Inferring the distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii

Abstract

Spontaneous mutations are the source of new genetic variation and are thus central to the evolutionary process. In molecular evolution and quantitative genetics, the nature of genetic variation depends critically on the distribution of effects of mutations on fitness and other quantitative traits. Spontaneous mutation accumulation (MA) experiments have been the principal approach for investigating the overall rate of occurrence and cumulative effect of mutations but have not allowed the phenotypic effects of individual mutations to be studied directly. Here, we crossed MA lines of the green alga Chlamydomonas reinhardtii with its unmutated ancestral strain to create haploid recombinant lines, each carrying an average of 50% of the accumulated mutations in a large number of combinations. With the aid of the genome sequences of the MA lines, we inferred the genotypes of the mutations, assayed their growth rate as a measure of fitness, and inferred the distribution of fitness effects (DFE) using a Bayesian mixture model. We infer that the DFE is highly leptokurtic (L-shaped). Of mutations with absolute fitness effects exceeding 1%, about one-sixth increase fitness in the laboratory environment. The inferred distribution of effects for deleterious mutations is consistent with a strong role for nearly neutral evolution. Specifically, such a distribution predicts that nucleotide variation and genetic variation for quantitative traits will be insensitive to change in the effective population size.

Fig 1. Relationship between growth rate and number of mutations carried by an RL or ancestor for the six CC-2931 MA line crosses.

Linear regression lines are shown. MA, mutation accumulation; RL, recombinant line.

Fig 2. Inferred DFE assuming a two-sided gamma model (smooth line) and a point mass DFE for the three-category model (transparent blue rectangles).

DFE, distribution of fitness effects.

Fig 3. The estimated reflected gamma distribution of effects (inferred gamma distribution) compared to the distribution of posterior mean estimates for the effects of the individual mutations (individual estimates).

Fig 4. Relationship between estimated fitness effects of mutations obtained by MCMC and estimates obtained from the difference in mean growth rate between recombinant lines carrying the mutant and wild-type allele (raw difference).

Raw difference estimates were calculated within MA line genotypes, excluding the ancestral lines (which are homozygous mutant or wild type for all mutations carried by a MA line). MA, mutation accumulation; MCMC, Markov chain Monte Carlo.