Multipartite graph decomposition: cycles and closed trails

This paper surveys results on cycle decompositions of complete multipartite graphs (where the parts are not all of size 1, so the graph is not K_n ), in the case that the cycle lengths are “small”. Cycles up to length n are considered, when the complete multipartite graph has n parts, but not hamilton cycles. Properties which the decompositions may have, such as being gregarious, are also mentioned

Multipartite graph decomposition: cycles and closed trails

This paper surveys results on cycle decompositions of complete multipartite graphs (where the parts are not all of size 1, so the graph is not <em>K</em>_<em>n</em> ), in the case that the cycle lengths are “small”. Cycles up to length <em>n</em> are considered, when the complete multipartite graph has <em>n</em> parts, but not hamilton cycles. Properties which the decompositions may have, such as being gregarious, are also mentioned.<br /

Evolutionary responses of fast adapting populations to opposing selection pressures

This thesis deals with the mathematical modeling of evolutionary processes that take place in heterogeneous populations. Its leitmotif is the response of complex ensembles of replicating entities to multiple (and often opposite) selection pressures. Even though the specific problems addressed in different chapters belong to different organizational levels—genome, population, and community—all of them can be conceptualized as the evolution of a heterogeneous population—let it be a population of genomic elements, viruses, or prokaryotic hosts and phages—facing a complex environment. As a result, the mathematical tools required for their study are quite similar. In contrast, the strategies that each population has discovered to perpetuate vary according to the different evolutionary challenges and environmental constraints that the population experiences. Along this thesis, there has been a special interest on connecting theoretical models with experimental results. To that end, most of the work presented here has been motivated either by laboratory findings or by the bioinformatic analysis of sequenced genomes. We strongly believe that such a multidisciplinary approach is necessary in order to improve our knowledge on how evolution works. Moreover, experiments are a must when it comes to propose antiviral strategies based on theoretical predictions, as we do in Chapter 3. This thesis is structured in two main blocks. The first one focuses on studying instances of viral evolution under the action of mutagenic drugs, paying particular attention to their possible application to the development of novel antiviral therapies. This block comprises chapters 2 and 3; the former dicussing the phenomenon of lethal defection and stochastic viral extinction; the latter dealing with the optimal way to combine mutagens and inhibitors in multidrug antiviral treatments. The second block is devoted to the study of the evolutionary forces underlying genome structure. In chapter 4, we propose a mechanism through which multipartite viruses could have originated. Interestingly, the pathway leading to genome segmentation shares some steps with lethal defection, but each outcome is reached at specific environmental conditions. Chapter 5 analyses the abundance distributions of transposable elements in prokaryotic genomes, with the aim of determining the key processes involved in their spreading. We explicitly explore the hypothesis that transposable elements follow a neutral dynamics, with a negligible fitness cost for their host genomes. A higher level of organization is studied in Chapter 6, where an agent based coevolutionary model based on Lotka-Volterra interactions is used to investigate the evolutionary dynamics of the prokaryotic antiviral immunity system CRISPR-Cas. This chapter also examines the environmental factors that are responsible for its maintenance or loss. Finally, Chapter 7 summarizes the main results obtained along the thesis and sketches possible lines of work based on them