolutionary patterns: the correlation structure of interspecific data. Evolution 50, 1404–1417 (1996)

    Article  PubMed  Google Scholar 

  16. Lynch, M. The rate of morphological evolution in mammals from the standpoint of the neutral expectation. Am. Nat. 136, 727–741 (1990)

    Article  ADS  Google Scholar 

  17. Schluter, D. The Ecology of Adaptive Radiation (Oxford Univ. Press, 2000)

  18. Houle, D. & Meyer, K. Estimating sampling error of evolutionary statistics based on genetic covariance matrices using maximum likelihood. J. Evol. Biol. 28, 1542–1549 (2015)

    Article  CAS  PubMed  Google Scholar 

  19. Weber, K. E. Selection on wing allometry in Drosophila melanogaster. Genetics 126, 975–989 (1990)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Weber, K. E. How small are the smallest selectable domains of form? Genetics 130, 345–353 (1992)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Houle, D., Mezey, J., Galpern, P. & Carter, A. Automated measurement of Drosophila wings. BMC Evol. Biol. 3, 25 (2003)

    Article  PubMed  PubMed Central  Google Scholar 

  22. Bolstad, G. H. et al. Complex constraints on allometry revealed by artificial selection on the wing of Drosophila melanogaster. Proc. Natl Acad. Sci. USA 112, 13284–13289 (2015)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  23. Lynch, M. Methods for the analysis of comparative data in evolutionary biology. Evolution 45, 1065–1080 (1991)

    Article  PubMed  Google Scholar 

  24. Lynch, M. & Hill, W. G. Phenotypic evolution by neutral mutation. Evolution 40, 915–935 (1986)

    Article  PubMed  Google Scholar 

  25. Hansen, T. F. & Houle, D. Measuring and comparing evolvability and constraint in multivariate characters. J. Evol. Biol. 21, 1201–1219 (2008)

    Article  CAS  PubMed  Google Scholar 

  26. Riedl, R. A systems-analytical approach to macro-evolutionary phenomena. Q. Rev. Biol. 52, 351–370 (1977)

    Article  CAS  PubMed  Google Scholar 

  27. Cheverud, J. M. Quantitative genetics and developmental constraints on evolution by selection. J. Theor. Biol. 110, 155–171 (1984)

    Article  CAS  PubMed  ADS  Google Scholar 

  28. Pavličev, M. & Cheverud, J. M. Constraints evolve: context dependency of gene effects allows evolution of pleiotropy. Annu. Rev. Ecol. Evol. Syst. 46, 413–434 (2015)

    Article  Google Scholar 

  29. Draghi, J. & Wagner, G. P. Evolution of evolvability in a developmental model. Evolution 62, 301–315 (2008)

    Article  PubMed  Google Scholar 

  30. Pavličev, M ., Cheverud, J. M. & Wagner, G. P. Evolution of adaptive phenotypic variation patterns by direct selection for evolvability. Proc. R. Soc. Lond. B 278, 1903–1912 (2011)

    Google Scholar 

  31. Jones, A. G., Bürger, R. & Arnold, S. J. Epistasis and natural selection shape the mutational architecture of complex traits. Nat. Commun. 5, 3709 (2014)

    Article  ADS  CAS  PubMed  Google Scholar 

  32. Hansen, T. F., Alvarez-Castro, J. M., Carter, A. J. R., Hermisson, J. & Wagner, G. P. Evolution of genetic architecture under directional selection. Evolution 60, 1523–1536 (2006)

    Article  PubMed  Google Scholar 

  33. Hansen, T. F. in Epigenetics: Linking Genotype and Phenotype in Development and Evolution (eds B. Hallgrimsson & B. K. Hall) 357–376 (Univ. California, 2011)

  34. Le Rouzic, A., Álvarez-Castro, J. M. & Hansen, T. F. The evolution of canalization and evolvability in stable and fluctuating environments. Evol. Biol. 40, 317–340 (2013)

    Article  Google Scholar 

  35. Grabowski, M. W., Polk, J. D. & Roseman, C. C. Divergent patterns of integration and reduced constraint in the human hip and the origins of bipedalism. Evolution 65, 1336–1356 (2011)

    Article  PubMed  Google Scholar 

  36. Mezey, J. G. & Houle, D. The dimensionality of genetic variation for wing shape in Drosophila melanogaster. Evolution 59, 1027–1038 (2005)

    Article  PubMed  Google Scholar 

  37. van der Linde, K., Houle, D., Spicer, G. S. & Steppan, S. J. A supermatrix-based molecular phylogeny of the family Drosophilidae. Genet. Res. 92, 25–38 (2010)

    Article  CAS  Google Scholar 

  38. Sanderson, M. J. Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach. Mol. Biol. Evol. 19, 101–109 (2002)

    Article  CAS  PubMed  Google Scholar 

  39. Obbard, D. J. et al. Estimating divergence dates and substitution rates in the Drosophila phylogeny. Mol. Biol. Evol. 29, 3459–3473 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Russo, C. A. M., Takezaki, N. & Nei, M. Molecular phylogeny and divergence times of drosophilid species. Mol. Biol. Evol. 12, 391–404 (1995)

    CAS  PubMed  Google Scholar 

  41. Tamura, K., Subramanian, S. & Kumar, S. Temporal patterns of fruit fly (Drosophila) evolution revealed by mutation clocks. Mol. Biol. Evol. 21, 36–44 (2004)

    Article  CAS  PubMed  Google Scholar 

  42. Grimaldi, D. & Engel, M. S. Evolution of the Insects (Cambridge Univ. Press, 2005)

  43. Wiegmann, B. M. et al. Episodic radiations in the fly tree of life. Proc. Natl Acad. Sci. USA 108, 5690–5695 (2011)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  44. O’Grady, P. M. Reevaluation of phylogeny in the Drosophila obscura species group based on combined analysis of nucleotide sequences. Mol. Phylogenet. Evol. 12, 124–139 (1999)

    Article  PubMed  Google Scholar 

  45. Van der Linde, K. & Houle, D. A supertree analysis and literature review of the genus Drosophila and closely related genera (Diptera, Drosophilidae). Insect Syst. Evol. 39, 241–267 (2008)

    Article  Google Scholar 

  46. Reed, L. K., Nyboer, M. & Markow, T. A. Evolutionary relationships of Drosophila mojavensis geographic host races and their sister species Drosophila arizonae. Mol. Ecol. 16, 1007–1022 (2007)

    Article  CAS  PubMed  Google Scholar 

  47. Stensmyr, M. C., Stieber, R. & Hansson, B. S. The Cayman crab fly revisited—phylogeny and biology of Drosophila endobranchia. PLoS One 3, e1942 (2008)

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  48. Oliveira, D. C. S. G. et al. Monophyly, divergence times, and evolution of host plant use inferred from a revised phylogeny of the Drosophila repleta species group. Mol. Phylogenet. Evol. 64, 533–544 (2012)

    Article  PubMed  Google Scholar 

  49. Wings: Automated Capture of Drosophila Wing Shape v.3.72 http://bio.fsu.edu/~dhoule/wings.html (2004–2009)

  50. Rohlf, F. J. & Slice, D. Extensions of the Procrustes method for the optimal superimposition of landmarks. Syst. Zool. 39, 40–59 (1990)

    Article  Google Scholar 

  51. Rousseeuw, P. J. & van Zomeren, B. C. Unmasking multivariate outliers and leverage points. J. Am. Stat. Assoc. 85, 633–639 (1990)

    Article  Google Scholar 

  52. MVE: Minimum Volume Ellipsoid Estimation for Robust Outlier Detection in Multivariate Space v. Java http://www.kimvdlinde.com/professional/mve.html (2004)

  53. Mitteroecker, P. & Bookstein, F. The ontogenetic trajectory of the phenotypic covariance matrix, with examples from craniofacial shape in rats and humans. Evolution 63, 727–737 (2009)

    Article  PubMed  Google Scholar 

  54. The SAS System for Windows Release 9.3 (SAS Institute, 2011)

  55. Wombat: A Program for Mixed Model Analyses by Restricted Maximum Likelihood (Animal Genetics and Breeding Unit, University of New England 2010–2015)

  56. Kirkpatrick, M. & Meyer, K. Direct estimation of genetic principal components: simplified analysis of complex phenotypes. Genetics 168, 2295–2306 (2004)

    Article  PubMed  PubMed Central  Google Scholar 

  57. Meyer, K. & Kirkpatrick, M. Restricted maximum likelihood estimation of genetic principal components and smoothed covariance matrices. Genet. Sel. Evol. 37, 1–30 (2005)

    Article  PubMed  PubMed Central  Google Scholar 

  58. Meyer, K. & Kirkpatrick, M. Perils of parsimony: properties of reduced-rank estimates of genetic covariance matrices. Genetics 180, 1153–1166 (2008)

    Article  PubMed  PubMed Central  Google Scholar 

  59. Hadfield, J. D. & Nakagawa, S. General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters. J. Evol. Biol. 23, 494–508 (2010)

    Article  CAS  PubMed  Google Scholar 

  60. Hansen, T. F., Armbruster, W. S., Carlson, M. L. & Pélabon, C. Evolvability and genetic constraints in Dalechampia blossoms: genetic correlations and conditional evolvability. J. Exp. Zool. B Mol. Dev. Evol. 296B, 23–39 (2003)

    Article  Google Scholar 

  61. Kristensen, K., Nielsen, A., Berg, C. & Skaug, H. Template model builder TMB. J. Stat. Softw. 70, 1–21 (2015)

    Google Scholar 

  62. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2016)

  63. Fuller, W. A. Measurement Error Models (Wiley, 1987)

  64. Hansen, T. F. & Bartoszek, K. Interpreting the evolutionary regression: the interplay between observational and biological errors in phylogenetic comparative studies. Syst. Biol. 61, 413–425 (2012)

    Article  PubMed  Google Scholar 

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Acknowledgements

We thank P. Galpern, J. Birdsley, F. S. Hollis, Y. Ng, and L. Carpenter for rearing and imaging Drosophilid species; C. Boake, J. David, G. Gilchrist, J. Hey, A. Hoikalla, L. Reed and J. True for contributing stocks, specimens or images; K. Meyer for assistance with Wombat; S. Steppan for help with r8s and phylogenetic analyses; J. Merilä and M. Kirkpatrick for comments; and to the many students who measured fly wings. This work was supported by US NSF DEB grants 0129219 and 0950002, and NSERC grants to D.H.

Author information

Authors and Affiliations

  1. Department of Biological Science, Florida State University, Tallahassee, 32306, Florida, USA

    David Houle, Geir H. Bolstad & Kim van der Linde

  2. Norwegian Institute for Nature Research (NINA), Trondheim, NO-7485, Norway

    Geir H. Bolstad

  3. Animal Genetics Inc., 1336 Timberlane Road, Tallahassee, 32312, Florida, USA

    Kim van der Linde

  4. Department of Biology, CEES & EVOGENE, University of Oslo, Oslo, 0316, Norway

    Thomas F. Hansen

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Contributions

D.H. conceived the project and supervised the gathering of data, K.v.d.L. wrote software and assembled the species dataset, T.F.H., G.H.B. and D.H. derived the major theoretical framework for the analyses, D.H. and G.H.B. analysed the data, and D.H., T.F.H. and G.H.B. wrote the manuscript.

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Correspondence to David Houle.

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Reviewer Information Nature thanks J. Cheverud and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Figure 1 Wing landmarks measured and representation of shape changes.

a, Vein model fitted to a D. melanogaster wing. The coordinates of the twelve vein intersections shown are the data for this study. b–d, Shape vectors for PC1 of the matrices. b, Mhom matrix. c, G matrix. d, R matrix. Each vector represents a pattern of changes in the locations of landmark intersections, represented by the arrows. The colours represent the pattern of landmark movements as local expansions and contractions that can explain the movements of the landmarks. The scale of local changes is in log2 units, so −1 represents a halving of local area, and +1 a local doubling.

Extended Data Figure 2 Divergence of wing phenotypes as a function of the time since the most common ancestor.

Size divergence (top) is the absolute value of the difference in log-transformed centroid size. Shape divergence (bottom) is measured as Procrustes distance.

Extended Data Figure 3 Relationships between variance in M, G and R in wing size and shape.

a, R and G on Mhom and Mhet. b, R on G. See legend of Fig. 4 for additional explanation.

Extended Data Figure 4 Relationships between conditional variance in M or G and variance at higher levels.

See Legend of Fig. 4 for explanation. Values of the scaling slopes and R2 are given in Extended Data Table 4. a, R and G on Mhom and Mhet for shape. b, R and G on Mhom and Mhet for shape–size. c, R on G for shape. d, R on G for shape–size.

Extended Data Table 1 Taxa included in the species dataset, but not included in ref. 22
Full size table
Extended Data Table 2 Ratios of evolvabilities of matrix 1 to matrix 2
Full size table
Extended Data Table 3 Univariate estimates of phylogenetic heritability (H2) for twenty shape traits, plus ln(centroid size)
Full size table
Extended Data Table 4 Regression of log10 variances in R (per Myr) or G on log10 conditional variances in G or M matrices
Full size table

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Houle, D., Bolstad, G., van der Linde, K. et al. Mutation predicts 40 million years of fly wing evolution. Nature 548, 447–450 (2017). https://doi.org/10.1038/nature23473

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