Complexities of Viral Mutation Rates

Abstract

Many viruses evolve rapidly. This is due, in part, to their high mutation rates. Mutation rate estimates for over 25 viruses are currently available. Here, we review the population genetics of virus mutation rates. We specifically cover the topics of mutation rate estimation, the forces that drive the evolution of mutation rates, and how the optimal mutation rate can be context-dependent.

Keywords: mutation rate evolution; polymerase; polymerase fidelity; viral mutation rates; virus evolution.

FIG 1

Viral mutation rates. (A) Viral evolutionary rates (substitutions per nucleotide site per year [s/n/y]) increase with mutation rate (substitutions per nucleotide site per cell infection [s/n/c]), up to a point (adapted from reference 3). (B) Evolutionary rates against mutation rate for individual viruses (adapted from reference 4). (C) Mutation rate (in s/n/c or substitutions per nucleotide site per generation [s/n/g]) against genome size (base pairs [bp]) for viruses and other organisms (data from references 5, 6). For complete data used to generate figures, visit https://github.com/lauringlab/JVI_Gem_2018. (+)ssRNA, positive single-stranded RNA; (−)ssRNA, negative single-stranded RNA; ssDNA, single-stranded DNA; dsRNA, double-stranded RNA; dsDNA, double-stranded DNA; retro, retrovirus.

FIG 2

Three hypotheses for why mutation rates have not evolved to be zero. (Left) The drift-barrier hypothesis posits that drift, which weakens as the effective population size grows larger, prevents mutation rates from reaching zero (6). (Center) The physicochemical limit hypothesis posits that the cost of perfect polymerase function pushes the mutation rate away from zero. (Right) The selection hypothesis posits that selection for adaptability and/or replicative speed drives mutation rates higher. Figures are approximate trends and are not meant to indicate exact relationships (e.g., linear).