Evolution of gene networks in sex determination
In this work, the evolution of sex determination gene networks is inves tigated using a modelling approach. Recent evidence indicates that an in crease in the complexity of interactions has played an important role in gene network evolution. Sex determination mechanisms offer a good model for studying gene network evolution because, among other reasons, they evolve rapidly. In chapter 2, the potential for evolutionary change of the existing Drosophila sex determination gene network is considered. With the aid of a synchronous logical model, theoretical concepts such as a network-specific form of mutation are defined, as well as a notion of functional equivalence between networks. Applying this theoretical framework to the sex deter mination mechanism, it is found that sex determination networks generally exist within large sets of functionally equivalent networks all of which satisfy the sex determination task. These large sets are in turn composed of sub sets which are mutationally related, suggesting a high degree of flexibility is available without compromising the core functionality. The technique for finding functional equivalence between networks suggests a general method for gene network reconstruction, which is explored in chapter 3. Lastly, in chapters 4 and 5, a hierarchical model is presented which integrates popu lation genetics techniques with network dynamics. This model consists of a core population genetics simulation within which parameters such as the sex and fitness of the genotype are calculated from the corresponding network dynamics. The model is used to investigate the early evolution of sex deter mination networks. Following from a hypothesis proposed by Wilkins (1995), the assumption is made that sex determination networks have evolved in a retrograde manner from bottom to top. Starting from the simplest possible ancestral system, based on a single locus, we explore the way in which more complex systems, involving two or three loci, could have evolved.