Precise estimates of mutation rate and spectrum in yeast

Abstract

Mutation is the ultimate source of genetic variation. The most direct and unbiased method of studying spontaneous mutations is via mutation accumulation (MA) lines. Until recently, MA experiments were limited by the cost of sequencing and thus provided us with small numbers of mutational events and therefore imprecise estimates of rates and patterns of mutation. We used whole-genome sequencing to identify nearly 1,000 spontaneous mutation events accumulated over ∼311,000 generations in 145 diploid MA lines of the budding yeast Saccharomyces cerevisiae. MA experiments are usually assumed to have negligible levels of selection, but even mild selection will remove strongly deleterious events. We take advantage of such patterns of selection and show that mutation classes such as indels and aneuploidies (especially monosomies) are proportionately much more likely to contribute mutations of large effect. We also provide conservative estimates of indel, aneuploidy, environment-dependent dominant lethal, and recessive lethal mutation rates. To our knowledge, for the first time in yeast MA data, we identified a sufficiently large number of single-nucleotide mutations to measure context-dependent mutation rates and were able to (i) confirm strong AT bias of mutation in yeast driven by high rate of mutations from C/G to T/A and (ii) detect a higher rate of mutation at C/G nucleotides in two specific contexts consistent with cytosine methylation in S. cerevisiae.neighbor-dependent mutation rate | strongly deleterious mutation S pontaneous mutations are the source of all genetic variation in nature. The rate of emergence of new mutations and the relative proportions of advantageous, neutral, and deleterious mutations are key determinants in how species evolve and adapt to new selective challenges. Unfortunately, our knowledge of the properties of spontaneous mutations remains incomplete primarily due to the difficulty of observing large enough numbers of mutational events in an unbiased way.Analyzing patterns of divergence in nonfunctional sequences is a statistically powerful method used to study relative rates of different mutation classes. This method is applicable to most organisms and now can generally be carried out on a genomewide scale. However, this approach relies crucially on the assumption that mutations in certain regions, such as pseudogenes or fourfold degenerate codon positions, are not affected by selection and are thus reliable approximations of true mutation rate. It is now becoming apparent that selection or selectionlike processes, such as biased gene conversion, are acting even at these sequences and can substantially bias the observed patterns (1-5).Studies focusing on mutations in reporter genes use a more restrictive method that can be applied only in model organisms. In some cases, such reporter genes can be placed genome-wide and thus provide estimates of genomic variation in mutation rates. However, this approach is limited by the inability to detect mutations without a visible phenotype and thus ...

The Rate and Molecular Spectrum of Spontaneous Mutations in the GC-Rich Multichromosome Genome of Burkholderia cenocepacia

“…Based on the 7.70 Mb genome size, these per-base mutation rates correspond to a genome-wide basesubstitution mutation rate of only 0.001/genome/generation, and an indel mutation rate of only 0.0001/genome/generation. Although the 1:3 ratio of synonymous to nonsynonymous substitutions is consistent with negligible influence of selection on base-substitution mutations in this study, too few indels occurred to evaluate a signature of selection, but their scarcity could reflect some selective loss of genotypes with lossof-function mutations (Heilbron et al 2014;Zhu et al 2014).…”

“…Based on the 7.70 Mb genome size, these per-base mutation rates correspond to a genome-wide basesubstitution mutation rate of only 0.001/genome/generation, and an indel mutation rate of only 0.0001/genome/generation. Although the 1:3 ratio of synonymous to nonsynonymous substitutions is consistent with negligible influence of selection on base-substitution mutations in this study, too few indels occurred to evaluate a signature of selection, but their scarcity could reflect some selective loss of genotypes with lossof-function mutations (Heilbron et al 2014;Zhu et al 2014).Base-substitution mutations are not AT biasedOne of the central motivations for studying the molecular mutation spectrum of B. cenocepacia was its high %GC content (66.8%). A universal mutation bias in the direction of AT has been observed in all other wild-type species studied by MA (Table 1) and has also been inferred in comparative analyses of several bacterial species, including B. pseudomallei…”

“…A universal mutation bias in the direction of AT has been observed in all other wild-type species studied by MA (Table 1) and has also been inferred in comparative analyses of several bacterial species, including B. pseudomallei (Lynch et al 2008;Denver et al 2009Denver et al , 2012Keightley et al 2009;Hershberg and Petrov 2010;Hildebrand et al 2010;Lynch 2010a;Ossowski et al 2010;Sung et al 2012a, b;Lee et al 2012;Schrider et al 2013;Zhu et al 2014). Thus, biased gene conversion and selection have been invoked to explain the high %GC content realized in many genomes (Lynch et al 2008;Duret and Galtier 2009;Raghavan et al 2012;Zhu et al 2014;Lassalle et al 2015). Our data for B. cenocepacia are inconsistent with prior published studies showing a mutation bias in the direction of AT (Table 1), but also suggest that biased gene conversion and/or selection must have mostly generated the realized %GC content of B. cenocepacia, which is substantially higher than expected based on mutation pressure alone.…”

“…G:C transitions also occurred at nearly the same rate as G:C . A:T transitions, the latter of which have been the most commonly observed substitution in other studies, putatively due to deamination of cytosine or 5-methyl-cytosine (Figure 2) (Lee et al 2012;Sung et al 2012b;Zhu et al 2014).…”

“…However, as a result of the genetic burden imposed by deleterious mutations, remarkably low mutation rates have evolved across all of life, making detection of these rare events technologically challenging and accurate measures of mutation rates and spectra exceedingly difficult (Kibota and Lynch 1996;Lynch and Walsh 1998;Sniegowski et al 2000;Lynch 2011;Fijalkowska et al 2012;Zhu et al 2014). Until recently, most estimates of mutational properties have been derived indirectly using comparative genomics at putatively neutral sites (Graur and Li 2000;Wielgoss et al 2011) or by extrapolation from small reporter-construct studies (Drake 1991).…”