Modelling the evolution of biological complexity with a two-dimensional lattice self-assembly process

The question how biological complexity increases in evolution is fundamental to biology, and is often linked to the idea of modular organisation, which has been defined in a variety of ways for biological structures and functions. Using a two-dimensional lattice self-assembly process, which serves as an abstract model of protein quaternary structure self-assembly, we can study the evolution of structural complexity using genetic algorithms. In this process square tiles bind together according to the interactions on their sides to form complex shapes. The specification of the interactions represents the genotype, and the final assembled structure represents the phenotype. The genetic algorithm mutates the genotype and applies a fitness function to the phenotype. This model has already been studied in detail and reproduces a number of known characteristics of evolving systems, and of other well-studied biological genotype-phenotype maps. The aim of this PhD project will be to use this approach to examine how structural and functional complexity can increase in the course of evolution. The advantage of the lattice self-assembly model (also called the 'Polyomino model') is that it allows for a rigorous quantitative definition of structural complexity. By examining different mutation events, such as point mutations and gene duplications, and with the possibility of introducing further levels of complexity, such as regulatory and epigenetic processes, this project will aim to establish how complexity can increase in evolution. Recent work has shown that changing environmental conditions may be key to this, and this will be one of the central causes examined using our approach.