Evolutionary dynamics of RNA-like replicators : A bioinformatic approach to the origin of life

Abstract

The origin of life has always attracted scientific inquiries. The RNA world hypothesis suggests that, before the evolution of DNAs and proteins, primordial life was based on RNAs both for information storage and chemical catalysis. In its simplest form, an RNA world consists of RNA molecules that can replicate themselves. Hence, an interesting question is how a system of such simple replicators can become life as we know it. Or, in a more manageable manner, How can a system of simple RNA-like replicators increase its complexity through Darwinian evolution? This is the central question discussed in this thesis. The thesis approaches this question from a view point of bioinformatics (i.e. the studies of informational processes in biotic systems). Mathematical or computational models are used to obtain novel insights into the evolutionary dynamics of replicator systems. The thesis presents the following results: 1. an overview of the subject from a view point of bioinformatics, 2. the mathematical formulation of phenotypic information-threshold and the examination of it in the RNA folding genotype-phenotype map, 3. the demonstration that lethal mutations make the loss of information due to erroneous replication a threshold-like transition, 4. the demonstration that complex formation between a replicase and template gives a significant selective advantages to parasites, 5. the demonstration that the evolution of complexity in RNA-like replicator systems is possible through a positive feedback between the evolution of information and that of (ecological) organization, 6. the analysis of a surprisingly complex relationship between diffusion and evolution through the investigation of replicators with strand displacement, 7. the analysis of novel evolutionary trends which emerge through the interactions between individual replicators and a higher level evolutionary entities (traveling waves and protocells). Overall, we conclude that multilevel evolution---evolution operating on multiple levels of biological organization---is a key process for the evolution of complexity.