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Dataset results
31 results for “low-coverage”
CONGA: Copy number variation genotyping in ancient genomes and low-coverage sequencing data
<p>To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by (i) most published genomes being <1x coverage, (ii) ancient DNA fragments being typically <80 bps. These characteristics preclude state-of-the-art CNV detection software to be effectively applied to ancient genomes. Here we present CONGA, an algorithm tailored for genotyping deletion and duplication events in genomes with low depths of coverage. Simulations and down-sampling experiments show that CONGA can genotype deletions >1 kbps with F-scores >0.75 at >=1x, and distinguish between heterozygous and homozygous states. Using CONGA, we analyse deletion events at 10,018 loci in 56 ancient human genomes spanning the last 50,000 years, with coverages 0.4x-26x. We show that inter-individual genetic diversity measured using deletions and SNPs are highly correlated, as in modern-day genomes, confirming that deletion frequencies broadly reflect demographic history. We also identify signatures of strong purifying selection on deletions in ancient-genomes, such as an excess of singletons compared to those in SNPs. CONGA paves the way for systematic studies of drift, mutation load, and adaptation in ancient and modern-day gene pools through the lens of CNVs.</p>
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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Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics
<p>Amplicon metabarcoding is an established technique to analyse the taxonomic composition of communities of organisms using high-throughput DNA sequencing, but there are doubts about its ability to quantify the relative proportions of the species, as opposed to the species list. Here, we bypass the enrichment step and avoid the PCR-bias, by directly sequencing the extracted DNA using shotgun metagenomics. This approach is common practice in prokaryotes, but not in eukaryotes, because of the low number of sequenced genomes of eukaryotic species. We tested the metagenomics approach using insect species whose genome is already sequenced and assembled to an advanced degree. We shotgun-sequenced, at low-coverage DNA, 18 species of insects in 22 single-species and 6 mixed-species libraries and mapped the reads against 110 reference genomes of insects. We used the single-species libraries to calibrate the process of assignation of reads to species and the libraries created from species mixtures to evaluate the ability of the method to quantify the relative species abundance. Our results showed that the shotgun metagenomic method is easily able to set apart closely-related insect species, like four species of <i>Drosophila</i> included in the artificial libraries. However, to avoid the counting of rare misclassified reads in samples, it was necessary to use a rather stringent detection limit of 0.001, so species with a lower relative abundance are ignored. We also identified that approximately half the raw reads were informative for taxonomic purposes. Finally, using the mixed-species libraries, we showed that it was feasible to quantify with confidence the relative abundance of individual species in the mixtures.</p>
Data from: Development of genomic tools in a widespread tropical tree, Symphonia globulifera L.f.: a new low-coverage draft genome, SNP and SSR markers
Population genetic studies in tropical plants are often challenging because of limited information on taxonomy, phylogenetic relationships and distribution ranges, scarce genomic information and logistic challenges in sampling. We describe a strategy to develop robust and widely applicable genetic markers based on a modest development of genomic resources in the ancient tropical tree species Symphonia globulifera L.f. (Clusiaceae), a keystone species in African and Neotropical rainforests. We provide the first low-coverage (11X) fragmented draft genome sequenced on an individual from Cameroon, covering 1.027 Gbp or 67.5% of the estimated genome size. Annotation of 565 scaffolds (7.57 Mbp) resulted in the prediction of 1046 putative genes (231 of them containing a complete open reading frame) and 1523 exact simple sequence repeats (SSRs, microsatellites). Aligning a published transcriptome of a French Guiana population against this draft genome produced 923 high-quality single nucleotide polymorphisms. We also preselected genic SSRs in silico that were conserved and polymorphic across a wide geographical range, thus reducing marker development tests on rare DNA samples. Of 23 SSRs tested, 19 amplified and 18 were successfully genotyped in four S. globulifera populations from South America (Brazil and French Guiana) and Africa (Cameroon and São Tomé island, FST = 0.34). Most loci showed only population-specific deviations from Hardy–Weinberg proportions, pointing to local population effects (e.g. null alleles). The described genomic resources are valuable for evolutionary studies in Symphonia and for comparative studies in plants. The methods are especially interesting for widespread tropical or endangered taxa with limited DNA availability.
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>
Data from: Development of genomic tools in a widespread tropical tree, Symphonia globulifera L.f.: a new low-coverage draft genome, SNP and SSR markers
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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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Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics
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Supplementary material 8 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 5 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 4 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 3 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 6 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
Supplementary material 7 from: Garrido-Sanz L, Senar MÀ, Piñol J (2020) Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics. Metabarcoding and Metagenomics 4: e48281. https://doi.org/10.3897/mbmg.4.48281
: Data type: Excel table
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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.