Dissertations / Theses on the topic 'Population genetic models'

The theory of probability and stochastic processes is applied to a current issue in population genetics, namely that of genealogy and genetic differentiation in subdivided populations. It is proved that under a reasonable model for reproduction and migration, the ancestral process of a sample from a subdivided population converges weakly, as the subpopulation sizes tend to infinity, to a continuous-time Markov chain called the "structured coalescent". The moment-generating function, the mean and the cond moment of the time since the most recent common ancestor (called the "coalescence time") of a pair of genes are calculated explicitly for a range of models of population structure. The value of Wright's coefficient FST, which serves as a measure of the subpopulation differentiation and which can be related to the coalescence times of pairs of genes sampled within or among subpopulations, is calculated explicitly for various models of population structure. It is shown that the dependence of FST on the mutation rate may be more marked than is generally believed, particularly when gene flow is restricted to an essentially one-dimensional habitat with a large number of subpopulations. Several more general results about genealogy and subpopulation differentiation are proved. Simple relationships are found between moments of within and between population coalescence times. Weighting each subpopulation by its relative size, the asymptotic behaviour of FST at large mutation rates is independent of the details of population structure. Two sets of symmetry conditions on the population structure are found for which the mean coalescence time of a pair of genes from a single subpopulation is independent of the migration rate and equal to that of two individuals from a panmictic population of the same total size. Under graph-theoretic conditions on the population structure, there is a uniform relationship between the FST value of a pair of neighbouring subpopulations, in the limit of zero mutation rate, and the migration rate

The aim of this study is to place a wide variety of two-phenotype frequency-dependent selection models into a unified population-genetic framework. This work is used to illuminate the possible genetic constraints that may exist in such models, and to address the question of evolutionary modification of these constraints. The first part of Chapter 1 synthesizes from the literature a general framework for applying a genetic structure to a simple class of two-phenotype models. It shows that genetic constraints may prevent the population from achieving a predicted phenotypic equilibrium, but the population will equilibrate at a point that is as close as possible to the phenotypic equilibrium. The second part of Chapter 1 goes on to ask whether evolutionary modification of the genetic system might be expected to remove these constraints. Chapter 2 provides an example of the application of the framework developed in Chapter 1. It presents re-analysis of a model for the evolution of social behavior by reciprocation (Brown et al. 1982). The genetic results of Chapter 1 apply to this model without modification. I show that Brown et al. were unnecessarily restrictive in their assumptions about the types of genetic systems that support their conclusions. Chapter 3 discusses some models for the evolution of altruism that do not fit the assumptions of Chapter 1, despite their two-phenotype structure. These models violate the fundamental assumption of Chapter 1, this being the way in which individual fitness is derived from the behavioral fitnesses. The first part is a complete, in-depth analysis of diploid sib-sib kin selection. I show that some results from the basic model can be used, provided the behavioral inclusive fitness functions are substituted for the true behavioral fitnesses. The second part is an analysis of the validity of the concept of behavioral structure, as introduced by Michod and Sanderson (1985). I show that this concept is flawed as a general principle. Chapter 4 extends the basic model to the case of sex-allocation evolution. I show how many of the central results of sex-allocation theory can be derived more simply using a two-phenotype framework.

This dissertation examines aspects of the relationship between connectivity and the development of genetic structure in subdivided coral reef populations using both simulation and algebraic methods. The first chapter develops an object-oriented, individual based method of simulating the dynamics of genes in subdivided populations. The model is then used to investigate how changes to different components of population structure (e.g., connectivity, birth rate, population size) influence genetic structure through the use of autocorrelation analysis. The autocorrelograms also demonstrate how relationships between populations change at different spatial and temporal scales. The second chapter uses discrete multivariate distributions to model the relationship between connectivity, selection and resource use in subdivided populations. The equations provide a stochastic basis for multiple-niche polymorphism through differential resource use, and the role of scale in changing selective weightings is also considered. The third chapter uses matrix equations to study the expected development of genetic structure among Caribbean coral reefs. The results show an expected break between eastern and western portions of the Caribbean, as well as additional nested structure within the Bahamas, the central Caribbean (Jamaica and the reefs of the Nicaraguan Rise) and the Mesoamerican Barrier Reef. The matrix equations provide an efficient means of modeling the development of genetic structure in subdivided populations through time. The fourth chapter uses matrix equations to examine the expected development of genetic structure among Southeast Asian coral reefs. Projecting genetic structure reveals an expected unidirectional connection from the South China Sea into the Coral Triangle region via the Sulu Sea. Larvae appear to be restricted from moving back into the South China Sea by a cyclonic gyre in the Sulu Sea. Additional structure is also evident, including distinct clusters within the Philippines, in the vicinity of the Makassar Strait, in the Flores Sea, and near Halmahera and the Banda Sea. The ability to evaluate the expected development of genetic structure over time in subdivided populations offers a number of potential benefits, including the ability to ascertain the expected direction of gene flow, to delineate natural regions of exchange through clustering, or to identify critical areas for conservation or for managing the spread of invasive material via elasticity analysis.

My thesis addresses a systematic approach to stochastic models in population genetics; in particular, the Wright-Fisher models affected only by the random genetic drift. I used various mathematical methods such as Probability, PDE, and Geometry to answer an important question: \"How do genetic change factors (random genetic drift, selection, mutation, migration, random environment, etc.) affect the behavior of gene frequencies or genotype frequencies in generations?”. In a Hardy-Weinberg model, the Mendelian population model of a very large number of individuals without genetic change factors, the answer is simple by the Hardy-Weinberg principle: gene frequencies remain unchanged from generation to generation, and genotype frequencies from the second generation onward remain also unchanged from generation to generation. With directional genetic change factors (selection, mutation, migration), we will have a deterministic dynamics of gene frequencies, which has been studied rather in detail. With non-directional genetic change factors (random genetic drift, random environment), we will have a stochastic dynamics of gene frequencies, which has been studied with much more interests. A combination of these factors has also been considered. We consider a monoecious diploid population of fixed size N with n + 1 possible alleles at a given locus A, and assume that the evolution of population was only affected by the random genetic drift. The question is that what the behavior of the distribution of relative frequencies of alleles in time and its stochastic quantities are. When N is large enough, we can approximate this discrete Markov chain to a continuous Markov with the same characteristics. In 1931, Kolmogorov first introduced a nice relation between a continuous Markov process and diffusion equations. These equations called the (backward/forward) Kolmogorov equations which have been first applied in population genetics in 1945 by Wright. Note that these equations are singular parabolic equations (diffusion coefficients vanish on boundary). To solve them, we use generalized hypergeometric functions. To know more about what will happen after the first exit time, or more general, the behavior of whole process, in joint work with J. Hofrichter, we define the global solution by moment conditions; calculate the component solutions by boundary flux method and combinatorics method. One interesting property is that some statistical quantities of interest are solutions of a singular elliptic second order linear equation with discontinuous (or incomplete) boundary values. A lot of papers, textbooks have used this property to find those quantities. However, the uniqueness of these problems has not been proved. Littler, in his PhD thesis in 1975, took up the uniqueness problem but his proof, in my view, is not rigorous. In joint work with J. Hofrichter, we showed two different ways to prove the uniqueness rigorously. The first way is the approximation method. The second way is the blow-up method which is conducted by J. Hofrichter. By applying the Information Geometry, which was first introduced by Amari in 1985, we see that the local state space is an Einstein space, and also a dually flat manifold with the Fisher metric; the differential operator of the Kolmogorov equation is the affine Laplacian which can be represented in various coordinates and on various spaces. Dynamics on the whole state space explains some biological phenomena.

Nous présentons une nouvelle méthode pour étudier les relations entre la structure génétique des populations et l'environnement. Cette méthode repose sur des modèles hiérarchiques bayésiens qui utilisent conjointement des données génétiques multi-locus et des données spatiales, environnementales et/ou culturelles. Elle permet d'estimer la structure génétique des populations, d'évaluer ses liens avec des covariables non génétiques, et de projeter la structure génétique des populations en fonction de ces covariables. Dans un premier temps, nous avons appliqué notre approche à des données de génétique humaine pour évaluer le rôle de la géographie et des langages dans la structure génétique des populations amérindiennes. Dans un deuxième temps, nous avons étudié la structure génétique des populations pour 20 espèces de plantes alpines et nous avons projeté les modifications intra spécifiques qui pourront être causées par le réchauffement climatique
We introduce a new method to study the relationships between population genetic structure and environment. This method is based on Bayesian hierarchical models which use both multi-loci genetic data, and spatial, environmental, and/or cultural data. Our method provides the inference of population genetic structure, the evaluation of the relationships between the structure and non-genetic covariates, and the prediction of population genetic structure based on these covariates. We present two applications of our Bayesian method. First, we used human genetic data to evaluate the role of geography and languages in shaping Native American population structure. Second, we studied the population genetic structure of 20 Alpine plant species and we forecasted intra-specific changes in response to global warming. STAR

Les coûts de la reproduction sont un compromis biologique (trade-off ) fondamental en théorie des histoires de vie. Par ce compromis, le succès, pour un organisme, d’un évènement de reproduction réduit sa survie et sa fertilité futures. Pour les écologues, ce trade-off correspond principalement à un compromis physiologique résultant d’un processus d’allocation ayant lieu à chaque instant et au niveau de chaque individu. Au contraire, en démographie évolutive, il est envisagé comme un trade-off génétique découlant du polymorphisme génotypique d’un gène pléiotropique agissant de manière antagoniste sur la reproduction aux jeunes âges et la fitness aux âges élevés. L’étude des mécanismes des coûts de la reproduction, physiologiques et génétiques, de leur possible cohabitation et de leur effets relatifs, croisés et conjoints est le sujet de cette thèse. Un examen attentif de la définition originelle des coûts de la reproduction par Williams (1966), nous permet de construire un modèle théorique des coûts physiologiques intégrant leurs aspects mécaniques et évolutifs. Cette construction nous permet d’induire l’intensité des coûts de la reproduction selon la position d’un organisme sur trois continuums d’histoire de vie: "slow-fast", "income-capital breeders" et "quantity-quality".A partir de la décomposition, par Stearns (1989b), de l’architecture des contraintes d’histoire de vie en trois parties – le niveau génotypique, la structure intermédiaire et le niveau phénotypique – nous étendons notre modèle conceptuel pour y intégrer à la fois des trade-offs physiologiques et génétiques. Cela nous permet d’inférer les effets de l’environnement, de sa variance et de la stochasticité individuelle sur la détectabilité de chaque famille de coûts. La différence entre coûts physiologiques et génétiques se retrouve également dans leur modélisation mathématique. Il est donc nécessaire de développer de nouveaux modèles permettant d’incorporer coûts physiologiques et génétiques. Nous proposons ensuite une méthode vectorielle de construction d’un tel type de modèle, que nous appelons Matrice de Projection de Population Multitrait (MPPM). Ce dernier peut implémenter chaque type de coût en l’intégrant dans la matrice en tant que trait. Nous étendons ensuite aux MPPMs les techniques d’analyse de sensibilité, standards en démographie évolutive, des modèles à un trait aux MPPMs. Surtout, nous décrivons un nouvel outil d’analyse, pertinent en théorie des histoires de vie et en démographie évolutive: la Trait Level Analysis. Elle consiste à comparer des modèles qui partagent les mêmes propriétés asymptotiques. Ceci est rendu possible par le repliement d’une MPPM selon certains traits, une opération qui réduit le nombre de traits du modèle en moyennant ses transitions selon les abondances ergodiques relatives. Ainsi, la Trait Level Analysis permet de mesurer l’importance évolutive des coûts de la reproduction en comparant des modèles implémentant ces coûts, avec des versions ergodiquement équivalentes de ces modèles mais repliées selon les traits supportant les compromis. Nous utilisons des méthodes, classiques et nouvelles, de calculs des moments de la fitness – gradient de sélection, variance du succès reproducteur, variance environnementale – que nous appliquons aux modèles avec coûts et sans coûts afin de mesurer leurs effets démographiques et évolutifs. Nous présentons les effets conjoints des coûts physiologiques et génétiques sur la distribution par âge des taux vitaux d’une population. Nous montrons également comment les coûts physiologiques influencent les deux composants de la sélection efficace, en aplatissant le gradient de sélection d’un côté et en accroissant la taille efficace de la population de l’autre. Enfin, nous démontrons comment l’effet tampon des coûts sur les variances environnementales et démographiques améliore la résilience d’une population soumise aux coûts physiologiques de la reproduction
Costs of reproduction are pervasive in life history theory. Through this constraint, the reproductive effort of an organism at a given time negatively affects its later survival and fertility. For life historians, they correspond mostly to a physiological trade-off that stems from an allocative process, occurring at each time-step, at the level of the individual. For evolutionary demographers, they are essentially about genetic trade-offs, arising from a genetic variance in a pleiotropic gene acting antagonistically on early-age and late-age fitness components. The study, from an evolutionary demographic standpoint, of these mechanisms and of the relative, cross and joint effects of physiological and genetic costs, is the aim of this thesis. The close examination of Williams (1966)’s original definition of the physiological costs of reproduction led us to produce a theoretical design of their apparatus that accounts for both their mechanistic and evolutionary mechanisms. This design allowed us to make predictions with regards to the strength of costs of reproduction for various positions of organisms on three life-history spectra: slow-fast, income-capital breeders and quality-quantity. From Stearns (1989b)’s tryptic architecture of life history trade-offs –that divides their structure into the genotypic level, the intermediate structure and the phenotypic level – we devised a general framework, which models the possible cohabitation of both physiological and genetic costs. From this, we inferred differing detectability patterns of both types of costs according to the environmental conditions, their variance and individual stochasticity. We could also establish that both costs buffer environmental variations, but with varying time windows of effect. Their dissimilarity emerges also from the differences between mathematical projection models specific to each cost. A new family of evolutionary models is therefore required to implement both physiological and genetic trade-offs. We then describe the vector-based construction method for such a model which we call Multitrait Population Projection Matrix (MPPM) and which allows incorporating both types of costs by embedding them as traits into the matrix. We extend the classical sensitivity analysis techniques of evolutionary demography to MPPMs. Most importantly, we present a new analysis tool for both life history and evolutionary demography: the Trait Level Analysis. It consists in comparing pairs of models that share the same asymptotic properties. Such ergodic equivalent matrices are produced by folding, an operation that consists in reducing the number of traits of a multi-trait model, by averaging transitions for the traits folded upon, whilst still preserving the asymptotic flows. The Trait Level Analysis therefore allows, for example, to measure the evolutionary importance of costs of reproduction by comparing models incorporating them with folded versions of these models from which the costs are absent. Using classical and new methods to compute fitness moments – selection gradient, variance in reproductive success, environmental variance - in models with and without the costs, we can show their effects on various demographic and evolutionary measures. We reveal, in this way, the combined effects of genetic and physiological costs on the vital rates of an age-structured population. We also demonstrate how physiological costs affect both components of effective selection, as they flatten the slope of selection gradients and increase the effective size of a population. Finally, we show how their buffering of environmental and demographic variance confer greater resilience to populations experiencing physiological costs of reproduction

Le modèle linéaire mixte a été formalisé il y a plus de 60 ans. Celui-ci permet d'estimer un modèle avec des effets fixes équivalents à ceux du modèle linéaire classique et des effets aléatoires. Ce type de modélisation, d'abord utilisé en génétique animale, est depuis quelques années largement utilisé en génétique humaine. Les utilisations de ce modèle sont nombreuses. En effet, il peut être utilisé en étude de liaison, d'association, pour l'estimation de l'héritabilité ou encore dans la recherche d'empreinte parentale et peut s'adapter à des données familiales ou en population.Le but de mon doctorat est d'exploiter différentes méthodes basées sur les modèles mixtes d'abord sur des données génétiques en population puis sur des données génétiques familiales.Dans un premier temps, nous explorons dans ce manuscrit la théorie des modèles linéaires mixtes et leur utilisation en génétique. Nous adaptons aussi certaines méthodes pour les appliquer à notre recherche. Ce travail a donné lieu au développement informatique d'un package R permettant d'utiliser ces modèles dans le cadre des études génétiques.Dans un deuxième temps, nous utilisons les modèles linéaires mixtes pour l'estimation de l'héritabilité dans une étude en population française, l'étude Trois-Cités. Nous disposons dans cette étude des génotypes des tag-SNPs habituellement utilisés dans les études d'association ainsi que des lieux de naissance et de plusieurs traits anthropométriques quantitatifs tels que la taille. L'objectif est alors d'étudier la présence et la prise en compte dans l'analyse de stratification de population dans cette étude. Dans ce manuscrit, nous analysons les coordonnées géographiques des lieux de naissance. Nos résultats mettent en évidence la difficulté pour corriger correctement la stratification de population avec les méthodes classiques dans certains cas. Nous analysons ensuite les traits anthropométriques en particulier la taille dont nous estimons l'héritabilité à 39% dans la population de l'étude Trois-Cités.Dans la dernière partie de ce manuscrit, nous nous concentrons sur les données familiales. Nous montrons le gain d’information que peut apporter ce type de données dans la recherche des variants causaux. Puis, nous explorons l'utilisation des modèles mixtes sur des données familiales en appliquant certaines des méthodes associées dans la recherche de signaux d'association pour la Sclérose en Plaques, une maladie auto-immune, en utilisant un échantillon d’une centaine de familles nucléaires avec au moins deux germains atteints. Nous avons alors mis en évidence l’inadéquation des méthodes classiques basées sur les modèles mixtes à ce type de données. Afin de mieux comprendre ce biais de sélection et de le corriger, plus d’investigations sont nécessaires
Linear mixed models have been formalized 60 years ago. These models allow to estimate fixed effects, as in the linear models, and random effects. First used in animal genetics, this type of modelling have been widely used in human genetics since a few years. Mixed models can be used in many genetic analysis; linkage and association studies, heritability estimations and Parent-of Origin effects studies for population or familial data.My thesis’ aim is to investigate mixed models based methods, for genetic data in population and, for familial genetic data.In the first part of my thesis, we investigated the mixed model statistical theory and their multiple uses in human genetics. We also adapted methods for our own work. An R package have been created which permits to analyze genetic data in R environment with mixed models.In a second part, we applied mixed models on Three-Cities data, a French longitudinal study, to estimate heritability of several traits. For this analysis, we have access to tag-SNPs typically used in genome-wide association studies, birthplaces and several anthropometric traits. The aim of our study is to analyze presence of population stratification and evaluate methods to correct it. In the one hand, we analyzed birthplace geographic coordinates and showed that the correction for population stratification by classical method is not sufficient in this case. In the other hand, we analyzed anthropometric traits, in particular the height for which we estimated heritability to 39% in Three-Cities study population.In the last part, we focused on family data. In a first work, we exploited familial information in causal variant research. In a second work, we explored mixed models uses for familial data, in particular association study, on Multiple Sclerosis data. We showed that mixed model methods can not be used without taking account the ascertainment scheme: in our data, all families have at least two affected sibs. To understand and correct this phenomenon, more investigations are needed

The study of DNA sequence variation is a powerful approach to study genome evolution, and to reconstruct evolutionary histories of species. In this thesis, I have studied genetic variation in the fungus Neurospora tetrasperma and other closely related Neurospora species. I have focused on N. tetrasperma in my research because it has large regions of suppressed recombination on its mating-type chromosomes, had undergone a recent change in reproductive mode and is composed of multiple reproductively isolated lineages. Using DNA sequence data from a large sample set representing multiple species of Neurospora I estimated that N. tetrasperma evolved ~1 million years ago and that it is composed of at least 10 lineages. My analysis of the type of asexual spores produced using newly described N. tetrasperma populations in Britain revealed that lineages differ considerably in life history characteristics that may have consequences for their evolution. A comparative genomic analysis using three genomes of N. tetrasperma and the genome of N. crassa revealed that the mat a chromosomes in the lineages examine have been introgressed from other Neurospora species and that this introgression has reduced levels of molecular degeneration on the mating-type chromosomes. Finally, I generated a population genomic dataset composed of 92 N. tetrasperma genomes and two genomes of other Neurospora species. Analysis of these genomes revealed that all strains of N. tetrasperma have large regions of suppressed recombination on their mating-type chromosomes ranging from 69-84% of the chromosome and that the extent of divergence between mating-type chromosomes within lineages varies greatly (from 1.3 to 3.2%). I concluded that the source of this great divergence mating-type chromosome is large-scale introgression from other Neurospora species, and that these introgressed tracts have become fixed within N. tetrasperma lineages. I also discovered that genes within non-recombining introgressed regions of the mating-type chromosome have severely reduced levels of genetic variation as compared to the autosomes, and exhibit signatures of reduced molecular degeneration. My analysis of variation in coding regions revealed that positive selection on the introgressed regions has resulted in the removal of deleterious mutations and is responsible for the reductions in molecular degeneration observed.

Parametric excitation and dispersal are added to discrete-time population models. Discrete-time models for growth with dispersal share many of the attributes of reaction-diffusion equations. At the same time, these models readily exhibit period doubling and chaos. Large parametric excitation (seasonality) is inevitably destabilizing, but mild seasonality may have a pronounced stabilizing effect. Seasonality also allows for the coexistence of alternative stable states (equilibria, cycles, chaos). Many examples are presented.

Nous introduisons un ensemble de modèles à facteurs latents dédié à la génomique du paysage et aux tests d'associations écologiques. Cela comprend des méthodes statistiques pour corriger des effets d'autocorrélation spatiale sur les cartes de composantes principales en génétique des populations (spFA), des méthodes pour estimer rapidement et efficacement les coefficients de métissage individuel à partir de matrices de génotypes de grande taille et évaluer le nombre de populations ancestrales (sNMF) et des méthodes pour identifier les polymorphismes génétiques qui montrent de fortes corrélations avec des gradients environnementaux ou avec des variables utilisées comme des indicateurs pour des pressions écologiques (LFMM). Nous avons aussi développé un ensemble de logiciels libres associés à ces méthodes, basés sur des programmes optimisés en C qui peuvent passer à l'échelle avec la dimension de très grand jeu de données, afin d'effectuer des analyses de structures de population et des cribles génomiques pour l'adaptation locale
We introduce a set of latent factor models dedicated to landscape genomics and ecological association tests. It includes statistical methods for correcting principal component maps for effects of spatial autocorrelation (spFA); methods for estimating ancestry coefficients from large genotypic matrices and evaluating the number of ancestral populations (sNMF); and methods for identifying genetic polymorphisms that exhibit high correlation with some environmental gradient or with the variables used as proxies for ecological pressures (LFMM). We also developed a set of open source softwares associated with the methods, based on optimized C programs that can scale with the dimension of very large data sets, to run analyses of population structure and genome scans for local adaptation

This thesis aims to develop and implement population genetic models that are directly interpretable in terms of events such as population fission and admixture. Two competing methods of approximating the Wright--Fisher model of genetic drift are critically examined, one due to Balding and Nichols and another to Nicholson and colleagues. The model of population structure consisting of all present-day subpopulations arising from a common ancestral population at a single fission event (first described by Nicholson et al.) is reimplemented and applied to single-nucleotide polymorphism data from the HapMap project. This Bayesian hierarchical model is then elaborated to allow general phylogenetic representations of the genetic heritage of present-day subpopulations and the performance of this model is assessed on simulated and HapMap data. The drift model of Balding and Nichols is found to be problematic for use in this context as the need for allele fixation to be modelled becomes apparent. The model is then further developed to allow the inclusion of admixture events. This new model is, again, demonstrated using HapMap data and its performance compared to that of the TreeMix model of Pickrell and Pritchard, which is also critically evaluated.

The long-term success of an introduced population depends on the ecological conditions in its new environment, but is also influenced by stochasticity. This is particularly clear in the first stage of an invasion when the population is still small and either goes extinct quickly or establishes a self-sustaining population. Once established, some populations grow and spread spatially, with potential impacts on native communities and ecosystems. The role of stochasticity during these later invasion stages remains unclear. Furthermore, little is known about the population genetic and evolutionary consequences of stochastic invasion trajectories. With this dissertation, I would like to contribute to a stochastic eco-genetic theory of the entire invasion process—from the first introduction up to potential impacts. The overarching questions in this dissertation are: a) How does a population’s movement through the invasion process depend on ecological factors influencing its average growth rate? b) How does it depend on factors influencing the stochastic variability in the population dynamics? c) How much genetic diversity do introduced populations harbor on average upon reaching a certain point in the invasion process? d) To what extent can the population-genetic consequences of invasion trajectories feed back onto the population dynamics? Together with my advisors and coauthors, I have conducted four studies, each addressing two or more of these questions for specific ecological scenarios. We employ several types of stochastic models: Markov chains, Markov processes, their diffusion approximations, and coalescent-like genealogy simulations. In Chapter 1 (Wittmann et al., 2013a, appeared in Theoretical Population Biology), we focus on a factor influencing the introduced population’s average growth rate: the intensity of competition with an ecologically similar native species. Our results indicate that the expected time until the introduced species drives the native competitor to extinction is smallest for intermediate competition intensity. This phenomenon results from the opposing effects of competition intensity at different points of the invasion process: On the one hand, intense competition renders the establishment of the introduced population more difficult; on the other hand, it facilitates the later exclusion of the native species. In Chapter 1, we also investigate to what extent the native species’ extinction is accelerated if a reduction in population size entails a reduction in genetic diversity and thus a reduced ability to adapt to a changing environment. We find this eco-genetic feedback to be particularly strong at small competition intensities. In Chapter 2 (Wittmann et al., 2013b, in press at Oikos), we compare introduction regimes with the same average number of individuals introduced per time unit, but with a different temporal distribution. Relative to regimes with many small introduction events, regimes with few large introduction events generate more variability in population-size trajectories. We show that this variability helps introduced populations to overcome difficult stages in the invasion process (those with a negative average growth rate), but is disadvantageous during easy stages (those with a positive average growth rate). In the light of our results, we can reinterpret three published data sets on invasion success under different introduction regimes. In Chapters 3 and 4 (Wittmann et al., 2013c,d), we examine levels of genetic diversity in populations that have successfully overcome a strong demographic Allee effect. In this ecological scenario, the average population growth rate is negative below a certain critical population size and positive above, such that the first stage in the invasion process is difficult and the second one easy. In Chapter 3, we assume Poisson-distributed offspring numbers. We show that compared to successful populations without an Allee effect, successful Allee-effect populations are expected to harbor either more or less genetic diversity, depending on the magnitude of typical founder population sizes relative to the critical population size. Part of the explanation is that, counter-intuitively, successful Allee-effect populations escape particularly fast from the range of small population sizes where genetic drift is strongest. In Chapter 3, we also identify conditions under which the critical population size can be estimated from genetic data. In Chapter 4, we consider a range of offspring-number models leading to either more or less variability in population dynamics than the Poisson model. For a fixed founder population size, we observe that the Allee effect has a negative influence on genetic diversity for small amounts of variability, but a positive influence for large amounts of variability. We show that the differences between our various offspring-number models are so substantial that they cannot be resolved by rescaling the parameters of the Poisson model. Taken together, these results offer some general conclusions with respect to the four main questions raised above. a) How fast an introduced population completes the invasion process is mainly determined by the presence and severity of difficult stages. Therefore, an ecological change promotes invasion success if it lessens such difficult stages. b) From the perspective of the introduced population, variability is advantageous during difficult but not during easy stages of the invasion process. c) Because the strength of genetic drift depends on population size, a key to understanding the population genetic consequences of invasion trajectories is to consider how much time the population of interest spends in different population-size ranges. d) Feedbacks between a reduction in population size and a loss of genetic diversity are strongest in ecological scenarios where the population of interest spends considerable time at small population sizes. Some of the most striking results in this dissertation cannot be understood from a deterministic point of view, but only when considering stochasticity. Thus, stochasticity does not just add “noise” to some average outcome, but can qualitatively change the behavior of biological systems.
Der langfristige Erfolg einer eingeführten Population hängt von den ökologischen Bedingungen in ihrer neuen Umgebung ab, aber auch vom Zufall. Besonders offensichtlich ist die wichtige Rolle des Zufalls für kleine Populationen im Anfangsstadium einer Invasion. In diesem Stadium entscheidet sich, ob die eingeführte Population nach kurzer Zeit ausstirbt oder sich dauerhaft etablieren kann. Manche etablierten Populationen wachsen dann weiter und breiten sich räumlich aus, zum Teil mit schwerwiegenden Folgen für einheimische Gemeinschaften und Ökosysteme. Bislang ist nicht klar, welche Rolle der Zufall in diesen späteren Invasionsstadien spielt und welche populationsgenetischen und evolutionären Auswirkungen vom Zufall geprägte Invasionsverläufe haben. Mit dieser Dissertation möchte ich beitragen zu einer stochastischen öko-genetischen Theorie des gesamten Invasionsprozesses – von der Einführung bis hin zu möglichen Auswirkungen. Meine übergreifenden Fragen sind: a) Welche Rolle für den Invasionsverlauf spielen ökologische Faktoren, die die durchschnittliche Wachstumsrate der eingeführten Population beeinflussen? b) Und welche Rolle spielen Faktoren, die die stochastische Variabilität der Populationsdynamik beeinflussen? c) Wie viel genetische Diversität weisen eingeführte Populationen im Durchschnitt auf, wenn sie einen bestimmten Punkt im Invasionsprozess erreichen? d) Inwiefern können die populationsgenetischen Auswirkungen von Invasionsverläufen wiederum die Populationsdynamik beeinflussen und so zu einer Rückkopplung führen? Zusammen mit meinen Betreuern und Koautoren habe ich vier Studien durchgeführt, die sich für bestimmte ökologische Szenarien jeweils mit mindestens zwei dieser Fragen befassen. Dazu kommen im Verlauf der Dissertation verschiedene Typen von stochastischen Modellen zum Einsatz: Markov-Ketten, Markov- und Diffusionsprozesse sowie Coalescent-artige Genealogie-Simulationen. In Kapitel 1 (Wittmann et al., 2013a, erschienen in Theoretical Population Biology) konzentrieren wir uns auf einen Faktor, der die durchschnittliche Wachstumsrate der Population beeinflusst: die Stärke der Konkurrenz mit einer ökologisch ähnlichen einheimischen Art. Unsere Ergebnisse deuten darauf hin, dass die erwartete Zeit bis zum Aussterben des einheimischen Konkurrenten für mittlere Konkurrenzstärken am kleinsten ist. Das können wir dadurch erklären, dass die Konkurrenzstärke gegensätzliche Auswirkungen in verschiedenen Stadien des Invasionsprozesses hat: Einerseits erschwert eine hohe Konkurrenzstärke die Etablierung der eingeführten Art, andererseits führt eine hohe Konkurrenzstärke aber auch dazu, dass die einheimische Art schnell verdrängt werden kann. Zusätzlich untersuchen wir in Kapitel 1, wie stark eine öko-genetische Rückkopplung das Aussterben der einheimischen Population beschleunigen würde. Dazu berücksichtigen wir, dass ein Rückgang der einheimischen Populationsgröße zu einem Verlust an genetischer Diversität führt, und das wiederum zu schlechterer Anpassung an veränderte Umweltbedingungen und darum weiterem Schrumpfen der Population. Unsere Ergebnisse legen nahe, dass diese öko-genetische Rückkopplung dann besonders stark ist, wenn die Konkurrenz zwischen einheimischer und eingeführter Art eher schwach ist. In Kapitel 2 (Wittmann et al., 2013b, im Druck bei Oikos) untersuchen wir für feste durchschnittliche Einführungsraten (Individuen pro Zeiteinheit), welche Rolle die zeitliche Verteilung der Individuen spielt. Besonders wichtig ist hierbei die Beziehung zwischen zeitlicher Verteilung und der Variabilität in der Größenentwicklung der Population. Wir zeigen, dass Fälle mit wenigen großen Einführungsereignissen zu mehr Variabilität führen als Fälle mit vielen kleinen Einführungsereignissen. Diese Variabilität hilft den eingeführten Populationen dabei, schwierige Stadien im Invasionsprozess (also solche mit einer negativen durchschnittlichen Wachstumsrate) zu bewältigen, ist aber anderseits in einfachen Stadien mit positiver durchschnittlicher Wachstumsrate von Nachteil. Im Lichte unserer Ergebnisse können wir aus der Literatur bekannte Daten zu Invasionsprozessen neu interpretieren. In den Kapiteln 3 und 4 (Wittmann et al., 2013c,d) untersuchen wir die genetische Diversität von Populationen, die einen starken demografischen Allee-Effekt erfolgreich überwunden haben. Laut Definition ist dabei die durchschnittliche Wachstumsrate bei Populationsgrößen unterhalb einer gewissen kritischen Größe negativ und in größeren Populationen positiv, so dass das erste Stadium des Invasionsprozesses schwierig ist und das zweite einfach. In Kapitel 3 zeigen wir unter der Annahme Poisson-verteilter Nachkommenzahlen, dass erfolgreiche Allee-Effekt-Populationen je nach Startgröße entweder eine höhere oder eine niedrigere durchschnittliche genetische Diversität aufweisen als erfolgreiche Populationen ohne Allee-Effekt. Das kommt zum Teil daher, dass erfolgreiche Allee-Effekt-Populationen besonders schnell das schwierige erste Stadium des Invasionsprozesses verlassen, wo genetische Drift am stärksten ist. Außerdem untersuchen wir in Kapitel 3, unter welchen Bedingungen sich die kritische Populationsgröße aus genetischen Daten schätzen lässt. In Kapitel 4 betrachten wir eine Reihe von Modellen für die Anzahl an Nachkommen von Individuen oder Paaren in der Population. Manche dieser Modelle führen zu mehr stochastischer Variabilität in der Populationsdynamik, andere zu weniger Variabilität als das in Kapitel 3 betrachtete Poisson-Modell. Für feste Startgröße beobachten wir, dass der Allee-Effekt bei kleiner Variabilität einen negativen Einfluss auf die genetische Diversität hat und bei großer Variabilität einen positiven Einfluss. Wir zeigen weiterhin, dass die Unterschiede zwischen unseren Nachkommenzahl-Modellen so substanziell sind, dass sie sich nicht durch eine Umskalierung der Parameter des Poisson-Modells erklären lassen. Zusammen genommen erlauben uns diese Ergebnisse einige allgemeine Schlussfolgerungen bezüglich der vier oben aufgeführten übergreifenden Fragen. a) Wie schnell eine eingeführte Population den Invasionsprozess durchläuft, hängt hauptsächlich davon ab, ob es schwierige Stadien gibt, und wie schwierig diese sind. Deshalb begünstigt eine ökologische Veränderung den Invasionserfolg dann, wenn sie schwierige Stadien im Invasionsprozess mindert. b) Aus der Perspektive der eingeführten Population ist Variabilität in schwierigen Stadien des Invasionsprozesses von Vorteil, aber in einfachen Stadien von Nachteil. c) Da die Stärke der genetischen Drift von der Populationsgröße abhängt, können wir die populationsgenetischen Auswirkungen von Invasionsverläufen verstehen, indem wir analysieren, wie viel Zeit die betrachtete Population in verschiedenen Populationsgrößenbereichen verbringt. d) Rückkopplungen zwischen einem Rückgang der Populationsgröße und einem Verlust genetischer Diversität sind am stärksten, wenn die Population viel Zeit im Bereich kleiner Populationsgrößen verbringt. Einige der wesentlichsten Ergebnisse dieser Dissertation können aus einer deterministischen Perspektive nicht verstanden werden, sondern sind ein direktes Produkt von Stochastizität. Dies macht deutlich, dass Stochastizität nicht einfach einem gewissen Durchschnitts- ergebnis etwas Rauschen hinzufügt, sondern das Verhalten biologischer Systeme qualitativ verändern kann.

The systematic and population genetic relationships were characterised for three ecologically related euphausiid species: Euphausia lucens, E. recurva and E. vallentini. These species have different geographical distributions and life histories. All three species have a circumpolar distribution in the Southern Hemisphere while E. recurva is also distributed in the North Pacific. DNA sequence variation was determined for three regions of mitochondrial DNA and a single nuclear gene. It was conclusively demonstrated that both E. lucens and E. vallentini represent valid taxonomic species with fixed differences observed in both the nuclear and mitochondrial genes and that the low divergences previously reported for these species with 16SrRNA and CO1 resulted from a species misidentification. It was also shown that previous attempts to date the divergence between Antarctic and Sub-Antarctic euphausiid species based on 16SrRNA distances suffer from a large overestimation due to a calculation error.

The aetiology of common diseases is shaped by the effects of genetic and environmental factors. Big efforts have been devoted to unravel the genetic basis of disease with the hope that it will help to develop new therapeutic treatments and to achieve personalized medicine. With the development of high-throughput genotyping technologies, hundreds of association studies have described many loci associated to disease. However, the depiction of disease architecture remains incomplete. The aim of this work is to perform exhaustive comparisons across human populations to evaluate pressing questions. Our results provide new insights in the allele frequency of risk variants, their sharing across populations and the likely architecture of disease
La etiología de las enfermedades comunes está formada por factores genéticos y ambientales. Se ha puesto mucho empeño en describir sus bases genéticas. Este conocimiento será útil para desarrollar nuevas terapias y la medicina personalizada. Gracias a las técnicas de genotipado masivo, centenares de estudios de asociación han descrito una infinidad de genes asociados a enfermedad. Pese a ello, la arquitectura genética de las enfermedades no ha sido totalmente descrita. Esta tesis pretende llevar a cabo exhaustivas comparaciones entre poblaciones para responder diversas preguntas candentes. Nuestros resultados dan pistas sobre la frecuencia de los alelos de riesgo, su presencia entre poblaciones y la probable arquitectura de las enfermedades.

Speciation can be understood as a continuum occurring at different levels, from population to species. The recent molecular revolution in population genetics has opened a pathway towards understanding species evolution. At the same time, speciation patterns can be better explained by incorporating a geographic context, through the use of geographic information systems (GIS). Phaedranassa (Amaryllidaceae) is a genus restricted to one of the world’s most biodiverse hotspots, the Northern Andes. I studied seven Phaedranassa species from Ecuador. Six of these species are endemic to the country. The topographic complexity of the Andes, which creates local microhabitats ranging from moist slopes to dry valleys, might explain the patterns of Phaedranassa species differentiation. With a Bayesian individual assignment approach, I assessed the genetic structure of the genus throughout Ecuador using twelve microsatellite loci. I also used bioclimatic variables and species geographic coordinates under a Maximum Entropy algorithm to generate distribution models of the species. My results show that Phaedranassa species are genetically well-differentiated. Furthermore, with the exception of two species, all Phaedranassa showed non-overlapping distributions. Phaedranassa viridiflora and P. glauciflora were the only species in which the model predicted a broad species distribution, but genetic evidence indicates that these findings are likely an artifact of species delimitation issues. Both genetic differentiation and non-overlapping geographic distribution suggest that allopatric divergence could be the general model of genetic differentiation. Evidence of sympatric speciation was found in two geographically and genetically distinct groups of P. viridiflora. Additionally, I report the first register of natural hybridization for the genus. The findings of this research show that the genetic differentiation of species in an intricate landscape as the Andes does not necessarily show a unique trend. Although allopatric speciation is the most common form of speciation, I found evidence of sympatric speciation and hybridization. These results show that the processes of speciation in the Andes have followed several pathways. The mixture of these processes contributes to the high biodiversity of the region

Orientadores: Vera Nisaka Solferini, John Wakeley
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia
Made available in DSpace on 2018-08-07T07:06:17Z (GMT). No. of bitstreams: 1 Jesus_FlaviaFuchsde_D.pdf: 1710104 bytes, checksum: 93b6ea526e59cb2c39bdd80b1e9207ba (MD5) Previous issue date: 2006
Resumo: A estrutura populacional é um dos principais fatores moldando os padrões de variabilidade genética no tempo e no espaço. Devido às flutuações climáticas que ocorreram durante o período Quaternário, muitas espécies podem ter sofrido redução e fragmentação populacional, ficando restritas a "refúgios" durante períodos glaciais e se expandindo novamente durante os interglaciais. Isto tem sido utilizado para explicar alguns padrões encontrados nas espécies atualmente. O presente trabalho consistiu no desenvolvimento e estudo de modelos para auxiliar na compreensão das conseqüências genéticas de mudanças cíclicas na estruturação e tamanho populacionais, como as que teriam ocorrido ao longo das flutuações climáticas do Quaternário. A redução populacional é capaz de causar redução do tamanho efetivo populacional, do tempo médio de coalescência e da variabilidade genética, ao passo que um aumento na subdivisão populacional pode ter o efeito oposto. Para investigar estes efeitos opostos, foram estudados dois modelos, ambos com alternância de duas fases correspondendo aos períodos glaciais e interglaciais. Em ambos os modelos permitiram-se mudanças na estrutura populacional, além de mudanças no tamanho populacional, de uma maneira cíclica. No primeiro modelo, fases totalmente panmíticas alternaram-se com fases totalmente estruturadas. A partir deste modelo, obteve-se uma expressão para a esperança do tempo de coalescência de duas seqüências e, a partir desta, uma expressão para a esperança do número de sítios polimórficos. Tanto o aumento do número de demes quanto da duração das fases estrutura das causaram um aumento do tempo de coalescência e dos níveis de variabilidade genética. Os resultados obtidos foram comparados com os que seriam esperados para uma população panrnítica de tamanho constante. Verificou-se que a estruturação pode superar o efeito da redução populacional durante os períodos glaciais. Especificamente, o número médio de sítios polimórficos pode ser maior no modelo proposto, mesmo quando o támanho populacional é muito reduzido durante as fases estruturadas. No segundo modelo, permitiu-se subdivisão populacional de acordo com o modelo de finitas ilhas em ambas as fases, com migração. O tamanho populacional, a taxa de migração e o número de demes variaram entre as fases. Para este modelo, além de uma expressão para a o tempo médio de coalescência, obteve-se também uma expressão para a distribuição dos tempos de coalescência de duas seqüências. As distribuições observadas foram muito diferentes do que seria esperado para uma população panrnítica de tamanho constante. Um tamanho populacional reduzido durante os períodos glaciais causou descontinuidades e picos múltiplos na distribuição dos tempos de coalescência, bem como uma redução dos tempo médios. O aumento da estrutura populacional, através da redução da taxa de migração, aumentou os tempos médios e atenuou os picos da distribuição. O tempo médio de coalescência, em geral, também aumentou em decorrência de um maior número de demes durante os períodos glaciais. Os resultados encontrados ajudam na compreensão das conseqüências genéticas de ciclos glaciais e, em especial, da importância da estrutura populacional na manutenção da variabilidade genética. Além' disso, oferecem uma possível explicação para padrões genéticos observados em muitas espécies em que genealogias gênicas muito longas são econtradas, com o ancestral comum mais recente antecedendo em muito ao último período glacial
Abstract: Population structure is one of the major factors shaping the pattems of genetic variation across time and space. Due to the climatic fluctuations of the Qua terna ry, several species may have suffered population reduction and fragmentation, becoming restricted to refugia during glacial periods and expanding again during interglacials. This has been used to explain some patterns currently observed in several species. The present work consisted in the development and study of models to help understand the genetic consequences of cyclic changes in population structure and size, such as the ones that may have occurred throughout the climatic fluctuations of the Quatemary. Population reduction may cause reduction in population effective size, mean coalescence time and genetic variation; whereas an increase in population subdivision may have the opposite effect. In order to investigate these two opposite effects, two models were studied, both with two alternating phases, corresponding to the glacial and interglacial periods. Both models included changes in population structure, besides those in population size, in a cyclic manner. In the first model, completely panrnictic phases were alternated with completely structured ones. Based on this model, an expression was derived for the expectation of coalescence times of two sequences and, from this, an expression for the expectation of the number of segregating sites. Both an increase in the number of demes and in the duration of the structured phases caused an increase in coalescence times and levels of genetic variation. The results obtained were compared to what would be expected for a panrnictic population of constant size. It was verified that population structure may outhweigh the effect of population reduction during glacial periods. Specifically, the mean number of segregating sites can be greater in the proposed model, even when population size is quite reduced during the structured phases. In the second mode!, population subdivision was allowed in both phases' - according the finite island model with migration. Population size, migration rate and number of demes varied between phases. For this model, besides an expression for the mean coalescence time, an expression for the distribution of coalescence times was also obtained. The distributions observed were quite different from what would be expected for a panrnictic population of constant size. Population reduction during glacial periods caused discontinuities and multiple peaks in the distribution of coalescence times, as well as a reduction in the expected times. An increase in population structure, through reducing migration rates, increased the mean times and attenuated the peaks of the distribution. Mean coalescence times, in general, also increased with a greater number of demes during glacial periods. The results obtained help understand the genetic consequences of glacial cycles, and, especially, point to the importance of population structure for the maintenance of genetic varlation. Besides, they offer a potential explanation for the genetic pattems observed in several species, for which long gene genealogies are observed, with the most recent ancestor predating by far the last glacial period
Doutorado
Genetica Animal e Evolução
Doutor em Genetica e Biologia Molecular

The aim of this study was to investigate the genetic diversity of the SLC22A1 gene and to deduce its possible pharmacogenetic implications within the Cape Coloured population of South 
Africa
a uniquely admixed population of immigrant Europeans, Asians and the indigenous populations. Recent studies have reported an abundance of polymorphic variants within this solute 
carrier transporter gene encoding for the organic cation transporter 1, as well as evidence linking these variants to an effect on metformin uptake. This study included establishing baseline 
frequency distribution of previously reported alleles for 20 SNP variants within the SLC22A1 gene, as well as the development of SNaPshot®
and Multiplex AS-PCR genotyping assays, and 
also exploring the possibility of using High-resolution melt (HRM) analysis as a costeffective alternative for SNP genotyping. Ethics clearance was obtained from the Ethics Committee of the 
University of the Western Cape. Biological samples in the form of buccal (oral) swabs were collected from 132 unrelated voluntary donors from the Cape Coloured population residing in the 
Cape Metropolitan area. Two SNaPshot®
Multiplex Systems were specifically designed for the study,successfully optimized and used for genotyping. Hundred genetic profiles were then generated for a total of 20 SNP variants on SLC22A1 gene, using this primer extension-based genotyping method that enables multiplexing up 10 SNPs. Population genetics data obtained for 
the investigated SNPs were analysed using various statistical analysis software. Important population genetic parameters were calculated, and possible pharmacogenetics implications were then discussed. Among others, allelic and genotypic frequencies, as well as linkage disequilibrium were determined and compared with world populations. Minor deviation from Hardy- Weinberg equilibrium was observed in the Cape Coloured population. No significantLinkage Disequilibrium between the investigated SNPs was observed in this population. A Multiplex allele specific &ndash
PCR (MAS-PCR) genotyping 
system was successfully designed and optimized for the genotyping of 10 SNPs from the SLC22A1. This system, also developed specifically for this study, was made of 2 multiplexes each covering 5 SNPs. It is an inexpensive genotyping assay that allows for efficient discrimination of SNP polymorphisms in one reaction tube with standard PCR conditions. A pilot study was 
conducted to explore the possibility of using High-resolution melt (HRM) analysis as a cost-effective alternative for SNP genotyping. In addition to genotyping, HRM analysis can be used to scan 
large numbers of samples for novel genetic variations. 

The extent to which natural selection shapes diversity within populations is a key question for population genetics. Thus, there is considerable interest in quantifying the strength of selection. In this thesis a full likelihood approach for inference about selection at a single site within an otherwise neutral fully-linked sequence of sites is developed. Integral to many of the ideas introduced in this thesis is the reversibility of the diffusion process, and some past approaches to this concept are reviewed. A coalescent model of evolution is used to model the ancestry of a sample of DNA sequences which have the selected site segregating. A novel method for simulating the coalescent with selection, acting at a single biallelic site, is described. Selection is incorporated through modelling the frequency of the selected and neutral allelic classes stochastically back in time. The ancestry is then simulated using a subdivided population model considering the population frequencies through time as variable population sizes. The approach is general and can be used for any selection scheme at a biallelic locus. The mutation model, for the selected and neutral sites, is the infinitely-many-sites model where there is no back or parallel mutation at sites. This allows a unique perfect phylogeny, a gene tree, to be constructed from the configuration of mutations on the sample sequences. An importance sampling algorithm is described to explore over coalescent tree space consistent with this gene tree. The method is used to assess the evidence for selection in a number of data sets. These are as follows: a partial selective sweep in the G6PD gene (Verrelli et al., 2002); a recent full sweep in the Factor IX gene (Harris and Hey, 2001); and balancing selection in the DCP1 gene (Rieder et al., 1999). Little evidence of the action of selection is found in the data set of Verrelli et al. (2002) and the data set of Rieder et al. (1999) seems inconsistent with the model of balancing selection. The patterns of diversity in the data set of Harris and Hey (2001) offer support of the hypothesis of a full sweep.

Les forces de sélection sont un des moteurs de l’évolution de la diversité phénotypique et de la diversité génétique neutre et des zones codantes du génome. Cette sélection peut s’appliquer sur des caractères transmis génétiquement ou culturellement. Le travail effectué s’intéresse à ces deux processus de sélection. Nous avons étudié dans un premier temps les effets de la transmission intergénérationnelle de la fécondité sur la diversité génétique neutre puis dans un deuxième temps l’impact de la sélection sur des phénotypes codés par des réseaux de gènes sur le polymorphisme de ces gènes.La transmission de la fécondité est un phénomène culturel ou génétique qui se caractérise par une corrélation positive entre la taille de fratrie d’un individu et la taille de fratrie de ses enfants. Il a été observé tant dans des populations humaines qu’animales. Nous montrons, par l’outil de la modélisation, que ses effets et la possibilité de le détecter dépendent autant du type de données étudiées (génétiques ou généalogiques), que des différents types de transmission (uniparentale, biparentale). Nous montrons que d’autres phénomènes, tels que l’hétérogénéité du succès reproducteur des individus, peuvent fortement moduler son impact. Nous développons un certain nombre d’outils permettant de détecter ce phénomène de transmission de la fécondité tant sur des données généalogiques que sur des données génétiques relevant de différents modèles mutationnels (microsatellite, séquences, SNPs) et de différents types de transmission (haploïde ou diploïde, lié au sexe ou non). Nous avons appliqué ces outils notamment à trois populations humaines du Cilento en Italie (généalogies et ADN mitochondrial), des données d’Asie Centrale (chromosome Y) et des données HapMap (autosomes).La seconde partie de la thèse porte sur la modélisation de l’action de la sélection naturelle sur des caractères codés par des réseaux de régulation et décrit l’impact de ce type de sélection sur l’évolution du phénotype et sur la diversité des gènes sous-jacents. Un phénotype est le résultat des interactions entre différents gènes et leurs produits. Nous montrons que la sélection sur ce phénotype va modifier l’organisation du réseau de gènes ainsi que le niveau de polymorphisme des gènes du réseau. Par exemple, lorsque le phénotype optimal correspond à une expression médiane des gènes, les gènes les plus régulateurs vont être soumis à une plus forte perte de diversité. En revanche, si le phénotype optimal correspond à une expression très forte, ce sont les gènes les plus régulés qui vont être les plus contraints. Cette analyse a permis de montrer la complexité des relations entre sélection, réseaux de régulation, phénotypes et environnement
Selective forces are one of the major determinants of the evolution of phenotypic diversity and genetic diversity, in neutral and coding zones of the genome. Selection can occur on genetically - or culturally - transmitted traits. This thesis considers these two selective processes. First, we studied the effects of intergenerational fertility transmission on neutral genetic diversity. Second, we considered the impact of selection on phenotypes coded by a gene network and on the polymorphism of genes within the network.Fertility transmission is a cultural or genetic phenomenon, which is characterised by a positive correlation between the sibship size of an individual and that of its children. It was observed both in human and animal populations. Using a modelling approach, we show that its effects and the possibility to detect it depend both on the kind of studied data (genetic or genealogical data) and on the different kind of transmission (uniparental, biparental). We show that other phenomena, such as the heterogeneity of reproductive success between individuals, can affect its effects. We develop several tools allowing to infer this phenomenon of fertility transmission on genealogical data, as well as on genetic polymorphism data that follows different mutational models (microsatellites, sequences, SNPs) and different transmission modes (haploid or diploid, sex-linked or not). We applied in particular these tools to three human populations of the Cilento area in Italy (genealogical and mitochondrial DNA data), to Central Asian data (Y chromosome) and to HapMap data (autosomes).The second part of this thesis deals with the modelling of the action of natural selection on traits coded by regulation networks and describes the impact of such selection on the evolution of the phenotype and of the underlying genes. A given phenotype is the result of the interaction between different genes and their products. We show that phenotypic selection will modify the gene network organisation, as well as the level of polymorphism of the genes involved in the network. For example, when the optimal phenotype corresponds to an intermediate level of gene expression, the most regulatory genes will lose much of their diversity. Conversely, if the optimal phenotype corresponds to a very strong expression of the genes, it will be the most regulated genes that will be the most constrained. This analysis allowed us to show the complexity of the relations between selection, regulation networks, phenotypes and the environment

L'hybridation et les maladies infectieuses sont deux problématiques majeures pour la conservation de la faune sauvage à travers le monde. Le Chat sauvage européen Felis silvestris silvestris, à travers ses interactions avec son proche apparenté le Chat domestique Felis silvestris catus, représente un modèle intéressant pour l'étude de ces deux problématiques et de leurs interactions. Le fait que le Chat sauvage soit touché par ces deux phénomènes, combiné à la variabilité des habitats dans lesquels il vit en Europe, permet de conduire des études comparées et de comprendre quels déterminants environnementaux influencent les flux de gènes et de pathogènes. Ici, nous proposons deux nouvelles approches méthodologiques basées sur l'analyse de marqueurs génétiques, pour une meilleure comparabilité entre études et une détection rapide des hybrides respectivement. Nous avons recherché les hybrides et regardé la distribution spatiale des individus apparentés dans deux populations locales divergeant principalement sur le niveau de fragmentation de l'environnement. Dans l'une de ces populations, nous avons également conduit une étude sérologique pour déterminer si les chats sauvages et domestiques échangeaient certains des virus communs du Chat domestique (PVF, HVF, CVF, VIF). Nous avons observé un taux d'hybridation plus élevé dans l'environnement le plus fragmenté. Malgré la ceinture de chats domestiques infectés à haute prévalence autour d'elle, la population de chats sauvages de ce même environnement n'était infectée par aucun des virus. La présence de barrières génétiques et/ou comportementales expliquerait ce résultat dans un environnement fragmenté permettant par ailleurs le maintien de souches généralistes. L'échantillonnage local présenté ici nous a permis de comprendre les mécanismes à la base de l'hybridation et de la circulation des virus. Présentement, le Chat sauvage européen ne semble pas menacé par le Chat domestique. Toutefois, des mesures préventives devraient être adoptées pour éviter que cela ne devienne le cas
Hybridization and infectious diseases are two major issues for wildlife conservation worldwide. The European wildcat Felis silvestris silvestris, through its interactions with its close relative the domestic cat Felis silvestris catus, represents a valuable model for the study of these two issues and their interactions. The European wildcat is both threatened by hybridization and infectious diseases. This, combined with the high diversity of environments where it lives throughout Europe, allows to lead comparative studies and to understand which environmental determinants impact gene and pathogen flows. Here we propose two new methodological developments for the detection of hybrids based on genetic markers allowing for a better comparability between studies and leading to a fast detection of hybrids respectively. Hybrid detection and assessment of spatial relatedness pattern were carried out in two local populations of European wildcats differing mostly on the level of fragmentation of their environment. On one of this population, we led a serological survey to investigate whether domestic cats and wildcats exchange some of the most common viruses of the domestic cat (FPV, FHV, FCV, FIV). We found a higher rate of hybridization in the most fragmented environment. There, the wildcat population, in spite of the domestic cats surrounding it that were infected at high prevalence with the viruses, was not infected by any of the viruses. The presence of genetic or behavioral barriers may explain this result in an environment that is not incompatible with the persistence of generalist strains. The local sampling achieved in this work allowed us to investigate mechanisms behind hybridization and viruses’ circulation. At the time, the European wildcat does not seem threatened by domestic cats. However, preventive measures should be taken to prevent a future increase in frequency of the phenomenon both for the control of gene and virus flows

Perissodus microlepis is a species of cichlid fish endemic to Lake Tanganyika (Africa). Adult P. microlepis are lepidophages, feeding on the scales of other living fish. As an adaptation for this feeding behavior P. microlepis exhibit lateral asymmetry with respect to jaw morphology: the mouth either opens to the right or left side of the body. Field data illustrate a temporal phenotypic oscillation in the mouth-handedness, and this oscillation is maintained by frequency-dependent selection. To better understand the oscillation, Takahashi and Hori model frequency-dependent selection in P. microlepis using a population genetic model. Their results are intriguing, and the purpose of this dissertation is to improve and extend their model, which fails to account for important biological aspects.We model P. microlepis with a novel approach that fuses the disparate modeling traditions of population genetics and population dynamics; we account for both processes since, in the case of P. microlepis, they occur on the same time scale (a case of microevolution). We construct our models using systems of difference equations. We prove the existence and uniqueness of a positive equilibrium, which corresponds to a 1 : 1 phenotypic ratio. Using a local stability and bifurcation analysis, we show that the equilibrium becomes unstable when frequency-dependent selection is sufficiently strong. We determine necessary and sufficient conditions for onset of oscillation. Local bifurcation analysis indicates key features of the oscillation that may suggest critical experiments.We determine the role of stage structure and the role of strong and weak intraspecific competition. We show that stage-structure is not necessary for, but enhances, oscillatory behavior. Finally we demonstrate the complicated interplay between population dynamic and population genetic processes. Our findings indicate that classical population genetic models can fail to elucidate complex dynamics.

Microorganisms are an indispensable part of our ecosystem, yet the natural metabolic and ecological diversity of these organisms is poorly understood due to a historical reliance of microbiology on laboratory grown cultures. The awareness that this diversity cannot be studied by laboratory isolation, together with recent advances in low cost scalable sequencing technology, have enabled the foundation of culture-independent microbiology, or metagenomics. The study of environmental microbial samples with metagenomics has led to many advances, but a number of technological and methodological challenges still remain. A potentially diverse set of taxa may be represented in anyone environmental sample. Existing tools for representing the genetic composition of such samples sequenced with short-read data, and tools for identifying variation amongst them, are still in their infancy. This thesis makes the case that a new framework based on a joint-genome graph can constitute a powerful tool for representing and manipulating the joint genomes of population samples. I present the development of a collection of methods, called SCRAPS, to construct these efficient graphs in small communities without the availability or bias of a reference genome. A key novelty is that genetic variation is identified from the data structure using a probabilistic algorithm that can provide a measure of the confidence in each call. SCRAPS is first tested on simulated short read data for accuracy and efficiency. At least 95% of non-repetitive small-scale genetic variation with a minor allele read depth greater than 10x is correctly identified; the number false positives per conserved nucleotide is consistently better than 1 part in 333 x 103. SCRAPS is then applied to artificially pooled experimental datasets. As part of this study, SCRAPS is used to identify genetic variation in an epidemiological 11 sample Neisseria meningitidis dataset collected from the African meningitis belt". In total 14,000 sites of genetic variation are identified from 48 million Illumina/Solexa reads. The results clearly show the genetic differences between two waves of infection that has plagued northern Ghana and Burkina Faso.

Cette thèse utilise des approches de génétique des populations et de statistique pour étudier des événements anciens de démographie humaine, inférer de l’adaptation locale dans diverses populations et étudier le déterminisme du goût. En utilisant une approche bayésienne, j’évalue les preuves génétiques d’une réduction de population entre 190 000 et 130 000 ans avant notre ère. Je trouve que les données sont en faveur d’un modèle sans goulot d’étranglement durant cette période. Dans le second article, je développe une méthode destinée à la détection d’adaptation locale basée sur l’étude des haplotypes privés. Appliquée à des données de génotypage, cette méthode permet de détecter des signaux d’adaptation connus chez l’Homme mais aussi d’étendre nos connaissances en matière d’adaptation. J’étudie ensuite les signaux d’adaptation dans des données de génomes entiers de plusieurs populations et montre que le régime alimentaire et les pathogènes ont une influence majeure sur la variabilité adaptative des populations prises en compte. J’étudie dans un dernier article les perceptions gustatives de populations ayant différents modes de vie. Je présente les résultats phénotypiques de perception des goûts, et les associe à des données de génotypage. Je montre que les gènes impliqués dans la perception des goûts ont évolué avec le mode de vie. En effectuant une étude d’association, je montre aussi que les variations dans la perception des goûts impliquent plus de gènes que les seuls gènes codant pour les récepteurs gustatifs. Mes résultats montrent l’utilité des données génétiques denses pour mieux comprendre l’évolution humaine
This thesis uses population genetics and statistical approaches to investigate early human demography, infer local adaptation in diverse sets of populations, and study the genetic basis for taste perception. Using a Bayesian approach, I evaluate the genetic evidence of a bottleneck between 190,000 and 130,000 years ago and find that the data is in favor of a model without bottleneck at this time point. I further develop a method to detect local adaptation based on frequencies of private haplotypes. Applied to large-scale human genotype data, this method detects known signals of positive selection but also permits to improve knowledge on potential adaptation events in humans. I further investigate patterns of adaptation in whole genome data based on a diverse set of African populations. The results from the regions potentially selected show that diet and pathogens are the common driving forces of adaptation in all studied populations. I last study taste perception in populations differing on lifestyle (hunter-gatherers, farmers and nomad herders). I present taste perception phenotypes for all tastes (sweet, bitter, sour, salty and umami) and relate them to high density genotype data. I show that taste and taste-involved genes have evolved with lifestyle. By performing an association study, I also show that variation in taste perception involves more genes than only the taste receptors genes.I covered several topics of human ancient demography and adaptation and show the utility of using large-scale genetic data to better understand human history

Cette thèse consiste à améliorer les outils statistiques adaptés à des modèles stochastiques de génétiques des populations et de développer des méthodes statistiques adaptées à des données génétiques de nouvelle génération. Pour un modèle paramétrique basé sur le coalescent, la vraisemblance en un point de l'espace des paramètres s'écrit comme la somme des probabilités de toutes les histoires (généalogies munies de mutations) possibles de l'échantillon observé. À l'heure actuelle, les meilleures méthodes d'inférence des paramètres de ce type de modèles sont les méthodes bayésiennes approchées et l'approximation de la fonction de vraisemblance.L'algorithme d'échantillonnage préférentiel séquentiel (SIS) estime la vraisemblance, en parcourant de manière efficace l'espace latent de ces histoires. Dans ce schéma, la distribution d'importance propose les histoires de l'échantillon observé les plus probables possibles. Cette technique est lourde en temps de calcul mais fournit des estimations par maximum de vraisemblance d'une grande précision.Les modèles que nous souhaitons inférer incluent des variations de la taille de la population. Les méthodes d'IS ne sont pas efficaces pour des modèles en déséquilibre car les distributions d'importance ont été développées pour une population de taille constante au cours du temps. Le temps de calcul augmente fortement pour la même précision de l'estimation de la vraisemblance. La première contribution de cette thèse a consisté à explorer l'algorithme SIS avec ré-échantillonnage (SISR). L'idée est de ré-échantillonner de façon à apprendre quelles sont les histoires proposées par la distribution d'importance qui seront les plus probables avant d'avoir terminé leur simulation et diminuer le temps de calcul. Par ailleurs, nous avons proposé une nouvelle distribution de ré-échantillonnage, tirant profit de l'information contenue dans la vraisemblance composite par paire de l'échantillon.Le développement récent des technologies de séquençage à haut débit a révolutionné la génération de données de polymorphisme chez de nombreux organismes. Les méthodes d'inférence classiques de maximum de vraisemblance ou basées sur le Sites Frequency Spectrum, adaptées à des jeux de données de polymorphisme génétique de quelques loci, supposent l'indépendance des généalogies des loci. Pour tirer parti de données beaucoup plus denses sur le génome, nous considérons la dépendance des généalogies sur des positions voisines du génome et modéliser la recombinaison génétique. Alors, la vraisemblance prend la forme d'une intégrale sur tous les graphes de recombinaison ancestraux possibles pour les séquences échantillonnées, un espace de bien plus grande dimension que l'espace des généalogies. Les méthodes d'inférence basées sur la vraisemblance ne peuvent plus être utilisées sans plus d'approximations. De nombreuses méthodes infèrent les changements historiques de la taille de la population mais ne considèrent pas la complexité du modèle ajusté. Même si certaines proposent un contrôle d'un potentiel sur-ajustement du modèle, à notre connaissance, aucune procédure de choix de modèle entre des modèles démographiques de complexité différente n'a été proposée à partir de longueurs de segments identiques. Nous nous concentrons sur un modèle de taille de population constante et un modèle de population ayant subit un unique changement de taille dans le passé. Puisque ces modèles sont emboîtés, la deuxième contribution de cette thèse a consisté à développer un critère de choix de modèle pénalisé basé sur la comparaison d'homozygotie haplotypique observée et théorique. Notre pénalisation, reposant sur des indices de sensibilité de Sobol, est liée à la complexité du modèle. Ce critère pénalisé de choix de modèle nous a permis de choisir entre un modèle de taille de population constante ou présentant un changement passé de la taille de la population sur des jeux de données simulés et sur un jeux de données de vaches
This thesis aims to improve statistical methods suitable for stochastic models of population genetics and to develop statistical methods adapted to next generation sequencing data.Sequential importance sampling algorithms have been defined to estimate likelihoods in models of ancestral population processes. However, these algorithms are based on features of the models with constant population size, and become inefficient when the population size varies in time, making likelihood-based inferences difficult in many demographic situations. In the first contribution of this thesis, we modify a previous sequential importance sampling algorithm to improve the efficiency of the likelihood estimation. Our procedure is still based on features of the model with constant size, but uses a resampling technique with a new resampling probability distribution depending on the pairwise composite likelihood. We tested our algorithm, called sequential importance sampling with resampling (SISR) on simulated data sets under different demographic cases. In most cases, we divided the computational cost by two for the same accuracy of inference, in some cases even by one hundred. This work provides the first assessment of the impact of such resampling techniques on parameter inference using sequential importance sampling, and extends the range of situations where likelihood inferences can be easily performed.The recent development of high-throughput sequencing technologies has revolutionized the generation of genetic data for many organisms : genome wide sequence data are now available. Classical inference methods (maximum likelihood methods (MCMC, IS), methods based on the Sites Frequency Spectrum (SFS)) suitable for polymorphism data sets of some loci assume that the genealogies of the loci are independent. To take advantage of genome wide sequence data with known genome, we need to consider the dependency of genealogies of adjacent positions in the genome. Thus, when we model recombination, the likelihood takes the form of an integral over all possible ancestral recombination graph for the sampled sequences. This space is of much larger dimension than the genealogies space, to the extent that we cannot handle likelihood-based inference while modeling recombination without further approximations.Several methods infer the historical changes in the effective population size but do not consider the complexity of the demographic model fitted.Even if some of them propose a control for potential over-fitting, to the best of our knowledge, no model choice procedure between demographic models of different complexity have been proposed based on IBS segment lengths. The aim of the second contribution of this thesis is to overcome this lack by proposing a model choice procedure between demographic models of different complexity. We focus on a simple model of constant population size and a slightly more complex model with a single past change in the population size.Since these models are embedded, we developed a penalized model choice criterion based on the comparison of observed and predicted haplotype homozygosity.Our penalization relies on Sobol's sensitivity indices and is a form of penalty related to the complexity of the model.This penalized model choice criterion allowed us to choose between a population of constant size and a population size with a past change on simulated data sets and also on a cattle data set

During speciation, the degree of clustering of a population in terms of genetic polymorphisms increases gradually until the exchange of genes between subpopulations is no longer possible. The isolation-with-migration (IM) model is used to estimate how long ago an ancestral population divided into two subpopulations, and to infer the level of gene flow between the subpopulations during genetic divergence. Its assumption of constant gene flow until the present is however particularly unrealistic in the context of two present-day species. In addition, traditional methods to fit the IM model are aimed at large numbers of DNA sequences from a small number of loci, and are computationally very expensive. To overcome these limitations, this thesis begins by focusing on an extension of the IM model in which the initial period of gene flow is followed by a period of isolation: the so-called isolation-with-initial-migration (IIM) model. For an IIM model with potentially asymmetric gene flow and unequal subpopulation sizes, the distribution of the number of nucleotide differences between two homologous DNA sequences is derived. Based on this distribution, we develop a maximum-likelihood estimation method which is appropriate for data sets containing observations from many independent loci, and is both very efficient and able to deal with mutation rate heterogeneity. Using a data set of Drosophila sequences from approximately 30,000 loci, we show how alternative models, representing different evolutionary scenarios, can be distinguished by means of likelihood ratio tests. To enable inference on both historical and contemporary rates of gene flow between two closely related species, our estimation method is extended to a generalised IM (GIM) model, in which gene flow rates and population sizes can change at some point in the past. Finally, we show how the theory of statistical inference under model misspecification can be used to improve the accuracy of interval estimation and comparison of speciation models; and we develop a simulation method to estimate the limiting distribution of the likelihood ratio statistic when the true parameter vector lies on the boundary of the parameter space.

Reconstructing the origins and evolutionary journey of humans is a central piece of biology. Complementary to archeology, population genetics studying genetic variation among individuals in extant populations has made considerable progress in understanding the evolution of our species. Particularly, studies in indigenous humans provide valuable insights on the prehistory of humans because their life history closely resembles that of our ancestors. Despite these efforts, it can be difficult to disentangle population genetic inferences because of the interplay among evolutionary forces, including mutation, recombination, selection, and demographic processes. To date, few studies have adopted a comprehensive framework to jointly account for these confounding effects. The shortage of such an approach inspired this dissertation work, which centered on the development of model-based analysis and demonstrated its importance in population genetic inferences. Indigenous African Pygmy hunter-gatherers have been long studied because of interest in their short stature, foraging subsistence strategy in rainforests, and long-term socio-economic relationship with nearby farmers. I proposed detailed demographic models using genomes from seven Western African Pygmies and nine Western African farmers (Appendix A). Statistical evidence was shown for a much deeper divergence than previously thought and for asymmetric migrations with a larger contribution from the farmers to Pygmies. The model-based analyses revealed significant adaption signals in the Pygmies for genes involved in muscle development, bone synthesis, immunity, reproduction, etc. I also showed that the proposed model-based approach is robust to the confounding effects of evolutionary forces (Appendix A). Contrary to the low-latitude African homeland of humans, the indigenous Siberians are long-term survivors inhabiting one of the coldest places on Earth. Leveraging whole exome sequencing data from two Siberian populations, I presented demographic models for these North Asian dwellers that include divergence, isolation, and gene flow (Appendix B). The best-fit models suggested a closer genetic affinity of these Siberians to East Asians than to Europeans. Using the model-based framework, seven NCBI BioSystems gene sets showed significance for polygenic selection in these Siberians. Interestingly, many of these candidate gene sets are heavily related to diet, indicating possible adaptations to special dietary requirements in these populations in cold, resource-limited environments. Finally, I moved beyond studying the history of extant humans to explore the origins of our species in Africa (Appendix C). Specifically, with statistical analyses using genomes only from extant Africans, I rejected the null model of no archaic admixture in Africa and in turn gave the first whole-genome evidence for interbreeding among human species in Africa. Using extensive simulation analyses under various archaic admixture models, the results suggest recurrent admixture between the ancestors of archaic and modern Africans, with evidence that at least one such event occurred in the last 30,000 years in Africa.

O objetivo do mapeamento de QTL (Quantitative Trait Loci ) e identificar sua posição no genoma, isto e, identificar em qual cromossomo esta e qual sua localização nesse cromossomo, bem como estimar seus efeitos genéticos. Uma vez que as localizações dos QTL não são conhecidas a priori, marcadores são usados frequentemente para auxiliar no seu mapeamento. Alguns marcadores podem estar altamente ligados a um ou mais QTL e, dessa forma eles podem mostrar uma alta associação com a característica fenotípica. O efeito genético do QTL e os valores fenotípicos de uma característica quantitativa são normalmente descritos por um modelo linear. Uma vez que as localizações dos QTL não são conhecidas a priori, marcadores são utilizados para representá-los. Em geral, e utilizado um numero grande de marcadores. Esses marcadores são utilizados no modelo linear para proceder ao processo de associação; dessa forma o modelo especificado contem um numero elevado de parâmetros a serem estimados. No entanto, e esperado que muitos destes parâmetros sejam não significativos, necessitando de um tratamento especial. Na estimação bayesiana esse problema e tratado por meio da estrutura de distribuições a priori utilizada. Um parâmetro que e esperado assumir o valor zero (não significativo) e naturalmente especificado por meio de uma distribuição que coloque um peso maior no zero, encolhimento bayesiano. Neste trabalho e proposta a utilização de dois modelos que utilizam distribuições a priori de encolhimento. Um dos modelos esta relacionado com o uso da distribuição a priori Laplace (Lasso bayesiano) e o outro com a Horseshoe (Estimador Horseshoe). Para avaliar o desempenho dos modelos na determinação da associação entre marcadores e QTL, realizou-se um estudo de simulação. Foi analisada a associação entre marcadores e QTL utilizando três características fenotípicas: produção de grãos, altura da espiga e altura da planta. Comparou-se os resultados obtidos neste trabalho com analises feitas na literatura na detecção dos marcadores associados a essas características. A implementação computacional dos algoritmos foi feita utilizando a linguagem C e executada no pacote estatístico R. O programa implementado na linguagem C e apresentado e disponibilizado. Devido a interação entre as linguagens de programação C e R, foi possível executar o programa no ambiente R.
The objective of the mapping of quantitative trait loci (QTL) is to identify its position in the genome, ie, identify which chromosome is and what is its location in the chromosome, as well as to estimate their genetic eects. Since the location of QTL are not known a priori, markers are often used to assist in it mapping. Some markers may be closely linked to one or more QTL, and thus they may show a strong association with the phenotypic trait. The genetic eect of QTL and the phenotypic values of a quantitative trait are usually described by a linear model. Since the QTL locations are not known a priori, markers are used to represent them. Generally is used a large number of markers. These markers are used in the linear model to make the process of association and thus the model specied contains a large number of parameters to be estimated. However, it is expected that many of these parameters are not signicant, requiring a special treatment. In Bayesian estimation this problem is treated through structure priori distribution used. A parameter that is expected to assume the value zero (not signicant) is naturally specied by means of a distribution that put more weight at zero, bayesian shrinkage. This paper proposes the use of two models using priori distributions to shrinkage. One of the models is related to the use of priori distribution Laplace (bayesian Lasso) and the other with Horseshoe (Horseshoe Estimator). To evaluate the performance of the models to determine the association between markers and QTL, we performed a simulation study. We analyzed the association between markers and QTL using three phenotypic traits: grain yield, ear height and plant height. We compared the results obtained in this study with analyzes in the literature on the detection of markers associated with these characteristics. The computational implementation of the algorithms was done using the C language and executed the statistical package R. The program is implemented in C languages presented and made available. Due to the interaction between the programming languages C and R, it was possible execute the program in the environment R.

The aim of the present study was to evaluate the power of discrimination and genetic (diversity) parameters in the Y chromosome extended haploytpe markers in populations of Tanzania for forensic and populations studies. Eleven Y chromosome extended haplotype markers were selected for this study, these includes Minimal haplotypes markers i.e. DYS19, DYS390, DYS391, DYS392, DYS393, DYS385a/b, DYS389I/II and two additional markers DYS438 and DYS439. Six populations of Tanzania were investigated under this study. These populations were selected based on the language family categories
Niger Congo (Kuria and Sukuma), Nilo Saharan (Luo and Maasai) and Afro Asiatic (Iraqw and Alagwa).

L'adaptation locale est un phénomène micro-évolutif qui peut survenir lorsque des populations d'une même espèce sont exposées à des conditions environnementales différentes.Si cet environnement exerce une pression sous forme de sélection naturelle, qu'il existe un potentiel adaptatif au sein des populations et que le flux de gènes est suffisamment modéré, les populations vont alors tendre vers un optimum adaptatif local.Dans cette thèse, je m'intéresse aux moyens méthodologiques de l'étude de l'adaptation locale d'une part, et à l'étude de ce phénomène le long d'un gradient d'altitude chez la plante alpine Arabis alpina d'autre part.Dans la première partie méthodologique, je montre que les méthodes de scan génomique pour détecter les marqueurs génétiques sous sélection peuvent souffrir de forts taux de faux positifs lorsqu'exposées à des jeux de données complexes, mais réalistes.Je présente ensuite une méthode statistique de détection de marqueurs génétiques sous sélection qui, contrairement aux méthodes existantes, utilisent à la fois la notion de différentiation génétique (ou Fst) et une information environnementale.Cette méthode a été développée de manière à limiter son taux de faux positifs de manière générale.J'offre enfin une perspective concernant les liens entre une expérience ancienne en biologie évolutive (l'expérience de jardin commun) et les nouveaux développements moléculaires et statistiques modernes.Dans la seconde partie empirique, je présente une analyse de la démographie d'A. alpina dans six populations naturelles. Outre qu'elle révèle des caractéristiques biologiques intéressantes sur cette espèce (faible espérance de vie, reproduction et survie très différentielle...), cette analyse montre que la croissance diminue et la survie augmente chez cette espèce avec la baisse de la température moyenne (donc avec l'altitude).Puisque ces analyses ne permettent pas d'exclure des hypothèses de dérive et de plasticité phénotype, je présente une analyse en jardin commun sur A. alpina qui permet de lisser les problèmes de plasticité phénotypique et qui, combinée à des analyses moléculaires, permettent d'exclure l'hypothèse de dérive.Les résultats montrent qu'il existe un syndrome phénotypique adaptatif lié à la température moyenne qui tend à des plantes plus petites, plus compactes, qui croissent et se reproduisent moins, dans les milieux froids.À l'aide des données moléculaires et de méthodes de scan génomique, je présente une liste de 40 locus qui peuvent être impliqués dans ce processus.Pour finir, je discute l'ensemble de ces résultats empiriques dans un contexte plus général d'écologie alpine. Je résume ensuite les principaux obstacles méthodologiques à l'étude de l'adaptation locale et je fourni quelques perspectives méthodologiques
Local adaptation is a micro-evolutionary phenomenon, which arises when populations of the same species are exposed to contrasted environmental conditions.If this environment exert some natural selection pressure, if an adaptive potential exists among the populations and if the gene flow is sufficiently mild, populations are expected to tend toward a local adaptive optimum.In this thesis, I study the methodological means of the study of local adaptation on the one hand, and I investigate this phenomenon along an elevation gradient in the alpine plant Arabis alpina on the other hand.In the first, methodological part, I show that the genome scan methods to detect selection using genetic markers might suffer strong false positive rates when confronted to complex but realistic datasets.I then introduce a statistical method to detect markers under selection, which, contrary to existing methods, make use of both the concept of genetic differentiation (or Fst) and environmental information.This method has been developed in order to reduce its global false positive rate.Finally, I present some perspectives regarding the relationships between the relatively old ``common garden'' experiment and the new developments in molecular biology and statistics.In the second, empirical part, I introduce an analysis of the demographic characteristics of A. alpina in six natural populations. Besides providing interesting biological information on this species (low life expectancy, strongly contrasted reproduction and survival...), these analyses show that growth increase and survival decrease with the decrease of average temperature (hence with altitude).Since these analyses do not allow us to rule out hypotheses such as drift and phenotypic plasticity, I show the results of a common garden experiment which enable us to smooth phenotypic plasticity and, when combined with molecular data, enable us to rule out the hypothesis of drift.The results show the existence of an adaptive phenotypic syndrome, in which plants are smaller, are more compact, grow slower and reproduce less in cold temperature environments.Using the molecular data, I draw a list of 40 locus which might be involved in this adaptive process.In the end, I discuss these empirical findings as a whole to place them in a more general context of alpine ecology. I sum up the main methodological challenges when studying local adaptation and offer some methodological perspectives