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Titolo/Abstract/Parole chiave

LE SIMULAZIONI DEL PROCESSO COALESCENTE IN GENETICA DI POPOLAZIONI: INFERENZE DEMOGRAFICHE ED EVOLUTIVE

Benazzo, Andrea (2012) LE SIMULAZIONI DEL PROCESSO COALESCENTE IN GENETICA DI POPOLAZIONI: INFERENZE DEMOGRAFICHE ED EVOLUTIVE. Tesi di Dottorato , Università degli studi di Ferrara.

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    Abstract

    The main goal of population genetics is to understand the factors that affect genetic variation within a species. Mathematical models are used to predict the effects on genetic variation of processes such as mutation, recombination, selection, migration and population size changes, but analytical results are difficult to obtain when these processes interact and when equilibrium conditions are not met. In these situations, common in real biological systems especially when recent human activities (e.g., stocking, urbanization, overhunting) perturb natural populations, computer simulations can be very useful. A computer simulation is a virtual experiment in which a model is used to mimic the biological process on a computer to study its properties. It is an excellent tool for understanding the functioning of complex systems. Simulations are generally used to make predictions about populations, validate statistical methods, study the properties of different sampling strategies, and estimate parameters from real data. In this thesis, I applied genetic simulations to address questions intractable with other methods. First, I analyzed the effects of violating the assumption of panmixiamade by “Extende Bayesian Skyline Plot” (EBSP) method. I showed that migration can influence the inferred demographic history of a population, suggesting wrong dynamics. Second, I used genetic simulations to analyse the performance of the EBSP method in reconstructing a population decline and to compare sampling schemes with different proportions of modern and ancient DNA. I identified some properties of the sampling scheme which clearly positively affect the demographic reconstruction, providing some simple hints for planning a genetic study when both modern and ancient samples are available. Third, I familiarized with the “Approximated Bayesian Computation” methodology and I contributed to a review article presenting the main features, with pros and cons, of this approach. Fourth, I applied the ABC procedure to analyze the hybridization history within the genus Chionodraco, and to evaluate the power of ABC in this context. Realistic demographic models were defined and compared, and evidence was found that hybridization occurred only in interglacial periods. Taken together, the results presented in this thesis confirm the importance of genetic simulations in evolutionary biology. If we consider the increasing availability of simulation packages, along with the increasing speed and storage capacity of personal computers and clusters, it is easy to predict that simulations of genetic and genomic data will spread in many fields to better explore more and more realistic, and consequently complex, models.

    Tipologia del documento:Tesi di Dottorato (Tesi di Dottorato)
    Data:16 Marzo 2012
    Relatore:Bertorelle, Giorgio
    Coordinatore ciclo:Barbujani, Guido
    Istituzione:Università degli studi di Ferrara
    Dottorato:XXIV Anno 2009 > BIOLOGIA EVOLUZIONISTICA E AMBIENTALE
    Struttura:Dipartimento > Biologia ed evoluzione
    Soggetti:Area 05 - Scienze biologiche > BIO/18 Genetica
    Parole chiave:variabilità genetica, coalescenza, simulazioni, statistica, genetic variation, coalescence, simulations, statistics
    Depositato il:27 Feb 2013 09:46

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