Dissertations / Theses on the topic 'Population Genetic Inference'
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Leslie, Stephen. "Inference of Population Stratification Using Population Genetic Data." Thesis, University of Oxford, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504423.
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Csilléry, Katalin. "Statistical inference in population genetics using microsatellites." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3865.
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Statistical inference from molecular population genetic data is currently a very active area of research for two main reasons. First, in the past two decades an enormous amount of molecular genetic data have been produced and the amount of data is expected to grow even more in the future. Second, drawing inferences about complex population genetics problems, for example understanding the demographic and genetic factors that shaped modern populations, poses a serious statistical challenge. Amongst the many different kinds of genetic data that have appeared in the past two decades, the highly polymorphic microsatellites have played an important role. Microsatellites revolutionized the population genetics of natural populations, and were the initial tool for linkage mapping in humans and other model organisms. Despite their important role, and extensive use, the evolutionary dynamics of microsatellites are still not fully understood, and their statistical methods are often underdeveloped and do not adequately model microsatellite evolution. In this thesis, I address some aspects of this problem by assessing the performance of existing statistical tools, and developing some new ones. My work encompasses a range of statistical methods from simple hypothesis testing to more recent, complex computational statistical tools. This thesis consists of four main topics. First, I review the statistical methods that have been developed for microsatellites in population genetics applications. I review the different models of the microsatellite mutation process, and ask which models are the most supported by data, and how models were incorporated into statistical methods. I also present estimates of mutation parameters for several species based on published data. Second, I evaluate the performance of estimators of genetic relatedness using real data from five vertebrate populations. I demonstrate that the overall performance of marker-based pairwise relatedness estimators mainly depends on the population relatedness composition and may only be improved by the marker data quality within the limits of the population relatedness composition. Third, I investigate the different null hypotheses that may be used to test for independence between loci. Using simulations I show that testing for statistical independence (i.e. zero linkage disequilibrium, LD) is difficult to interpret in most cases, and instead a null hypothesis should be tested, which accounts for the “background LD” due to finite population size. I investigate the utility of a novel approximate testing procedure to circumvent this problem, and illustrate its use on a real data set from red deer. Fourth, I explore the utility of Approximate Bayesian Computation, inference based on summary statistics, to estimate demographic parameters from admixed populations. Assuming a simple demographic model, I show that the choice of summary statistics greatly influences the quality of the estimation, and that different parameters are better estimated with different summary statistics. Most importantly, I show how the estimation of most admixture parameters can be considerably improved via the use of linkage disequilibrium statistics from microsatellite data.
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Anderson, Eric C. "Monte Carlo methods for inference in population genetic models /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/6368.
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Li, Xin. "Haplotype Inference from Pedigree Data and Population Data." Cleveland, Ohio : Case Western Reserve University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1259867573.
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Thesis(Ph.D.)--Case Western Reserve University, 2010Title from PDF (viewed on 2009-12-30) Department of Electrical Engineering and Computer Science Includes abstract Includes bibliographical references and appendices Available online via the OhioLINK ETD Center
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Shringarpure, Suyash. "Statistical Methods for studying Genetic Variation in Populations." Research Showcase @ CMU, 2012. http://repository.cmu.edu/dissertations/117.
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The study of genetic variation in populations is of great interest for the study of the evolutionary history of humans and other species. Improvement in sequencing technology has resulted in the availability of many large datasets of genetic data. Computational methods have therefore become quite important in analyzing these data. Two important problems that have been studied using genetic data are population stratification (modeling individual ancestry with respect to ancestral populations) and genetic association (finding genetic polymorphisms that affect a trait). In this thesis, we develop methods to improve our understanding of these two problems.
For the population stratification problem, we develop hierarchical Bayesian models that incorporate the evolutionary processes that are known to affect genetic variation. By developing mStruct, we show that modeling more evolutionary processes improves the accuracy of the recovered population structure. We demonstrate how nonparametric Bayesian processes can be used to address the question of choosing the optimal number of ancestral populations that describe the genetic diversity of a given sample of individuals. We also examine how sampling bias in genotyping study design can affect results of population structure analysis and propose a probabilistic framework for modeling and correcting sample selection bias.
Genome-wide association studies (GWAS) have vastly improved our understanding of many diseases. However, such studies have failed to uncover much of the variation responsible for a number of common multi-factorial diseases and complex traits. We show how artificial selection experiments on model organisms can be used to better understand the nature of genetic associations. We demonstrate using simulations that using data from artificial selection experiments improves the performance of conventional methods of performing association. We also validate our approach using semi-simulated data from an artificial selection experiment on Drosophila Melanogaster.
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Nunziata, Schyler O. "USING GENOMICS TO UNDERSTAND POPULATION DEMOGRAPHICS IN THE CONTEXT OF AMPHIBIAN CONSERVATION." UKnowledge, 2017. http://uknowledge.uky.edu/biology_etds/49.
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Understanding the demography of species over recent history (e.g., < 100 years) is critical in studies of ecology and evolution, but records of population history are rarely available. Large single nucleotide polymorphism datasets generated with restriction-site associated DNA sequencing (RADseq), in combination with demographic inference methods, are improving our ability to gain insights into the population history of both model and non-model species. However, to assess the performance of genetic methods it is important to compare their estimates of population history to known demography, in both simulation and empirical settings. Here, I used a simulation approach to examine the potential for RADseq datasets to accurately estimate effective population size (Ne) in Wright-Fisher populations over the course of stable and declining population trends, and distinguish stable from steadily declining populations over a contemporary time scale (20 generations). Overall, my results reveal that demographic inference using genome-wide data can be successfully applied to estimate Ne, and the detection of population-size declines. Next, I assess these methods in an empirical study from a wetland with 37 years of amphibian mark-recapture data to study the utility of genetically-based demographic inference on salamander species with documented population declines (Ambystoma talpoideum) and expansions (A. opacum). For both species, demographic model inference supported population size changes that corroborated mark-recapture data. To further validate these findings, I used individual-based population models of the pond-breeding salamander, Ambystoma opacum, with life-history parameters estimated from a long-term dataset, over a 50 year projection. My results demonstrate that genetically estimated Ne is positively correlated with census size in isolated and subdivided A. opacum populations. Finally, I investigated metapopulation patterns of genomic diversity in A. opacum and A. talpoideum and how migration may impact Ne estimation. I found strong patterns of subpopulation structuring, signatures of migration between subpopulations, and differences in Ne at the subpopulation level in both species. Overall, my findings suggest the ability of genomic data to reconstruct recent demographic changes, which can have important applications to conservation biology, and ultimately can help us elucidate the effects of environmental disturbances in the demography of endangered or declining species.
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Coelho, Alexandre Siqueira Guedes. "Abordagem Bayesiana na análise genética de populações utilizando dados de marcadores moleculares." Universidade de São Paulo, 2002. http://www.teses.usp.br/teses/disponiveis/11/11137/tde-30102002-163254/.
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Dentre os diversos aspectos geralmente observados na caracterização genética de populações naturais, a avaliação do grau de estruturação da variabilidade genética entre e dentro dos indivíduos e a obtenção de estimativas de parâmetros genéticos indicadores do sistema reprodutivo da espécie assumem grande importância. Os parâmetros de maior interesse neste caso são o índice de fixação intrapopulacional (f) e a taxa de fecundação cruzada (t). Pelo uso de simulações computacionais, este trabalho demonstra o caráter dinâmico do índice de fixação intrapopulacional em diferentes locos ao longo das gerações em decorrência do caráter finito da população e de variação nas taxas médias de fecundação cruzada entre gerações. Sugere-se que este caráter dinâmico representa uma explicação para a elevada variação, comumente reportada na literatura, das estimativas de f obtidas com locos diferentes avaliados em uma mesma população. Utilizando a abordagem Bayesiana, um modelo hierárquico de análise é proposto para a estimação de f, incorporando as informações obtidas de múltiplos locos não ligados, levando-se em conta a condicionalidade do processo de estimação ao polimorfismo dos locos utilizados. O modelo proposto incorpora o caráter dinâmico de f para diferentes locos e permite a estimação do número efetivo de indivíduos reprodutivamente ativos em uma população. Propõe-se ainda um modelo Bayesiano para a estimação da taxa de fecundação cruzada com base na informação de múltiplos locos, admitindo-se a possibilidade de ocorrência de apomixia. Os modelos propostos são avaliados por simulação e exemplos de aplicação a dados reais de marcadores moleculares codominantes são discutidos. Os resultados obtidos demonstram a aplicabilidade das metodologias propostas e o elevado potencial de aplicação da estatística Bayesiana em estudos de genética de populações.Among the various aspects generally considered in the genetic characterization of natural populations of plant species, the evaluation of the degree of genetic structure within and among individuals and the estimation of parameters related to the species mating system are of great importance. In general, considerable effort is focused on the estimation of the intrapopulation fixation index (f) and the outcrossing rate (t). Using computer simulated data, the dynamic nature of f for different loci along generations is illustrated. The dynamic nature of f is shown to result from the finite condition of populations and from the variation in the mean values of the outcrossing rates among generations. It is suggested that this dynamic behavior explains the inconsistency, commonly reported in the literature, of f estimates obtained for different loci in a given population. Using a Bayesian approach, we propose a hierarchical model for the estimation of f, incorporating information obtained from different unlinked loci and considering the conditionality of the estimation process to genetic polymorphism. The proposed model incorporates the dynamic nature of f values for different loci and allows the estimation of the effective number of reproductively active individuals in a given population. Using a similar approach, a Bayesian model is also proposed for estimating the outcrossing rate using multiple loci information and incorporating the possibility of apomixis. The models proposed are evaluated by computer simulations and examples using real data from codominant molecular markers are presented. Results obtained illustrate the applicability of the proposed methods and reveal the great potential of use of Bayesian statistics in population genetic studies.
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Wallace, Lisa Ellen. "Systematic and Population Genetic Analyses of Northern Vs Southern Yellow Lady's Slippers (Cypripedium parviflorum Vars parviflorum, pubescens, and makasin): Inference from Isozyme and Morphological Data." W&M ScholarWorks, 1997. https://scholarworks.wm.edu/etd/1539626099.
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Maritz, E. L. "Computational inference with the coalescent in molecular population genetics." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.270209.
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Jones, Mary Beatrix. "Likelihood inference for parametric models of dispersal /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/8934.
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Haber, Marc 1980. "Study of human genetic diversity : inferences on population origin and history." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/127113.
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Patterns of human genetic diversity suggest that all modern humans originated from a small population in Africa that expanded rapidly 50,000 years ago to occupy the whole world. While moving into new environments, genetic drift and natural selection affected populations differently, creating genetic structure. By understanding the genetic structure of human populations, we can reconstruct human history and understand the genetic basis of diseases. The work presented here contributes to the ongoing effort to catalogue human genetic diversity by exploring populations that have been underrepresented in genetic studies. We use variations on the genomes of populations from Central Asia, the Near East, and North Africa to reconstruct the history of these populations. We find that climate change and geography appear to be major factors shaping genetic diversity. In addition, we identify recent cultural developments and historical events that have influenced admixture and gene flow between populations, leading to the genetic diversity observed in humans today.Els patrons de diversitat genètica humana suggereixen que els humans van sorgir d’un petit grup a l’Àfrica que es va expandir ràpidament fa uns 50,000 anys per tot el planeta. En migrar cap a nous hàbitats, la deriva genètica i la selecció natural van afectar de manera diferencial les poblacions, generant una estructura genètica. Mitjançant la comprensió de l’estructura genètica de les poblacions podem reconstruir la història humana i entendre la base genètica de les malalties. Aquest treball contribueix a l’esforç continu de catalogar la diversitat genètica humana explorant poblacions poc representades en altres estudis genètics. Hem utilitzat variacions al llarg del genoma de poblacions d’Àsia Central, Orient Mitjà i el Nord d’Àfrica per tal de reconstruir la seva història. Hem observat que canvis climàtics i geogràfics semblen ser els factors principals que han modelat la diversitat genètica. A més, hem identificat esdeveniments culturals i històrics recents que afavorit les barreges i el flux genètic entre poblacions, generant la diversitat genètica observada avui en dia.
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Quinto, Cortes Consuelo Dayzu, and Cortes Consuelo Dayzu Quinto. "Inferring Demographic History of Admixed Human Populations with SNP Array Data." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/621870.
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The demographic history of human populations, both archaic and modern, have been the focus of extensive research. Earlier studies were based on a small number of genetic markers but technological advances have made possible the examination of data at the genome scale to answer important questions regarding the history of our species. A widely used application of single nucleotide polymorphisms (SNPs) are genotyping arrays that allow the study of several hundred thousand of these sites at the same time. However, most of the SNPs present in commercial genotyping arrays have often been discovered by sampling a small number of chromosomes from a group of selected populations. This form of non-random discovery skews patterns of nucleotide diversity and can affect population genetic inferences. Although different methods have been proposed to take into account this ascertainment bias, the challenge remains because the exact discovery protocols are not known for most of the commercial arrays. In this dissertation, I propose a demographic inference pipeline that explicitly models the underlying SNP discovery and I implement this methodology in specific examples of admixture in human populations when only SNP array data are available. In the first chapter, I describe the developed pipeline and applied it to a known example of recent population admixture in Mexico. The inferred time of admixture between Iberian and Native American populations that gave rise to admixed Mexicans was in line with historical records, as opposed to previous published underestimates. Next, I examined different demographic models on the first human settlement in Easter Island and determined that the island of Mangareva is the most likely point of origin for this migration. Finally, I investigated the dynamics of the admixture process between the ancestral Jomon and Yayoi populations in different locations across Japan. The estimates of the time of this encounter were closer to dates inferred from anthropological data, in contrast with past works. The results show that the proposed framework corrects ascertainment bias to improve inference in cases when only SNP chip data are available, and for genotype data originated from different platforms.
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Gladstein, Ariella. "Inference of Recent Demographic History of Population Isolates Using Genome-Wide High Density SNP Arrays and Whole Genome Sequences." Thesis, The University of Arizona, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10839026.
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In this dissertation I addressed the problem of SNP array bias when finding runs of ho- mozygosity. I demonstrated the pitfalls of using uninformed methods for finding runs of homozygosity and provide better alternatives, including a more reliable algorithm for identi- fying runs of homozygosity than the most commonly used program. I then provide a review of Ashkenazi population genetics. Next, I developed software to efficiently run millions of whole chromosome simulations, which is publicly available through GitHub, DockerHub, and on the CyVerse Discovery Environment. I applied my computational method to use Approximate Bayesian Computation to test models of Ashkenazi Jewish demographic his- tory. I found that the Ashkenazi Jews are comprised of genetically distinct subgroups from Eastern and Western Europe, as a result of massive population growth in the Eastern Ashkenazi Jews, but not in the Western Ashkenazi Jews. I further confirmed that the Ashkenazi Jews do not primarily originate from Khazaria. Finally, I created a correction for SNP array ascertainment bias in the median and total length of runs of homozygosity, and applied this correction to world-wide human populations. However, I found that ascertainment bias plays a minor role compared to SNP array bias in human populations.
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Ansari, M. Azim. "Inference of recombination properties in bacteria from whole genomes." Thesis, University of Oxford, 2014. https://ora.ox.ac.uk/objects/uuid:b830a37a-fa7e-4b68-9868-fc5c629d45f5.
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The concept of species in bacteria is a matter of contention. The current definition is based on DNA-DNA hybridisation and does not account for evolutionary forces that are important in demarcating species. In this thesis we investigate two evolutionary forces that are important in speciation in bacteria, propose novel statistical models for them and infer parameters of interest. We present the first attempt at inferring the bias in the recombination process from whole bacterial genomes. Despite empirical evidence that recombination is biased and theoretical results that this bias is important in speciation, it is usually ignored. We propose a coalescent based model that accounts for the bias in the recombination process. We use approximate Bayesian computation for inference and describe an efficient method for simulating from the model. We show that our method performs well on simulated datasets and is robust to slight misspecification of the history of the samples. Application of our method to a Bacillus cereus dataset shows that it contain evidence that the recombination process depends on the evolutionary distance between donors and recipients. We demonstrate that the rate of bias in the recombination process for this dataset is far lower than what theoretical studies require for the spontaneous generation of populations that can be called species under neutral model. Next we propose a model for occurrence of adaptive events on a phylogenetic tree. We use the model to infer the boundaries of clusters on a phylogenetic tree that correspond to ecologically distinct lineages. we characterise our method using simulated datasets and show that it is conservative in estimating the number of adaptive events. Finally we apply our method to two bacterial datasets of Salmonella enterica and Vibrionaceae. We show that there is decisive evidence that isolates in these datasets partition into numerous ecologically distinct lineages and use our method to delineate the boundaries of these lineages.
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Delaney, Paul L. IV. "Testing for Cryptic Diversity and Inference of Population Structure in the Cosmopolitan Hoplonemertean Emplectonema gracile (Nemertea)." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/6108.
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Emplectonema gracile (Johnston 1837) is a hoplonemertean of marine intertidal hard-bottom communities and is distributed throughout the Northern Hemisphere. Although possessing a planktonic larval stage in its life history, the range of such cosmopolitan marine invertebrate species is often explained by cryptic speciation and anthropogenic transport. The purpose of this study is to test for possible cryptic species using mtDNA markers (COI and 16S rDNA) and to investigate population structure in E. gracile over a portion of its geographic range using mtDNA markers and ddRADseq nuclear SNP data. The results of both phylogenetic- and tree-based species delimitation revealed that E. gracileis a morphotype containing cryptic species. Three North Atlantic and one Pacific coast population are inferred as one species (E. gracile sensu stricto) and two Pacific coast populations (Akkeshi, Japan and Charleston, Oregon) are inferred as another species (Emplectonemasp 1), strongly confirming an earlier study and extending the range of the latter species to the Pacific coast of Japan. Anthropogenic transport is suggested as the likely mode of transport for E. gracile.Both Fst, PCA and haplotype network analyses suggest a lack of differentiation between E. gracile populations separated by large geographic distances.In contrast corresponding analyses forEmplectonemasp. 1 indicate differentiation between the two populations sampled. Further research will be necessary to reveal if rare anthropogenic transport or natural dispersal (larval transport, rafting) between geographically adjacent yet to be delimitedE. gracile morphotype populations is responsible for its seemingly disjunct distribution.
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Peters, Melinda Dean. "Genetic analyses of the federally endangered Echinacea laevigata using amplified fragment length polymorphisms (AFLP) ? Inferences in population genetic structure and mating system." NCSU, 2005. http://www.lib.ncsu.edu/theses/available/etd-10292005-111050/.
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Echinacea laevigata is a federally endangered species and a close relative of the medicinally important E. purpurea. The species has 24 recognized populations restricted to four states (VA, NC, SC, GA). To determine the population structure and outcrossing rate across the range of the species, we conducted AFLP analysis using four primer combinations for 22 populations. The genetic diversity of this species was found to be high based on the level of polymorphic loci (200 of 210 loci; 95.24%) and Nei?s gene diversity (ranging from 0.1398 to 0.2606; overall 0.2611). There was significant population genetic differentiation (GST of 0.2941), suggesting possible adaptation to local environments. Results from the AMOVA analysis suggest that a majority of the genetic variance is attributed to variation within populations (70.26%). These results are congruent to a previous allozyme study that examined the genetic makeup of 11 of the 24 populations, excluding any Georgia populations. An isolation by distance (IBD) analysis indicated that genetic differentiation among populations is a function of geographic distance, although long-distance gene dispersal (LDGF) between some populations was suggested based on the NJ tree. An estimate of the outcrossing rate based on genotypes of progenies from six of the 22 populations using a multilocus estimate was 0.833-1.2, where 1.2 is considered complete outcrossing, suggesting that the species is predominantly outcrossing. The remaining populations of E. laevigata have significant levels of population diversity, which is encouraging because the long-term survival of this species will depend on moderate to high levels of genetic diversity and management efforts can focus on other issues instead of increasing the genetic diversity.
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Wang, Heming. "LOCAL ANCESTRY INFERENCE AND ITS IMPLICATION IN SEARCHING FOR SELECTION EVIDENCE IN RECENT ADMIXED POPULATION." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1473439566976121.
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Mattucci, Federica <1982>. "Conservation genetics of European wildcat (Felis silvestris silvestris): a wide and integrating analysis protocol for admixture inferences and population structure." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amsdottorato.unibo.it/6459/.
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Introgression of domestic cat genes into European wildcat (Felis silvestris silvestris) populations and reduction of wildcats’ range in Europe, leaded by habitat loss and fragmentation, are considered two of the main conservation problems for this endangered feline. This thesis addressed the questions related with the artificial hybridization and populations’ fragmentation, using a conservation genetics perspective.
We combined the use of highly polymorphic loci, Bayesian statistical inferences and landscape analyses tools to investigate the origin of the geographic-genetic substructure of European wildcats (Felis silvestris silvestris) in Italy and Europe.
The genetic variability of microsatellites evidenced that European wildcat populations currently distributed in Italy differentiated in, and expanded from two distinct glacial refuges during the Last Glacial Maximum. The genetic and geographic substructure detected between the eastern and western sides of the Apennine ridge, resulted by adaptation to specific ecological conditions of the Mediterranean habitats.
European wildcat populations in Europe are strongly structured into 5 geographic-genetic macro clusters corresponding to: the Italian peninsular & Sicily; Balkans & north-eastern Italy; Germany eastern; central Europe; and Iberian Peninsula. Central European population might have differentiated in the extra-Mediterranean Würm ice age refuge areas (Northern Alps, Carpathians, and the Bulgarian mountain systems), while the divergence among and within the southern European populations might have resulted by the Pleistocene bio geographical framework of Europe, with three southern refugia localized in the Balkans, Italian Peninsula and Iberia Peninsula.
We further combined the use of most informative autosomal SNPs with uniparental markers (mtDNA and Y-linked) for accurately detecting parental genotypes and levels of introgressive hybridization between European wild and domestic cats. A total of 11 hybrids were identified. The presence of domestic mitochondrial haplotypes shared with some wild individuals led us to hypnotize the possibility that ancient introgressive events might have occurred and that further investigation should be recommended.
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Barrigana, Ramos Da Costa R. J. "Stochastic models and statistical inference in evolutionary genetics : using DNA sequence data to learn about population divergence and speciation." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/1568254/.
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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.
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Hsieh, PingHsun. "Model-Based Population Genetics in Indigenous Humans: Inferences of Demographic History, Adaptive Selection, and African Archaic Admixture using Whole-Genome/Exome Sequencing Data." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/612540.
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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.
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Hoyo, Leal Alberto del. "Filogenia y genética poblacional del género Androcymbium (Colchiceae)." Doctoral thesis, Universitat de Girona, 2006. http://hdl.handle.net/10803/7908.
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En este trabajo se ha estudiado el género Androcymbium (Colchicaceae) a dos niveles: macro- y micro- evolutivo. A nivel microevolutivo se ha obtenido que para las especies de Sudáfrica oriental la componente interpoblacional es muy importante para explicar la distribución de la variabilidad genética, igual que en Sudáfrica occidental. Para las especies de Namibia, la componente mas importante es la intrapoblacional, igual que en el norte de África. A nivel macroevolutivo se ha obtenido que el origen del género se sitúa en Sudáfrica occidental, datándose en 11,22 ma. Este género ha resultado ser parafilético, dada la aparición conjunta en un mismo clado de especies de Androcymbium y Colchicum, y las especies del norte de África derivan de un taxa de Namibia que llegó a la cuenca Mediterránea a principios del Plioceno gracias a la formación de un corredor árido entre las zonas áridas del suroeste y este de África.In this study the genus Androcymbium (Colchicaceae) has been studied at two levels: macro- and micro- evolutive. At the microevolutive level it has been obtained that in the western south African species, the inter-populational component is very important to explain the distribution of the genetic variability, the same case like in western South Africa. In the Namibian species, the main component in the intra-populational, the same case as in north Africa. At the macroevolutive level it has obtained that the origin of the genus is located in western South Africa and it has been dated in 12.22 mya. This genus is paraphyletic because of the inclusion of some species of Colchicum within Androcymbium, and the origin of the northern Africa taxa are related with a Namibian taxa that colonized the Mediterranean basin at the beginning of Pliocene thanks to the formation of an arid corridor between the arid areas of south-western and eastern Africa.
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Cui, Lingfei. "A Likelihood Method to Estimate/Detect Gene Flow and A Distance Method to Estimate Species Trees in the Presence of Gene Flow." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406158261.
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Schug, Malcolm D. "Invasion of a Freshwater Archipelago: Inferences From Population Genetics of Mosquitofish (Gambusia Hubbsi) in Blueholes on Andros Island, Commonwealth of the Bahamas /." The Ohio State University, 1995. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487931512618629.
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Williamson, Jill Marie. "Global investigation into the population genetic structure of Ciyptosporidium hominis based on a whole genome multi-locus SNP-typing scheme; inferences about the existence of biogeographical partitions." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/15002.
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Previously considered a disease of importance strictly to veterinary medicine Cryptosporidium has emerged as a highly successful opportunistic parasitic protozoan posing a significant threat to public health.
Intricate transmission dynamics, a complex epidemiology, and parasite robustness and persistence have all hampered efforts for the prevention and control of Cryptosporidium. Genetic diversity is a prerequisite to better understand the role of parasite variation in disease etiology and pathobiology. The extent of genetic
structure among C. hominis and C. parvum, the two most prevalent species of Ciyptosporidium, is insufficiently understood with the population structure still largely suspect. We report on the distribution of genetic diversity and possible existence of geographic partitions
among C. hominis subpopulations from Australia, Kenya, Peru and Scotland. We studied C. hominis population genetic structure using a multi-locus SNP-type (M1St) established from 45 single nucleotide
polymorphic loci covering 13 bio-functionally relevant proteins. A total of 77 isolates from 4 intercontinental
subpopulations were genetically typed. Twenty-four unique M1St’s were identified, 25% of which were found to be located within one or more subpopulations. Diversity statistical tests to discern the degree of ultrapopulation and inter-population diversity, genetic distance, and genetic identity variation were used to examine
the population genetic structure. Within-population differences among subpopulations account for 69.6% of genetic variation; differentiation among subpopulations constitute 30.4%. Genetic distances among
subpopulations averaged 0.048 and varied from 0.03 4 between the Australian and Scotland subpopulations to 0.061 between Scotland and Kenya. More broadly, our results argue that too wide of a geographic boundary can impede rather than advance genetic population studies and that the practice of sampling more regional
subpopulations be adopted. A fifth subpopulation, a combination of C. hominis and C. parvum isolates, was drawn upon to
determine whether or not a pre-defined allelic profile of single nucleotide polymorphisms (SNPs) was an efficient and reliable means for species specific identification. Results showed the SNP-typing approach’s ability to distinguish between different species as well as being capable of uncovering potential novel SNPs
within an individual isolate. We propose that the patterns of genetic variation are influenced by geography and that the
identification of host adapted geographically conserved sub-genotypes within a defined geographic cohort
versus widespread dissemination of genetically stable isolates could ultimately provide a valuable basis for the
predictive epidemiology of Cryptosporidiwn infection. Our fmdings provide an alternative method for species detection, a crucial element to epidemiological investigations.
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Tournebize, Rémi. "Influence des variations spatio-temporelles de l’environnement sur la distribution actuelle de la diversité génétique des populations." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTT140.
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Ce projet vise à comprendre comment la structure génétique intra-spécifique d'espèces végétales tropicales emblématiques et de l’espèce humaine a été affectée par les variations spatio-temporelles de l’environnement actuel et passé. Nous avons développé une approche d’inférence génétique basée sur la théorie de la coalescence pour évaluer l’influence potentielle des changements climatiques passés sur l’évolution de la distribution géographique et de la diversité génétique neutre et/ou adaptative d’Amborella trichopoda Baill. en Nouvelle-Calédonie (espèce-sœur des angiospermes, données NGS et microsatellites), de Coffea canephora Pierre ex A. Froehn en Afrique tropicale (caféier Robusta, données NGS) et de populations européenne et africaine (Luhya, Kenya) d’humains anatomiquement modernes (données NGS issues du Projet 1000 Génomes). Nos travaux suggèrent que les fluctuations climatiques du Pleistocène tardif ont joué un rôle majeur sur l’évolution de la diversité génétique des espèces étudiées de milieux tropicaux et tempérés, avec une empreinte remarquable du Dernier Maximum Glaciaire (DMG, 21 000 ans avant le présent). Les contractions démographiques associées à la glaciation planétaire ont vraisemblablement conduit à la divergence entre les lignées génétiques d’Amborella et participé à l’accumulation des différences génétiques entre les lignées de C. canephora. Nos résultats suggèrent que les événements de glaciation planétaire ont probablement entraîné une différenciation génétique idiosyncratique dans les forêts tropicales humides mais l’intensité de cette réponse semble avoir varié entre espèces. Nous avons également identifié de nombreux événements passés de sélection dans les génomes de la population humaine européenne qui ont été vraisemblablement provoquées par les conditions environnementales au cours du DMG. Les adaptations phénotypiques associées ont probablement assuré le maintien de l’expansion démographique en dépit des pressions de sélection nouvelles auxquelles les populations étaient confrontées au cours du dernier âge glaciaire en EuropeThis project aims at understanding how the structure of the intra-specific genetic diversity in emblematic tropical plant species and in the human species was shaped by the spatiotemporal variation of current and past environments. We developed a genetic inference approach based on the coalescent theory to assess the potential impact of past climatic change onto the evolution of the geographic range and of the neutral and/or adaptive genetic diversity in Amborella trichopoda Baill. in New Caledonia (sister-species of all extant angiosperms, NGS and microsatellite datasets), in Coffea canephora Pierre ex A. Froehn in tropical Africa (Robusta coffee, NGS dataset) and in North-Western European and African (Luhya, Kenya) human populations (NGS dataset 1000 Genomes Project). We found that the climatic fluctuations of the Late Pleistocene influenced the evolution of genetic diversity in these species distributed in temperate and tropical environments. The environmental conditions during the Last Glacial Maximum (LGM, 21.000 years before present) appear as an important factor. The demographic contraction associated with the last global glaciation influenced the divergence between Amborella genetic lineages and contributed to the accumulation of genetic differences between C. canephora lineages. Our results suggest that global glaciation events likely drove idiosyncratic genetic differentiation in tropical rain forests but the intensity of this response varied between species. We also identified multiple events of selection in the genomes of the European human population which were likely triggered by the environmental conditions during the LGM. The associated phenotypic adaptations probably allowed the paleo-populations to maintain their demographic expansion despite the new kinds of selective pressure they faced during the last glacial age in Europe
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Hivert, Valentin. "Analyse de la différenciation génétique à l'ère des nouvelles technologies de séquençage." Electronic Thesis or Diss., Montpellier, SupAgro, 2018. http://www.theses.fr/2018NSAM0061.
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L’avancée des technologies de séquençage et de génotypage à haut-débit permet la comparaison de patrons de polymorphisme à un très grand nombre de marqueurs génétiques. L'analyse de la différenciation des populations à une échelle génomique rend ainsi possible la recherche de régions génomiques impliquées dans l’adaptation locale des organismes à leur environnement. Dans cette thèse, nous avons suivi deux approches complémentaires pour caractériser la différenciation génétique à partir de données de génotypage à haut-débit. Dans un premier temps, nous avons développé un estimateur non-biaisé du paramètre FST pour des données de génotypage d’individus en mélange (Pool-seq). La construction de cet estimateur, dans un contexte d’analyse de variance, a nécessité de bien prendre en compte les différentes étapes de l’échantillonnage : des gènes dans le mélange d'individus et des lectures de séquençage parmi les gènes. Nous montrons qu’il surpasse les estimateurs utilisés jusqu'à présent. Dans un deuxième temps, nous avons développé une méthode d'analyse de la différenciation génétique à l'échelle du génome, dans le cadre d’un modèle bayésien hiérarchique, pour distinguer l'effet de la démographie de celui de la sélection. Pour cela, nous avons implémenté plusieurs extensions au modèle SelEstim, pour exploiter l'information de déséquilibre de liaison entre les marqueurs. Une première stratégie a consisté à analyser des données multialléliques, obtenues par le regroupement local de marqueurs SNPs en blocs d'haplotypes. Une stratégie alternative a consisté à intégrer un modèle de lissage prenant en compte la dépendance spatiale entre marqueurs adjacents. Cette approche repose sur l'analyse de données bialléliques, ce qui la rend applicable à la fois à des données de génotypage individuel et à des données Pool-seq. Nous discutons, sur la base de l'analyse de jeux de données simulées, des mérites relatifs de ces différentes approchesThe advent of high throughput sequencing and genotyping technologies allows the comparison of patterns of polymorphisms at a very large number of genetic markers. The analysis of genetic differentiation between populations at a whole-genome scale makes it possible to characterize genomic regions involved in the local adaptation of organisms to their environment. In this thesis, we followed two complementary approaches to characterize differentiation from high-throughput genotyping data. First, we developed an unbiased estimator of the parameter FST for individuals sequenced in pools (Pool-seq). Deriving this estimator, in an analysis-of-variance framework, required to properly account for the different sampling steps: individual genes from the pool, and sequence reads from these genes. We show that it outperforms previously proposed estimators. Second, we developed a method to analyze genetic differentiation at a whole-genome scale in a hierarchical bayesian framework, in order to untangle the effect of demography from that of selection. To this end, we implemented different extensions to the SelEstim model, aimed at leveraging the information from linkage disequilibrium between markers. A first approach consisted in analyzing multiallelic data derived from the local clustering of SNPs into haplotype blocks. An alternative strategy consisted in including a smoothing model, which accounts for the spatial dependency between neighboring markers. This strategy relies on the analysis of biallelic data, and can be used both with individual genotype data or Pool-seq data. We discuss the relative benefits of these different approaches, based on the analysis of simulated data sets
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Pereira, Renato Nunes. "Modelo hierárquico bayesiano na determinação de associação entre marcadores e QTL em uma população F2." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-25042012-161429/.
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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.
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Simon, Helmut. "Mutation, Polymorphism and Population Genetic Inference." Phd thesis, 2022. http://hdl.handle.net/1885/261178.
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Prior to the advent of DNA sequencing technology, the progress of population genetics was constrained by the unavailability of molecular-level data to test competing hypotheses and models. Genomic data obtained from DNA sequencing has revealed that evolutionary processes in real populations diverge substantially from the simplifying assumptions of earlier models. In this thesis, I have applied more recent advances in data availability, statistical methods and computational technology to explore the consequences of relaxing the assumptions of earlier models to better reflect what has been learned about populations and the genome. I have focused on two main areas arising from the study of mutation: characterising intragenomic mutational heterogeneity and making inferences about the history of a population from variant data.
In the first instance, I address two primary causes of mutation rate heterogeneity: sequence context and recombination. Mutation rates have also been shown to vary, not only between different bases and mutation directions, but also with genomic location at scales ranging from individual nucleotides to multi-megabase sized regions. The patterns in the heterogeneity of mutation rates at varying scales provide can be used to increase understanding of factors influencing mutation and of the relative magnitude of their effects. I also examined the variance in the probability of polymorphism when conditioned on contexts of various sizes and found that when the 12 point mutation directions are considered separately, variance due to context increases significantly as we move from 3-mer to 5-mer and from 5-mer to 7-mer contexts. However, when all mutations are considered in aggregate, these differences are outweighed by the effect of interaction between the central base and its immediate neighbours. I then calculated the variance due to recombination and the probability that a recombination event causes a mutation, employing statistical procedures used in the analysis of time series to take account of the spatial auto-correlation of recombination and mutation rates along the genome. My results support the view that genomic diversity in recombination hotspots arises largely from a direct effect of recombination on mutation rather than predominantly from the effect of selective sweeps.
I also investigated how polymorphism data can be used to make inferences about historical evolutionary influences without the assumptions on the demographic history of a population that have previously been required. I develop a method of testing for selection that can use null models incorporating such a demographic history and that benefits from the power of using the full likelihood of the null model. I compare this method to the well-known statistic Tajima's D and also use it to investigate some regions of the human genome that are candidates for the operation of natural selection. Methods for inferring the genealogical history of a sample from a population have also relied on the assumption that the population has maintained a constant size or some related constraint. In Chapter 4, I present a method of making such inferences without relying on assumptions of this type. This method makes use of Bayesian MCMC techniques with a novel approach to the selection of prior distributions.
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Steinrücken, Matthias [Verfasser]. "Multiple merger coalescents and population genetic inference / vorgelegt von Matthias Steinrücken." 2009. http://d-nb.info/998939536/34.
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Delport, Wayne. "Population genetic inference of demographic processes in the African Wild Silk Moth, Gonometa postica (Lasiocampidae)." Thesis, 2006. http://hdl.handle.net/2263/29290.
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The African Wild Silk moths (Gonometa spp., Lasiocampidae) are species that are presently of particular economic interest in southern Africa. Both Gonometa postica and G. rufobrunnea, two species of African Wild Silk moth native to southern Africa, have been shown to possess a silk fibre of exceptional quality. A small-scale cottage industry utilizing the silk of Gonometa species currently exists in southern Africa, yet a consistent complaint is the lack of supply of cocoons. The Gonometa species in southern Africa have been shown to exhibit large inter-annual population fluctuations. However, it is uncertain whether eruptions are only the result of local populations experiencing ideal conditions or whether current eruptions are initiated by dispersal of individuals from eruptive populations in previous generations. A second observation, regarding eruptions, is that they are patchily distributed at both the local (within outbreaks) and regional scale (across southern Africa). In this thesis I have studied population eruptions through distribution analysis of three years of presence/absence data, and through spatial and temporal population genetic analysis. The analysis of population genetic data allows the inference of population demographic parameters such as population size fluctuations and migrations. In particular, the use of microsatellite markers allows a high-resolution analysis of the connectivity of populations, and provides signal of population size fluctuations. I utilise both mitochondrial DNA control region sequences and polymorphic microsatellite loci to make inferences of population processes in G. postica, using a combination of both analytical and simulation model analysis approaches. The results, in general, indicate that dispersal of moths across South Africa is extensive. These results are further considered in light of the effects of population size fluctuations on spatial genetic pattern, where the potential exists for unstable population demography to influence the inference of dispersal from population genetic data. The population genetic analyses presented here allow the inference of the extent of a local population/outbreak, and the degree of movement between local populations. Given that a large-scale population dynamics project based on G. postica is currently under development, the results determine the geographical extent at which the population dynamics study should be conducted. Furthermore, the population genetics data generated will contribute to the construction of a population dynamics model, including abiotic and biotic variables, which will allow a better understanding of eruptions in this species.Thesis (PhD (Genetics))--University of Pretoria, 2006.
Genetics
unrestricted
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"Spatial Genetic Structure under Limited Dispersal: Theory, Methods and Consequences of Isolation-by-Distance." Doctoral diss., 2015. http://hdl.handle.net/2286/R.I.38573.
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abstract: Isolation-by-distance is a specific type of spatial genetic structure that arises when parent-offspring dispersal is limited. Many natural populations exhibit localized dispersal, and as a result, individuals that are geographically near each other will tend to have greater genetic similarity than individuals that are further apart. It is important to identify isolation-by-distance because it can impact the statistical analysis of population samples and it can help us better understand evolutionary dynamics. For this dissertation I investigated several aspects of isolation-by-distance. First, I looked at how the shape of the dispersal distribution affects the observed pattern of isolation-by-distance. If, as theory predicts, the shape of the distribution has little effect, then it would be more practical to model isolation-by-distance using a simple dispersal distribution rather than replicating the complexities of more realistic distributions. Therefore, I developed an efficient algorithm to simulate dispersal based on a simple triangular distribution, and using a simulation, I confirmed that the pattern of isolation-by-distance was similar to other more realistic distributions. Second, I developed a Bayesian method to quantify isolation-by-distance using genetic data by estimating Wright’s neighborhood size parameter. I analyzed the performance of this method using simulated data and a microsatellite data set from two populations of Maritime pine, and I found that the neighborhood size estimates had good coverage and low error. Finally, one of the major consequences of isolation-by-distance is an increase in inbreeding. Plants are often particularly susceptible to inbreeding, and as a result, they have evolved many inbreeding avoidance mechanisms. Using a simulation, I determined which mechanisms are more successful at preventing inbreeding associated with isolation-by-distance.Dissertation/Thesis
Doctoral Dissertation Molecular and Cellular Biology 2015
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Sousa, Vitor C. "Inference of admixture and population size changes in structured populations with applications to conservation genetics." Doctoral thesis, 2009. http://hdl.handle.net/10451/1825.
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Tese de doutoramento, Biologia (Biologia Evolutiva), 2010, Universidade de Lisboa, Faculdade de CiênciasReconstructing the demographic history of populations with genetic data from present-day samples is a challenging inference problem. The general aim of this thesis is to determine whether major demographic events can be detected, quantified and dated using model-based inference approaches. The emphasis is on the study of admixture events and population size changes, which are relevant for conservation biology. Approximate Bayesian computation (ABC) methods were developed to make inference under models involving admixture. These methods were first implemented into a general and relatively simple model and later improved to deal with up to four populations and two admixture events. An ABC approach based onallele-frequencies was tested and compared in detail with a full-likelihood methods. Several aspects of theABC methodology were investigated in a simulation study, such as the choice of summary statistics anddistance metrics. The estimates obtained with the ABC approximated well the full-likelihood. Moreover, amodel choice procedure was developed to assess the relative probability of alternative admixture and populationsplit models. The results indicate that the ABC approach is able to identify with high probability thecorrect model. These methods have been implemented in a user-friendly software.The effect of population structure on estimates of population size change was also investigated. A simulationstudy was performed to assess the robustness of full-likelihood methods to deviations due to populationstructure. The results show a clear effect of population structure, leading to the detection of spurious bottlenecks,which depends on the sampling scheme and is stronger with limited gene-flow level, and higherscaled mutation rate.The methods developed and investigated here were applied to study two critically endangered freshwaterfish species, Iberochondrostoma lusitanicum and I. almacai. Results suggest that both species were highlystructured, and suffered recent population declines. The re-analysis of I. lusitanicum data with the ABCmethod developed suggested that the potential admixture events were likely due to shared polymorphism.Regarding the bottleneck signatures, the results suggest that the observed data cannot be explained by thepopulation structure alone, indicating that these species are undergoing a population decline.Overall, the results of this thesis may contribute to a better understanding of the potential and limitations of model-based inference methods using genetic data.
The work presented in this dissertation was developed with the support of the Fundação para a Ciência e a Tecnologia:PhD Fellowship (SFRH/BD/22224/2005) and by the Projects Demographic and genetic responses to habitat fragmentationand habitat loss in large forest mammals (PTDC/BIA-BDE/71299/2006), GENESTREAM - Landscape genetics of freshwaterfishes: the geographical dimension of genetic diversity (PTDC/BIA-BDE/66519/2006), and Evolutionary processes in the originof Hotspots for Biodiversity': insights from southern Portuguese areas based on novel nuclear multilocus approaches in targetfreshwater fishes and amphibians (PTDC/BIA-BDE/69769/2006).
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Drummond, Alexei James. "Computational Statistical Inference for Molecular Evolution and Population Genetics." 2002. http://hdl.handle.net/2292/1053.
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This research aims to develop new methods and software for evolutionary inference. The focus will be on two challenges that analysis of molecular data in the genomic age provides: (1) measurably evolving populations and (ii) evolution of RNA secondary structure. Molecular sequence data is increasing in length, and also acquiring a depth in the rime dimension (for example, HIV-1, human influenza A, and ancient mtDNA). This has provided an innovative research direction, for which explicit evolutionary inference methods are required. The first aim of this research is to provide new statistical methods and new bioinformatic tools (software packages) to assist in tackling this new problem in evolutionary biology. Both maximum likelihood and Bayesian inference methods are developed for the purpose of estimating substitution rates and concerted changes in the substitution rate. In addition, with the rapid succession of newly sequenced full genomes, researchers can no longer use simple molecular sequence similarity to infer homology. Knowledge of molecular structure needs to be incorporated into evolutionary inference methods. The evolutionary relationship between sequence and structure is still poorly understood and the new wealth of data provides an exciting opportunity to guide theoretical developments. The second major objective of this research is to use the wealth of sequence data available to explore the role and impact of RNA secondary structure on evolution. To this end, empirical studies and simulations are undertaken to explore the role of RNA secondary structure in the evolution of 16S-like rRNA-encoding genes. Finally the inference of spatially resolved populations from gene sequences is briefly investigated. This research project has both computational and conceptual objectives. In both cases, the concrete result of these objectives will be new statistical models and computer software for evolutionary inference and a better understanding of the action of molecular and population processes during evolution.
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GRADIE, MARGARET ISABEL. "INFERENCE ON GENETIC STRUCTURE FROM POTENTIAL MATES ANALYSIS, A STUDY OF TWO HISTORICAL POPULATIONS (ANTHROPOLOGY, DEMOGRAPHY)." 1986. https://scholarworks.umass.edu/dissertations/AAI8612041.
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The objective of this research is to better understand the number of potential mates as a variable for analyzing the processes which lead to genetic structure. To do this, variation in the number of potential mates over space and time is examined. In particular, the effects of demographic change, geographic location, and kinship within the mate pool are examined for their influence on the size of the mate pool, mating patterns, and genetic structure, in two historical populations. The method compares the effects of these variables in populations with different geographic structures, but similar histories of population growth and decline. The geographic difference is relevant since most potential mates analysis has been applied to island isolates. The similarity in demographic history is important since it allows some control over between-population comparisons. The study populations are North Ronaldsay, one of the Orkney Islands located off the east coast of Scotland, and Ashfield, Massachusetts, a town in the Connecticut River Valley. These populations fill the requirements of the study in that they share similar demographic histories, but are different in geographic characteristics. The expectations represent a null hypothesis that both populations should look the same. The results show that change in numbers of potential mates over time is not strictly related to change in population size, but responds to changes in the age range in which males enter the mate pool. These changes are not the result of distortions in the age-sex structure. There is considerable variation between individuals in their numbers of available mates in all time periods in both populations. North Ronaldsay shows very little intermarriage with neighboring populations, while in Ashfield geographically close populations contribute a significant number to the mate pool. Individuals who fail to marry on North Ronaldsay do not appear to have a larger proportion of kin as potential mates. In fact, there appear to be distinct mating preferences for some categories of kin. In Ashfield, very little kinship within the mate pool is observed. This is consistent with other studies of kinship in Connecticut Valley towns.
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Oliveira, Rita Isabel Ribeiro Miranda de. "Towards a wide genetic approach for the European wildcat [Felis silvestris silvestris] conservation: improving noninvasive molecular techniques, population analysis and admixture inferences." Doctoral thesis, 2013. https://repositorio-aberto.up.pt/handle/10216/69691.
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Oliveira, Rita Isabel Ribeiro Miranda de. "Towards a wide genetic approach for the European wildcat [Felis silvestris silvestris] conservation: improving noninvasive molecular techniques, population analysis and admixture inferences." Tese, 2013. https://repositorio-aberto.up.pt/handle/10216/69691.
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