840 resultados para Evolutionary clustering
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The study of the Schistosoma mansoni genome, one of the etiologic agents of human schistosomiasis, is essential for a better understanding of the biology and development of this parasite. In order to get an overview of all S. mansoni catalogued gene sequences, we performed a clustering analysis of the parasite mRNA sequences available in public databases. This was made using softwares PHRAP and CAP3. The consensus sequences, generated after the alignment of cluster constituent sequences, allowed the identification by database homology searches of the most expressed genes in the worm. We analyzed these genes and looked for a correlation between their high expression and parasite metabolism and biology. We observed that the majority of these genes is related to the maintenance of basic cell functions, encoding genes whose products are related to the cytoskeleton, intracellular transport and energy metabolism. Evidences are presented here that genes for aerobic energy metabolism are expressed in all the developmental stages analyzed. Some of the most expressed genes could not be identified by homology searches and may have some specific functions in the parasite.
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SummaryGene duplication and neofunctidnalization are important processes in the evolution of phenotypic complexity. They account for important evolutionary novelties that confer ecological adaptation, such as the major histocompatibility complex (MHC), a multigene family with a central role in vertebrates' adaptive immune system. Multigene families, which evolved in large part through duplication, represent promising systems to study the still strongly depbated relative roles of neutral and adaptive processes in the evolution of phenotypic complexity. Detailed knowledge on ecological function and a well-characterized evolutionary history place the mammals' MHC amongst ideal study systems. However mammalian MHCs usually encompass several million base pairs and hold a large number of functional and non-functional duplicate genes, which makes their study complex. Avian MHCs on the other hand are usually way more compact, but the reconstruction of. their evolutionary history has proven notoriously difficult. However, no focused attempt has been undertaken so far to study the avian MHC evolutionary history in a broad phylogenetic context and using adequate gene regions.In the present PhD, we were able to make important contributions to the understanding of the long-term evolution of the avian MHC class II Β (MHCI1B). First, we isolated and characterized MHCIIB genes in barn owl (Tyto alba?, Strigiformes, Tytonidae), a species from an avian lineage in which MHC has not been studied so far. Our results revealed that with only two functional MHCIIB genes the MHC organization of barn owl may be similar to the 'minimal essential' MHC of chicken (Gallus gallus), indicating that simple MHC organization may be ancestral to birds. Taking advantage of the sequence information from barn owl, we studied the evolution of MHCIIB genes in 13 additional species of 'typical' owls (Strigiformes, Strigidae). Phylogenetic analyses revealed that according to their function, in owls the peptide-binding region (PBR) encoding exon 2 and the non-PBR encoding exon 3 evolve by different patterns. Exon 2 exhibited an evolutionary history of positive selection and recombination, while exon 3 traced duplication history and revealed two paralogs evolving divergently from each other in owls, and in a shorebird, the great snipe {Gallinago media). The results from exon 3 were the first ever from birds to demonstrate gene orthology in species that diverged tens of millions of years ago, and strongly questioned whether the taxa studied before provided an adequate picture of avian MHC evolution. In a follow-up study, we aimed at explaining a striking pattern revealed by phylogenetic trees analyzing the owl sequences along with MHCIIB sequences from other birds: One owl paralog (termed DAB1) grouped with sequences of passerines and falcons, while the other (DAB2) grouped with wildfowl, penguins and birds of prey. This could be explained by either a duplication event preceding the evolution of these bird orders, or by convergent evolution of similar sequences in a number of orders. With extensive phylogenetic analyses we were able to show, that indeed a duplication event preceeded the major avian radiation -100 my ago, and that following this duplication, the paralogs evolved under positive selection. Furthermore, we showed that the divergently evolving amino acid residues in the MHCIIB-encoded β-chain potentially interact with the MHCI I α-chain, and that molecular coevolution of the interacting residues may have been involved in the divergent evolution of the MHCIIB paralogs.The findings of this PhD are of particular interest to the understanding of the evolutionary history of the avian MHC and, by providing essential information on long-term gene history in the avian MHC, open promising perspectives for advances in the understanding of the evolution of multigene families in general, and for avian MHC organization in particular. Amongst others I discuss the importance of including protein structure in the phylogenetic study of multigene families, and the roles of ecological versus molecular selection pressures. I conclude by providing a population genomic perspective on avian MHC, which may serve as a basis for future research to investigate the relative roles of neutral processes involving effective population size effects and of adaptation in the evolution of avian MHC diversity and organization.RésuméLa duplication de gènes et leur néo-fonctionnalisation sont des processus importants dans l'évolution de la complexité phénotypique. Ils sont impliqués dans l'apparition d'importantes nouveautés évolutives favorisant l'adaptation écologique, comme c'est le cas pour le complexe majeur d'histocompatibilité
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A population-genetic model indicates that if there is a gene responsible for homosexual behaviour it can readily spread in populations. The model also predicts widespread bisexuality in humans.
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Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.
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Background: Within the Coleoptera, the largest order in the animal kingdom, the exclusively herbivorous Chrysomelidae are recognized as one of the most species rich beetle families. The evolutionary processes that have fueled radiation into the more than thirty-five thousand currently recognized leaf beetle species remain partly unresolved. The prominent role of leaf beetles in the insect world, their omnipresence across all terrestrial biomes and their economic importance as common agricultural pest organisms make this family particularly interesting for studying the mechanisms that drive diversification. Here we specifically focus on two ecotypes of the alpine leaf beetle Oreina speciosissima (Scop.), which have been shown to exhibit morphological differences in male genitalia roughly corresponding to the subspecies Oreina speciosissima sensu stricto and Oreina speciosissima troglodytes. In general the two ecotypes segregate along an elevation gradient and by host plants: Oreina speciosissima sensu stricto colonizes high forb vegetation at low altitude and Oreina speciosissima troglodytes is found in stone run vegetation at higher elevations. Both host plants and leaf beetles have a patchy geographical distribution. Through use of gene sequencing and genome fingerprinting (AFLP) we analyzed the genetic structure and habitat use of Oreina speciosissima populations from the Swiss Alps to examine whether the two ecotypes have a genetic basis. By investigating a wide range of altitudes and focusing on the structuring effect of habitat types, we aim to provide answers regarding the factors that drive adaptive radiation in this phytophagous leaf beetle.Results: While little phylogenetic resolution was observed based on the sequencing of four DNA regions, the topology and clustering resulting from AFLP genotyping grouped specimens according to their habitat, mostly defined by plant associations. A few specimens with intermediate morphologies clustered with one of the two ecotypes or formed separate clusters consistent with habitat differences. These results were discussed in an ecological speciation framework.Conclusions: The question of whether this case of ecological differentiation occurred in sympatry or allopatry remains open. Still, the observed pattern points towards ongoing divergence between the two ecotypes which is likely driven by a recent shift in host plant use.
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The trend of closely related taxa to retain similar environmental preferences mediated by inherited traits suggests that several patterns observed at the community scale originate from longer evolutionary processes. While the effects of phylogenetic relatedness have been previously studied within a single genus or family, lineage-specific effects on the ecological processes governing community assembly have rarely been studied for entire communities or flora. Here, we measured how community phylogenetic structure varies across a wide elevation gradient for plant lineages represented by thirty-five families, using a co-occurrence index and net relatedness index (NRI). We propose a framework that analyses each lineage separately and reveals the trend of ecological assembly at tree nodes. We found prevailing phylogenetic clustering for more ancient nodes and overdispersion in more recent tree nodes. Closely related species may thus rapidly evolve new environmental tolerances to radiate into distinct communities, while older lineages likely retain inherent environmental tolerances to occupy communities in similar environments, either through efficient dispersal mechanisms or the exclusion of older lineages with more divergent environmental tolerances. Our study illustrates the importance of disentangling the patterns of community assembly among lineages to better interpret the ecological role of traits. It also sheds light on studies reporting absence of phylogenetic signal, and opens new perspectives on the analysis of niche and trait conservatism across lineages.
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Self-compatible hermaphroditic organisms that mix self-fertilization and outcrossing are of great interest for investigating the evolution of mating systems. We investigate the evolution of selfing in Lymnaea truncatula, a self-compatible hermaphroditic freshwater snail. We first analyze the consequences of selfing in terms of genetic variability within and among populations and then investigate how these consequences along with the species ecology (harshness of the habitat and parasitism) might govern the evolution of selfing. Snails from 13 localities (classified as temporary or permanent depending on their water availability) were sampled in western Switzerland and genotyped for seven microsatellite loci. F(IS) (estimated on adults) and progeny array analyses (on hatchlings) provided similar selfing rate estimates of 80%. Populations presented a low polymorphism and were highly differentiated (F(ST) = 0.58). Although the reproductive assurance hypothesis would predict higher selfing rate in temporary populations, no difference in selfing level was observed between temporary and permanent populations. However, allelic richness and gene diversity declined in temporary habitats, presumably reflecting drift. Infection levels varied but were not simply related to either estimated population selfing rate or to differences in heterozygosity. These findings and the similar selfing rates estimated for hatchlings and adults suggest that within-population inbreeding depression is low in L. truncatula.
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In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach
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Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process