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. 2010 Aug;26(8):345-52.
doi: 10.1016/j.tig.2010.05.003. Epub 2010 Jun 30.

Evolution of the mutation rate

Michael Lynch  1
Affiliations

Evolution of the mutation rate

Michael Lynch. Trends Genet. 2010 Aug.

Abstract

Understanding the mechanisms of evolution requires information on the rate of appearance of new mutations and their effects at the molecular and phenotypic levels. Although procuring such data has been technically challenging, high-throughput genome sequencing is rapidly expanding knowledge in this area. With information on spontaneous mutations now available in a variety of organisms, general patterns have emerged for the scaling of mutation rate with genome size and for the likely mechanisms that drive this pattern. Support is presented for the hypothesis that natural selection pushes mutation rates down to a lower limit set by the power of random genetic drift rather than by intrinsic physiological limitations, and that this has resulted in reduced levels of replication, transcription, and translation fidelity in eukaryotes relative to prokaryotes.

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Figures

Figure 1
Figure 1
The scaling of base substitution rate/nucleotide site/generation with genome size. Each data point represents the average estimate for a separate taxon, although the results for most microbes are based on just one or a few reporter constructs (and hence have high sampling error), whereas those for most multicellular taxa are based on very large data sets (in several cases, whole genome sequences). (a) For non-eukaryotes, two separate regressions are provided, one for RNA viruses alone, and one for the pooled data from double-stranded DNA viruses, eubacteria, and archaea. The respective regressions of the log10 plotted mutation rates are −0.17 – 1.83log10(G) and 0.24 – 1.12log10(G), with G denoting the genome size in megabases, and r2 = 0.78 and 0.72, respectively. (b) The regression for cellular organisms is −0.81 + 0.68log10(G), with r2 = 0.80. Here, the results for various eubacteria (excluding Buchnera, which has an unusually small genome) are averaged into a single point. The pattern is quite similar if prokaryotes are excluded (the slope = 0.59 and r2 = 0.83).
Figure 2
Figure 2
The scaling of the base substitution mutation rate per generation (u) and the effective number of genes per locus (2Ne for diploids, and Ne for haploids). (a) The slope of the log-log regression for the nuclear genome of major phylogenetic groupings is −0.60 (0.16), where the number in parentheses denotes the standard error, with r2 = 0.84, although if the estimated Ne for prokaryotes is assumed to be 10 times too low (Lynch 2007), the slope is modified to −0.52 (0.02) with r2 = 0.99. (b) The slope of the log-log regression for the mitochondrial genome of mammalian lineages is −0.60 (0.15), with r2 = 0.84. The data are the average estimates from analyses assuming fixed and variable substitution rates in Piganeau and Eyre-Walker (2009).
Figure 3
Figure 3
Tissue-specific frequencies of mutations as a function of age in mouse lines carrying Lac reporter constructs. Results are averaged over multiple studies (Supplemental Material).
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