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ShareScore release 0.7.1
Dataset results
13 results for “Low-coverage whole genomes”
Genotypes of Aedes aegypti mosquitoes derived from SNP chip and low-coverage whole genome sequencing for platform cross-validation
<p>The mosquito <em>Aedes aegypti </em>is the primary vector of many human arboviruses such as dengue, yellow fever, chikungunya, and Zika, which affect millions of people world-wide. Population genetics studies on this mosquito have been important in understanding its invasion pathways and success as a vector of human disease. The Axiom aegypti1 SNP chip was developed from a sample of geographically diverse <em>Ae. aegypti </em>populations to facilitate genomic studies on this species. Here we evaluate the utility of the Axiom aegypti1 SNP chip for population genetics and compare it with a low-depth shot-gun sequencing approach using mosquitoes from the species' native (Africa) and invasive range (outside Africa). These analyses indicate that the results from the SNP chip are highly reproducible and have a higher sensitivity to capture alternative alleles than a low-coverage whole-genome sequencing approach. Although the SNP chip suffers from ascertainment bias, results from population structure, ancestry, demographic, and phylogenetic analyses using the SNP chip were congruent with those derived from low coverage whole genome sequencing, and consistent with previous reports on Africa and outside Africa populations using microsatellites. More importantly, we identified a subset of SNPs that can be reliably used to generate merged databases, opening the door to combined analyses. We conclude that the Axiom aegypti1 SNP chip is a convenient, more accurate, low-cost alternative to low-depth whole genome sequencing for population genetic studies of <em>Ae. aegypti</em> that do not rely on full allelic frequency spectra. Whole genome sequencing and SNP chip data can be easily merged, extending the usefulness of both approaches. </p>
Low-coverage whole genome sequencing for highly accurate population assignment: Mapping migratory connectivity in the American Redstart (Setophaga ruticilla)
<p>Understanding the geographic linkages among populations across the annual cycle is an essential component for understanding the ecology and evolution of migratory species and for facilitating their effective conservation. While genetic markers have been widely applied to describe migratory connections, the rapid development of new sequencing methods, such as low-coverage whole genome sequencing (lcWGS), provides new opportunities for improved estimates of migratory connectivity. Here, we use lcWGS to identify fine-scale population structure in a widespread songbird, the American Redstart (<em>Setophaga</em> <em>ruticilla</em>), and accurately assign individuals to genetically distinct breeding populations. Assignment of individuals from the nonbreeding range reveals population-specific patterns of varying migratory connectivity. By combining migratory connectivity results with demographic analysis of population abundance and trends, we consider full annual cycle conservation strategies for preserving numbers of individuals and genetic diversity. Notably, we highlight the importance of the Northern Temperate-Greater Antilles migratory population as containing the largest proportion of individuals in the species. Finally, we highlight valuable considerations for other population assignment studies aimed at using lcWGS. Our results have broad implications for improving our understanding of the ecology and evolution of migratory species through conservation genomics approaches.</p>
Low-coverage whole genome sequencing for highly accurate population assignment: Mapping migratory connectivity in the American Redstart (Setophaga ruticilla)
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Genotypes of Aedes aegypti mosquitoes derived from SNP chip and low-coverage whole genome sequencing for platform cross-validation
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A comparison of phylogenomic inference pipelines for low-coverage whole-genome sequencing in Formica ants
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Genotype likelihoods for low-coverage whole-genome sequencing data of yellow warblers
<p>The following datasets include the required input files used to empirically test population assignment in WGSassign on Yellow Warbler data. The file "yewa.known.ind105.ds_2x.beagle.gz" includes the filtered variants of 105 Yellow Warbler individuals output as genotype likelihoods and stored in a Beagle-formatted file. The ID file, "yewa.known.ind105.reference.IDs.txt", is a tab-delimited file with 2 columns, the first being the sample ID, and the second being the known reference population. The sample order in the ID file should match that of the input beagle file. To measure the assignment accuracy of WGSassign, we used leave-one-out cross validation using the input beagle file and our ID file.</p>
Low-coverage whole-genome sequencing reveals molecular markers for spawning season and sex identification in Gulf of Maine Atlantic cod (Gadus morhua, Linnaeus 1758)
<p class="CxSpFirst">Atlantic cod (<i>Gadus morhua</i>,<i> </i>Linnaeus 1758) in the western Gulf of Maine are managed as a single stock despite several lines of evidence supporting two spawning groups (spring and winter) that overlap spatially, while exhibiting seasonal spawning isolation. Low-coverage whole genome sequencing was used to evaluate the genomic population structure of Atlantic cod spawning groups in the western Gulf of Maine and Georges Bank using 222 individuals collected over multiple years. Results indicated low total genomic differentiation, while also showing strong differentiation between spring and winter spawning groups at specific regions of the genome. Guided regularized random forest and ranked <i>F</i><sub>ST</sub> methods were used to select panels of single nucleotide polymorphisms (SNPs) that could reliably distinguish spring and winter-spawning Atlantic cod (88.5% assignment rate), as well as males and females (95.0% assignment rate) collected in the western Gulf of Maine. These SNP panels represent a valuable tool for fisheries research and management of Atlantic cod in the western Gulf of Maine that will aid investigations of stock production and support accuracy of future assessments.</p>
Genotype likelihoods for low-coverage whole-genome sequencing data of yellow warblers
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Low-coverage whole-genome sequencing reveals molecular markers for spawning season and sex identification in Gulf of Maine Atlantic cod (Gadus morhua, Linnaeus 1758)
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Data from: Low-coverage, whole-genome sequencing of Artocarpus camansi (Moraceae) for phylogenetic marker development and gene discovery
Premise of the study: We used moderately low-coverage (17×) whole-genome sequencing of Artocarpus camansi (Moraceae) to develop genomic resources for Artocarpus and Moraceae. Methods and Results: A de novo assembly of Illumina short reads (251,378,536 pairs, 2 × 100 bp) accounted for 93% of the predicted genome size. Predicted coding regions were used in a three-way orthology search with published genomes of Morus notabilis and Cannabis sativa. Phylogenetic markers for Moraceae were developed from 333 inferred single-copy exons. Ninety-eight putative MADS-box genes were identified. Analysis of all predicted coding regions resulted in preliminary annotation of 49,089 genes. An analysis of synonymous substitutions for pairs of orthologs (Ks analysis) in M. notabilis and A. camansi strongly suggested a lineage-specific whole-genome duplication in Artocarpus. Conclusions: This study substantially increases the genomic resources available for Artocarpus and Moraceae and demonstrates the value of low-coverage de novo assemblies for nonmodel organisms with moderately large genomes.
Data from: Low-coverage, whole-genome sequencing of Artocarpus camansi (Moraceae) for phylogenetic marker development and gene discovery
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Chromosomal microarray data for validation of copy-number variants detection from a low-coverage whole-genome sequencing approach in clinical samples
GEO Series GSE73191. Homo sapiens. 72 samples. Type: Genome variation profiling by array; Genome variation profiling by SNP array; SNP genotyping by SNP array.
Evaluation of copy number variation detection between high-resolution array CGH and low-coverage short-insert and mate-pair whole-genome sequencing
GEO Series GSE105092. Homo sapiens. 2 samples. Type: Genome variation profiling by array.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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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.