Old Trade, New Tricks: Insights into the Spontaneous Mutation Process from the Partnering of Classical Mutation Accumulation Experiments with High-Throughput Genomic Approaches

Abstract

Mutations spawn genetic variation which, in turn, fuels evolution. Hence, experimental investigations into the rate and fitness effects of spontaneous mutations are central to the study of evolution. Mutation accumulation (MA) experiments have served as a cornerstone for furthering our understanding of spontaneous mutations for four decades. In the pregenomic era, phenotypic measurements of fitness-related traits in MA lines were used to indirectly estimate key mutational parameters, such as the genomic mutation rate, new mutational variance per generation, and the average fitness effect of mutations. Rapidly emerging next-generating sequencing technology has supplanted this phenotype-dependent approach, enabling direct empirical estimates of the mutation rate and a more nuanced understanding of the relative contributions of different classes of mutations to the standing genetic variation. Whole-genome sequencing of MA lines bears immense potential to provide a unified account of the evolutionary process at multiple levels—the genetic basis of variation, and the evolutionary dynamics of mutations under the forces of selection and drift. In this review, we have attempted to synthesize key insights into the spontaneous mutation process that are rapidly emerging from the partnering of classical MA experiments with high-throughput sequencing, with particular emphasis on the spontaneous rates and molecular properties of different mutational classes in nuclear and mitochondrial genomes of diverse taxa, the contribution of mutations to the evolution of gene expression, and the rate and stability of transgenerational epigenetic modifications. Future advances in sequencing technologies will enable greater species representation to further refine our understanding of mutational parameters and their functional consequences.

Prolonged exposure to constant environmental conditions prompts nonrandom genetic variation

“…In an experimental setting where the efficacy of natural selection is maximally minimized (Katju and Bergthorsson 2019) and new genetic variation is negligible (Sung et al 2012) , we found that independent replicate lines of P. tetraurelia accrue an excess of the same developmental variants during the course of a ∼4-year MA experiment. Such developmental variants fall into a class of sequences that may be trans-generationally inherited.…”

“…Minimal selection efficacy is the central characteristic of Mutation Accumulation (MA) experiments. In MA experiments, replicate lines with the same genotype are allowed to accumulate spontaneous mutations under conditions where each generation experiences extreme bottlenecking (Katju and Bergthorsson 2019) . Further, MA lines are reared in constant environmental conditions ( e.g ., high nutrient level), which may foster directional organismal changes under the environment induction-based mechanism of adaptation illustrated above.…”

Long-term experimental evolution reveals purifying selection on piRNA-mediated control of transposable element expression

“…One way to study this is to use a mutation accumulation (MA) framework in 104 which replicate lines descended from a single common ancestor are propagated 105 under a regime of drastic population bottlenecks for several hundred 106 generations (Halligan and Keightley, 2009;Katju and Bergthorsson, 2019). The 107 maintenance of these lines at a minimal population size attenuates the efficacy of 108 selection, thereby enabling the accumulation of a large, unbiased sample of 109 spontaneous mutations under conditions of genetic drift which can subsequently 110 be identified and their fitness effects investigated.…”

Direct inference of the distribution of fitness effects of spontaneous mutations inChlamydomonas reinhardtii

“…Genome sequencing technology now allows the identification of the nearly complete complement of mutations carried by a set of MA lines, and in combination with phenotypic information this can potentially be used to leverage information on the DFE (Katju and Bergthorsson 2018). Previous analysis of spontaneous MA experiments have, however, only studied the cumulative effects of new mutations, whereas accurate inference requires estimation of the effects of individual mutations.…”