Genomic signatures of selection and non-adaptive evolution in a social microbe

Abstract

Evolutionary processes leave footprints across the genome. In its several forms, natural selection favours or removes mutations based on their fitness effects, which has consequences to patterns of standing variation, linkage disequilibrium, and rates of evolution. Genomic tools have allowed for a revolution in how we can study these problems, leading to great progress from the understanding of co-evolutionary dynamics in nature to the design of parasite-targeted drugs in medical sciences. However, despite the inarguable importance of selection, patterns across the genome are not necessarily a result of selection, even when selection might appear as the best explanation. In fact, in many cases, the patterns we observe emerge precisely because selection is not strong enough to overcome the effect of stochastic processes of mutation and genetic drift. Genomic signatures left by weak selection can mimic the footprints of adaptive evolution in several ways – from accumulation of intraspecific variation and accelerated divergence between species to strong biases in usage of alternative codons and amino acids. A detailed investigation of these sources of molecular information can, however, disentangle patterns emerging from adaptive and non-adaptive processes. Here, we use the social amoeba Dictyostelium discoideum as a model system to investigate fundamental evolutionary questions, with a special focus on disentangling the contribution of adaptive from non-adaptive forces shaping molecular variation. Chapter 1 provides a brief overview of the main points to be discussed throughout this work. In chapter 2, we integrate evolutionary theory with large-scale expression and genomic data from natural populations to understand evolutionary processes shaping genes associated with social behaviour. In chapter 3, we investigate implications of a strongly AT-biased genome for usage of alternative codons. In chapter 4 we address the often overlooked impact of overall processes shaping genome and cell economics on amino acid content and evolution of proteins. Finally, chapter 5 provides a short general discussion of the main findings of this work.

Date of Award	13 Feb 2019
Original language	English
Awarding Institution	University of Bath
Supervisor	Araxi Urrutia (Supervisor) & Jason Wolf (Supervisor)