83 resultados para Approximate Bayesian computation

em Université de Lausanne, Switzerland


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Extensive gene flow between wheat (Triticum sp.) and several wild relatives of the genus Aegilops has recently been detected despite notoriously high levels of selfing in these species. Here, we assess and model the spread of wheat alleles into natural populations of the barbed goatgrass (Aegilops triuncialis), a wild wheat relative prevailing in the Mediterranean flora. Our sampling, based on an extensive survey of 31 Ae. triuncialis populations collected along a 60 km × 20 km area in southern Spain (Grazalema Mountain chain, Andalousia, totalling 458 specimens), is completed with 33 wheat cultivars representative of the European domesticated pool. All specimens were genotyped with amplified fragment length polymorphism with the aim of estimating wheat admixture levels in Ae. triuncialis populations. This survey first confirmed extensive hybridization and backcrossing of wheat into the wild species. We then used explicit modelling of populations and approximate Bayesian computation to estimate the selfing rate of Ae. triuncialis along with the magnitude, the tempo and the geographical distance over which wheat alleles introgress into Ae. triuncialis populations. These simulations confirmed that extensive introgression of wheat alleles (2.7 × 10(-4) wheat immigrants for each Ae. triuncialis resident, at each generation) into Ae. triuncialis occurs despite a high selfing rate (Fis ≈ 1 and selfing rate = 97%). These results are discussed in the light of risks associated with the release of genetically modified wheat cultivars in Mediterranean agrosystems.

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The perceived low levels of genetic diversity, poor interspecific competitive and defensive ability, and loss of dispersal capacities of insular lineages have driven the view that oceanic islands are evolutionary dead ends. Focusing on the Atlantic bryophyte flora distributed across the archipelagos of the Azores, Madeira, the Canary Islands, Western Europe, and northwestern Africa, we used an integrative approach with species distribution modeling and population genetic analyses based on approximate Bayesian computation to determine whether this view applies to organisms with inherent high dispersal capacities. Genetic diversity was found to be higher in island than in continental populations, contributing to mounting evidence that, contrary to theoretical expectations, island populations are not necessarily genetically depauperate. Patterns of genetic variation among island and continental populations consistently fitted those simulated under a scenario of de novo foundation of continental populations from insular ancestors better than those expected if islands would represent a sink or a refugium of continental biodiversity. We, suggest that the northeastern Atlantic archipelagos have played a key role as a stepping stone for transoceanic migrants. Our results challenge the traditional notion that oceanic islands are the end of the colonization road and illustrate the significant role of oceanic islands as reservoirs of novel biodiversity for the assembly of continental floras.

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BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.

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Summary (in English) Computer simulations provide a practical way to address scientific questions that would be otherwise intractable. In evolutionary biology, and in population genetics in particular, the investigation of evolutionary processes frequently involves the implementation of complex models, making simulations a particularly valuable tool in the area. In this thesis work, I explored three questions involving the geographical range expansion of populations, taking advantage of spatially explicit simulations coupled with approximate Bayesian computation. First, the neutral evolutionary history of the human spread around the world was investigated, leading to a surprisingly simple model: A straightforward diffusion process of migrations from east Africa throughout a world map with homogeneous landmasses replicated to very large extent the complex patterns observed in real human populations, suggesting a more continuous (as opposed to structured) view of the distribution of modern human genetic diversity, which may play a better role as a base model for further studies. Second, the postglacial evolution of the European barn owl, with the formation of a remarkable coat-color cline, was inspected with two rounds of simulations: (i) determine the demographic background history and (ii) test the probability of a phenotypic cline, like the one observed in the natural populations, to appear without natural selection. We verified that the modern barn owl population originated from a single Iberian refugium and that they formed their color cline, not due to neutral evolution, but with the necessary participation of selection. The third and last part of this thesis refers to a simulation-only study inspired by the barn owl case above. In this chapter, we showed that selection is, indeed, effective during range expansions and that it leaves a distinguished signature, which can then be used to detect and measure natural selection in range-expanding populations. Résumé (en français) Les simulations fournissent un moyen pratique pour répondre à des questions scientifiques qui seraient inabordable autrement. En génétique des populations, l'étude des processus évolutifs implique souvent la mise en oeuvre de modèles complexes, et les simulations sont un outil particulièrement précieux dans ce domaine. Dans cette thèse, j'ai exploré trois questions en utilisant des simulations spatialement explicites dans un cadre de calculs Bayésiens approximés (approximate Bayesian computation : ABC). Tout d'abord, l'histoire de la colonisation humaine mondiale et de l'évolution de parties neutres du génome a été étudiée grâce à un modèle étonnement simple. Un processus de diffusion des migrants de l'Afrique orientale à travers un monde avec des masses terrestres homogènes a reproduit, dans une très large mesure, les signatures génétiques complexes observées dans les populations humaines réelles. Un tel modèle continu (opposé à un modèle structuré en populations) pourrait être très utile comme modèle de base dans l'étude de génétique humaine à l'avenir. Deuxièmement, l'évolution postglaciaire d'un gradient de couleur chez l'Effraie des clocher (Tyto alba) Européenne, a été examiné avec deux séries de simulations pour : (i) déterminer l'histoire démographique de base et (ii) tester la probabilité qu'un gradient phénotypique, tel qu'observé dans les populations naturelles puisse apparaître sans sélection naturelle. Nous avons montré que la population actuelle des chouettes est sortie d'un unique refuge ibérique et que le gradient de couleur ne peux pas s'être formé de manière neutre (sans l'action de la sélection naturelle). La troisième partie de cette thèse se réfère à une étude par simulations inspirée par l'étude de l'Effraie. Dans ce dernier chapitre, nous avons montré que la sélection est, en effet, aussi efficace dans les cas d'expansion d'aire de distribution et qu'elle laisse une signature unique, qui peut être utilisée pour la détecter et estimer sa force.

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The use of molecular data to reconstruct the history of divergence and gene flow between populations of closely related taxa represents a challenging problem. It has been proposed that the long-standing debate about the geography of speciation can be resolved by comparing the likelihoods of a model of isolation with migration and a model of secondary contact. However, data are commonly only fit to a model of isolation with migration and rarely tested against the secondary contact alternative. Furthermore, most demographic inference methods have neglected variation in introgression rates and assume that the gene flow parameter (Nm) is similar among loci. Here, we show that neglecting this source of variation can give misleading results. We analysed DNA sequences sampled from populations of the marine mussels, Mytilus edulis and M. galloprovincialis, across a well-studied mosaic hybrid zone in Europe and evaluated various scenarios of speciation, with or without variation in introgression rates, using an Approximate Bayesian Computation (ABC) approach. Models with heterogeneous gene flow across loci always outperformed models assuming equal migration rates irrespective of the history of gene flow being considered. By incorporating this heterogeneity, the best-supported scenario was a long period of allopatric isolation during the first three-quarters of the time since divergence followed by secondary contact and introgression during the last quarter. By contrast, constraining migration to be homogeneous failed to discriminate among any of the different models of gene flow tested. Our simulations thus provide statistical support for the secondary contact scenario in the European Mytilus hybrid zone that the standard coalescent approach failed to confirm. Our results demonstrate that genomic variation in introgression rates can have profound impacts on the biological conclusions drawn from inference methods and needs to be incorporated in future studies.

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Genome-wide scans of genetic differentiation between hybridizing taxa can identify genome regions with unusual rates of introgression. Regions of high differentiation might represent barriers to gene flow, while regions of low differentiation might indicate adaptive introgression-the spread of selectively beneficial alleles between reproductively isolated genetic backgrounds. Here we conduct a scan for unusual patterns of differentiation in a mosaic hybrid zone between two mussel species, Mytilus edulis and M. galloprovincialis. One outlying locus, mac-1, showed a characteristic footprint of local introgression, with abnormally high frequency of edulis-derived alleles in a patch of M. galloprovincialis enclosed within the mosaic zone, but low frequencies outside of the zone. Further analysis of DNA sequences showed that almost all of the edulis allelic diversity had introgressed into the M. galloprovincialis background in this patch. We then used a variety of approaches to test the hypothesis that there had been adaptive introgression at mac-1. Simulations and model fitting with maximum-likelihood and approximate Bayesian computation approaches suggested that adaptive introgression could generate a "soft sweep," which was qualitatively consistent with our data. Although the migration rate required was high, it was compatible with the functioning of an effective barrier to gene flow as revealed by demographic inferences. As such, adaptive introgression could explain both the reduced intraspecific differentiation around mac-1 and the high diversity of introgressed alleles, although a localized change in barrier strength may also be invoked. Together, our results emphasize the need to account for the complex history of secondary contacts in interpreting outlier loci.

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Whether or not species participating in specialized and obligate interactions display similar and simultaneous demographic variations at the intraspecific level remains an open question in phylogeography. In the present study, we used the mutualistic nursery pollination occurring between the European globeflower Trollius europaeus and its specialized pollinators in the genus Chiastocheta as a case study. Explicitly, we investigated if the phylogeographies of the pollinating flies are significantly different from the expectation under a scenario of plant-insect congruence. Based on a large-scale sampling, we first used mitochondrial data to infer the phylogeographical histories of each fly species. Then, we defined phylogeographical scenarios of congruence with the plant history, and used maximum likelihood and Bayesian approaches to test for plant-insect phylogeographical congruence for the three Chiastocheta species. We show that the phylogeographical histories of the three fly species differ. Only Chiastocheta lophota and Chiastocheta dentifera display strong spatial genetic structures, which do not appear to be statistically different from those expected under scenarios of phylogeographical congruence with the plant. The results of the present study indicate that the fly species responded in independent and different ways to shared evolutionary forces, displaying varying levels of congruence with the plant genetic structure

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Gradients of variation-or clines-have always intrigued biologists. Classically, they have been interpreted as the outcomes of antagonistic interactions between selection and gene flow. Alternatively, clines may also establish neutrally with isolation by distance (IBD) or secondary contact between previously isolated populations. The relative importance of natural selection and these two neutral processes in the establishment of clinal variation can be tested by comparing genetic differentiation at neutral genetic markers and at the studied trait. A third neutral process, surfing of a newly arisen mutation during the colonization of a new habitat, is more difficult to test. Here, we designed a spatially explicit approximate Bayesian computation (ABC) simulation framework to evaluate whether the strong cline in the genetically based reddish coloration observed in the European barn owl (Tyto alba) arose as a by-product of a range expansion or whether selection has to be invoked to explain this colour cline, for which we have previously ruled out the actions of IBD or secondary contact. Using ABC simulations and genetic data on 390 individuals from 20 locations genotyped at 22 microsatellites loci, we first determined how barn owls colonized Europe after the last glaciation. Using these results in new simulations on the evolution of the colour phenotype, and assuming various genetic architectures for the colour trait, we demonstrate that the observed colour cline cannot be due to the surfing of a neutral mutation. Taking advantage of spatially explicit ABC, which proved to be a powerful method to disentangle the respective roles of selection and drift in range expansions, we conclude that the formation of the colour cline observed in the barn owl must be due to natural selection.

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Sex chromosomes are expected to evolve suppressed recombination, which leads to degeneration of the Y and heteromorphism between the X and Y. Some sex chromosomes remain homomorphic, however, and the factors that prevent degeneration of the Y in these cases are not well understood. The homomorphic sex chromosomes of the European tree frogs (Hyla spp.) present an interesting paradox. Recombination in males has never been observed in crossing experiments, but molecular data are suggestive of occasional recombination between the X and Y. The hypothesis that these sex chromosomes recombine has not been tested statistically, however, nor has the X-Y recombination rate been estimated. Here, we use approximate Bayesian computation coupled with coalescent simulations of sex chromosomes to quantify X-Y recombination rate from existent data. We find that microsatellite data from H. arborea, H. intermedia and H. molleri support a recombination rate between X and Y that is significantly different from zero. We estimate that rate to be approximately 10(5) times smaller than that between X chromosomes. Our findings support the notion that very low recombination rate may be sufficient to maintain homomorphism in sex chromosomes.

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Many eukaryote organisms are polyploid. However, despite their importance, evolutionary inference of polyploid origins and modes of inheritance has been limited by a need for analyses of allele segregation at multiple loci using crosses. The increasing availability of sequence data for nonmodel species now allows the application of established approaches for the analysis of genomic data in polyploids. Here, we ask whether approximate Bayesian computation (ABC), applied to realistic traditional and next-generation sequence data, allows correct inference of the evolutionary and demographic history of polyploids. Using simulations, we evaluate the robustness of evolutionary inference by ABC for tetraploid species as a function of the number of individuals and loci sampled, and the presence or absence of an outgroup. We find that ABC adequately retrieves the recent evolutionary history of polyploid species on the basis of both old and new sequencing technologies. The application of ABC to sequence data from diploid and polyploid species of the plant genus Capsella confirms its utility. Our analysis strongly supports an allopolyploid origin of C. bursa-pastoris about 80 000 years ago. This conclusion runs contrary to previous findings based on the same data set but using an alternative approach and is in agreement with recent findings based on whole-genome sequencing. Our results indicate that ABC is a promising and powerful method for revealing the evolution of polyploid species, without the need to attribute alleles to a homeologous chromosome pair. The approach can readily be extended to more complex scenarios involving higher ploidy levels.

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Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.

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Genetic evaluation using animal models or pedigree-based models generally assume only autosomal inheritance. Bayesian animal models provide a flexible framework for genetic evaluation, and we show how the model readily can accommodate situations where the trait of interest is influenced by both autosomal and sex-linked inheritance. This allows for simultaneous calculation of autosomal and sex-chromosomal additive genetic effects. Inferences were performed using integrated nested Laplace approximations (INLA), a nonsampling-based Bayesian inference methodology. We provide a detailed description of how to calculate the inverse of the X- or Z-chromosomal additive genetic relationship matrix, needed for inference. The case study of eumelanic spot diameter in a Swiss barn owl (Tyto alba) population shows that this trait is substantially influenced by variation in genes on the Z-chromosome (sigma(2)(z) = 0.2719 and sigma(2)(a) = 0.4405). Further, a simulation study for this study system shows that the animal model accounting for both autosomal and sex-chromosome-linked inheritance is identifiable, that is, the two effects can be distinguished, and provides accurate inference on the variance components.

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Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.

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Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.

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The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.