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9 results for “Empirical Population Genetics”
Data from: Does human-induced hybridization have long-term genetic effects? Empirical testing with domesticated, wild and hybridized fish populations
Current conservation practices exclude human-generated hybridized populations from protection, as the genetic effects of hybridization in the wild have been observed to be long-lasting based on neutral genetic markers and are considered potentially irreversible. Theory, however, predicts otherwise for genes under selection. We transplanted combinations of wild, domesticated and hybridized populations of a fish species to new environments. We then compared survival, phenotypic variation and plasticity to determine whether hybridization affects adaptive potential after multiple generations of selection in the wild. Although the fitness of our hybridized populations at the onset of hybridization cannot be assessed, our results suggest that within five to eleven generations, selection can remove introduced foreign genes from wild populations that have hybridized with domesticated conspecifics. The end result is hybridized populations that, in terms of survival, phenotypic plasticity, mean trait expression and overall general responses to environmental change, closely resemble neighbouring wild populations. These results have important implications for considering the potential conservation value of hybridized populations and illustrate the effectiveness of selection in a local environment.
Data from: Effect of microsatellite selection on individual and population genetic inferences: an empirical study using cross-specific and species-specific amplifications
Although whole-genome sequencing is becoming more accessible and feasible for nonmodel organisms, microsatellites have remained the markers of choice for various population and conservation genetic studies. However, the criteria for choosing microsatellites are still controversial due to ascertainment bias that may be introduced into the genetic inference. An empirical study of red deer (Cervus elaphus) populations, in which cross-specific and species-specific microsatellites developed through pyrosequencing of enriched libraries, was performed for this study. Two different strategies were used to select the species-specific panels: randomly vs. highly polymorphic markers. The results suggest that reliable and accurate estimations of genetic diversity can be obtained using random microsatellites distributed throughout the genome. In addition, the results reinforce previous evidence that selecting the most polymorphic markers leads to an ascertainment bias in estimates of genetic diversity, when compared with randomly selected microsatellites. Analyses of population differentiation and clustering seem less influenced by the approach of microsatellite selection, whereas assigning individuals to populations might be affected by a random selection of a small number of microsatellites. Individual multilocus heterozygosity measures produced various discordant results, which in turn had impacts on the heterozygosity-fitness correlation test. Finally, we argue that picking the appropriate microsatellite set should primarily take into account the ecological and evolutionary questions studied. Selecting the most polymorphic markers will generally overestimate genetic diversity parameters, leading to misinterpretations of the real genetic diversity, which is particularly important in managed and threatened populations.
Simulation and empirical data for "Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations"
<p>Simulation data and empirical data used to generate figures from "Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations". Can be used with code provided on the associated github to regenerate the figures. </p>
Data from: Effect of microsatellite selection on individual and population genetic inferences: an empirical study using cross-specific and species-specific amplifications
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Data from: Does human-induced hybridization have long-term genetic effects? Empirical testing with domesticated, wild and hybridized fish populations
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Data from: Genetic load, inbreeding depression and hybrid vigor covary with population size: an empirical evaluation of theoretical predictions
Reduced population size is thought to have strong consequences for evolutionary processes as it enhances the strength of genetic drift. In its interaction with selection, this is predicted to increase the genetic load, reduce inbreeding depression, and increase hybrid vigour, and in turn affect phenotypic evolution. Several of these predictions have been tested, but comprehensive studies controlling for confounding factors are scarce. Here we show that populations of Daphnia magna, which vary strongly in genetic diversity, also differ in genetic load, inbreeding depression, and hybrid vigor in a way that strongly supports theoretical predictions: Inbreeding depression is positively correlated with genetic diversity (a proxy for Ne), and genetic load and hybrid vigour are negatively correlated with genetic diversity. These patterns remain significant after accounting for potential confounding factors and indicate that, in small populations, a large proportion of the segregation load is converted into fixed load. Overall, the results suggest that the nature of genetic variation for fitness-related traits differs strongly between large and small populations. This has large consequences for evolutionary processes in natural populations, such as selection on dispersal, breeding systems, ageing, and local adaptation.
The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical datasets
<p class="CxSpFirst">The software program STRUCTURE is one of the most cited tools for determining population structure. To infer the optimal number of clusters from STRUCTURE output, the Δ<i>K</i> method is often applied. However, a recent study relying on simulated microsatellite data suggested that this method has a downward bias in its estimation of <i>K</i> and is sensitive to uneven sampling. If this finding holds for empirical datasets, conclusions about the scale of gene flow may have to be revised for a large number of studies. To determine the impact of method choice, we applied recently described estimators of <i>K</i> to re-estimate genetic structure in 41 empirical microsatellite datasets; 15 from a broad range of taxa and 26 focused on a diverse phylogenetic group, coral. We compared alternative estimates of <i>K</i> (Puechmaille statistics) with traditional (Δ<i>K</i> and posterior probability) estimates and found widespread disagreement of estimators across datasets. Thus, one estimator alone is insufficient for determining the optimal number of clusters regardless of study organism or evenness of sampling scheme. Subsequent analysis of molecular variance (AMOVA) between clustering solutions did not necessarily clarify which solution was best. To better infer population structure, we suggest a combination of visual inspection of STRUCTURE plots and calculation of the alternative estimators at various thresholds in addition to Δ<i>K</i>. Differences between estimators could reveal patterns with important biological implications, such as the potential for more population structure than previously estimated, as was the case for many studies reanalyzed here.</p>
Data from: Genetic load, inbreeding depression and hybrid vigor covary with population size: an empirical evaluation of theoretical predictions
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The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical datasets
Open the record for dataset details and reuse information.
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