How does mutation affect the distribution of phenotypes?

The Contribution of Mutation to Variation in Temperature-Dependent Sprint Speed in Zebrafish, Danio rerio

AbstractThe contribution of new mutations to phenotypic variation and the consequences of this variation for individual fitness are fundamental concepts for understanding genetic variation and adaptation. Here, we investigated how mutation influenced variation in a complex trait in zebrafish, Danio rerio. Typical of many ecologically relevant traits in ectotherms, swimming speed in fish is temperature dependent, with evidence of adaptive evolution of thermal performance. We chemically induced novel germline point mutations in males and measured sprint speed in their sons at six temperatures (between 16°C and 34°C). Heterozygous mutational effects on speed were strongly positively correlated among temperatures, resulting in statistical support for only a single axis of mutational variation, reflecting temperature-independent variation in speed (faster-slower mode). These results suggest pleiotropic effects on speed across different temperatures; however, spurious correlations arise via linkage or heterogeneity in mutation number when mutations have consistent directional effects on each trait. Here, mutation did not change mean speed, indicating no directional bias in mutational effects. The results contribute to emerging evidence that mutations may predominantly have synergistic cross-environment effects, in contrast to conditionally neutral or antagonistic effects that underpin thermal adaptation. We discuss several aspects of experimental design that may affect resolution of mutations with nonsynergistic effects.

A broad mutational target explains a fast rate of phenotypic evolution

The rapid evolution of a trait in a clade of organisms can be explained by the sustained action of natural selection or by a high mutational variance, that is the propensity to change under spontaneous mutation. The causes for a high mutational variance are still elusive. In some cases, fast evolution depends on the high mutation rate of one or few loci with short tandem repeats. Here, we report on the fastest evolving cell fate among vulva precursor cells in Caenorhabditis nematodes, that of P3.p. We identify and validate causal mutations underlying P3.p's high mutational variance. We find that these positions do not present any characteristics of a high mutation rate, are scattered across the genome and the corresponding genes belong to distinct biological pathways. Our data indicate that a broad mutational target size is the cause of the high mutational variance and of the corresponding fast phenotypic evolutionary rate.

Heritable characteristics or traits of a group of organisms, for example the large brain size of primates or the hooves of a horse, are determined by genes, the environment, and by the interactions between them. Traits can change over time and generations when enough mutations in these genes have spread in a species to result in visible differences.

However, some traits, such as the large brain of primates, evolve faster than others, but why this is the case has been unclear. It could be that a few specific genes important for that trait in question mutate at a high rate, or, that many genes affect the trait, creating a lot of variation for natural selection to choose from.

Here, Besnard, Picao-Osorio et al. studied the roundworm Caenorhabditis elegans to better understand the causes underlying the different rates of trait evolution. These worms have a short life cycle and evolve quickly over many generations, making them an ideal candidate for studying mutation rates in different traits.

Previous studies have shown that one of C. elegans’ six cells of the reproductive system evolves faster than the others. To investigate this further, Besnard, Picao-Osorio et al. analysed the genetic mutations driving change in this cell in 250 worm generations. The results showed that five mutations in five different genes – all responsible for different processes in the cells – were behind the supercharged evolution of this particular cell. This suggests that fast evolution results from natural selection acting upon a collection of genes, rather than one gene, and that many genes and pathways shape this trait.

In conclusion, these results demonstrate that how traits are coded at the molecular level, in one gene or many, can influence the rate at which they evolve.

Protein deprivation facilitates the independent evolution of behavior and morphology

Ecological conditions such as nutrition can change genetic covariances between traits and accelerate or slow down trait evolution. As adaptive trait correlations can become maladaptive following rapid environmental change, poor or stressful environments are expected to weaken genetic covariances, thereby increasing the opportunity for independent evolution of traits. Here, we demonstrate the differences in genetic covariance among multiple behavioral and morphological traits (exploration, aggression, and body weight) between southern field crickets (Gryllus bimaculatus) raised in favorable (free-choice) versus stressful (protein-deprived) nutritional environments. We also quantify the extent to which differences in genetic covariance structures contribute to the potential for the independent evolution of these traits. We demonstrate that protein-deprived environments tend to increase the potential for traits to evolve independently, which is caused by genetic covariances that are significantly weaker for crickets raised on protein-deprived versus free-choice diets. The weakening effects of stressful environments on genetic covariances tended to be stronger in males than in females. The weakening of the genetic covariance between traits under stressful nutritional environments was expected to facilitate the opportunity for adaptive evolution across generations. Therefore, the multivariate gene-by-environment interactions revealed here may facilitate behavioral and morphological adaptations to rapid environmental change.

Do slower movers have lower reproductive success and higher mutation load?

Deleterious mutations occur frequently in eukaryotes, resulting in individuals carrying multiple alleles that decrease their fitness. At a population level, if unchecked, accumulation of this mutation load can ultimately lead to extinction. How selection counters the accumulation of mutation load, limiting declines in population fitness, is not well understood. Here, we use manipulative experiments in zebrafish (Danio rerio) to investigate the opportunities for selection on mutation load. Inducing high mutation load through mutagenesis, we applied one generation of within‐family selection on locomotor performance and characterized both the direct response to this selection and the indirect response of reproductive success. Offspring of slow swimming parents exhibited age‐dependent declines in swimming speed, whereas their cousins, with faster swimming parents, did not. This pattern mimics previously documented differences between high and low mutation load populations of zebrafish, suggesting that slow swimming siblings inherited (and transmitted) more mutations than their faster swimming siblings. Crosses among offspring of slow swimming fish had, on average, <75% of the reproductive success of crosses among offspring of fast swimming parents, or crosses of offspring of slow swimmers with offspring of fast swimmers. This evidence of mutationally correlated swimming speed and reproductive success reveals the potential for concordant selection on mutation load through different fitness components. There was no evidence that crosses within families (where parents potentially shared the same mutations inherited from their common ancestor) had lower reproductive success than crosses among families, suggesting that viability selection was not acting predominantly through lethal recessive homozygotes. Rather, patterns of reproductive success are suggestive of effects of mutation number per se on embryo viability. Overall, our results highlight the potential for early life mortality to remove deleterious mutations, and the need to account for this mortality when investigating the evolutionary dynamics of mutation load.