998 resultados para Evolutionary clustering


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Evolutionary history of biological entities is recorded within their nucleic acid sequences and can (sometimes) be deciphered by thorough genomic analysis. In this study we sought to gain insights into the diversity and evolution of bacterial and archaeal viruses. Our primary interest was pointed towards those virus groups/families for which comprehensive genomic analysis was not previously possible due to the lack of sufficient amount of genomic data. During the course of this work twenty-five putative proviruses integrated into various prokaryotic genomes were identified, enabling us to undertake a comparative genomics approach. This analysis allowed us to test the previously formulated evolutionary hypotheses and also provided valuable information on the molecular mechanisms behind the genome evolution of the studied virus groups.

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Environmental variation is a fact of life for all the species on earth: for any population of any particular species, the local environmental conditions are liable to vary in both time and space. In today's world, anthropogenic activity is causing habitat loss and fragmentation for many species, which may profoundly alter the characteristics of environmental variation in remaining habitat. Previous research indicates that, as habitat is lost, the spatial configuration of remaining habitat will increasingly affect the dynamics by which populations are governed. Through the use of mathematical models, this thesis asks how environmental variation interacts with species properties to influence population dynamics, local adaptation, and dispersal evolution. More specifically, we couple continuous-time continuous-space stochastic population dynamic models to landscape models. We manipulate environmental variation via parameters such as mean patch size, patch density, and patch longevity. Among other findings, we show that a mixture of high and low quality habitat is commonly better for a population than uniformly mediocre habitat. This conclusion is justified by purely ecological arguments, yet the positive effects of landscape heterogeneity may be enhanced further by local adaptation, and by the evolution of short-ranged dispersal. The predicted evolutionary responses to environmental variation are complex, however, since they involve numerous conflicting factors. We discuss why the species that have high levels of local adaptation within their ranges may not be the same species that benefit from local adaptation during range expansion. We show how habitat loss can lead to either increased or decreased selection for dispersal depending on the type of habitat and the manner in which it is lost. To study the models, we develop a recent analytical method, Perturbation expansion, to enable the incorporation of environmental variation. Within this context, we use two methods to address evolutionary dynamics: Adaptive dynamics, which assumes mutations occur infrequently so that the ecological and evolutionary timescales can be separated, and via Genotype distributions, which assume mutations are more frequent. The two approaches generally lead to similar predictions yet, exceptionally, we show how the evolutionary response of dispersal behaviour to habitat turnover may qualitatively depend on the mutation rate.

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The noted 19th century biologist, Ernst Haeckel, put forward the idea that the growth (ontogenesis) of an organism recapitulated the history of its evolutionary development. While this idea is defunct within biology, the idea has been promoted in areas such as education (the idea of an education being the repetition of the civilizations before). In the research presented in this paper, recapitulation is used as a metaphor within computer-aided design as a way of grouping together different generations of spatial layouts. In most CAD programs, a spatial layout is represented as a series of objects (lines, or boundary representations) that stand in as walls. The relationships between spaces are not usually explicitly stated. A representation using Lindenmayer Systems (originally designed for the purpose of modelling plant morphology) is put forward as a way of representing the morphology of a spatial layout. The aim of this research is not just to describe an individual layout, but to find representations that link together lineages of development. This representation can be used in generative design as a way of creating more meaningful layouts which have particular characteristics. The use of genetic operators (mutation and crossover) is also considered, making this representation suitable for use with genetic algorithms.

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Productivity is predicted to drive the ecological and evolutionary dynamics of predator-prey interaction through changes in resource allocation between different traits. However, resources are seldom constantly available and thus temporal variation in productivity could have considerable effect on the species' potential to evolve. To study this, three long-term microbial laboratory experiments were established where Serratia marcescens prey bacteria was exposed to predation of protist Tetrahymena thermophila in different prey resource environments. The consequences of prey resource availability for the ecological properties of the predator-prey system, such as trophic dynamics, stability, and virulence, were determined. The evolutionary changes in species traits and prey genetic diversity were measured. The prey defence evolved stronger in high productivity environment. Increased allocation to defence incurred cost in terms of reduced prey resource use ability, which probably constrained prey evolution by increasing the effect of resource competition. However, the magnitude of this trade-off diminished when measured in high resource concentrations. Predation selected for white, non-pigmented, highly defensive prey clones that produced predation resistant biofilm. The biofilm defence was also potentially accompanied with cytotoxicity for predators and could have been traded off with high motility. Evidence for the evolution of predators was also found in one experiment suggesting that co-evolutionary dynamics could affect the evolution and ecology of predator-prey interaction. Temporal variation in resource availability increased variation in predator densities leading to temporally fluctuating selection for prey defences and resource use ability. Temporal variation in resource availability was also able to constrain prey evolution when the allocation to defence incurred high cost. However, when the magnitude of prey trade-off was small and the resource turnover was periodically high, temporal variation facilitated the formation of predator resistant biofilm. The evolution of prey defence constrained the transfer of energy from basal to higher trophic levels, decreasing the strength of top-down regulation on prey community. Predation and temporal variation in productivity decreased the stability of populations and prey traits in general. However, predation-induced destabilization was less pronounced in the high productivity environment where the evolution of prey defence was stronger. In addition, evolution of prey defence weakened the environmental variation induced destabilization of predator population dynamics. Moreover, protozoan predation decreased the S. marcescens virulence in the insect host moth (Parasemia plantaginis) suggesting that species interactions outside the context of host-pathogen relationship could be important indirect drivers for the evolution of pathogenesis. This thesis demonstrates that rapid evolution can affect various ecological properties of predator-prey interaction. The effect of evolution on the ecological dynamics depended on the productivity of the environment, being most evident in the constant environments with high productivity.

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Predicting evolutionary outcomes and reconstructing past evolutionary transitions are among the main goals of evolutionary biology. Ultimately, understanding the mechanisms of evolutionary change will also provide answers to the timely question of whether and how organisms will adapt to changing environmental conditions. In this thesis, I have investigated the relative roles of natural selection, random genetic drift and genetic correlations in the evolution of complex traits at different levels of organisation from populations to individuals. I have shown that natural selection has been the driving force behind body shape divergence of marine and freshwater threespine stickleback (Gasterosteus aculeatus) populations, while genetic drift may have played a significant role in the more fine scale divergence among isolated freshwater populations. These results are concurrent with the patterns that have emerged in the published studies comparing the relative importance of natural selection and genetic drift as explanations for population divergence in different traits and taxa. I have also shown that body shape and armour divergence among threespine stickleback populations is likely to be biased by the patterns of genetic variation and covariation. Body shape and armour variation along the most likely direction of evolution the direction of maximum genetic variance reflects the general patterns of variation observed wild populations across the distribution range of the threespine stickleback. Conversely, it appears that genetic correlations between the sexes have not imposed significant constraints on the evolution of sexual dimorphism in threespine stickleback body shape and armour. I have demonstrated that the patterns of evolution seen in the wild can be experimentally recreated to tease out the effects of different selection agents in detail. In addition, I have shown how important it is to take into account the correlative nature of traits, when making interpretations about the effects of natural selection on individual traits. Overall, this thesis provides a demonstration of how considering the relative roles of different mechanism of evolutionary change at different levels of organisation can aid in an emergence of a comprehensive picture of how adaptive divergence in wild populations occurs.

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Evolutionary genetics incorporates traditional population genetics and studies of the origins of genetic variation by mutation and recombination, and the molecular evolution of genomes. Among the primary forces that have potential to affect the genetic variation within and among populations, including those that may lead to adaptation and speciation, are genetic drift, gene flow, mutations and natural selection. The main challenges in knowing the genetic basis of evolutionary changes is to distinguish the adaptive selection forces that cause existent DNA sequence variants and also to identify the nucleotide differences responsible for the observed phenotypic variation. To understand the effects of various forces, interpretation of gene sequence variation has been the principal basis of many evolutionary genetic studies. The main aim of this thesis was to assess different forms of teleost gene sequence polymorphisms in evolutionary genetic studies of Atlantic salmon (Salmo salar) and other species. Firstly, the level of Darwinian adaptive evolution affected coding regions of the growth hormone (GH) gene during the teleost evolution was investigated based on the sequence data existing in public databases. Secondly, a target gene approach was used to identify within population variation in the growth hormone 1 (GH1) gene in salmon. Then, a new strategy for single nucleotide polymorphisms (SNPs) discovery in salmonid fishes was introduced, and, finally, the usefulness of a limited number of SNP markers as molecular tools in several applications of population genetics in Atlantic salmon was assessed. This thesis showed that the gene sequences in databases can be utilized to perform comparative studies of molecular evolution, and some putative evidence of the existence of Darwinian selection during the teleost GH evolution was presented. In addition, existent sequence data was exploited to investigate GH1 gene variation within Atlantic salmon populations throughout its range. Purifying selection is suggested to be the predominant evolutionary force controlling the genetic variation of this gene in salmon, and some support for gene flow between continents was also observed. The novel approach to SNP discovery in species with duplicated genome fragments introduced here proved to be an effective method, and this may have several applications in evolutionary genetics with different species - e.g. when developing gene-targeted markers to investigate quantitative genetic variation. The thesis also demonstrated that only a few SNPs performed highly similar signals in some of the population genetic analyses when compared with the microsatellite markers. This may have useful applications when estimating genetic diversity in genes having a potential role in ecological and conservation issues, or when using hard biological samples in genetic studies as SNPs can be applied with relatively highly degraded DNA.

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The first part of this work investigates the molecular epidemiology of a human enterovirus (HEV), echovirus 30 (E-30). This project is part of a series of studies performed in our research team analyzing the molecular epidemiology of HEV-B viruses. A total of 129 virus strains had been isolated in different parts of Europe. The sequence analysis was performed in three different genomic regions: 420 nucleotides (nt) in the VP4/VP2 capsid protein coding region, the entire VP1 capsid protein coding gene of 876 nt, and 150 nt in the VP1/2A junction region. The analysis revealed a succession of dominant sublineages within a major genotype. The temporally earlier genotypes had been replaced by a genetically homogenous lineage that has been circulating in Europe since the late 1970s. The same genotype was found by other research groups in North America and Australia. Globally, other cocirculating genetic lineages also exist. The prevalence of a dominant genotype makes E-30 different from other previously studied HEVs, such as polioviruses and coxsackieviruses B4 and B5, for which several coexisting genetic lineages have been reported. The second part of this work deals with molecular epidemiology of human rhinoviruses (HRVs). A total of 61 field isolates were studied in the 420-nt stretch in the capsid coding region of VP4/VP2. The isolates were collected from children under two years of age in Tampere, Finland. Sequences from the clinical isolates clustered in the two previously known phylogenetic clades. Seasonal clustering was found. Also, several distinct serotype-like clusters were found to co-circulate during the same epidemic season. Reappearance of a cluster after disappearing for a season was observed. The molecular epidemiology of the analyzed strains turned out to be complex, and we decided to continue our studies of HRV. Only five previously published complete genome sequences of HRV prototype strains were available for analysis. Therefore, all designated HRV prototype strains (n=102) were sequenced in the VP4/VP2 region, and the possibility of genetic typing of HRV was evaluated. Seventy-six of the 102 prototype strains clustered in HRV genetic group A (HRV-A) and 25 in group B (HRV-B). Serotype 87 clustered separately from other HRVs with HEV species D. The field strains of HRV represented as many as 19 different genotypes, as judged with an approximate demarcation of a 20% nt difference in the VP4/VP2 region. The interserotypic differences of HRV were generally similar to those reported between different HEV serotypes (i.e. about 20%), but smaller differences, less than 10%, were also observed. Because some HRV serotypes are genetically so closely related, we suggest that the genetic typing be performed using the criterion "the closest prototype strain". This study is the first systematic genetic characterization of all known HRV prototype strains, providing a further taxonomic proposal for classification of HRV. We proposed to divide the genus Human rhinoviruses into HRV-A and HRV-B. The final part of the work comprises a phylogenetic analysis of a subset (48) of HRV prototype strains and field isolates (12) in the nonstructural part of the genome coding for the RNA-dependent RNA polymerase (3D). The proposed division of the HRV strains in the species HRV-A and HRV-B was also supported by 3D region. HRV-B clustered closer to HEV species B, C, and also to polioviruses than to HRV-A. Intraspecies variation within both HRV-A and HRV-B was greater in the 3D coding region than in the VP4/VP2 coding region, in contrast to HEV. Moreover, the diversity of HRV in 3D exceeded that of HEV. One group of HRV-A, designated HRV-A', formed a separate cluster outside other HRV-A in the 3D region. It formed a cluster also in the capsid region, but located within HRV-A. This may reflect a different evolutionary history of distinct genomic regions among HRV-A. Furthermore, the tree topology within HRV-A in the 3D region differed from that in the VP4/VP2, suggesting possible recombination events in the evolution of the strains. No conflicting phylogenies were observed in any of the 12 field isolates. Possible recombination was further studied using the Similarity and Bootscanning analyses of the complete genome sequences of HRV available in public databases. Evidence for recombination among HRV-A was found, as HRV2 and HRV39 showed higher similarity in the nonstructural part of the genome. Whether HRV2 and HRV39 strains - and perhaps also some other HRV-A strains not yet completely sequenced - are recombinants remains to be determined.

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This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.

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Background: The members of cupin superfamily exhibit large variations in their sequences, functions, organization of domains, quaternary associations and the nature of bound metal ion, despite having a conserved beta-barrel structural scaffold. Here, an attempt has been made to understand structure-function relationships among the members of this diverse superfamily and identify the principles governing functional diversity. The cupin superfamily also contains proteins for which the structures are available through world-wide structural genomics initiatives but characterized as ``hypothetical''. We have explored the feasibility of obtaining clues to functions of such proteins by means of comparative analysis with cupins of known structure and function. Methodology/Principal Findings: A 3-D structure-based phylogenetic approach was undertaken. Interestingly, a dendrogram generated solely on the basis of structural dissimilarity measure at the level of domain folds was found to cluster functionally similar members. This clustering also reflects an independent evolution of the two domains in bicupins. Close examination of structural superposition of members across various functional clusters reveals structural variations in regions that not only form the active site pocket but are also involved in interaction with another domain in the same polypeptide or in the oligomer. Conclusions/Significance: Structure-based phylogeny of cupins can influence identification of functions of proteins of yet unknown function with cupin fold. This approach can be extended to other proteins with a common fold that show high evolutionary divergence. This approach is expected to have an influence on the function annotation in structural genomics initiatives.

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Partitional clustering algorithms, which partition the dataset into a pre-defined number of clusters, can be broadly classified into two types: algorithms which explicitly take the number of clusters as input and algorithms that take the expected size of a cluster as input. In this paper, we propose a variant of the k-means algorithm and prove that it is more efficient than standard k-means algorithms. An important contribution of this paper is the establishment of a relation between the number of clusters and the size of the clusters in a dataset through the analysis of our algorithm. We also demonstrate that the integration of this algorithm as a pre-processing step in classification algorithms reduces their running-time complexity.