Epistasis and Pleiotropy in Evolving Populations

Abstract

In the era of high-throughput genome sequencing, it has become possible to measure the genetic changes that drive evolution. These direct observations enable us to test both qualitative and quantitative hypotheses about the microevolutionary process. Laboratory evolution of microbial populations provides a simple model system for studying microevolution quantitatively. We can exploit the short generation times and large population sizes of microbes, as well as genetic tools and the capacity to freeze and revive populations, to examine evolution in real time in the lab. In the midst of such a complex process, a simple model system like this one can ideally help us tease apart which complications are essential, and which we might safely ignore. It can also help us explore which aspects of such a stochastic and complicated process are in principle predictable, and what important features we should measure to make these predictions.

In this thesis, we use experimental evolution of laboratory populations of budding yeast, as well as theoretical analysis, to probe two such complicating factors: the influence of the genotype and the environment on evolving populations. We expect that not all genotypes will have access to the same pool of beneficial mutations, and therefore that the genotype will influence both the capacity for adaptation and the mutations that accumulate during this process. However, whether the available mutations and their effects depend on the genotype in a systematic way remains largely unknown. We examine this question in Chapters 3 and 4.

If the available mutations depend on the genotype, certain types of evolutionarily-stable states may emerge in populations in the long run. We study one such state theoretically in Chapter 6.

While environmental variation is clearly important to evolutionary processes like specialization, we lack a good understanding of how and when differences in environmental conditions affect evolution. Part of this gap is empirical, and part theoretical. In Chapter 2, we explore one aspect of this question: the extent to which adaptation to one environmental condition constrains fitnesses in others. In Chapter 5, we analyze theoretically the influence that a fluctuating environment has on the probability that a new mutation fixes, or spreads throughout, a population.