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44 results for “Genetic simulation”
Simulated genetic data in a hierarchical metapopulation structure
<p>The data are linked to a research article entitled: “<em>Interactions between microenvironment, selection and genetic architecture drive multiscale adaptation in a simulation experiment” </em>in<em> Journal of Evolutionary Biology</em> (see References).</p> <p>In this research on multiscale adaptation, we simulated a hierarchical metapopulation structure with four populations, two environments per population and three patches per environment, in a two-step procedure:</p> <ul> <li>an initialization step without selection, with eight combinations of mutation type, selfing rate and QTL number parameters (2 modes each); out of 200,000 simulated generations in each case, we chose one with appropriate characteristics as a starting point for the next step;</li> <li>a selection step with all possible combinations of the following parameters: environmental pattern (4 modes), environmental range (5 modes), selection intensity (4 modes), fecundity (3 modes).</li> </ul> <p>This resulted in 240 scenarios for each initialized metapopulation, i.e. 1,920 scenarios in total. Each scenario was replicated 10 times, i.e. 19,200 simulation runs.</p> <p>The archive includes all data needed to reproduce the simulations and analyses, or to re-use the simulated metapopulations for other analyses. It has the following structure (further detailed below):</p> <ol> <li><strong>NemoScripts directory </strong>contains the <em>Nemo </em>input files used to perform simulations for the initialization step and the selection step;</li> <li><strong>RScripts directory </strong>contains the <em>R</em> scripts to read the <em>Nemo </em>output files, compute synthetic variables(*), and produce the figures as they appear in the publication and supplementary material (*: long computations, therefore we also directly provide those synthetic variables in the Data directory);</li> <li><strong>Data directory </strong>contains the <em>Nemo </em>output files, the synthetic variables, and other data needed to reproduce the figures; this directory can be used as a working directory for the <em>R</em> scripts (recommended).</li> </ol> <p>Running the following command in a terminal <strong><em>tar –xzvf Archive_PC_SOM_IS_FL.tar</em></strong> will create a directory named <strong><em>Archive_PC_SOM_IS_FL</em></strong>, which detailed content is described in the <strong><em>README.pdf</em></strong> file.<br> Warning: the extracted archive is large (460Go, >40,000 files) and extraction may take some time.</p>
A Linked Application of Discrete Differential Evolution Algorithm Coupled with Simulation- Optimization Model and Comparative Analysis by Genetic Algorithm for Discrete Groundwater Management Problems
<p>Complete dataset of publication name as "The complete publication dataset is "A Discrete Differential Evolution- Linear Programming Algorithm for Groundwater Management Problems." You can find all the written codes in the zip file.</p>
Data and codes from "Daniel et al. What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA"
<p><span>Data and codes used for </span><span>“Daniel et al. What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA”</span></p>
Microsat Data for 'Simulated Disperser Analysis: determining the number of loci required to genetically identify dispersers'
<p>Microsattelite data from 94 samples (<em>Stunus vulgaris</em>) from 3 populations and including 29 loci. Used in the paper 'Simulated Disperser Analysis: determining the number of loci required to genetically identify dispersers'. </p>
Code and initial metapopulation data for model construction and simulation analyses for: Genetic rescue from protected areas is modulated by migration, hunting rate and timing of harvest
<p>Migrants from protected areas may buffer the risk of harvest-induced evolutionary changes in exploited populations that face strong selective harvest pressures in both terrestrial and marine ecosystems. Understanding the mechanisms favouring genetic rescue through migration could help ensure sustainable harvest outside protected areas and conserve genetic diversity inside those areas. We developed a stochastic individual-based metapopulation model to evaluate the potential for migration from protected areas to mitigate the evolutionary consequences of selective harvest. We parameterized the model with detailed data from individual monitoring of two populations of bighorn sheep subjected to trophy hunting. We tracked horn length through time in a metapopulation including large protected and trophy-hunted populations connected through male breeding migrations. We quantified and compared declines in horn length and rescue potential under various combinations of migration rate, hunting rate in hunted areas and temporal overlap in timing of harvest and migrations, which affects the migrants' survival and chances to breed within exploited areas. Our simulations suggest that the effects of size-selective harvest on male horn length in hunted populations can be dampened or avoided if harvest pressure is low, migration rate is substantial, and migrants have a low risk of being shot. Intense size-selective harvest impacts the phenotypic and genetic diversity in horn length, and population structure through changes in proportions of large-horned males, sex ratio and age structure. When hunting pressure is high and overlaps with male migrations, effects of selective removal also emerge in the protected population, so that instead of a genetic rescue of hunted populations, our model predicts undesirable effects inside protected areas. Our results stress the importance of a metapopulational approach to management, to promote genetic rescue from protected areas and limit ecological and evolutionary impacts of harvest on both harvested and protected populations.</p>
Data and codes from "How does dispersal shape the genetic structure of animal populations in European cities? A simulation approach"
<p>Codes and data used for "Savary et al. How does dispersal shape the genetic structure of animal populations in European cities? A simulation approach".</p> <p> </p>
Simulating genetic mixing in strongly structured populations of the threatened southern brown bandicoot (Isoodon obesulus)
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Code and initial metapopulation data for model construction and simulation analyses for: Genetic rescue from protected areas is modulated by migration, hunting rate and timing of harvest
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Dataset for METAPOPGEN 2.0: a multi-locus genetic simulator to model populations of large size
<p>Multi-locus genetic processes in subdivided populations can be complex and difficult to interpret using theoretical population genetics models. Genetic simulators offer a valid alternative to study multi-locus genetic processes in arbitrarily complex scenarios. However, the use of forward-in-time simulators in realistic scenarios involving high numbers of individuals distributed in multiple local populations is limited by computation time and memory requirements. These limitations increase with the number of simulated individuals. We developed a genetic simulator, <span>MetaPopGen</span> 2.0, to model multi-locus population genetic processes in subdivided populations of arbitrarily large size. It allows for spatial and temporal variation in demographic parameters, age structure, adult and propagule dispersal, variable mutation rates and selection on survival and fecundity. We developed <span>MetaPopGen</span> 2.0 in the R environment to facilitate its use by non-modeler ecologists and evolutionary biologists. We illustrate the capabilities of <span>MetaPopGen</span> 2.0 for studying adaptation to water salinity in the striped red mullet <i>Mullus surmuletus</i>.</p>
Assessment of connectivity patterns of the marbled crab Pachygrapsus marmoratus in the Adriatic and Ionian seas through combination of genetic data and Lagrangian simulations
<p>Seascape connectivity studies, informing the level of exchange of individuals between populations, can provide extremely valuable data for marine population biology and conservation strategy definition. Here we used a multidisciplinary approach to investigate the connectivity of the marbled crab (Pachygrapsus marmoratus), a high dispersal species, in the Adriatic and Ionian basins. A combination of genetic analyses (based on 15 microsatellites screened in 314 specimens), Lagrangian simulations (obtained with a biophysical model of larval dispersal) and individual-based forward-time simulations (incorporating species-specific fecundity and a wide range of population sizes) disclosed the realized and potential connectivity among eight different locations, including existing or planned Marine Protected Areas (MPAs). Overall, data indicated a general genetic homogeneity, after removing a single outlier locus potentially under directional selection. Lagrangian simulations showed that direct connections potentially exist between several sites, but most sites did not exchange larvae. Forward-time simulations indicated that a few generations of drift would produce detectable genetic differentiation in case of complete isolation as well as when considering the direct connections predicted by Lagrangian simulations.Overall, our results suggest that the observed genetic homogeneity reflects a high level of realized connectivity among sites, which might result from a regional metapopulation dynamics, rather than from direct exchange among populations of the existing or planned MPAs. Thus, in the Adriatic and Ionian basins, connectivity might be critically dependent on unsampled, unprotected, populations, even in species with very high dispersal potential like the marbled crab. Our study pointed out the pitfalls of using wide-dispersing species with broad habitat availability when assessing genetic connectivity among MPAs or areas deserving protection and prompts for the careful consideration of appropriate dispersing features, habitat suitability, reproductive timing and duration in the selection of informative species.</p>
Simulated data for: The evolution of mating preferences for genetic attractiveness and quality in the presence of sensory bias
<p>This repository contains simulated datasets relating to the publication: </p> <p>Henshaw JM, Fromhage L, Jones AG (2022) The evolution of mating preferences for genetic attractiveness and quality in the presence of sensory bias. Proc. Natl. Acad. Sci. USA (doi:10.1073/pnas.2206262119)</p> <p>In this paper, we simulate the evolution of female preferences for multiple male ornament types (e.g., 'Fisherian', 'handicap' and 'indicator' ornaments) that differ in their associations with genes for attractiveness and for general 'quality' (operationalized as the ability to acquire resources). We allowed for ornaments to differ in their saliency to females. We also analyze the causal mechanisms generating sexual selection (e.g., 'good genes' and 'sexy sons') using causal inference. </p> <p>Datasets are organised into ZIP files named after the corresponding figure in the publication. For further information see the publication and the file README.txt in this repository.</p>
SimBit: A high performance, flexible and easy-to-use population genetic simulator
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Assessment of connectivity patterns of the marbled crab Pachygrapsus marmoratus in the Adriatic and Ionian seas through combination of genetic data and Lagrangian simulations
Open the record for dataset details and reuse information.
Dataset for METAPOPGEN 2.0: a multi-locus genetic simulator to model populations of large size
Open the record for dataset details and reuse information.
Simulated data for: The evolution of mating preferences for genetic attractiveness and quality in the presence of sensory bias
Open the record for dataset details and reuse information.
Stan code from: Simulation modeling reveals the evolutionary role of landscape shape and species dispersal on genetic variation within a metapopulation
Different shapes of landscape boundaries can affect the habitat networks within them and consequently the spatial genetic-patterns of a metapopulation. In this study, we used a mechanistic framework to evaluate the effects of landscape shape, through watershed elongation, on genetic divergence among populations at the metapopulation scale. Empirical genetic data from four, sympatric stream-macroinvertebrates having aerial adults were collected from streams in Japan to determine the roles of species-specific dispersal strategies on metapopulation genetics. Simulation results indicated that watershed elongation allows the formation of river networks with fewer branches and larger topographic constraints. This results in decreased interpopulation connectivity but a lower level of spatial isolation of distal populations (e.g., those found in headwaters) occurring in the landscapes examined. Distal populations had higher genetic divergence when their downstream-biased dispersal (relative to upstream- and/or overland-biased dispersal) was high. This underscores the importance of distal populations influencing genetic divergence at the metapopulation scale for species having downstream-biased dispersal. In turn, lower genetic divergence was observed under watershed elongation when the genetic isolation of distal populations was decreased in such species. This strong association between landscape shape and evolutionary processes highlights the importance of natural, spatial architecture in assessing the effectiveness of conservation and management strategies.
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
In this work, we assess both the morphological and genetic diversity of 68 important olive cultivars from three Southern Italian regions: Calabria, Campania and Sicily. Twenty-five phenotypic traits were evaluated and 12 simple sequence repeat (SSR) markers were analysed. All SSR primers were polymorphic and reliable. The total number of alleles per locus varied from 5 to 19 with an average number of 13.1 and a mean polymorphic information content (PIC) of 0.81. These results suggested high genetic diversity within these three olive germplasm collections. Morphological traits also showed significant variability amongst cultivars. Two cases of identity were found and ten statistically significant cases of putative parent/sibling were discovered by performing a SSR-based parentage simulation analysis with CERVUS. The Mantel test indicated low but significant correlations between the morphological data and SSR allelic frequency, origin and SSR allelic frequency, and origin and morphology. Structure software allowed inference of relationships between the three olive germplasm collections and allowed us to obtain the most consistent grouping and to identify putative admixed or exchanged cultivars. Cluster and multivariate analysis, based on morphological traits, revealed geographic grouping in agreement with UPGMA dendrogram and structure analysis using SSRs. Sicilian cultivars showed a more homogenous genetic makeup, probably due to geographical isolation, whilst Calabrian and Campanian cultivars seemed to have a less distinct genetic structure, with a greater degree of intermixing. A correlation between the presence of certain SSR alleles and fruit size was also found.
Data from: Understanding age-specific dispersal in fishes through hydrodynamic modelling, genetic simulations and microsatellite DNA analysis
Many marine species have vastly different capacities for dispersal during larval, juvenile and adult life stages, and this has the potential to complicate the identification of population boundaries and the implementation of effective management strategies such as marine protected areas. Genetic studies of population structure and dispersal rarely disentangle these differences and usually provide only lifetime-averaged information that can be considered by managers. We address this limitation by combining age-specific autocorrelation analysis of microsatellite genotypes, hydrodynamic modelling and genetic simulations to reveal changes in the extent of dispersal during the lifetime of a marine fish. We focus on an exploited coral reef species, Lethrinus nebulosus, which has a circum-tropical distribution and is a key component of a multispecies fishery in northwestern Australia. Conventional population genetic analyses revealed extensive gene flow in this species over vast distances (up to 1500 km). Yet, when realistic adult dispersal behaviours were modelled, they could not account for these observations, implying adult dispersal does not dominate gene flow. Instead, hydrodynamic modelling showed that larval L. nebulosus are likely to be transported hundreds of kilometres, easily accounting for the observed gene flow. Despite the vast scale of larval transport, juvenile L. nebulosus exhibited fine-scale genetic autocorrelation, which declined with age. This implies both larval cohesion and extremely limited juvenile dispersal prior to maturity. The multidisciplinary approach adopted in this study provides a uniquely comprehensive insight into spatial processes in this marine fish.
Data from: Looking into the black box: simulating the role of self-fertilization and mortality in the genetic structure of Macrocystis pyrifera
Patterns of spatial genetic structure (SGS), typically estimated by genotyping adults, integrate migration over multiple generations and measure the effective gene flow of populations. SGS results can be compared with direct ecological studies of dispersal or mating system to gain additional insights. When mismatches occur, simulations can be used to illuminate the causes of these mismatches. Here we report a SGS and simulation-based study of self-fertilization in Macrocystis pyrifera, the giant kelp. We found that SGS is weaker than expected in M. pyrifera, and used computer simulations to identify selfing and early mortality rates for which the individual heterozygosity distribution fits that of the observed data. Only one (of three) population showed both elevated kinship in the smallest distance class and a significant negative slope between kinship and geographic distance. All simulations had poor fit to the observed data unless mortality due to inbreeding depression was imposed. This mortality could only be imposed for selfing, as these were the only simulations to show an excess of homozygous individuals relative to the observed data. Thus, the expected data consistently achieved non-significant differences from the observed data only under models of selfing with mortality, with best fits between 32-42% selfing. Inbreeding depression ranged from 0.70-0.73. The results suggest that density-dependent mortality of early life stages is a significant force in structuring Macrocystis populations, with few highly-homozygous individuals surviving. The success of these results should help to validate simulation approaches even in data-poor systems, as a means to estimate otherwise difficult-to-measure life-cycle parameters.
Data from: Connectivity in grey reef sharks (Carcharhinus amblyrhynchos) determined using empirical and simulated genetic data
Grey reef sharks (Carcharhinus amblyrhynchos) can be one of the numerically dominant high order predators on pristine coral reefs, yet their numbers have declined even in the highly regulated Australian Great Barrier Reef (GBR) Marine Park. Knowledge of both large scale and fine scale genetic connectivity of grey reef sharks is essential for their effective management, but no genetic data are yet available. We investigated grey reef shark genetic structure in the GBR across a 1200 km latitudinal gradient, comparing empirical data with models simulating different levels of migration. The empirical data did not reveal any genetic structuring along the entire latitudinal gradient sampled, suggesting regular widespread dispersal and gene flow of the species throughout most of the GBR. Our simulated datasets indicate that even with substantial migrations (up to 25% of individuals migrating between neighboring reefs) both large scale genetic structure and genotypic spatial autocorrelation at the reef scale were maintained. We suggest that present migration rates therefore exceed this level. These findings have important implications regarding the effectiveness of networks of spatially discontinuous Marine Protected Areas to protect reef sharks.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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