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The population genetics and evolutionary epidemiology of RNA viruses

Nature Reviews Microbiology volume 2, pages 279–288 (2004)Cite this article

Key Points

  • The authors discuss the main mechanisms of RNA virus evolution — mutation, recombination, natural selection, genetic drift and migration, and how these interact to shape the genetic structure of populations.

  • The quasispecies model of RNA virus evolution is explained and the question of whether this model provides an accurate description of RNA virus evolution is discussed.

  • Experiments that can be carried out to test the basic principles of evolutionary theory are briefly described. The authors review what such experiments have told us about virus evolution and, more widely, what these experiments have revealed in terms of general evolutionary principles.

  • RNA viruses evolve quickly, so a detailed reconstruction of their epidemiological history can be undertaken. The authors show how epidemiological patterns of viruses result from their evolution at two different levels: within individual hosts (and vectors) and among hosts at the population level.

  • Using several examples, including HIV and SARS, the authors describe how studying RNA virus evolution could be used to understand virus emergence.

  • Finally, the important topics of the evolution of virulence and resistance to drugs are discussed.

Abstract

RNA viruses are ubiquitous intracellular parasites that are responsible for many emerging diseases, including AIDS and SARS. Here, we discuss the principal mechanisms of RNA virus evolution and highlight areas where future research is required. The rapidity of sequence change in RNA viruses means that they are useful experimental models for the study of evolution in general and it enables us to watch them change in 'real time', and retrace the spread through populations with molecular phylogenies. An understanding of the mechanisms of RNA virus sequence change is also crucial to predicting important aspects of their emergence and long-term evolution.

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Figure 1: Two alternative epidemiological scenarios translate into different phylogenetic tree topologies, the statistical support for which can be compared directly.
Figure 2: The phylogenetic relationships of SARS coronavirus (SARS-CoV) inferred using sequences of the spike glycoprotein.

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References

  1. Domingo, E. & Holland, J. J. RNA virus mutations and fitness for survival. Ann. Rev. Microbiol. 51, 151–178 (1997).

    CAS  Google Scholar 

  2. Domingo, E., Webster, R. & Holland, J. (eds). Origin and Evolution of Viruses (Academic Press, London, 1999).

    Google Scholar 

  3. Grenfell, B. T. et al. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303, 327–332 (2004).

    CAS  PubMed  Google Scholar 

  4. Elena, S. F., Miralles, R. & Moya, A. Frequency-dependent selection in a mammalian RNA virus. Evolution 5, 984–987 (1997).

    Google Scholar 

  5. Drake, J. W. Rates of spontaneous mutation among RNA viruses. Proc. Natl Acad. Sci. USA 90, 4171–4175 (1993). A key reference giving figures for the spontaneous rate of mutation in RNA viruses and the difficulties in making these measurements.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Malpica, J. M. et al. The rate and character of spontaneous mutation in an RNA virus. Genetics 162, 1505–1511 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Eigen, M. Self-organisation of matter and the evolution of biological macromolecules. Naturwissenschaften 58, 465 (1971).

    CAS  PubMed  Google Scholar 

  8. Maynard Smith, J. & Szathmáry, E. The Major Transitions of Evolution (W. H. Freeman & Co., Oxford, 1995).

    Google Scholar 

  9. Rouzine, I. M., Rodrigo, A. & Coffin, J. M. Transition between stochastic evolution and deterministic evolution in the presence of selection: general theory and application to virology. Microbiol. Mol. Biol. Rev. 65, 151–185 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Osada, D., Crandall, K. A. & Holmes, E. C. Recombination in evolutionary genomics. Ann. Rev. Genet. 36, 75–97 (2002).

    Google Scholar 

  11. Rhodes, T., Wargo, H. & Hu, W. S. High rates of human immunodeficiency virus type 1 recombination: near-random segregation of markers one kilobase apart in one round of viral replication. J. Virol. 77, 11193–11200 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Boerlijst, M. C., Bonhoeffer, S. & Nowak, M. A. Viral quasi-species and recombination. Proc. R. Soc. Lond. B Biol. Sci. 263, 1577–1584 (1996).

    Google Scholar 

  13. Chare, E. R., Gould, E. A. & Holmes, E. C. Phylogenetic analysis reveals a low rate of homologous recombination in negative-sense RNA viruses. J. Gen. Virol. 84, 2691–2703 (2003).

    CAS  PubMed  Google Scholar 

  14. Navas, S., Martin, J., Quiroga, J. A., Castillo, I. & Carreño, V. Genetic diversity and tissue compartmentalization of the hepatitis C virus genome in blood mononuclear cells, liver, and serum from chronic hepatitis C patients. J. Virol. 72, 1640–1646 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Miralles, R., Moya, A. & Elena, S. F. Effect of population patchiness and migration rates on the adaptation and divergence of vesicular stomatitis virus quasispecies populations. J. Gen. Virol. 80, 2051–2059 (1999).

    CAS  PubMed  Google Scholar 

  16. Eigen, M. & Schuster, P. The hypercycle. A principle of natural self-organization. Part A: emergence of the hypercycle. Naturwissenschaften 64, 541–565 (1977).

    CAS  PubMed  Google Scholar 

  17. Eigen, M. Steps Towards Life (Oxford Univ. Press, New York, 1996).

    Google Scholar 

  18. Domingo, E., Sabo, D., Taniguchi, T. & Weissman, C. Nucleotide sequence heterogeneity of an RNA phage population. Cell 13, 735–744 (1978).

    CAS  PubMed  Google Scholar 

  19. de la Torre, J. C. & Holland, J. J. RNA virus quasispecies populations can suppress vastly superior mutant progeny. J. Virol. 64, 6278–6281 (1990). An important experimental study showing that a high-fitness variant was suppressed in a low-fitness population. Often interpreted as indicating that RNA viruses form quasispecies.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Jenkins, G. M., Worobey, M., Woelk, C. H. & Holmes, E. C. Evidence for the nonquasispecies evolution of RNA viruses. Mol. Biol. Evol. 18, 987–994 (2001).

    CAS  PubMed  Google Scholar 

  21. Holmes, E. C. & Moya, A. Is the quasispecies concept relevant to RNA viruses? J. Virol. 76, 460–462 (2002). A paper questioning the relevance of the quasispecies model to the evolution of RNA viruses in Nature. The accompanying paper by Domingo provides a counter argument.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Burch, C. L. & Chao, L. Evolvability of an RNA virus is determined by its mutational neighborhood. Nature 406, 625–628 (2000).

    CAS  PubMed  Google Scholar 

  23. Wichman, H. A., Scott, L. A., Yarber, C. D. & Bull, J. J. Experimental evolution recapitulates natural evolution. Philos. Trans R. Soc. Lond. B Biol. Sci. 355, 1677–1684 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Ebert, D. Experimental evolution of parasites. Science 282, 1432–1435 (1998).

    CAS  PubMed  Google Scholar 

  25. Elena, S. F. Restrictions to RNA virus adaptation: an experimental approach. Antonie van Leeuwenhoek 81, 135–142 (2002).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Cuevas, J. M., Elena, S. F. & Moya, A. molecular basis of adaptive convergence in experimental populations of RNA viruses. Genetics 162, 533–542 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Badgett, M. R., Auer, A., Carmichael, L. E., Parrish, C. R. & Bull, J. J. Evolutionary dynamics of viral attenuation. J. Virol. 76, 10524–10529 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Rokyta, D., Badgett, M. R., Molineux, I. J. & Bull, J. J. Experimental genomic evolution: extensive compensation for loss of DNA ligase activity in a virus. Mol. Biol. Evol. 19, 230–238 (2002).

    CAS  PubMed  Google Scholar 

  30. Elena, S. F. & Moya, A. Rate of deleterious mutation and the distribution of its effects on fitness in vesicular stomatitis virus. J. Evol. Biol. 12, 1078–1088 (1999).

    Google Scholar 

  31. Chao, L., Rang, C. U. & Wong, L. E. Distribution of spontaneous mutants and inferences about the replication mode of the RNA bacteriophage φ6. J. Virol. 76, 3276–3281 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Wahl, L. M., Gerrish, P. J. & Saika-Voivod, I. Evaluating the impact of population bottlenecks in experimental evolution. Genetics 162, 961–971 (2002).

    PubMed  PubMed Central  Google Scholar 

  33. Lazaro, E., Escarmis, C., Perez-Mercader, J., Manrubia, S. C. & Domingo, E. Resistance of virus to extinction on bottleneck passages: study of a decaying and fluctuating pattern of fitness loss. Proc. Natl Acad. Sci. USA 100, 10830–10835 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Miralles, R., Gerrish, P. J., Moya, A. & Elena, S. F. Clonal interference and the evolution of RNA viruses. Science 285, 1745–1747 (1999). An important experimental demonstration that clonal interference slows down the rate of adaptive evolution in RNA viruses.

    CAS  PubMed  Google Scholar 

  35. Novella, I. S. Contributions of vesicular stomatitis virus to the understanding of RNA virus evolution. Curr. Opin. Microbiol. 6, 399–405 (2003).

    CAS  PubMed  Google Scholar 

  36. Wahl, L. M. & Krakauer, D. C. Models of experimental evolution: the role of genetic chance and selective necessity. Genetics 156, 1437–1448 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Chao, L. Fitness of RNA virus decreased by Muller's ratchet. Nature 348, 454–455 (1990). A seminal paper on experimental evolution with RNA viruses demonstrating the action of Muller's ratchet.

    CAS  PubMed  Google Scholar 

  38. de la Pe–a, M., Elena, S. F. & Moya, A. Effect of deleterious mutation-accumulation on the fitness of RNA bacteriophage MS2. Evolution 54, 686–691 (2000).

    Google Scholar 

  39. Fraile, A. et al. Genetic exchange by recombination or reassortment is infrequent in natural populations of a tripartite RNA plant virus. J. Virol. 71, 934–940 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Chao, L., Tran, T. T. & Tran, T. T. The advantage of sex in the RNA virus φ6. Genetics 147, 953–959 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 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 

  42. Chao, L. Evolution of sex and the molecular clock in RNA viruses. Gene 205, 301–308 (1997).

    CAS  PubMed  Google Scholar 

  43. Clarke, D. K. et al. The red queen reigns in the kingdom of RNA viruses. Proc. Natl Acad. Sci. USA 91, 4821–4824 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Wichman, H. A., Badgett, M. R., Scott, L. A., Boulianne, C. M. & Bull, J. J. Different trajectories of parallel evolution during viral adaptation. Science 285, 422–424 (1999). A key experimental paper that provides evidence for both frequent adaptive and parallel evolution in RNA viruses.

    CAS  PubMed  Google Scholar 

  45. Gerrish, P. J. The rhythm of microbial adaptation. Nature 413, 299–302 (2001).

    CAS  PubMed  Google Scholar 

  46. Turner, P. E. & Chao, L. Prisoner's dilemma in an RNA virus. Nature 398, 441–443 (1999).

    CAS  PubMed  Google Scholar 

  47. Turner, P. E. & Chao, L. Escape from prisoner's dilemma in RNA phage φ. Am. Nat. 161, 497–505 (2003).

    PubMed  Google Scholar 

  48. Wilke, C. O. & Adami, C. The biology of digital organisms. Trends Ecol. Evol. 17, 528–532 (2002).

    Google Scholar 

  49. Yedid, G. & Bell, G. Microevolution in an electronic microcosm. Am. Nat. 157, 465–487 (2001).

    CAS  PubMed  Google Scholar 

  50. Yedid, G. & Bell, G. Macroevolution simulated with autonomously replicating computer programs. Nature 420, 810–812 (2002).

    CAS  PubMed  Google Scholar 

  51. Lenski, R. E., Ofria, C., Collier, T. C. & Adami, C. Genome complexity, robustness and genetic interactions in digital organisms. Nature 400, 661–664 (1999).

    CAS  PubMed  Google Scholar 

  52. Wilke, C. O., Wang, J. L., Ofria, C., Lenski, R. E. & Adami, C. Evolution of digital organisms at high mutation rates leads to survival of the flattest. Nature 412, 331–333 (2001).

    CAS  PubMed  Google Scholar 

  53. Kilbourne, E. D. The molecular epidemiology of influenza. J. Infect. Dis. 127, 478–487 (1973).

    CAS  PubMed  Google Scholar 

  54. Holmes, E. C., Zhang, L. Q., Simmonds, P., Ludlam, C. A. & Brown, A. J. Convergent and divergent sequence evolution in the surface envelope glycoprotein of human immunodeficiency virus type 1 within a single infected patient. Proc. Natl Acad. Sci. USA 89, 4835–4839 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Scott, T. W., Weaver, S. C. & Mallampalli, V. L. in The Evolutionary Biology of Viruses (ed. Morse, S. S.) 293–324 (Raven Press, New York, 1994).

    Google Scholar 

  56. Rosenberg, N. A. & Nordborg, M. Genealogical trees, coalescent theory and the analysis of genetic polymorphisms. Nature Rev. Genet. 3, 380–390 (2002).

    CAS  PubMed  Google Scholar 

  57. Drummond, A. J., Pybus, O. G., Rambaut, A., Forsberg, R. & Rodrigo, A. G. Measurably evolving populations. Trends Ecol. Evol. 18, 481–488 (2003). Theoretical and practical introduction to the analysis of serially sampled gene sequences, including those from RNA viruses.

    Google Scholar 

  58. 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 

  59. Drummond, A. J., Nicholls, G. K., Rodrigo, A. G. & Solomon, W. Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data. Genetics 161, 1307–1320 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Drummond, A., Forsberg, R. & Rodrigo, A. G. The inference of stepwise changes in substitution rates using serial sequence samples. Mol. Biol. Evol. 18, 1365–1371 (2001).

    CAS  PubMed  Google Scholar 

  61. Seo, T. K., Thorne, J. L., Hasegawa, M. & Kishino, H. A viral sampling design for testing the molecular clock and for estimating evolutionary rates and divergence times. Bioinformatics 18, 115–123 (2002).

    CAS  PubMed  Google Scholar 

  62. Kingman, J. F. C. On the genealogy of large populations. J. Appl. Prob. 19, 27–43 (1982).

    Google Scholar 

  63. Tajima, F. Evolutionary relationship of DNA sequences in finite populations. Genetics 105, 437–460 (1983).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Hudson, R. R. Properties of a neutral allele model with intragenic recombination. Theor. Pop. Biol. 23, 183–201 (1983).

    CAS  Google Scholar 

  65. Marra, M. A. et al. The genome sequence of the SARS-associated coronavirus. Science 300, 1399–1404 (2003).

    CAS  PubMed  Google Scholar 

  66. Robbins, K. E. et al. US human immunodeficiency virus type 1 epidemic: date of origin, population history, and characterization of early strains. J. Virol. 77, 6359–6366 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Lemey, P. et al. Tracing the origin and history of the HIV-2 epidemic. Proc. Natl Acad. Sci. USA 100, 6588–6592 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Ou, C. Y. et al. Molecular epidemiology of HIV transmission in a dental practice. Science 256, 1165–1171 (1992).

    CAS  PubMed  Google Scholar 

  69. Albert, J., Wahlberg, J., Leitner, T., Escanilla, D. & Uhlen, M. Analysis of a rape case by direct sequencing of the human immunodeficiency virus type 1 pol and gag genes. J. Virol. 68, 5918–5924 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Power, J. P. et al. Molecular epidemiology of an outbreak of infection with hepatitis C virus in recipients of anti-D immunoglobulin. Lancet 345, 1211–1213 (1995).

    CAS  PubMed  Google Scholar 

  71. Esteban, J. I. et al. Transmission of hepatitis C virus by a cardiac surgeon. N. Engl. J. Med. 334, 555–560 (1996).

    CAS  PubMed  Google Scholar 

  72. Ross, H. A. & Rodrigo, A. G. Immune-mediated positive selection drives human immunodeficiency virus type 1 molecular variation and predicts disease duration. J. Virol. 76, 11715–11720 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Nielsen, R. & Yang, Z. Likelihood model for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics 148, 929–936 (1998). Develops a rigorous, statistical methodology to determine selection pressures at individual amino acid sites.

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Holmes, E. C. Patterns of intra- and interhost nonsynonymous variation reveal strong purifying selection in dengue virus. J. Virol. 77, 11296–11298 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Costa-Mattioli, M. et al. Evidence of recombination in natural populations of hepatitis A virus. Virology 311, 51–59 (2003).

    CAS  PubMed  Google Scholar 

  76. Kalinina, O., Norder, H., Mukomolov, S. & Magnius, L. O. A natural intergenotypic recombinant of hepatitis C virus identified in St Petersburg. J. Virol. 76, 4034–4043 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Korber, B. et al. Timing the ancestor of the HIV-1 pandemic strains. Science 288, 1789–1796 (2000).

    CAS  PubMed  Google Scholar 

  78. Pavesi, A. Origin and evolution of GBV-C/hepatitis G virus and relationships with ancient human migrations. J. Mol. Evol. 53, 104–113 (2001).

    CAS  PubMed  Google Scholar 

  79. Pybus, O. G., Rambaut, A. & Harvey, P. H. An integrated framework for the inference of viral population history from reconstructed genealogies. Genetics 155, 1429–1437 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Pybus, O. G. et al. The epidemic behavior of the hepatitis C virus. Science 292, 2323–2325 (2001). Establishes the link between population genetics and mathematical epidemiology through the use of molecular phylogenies to study the population dynamics of infectious diseases.

    CAS  PubMed  Google Scholar 

  81. Tanaka, Y. et al. A comparison of the molecular clock of hepatitis C virus in the United States and Japan predicts that hepatocellular carcinoma incidence in the United States will increase over the next two decades. Proc. Natl Acad. Sci. USA 99, 15584–15589 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Jenkins, G. M., Rambaut, A., Pybus, O. G. & Holmes, E. C. Rates of molecular evolution in RNA viruses: a quantitative phylogenetic analysis. J. Mol. Evol. 54, 156–165 (2002).

    CAS  PubMed  Google Scholar 

  83. Salemi, M. et al. Different population dynamics of human T-cell lymphotropic virus type II in intravenous drug users compared with endemically infected tribes. Proc. Natl Acad. Sci. USA 96, 13253–13258 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Buonagurio, D. A. et al. Evolution of human influenza A viruses over 50 years: rapid, uniform rate of change in NS gene. Science 232, 930–932 (1986). A pioneering paper describing the molecular epidemiological analysis of RNA viruses.

    Google Scholar 

  85. Gillespie, J. H. Episodic evolution of RNA viruses. Proc. Natl Acad. Sci. USA 90, 10411–11041 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Nichol, S. T., Rowe, J. E. & Fitch, W. M. Punctuated equilibrium and positive Darwinian evolution in vesicular stomatitis virus. Proc. Natl Acad. Sci. USA 90, 10424–11042 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Li, W. H., Tanimura, M. & Sharp, P. M. Rates and dates of divergence between AIDS virus nucleotide sequences. Mol. Biol. Evol. 5, 313–330 (1988).

    CAS  PubMed  Google Scholar 

  88. Overbaugh, J. & Bangham, C. R. M. Selection forces and constraints on retroviral sequence variation. Science 292, 1106–1109 (2001). Illustrates some of the key factors that constrain the adaptability of RNA viruses.

    CAS  PubMed  Google Scholar 

  89. Holmes, E. C. Molecular clocks and the puzzle of RNA virus origins. J. Virol. 77, 3893–3897 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Plyusnin, A. & Morzunov, S. P. Virus evolution and genetic diversity of hantaviruses and their rodent hosts. Curr. Top. Microbiol. Immunol. 256, 47–75 (2001).

    CAS  PubMed  Google Scholar 

  91. McGeoch, D. J., Dolan, A. & Ralph, A. C. Toward a comprehensive phylogeny for mammalian and avian herpesviruses. J. Virol. 74, 10401–10406 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Daszak, P., Cunningham, A. A. & Hyatt, A. D. Emerging infectious diseases of wildlife: threats to biodiversity and human health. Science 287, 443–449 (2000).

    CAS  PubMed  Google Scholar 

  93. Morse, S. S. Factors in the emergence of infectious diseases. Emerg. Infect. Dis. 1, 7–15 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Cleaveland, S., Laurenson, M. K. & Taylor, L. H. Diseases of humans and their domestic mammals: pathogen characteristics, host range and the risk of emergence. Philos. Trans R. Soc. Lond. B Biol. Sci. 356, 991–999 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Woolhouse, M. E. J., Taylor, L. H. & Haydon, D. T. Population biology of multihost pathogens. Science 292, 1109–1112 (2001).

    CAS  PubMed  Google Scholar 

  96. Holmes, E. C. Error thresholds and the constraints to RNA virus evolution. Trends Microbiol. 11 543–546 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  97. Woelk, C. H. & Holmes, E. C. Reduced positive selection in vector-borne RNA viruses. Mol. Biol. Evol. 19, 2333–2336 (2002).

    CAS  PubMed  Google Scholar 

  98. Defilippis, V. R. & Villarreal, L. P. in Viral Ecology (ed. Hurst, C. J.) 126–208 (Academic Press, New York, 2000).

    Google Scholar 

  99. Baranowski, E., Ruiz-Jarabo, C. M. & Domingo, E. Evolution of cell recognition by viruses. Science 292, 1102–1105 (2001).

    CAS  PubMed  Google Scholar 

  100. Scholtissek, C., Ludwig, S. & Fitch, W. M. Analysis of influenza A virus nucleoproteins for the assessment of molecular genetic mechanisms leading to new phylogenetic virus lineages. Arch. Virol. 131, 237–250 (1993).

    CAS  PubMed  Google Scholar 

  101. Peeters, M. et al. Risk to human health from a plethora of simian immunodeficiency viruses in primate bushmeat. Emerg. Infect. Dis. 8, 451–457 (2002). A remarkable demonstration of the frequency with which primate bushmeat is infected with SIVs.

    PubMed  PubMed Central  Google Scholar 

  102. Gao, F. et al. Origin of HIV-1 in the chimpanzee Pan troglodytes troglodytes. Nature 397, 436–441 (1999).

    CAS  PubMed  Google Scholar 

  103. Hahn, B. H., Shaw, G. M., de Cock, K. M. & Sharp, P. M. AIDS as a zoonosis: scientific and public health implications. Science 287, 607–614 (2000).

    CAS  PubMed  Google Scholar 

  104. Charleston, M. A. & Robertson, D. L. Preferential host switching by primate lentiviruses can account for phylogenetic similarity with the primate phylogeny. Syst. Biol. 51, 528–535 (2002).

    CAS  PubMed  Google Scholar 

  105. Rota, P. A. et al. Characterization of a novel coronavirus associated with severe acute respiratory syndrome. Science 300, 1394–1399 (2003).

    CAS  PubMed  Google Scholar 

  106. Eickmann, M. et al. Phylogeny of the SARS coronavirus. Science 302, 1504–1505 (2003).

    CAS  PubMed  Google Scholar 

  107. Guan, Y. et al. Isolation and characterization of viruses related to the SARS coronavirus from animals in southern China. Science 302, 276–278 (2003).

    CAS  PubMed  Google Scholar 

  108. Stavrinides, J. & Guttman, D. S. Mosaic evolution of the severe acute respiratory syndrome coronavirus. J. Virol. 78, 76–82 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Bush, R. M., Bender, C. A., Subbarao, K., Cox, N. J. & Fitch, W. M. Predicting the evolution of human influenza A. Science 286, 1921–1925 (1999).

    CAS  PubMed  Google Scholar 

  110. Anderson, R. M. & May, R. M. Infectious Diseases of Humans (Oxford Univ. Press, Oxford, 1991).

    Google Scholar 

  111. Culley, A. I., Lang, A. S. & Suttle, C. A. High diversity of unknown picorna-like viruses in the sea. Nature 424, 1054–1057 (2003). A PCR-based analysis of viral diversity in marine environments, which revealed a remarkable number of previously unknown viruses.

    CAS  PubMed  Google Scholar 

  112. Levin, S. A. & Andreasen, V. Disease transmission dynamics and the evolution of antibiotic resistance in hospitals and communal settings. Proc. Natl Acad. Sci. USA 96, 800–801 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  113. Levin, B. R., Lipsitch, M. & Bonhoeffer, S. Population biology, evolution, and infectious disease: convergence and synthesis. Science 283, 806–809 (1999).

    CAS  PubMed  Google Scholar 

  114. Wain-Hobson, S. Down or out in blood and lymph? Nature 387, 123–124 (1997).

    CAS  PubMed  Google Scholar 

  115. Wong, J. K. et al. Recovery of replication-competent HIV despite prolonged suppression of plasma viremia. Science 278, 1291–1295 (1997).

    CAS  PubMed  Google Scholar 

  116. Jung, A. et al. Recombination: multiply infected spleen cells in HIV patients. Nature 418, 144 (2002).

    CAS  PubMed  Google Scholar 

  117. Bonhoeffer, S., May, R. M., Shaw, G. M. & Nowak, M. A. Virus dynamics and drug therapy. Proc. Natl Acad. Sci. USA 94, 6971–6976 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  118. Back, N. K. et al. Reduced replication of 3TC-resistant HIV-1 variants in primary cells due to a processivity defect of the reverse transcriptase enzyme. EMBO J. 15, 4040–4049 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  119. Simon, V. et al. Infectivity and replication capacity of drug-resistant human immunodeficiency virus type 1 variants isolated during primary infection. J. Virol. 77, 7736–7745 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. Pitisuttithum, P. et al. Safety and immunogenicity of combinations of recombinant subtype E and B human immunodeficiency virus type 1 envelope glycoprotein 120 vaccines in healthy Thai adults. J. Infect. Dis. 188, 219–227 (2003).

    CAS  PubMed  Google Scholar 

  121. Fitch, W. M., Leiter, J. M. E., Li, X. Q. & Palese, P. Positive Darwinian evolution in human influenza-A viruses. Proc. Natl Acad. Sci. USA 88, 4270–4274 (1991).

    CAS  PubMed  PubMed Central  Google Scholar 

  122. Yusim, K. et al. Clustering patterns of cytotoxic T-lymphocyte epitopes in human immunodeficiency virus type 1 (HIV-1) proteins reveal imprints of immune evasion on HIV-1 global variation. J. Virol. 76, 8757–8768 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  123. Moore, C. B. et al. Evidence for HIV-1 adaptation to HLA-restricted immune responses at the population level. Science 296, 1439–1443 (2002).

    CAS  PubMed  Google Scholar 

  124. Wei, X. et al. Antibody neutralization and escape by HIV-1. Nature 422, 307–312 (2003). Recent paper showing that the intra-host evolution of HIV-1 is dominated by immune-driven positive selection.

    CAS  PubMed  Google Scholar 

  125. Grassly, N. C., Harvey, P. H. & Holmes, E. C. Population dynamics of HIV-1 inferred from gene sequences. Genetics 151, 427–438 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  126. Delwart, E. et al. Homogeneous quasispecies in 16 out of 17 individuals during very early HIV-1 primary infection. AIDS 16, 189–195 (2002).

    CAS  PubMed  Google Scholar 

  127. Lipsitch, M. & Moxon, E. R. Virulence and transmissibility of pathogens: what is the relationship? Trends Microbiol. 5, 31–37 (1997).

    CAS  PubMed  Google Scholar 

  128. Ebert, D. & Bull, J. J. Challenging the trade-off model for the evolution of virulence: is virulence management feasible? Trends Microbiol. 11, 15–20 (2003).

    CAS  PubMed  Google Scholar 

  129. Bergstrom, C. T., McElhany, P. & Real, L. A. Transmission bottlenecks as determinants of virulence in rapidly evolving pathogens. Proc. Natl Acad. Sci. USA 96, 5095–5100 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  130. Nowak, M. A. & May, R. M. Superinfection and the evolution of parasite virulence. Proc. R. Soc. Lond. B Biol. Sci. 255, 81–89 (1994).

    CAS  Google Scholar 

  131. Zhang, L. et al. Chemokine coreceptor usage by diverse primary isolates of human immunodeficiency virus type 1. J. Virol. 72, 9307–9312 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  132. Zhu, T. et al. Genotypic and phenotypic characterization of HIV-1 patients with primary infection. Science 261, 1179–1181 (1993).

    CAS  PubMed  Google Scholar 

  133. Metzker, M. L. et al. Molecular evidence of HIV-1 transmission in a criminal case. Proc. Natl Acad. Sci. USA 99, 14292–14297 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  134. González-Candelas, F., Bracho, M. A. & Moya, A. Molecular epidemiology and forensic genetics: application to a hepatitis C virus transmission event at a hemodialysis unit. J. Infect. Dis. 187, 352–358 (2003).

    PubMed  Google Scholar 

  135. Strimmer, K. & von Haeseler, A. Quartet puzzling: a quartet maximum likelihood method for reconstructing tree topologies. Mol. Biol. Evol. 13, 964–969 (1996).

    CAS  Google Scholar 

  136. Swofford, D. L. PAUP*. Phylogenetic Analysis Using Parsimony (*and other methods). Version 4. (Sinauer Associates, Sunderland, Massachusetts, 2002).

    Google Scholar 

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Acknowledgements

This work has been funded by The Wellcome Trust, the Spanish Ministerio de Ciencia y Tecnologia and Generalitat Valenciana. We would like to thank J. M. Cuevas and R. Sanjuan for help in preparing Box 1. We also thank four referees for useful comments.

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Authors and Affiliations

  1. Institut Cavanilles de Biodiversitat i Biolog'a Evolutiva, Universitat de València, Apartado Postal 22085, Valencia, 46071, Spain

    Andrés Moya & Fernando González-Candelas

  2. Department of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, UK

    Edward C. Holmes

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  1. Andrés Moya
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  2. Edward C. Holmes
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Correspondence to Andrés Moya.

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FURTHER INFORMATION

Unidad de Investigation de Genetica Evolutiva

Evolutionary Biology Group

Glossary

GENETIC DRIFT

Stochastic changes in allele frequencies in a finite population due to the random sampling of genes at reproduction.

FITNESS

The contribution of a genotype to the next generation, relative to that of other genotypes in the population, reflecting its probability of survival and its reproductive output.

ERROR THRESHOLD

Maximum mutation rate that is tolerable for a given genome size. Crossing the error threshold leads to dramatic fitness losses.

POPULATION BOTTLENECK

A severe reduction in population size that causes a loss of genetic variation. Under strong bottlenecks, genetic drift can be more important in evolution than natural selection.

EFFECTIVE POPULATION SIZE

(Ne). The size of an idealized population that would experience genetic drift in the same way as the actual population. Ne can be lower than the census population size (N) owing to various factors, including a history of population bottlenecks and variance in reproductive rates.

RUGGED FITNESS LANDSCAPE

A rugged fitness landscape is one with multiple fitness peaks. The more rugged a landscape the lower the average fitness correlations between neighbouring points.

CONVERGENT EVOLUTION

The independent evolution of similar traits in two or more unrelated or distantly related lineages.

CLONAL INTERFERENCE

In asexual populations beneficial mutations compete (or 'interfere') with each other as they go to fixation. Therefore, the fixation of advantageous mutations is sequential. This has important implications for the rate of adaptive evolution.

COMPLEMENTATION

The cooperative interaction of mutant genes in viral populations resulting in a phenotype closer to the wild type. In a broader sense, it refers to the use of genetic information belonging to another member of the population.

MULLER'S RATCHET

The successive build-up of deleterious mutations in finite asexual populations. It has been proposed to be an important reason for the evolution of sexual reproduction.

COMPETITIVE EXCLUSION

In the absence of ecological niche differentiation, only one of a set of competing species can occupy a particular niche, leading to the elimination of other species.

RED QUEEN HYPOTHESIS

A dynamic equilibrium between competing species, in which no species can ever win, and new adversaries continually replace the losers. It therefore depicts an ongoing arms race.

PRISONER'S DILEMMA

A theoretical game that highlights the costs and benefits of the evolution of cooperation. For example, games can be played when the population is composed of 'defectors' and 'cooperators'.

MOLECULAR CLOCK

The theory that the evolution of gene or protein sequences proceeds at a constant rate.

BASIC REPRODUCTIVE RATE

(R0). For viruses, this is defined as the number of secondary infections that are caused by a single index case in an entirely susceptible population. For an epidemic to proceed, R0 needs to exceed 1.

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Moya, A., Holmes, E. & González-Candelas, F. The population genetics and evolutionary epidemiology of RNA viruses. Nat Rev Microbiol 2, 279–288 (2004). https://doi.org/10.1038/nrmicro863

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