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44 results for “Genetic simulation”
Data from: When can refuges mediate the genetic effects of fire regimes? A simulation study of the effects of topography and weather on neutral and adaptive genetic diversity in fire-prone landscapes
Understanding how landscape heterogeneity mediates the effects of fire on biodiversity is increasingly important under global changes in fire regimes. We used a simulation experiment to investigate how fire regimes interact with topography and weather to shape neutral and selection-driven genetic diversity under alternative dispersal scenarios, and to explore the conditions under which microrefuges can maintain genetic diversity of populations exposed to recurrent fire. Spatial heterogeneity in simulated fire frequency occurred in topographically complex landscapes, with fire refuges and fire-prone "hotspots" apparent. Interannual weather variability reduced the effect of topography on fire patterns, with refuges less apparent under high weather variability. Neutral genetic diversity was correlated with long-term fire frequency under spatially heterogeneous fire regimes, being higher in fire refuges than fire-prone areas, except under high dispersal or low fire severity (low mortality). This generated different spatial genetic structures in fire-prone and fire-refuge components of the landscape, despite similar dispersal. In contrast, genetic diversity was only associated with time since the most recent fire in flat landscapes without predictable refuges and hotspots. Genetic effects of selection driven by fire-related conditions depended on selection pressure, migration distance and spatial heterogeneity in fire regimes. Allele frequencies at a locus conferring higher fitness under successional environmental conditions followed a pattern of "temporal adaptation" to contemporary conditions under strong selection pressure and high migration. However, selected allele frequencies were correlated with spatial variation in long-term mean fire frequency (relating to environmental predictability) under weak dispersal, low selection pressure and strong spatial heterogeneity in fire regimes.
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>
Simulation code for: Effects of population size change on the genetics of adaptation following an abrupt change in environment
<p>Since the rediscovery of Mendelian genetics over a century ago, there has been much debate about the evolutionary importance of mutations with large phenotypic effects. While population genetic models predict that large-effect mutations will typically contribute to adaptation following an abrupt change in environment, the prediction applies to populations of stable size and overlooks effects of population size change on adaptation (e.g., population decline following habitat loss; growth during range expansion). We evaluate the phenotypic and fitness effects of mutations contributing to adaptation immediately following an abrupt environmental shift that alters both selection and population size dynamics. We show that large-effect mutations are likely to contribute to adaptation in populations declining to a new carrying capacity, somewhat smaller-effect mutations contribute to evolutionary rescue, and small-effect mutations predominate in growing populations. We also show that the relative contributions of positively selected and overdominant mutations to adaptation depend on interactions between the phenotypic effect size distribution for new mutations and the specific form of population size change during adaptation (i.e., growth, decline, or evolutionary rescue). Our results illustrate how population size dynamics can shape the genetic basis of adaptation, which should motivate empirical comparisons of populations adapting in different demographic contexts.</p>
Data from: Connectivity in grey reef sharks (Carcharhinus amblyrhynchos) determined using empirical and simulated genetic data
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Data from: Genetic relationships, structure and parentage simulation among the olive tree (Olea europaea L. subsp. europaea) cultivated in Southern Italy revealed by SSR markers
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Data from: When can refuges mediate the genetic effects of fire regimes? A simulation study of the effects of topography and weather on neutral and adaptive genetic diversity in fire-prone landscapes
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Simulation code for: Effects of population size change on the genetics of adaptation following an abrupt change in environment
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Data from: Re-imagining maize inbred potential: identifying breeding crosses using genetic variance of simulated progeny
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Data from: Understanding age-specific dispersal in fishes through hydrodynamic modelling, genetic simulations and microsatellite DNA analysis
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Data from: Simulating local adaptation to climate of forest trees with a Physio-Demo-Genetics model
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Stan code from: Simulation modeling reveals the evolutionary role of landscape shape and species dispersal on genetic variation within a metapopulation
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Data from: Looking into the black box: simulating the role of self-fertilization and mortality in the genetic structure of Macrocystis pyrifera
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The influence of a priori grouping on inference of genetic clusters: simulation study and literature review of the DAPC method
Inference of genetic clusters is a key aim of population genetics, sparking development of numerous analytical methods. Within these, there is a conceptual divide between finding de novo structure versus assessment of a priori groups. Recently developed, Discriminant Analysis of Principal Components (DAPC), combines discriminant analysis (DA) with principal component (PC) analysis. When applying DAPC, the groups used in the DA (specified a priori or described de novo) need to be carefully assessed. While DAPC has rapidly become a core technique, the sensitivity of the method to misspecification of groups and how it is being empirically applied, are unknown. To address this, we conducted a simulation study examining the influence of a priori versus de novo group designations, and a literature review of how DAPC is being applied. We found that with a priori groupings, distance between genetic clusters reflected underlying FST. However, when migration rates were high and groups were described de novo there was considerable inaccuracy, both in terms of the number of genetic clusters suggested and placement of individuals into those clusters. Nearly all (90.1%) of 224 studies surveyed used DAPC to find de novo clusters, and for the majority (62.5%) the stated goal matched the results. However, most studies (52.3%) omit key run parameters, preventing repeatability and transparency. Therefore, we present recommendations for standard reporting of parameters used in DAPC analyses. The influence of groupings in genetic clustering is not unique to DAPC, and researchers should consider their goal and which methods will be most appropriate.
Data from: QuLinePlus: extending plant breeding strategy and genetic model simulation to cross-pollinated populations – case studies in forage breeding
Plant breeders are supported by a range of tools that assist them to make decisions about the conduct or design of plant breeding programs. Simulations are a strategic tool that enable the breeder to integrate the multiple components of a breeding program into a number of proposed scenarios that are compared by a range of statistics measuring the efficiency of the proposed systems. A simulation study for the trait growth score compared two major strategies for breeding forage species, among half-sib family selection and among and within half-sib family selection. These scenarios highlighted new features of the QuLine program, now called QuLinePlus, incorporated to enable the software platform to be used to simulate breeding programs for cross pollinated species. Each strategy was compared across three levels of HS family mean heritability (0.1, 0.5 and 0.9), across three sizes of the initial parental population (10, 50, and 100), and across three genetic effects models (fully additive model, a mixture of additive, partial and over dominance model, and a mixture of partial dominance and over dominance model). Among and within half-sib selection performed better than among half-sib selection for all scenarios. The new tools introduced into QuLinePlus should serve to accurately compare among methods and provide direction on how to achieve specific goals in the improvement of plant breeding programs for cross breeding species.
Data from: Dendritic connectivity shapes spatial patterns of genetic diversity: a simulation-based study
Landscape features notoriously affect spatial patterns of biodiversity. For instance, in dendritic ecological networks (such as river basins), dendritic connectivity has been proposed to create unique spatial patterns of biodiversity. Here, we compared genetic datasets simulated under a lattice-like, a dendritic and a circular landscape to test the influence of dendritic connectivity on neutral genetic diversity. The circular landscape had a level of connectivity similar to that of the dendritic landscape, so as to isolate the influence of dendricity on genetic diversity. We found that genetic diversity and differentiation varied strikingly among the three landscapes. For instance, the dendritic landscape generated higher total number of alleles and higher global Fst than the lattice-like landscape, and these indices also varied between the dendritic and the circular landscape, suggesting an effect of dendricity. Furthermore, in the dendritic landscape, allelic richness was higher in highly connected demes (e.g. confluences in rivers) than in low connected demes (e.g. upstream and downstream populations), which was not the case in the circular landscape, hence confirming the major role of dendricity. This led to bell-shaped distributions of allelic richness along an upstream-downstream gradient. Conversely, genetic differentiation (Fst) was lower in highly than in low connected demes (which was not observed in circular landscape), and significant patterns of isolation-by-distance (IBD) were also observed in the dendritic landscape. We conclude that in dendritic networks, the combined influence of dendricity and connectivity generates unique spatial patterns of neutral genetic diversity, which has implications for population geneticists and conservationists.
Data from: Sex chromosome turnovers and genetic drift: a simulation study
The recent advances of new genomic technologies has enabled to identify and characterize sex chromosomes in an increasing number of non-model species, revealing that many plants and animals undergo frequent sex chromosome turnovers. What evolutionary forces drive these turnovers remains poorly understood, but it was recently proposed that drift might play a more important role than generally assumed. We analyzed the dynamics of different types of turnovers using individual-based simulations, and show that when mediated by genetic drift, turnovers are usually easier to achieve than substitutions at neutral markers, but that their dynamics and relative likelihoods vary with the type of the resident and emergent sex chromosome system (XY and/or ZW), and the dominance relationships among the sex-determining factors. Focusing on turnovers driven by epistatically dominant mutations, we find that drift-mediated turnovers that preserve the heterogamety pattern are 2-4x more likely than those along which the heterogametic sex changes. This ratio nevertheless decreases along with effective population size, and can even reverse in case of extreme polygyny. This can be attributed to a "drift-induced" selective force, known to influence transitions between male and female heterogamety, but which according to our study, does not affect turnovers that preserve the heterogametic sex.
The influence of a priori grouping on inference of genetic clusters: simulation study and literature review of the DAPC method
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Data from: Sex chromosome turnovers and genetic drift: a simulation study
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Data from: QuLinePlus: extending plant breeding strategy and genetic model simulation to cross-pollinated populations – case studies in forage breeding
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Data from: Dendritic connectivity shapes spatial patterns of genetic diversity: a simulation-based study
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.