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Neutralism and selectionism: a network-based reconciliation

Abstract

Neutralism and selectionism are extremes of an explanatory spectrum for understanding patterns of molecular evolution and the emergence of evolutionary innovation. Although recent genome-scale data from protein-coding genes argue against neutralism, molecular engineering and protein evolution data argue that neutral mutations and mutational robustness are important for evolutionary innovation. Here I propose a reconciliation in which neutral mutations prepare the ground for later evolutionary adaptation. Key to this perspective is an explicit understanding of molecular phenotypes that has only become accessible in recent years.

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Figure 1: Protein structures that are highly robust to mutations evolve greater functional enzymatic diversity.
Figure 2: Robust phenotypes can lead to a rapid yet neutral exploration of sequence space.
Figure 3: Cycles of neutral evolution and positive selection through traversal of multiple networks in adaptive evolution.
Figure 4: Neutrality of mutations depends on the order in which the mutations occur.
Figure 5: Positive selection acts episodically on different codons in the envelope protein of HIV.

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Armand M. Leroi, Ben Lambert, … Giorgos D. Kokkoris

References

  1. Kimura, M. The Neutral Theory of Molecular Evolution (Cambridge Univ. Press, Cambridge, 1983).

    Book  Google Scholar 

  2. Kimura, M. & Ohta, T. On some principles governing molecular evolution. Proc. Natl Acad. Sci. USA 71, 2848–2852 (1974).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Mayr, E. Animal Species and Evolution (Belknap, Cambridge, Massachusetts, 1963).

    Google Scholar 

  4. Kreitman, M. The neutral theory is dead: long live the neutral theory. Bioessays 18, 678–683 (1996).

    CAS  PubMed  Google Scholar 

  5. Ohta, T. The current significance and standing of neutral and nearly neutral theories. Bioessays 18, 673–684 (1996).

    CAS  PubMed  Google Scholar 

  6. Nei, M. Selectionism and neutralism in molecular evolution. Mol. Biol. Evol. 22, 2318–2342 (2005).

    CAS  PubMed  Google Scholar 

  7. Lynch, M. The Origins of Genome Architecture (Sinauer, Sunderland, Massachusetts, 2007).

    Google Scholar 

  8. McDonald, J. H. & Kreitman, M. Adaptive protein evolution at the Adh locus in Drosophila. Nature 351, 652–654 (1991).

    CAS  PubMed  Google Scholar 

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

    Google Scholar 

  10. Akashi, H. Inferring weak selection from patterns of polymorphism and divergence at silent sites in Drosophila DNA. Genetics 139, 1067–1076 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Fay, J. C., Wyckoff, G. J. & Wu, C. I. Testing the neutral theory of molecular evolution with genomic data from Drosophila. Nature 415, 1024–1026 (2002).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  13. Bierne, N. & Eyre-Walker, A. The genomic rate of adaptive amino acid substitution in Drosophila. Mol. Biol. Evol. 21, 1350–1360 (2004).

    CAS  PubMed  Google Scholar 

  14. Sawyer, S. A., Kulathinal, R. J., Bustamante, C. D. & Hartl, D. L. Bayesian analysis suggests that most amino acid replacements in Drosophila are driven by positive selection. J. Mol. Evol. 57, S154–S164 (2003).

    CAS  PubMed  Google Scholar 

  15. Shapiro, J. A. et al. Adaptive genic evolution in the Drosophila genomes. Proc. Natl Acad. Sci. USA 104, 2271–2276 (2007).

    PubMed  PubMed Central  Google Scholar 

  16. Andolfatto, P. Hitchhiking effects of recurrent beneficial amino acid substitutions in the Drosophila melanogaster genome. Genome Res. 17, 1755–1762 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Begun, D. J. et al. Population genomics: whole-genome analysis of polymorphism and divergence in Drosophila simulans. PloS Biol. 5, 2534–2559 (2007).

    CAS  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  19. Kohn, M. H., Fang, S. & Wu, C. I. Inference of positive and negative selection on the 5′ regulatory regions of Drosophila genes. Mol. Biol. Evol. 21, 374–383 (2004).

    CAS  PubMed  Google Scholar 

  20. Charlesworth, J. & Eyre-Walker, A. The rate of adaptive evolution in enteric bacteria. Mol. Biol. Evol. 23, 1348–1356 (2006).

    CAS  PubMed  Google Scholar 

  21. Akashi, H. Inferring the fitness effects of DNA mutations from polymorphism and divergence data: statistical power to detect directional selection under stationarity and free recombination. Genetics 151, 221–238 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  23. Gillespie, J. H. Is the population size of a species relevant to its evolution? Evolution 55, 2161–2169 (2001).

    CAS  PubMed  Google Scholar 

  24. Maynard Smith, J. & Haigh, J. The hitch-hiking effect of a favorable gene. Genet. Res. 23, 23–35 (1974).

    Google Scholar 

  25. Schultes, E. & Bartel, D. One sequence, two ribozymes: implications for the emergence of new ribozyme folds. Science 289, 448–452 (2000).

    CAS  PubMed  Google Scholar 

  26. Smith, D. J. et al. Mapping the antigenic and genetic evolution of influenza virus. Science 305, 371–376 (2004).

    CAS  PubMed  Google Scholar 

  27. Koelle, K., Cobey, S., Grenfell, B. & Pascual, M. Epochal evolution shapes the phylodynamics of interpandemic influenza A (H3N2) in humans. Science 314, 1898–1903 (2006).

    CAS  PubMed  Google Scholar 

  28. Bloom, J. D., Labthavikul, S. T., Otey, C. R. & Arnold, F. H. Protein stability promotes evolvability. Proc. Natl Acad. Sci. USA 103, 5869–5874 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Aharoni, A. et al. The 'evolvability' of promiscuous protein functions. Nature Genet. 37, 73–76 (2005).

    CAS  PubMed  Google Scholar 

  30. Bloom, J., Romero, P., Lu, Z. & Arnold, F. Neutral genetic drift can alter promiscuous protein functions, potentially aiding functional evolution. Biol. Direct 2, 17 (2007).

    PubMed  PubMed Central  Google Scholar 

  31. Amitai, G., Gupta, R. & Tawfik, D. Latent evolutionary potentials under the neutral mutational drift of an enzyme HFSP J. 1, 67–78 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Bloom, J. D. et al. Thermodynamic prediction of protein neutrality. Proc. Natl Acad. Sci. USA 102, 606–611 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. England, J. L. & Shakhnovich, E. I. Structural determinant of protein designability. Phys. Rev. Lett. 90, 218101 (2003).

    PubMed  Google Scholar 

  34. Ferrada, E. & Wagner, A. Protein robustness promotes evolutionary innovations on large evolutionary time scales. Proc. Roy. Soc. Lond. B. 275, 1595–1602 (2008).

    CAS  Google Scholar 

  35. Shakhnovich, B. E., Deeds, E., Delisi, C. & Shakhnovich, E. Protein structure and evolutionary history determine sequence space topology. Genome Res. 15, 385–392 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Ginsberg, A. M., King, B. O. & Roeder, R. G. Xenopus 5S gene transcription factor, TFIIIA: characterization of a cDNA clone and measurement of RNA levels throughout development. Cell 39, 479–489 (1984).

    CAS  PubMed  Google Scholar 

  37. Michael, S. F., Kilfoil, V. J., Schmidt, M. H., Amann, B. T. & Berg, J. M. Metal binding and folding properties of a minimalist Cys2His2 Zinc finger peptide. Proc. Natl Acad. Sci. USA 89, 4796–4800 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Durai, S. et al. Zinc finger nucleases: custom-designed molecular scissors for genome engineering of plant and mammalian cells. Nucleic Acids Res. 33, 5978–5990 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Venter, J. C. et al. The sequence of the human genome. Science 291, 1304–1351 (2001).

    CAS  PubMed  Google Scholar 

  40. Lynch, M. & Conery, J. S. The evolutionary fate and consequences of duplicate genes. Science 290, 1151–1155 (2000).

    CAS  PubMed  Google Scholar 

  41. Gu, Z. L., Cavalcanti, A., Chen, F. C., Bouman, P. & Li, W. H. Extent of gene duplication in the genomes of Drosophila, nematode, and yeast. Mol. Biol. Evol. 19, 256–262 (2002).

    CAS  PubMed  Google Scholar 

  42. Irish, V. F. & Litt, A. Flower development and evolution: gene duplication, diversification and redeployment. Curr. Opin. Genet. Dev. 15, 454–460 (2005).

    CAS  PubMed  Google Scholar 

  43. Lemons, D. & McGinnis, W. Genomic evolution of Hox gene clusters. Science 313, 1918–1922 (2006).

    CAS  PubMed  Google Scholar 

  44. Olson, E. Gene regulatory networks in the evolution and development of the heart. Science 313, 1922–1927 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Wagner, A. Gene duplications, robustness, and evolutionary innovations. Bioessays 30, 367–373 (2008).

    CAS  PubMed  Google Scholar 

  46. Ohno, S. Evolution by Gene Duplication (Springer, New York, 1970).

    Google Scholar 

  47. Ciliberti, S., Martin, O. C. & Wagner, A. Circuit topology and the evolution of robustness in complex regulatory gene networks. PloS Comput. Biol. 3, e15 (2007).

    PubMed  PubMed Central  Google Scholar 

  48. Isalan, M. et al. Evolvability and hierarchy in rewired bacterial gene networks. Nature 452, 840–845 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Tsong, A. E., Tuch, B. B., Li, H. & Johnson, A. D. Evolution of alternative transcriptional circuits with identical logic. Nature 443, 415–420 (2006).

    CAS  PubMed  Google Scholar 

  50. Wagner, A. Robustness and evolvability: a paradox resolved. Proc. Roy. Soc. Lond. B 275, 91–100 (2008).

    Google Scholar 

  51. Sumedha, Martin, O. C. & Wagner, A. New structural variation in evolutionary searches of RNA neutral networks. Biosystems. 90, 475–485. (2007).

    PubMed  Google Scholar 

  52. Huynen, M. Exploring phenotype space through neutral evolution. J. Mol. Evol. 43, 165–169 (1996).

    CAS  PubMed  Google Scholar 

  53. Ciliberti, S., Martin, O. C. & Wagner, A. Innovation and robustness in complex regulatory gene networks Proc. Natl Acad. Sci. USA 104, 13591–13596 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Fontana, W. & Schuster, P. Continuity in evolution: on the nature of transitions. Science 280, 1451–1455 (1998).

    CAS  PubMed  Google Scholar 

  55. Elena, S. F., Cooper, V. S. & Lenski, R. E. Punctuated evolution caused by selection of rare beneficial mutations. Science 272, 1802–1804 (1996).

    CAS  PubMed  Google Scholar 

  56. Cordell, H. J. Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans. Hum. Mol. Genet. 11, 2463–2468 (2002).

    CAS  PubMed  Google Scholar 

  57. Carlborg, O. & Haley, C. S. Epistasis: too often neglected in complex trait studies? Nature Rev. Genet. 5, 618–625 (2004).

    CAS  PubMed  Google Scholar 

  58. Kulathinal, R. J., Bettencourt, B. R. & Hartl, D. L. Compensated deleterious mutations in insect genomes. Science 306, 1553–1554 (2004).

    CAS  PubMed  Google Scholar 

  59. Kern, A. D. & Kondrashov, F. A. Mechanisms and convergence of compensatory evolution in mammalian mitochondrial tRNAs. Nature Genet. 36, 1207–1212 (2004).

    CAS  PubMed  Google Scholar 

  60. Kondrashov, A. S., Sunyaev, S. & Kondrashov, F. A. Dobzhansky–Muller incompatibilities in protein evolution. Proc. Natl Acad. Sci. USA 99, 14878–14883 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Weinreich, D. M., Delaney, N. F., DePristo, M. A. & Hartl, D. L. Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312, 111–114 (2006).

    CAS  PubMed  Google Scholar 

  62. Weinreich, D. M. & Chao, L. Rapid evolutionary escape by large populations from local fitness peaks is likely in nature. Evolution 59, 1175–1182 (2005).

    CAS  PubMed  Google Scholar 

  63. DePristo, M. A., Hartl, D. L. & Weinreich, D. M. Mutational reversions during adaptive protein evolution. Mol. Biol. Evol. 24, 1608–1610 (2007).

    CAS  PubMed  Google Scholar 

  64. Stephan, W. The rate of compensatory evolution. Genetics 144, 419–426 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Takahasi, K. R. & Tajima, F. Evolution of coadaptation in a two-locus epistatic system. Evolution 59, 2324–2332 (2005).

    PubMed  Google Scholar 

  66. Cowperthwaite, M. C., Bull, J. J. & Meyers, L. A. From bad to good: fitness reversals and the ascent of deleterious mutations. PloS Comput. Biol. 2, 1292–1300 (2006).

    CAS  Google Scholar 

  67. Wilke, C. O., Lenski, R. E. & Adami, C. Compensatory mutations cause excess of antagonistic epistasis in RNA secondary structure folding. BMC Evol. Biol. 3, 3 (2003).

    PubMed  PubMed Central  Google Scholar 

  68. Weinreich, D. M., Watson, R. A. & Chao, L. Perspective: sign epistasis and genetic constraint on evolutionary trajectories. Evolution 59, 1165–1174 (2005).

    CAS  PubMed  Google Scholar 

  69. DePristo, M. A., Weinreich, D. M. & Hartl, D. L. Missense meanderings in sequence space: a biophysical view of protein evolution. Nature Rev. Genet. 6, 678–687 (2005).

    CAS  PubMed  Google Scholar 

  70. Tokuriki, N., Stricher, F., Schymkowitz, J., Serrano, L. & Tawfik, D. S. The stability effects of protein mutations appear to be universally distributed. J. Mol. Biol. 369, 1318–1332 (2007).

    CAS  PubMed  Google Scholar 

  71. Bershtein, S., Goldin, K. & Tawfik, D. Intense neutral drifts yield robust and evolvable consensus proteins. J. Mol. Biol. 379, 1029–1044 (2008).

    CAS  PubMed  Google Scholar 

  72. Bridgham, J. T., Carroll, S. M. & Thornton, J. W. Evolution of hormone-receptor complexity by molecular exploitation. Science 312, 97–101 (2006).

    CAS  PubMed  Google Scholar 

  73. Ortlund, E. A., Bridgham, J. T., Redinbo, M. R. & Thornton, J. W. Crystal structure of an ancient protein: evolution by conformational epistasis. Science 317, 1544–1548 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Dean, A. M. & Thornton, J. W. Mechanistic approaches to the study of evolution: the functional synthesis. Nature Rev. Genet. 8, 675–688 (2007).

    CAS  PubMed  Google Scholar 

  75. Bershtein, S., Segal, M., Bekerman, R., Tokuriki, N. & Tawfik, D. S. Robustness–epistasis link shapes the fitness landscape of a randomly drifting protein. Nature 444, 929–932 (2006).

    CAS  PubMed  Google Scholar 

  76. Schilling, C. H. & Palsson, B. O. Assessment of the metabolic capabilities of Haemophilus influenzae Rd through a genome-scale pathway analysis. J. Theor. Biol. 203, 249–283 (2000).

    CAS  PubMed  Google Scholar 

  77. Forster, J., Famili, I., Fu, P., Palsson, B. & Nielsen, J. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res. 13, 244–253 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Edwards, J. S. & Palsson, B. O. Robustness analysis of the Escherichia coli metabolic network. Biotechnol. Prog. 16, 927–939 (2000).

    CAS  PubMed  Google Scholar 

  79. Segre, D., Vitkup, D. & Church, G. Analysis of optimality in natural and perturbed metabolic networks. Proc. Natl Acad. Sci. USA 99, 15112–15117 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Motter, A. E., Gulbahce, N., Almaas, E. & Barabasi, A. L. Predicting synthetic rescues in metabolic networks. Mol. Syst. Biol. 4, 168 (2008).

    PubMed  PubMed Central  Google Scholar 

  81. Goldman, N. & Yang, Z. H. Codon-based model of nucleotide substitution for protein-coding DNA sequences. Mol. Biol. Evol. 11, 725–736 (1994).

    CAS  PubMed  Google Scholar 

  82. Yang, Z. H. & Nielsen, R. Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. Mol. Biol. Evol. 17, 32–43 (2000).

    CAS  PubMed  Google Scholar 

  83. Yang, Z. H. & Nielsen, R. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol. Biol. Evol. 19, 908–917 (2002).

    CAS  PubMed  Google Scholar 

  84. Zhang, J. Z., Nielsen, R. & Yang, Z. H. Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level. Mol. Biol. Evol. 22, 2472–2479 (2005).

    CAS  PubMed  Google Scholar 

  85. Guindon, S., Rodrigo, A. G., Dyer, K. A. & Huelsenbeck, J. P. Modeling the site-specific variation of selection patterns along lineages. Proc. Natl Acad. Sci. USA 101, 12957–12962 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Shankarappa, R. et al. Consistent viral evolutionary changes associated with the progression of human immunodeficiency virus type 1 infection. J. Virol. 73, 10489–10502 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Philippe, H., Casane, D., Gribaldo, S., Lopez, P. & Meunier, J. Heterotachy and functional shift in protein evolution. Iubmb Life 55, 257–265 (2003).

    CAS  PubMed  Google Scholar 

  88. Lopez, P., Casane, D. & Philippe, H. Heterotachy, an important process of protein evolution. Mol. Biol. Evol. 19, 1–7 (2002).

    CAS  PubMed  Google Scholar 

  89. Thatcher, J. W., Shaw, J. M. & Dickinson, W. J. Marginal fitness contributions of nonessential genes in yeast. Proc. Natl Acad. Sci. USA 95, 253–257 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Carter, A. J. R. & Wagner, G. P. Evolution of functionally conserved enhancers can be accelerated in large populations: a population-genetic model. Proc. Roy. Soc. Lond. B 269, 953–960 (2002).

    Google Scholar 

  91. Gavrilets, S. Fitness Landscapes and the Origin of Species (Princeton Univ. Press, Princeton, New Jersey, 2004).

    Google Scholar 

  92. Gavrilets, S. Evolution and speciation on holey adaptive landscapes. Trends Ecol. Evol. 12, 307–312 (1997).

    CAS  PubMed  Google Scholar 

  93. Gould, S. & Vrba, E. Exaptation — a missing term in the science of form. Paleobiology 8, 4–15 (1982).

    Google Scholar 

  94. Provine, W. B. Sewall Wright and Evolutionary Biology (Univ. of Chicago Press, Chicago, Illinois, 1986).

    Google Scholar 

  95. Hartl, D. & Clark, A. Principles of Population Genetics (Sinauer Associates Sunderland, Massachusetts, 2007).

    Google Scholar 

  96. Charlesworth, B., Morgan, M. T. & Charlesworth, D. The effect of deleterious mutations on neutral molecular variation. Genetics 134, 1289–1303 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  97. Lynch, M. & Conery, J. The origins of genome complexity. Science 302, 1401–1404 (2003).

    CAS  PubMed  Google Scholar 

  98. Schuster, P., Fontana, W., Stadler, P. & Hofacker, I. From sequences to shapes and back — a case-study in RNA secondary structures. Proc. Roy. Soc. Lond. B 255, 279–284 (1994).

    CAS  Google Scholar 

  99. Maynard Smith, J. Natural selection and the concept of a protein space. Nature 222, 563–564 (1970).

    Google Scholar 

  100. Babajide, A., Hofacker, I., Sippl, M. & Stadler, P. Neutral networks in protein space: a computational study based on knowledge-based potentials of mean force. Fold. Des. 2, 261–269 (1997).

    CAS  PubMed  Google Scholar 

  101. Li, H., Helling, R., Tang, C. & Wingreen, N. Emergence of preferred structures in a simple model of protein folding. Science 273, 666–669 (1996).

    CAS  PubMed  Google Scholar 

  102. Chan, H. & Bornberg-Bauer, E. Perspectives on protein evolution from simple exact models. Appl. Bioinformatics 1, 121–144 (2003).

    Google Scholar 

  103. Xia, Y. & Levitt, M. Roles of mutation and recombination in the evolution of protein thermodynamics. Proc. Natl Acad. Sci. USA 99, 10382–10387 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  104. Hofacker, I., Schuster, P. & Stadler, P. Combinatorics of RNA secondary structures. Discrete Appl. Math. 88, 207–237 (1998).

    Google Scholar 

  105. Schuster, P. in Evolutionary Dynamics: Exploring the Interplay of Selection, Accident, Neutrality, and Function (eds Crutchfield, J. P. & Schuster, P.) 163–215 (Oxford Univ. Press, New York, 2003).

    Google Scholar 

  106. Reidys, C., Stadler, P. & Schuster, P. Generic properties of combinatory maps: neutral networks of RNA secondary structures. Bull. Math. Biol. 59, 339–397 (1997).

    CAS  PubMed  Google Scholar 

  107. Eigen, M. & Schuster, P. The Hypercycle: a Principle of Natural Self-Organization (Springer, Berlin, 1979).

    Google Scholar 

  108. Pegg, S. C. H. et al. Leveraging enzyme structure–function relationships for functional inference and experimental design: the structure–function linkage database. Biochemistry 45, 2545–2555 (2006).

    CAS  PubMed  Google Scholar 

  109. Wagner, A. Robustness and evolvability: a paradox resolved. Proc. Roy. Soc. Lond. B 275, 91–100 (2008).

    Google Scholar 

  110. Hofacker, I. et al. Fast folding and comparison of RNA secondary structures. Monatsh. Chem. 125, 167–188 (1994).

    CAS  Google Scholar 

  111. Kwong, P. D. et al. Structure of an HIV gp120 envelope glycoprotein in complex with the CD4 receptor and a neutralizing human antibody. Nature 393, 648–659 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

I am grateful to M. Isalan for pointing me to the role of zinc fingers in protein engineering. I would also like to thank S. Guindon for assistance with his software, fitModeL. This work was in part supported by grant 315200-116814 from the Swiss National Science Foundation.

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Glossary

Effective population size

Indicates how many individuals actually contribute alleles to the next generation, as opposed to the actual number of individuals in a population. For various reasons, including the preferential reproduction of some individuals and population size fluctuations over time, the effective population size is typically smaller than the actual number of individuals in the population.

Eigenvalue

For a matrix A and a vector v, an eigenvalue c is a scalar that obeys the equation Av = cv.

Epistasis

The dependency of the effects of a mutation on mutations in other parts of a gene or genome.

Gene ontology

A widely used classification system of gene functions and other gene attributes that uses a controlled vocabulary.

Maximum-likelihood estimation

A statistical method for fitting mathematical models to data. It is widely used to estimate the structure of phylogenetic trees from sequence data.

McDonald–Kreitman test

A statistical test that can detect positive selection based on intra- and interpopulation divergence of nucleotide changes in proteins.

Molecular phenotype

A phenotype is any observable trait or feature of an organism other than the DNA itself (that is, the genotype). Molecular features, such as the structure of a particular proteins, are molecular phenotypes.

Mutational walk

A series of small mutational changes in sequence space.

Positive selection

Also known as directional selection. A process by which natural selection favours a single beneficial genotype over other genotypes and may drive this genotype to a high frequency in a population.

Selection coefficient

The fitness difference of a genotype compared with the wild-type genotype.

Selective sweep

When a mutation with beneficial fitness effects arises in a population, natural selection may drive or sweep this mutation to a high frequency or to fixation (a frequency of 100%) within a short amount of time.

Sequence space

All DNA, RNA or amino-acid sequences of a given length, that is, a given number of monomers.

Zinc-finger domain

A protein domain in which a zinc ion is bound to two conserved cysteine and histidine residues, an interaction that stabilizes the structure of the domain.

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Wagner, A. Neutralism and selectionism: a network-based reconciliation. Nat Rev Genet 9, 965–974 (2008). https://doi.org/10.1038/nrg2473

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