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Virus Evolution. Lecture 6. Chapter 20, pp. 759 – 777. Basic point: Virus evolution is fast Fast generation time High rates of fecundity High rates of mutation. Mechanisms of viral evolution. Mutation Recombination Reassortment Selection.

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virus evolution lecture 6 chapter 20 pp 759 777

Virus Evolution.Lecture 6. Chapter 20, pp. 759 – 777.

Basic point: Virus evolution is fast

Fast generation time

High rates of fecundity

High rates of mutation

mechanisms of viral evolution
Mechanisms of viral evolution
  • Mutation
  • Recombination
  • Reassortment
  • Selection
virus infected cells produce large numbers of progeny fecundity
Virus-infected cells produce large numbers of progeny (fecundity)
  • Infection of a single cell by poliovirus can yield up to 104 viral particles.
  • In a person, up to 109 – 1011 particles can be produced per day
  • Enough to infect every person on the planet.
high mutation rates genome replication is inaccurate
High mutation rates: genome replication is inaccurate
  • Evolution requires mutation
  • Mutations occur when nucleic acids are copied (i.e. genome replication)
  • Baseline chemical mutation rate (keto to enol tautamarization of thymidine) = 10-4
  • Error rate of human DNA polymerase is approximately 10-9 (3 mutations per replication of the human genome).
  • Error correction machinery lowers this to 10-11
  • Virus RNA and DNA polymerases are much more error prone
    • RNA dependent RNA pol error rates: 10-4 – 10-5
    • DNA polymerases: 10-6 – 10-7
some numbers
Some numbers


  • An RNA virus with a genome of 10 kb (i.e. 104 kb)
  • RDRP error rate of 10-5
  • 10-5/104 = 10-1 = 1 in 10 progeny genomes will contain a mutation.
  • If 109 viral particles produced in a person per day, then 108 mutant progeny are being produced in that one individual each day of infection!
quasispecies error threshold bottlenecks and fitness
Quasispecies, error threshold, bottlenecks and fitness
  • Quasispecies: Virus populations as
  • dynamic distributions of nonidentical
  • but related replicons.
  • The error threshold: Too much mutation can be lead to loss of vital information, while too little mutation can lead to host defenses overcoming the virus. Error threshold is a mathematical parameter that measures the complexity of the information that must be maintained to ensure survival of the population. The greatest fitness is when mutation rates approach the error threshold.
  • Genetic drift: slow accumulation of mutations in a population. Due to constant selective pressure in a single host species.
  • Genetic shift: a major genetic change caused by mixing of genomes derived from two distinct populations of viruses, e.g. viruses that infect two different species.
more terms
More Terms
  • Genetic information exchange: Genetic information is exchanged by recombination of genome segments. Infection of a cell by two different viruses can result in exchange of genetic information, resulting in production of mixed progeny.
  • Genetic bottleneck: extreme selective pressure on a small population. Results in loss of diversity and accumulation of non-selected mutations.
  • Fitness: the replicative adaptability of an organism to its environment. Fitness is influenced by all of the above.
two general pathways for virus evolution
Two general pathways for virus evolution

Co-evolution with host

  • Advantage: prosperous host = prosperous virus
  • Disadvantage: virus shares same fate as host. Genetic bottleneck events can be fatal.
  • Typically used by DNA viruses

Infection of multiple host species.

  • Advantage: if one host species is compromised, virus can replicate in another
  • Disadvantage: cannot optimize for any one situation.
  • Typically used by RNA viruses
the origin of viruses table 20 3
The origin of viruses (Table 20.3).

1. Regressive evolution (parasitism)

  • Viruses degenerated from previously independent life forms
  • Lost many functions
  • Retain only what they needed for parasitic lifestyle

2. Cellular origins

  • Viruses derived from subcellular functional assemblies of macromolecules that gained the capacity to move from cell to cell.

3. Independent entities

  • Evolution on course parallel to that of cellular organisms.
  • Evolved from primitive, pre-biotic self-replicating molecules.
Problem: no fossil record.
  • Solution: Genomes as the fossil record.
  • Relationships among different viral genomes provide insight into virus origins. This is the basis of molecular taxonomy. Fig. 20.2
co evolution with host populations
Co-evolution with host populations.
  • Association of a given viral genome sequence with a particular host group.
    • e.g. different papillomaviruses subtypes are more prevalent in different human populations.
  • Can use viruses to trace human origins
co evolution and fitness
Co-evolution and fitness
  • Highly virulent virus will kill the host too soon
  • Too exposed and the host will kill it.

 Viruses and hosts tend to co-evolve toward symbiotic or at least mutualistic relationships.

co evolution and fitness15






Co-evolution and fitness
  • Example: the yeast killer virus.
    • L-A is a metabolic parasite of the host
    • M is a parasite of L-A
    • However, M confers a selective advantage on host.
    • Host tolerates L-A to maintain M.
    • L-A tolerates M to stay in good graces with host.
evolution is both constrained and driven by the fundamental properties of viruses
Evolution is both constrained and driven by the fundamental properties of viruses
  • A virus clade can be < 10% divergent
  • Despite lots of sequence diversity, viral populations maintain stable master or consensus sequences.
  • Diversity limited to ability to function within certain constraints. These include:
    • Particle geometry: eg. Icosahedral capsids limit genome size by limiting volume.
    • Genomes composed of nucleic acids limits solutions to replication of decoding of viral information.
    • Requirement for interactions with host cell machinery.
    • Requirements for interactions within the host organism.
evolution of new viruses
Evolution of new viruses.
  • Even within constraints, the potential for new mutations is huge.
    • e.g. fully ½ of all bases in an RNA genome can be mutated without killing the virus.
  • For a virus of 104 kb,  45000 possible sequence permutations due to simple mutation alone.
  • Even more with recombination.
  • By contrast, the visible universe contains 4135 atoms.
  • Conclusion: virus evolution is inescapable and relentless.