Re-creating and understanding the origin of life represents one of the major challenges facing the scientific community. We will never know exactly how life started on planet Earth, however, we can reconstruct the most likely chemical pathways that could have contributed to the formation of the first living systems. Traditionally, prebiotic chemistry has investigated the formation of modern life’s precursors and their self-organisation under very specific conditions thought to be ‘plausible’. So far, this approach has failed to produce a living system from the bottom-up. In the work presented herein, two different approaches are employed to explore the transition from inanimate to living matter. The development of microfluidic technology during the last decades has changed the way traditional chemical and biological experiments are performed. Microfluidics allows the handling of low volumes of reagents with very precise control. The use of micro-droplets generated within microfluidic devices is of particular interest to the field of Origins of Life and Artificial Life. Whilst many efforts have been made aiming to construct cell-like compartments from modern biological constituents, these are usually very difficult to handle. However, microdroplets can be easily generated and manipulated at kHz rates, making it suitable for high-throughput experimentation and analysis of compartmentalised chemical reactions. Therefore, we decided to develop a microfluidic device capable of manipulating microdroplets in such a way that they could be efficiently mixed, split and sorted within iterative cycles. Since no microfluidic technology had been developed before in the Cronin Group, the first chapter of this thesis describes the soft lithographic methods and techniques developed to fabricate microfluidic devices. Also, special attention is placed on the generation of water-in-oil microdroplets, and the subsequent modules required for the manipulation of the droplets such as: droplet fusers, splitters, sorters and single/multi-layer micromechanical valves. Whilst the first part of this thesis describes the development of a microfluidic platform to assist chemical evolution, finding a compatible set of chemical building blocks capable of reacting to form complex molecules with endowed replicating or catalytic activity was challenging. Hence, the second part of this thesis focuses on potential chemistry that will ultimately possess the properties mentioned above. A special focus is placed on the formation of peptide bonds from unactivated amino acids, despite being one of the greatest challenges in prebiotic chemistry. As opposed to classic prebiotic experiments, in which a specific set of conditions is studied to fit a particular hypothesis, we took a different approach: we explored the effects of several parameters at once on a model polymerisation reaction, without constraints on hypotheses on the nature of optimum conditions or plausibility. This was facilitated by development of a new high-throughput automated platform, allowing the exploration of a much larger number of parameters. This led us to discover that peptide bond formation is less challenging than previously imagined. Having established the right set of conditions under which peptide bond formation was enhanced, we then explored the co-oligomerisation between different amino acids, aiming for the formation of heteropeptides with different structure or function. Finally, we studied the effect of various environmental conditions (rate of evaporation, presence of salts or minerals) in the final product distribution of our oligomeric products.

Land plants are characterized by the alternation of two generations: the haploid gametophyte and the diploid sporophyte. As land plants evolved from bryophytes to vascular plants, the sporophyte became the dominant generation in the life cycle. The sporophytes of bryophytes are developmentally simple structures characterized by determinate growth. In contrast, the sporophytes of vascular plants diverged to become highly variable and often complex structures with indeterminate growth. KNOTTED1-LIKE HOMEOBOX (KNOX) genes encode homeodomain containing transcription factors that are key regulators of sporophyte development. KNOX genes are divided into two subclasses, class 1 and class 2. The critical role of class 1 KNOX genes in the apical growth of all extant land plants studied to date, suggests that modifications to class 1 KNOX gene function may have played an important role in sporophyte evolution. However, the nature of any such modifications is largely unknown. In this study, a number of cross-species complementation experiments were carried out to determine the extent to which class 1 KNOX gene function is conserved between different land plant groups. The role of KNOX genes in hornworts was also investigated because hornworts are believed to be the sister group to vascular plants. The work presented in this thesis demonstrates that the function of class 1 KNOX genes is conserved between lycophytes and angiosperms. In contrast, the function of class 1 KNOX genes appears to have diversified between bryophytes and vascular plants. Collectively, these results indicate increased complexity of class 1 KNOX gene function during the evolution of land plants.

How are processes working at the individual level, the species level and the macro-ecological level connected? This thesis explores the theoretical and structural constraints on biological evolution. It does this by developing an evolutionary program to model biological form. This development was necessary as the existing models of evolution are poorly suited to modelling morphological constraint. The model of biological form developed in this thesis uses graphs to abstractly represent organisms and the relationships of their internal structure. We show that by increasing the number of degrees of freedom, or by increasing the ruggedness of the fitness landscape, higher levels of diversity are supported - particularly when there is strong directional selection. We explore whether meta-regulation is bounded in the model by using an analytical framework. We show that there is no analytical steady state, but that one can be induced in the model by selection effects. We find that a mixed strategy between increasing object complexity and increasing hierarchical complexity maximises the average degree of a vertex. This agrees with the evolutionary history of meta-regulation. We claim that the macro-ecological response to environmental perturbation is determined by both the characteristic time scale of mutation and the time scale of the environmental change. We show that for high amplitude changes the system can adapt provide the mutation time scale is smaller than the environmental change. We also show that low amplitude environmental changes cause rapid turnovers in species' diversity. Finally, we show that mass extinctions can be the result of species' interactions and background rates of extinction, and do not need large external perturbations to occur. This, combined with the results above, suggests that many of the trends seen over geologically long time periods can be explained as a result of the interacting processes at the individual and species level.

Evolution is notorious for its creative power, but also for giving rise to complex, unpredictable dynamics. As a result, practitioners of artificial evolution have encountered difficulties in predicting, analysing, or even understanding the outcome of their experiments. In particular, the concept of evolutionary "progress" (whether in the sense of performance increase or complexity growth) has given rise to much debate and confusion. After a careful description of the mechanisms of evolution and natural selection, we provide usable concepts of performance and progress in coevolution. In particular, we introduce a distinction between three types of progress: local, historical, and global, which we suggest underlies much of the confusion that surrounds coevolutionary dynamics. Similarly, we provide a comprehensive answer to the question of whether an "arrow of complexity" exists in evolution. We introduce several methods to detect and analyse performance and progress in coevolutionary experiments. We propose a statistical measure (Fitness Transmission) to detect the presence of adaptive Darwinian evolution in a reproducing population, based solely on genealogic records; we also point out the limitations of a popular method (the Bedau-Packard statistics of evolutionary activity) for this purpose. To test and illustrate our results, we implement a rich experimental system, inspired by the seminal work of Karl Sims, in which virtual creatures can evolve and interact under various conditions in a physically realistic three-dimensional (3D) environment. To our knowledge, this is the first complete reimplementation and extension of Sims' results. We later extend this system with the introduction of physical combat between creatures, also a first. Finally, we introduce Evosphere, an open, planet-like environment in which 3D artificial creatures interact, reproduce and evolve freely. We conclude our discussion by using Fitness Transmission to detect the onset of adaptive evolution in this system.

One of evolution's greatest innovations was group living; indeed, it is fundamental to our daily lives as humans. Yet despite intense theoretical and empirical work, the details of how group living arose and is maintained are poorly understood. A central question in this area concerns the strength of natural selection operating between groups of organisms (group selection) because some think this is key to the evolution of group behaviour. It is, however, challenging to measure natural selection occurring between groups and between the individuals within those groups simultaneously. Consequently, a number of contentious theoretical issues have plagued group selection research for a number of decades, and empirical work on this topic is often misinterpreted. In this thesis, I investigate three biological systems that are candidates for group selection where empirical data is readily available. Using techniques from theoretical and computational biology - simulations, game theory and population genetics - I model evolution occurring at multiple levels simultaneously (multi-level selection), shedding light on the evolution and maintenance of group traits. First, I consider the evolution of a trait - lateralization - at the population- and colony-level in eusocial organisms, which have a reproductive structure that promotes group organisation and cooperation. I provide an evolutionary explanation for the strength of lateralization in colonies of the red wood ant, Formica rufa, as a compromise between intraspecific and predatory interactions. After extending the analysis to involve predators targeting multiple colonies simultaneously, I show that populations should tend towards an equal distribution of left- and right- lateralized colonies, resulting in zero population-level lateralization. This contradicts the established view that sociality should produce strong levels of lateralization at the population level. Second, I study a sub-social spider, Anelosimus studiosus, which is a group-living species that has recently been claimed to exhibit group-level adaptation. I use evolutionary game theory to explain the evolution of colony aggression with individual costs and benefits, providing an alternative to the existing group-level interpretation. The model generates a striking fit to the data without any between-group interactions. Therefore, I conclude that more evidence is needed to infer group-level adaptation in this colonial spider. Third, I study the Solanaceae, a plant family whose breeding system is reported to have undergone species selection - group selection acting on whole species. I investigate the evolution of self-fertilization over the family's phylogenetic history. By integrating an existing phylogeny with models of breeding system evolution at the individual level, I find the average selection pressure - and attendant properties of populations - expected to have characterised the Solanaceae over ~36 million years. In conclusion, I have shown the power of modelling approaches to clarify evolutionary explanations, to question existing interpretations, and to identify experiments that can help researchers identify the true causes of trait evolution.

The history of life has involved several major evolutionary transitions that have each led to the emergence of a new individual. Examples of major transitions in individuality include the evolution of the eukaryotic cell, multicellular organisms and eusocial societies. In each of these events, previously independently replicating units (cells, individuals etc.) cooperate to form a new individual, which can then only replicate as a whole. For this to occur, conflict between individuals needs to be minimised, to allow maximising their inclusive fitness to be roughly equivalent to maximising group fitness. It has been predicted that the way in which social groups form should be key for eliminating conflict between individuals and promoting cooperation. In this thesis, I have focused on two major evolutionary transitions; the evolution of multicellularity and the evolution of symbiosis, and show that the mode of group formation (whether groups are parentoffspring associations or not) is crucial for understanding when and why major transitions occur. Firstly, I show that the major transition to obligate multicellularity has only occurred with clonal group formation (where cells remain together after division). Secondly, I use an experimental system to show that predation pressure may be key in promoting the formation of multicellular groups in algae. Finally, I show that the mode of group formation is also important in between-species transitions. I use the evolution of symbiosis to show that transmission route of symbionts and environmental factors, determine how cooperative symbionts will be towards their hosts.

Geometric morphometrics, the science about the study of shape, has developed much in the last twenty years. In this thesis I first study the reliability of the phylogenies built using geometric morphometrics. The effect of different evolutionary models, branch-length combinations, dimensionality and degrees of integration is explored using computer simulations. Unfortunately in the most common situations (presence of stabilizing selection, short distance between internal nodes and presence of integration) the reliability of the phylogenies is very low. Different empirical studies are analysed to estimate the degree of evolutionary integration usually found in nature. This gives an idea about how powerful the effect of integration is over the reliability of the phylogenies in empirical studies. Evolutionary integration is studied looking at the decrease of variance in the principal components of the tangent shape space using the independent contrasts of shape. The results suggest that empirical data usually show strong degrees of integration in most of the organisms and structures analysed. These are bad news, since strong degree of integration has devastating effects over the phylogenetic reliability, as suggested by our simulations. However, we also propose the existence of other theoretical situations in which strong integration may not translate into convergence between species, like perpendicular orientation of the integration patterns or big total variance relative to the distance between species in the shape space. Finally, geometric morphometrics is applied to the study of the evolution of shape in proteins. There are reasons to think that, because of their modular nature and huge dimensionality, proteins may show different patterns of evolutionary integration. Unfortunately, proteins also show strong functional demands, which influence their evolution and that cause strong integration patterns. Integration is then confirmed as a widespread property in the evolution of shape, which causes poor phylogenetic estimates.

In this paper we present general results on aggregation of variables, specifically as it applies to decomposable (partitionable) dynamical systems. We show that a particular class of transition matrices, namely, those satisfying an equitable partitioning property, are aggregable under appropriate decomposition operators. It is also shown that equitable partitions have a natural application to the description of mutation-selection matrices (fitness landscapes) when their fitness functions have certain symmetries concordant with the neighborhood relationships in the underlying configuration space. We propose that the aggregate variable descriptions of mutation-selection systems offer a potential formal definition of units of selection and evolution.

In this paper, we investigate fitness landscapes (under point mutation and recombination) from the standpoint of whether the induced evolutionary dynamics have a “fast-slow” time scale associated with the differences in relaxation time between local quasi-equilibria and the global equilibrium. This dynamical hevavior has been formally described in the econometrics literature in terms of the spectral properties of the appropriate operator matrices by Simon and Ando (Econometrica 29 (1961) 111), and we use the relations they derive to ask which fitness functions and mutation/recombination operators satisfy these properties. It turns out that quite a wide range of landscapes satisfy the condition (at least trivially) under point mutation given a sufficiently low mutation rate, while the property appears to be difficult to satisfy under genetic recombination. In spite of the fact that Simon-Ando decomposability can be realized over fairly wide range of parameters, it imposes a number of restriction on which landscape partitionings are possible. For these reasons, the Simon-Ando formalism does not appear to be applicable to other forms of decomposition and aggregation of variables that are important in evolutionary systems.

The systematic assessment of rate variations across large datasets requires a systematic approach for summarizing results from individual tests. Often, this is performed by coarse-graining the phylogeny to consider rate variations at the level of sub-claded. In a phylo-geographic setting, however, one is often more interested in other partitions of the data, and in an exploratory mode a pre-specified subdivision of the data is often undesirable. We propose here to arrange rate variation data as the partially ordered set defined by the significant test results.