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  • Review Article
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Fitness and its role in evolutionary genetics

Nature Reviews Genetics volume 10, pages 531–539 (2009)Cite this article

Key Points

  • This article starts by reviewing the differences between various measures of fitness, for example, individual fitness, absolute fitness, relative fitness and geometric mean fitness.

  • Differences in fitness (when measured appropriately) can be used to derive selection equations, which show how natural selection changes the genetic composition of a population through time.

  • Quantitative geneticists derived the secondary theorem of natural selection, which shows how selection on fitness will change other, genetically correlated traits.

  • Fitness landscape models, whether continuous or discrete, can be used to analyse how natural selection will drive a population to the top of a fitness peak.

  • Evolutionary geneticists are currently pursuing several empirical approaches to the study of fitness, including direct fitness assays, microbial experimental evolution and the use of DNA sequence data to infer a history of positive natural selection.

  • The concluding section sketches several major unresolved problems in the experimental study of fitness.

Abstract

Although the operation of natural selection requires that genotypes differ in fitness, some geneticists may find it easier to understand natural selection than fitness. Partly this reflects the fact that the word 'fitness' has been used to mean subtly different things. In this Review I distinguish among these meanings (for example, individual fitness, absolute fitness and relative fitness) and explain how evolutionary geneticists use fitness to predict changes in the genetic composition of populations through time. I also review the empirical study of fitness, emphasizing approaches that take advantage of recent genetic and genomic data, and I highlight important unresolved problems in understanding fitness.

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Figure 1: Allele frequency versus time.
Figure 2: A three-dimensional Wrightian fitness landscape.

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References

  1. Brandon, R. N. Adaptation and evolutionary theory. Stud. Hist. Philos. Sci. 9, 181–206 (1978).

    Google Scholar 

  2. Brandon, R. N. Adaptation and Environment (Princeton Univ. Press, New Jersey, 1990).

    Google Scholar 

  3. Mills, S. & Beatty, J. The propensity interpretation of fitness. Philos. Sci. 46, 263–286 (1979).

    Google Scholar 

  4. Sober, E. The Nature of Selection (MIT Press, Massachusetts, 1984).

    Google Scholar 

  5. Sober, E. in Thinking About Evolution (eds Singh R. S., Krimbas, C. B., Paul, D. B & Beatty, J.) 309–321 (Cambridge Univ. Press, Cambridge, 2001).

    Google Scholar 

  6. Barker, J. S. F. in Adaptation and Fitness in Animal Populations (eds van der Werf, J., Graser, H.-U., Frankham, R. & Gondro, C.) 3–14 (Springer, Heidelberg, 2009).

    Google Scholar 

  7. Haldane, J. B. S. The Causes of Evolution (Longmans, Green & Co., Ltd, New York, 1932).

    Google Scholar 

  8. Dobzhansky, T. Genetics and the Origin of Species 3rd edn (Columbia Univ. Press, New York, 1951).

    Google Scholar 

  9. Dobzhansky, T. A review of some fundamental concepts and problems of population genetics. Cold Spring Harb. Symp. Quant. Biol. 20, 1–15 (1955).

    CAS  PubMed  Google Scholar 

  10. Gillespie, J. H. Population Genetics: a Concise Guide (Johns Hopkins Univ. Press, Baltimore, 2004). A brief but clear introduction to mathematical population genetics. Little mathematical background is assumed.

    Google Scholar 

  11. Crow, J. F. & Kimura, M. An Introduction to Population Genetics Theory (Harper and Row, New York, 1970). The gold standard textbook of classical population genetics, including rigorous treatments of fitness and natural selection. The work is, in places, mathematically demanding.

    Google Scholar 

  12. Gillespie, J. Natural selection for variances in offspring number: a new evolutionary principle. Am. Nat. 111, 1010–1014 (1977).

    Google Scholar 

  13. Frank, S. A. & Slatkin, M. Evolution in a variable environment. Am. Nat. 136, 244–260 (1990).

    Google Scholar 

  14. Orr, H. A. Absolute fitness, relative fitness, and utility. Evolution 61, 2997–3000 (2007).

    PubMed  Google Scholar 

  15. Felsenstein, J. Theoretical Evolutionary Genetics 408 [online], (2007).

    Google Scholar 

  16. Gillespie, J. H. Natural selection with varying selection coefficients — a haploid model. Genet. Res. 21, 115–120 (1973).

    Google Scholar 

  17. Gillespie, J. H. The Causes of Molecular Evolution (Oxford Univ. Press, Oxford, 1991).

    Google Scholar 

  18. Seger, J. & Brockman, H. J. in Oxford Surveys in Evolutionary Biology (eds Harvey, P. H. & Partridge, L.) 182–211 (Oxford Univ. Press, Oxford, 1987).

    Google Scholar 

  19. Bulmer, M. Theoretical Evolutionary Ecology 352 (Sinauer, Sunderland, Massachusetts, 1994).

    Google Scholar 

  20. Stearns, S. C. Daniel Bernoulli (1738): evolution and economics under risk. J. Biosci. 25, 221–228 (2000).

    CAS  PubMed  Google Scholar 

  21. Levene, H. Genetic equilibrium when more than one ecological niche is available. Am. Nat. 87, 331–333 (1953).

    Google Scholar 

  22. Dempster, E. R. Maintenance of genetic heterogeneity. Cold Spring Harb . Symp . Quant . Biol. 20, 25–32 (1955).

    CAS  PubMed  Google Scholar 

  23. Wallace, B. Topics in Population Genetics (Norton, New York, 1968).

    Google Scholar 

  24. Robertson, A. A mathematical model of the culling process in dairy cattle. Anim. Prod. 8, 95–108 (1966). A little-read but enormously important paper in the history of quantitative genetics. The paper introduces the secondary theorem of natural selection.

    Google Scholar 

  25. Price, G. R. Selection and covariance. Nature 227, 520–521 (1970).

    CAS  PubMed  Google Scholar 

  26. Falconer, D. S. Introduction to Quantitative Genetics 2nd edn (Longman, UK, 1981).

    Google Scholar 

  27. Price, G. R. Extension of covariance selection mathematics. Ann. Hum. Genet. 35, 485–490 (1972).

    CAS  PubMed  Google Scholar 

  28. Crow, J. F. & Nagylaki, T. The rate of change of a character correlated with fitness. Am. Nat. 110, 207–213 (1976).

    PubMed  Google Scholar 

  29. Fisher, R. A. The Genetical Theory of Natural Selection (Oxford Univ. Press, Oxford, 1930).

    Google Scholar 

  30. Robertson, A. Selection in animals: synthesis. Cold Spring Harb. Symp. Quant. Genet. 20, 225–229 (1955).

    CAS  Google Scholar 

  31. Robertson, A. in Heritage from Mendel (ed. Brink, A.) 265–280 (Univ. Wisconsin Press, Madison, 1967).

    Google Scholar 

  32. Robertson, A. in Population Biology and Evolution (ed. Lewontin, R. C.) 5–16 (Syracuse Univ. Press, New York, 1968).

    Google Scholar 

  33. Ewens, W. J. An interpretation and proof of the fundamental theorem of natural selection. Theor. Pop. Biol. 36, 167–180 (1989).

    CAS  Google Scholar 

  34. Ewens, W. J. An optimizing principle of natural selection in evolutionary population genetics. Theor. Pop. Biol. 42, 333–346 (1992).

    CAS  Google Scholar 

  35. Edwards, A. W. F. The fundamental theorem of natural selection. Biol. Rev. 69, 443–474 (1994).

    CAS  PubMed  Google Scholar 

  36. Lessard, S., Fisher's fundamental theorem of natural selection revisited. Theor. Pop. Biol. 52, 119–136 (1997).

    CAS  Google Scholar 

  37. Crow, J. F. Here's to Fisher, additive genetic variance, and the fundamental theorem of natural selection. Evolution 56, 1313–1316 (2002).

    PubMed  Google Scholar 

  38. Kauffman, S. A. The Origins of Order 709 (Oxford Univ. Press, New York, 1993).

    Google Scholar 

  39. Orr, H. A. Genetic theories of adaptation: a brief history. Nature Rev. Genet. 6, 119–127 (2005).

    CAS  PubMed  Google Scholar 

  40. Joyce, P. et al. A general extreme value theory model for the adaptation of DNA sequences under strong selection and weak mutation. Genetics 180, 1627–1643 (2008).

    PubMed  PubMed Central  Google Scholar 

  41. Wright, S. Evolution in Mendelian populations. Genetics 16, 97–159 (1931).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Wright, S. The roles of mutation, inbreeding, crossbreeding, and selection in evolution. Proc. 6th Int. Cong. Genet. 1, 356–366 (1932). Wright's famous description of adaptive (or fitness) landscapes.

    Google Scholar 

  43. Wright, S. Character change, speciation, and the higher taxa. Evolution 36, 427–443 (1982).

    PubMed  Google Scholar 

  44. Coyne, J. A., Barton, N. H. & Turelli, M. A critique of Sewall Wright's shifting balance theory of evolution. Evolution 51, 643–671 (1997).

    PubMed  Google Scholar 

  45. Maynard Smith, J. in The Scientist Speculates: an Anthology of Partly-Baked Ideas (ed. Good, I. J.) 252–256 (Basic Books, Inc., New York, 1962).

    Google Scholar 

  46. Maynard Smith, J. Natural selection and the concept of a protein space. Nature 225, 563–564 (1970). A brilliant description of the problem of increasing fitness by evolution through a discrete sequence space.

    Google Scholar 

  47. Gillespie, J. H. A simple stochastic gene substitution model. Theor. Pop. Biol. 23, 202–215 (1983).

    CAS  Google Scholar 

  48. Gillespie, J. Molecular evolution over the mutational landscape. Evolution 38, 1116–1129 (1984).

    CAS  PubMed  Google Scholar 

  49. Kauffman, S. & Levin, S. Towards a general theory of adaptive walks on rugged landscapes. J. Theor. Biol. 128, 11–45 (1987).

    CAS  PubMed  Google Scholar 

  50. Kauffman, S. A., Weinberger, E. D. & Perelson, A. S. in Theoretical Immunology: Part One (ed. A. S. Perelson) 349–382 (Addison-Wesley, New York, 1988).

    Google Scholar 

  51. Macken, C. A. & Perelson, A. S. Protein evolution on rugged landscapes. Proc. Natl Acad. Sci. USA 86, 6191–6195 (1989).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Macken, C. A., Hagan, P. S. & Perelson, A. S. Evolutionary walks on rugged landscapes. SIAM J. Appl. Math. 51, 799–827 (1991).

    Google Scholar 

  53. Perelson, A. S. & Macken, C. A. Protein evolution on partially correlated landscapes. Proc. Natl Acad. Sci. USA 92, 9657–9661 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Orr, H. A. The population genetics of adaptation: the adaptation of DNA sequences. Evolution 56, 1317–1330 (2002).

    CAS  PubMed  Google Scholar 

  55. Orr, H. A. The distribution of fitness effects among beneficial mutations. Genetics 163, 1519–1526 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Orr, H. A. The probability of parallel adaptation. Evolution 59, 216–220 (2004).

    Google Scholar 

  57. Orr, H. A. Theories of adaptation: what they do and don't say. Genetica 123, 3–13 (2005).

    PubMed  Google Scholar 

  58. Lewontin, R. C., Moore, J. A., Provine, W. B. & Wallace, B. (eds). Dobzhansky's Genetics of Natural Populations I-XLIII (Columbia Univ. Press, New York, 1981). An important compilation of Dobzhansky's experimental studies of fitness in natural populations of D. pseudoobscura.

  59. Lewontin, R. C. The Genetic Basis of Evolutionary Change 346 (Columbia Univ. Press, New York, 1974).

    Google Scholar 

  60. Hedrick, P. W. Genetics of Populations Ch. 5 (Science Books International, Boston, 1983).

    Google Scholar 

  61. Hedrick, P. W. Murray, E. in Genetics and Biology of Fitness (eds Ashburner, M., Carson, H. L. & Thompson, J. N.) 61–104 (Academic, New York, 1983).

    Google Scholar 

  62. Christiansen, F. B. & Frydenberg, O. Selection component analysis of natural polymorphisms using population samples including mother-offspring combinations. Theor. Pop. Biol. 4, 425–445 (1973).

    CAS  Google Scholar 

  63. Bundgaard, J. & Christiansen, F. B. Dynamics of polymorphisms: I. Selection components of Drosophila melanogaster. Genetics 71, 439–460 (1972).

    CAS  PubMed  Google Scholar 

  64. Lewontin, R. C. & Cockerham, C. C. The goodness-of-fit test for detecting natural selection in randomly mating populations. Evolution 13, 561–564 (1959).

    Google Scholar 

  65. Prout, T. The estimation of fitnesses from genotypic frequencies. Evolution 19, 546–551 (1965).

    Google Scholar 

  66. Prout, T. The estimation of fitnesses from population data. Genetics 63, 949–967 (1969).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Denniston, C. & Crow, J. F. Alternative fitness models with the same allele frequency dynamics. Genetics 125, 201–205 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Kreitman, M. in Evolution at the Molecular Level (eds Selander, R. K., Clark, A. G. & Whittam, T. S.) 204–221 (Sinauer Associates, Inc., Sunderland, Massachusetts, 1991).

    Google Scholar 

  69. Kreitman, M. The neutral theory is dead. Long live the neutral theory. BioEssays 18, 678–683 (1996).

    CAS  PubMed  Google Scholar 

  70. Otto, S. P. Detecting the form of selection from DNA sequence data. Trends Genet. 16, 526–529 (2000).

    CAS  PubMed  Google Scholar 

  71. Eyre-Walker, A. The genomic rate of adaptive evolution. Trends Ecol. Evol. 21, 569–575 (2006). A review of Eyre-Walker's approach to using DNA sequence data to estimate the proportion of amino acid substitutions driven by natural selection.

    PubMed  Google Scholar 

  72. Hahn, M. W. Toward a selection theory of molecular evolution. Evolution 62, 255–265 (2008).

    CAS  PubMed  Google Scholar 

  73. McDonald, J. H. & Kreitman, M. Adaptive protein evolution at the Adh locus in Drosophila. Nature 351, 652–654 (1991). The paper that introduced the most widely used statistical test of neutrality versus selection at the level of DNA sequences.

    CAS  PubMed  Google Scholar 

  74. Begun, D. J. et al. Population genomics: whole-genome analysis of polymorphism and divergence in Drosophila simulans. PLoS Biol. 5, e310 (2007). A genome-wide analysis of molecular evolution in D. simulans . The paper provides evidence for frequent positive natural selection.

    PubMed  PubMed Central  Google Scholar 

  75. Smith, N. G. C. & Eyre-Walker, A. Adaptive protein evolution in Drosophila. Nature 415, 1022–1024 (2002).

    CAS  PubMed  Google Scholar 

  76. Andolfatto, P. Adaptive evolution of non-coding DNA in Drosophila. Nature 437, 1149–1152 (2005).

    CAS  PubMed  Google Scholar 

  77. Kim, Y. & Stephan, W. Detecting a local signature of genetic hitchhiking along a recombining chromosome. Genetics 160, 765–777 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Wright, S. I. et al. The effects of artificial selection on the maize genome. Science 308, 1310–1314 (2005).

    CAS  PubMed  Google Scholar 

  79. Lenski, R. E. & Travisano, M. Dynamics of adaptation and diversification: a 10,000-generation experiment with bacterial populations. Proc. Natl Acad. Sci. USA 91, 6808–6814 (1994). A classic account of a real-time experimental evolution study in Escherichia coli.

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Sniegowski, P. D., Gerrish, P. J. & Lenski, R. E. Evolutionof high mutation rates in experimental populations of E. coli. Nature 387, 703–705 (1997).

    CAS  PubMed  Google Scholar 

  81. Bull, J., Badgett, M. & Wichman, H. Big-benefit mutations in a bacteriophage inhibited with heat. Mol. Biol. Evol. 17, 942–950 (2000).

    CAS  PubMed  Google Scholar 

  82. Holder, K. & Bull, J. Profiles of adaptation in two similar viruses. Genetics 159, 1393–1404 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Travisano, M. & Lenski, R. E. Long-term experimental evolution in Escherichia coli. IV. Targets of selection and the specificity of adaptation. Genetics 143, 15–26 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Elena, S. F. et al. Evolutionary dynamics of fitness recovery from the debilitating effects of Muller's ratchet. Evolution 52, 309–314 (1998).

    PubMed  Google Scholar 

  85. Bull, J. J. et al. Exceptional convergent evolution in a virus. Genetics 147, 1497–1507 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Wichman, H. A. et al. Different trajectories of parallel evolution during viral adaptation. Science 285, 422–424 (1999).

    CAS  PubMed  Google Scholar 

  87. Elena, S. F. & Lenski, R. E. Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nature Rev. Genet. 4, 457–469 (2003).

    CAS  PubMed  Google Scholar 

  88. Silander, O. K., Tenaillon, O. & Chao, L. Understanding the evolutionary fate of finite populations: the dynamics of mutational effects. PLoS Biol. 5, e94 (2007).

    PubMed  PubMed Central  Google Scholar 

  89. Betancourt, A. Genome-wide patterns of substitution in adaptively evolving populations of the RNA bacteriophage MS2. Genetics 181, 1535–1544 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Stern, D. L. & Orgogozo, V. The locus of evolution: how predictable is genetic evolution? Evolution 62, 2155–2177 (2008).

    PubMed  PubMed Central  Google Scholar 

  91. Hoekstra, H. E. & Coyne, J. A. The locus of evolution: evo–devo and the genetics of adaptation. Evolution 61, 995–1016 (2007).

    PubMed  Google Scholar 

  92. Rokyta, D. R. et al. An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus. Nature Genet. 37, 441–444 (2005).

    CAS  PubMed  Google Scholar 

  93. Coyne, J. A. & Orr, H. A. Speciation (Sinauer Associates Inc., Sunderland, Massachusetts, 2004).

    Google Scholar 

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Acknowledgements

This work was suppported by a grant from the US National Institutes of Health.

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  1. Department of Biology, University of Rochester, River Campus Box 270211, Rochester, 14627-0211, New York, USA

    H. Allen Orr

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Nature Reviews Genetics Series on Modelling

Glossary

Instar

A developmental stage of insect larvae.

Random variable

A quantity that might take any of a range of values (discrete or continuous) that cannot be predicted with certainty but only described probabilistically.

Covariance

A measure of association between two variables that characterizes the tendency for the two variables to covary around their means in a systematic way.

Genetic drift

Random fluctuation in allele frequency owing to the sampling of gametes in a finite population.

Interdemic selection

Selection wherein local populations (demes) compete with each other. Wright believed that fitter populations would also produce more migrants.

NK model

A class of fitness landscape model that considers evolution through a discrete sequence space. The model allows the ruggedness of a landscape to be varied from very rugged (many local optima) to very smooth (one optimum) by changing one parameter.

Hardy–Weinberg equilibrium

A state in which the frequency of each diploid genotype at a locus equals that expected from the random union of alleles (genotypes AA, Aa and aa will be at frequencies p2, 2pq and q2, respectively). These expectations are based on a stable population undergoing random mating in the absence of selection, new mutations and migration.

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Orr, H. Fitness and its role in evolutionary genetics. Nat Rev Genet 10, 531–539 (2009). https://doi.org/10.1038/nrg2603

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