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20 results for “population genetic dataset”
Example Dataset for npstat: Population genetics from Pooled NGS data NPStat v1: User guide
<p>Example Dataset for npstat to test the program and the different options.</p> <p>The example dataset contains a pileup file with sequences of of the 2L chromosome from fifteen pooled inbreed individuals of <em>Drosophila melanogaster </em>(<span>doi: 10.1038/nature10811</span>). The dataset also contains the sequence reference of the 2L chromosome in fasta format, an outgroup sequence in fasta format of <em>D. yakuba</em> (SRR26246471), a GFF3 annotation file and a file with a brief list of selected SNPs to be analyzed.</p>
Raw Genotyping data from: Variation in recombination rate and its genetic determinism in sheep populations from combining multiple genomewide datasets
<p>Data supporting :</p> <p><strong>Variation in recombination rate and its genetic determinism in sheep populations from combining multiple genomewide datasets</strong></p> <p>Morgane Petit, Jean-Michel Astruc, Julien Sarry, Laurence Drouilhet, Stephane Fabre, Carole Moreno, Bertrand Servin</p> <p>http://doi.org/10.1534/genetics.117.300123</p> <p><strong>Abstract</strong></p> <p>Recombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and datasets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified about 50,000 crossover hotspots on the genome and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting inter-individual variation in recombination rate in Lacaune, including the <em>RNF212</em> and<em> HEI10</em> genes and possibly 2 other loci of smaller effects including the <em>KCNJ15</em> and <em>FSHR</em> genes. Finally, we compared our results to those obtained previously in a distantly related population of domestic sheep, the Soay. This comparison revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome and that the two datasets can be combined to create more precise male meiotic recombination maps in sheep. Despite their similar recombination maps, we show that Soay and Lacaune males exhibit different heritabilities and QTL effects for inter-individual variation in genome-wide recombination rates.</p> <p> </p> <p>Data files are provided in Plink format ( https://www.cog-genomics.org/plink2 ).</p> <p> </p>
Dataset and R code: Genetic diversity of lion populations in Kenya: evaluating past management practices and recommendations for future conservation actions by Chege M et.al
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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>
Dataset for "Genetic diversity and population structure of a wide Pisum spp. core collection."
<p>Silico-DArT and SNP datasets of the IAS pea core collection.</p> <p>Each file contain key information of the molecular markers used to establish the population structure and genetic diversity of the IAs pea core collection.</p>
Dataset 2 for Large‐ and small‐scale geographic structures affecting genetic patterns across populations of an Alpine butterfly
<p>Understanding factors influencing patterns of genetic diversity and the population genetic structure of species is of particular importance in the current era of global climate change and habitat loss. These factors include the evolutionary history of a species as well as heterogeneity in the environment it occupies, which in turn can change across time. Most studies investigating spatio-temporal genetic patterns have focused on patterns across wide geographical areas rather than local variation, but the latter can nevertheless be important particularly in topographically complex areas. Here we consider these issues in the Sooty Copper butterfly (<i>Lycaena tityrus</i>) from the European Alps, using genome-wide SNPs identified through RADseq. We found strong genetic differentiation within the Alps with four genetic clusters, indicating western, central, and eastern refuges, and a strong reduction of genetic diversity from west to east. This reduction in diversity may suggest that the southwestern refuge was the largest one in comparison to other refuges. Also, the high genetic diversity in the West may result from (1) admixture of different western refuges, (2) more recent demographic changes, or (3) introgression of lowland <i>L. tityrus</i> populations. At small spatial scales, populations were structured by several landscape features and especially by high mountain ridges and large river valleys. We detected 36 outlier loci likely under altitudinal selection, including several loci related to membranes and cellular processes. We suggest that efforts to preserve alpine <i>L. tityrus </i>should focus on the genetically diverse populations in the western Alps, and that the dolomite populations should be treated as genetically distinct management units, since they appear to be currently more threatened than others. This study demonstrates the usefulness of SNP-based approaches for understanding patterns of genetic diversity, gene flow and selection in a region that is expected to be particularly vulnerable to climate change.</p>
Dataset for: Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development
<p class="MsoNormal"><span>With new motivation to increase the proportion of energy demands met by zero-carbon sources, there is a greater focus on efforts to assess and mitigate the impacts of renewable energy development on sensitive ecosystems and wildlife, of which birds are of particular interest. One challenge for researchers, due in part to a lack of appropriate tools, has been estimating the effects from such development on individual breeding populations of migratory birds. To help address this, we utilize a newly developed, high-resolution genetic tagging method to rapidly identify the breeding population of origin of carcasses recovered from renewable energy facilities and combine them with maps of genetic variation across geographic space (called 'genoscapes') for five species of migratory birds known to be exposed to energy development, to assess the extent of population-level effects on migratory birds. We demonstrate that most avian remains collected were from the largest populations of a given species. In contrast, those remains from smaller, declining populations made up a smaller percentage of the total number of birds assayed. Results suggest that application of this genetic tagging method can successfully define population-level exposure to renewable energy development and may be a powerful tool to inform future siting and mitigation activities associated with renewable energy programs.</span></p>
Dataset 1 for Large- and small-scale geographic structures affect genetic patterns across populations of an Alpine butterfly
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Dataset 2 for Large‐ and small‐scale geographic structures affecting genetic patterns across populations of an Alpine butterfly
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Dataset for: Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development
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Dataset for METAPOPGEN 2.0: a multi-locus genetic simulator to model populations of large size
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Datasets for: Genome wide analysis reveals genetic divergence between Goldsinny wrasse populations
<p><b>Background</b>: Marine fish populations are often characterized by high levels of gene flow and correspondingly low genetic divergence. This presents a challenge to define management units. Goldsinny wrasse (<i>Ctenolabrus rupestris</i>) is a heavily exploited species due to its importance as a cleaner-fish in commercial salmonid aquaculture. However, at the present, the population genetic structure of this species is still largely unresolved. Here, full-genome sequencing was used to produce the first genomic reference for this species, to study population-genomic divergence among four geographically distinct populations, and, to identify informative SNP markers for future studies.</p> <p><b>Results:</b> After construction of a <i>de novo </i>assembly, the genome was estimated to be highly polymorphic and of ~600Mbp in size. 33 235 genome wide SNPs were thereafter selected to assess genomic diversity and differentiation among four populations collected from Scandinavia, Scotland, and Spain. Global <i>F<sub>ST</sub></i> among these populations was 0.015–0.092. Approximately 4% of the investigated loci were identified as putative global outliers, and ~1% within Scandinavia. SNPs showing large divergence (<i>F<sub>ST</sub></i>>0.15) were picked as candidate diagnostic markers for population assignment. 173 of the most diagnostic SNPs between the two Scandinavian populations were validated by genotyping 47 individuals from each end of the species' Scandinavian distribution range. 69 of these SNPs were significantly (<i>p</i><0.05) differentiated (mean <i>F<sub>ST_173_loci</sub></i><i>=</i>0.065<i>, F<sub>ST_69_</sub></i><i><sub>loci</sub></i><i>=</i>0.140). Using these validated SNPs, individuals were assigned with high probability (≥ 94%) to their populations of origin.</p> <p><b>Conclusions:</b> Goldsinny wrasse displays a highly polymorphic genome, and substantial population genomic structure. Diversifying selection likely affects population structuring globally and within Scandinavia. The diagnostic loci identified now provide a promising and cost-efficient tool to investigate goldsinny wrasse populations further.</p>
High genetic diversity but no geographic structure of Aedes albopictus populations in Reunion Island _ Dataset
<p>Microsatellite dataset of <em>Aedes albopictus</em> individuals sampled in Reunion Island. </p>
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>
Sheepnose mussel (P. cyphyus) microsatellite dataset for population genetic analysis
<p class="Body">North American freshwater mussel species have experienced substantial range fragmentation and population reductions. These impacts have the potential to reduce genetic connectivity among populations and increase the risk of losing genetic diversity. Thirteen microsatellite loci and an 883 bp fragment of the mitochondrial ND1 gene were used to assess genetic diversity, population structure, contemporary migration rates, and population size changes across the range of the Sheepnose mussel (<em>Plethobasus cyphyus</em>). Population structure analyses reveal five populations, three in the Upper Mississippi River Basin and two in the Ohio River Basin. Sampling locations exhibit a high degree of genetic diversity and contemporary migration estimates indicate that migration between populations within river basins is occurring, although at low rates. but no migration is occurring between the Ohio and Mississippi river basins. No evidence of bottlenecks was detected, and almost all locations exhibited the signature of population expansion. Our results indicate that although anthropogenic activity has altered the landscape across the range of the Sheepnose, these activities have yet to be reflected in losses of genetic diversity. Efforts to conserve Sheepnose populations should focus on maintaining existing habitats and fostering genetic connectivity between extant demes to conserve remaining genetic diversity for future viable Sheepnose populations.</p>
Sheepnose mussel (P. cyphyus) microsatellite dataset for population genetic analysis
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Datasets for: Genome wide analysis reveals genetic divergence between Goldsinny wrasse populations
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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
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Gene expression profiles of oil palm leaves from different oil yields and genetic population: Transcriptomic dataset
GEO Series GSE222528. Elaeis guineensis. 9 samples. Type: Expression profiling by high throughput sequencing.
The Influence of Genetics and Environment on different populations of the Invasive Species Carpobrotus sp.pl (dataset)
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.