33 resultados para structured pseudospectrum

em Université de Lausanne, Switzerland


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Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

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The neutral rate of allelic substitution is analyzed for a class-structured population subject to a stationary stochastic demographic process. The substitution rate is shown to be generally equal to the effective mutation rate, and under overlapping generations it can be expressed as the effective mutation rate in newborns when measured in units of average generation time. With uniform mutation rate across classes the substitution rate reduces to the mutation rate.

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In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

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Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

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Studying patterns of species distributions along elevation gradients is frequently used to identify the primary factors that determine the distribution, diversity and assembly of species. However, despite their crucial role in ecosystem functioning, our understanding of the distribution of below-ground fungi is still limited, calling for more comprehensive studies of fungal biogeography along environmental gradients at various scales (from regional to global). Here, we investigated the richness of taxa of soil fungi and their phylogenetic diversity across a wide range of grassland types along a 2800 m elevation gradient at a large number of sites (213), stratified across a region of the Western Swiss Alps (700 km(2)). We used 454 pyrosequencing to obtain fungal sequences that were clustered into operational taxonomic units (OTUs). The OTU diversity-area relationship revealed uneven distribution of fungal taxa across the study area (i.e. not all taxa are everywhere) and fine-scale spatial clustering. Fungal richness and phylogenetic diversity were found to be higher in lower temperatures and higher moisture conditions. Climatic and soil characteristics as well as plant community composition were related to OTU alpha, beta and phylogenetic diversity, with distinct fungal lineages suggesting distinct ecological tolerances. Soil fungi, thus, show lineage-specific biogeographic patterns, even at a regional scale, and follow environmental determinism, mediated by interactions with plants.

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OBJECTIVES: After structured treatment interruption (STI) of treatment for HIV-1, a fraction of patients maintain suppressed viral loads. Prospective identification of such patients might improve HIV-1 treatment, if selected patients are offered STI. METHODS: We analysed the effect of previously identified genetic modulators of HIV-1 disease progression on patients' ability to suppress viral replication after STI. Polymorphisms in the genes killer cell immunoglobulin-like receptor 3DLI (KIR3DL1)/KIR3DS1, human leucocyte antigen B (HLA-B) and HLA Complex P5 (HCP5), and a polymorphism affecting HLA-C surface expression were analysed in 130 Swiss HIV Cohort Study patients undergoing STI. Genotypes were correlated with viral load levels after STI. RESULTS: We observed a statistically significant reduction in viral load after STI in carriers of HLA-B alleles containing either the Bw480Thr or the Bw480Ile epitope (mean adjusted effect on post-STI viral load: -0.82 log HIV-1 RNA copies/ml, P < 0.001; and -1.12 log copies/ml, P < 0.001, respectively). No significant effects were detected for the other polymorphisms analysed. The likelihood of being able to control HIV-1 replication using a prespecified cut-off (viral load increase < 1000 copies/ml) increased from 39% in Bw4-negative patients to 53% in patients carrying Bw4-80Thr, and to 65% in patients carrying Bw4-80Ile (P = 0.02). CONCLUSIONS: These data establish a significant impact of HLA-Bw4 on the control of viral replication after STI.

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Here we present a processing route to produce multi-structured ceramic foams based on the combination of particle-stabilized foams with polymeric sponges to produce positive and negative templating structures. Polyester sponges are infiltrated with freshly produced calcium aluminate alumina foams and upon sintering either positive templating structures are produced when wetting the sponges, or negative templating foams with a percolating pore network are obtained when completely filling the sponges. Additionally, by combining different layers of these particle-stabilized foam infiltrated sponges, various different structures can be produced, including sandwich structures, pore size gradients, and ceramic bone-like structures applying to different types of bone. The particle-stabilized foams used were in situ self-hardening calcium aluminate cement enriched alumina foams to obtain crack-free samples with pore interconnections and tailorable pore sizes.

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Animals can often coordinate their actions to achieve mutually beneficial outcomes. However, this can result in a social dilemma when uncertainty about the behavior of partners creates multiple fitness peaks. Strategies that minimize risk ("risk dominant") instead of maximizing reward ("payoff dominant") are favored in economic models when individuals learn behaviors that increase their payoffs. Specifically, such strategies are shown to be "stochastically stable" (a refinement of evolutionary stability). Here, we extend the notion of stochastic stability to biological models of continuous phenotypes at a mutation-selection-drift balance. This allows us to make a unique prediction for long-term evolution in games with multiple equilibria. We show how genetic relatedness due to limited dispersal and scaled to account for local competition can crucially affect the stochastically-stable outcome of coordination games. We find that positive relatedness (weak local competition) increases the chance the payoff dominant strategy is stochastically stable, even when it is not risk dominant. Conversely, negative relatedness (strong local competition) increases the chance that strategies evolve that are neither payoff nor risk dominant. Extending our results to large multiplayer coordination games we find that negative relatedness can create competition so extreme that the game effectively changes to a hawk-dove game and a stochastically stable polymorphism between the alternative strategies evolves. These results demonstrate the usefulness of stochastic stability in characterizing long-term evolution of continuous phenotypes: the outcomes of multiplayer games can be reduced to the generic equilibria of two-player games and the effect of spatial structure can be analyzed readily.

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The populations of parasites and infectious agents are most of the time structured in complex hierarchy that lies beyond the classical nested design described by Wright's F-statistics (F(IS), F(ST) and F(IT)). In this note we propose a user-friendly step-by-step notice for using recent software (HierFstat) that computes and test fixation indices for any hierarchical structure. We add some tricks and tips for some special data kind (haploid, single locus), some other procedure (bootstrap over loci) and how to handle crossed factors.

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Cet article est un compte-rendu du colloque "Evolution in Structured Population", tenu du 14 au 16 Septembre 1994 à l'Université de Lausanne. Consacré aux causes écologiques et conséquences évolutives d'horizons divers (zoologie, botanique, anthropologie, mathématiques), utilisant des approches variées, aussi bien empiriques que théoriques. Plusieurs exemples concrets de structurations génétiques de populations naturelles ont été documentés, et leurs causes analysées. Celles-ci sont variées, certaines étant extrinsèques à la biologie des espèces concernées (distances géographique, barrières écologiques, etc), d'autres intrinsèques (stratégies de reproduction, mutations chromosomiques). Les outils quantitatifs les plus largement utilisés pour analyser ces structures restent les F-statistiques de Whright; elles ont néanmoins fait l'objet de plusieurs critiques: d'une part, elles n'exploitent pas toute l'information disponible (certains orateurs ont d'ailleurs proposé diverses améliorations dans ce sens); d'autre part, les hypothèses qui sous-tendent leur interprétation conventionelle (en particulier l'hypothèse de populations à l'équilibre) sont régulièrement violées. Plusieurs des travaux présentés se sont précisément intéressés aux situations de déséquilibre et à leurs conséquences sur la dynamique et l'évolution des populations. Parmi celles ci: l'effet d'extinctions démiques sur les stratégies de dispersion des organismes et la structure génétique de leurs métapopulations, l'inadéquation du modèle classique de métapopulation, dit modèle en île (les modèles de diffusion ou de "pas japonais" (stepping stone) semblent généralement préférables), et le rôle de la "viscosité" des populations, en particulier en relation avec la sélection de parentèle et l'évolution de structures sociales. Le rôle important d'événements historiques sur les structures actuelles a été souligné, notamment dans le cadre de contacts secondaires entre populations hautement différenciées, leur introgression possible et la biogéographie de taxons vicariants. Parmi les problèmes récurrents notés: l'identification de l'unité panmictique, l'échelle de mesure spatiale appropriée, et les difficulté d'estimation des taux de migration et de flux de gènes. Plusieurs auteurs ont relevé la nécessité d'études biologiques de détail: les structures génétiques n'ont d'intérêt que dans la mesure où elles peuvent être situées dans un contexte écologique et évolutif précis. Ce point a été largement illustré dans le cadre des realtions entre structures génétiques et stratégies de reproduction/dispersion.

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When individuals in a population can acquire traits through learning, each individual may express a certain number of distinct cultural traits. These traits may have been either invented by the individual himself or acquired from others in the population. Here, we develop a game theoretic model for the accumulation of cultural traits through individual and social learning. We explore how the rates of innovation, decay, and transmission of cultural traits affect the evolutionary stable (ES) levels of individual and social learning and the number of cultural traits expressed by an individual when cultural dynamics are at a steady-state. We explore the evolution of these phenotypes in both panmictic and structured population settings. Our results suggest that in panmictic populations, the ES level of learning and number of traits tend to be independent of the social transmission rate of cultural traits and is mainly affected by the innovation and decay rates. By contrast, in structured populations, where interactions occur between relatives, the ES level of learning and the number of traits per individual can be increased (relative to the panmictic case) and may then markedly depend on the transmission rate of cultural traits. This suggests that kin selection may be one additional solution to Rogers's paradox of nonadaptive culture.

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Geographical body size variation has long interested evolutionary biologists, and a range of mechanisms have been proposed to explain the observed patterns. It is considered to be more puzzling in ectotherms than in endotherms, and integrative approaches are necessary for testing non-exclusive alternative mechanisms. Using lacertid lizards as a model, we adopted an integrative approach, testing different hypotheses for both sexes while incorporating temporal, spatial, and phylogenetic autocorrelation at the individual level. We used data on the Spanish Sand Racer species group from a field survey to disentangle different sources of body size variation through environmental and individual genetic data, while accounting for temporal and spatial autocorrelation. A variation partitioning method was applied to separate independent and shared components of ecology and phylogeny, and estimated their significance. Then, we fed-back our models by controlling for relevant independent components. The pattern was consistent with the geographical Bergmann's cline and the experimental temperature-size rule: adults were larger at lower temperatures (and/or higher elevations). This result was confirmed with additional multi-year independent data-set derived from the literature. Variation partitioning showed no sex differences in phylogenetic inertia but showed sex differences in the independent component of ecology; primarily due to growth differences. Interestingly, only after controlling for independent components did primary productivity also emerge as an important predictor explaining size variation in both sexes. This study highlights the importance of integrating individual-based genetic information, relevant ecological parameters, and temporal and spatial autocorrelation in sex-specific models to detect potentially important hidden effects. Our individual-based approach devoted to extract and control for independent components was useful to reveal hidden effects linked with alternative non-exclusive hypothesis, such as those of primary productivity. Also, including measurement date allowed disentangling and controlling for short-term temporal autocorrelation reflecting sex-specific growth plasticity.

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Adaptive dynamics shows that a continuous trait under frequency dependent selection may first converge to a singular point followed by spontaneous transition from a unimodal trait distribution into a bimodal one, which is called "evolutionary branching". Here, we study evolutionary branching in a deme-structured population by constructing a quantitative genetic model for the trait variance dynamics, which allows us to obtain an analytic condition for evolutionary branching. This is first shown to agree with previous conditions for branching expressed in terms of relatedness between interacting individuals within demes and obtained from mutant-resident systems. We then show this branching condition can be markedly simplified when the evolving trait affect fecundity and/or survival, as opposed to affecting population structure, which would occur in the case of the evolution of dispersal. As an application of our model, we evaluate the threshold migration rate below which evolutionary branching cannot occur in a pairwise interaction game. This agrees very well with the individual-based simulation results.