Mutation is the source of all genetic variation, and is critical for evolution. Despite its importance, we still have a lot to learn about mutation. Why does the rate of mutation vary among species, genotypes, and genome architectures? What makes some sites in a genome more susceptible to mutation than others? How do the rate and fitness consequences of mutations vary across environments? What drives the evolution of the mutation process itself? Work in our lab incorporates not just single-nucleotide changes, but also the wide spectrum of structural alterations that can dramatically alter genetic structure, promote adaptation, or lead to disease. Using experiments with yeast and fruit flies, combined with genome sequencing and bioinformatics, the Sharp Lab examines these and other aspects of mutation to broaden our understanding of this fundamental genetic process.
We now know that mutations don’t necessarily occur at a constant rate. Environmental conditions, genetic background, and genome architecture can all influence the mutation process.
Whether or not higher mutation rates are adaptive will depend on the fraction of mutations that are beneficial. Beneficial mutations are thought to be rare, but the true distribution of fitness effects of new mutations is still unknown.
When most mutations are harmful, we might expect natural selection to favour reduced mutation rates. But there are limits to how effective selection can be, which may explain why we find genetic variation for mutation rates.
We can measure fitness and other phenotypes in strains with spontaneous mutations to learn more about the consequences of the mutation process. Most mutations are either neutral or deleterious, but we know that beneficial mutations can occur as well. More experiments are needed to understand how genetic background and the environment interact to determine the fraction of new mutations that are beneficial.
Many types of mutation are possible, but they are not all equally likely. Even considering just single-nucleotide substitutions, the probability of each mutation type can depend on many aspects of genomic context, including nearby bases, GC content, recombination rate, chromosomal position, and the timing and direction of DNA replication.
We need to learn more about how the mutation spectrum depends on genomic context in order to better understand and predict molecular evolution.
We can also learn about the mutation process from the perspective of population genetics theory. Using controlled crossing designs and experimental evolution, we can generate and test predictions for how the rate and consequences of mutations will change over time and across environments.