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Mutational effects and the evolution of new protein functions

Nature Reviews Genetics volume 11, pages 572–582 (2010)Cite this article

Subjects

Key Points

  • The divergence of new genes and proteins occurs through mutations that modulate protein function. The effects of these mutations are pleiotropic, thus imposing trade-offs between selection pressures for the existing function and the newly evolving one and among the protein's activity, stability and dosage.

  • Various compensatory and buffering mechanisms, such as gene duplication, upregulation of expression, stabilizing mutations and chaperone folding assistance, can alleviate these trade-offs and so facilitate functional divergence.

  • Despite buffering effects, the fitness distribution of mutations at the protein level, and for whole organisms, is such that most of the mutations are either neutral or deleterious. This results in the rapid and irreversible non-functionalization of proteins that accumulate mutations under no selection.

  • The distribution of fitness effects of mutations for whole organisms is comparable, and possibly even more deleterious, than that of protein mutations.

  • Duplication underlies the divergence of new genes and proteins. Duplication is almost as frequent as point mutations and is a common mechanism for resolving the trade-off conflicts that arise owing to parallel selection pressures. These pressures may regard the existing and the new function and maintenance of the protein's structural stability.

  • Duplication, and the emergence of new genes and proteins, may occur at different stages of the divergence process. The selection pressures that act on the gene and its duplicate may differ, giving rise to different mechanisms of divergence. These mechanisms are described under three schematic models — Ohno's model, the 'divergence before duplication' (DPD) model and the sub-functionalization model.

  • In Ohno's model of divergence, duplication is a neutral event. The duplicated copy of the protein drifts under no selection until a new function becomes under selection. The downside of this model is that under no selection, non-functionalization of the drifting protein is inevitable. Its advantage is that divergence is independent of trade-offs between the new and existing functions.

  • The DPD model is based on a 'generalist' intermediate that confers a selectable degree of both the new and existing functions. Duplication occurs after the acquisition of a new function, and occurs under positive selection to increase protein dosage and/or alleviate trade-offs that make the acquisition of new function depend on loss of the existing one.

  • The sub-functionalization model combines elements of the DPD model and Ohno's model. Duplication is initially a neutral event, but once mutations that partially reduce protein activity or dosage appear, both copies must remain functional. Duplication therefore enables a larger genetic variability to accumulate, thereby facilitating the emergence of new functions.

  • The DPD and sub-functionalization models are both based on mutations with adaptive potential initially accumulating as neutral. As such, they are related to the notions of hidden or apparently neutral variation and of neutral networks.

Abstract

The divergence of new genes and proteins occurs through mutations that modulate protein function. However, mutations are pleiotropic and can have different effects on organismal fitness depending on the environment, as well as opposite effects on protein function and dosage. We review the pleiotropic effects of mutations. We discuss how they affect the evolution of gene and protein function, and how these complex mutational effects dictate the likelihood and mechanism of gene duplication and divergence. We propose several factors that can affect the divergence of new protein functions, including mutational trade-offs and hidden, or apparently neutral, variation.

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Figure 1: Rapid fitness declines result in increased likelihood of a new function emerging under selection for the existing one.
Figure 2: Protein fitness and mutational trade-offs.
Figure 3: Divergence of protein-coding genes.
Figure 4: Divergent evolution via gene duplication.

References

  1. Conant, G. C. & Wolfe, K. H. Turning a hobby into a job: how duplicated genes find new functions. Nature Rev. Genet. 9, 938–950 (2008).

    CAS  PubMed  Google Scholar 

  2. Innan, H. & Kondrashov, F. The evolution of gene duplications: classifying and distinguishing between models. Nature Rev. Genet. 11, 97–108 (2010).

    CAS  PubMed  Google Scholar 

  3. 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 

  4. Pal, C., Papp, B. & Lercher, M. J. An integrated view of protein evolution. Nature Rev. Genet. 7, 337–348 (2006).

    CAS  PubMed  Google Scholar 

  5. 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 

  6. Tokuriki, N. & Tawfik, D. S. Stability effects of mutations and protein evolvability. Curr. Opin. Struct. Biol. 19, 596–604 (2009).

    CAS  PubMed  Google Scholar 

  7. Eyre-Walker, A. & Keightley, P. D. The distribution of fitness effects of new mutations. Nature Rev. Genet. 8, 610–618 (2007).

    CAS  PubMed  Google Scholar 

  8. Camps, M., Herman, A., Loh, E. & Loeb, L. A. Genetic constraints on protein evolution. Crit. Rev. Biochem. Mol. Biol. 42, 313–326 (2007).

    CAS  PubMed  Google Scholar 

  9. 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 

  10. 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 

  11. Bershtein, S. & Tawfik, D. S. Ohno's model revisited: measuring the frequency of potentially adaptive mutations under various mutational drifts. Mol. Biol. Evol. 25, 2311–2318 (2008).

    CAS  PubMed  Google Scholar 

  12. Hecky, J. & Muller, K. M. Structural perturbation and compensation by directed evolution at physiological temperature leads to thermostabilization of β-lactamase. Biochemistry 44, 12640–12654 (2005).

    CAS  PubMed  Google Scholar 

  13. Yue, P. & Moult, J. Identification and analysis of deleterious human SNPs. J. Mol. Biol. 356, 1263–1274 (2006).

    CAS  PubMed  Google Scholar 

  14. Tokuriki, N., Oldfield, C. J., Uversky, V. N., Berezovsky, I. N. & Tawfik, D. S. Do viral proteins possess unique biophysical features? Trends Biochem. Sci. 34, 53–59 (2009).

    CAS  PubMed  Google Scholar 

  15. Wang, X., Minasov, G. & Shoichet, B. K. Evolution of an antibiotic resistance enzyme constrained by stability and activity trade-offs. J. Mol. Biol. 320, 85–95 (2002).

    CAS  PubMed  Google Scholar 

  16. Tokuriki, N., Stricher, F., Serrano, L. & Tawfik, D. S. How protein stability and new functions trade off. PLoS Comput. Biol. 4, e1000002 (2008).

    PubMed  PubMed Central  Google Scholar 

  17. Levin, K. B. et al. Following evolutionary paths to protein–protein interactions with high affinity and selectivity. Nature Struct. Mol. Biol. 16, 1049–1055 (2009).

    CAS  Google Scholar 

  18. Lindner, A. B., Madden, R., Demarez, A., Stewart, E. J. & Taddei, F. Asymmetric segregation of protein aggregates is associated with cellular aging and rejuvenation. Proc. Natl Acad. Sci. USA 105, 3076–3081 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. McLoughlin, S. Y. & Copley, S. D. A compromise required by gene sharing enables survival: implications for evolution of new enzyme activities. Proc. Natl Acad. Sci. USA 105, 13497–13502 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Vick, J. E., Schmidt, D. M. & Gerlt, J. A. Evolutionary potential of (β/α)8-barrels: in vitro enhancement of a 'new' reaction in the enolase superfamily. Biochemistry 44, 11722–11729 (2005).

    CAS  PubMed  Google Scholar 

  21. Khersonsky, O. & Tawfik, D. S. Enzyme promiscuity: a mechanistic and evolurtionary perpective. Ann. Rev. Biochem. 79, 471–505 (2010).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  23. Tokuriki, N. & Tawfik, D. S. Protein dynamism and evolvability. Science 324, 203–207 (2009).

    CAS  PubMed  Google Scholar 

  24. Scannell, D. R. & Wolfe, K. H. A burst of protein sequence evolution and a prolonged period of asymmetric evolution follow gene duplication in yeast. Genome Res. 18, 137–147 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Kaessmann, H. Genetics. More than just a copy. Science 325, 958–959 (2009).

    PubMed  Google Scholar 

  26. Parker, H. G. et al. An expressed fgf4 retrogene is associated with breed-defining chondrodysplasia in domestic dogs. Science 325, 995–998 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Andersson, D. I. & Hughes, D. Gene amplification and adaptive evolution in bacteria. Annu. Rev. Genet. 43, 167–195 (2009).

    CAS  PubMed  Google Scholar 

  28. Schimke, R. T. Gene amplification in cultured cells. J. Biol. Chem. 263, 5989–5992 (1988).

    CAS  PubMed  Google Scholar 

  29. Papp, B., Pal, C. & Hurst, L. D. Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast. Nature 429, 661–664 (2004).

    CAS  PubMed  Google Scholar 

  30. Perry, G. H. et al. Diet and the evolution of human amylase gene copy number variation. Nature Genet. 39, 1256–1260 (2007).

    CAS  PubMed  Google Scholar 

  31. Fablet, M., Bueno, M., Potrzebowski, L. & Kaessmann, H. Evolutionary origin and functions of retrogene introns. Mol. Biol. Evol. 26, 2147–2156 (2009).

    CAS  PubMed  Google Scholar 

  32. Jablonka, E. & Lamb, M. J. Epigenetic Inheritance and Evolution: The Lamarckian Dimension (Oxford Univ. Press, Oxford, UK, 1995).

    Google Scholar 

  33. Steele, E. J., Lindley, R. A. & Blanden, R. V. Lamarck's Signature: How Retrogenes Are Changing Darwin's Natural Selection Paradigm, (Allen & Unwin; Perseus Books, Australia, 1988).

    Google Scholar 

  34. Chen, G. K. et al. Preferential expression of a mutant allele of the amplified MDR1 (ABCB1) gene in drug-resistant variants of a human sarcoma. Genes Chromosomes Cancer 34, 372–383 (2002).

    PubMed  Google Scholar 

  35. Qian, W. & Zhang, J. Gene dosage and gene duplicability. Genetics 179, 2319–2324 (2008).

    PubMed  PubMed Central  Google Scholar 

  36. Goldsmith, M. & Tawfik, D. S. Potential role of phenotypic mutations in the evolution of protein expression and stability. Proc. Natl Acad. Sci. USA 106, 6197–6202 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Siu, L. K., Ho, P. L., Yuen, K. Y., Wong, S. S. & Chau, P. Y. Transferable hyperproduction of TEM-1 β-lactamase in Shigella flexneri due to a point mutation in the pribnow box. Antimicrob. Agents Chemother. 41, 468–470 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Hall, B. G. Evolution of a regulated operon in the laboratory. Genetics 101, 335–344 (1982).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Hall, B. G. The EBG system of E. coli: origin and evolution of a novel β-galactosidase for the metabolism of lactose. Genetica 118, 143–156 (2003).

    CAS  PubMed  Google Scholar 

  40. Stoebel, D. M., Dean, A. M. & Dykhuizen, D. E. The cost of expression of Escherichia coli lac operon proteins is in the process, not in the products. Genetics 178, 1653–1660 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Wagner, A. Energy constraints on the evolution of gene expression. Mol. Biol. Evol. 22, 1365–1374 (2005).

    CAS  PubMed  Google Scholar 

  42. Vavouri, T., Semple, J. I., Garcia-Verdugo, R. & Lehner, B. Intrinsic protein disorder and interaction promiscuity are widely associated with dosage sensitivity. Cell 138, 198–208 (2009).

    CAS  PubMed  Google Scholar 

  43. Veitia, R. A. Gene dosage balance: deletions, duplications and dominance. Trends Genet. 21, 33–35 (2005).

    CAS  PubMed  Google Scholar 

  44. Drummond, D. A., Bloom, J. D., Adami, C., Wilke, C. O. & Arnold, F. H. Why highly expressed proteins evolve slowly. Proc. Natl Acad. Sci. USA 102, 14338–14343 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Fares, M. A., Ruiz- González, M. X., Moya, A., Elena, S. F. & Barrio, E. Endosymbiotic bacteria: GroEL buffers against deleterious mutations. Nature 417, 398 (2002).

    CAS  PubMed  Google Scholar 

  46. Rutherford, S., Hirate, Y. & Swalla, B. J. The Hsp90 capacitor, developmental remodeling, and evolution: the robustness of gene networks and the curious evolvability of metamorphosis. Crit. Rev. Biochem. Mol. Biol. 42, 355–372 (2007).

    CAS  PubMed  Google Scholar 

  47. Cowen, L. E. & Lindquist, S. Hsp90 potentiates the rapid evolution of new traits: drug resistance in diverse fungi. Science 309, 2185–2189 (2005).

    CAS  PubMed  Google Scholar 

  48. Parent, K. N., Ranaghan, M. J. & Teschke, C. M. A second-site suppressor of a folding defect functions via interactions with a chaperone network to improve folding and assembly in vivo. Mol. Microbiol. 54, 1036–1050 (2004).

    CAS  PubMed  Google Scholar 

  49. Tokuriki, N. & Tawfik, D. S. Chaperonin overexpression promotes genetic variation and enzyme evolution. Nature 459, 668–673 (2009).

    CAS  PubMed  Google Scholar 

  50. Zhang, L. & Watson, L. T. Analysis of the fitness effect of compensatory mutations. HFSP J. 3, 47–54 (2009).

    PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  52. Hecky, J., Mason, J. M., Arndt, K. M. & Muller, K. M. A general method of terminal truncation, evolution, and re-elongation to generate enzymes of enhanced stability. Methods Mol. Biol. 352, 275–304 (2007).

    CAS  PubMed  Google Scholar 

  53. Kather, I., Jakob, R. P., Dobbek, H. & Schmid, F. X. Increased folding stability of TEM-1 β-lactamase by in vitro selection. J. Mol. Biol. 383, 238–251 (2008).

    CAS  PubMed  Google Scholar 

  54. Marciano, D. C. et al. Genetic and structural characterization of an L201P global suppressor substitution in TEM-1 β-lactamase. J. Mol. Biol. 384, 151–164 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Kimura, M. The role of compensatory neutral mutations in molecular evolution. J. Genet. 64, 7–19 (1985).

    CAS  Google Scholar 

  56. 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 

  57. McIntosh, B. E., Hogenesch, J. B. & Bradfield, C. A. Mammalian Per-Arnt-Sim proteins in environmental adaptation. Annu. Rev. Physiol. 72, 625–645 (2010).

    CAS  PubMed  Google Scholar 

  58. Lynch, M. Genomics. Gene duplication and evolution. Science 297, 945–947 (2002).

    CAS  PubMed  Google Scholar 

  59. Beckmann, J. S., Estivill, X. & Antonarakis, S. E. Copy number variants and genetic traits: closer to the resolution of phenotypic to genotypic variability. Nature Rev. Genet. 8, 639–646 (2007).

    CAS  PubMed  Google Scholar 

  60. Hastings, P. J., Lupski, J. R., Rosenberg, S. M. & Ira, G. Mechanisms of change in gene copy number. Nature Rev. Genet. 10, 551–564 (2009).

    CAS  PubMed  Google Scholar 

  61. Liao, B. Y. & Zhang, J. Null mutations in human and mouse orthologs frequently result in different phenotypes. Proc. Natl Acad. Sci. USA 105, 6987–6992 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Ohno, S. Evolution by Gene Duplication (Allen & Unwin; Springer, New York, 1970).

    Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Zhang, J. Evolution by gene duplication: an update. Trends Ecol. Evol. 18, 292–298 (2003).

    Google Scholar 

  65. Hughes, A. L. Adaptive evolution after gene duplication. Trends Genet. 18, 433–434 (2002).

    CAS  PubMed  Google Scholar 

  66. Lynch, M. & Katju, V. The altered evolutionary trajectories of gene duplicates. Trends Genet. 20, 544–549 (2004).

    CAS  PubMed  Google Scholar 

  67. Kondrashov, F. A. & Koonin, E. V. A common framework for understanding the origin of genetic dominance and evolutionary fates of gene duplications. Trends Genet. 20, 287–290 (2004).

    CAS  PubMed  Google Scholar 

  68. Bergthorsson, U., Andersson, D. I. & Roth, J. R. Ohno's dilemma: evolution of new genes under continuous selection. Proc. Natl Acad. Sci. USA 104, 17004–17009 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Kondrashov, F. A. In search of the limits of evolution. Nature Genet. 37, 9–10 (2005).

    CAS  PubMed  Google Scholar 

  70. Boehr, D. D., Nussinov, R. & Wright, P. E. The role of dynamic conformational ensembles in biomolecular recognition. Nature Chem. Biol. 5, 789–796 (2009).

    CAS  Google Scholar 

  71. Piatigorsky, J. et al. Gene sharing by D-crystallin and argininosuccinate lyase. Proc. Natl Acad. Sci. USA 85, 3479–3483 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Piatigorsky, J. Gene Sharing and Evolution: The Diversity of Protein Functions, (Harvard Univ. Press, Cambridge, Massachusetts, USA; London, UK, 2007).

    Google Scholar 

  73. Lee, Y. N., Nechushtan, H., Figov, N. & Razin, E. The function of lysyl-tRNA synthetase and Ap4A as signaling regulators of MITF activity in FceRI-activated mast cells. Immunity 20, 145–151 (2004).

    CAS  PubMed  Google Scholar 

  74. Sedlak, T. W. & Snyder, S. H. Messenger molecules and cell death: therapeutic implications. JAMA 295, 81–89 (2006).

    CAS  PubMed  Google Scholar 

  75. Rosenberg, H. F. RNase A ribonucleases and host defense: an evolving story. J. Leukoc. Biol. 83, 1079–1087 (2008).

    CAS  PubMed  Google Scholar 

  76. Jensen, R. A. Enzyme recruitment in evolution of new function. Annu. Rev. Microbiol. 30, 409–425 (1974).

    Google Scholar 

  77. O'Brien, P. J. & Herschlag, D. Catalytic promiscuity and the evolution of new enzymatic activities. Chem. Biol. 6, R91–R105 (1999).

    CAS  PubMed  Google Scholar 

  78. Palmer, D. R. et al. Unexpected divergence of enzyme function and sequence: 'N-acylamino acid racemase' is o-succinylbenzoate synthase. Biochemistry 38, 4252–4258 (1999).

    CAS  PubMed  Google Scholar 

  79. James, L. C. & Tawfik, D. S. Catalytic and binding poly-reactivities shared by two unrelated proteins: the potential role of promiscuity in enzyme evolution. Protein Sci. 10, 2600–2607 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Afriat, L., Roodveldt, C., Manco, G. & Tawfik, D. S. The latent promiscuity of newly identified microbial lactonases is linked to a recently diverged phosphotriesterase. Biochemistry 45, 13677–13686 (2006).

    CAS  PubMed  Google Scholar 

  81. Copley, S. D. Evolution of efficient pathways for degradation of anthropogenic chemicals. Nature Chem. Biol. 5, 559–566 (2009).

    CAS  Google Scholar 

  82. Copley, S. D. Comprehensive Natural Products II: Chemistry and Biology (eds Mander, L. & Liu, H.-W.) (Elsevier, Oxford, 2010).

    Google Scholar 

  83. Hughes, A. L. The evolution of functionally novel proteins after gene duplication. Proc. Biol. Sci. 256, 119–124 (1994).

    CAS  PubMed  Google Scholar 

  84. Barkman, T. & Zhang, J. Evidence for escape from adaptive conflict? Nature 462, e1; discussion e2–e3 (2009).

    CAS  PubMed  Google Scholar 

  85. Des Marais, D. L. & Rausher, M. D. Escape from adaptive conflict after duplication in an anthocyanin pathway gene. Nature 454, 762–765 (2008).

    CAS  PubMed  Google Scholar 

  86. Lynch, M. & Force, A. The probability of duplicate gene preservation by subfunctionalization. Genetics 154, 459–473 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Dykhuizen, D. & Hartl, D. L. Selective neutrality of 6PGD allozymes in E. coli and the effects of genetic background. Genetics 96, 801–817 (1980).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Force, A. et al. Preservation of duplicate genes by complementary, degenerative mutations. Genetics 151, 1531–1545 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Nei, M. The new mutation theory of phenotypic evolution. Proc. Natl Acad. Sci. USA 104, 12235–12242 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Wagner, A. Robustness and Evolvability in Living Systems (Princeton Univ. Press, Princeton, USA, 2005).

    Google Scholar 

  91. Schuster, P. & Fontana, W. Chance and necessity in evolution: lessons from RNA. Physica D 133, 427–452 (1999).

    CAS  Google Scholar 

  92. Wroe, R., Chan, H. S. & Bornberg-Bauer, E. A structural model of latent evolutionary potentials underlying neutral networks in proteins. HFSP J. 1, 79–87 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. Klassen, J. L. Pathway evolution by horizontal transfer and positive selection is accommodated by relaxed negative selection upon upstream pathway genes in purple bacterial carotenoid biosynthesis. J. Bacteriol. 191, 7500–7508 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Wloch, D. M., Szafraniec, K., Borts, R. H. & Korona, R. Direct estimate of the mutation rate and the distribution of fitness effects in the yeast Saccharomyces cerevisiae. Genetics 159, 441–452 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Kivisaar, M. Degradation of nitroaromatic compounds: a model to study evolution of metabolic pathways. Mol. Microbiol. 74, 777–781 (2009).

    CAS  PubMed  Google Scholar 

  96. Wackett, L. P. Questioning our perceptions about evolution of biodegradative enzymes. Curr. Opin. Microbiol. 12, 244–251 (2009).

    CAS  PubMed  Google Scholar 

  97. Newcomb, R. D., Gleeson, D. M., Yong, C. G., Russell, R. J. & Oakeshott, J. G. Multiple mutations and gene duplications conferring organophosphorus insecticide resistance have been selected at the Rop-1 locus of the sheep blowfly, Lucilia cuprina. J. Mol. Evol. 60, 207–220 (2005).

    CAS  PubMed  Google Scholar 

  98. Patzoldt, W. L., Hager, A. G., McCormick, J. S. & Tranel, P. J. A codon deletion confers resistance to herbicides inhibiting protoporphyrinogen oxidase. Proc. Natl Acad. Sci. USA 103, 12329–12334 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. O'Maille, P. E. et al. Quantitative exploration of the catalytic landscape separating divergent plant sesquiterpene synthases. Nature Chem. Biol. 4, 617–623 (2008).

    CAS  Google Scholar 

  100. Lozovsky, E. R. et al. Stepwise acquisition of pyrimethamine resistance in the malaria parasite. Proc. Natl Acad. Sci. USA 106, 12025–12030 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  101. Poelwijk, F. J., Kiviet, D. J., Weinreich, D. M. & Tans, S. J. Empirical fitness landscapes reveal accessible evolutionary paths. Nature 445, 383–386 (2007).

    CAS  PubMed  Google Scholar 

  102. 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 

  103. 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 

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Acknowledgements

D.S.T. is the incumbent of the Nella and Leon Benoziyo Professorial Chair. Financial support from the Meil de Botton Aynsley and the EU network BioModularH2 are gratefully acknowledged. We are very grateful to S. Bershtein, N. Tokuriki, F. Kondrashov and J. G. Zhang for their insightful comments regarding this manuscript and to A. Eyre-Walker for providing the data for the figure in Box 1.

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  1. Department of Biological Chemistry, Weizmann Institute of Science, Rehovot, 76100, Israel

    Misha Soskine & Dan S. Tawfik

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  1. Misha Soskine
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Correspondence to Dan S. Tawfik.

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Glossary

Protein mutations

Missense mutations that occur in encoded open reading frames.

Trade-offs

Gains of a new activity or property at the expense of other activities or properties.

Protein stability

The capacity of a protein to adopt its native, functional structure. Stability also correlates with cellular protein levels.

Sub-functionalization

Degenerate mutations that result in a gene and its duplicated copy sharing the burden of one function.

Negative epistasis

The combined effect of mutations being more deleterious than expected from their individual effects.

Protein fitness

Levels of physiological function exerted by a given protein variant under a certain selection pressure.

Non-functionalization

The complete inactivation of a gene or protein by highly deleterious mutations.

Neo-functionalization

The divergence of a duplicated gene or protein to execute a new function.

ΔΔG

The stability difference for a protein variant versus its wild-type reference (ΔΔG > 0 indicates lower stability).

Disordered domains

Protein domains with a high degree of random coil and loop regions and a low degree of highly ordered secondary structure.

Apparently neutral mutations

Mutations that have no significant or observable fitness effect under a given environment.

New-function mutations

Mutations that mediate changes in protein activity, typically by increasing a weak, latent promiscuous function.

New–existing function trade-offs

The acquisition of a new function through mutations that undermine the existing function.

Chaperones

Proteins that mediate the correct folding and assembly of other proteins.

Specialists

Genes or proteins that exert one specific function with high proficiency.

Generalist

A gene or protein that exerts multiple functions, typically one primary function and additional secondary or promiscuous functions.

New-function–stability trade-offs

Mutations that increase the new, evolving function but reduce protein stability and protein dosage.

Productive variation

Genetic variation that does not compromise fitness in the dwelling environment but holds the potential for adaptation to new environments.

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Soskine, M., Tawfik, D. Mutational effects and the evolution of new protein functions. Nat Rev Genet 11, 572–582 (2010). https://doi.org/10.1038/nrg2808

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