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11,177 results for “identify”
Data from: Identifying genetic markers for a range of phylogenetic utility–from species to family level
Resolving the phylogenetic relationships of closely related species using a small set of loci is challenging as sufficient information may not be captured from a limited sample of the genome. Relying on few loci can also be problematic when conflict between gene-trees arises from incomplete lineage sorting and/or ongoing hybridization, problems especially likely in recently diverged lineages. Here, we developed a method using limited genomic resources that allows identification of many low copy candidate loci from across the nuclear and chloroplast genomes, design probes for target capture and sequence the captured loci. To validate our method we present data from Eucalyptus and Melaleuca, two large and phylogenetically problematic genera within the Myrtaceae family. With one annotated genome, one transcriptome and two whole-genome shotgun sequences of one Eucalyptus and four Melaleuca species, respectively, we identified 212 loci representing 263 kbp for targeted sequence capture and sequencing. Of these, 209 were successfully tested from 47 samples across five related genera of Myrtaceae. The average percentage of reads mapped back to the reference was 57.6% with coverage of more than 20 reads per position across 83.5% of the data. The methods developed here should be applicable across a large range of taxa across all kingdoms. The core methods are very flexible, providing a platform for various genomic resource availabilities and are useful from shallow to deep phylogenies.
Data from: RClone: a package to identify MultiLocus Clonal Lineages and handle clonal datasets in R
Partially clonal species are common in the Tree of Life. And yet, population genetics models still mostly focus on the extremes: strictly sexual versus purely asexual reproduction. Here we present an R package built upon GenClone software including new functions and several improvements. The RClone package includes functions to handle clonal datasets, allowing (i) checking for dataset reliability to discriminate multi-locus genotypes (MLG), (ii) ascertainment of MLG and semi-automatic determination of clonal lineages (MLL), (iii) genotypic richness and evenness indices calculation based on MLGs or MLLs, and (iv) describing several spatial components of clonality. RClone allows the one shot analysis of multi-population datasets without size limitation, suitable for datasets now increasingly produced through Next Generation Sequencing. A major improvement compared to existing software is the ability to determine the threshold to cluster similar MLGs into MLLs, based on implemented simulations of sexual events. Several functions allow data importation, conversion and exportation with adegenet, Genetix or Arlequin. RClone is provided with two vignettes to handle analysis on one (RClone_quickmanual) or several populations (RClone_qmsevpops).
Data from: Using Drosophila melanogaster to identify chemotherapy toxicity genes
The severity of the toxic side effects of chemotherapy shows a great deal of interindividual variability, and much of this variation is likely genetically based. Simple DNA tests predictive of toxic side effects could revolutionize the way chemotherapy is carried out. Due to the challenges in identifying polymorphisms that affect toxicity in humans, we use Drosophila fecundity following oral exposure to carboplatin, gemcitabine and mitomycin C as a model system to identify naturally occurring DNA variants predictive of toxicity. We use the Drosophila Synthetic Population Resource (DSPR), a panel of recombinant inbred lines derived from a multiparent advanced intercross, to map quantitative trait loci affecting chemotoxicity. We identify two QTL each for carboplatin and gemcitabine toxicity and none for mitomycin. One QTL is associated with fly orthologs of a priori human carboplatin candidate genes ABCC2 and MSH2, and a second QTL is associated with fly orthologs of human gemcitabine candidate genes RRM2 and RRM2B. The third, a carboplatin QTL, is associated with a posteriori human orthologs from solute carrier family 7A, INPP4A&B, and NALCN. The fourth, a gemcitabine QTL that also affects methotrexate toxicity, is associated with human ortholog GPx4. Mapped QTL each explain a significant fraction of variation in toxicity, yet individual SNPs and transposable elements in the candidate gene regions fail to singly explain QTL peaks. Furthermore, estimates of founder haplotype effects are consistent with genes harboring several segregating functional alleles. We find little evidence for nonsynonymous SNPs explaining mapped QTL; thus it seems likely that standing variation in toxicity is due to regulatory alleles.
Data from: Chlamydomonas genome resource for laboratory strains reveals a mosaic of sequence variation, identifies true strain histories, and enables strain-specific studies
Chlamydomonas reinhardtii is a widely used reference organism in studies of photosynthesis, cilia, and biofuels. Most research in this field uses a few dozen standard laboratory strains that are reported to share a common ancestry, but exhibit substantial phenotypic differences. In order to facilitate ongoing Chlamydomonas research and explain the phenotypic variation, we mapped the genetic diversity within these strains using whole-genome resequencing. We identified 524,640 single nucleotide variants and 4812 structural variants among 39 commonly used laboratory strains. Nearly all (98.2%) of the total observed genetic diversity was attributable to the presence of two, previously unrecognized, alternate haplotypes that are distributed in a mosaic pattern among the extant laboratory strains. We propose that these two haplotypes are the remnants of an ancestral cross between two strains with ∼2% relative divergence. These haplotype patterns create a fingerprint for each strain that facilitates the positive identification of that strain and reveals its relatedness to other strains. The presence of these alternate haplotype regions affects phenotype scoring and gene expression measurements. Here, we present a rich set of genetic differences as a community resource to allow researchers to more accurately conduct and interpret their experiments with Chlamydomonas.
Data from: Generation of a monoclonal antibody recognizing the heavily glycosylated CD45 Protein and its application on identifying circulating tumor cells
Here, we provide direct evidence that using recombinant proteins expressed in eukaryotic cells as antigen is a practical way to generate monoclonal antibodies (mAbs) against heavily glycosylated proteins. Heavily glycosylated proteins are typically difficult targets for mAb generation, being limited by unsatisfactory affinity and low specificity. Using the heavily glycosylated CD45 protein as an example, we demonstrate the entire process of expressing the protein in eukaryotic cells and using it as an antigen to generate CD45-targeting mAbs in mice. The mAbs generated showed robust affinity and specificity, which are crucial factors for differentiate circulating tumor cells from white blood cells in human breast cancer patient samples. Only 1 cell fusion and 2 cyclic sub-cloning steps were necessary before mAbs with satisfactory performance were obtained.
Data from: A model to identify urban traffic congestion hotspots in complex networks
The rapid growth of population in urban areas is jeopardizing the mobility and air quality worldwide. One of the most notable problems arising is that of traffic congestion. With the advent of technologies able to sense real-time data about cities, and its public distribution for analysis, we are in place to forecast scenarios valuable for improvement and control. Here, we propose an idealized model, based on the critical phenomena arising in complex networks, that allows to analytically predict congestion hotspots in urban environments. Results on real cities' road networks, considering, in some experiments, real- traffic data, show that the proposed model is capable of identifying susceptible junctions that might becomes hotspots if mobility demand increases.
Data from: Selection by parasitoid females among closely related hosts based on volatiles: Identifying relevant chemical cues
Parasitoid fitness is influenced by the ability to overcome host defense strategies and by the ability of parasitoid females to select high-quality host individuals. When females are unable to differentiate among hosts, their fitness will decrease with an increasing abundance of resistant hosts. To understand the effect of mixed host populations on female fitness, it is therefore necessary to investigate the ability of female parasitoids to select among hosts. Here, we used behavioral assays, headspace volatile collection, and electrophysiology to study the ability of Asecodes parviclava to use olfactory cues to select between a susceptible host (Galerucella calmariensis) and a resistant host (Galerucella pusilla) from a distance. Our studies show that parasitoid females have the capacity to distinguish the two hosts and that the selection behavior is acquired through experiences during earlier life stages. Further, we identified two volatiles (α-terpinolene and [E]-β-ocimene) which amounts differ between the two plant–herbivore systems and that caused behavioral and electrophysiological responses. The consequence of this selection behavior is that females have the capacity to avoid laying eggs in G. pusilla, where the egg mortality is higher due to much stronger immune responses toward A. parviclava than in larvae of G. calmariensis.
Data from: Identifying biases at different spatial and temporal scales of diversification: a case study in the Neotropical parrotlet genus Forpus
The temporal origins of the extraordinary biodiversity of the Neotropical region are highly debated. Recent empirical work has found support for alternative models on the tempo of speciation in Neotropical species further fuelling the debate. However, relationships within many Neotropical lineages are poorly understood and it is unclear how this uncertainty impacts inferences on the evolution of taxa in the region. We examined the robustness of diversification patterns in the avian genus Forpus by testing whether the use of different units of biodiversity (i.e. biological species and statistically inferred species) impacted diversification rates and inferences regarding important biogeographic breaks in the genus. We found that the best-fit model of diversification for the biological species data set was a declining rate of diversification; whereas a model of constant diversification was the best-fit model for statistically inferred species or subspecies. Moreover, the relative importance of different landscape features in delimiting genetic structure across the landscape varied across data sets with differing units of biodiversity. Patterns based on divergence times among biological species indicated old speciation events across major geographic and river barriers, in contrast, data sets more inclusive of the diversity in Forpus illustrate the role of both old divergence across major landscape features as well as more recent divergences that are possibly attributed to Pleistocene climatic changes. Overall, these results indicate that conflicting models on the temporal origins of Neotropical birds may be attributable to sampling biases.
Data from: Genome-wide association study identifies vitamin B5 biosynthesis as a host specificity factor in Campylobacter
Genome-wide association studies have the potential to identify causal genetic factors underlying important phenotypes but have rarely been performed in bacteria. We present an association mapping method that takes into account the clonal population structure of bacteria and is applicable to both core and accessory genome variation. Campylobacter is a common cause of human gastroenteritis as a consequence of its proliferation in multiple farm animal species and its transmission via contaminated meat and poultry. We applied our association mapping method to identify the factors responsible for adaptation to cattle and chickens among 192 Campylobacter isolates from these and other host sources. Phylogenetic analysis implied frequent host switching but also showed that some lineages were strongly associated with particular hosts. A seven-gene region with a host association signal was found. Genes in this region were almost universally present in cattle but were frequently absent in isolates from chickens and wild birds. Three of the seven genes encoded vitamin B5 biosynthesis. We found that isolates from cattle were better able to grow in vitamin B5-depleted media and propose that this difference may be an adaptation to host diet.
Data from: Male zebra finches have limited ability to identify high-fecundity females
In species with biparental care and lifetime monogamy, the fecundity of a male's partner can be a major component of his fitness but it is unclear whether males can assess female fecundity before breeding. We carried out an experiment in which we measured variation in female fecundity (repeatability 39%, 213 females) in a captive zebra finch population and tested whether males preferred unfamiliar females of high fecundity (approximately top 10% of the population; 30 eggs laid on average) over those of low fecundity (bottom 10%; 6 eggs). We first tested whether naïve human observers could identify the high-fecundity female when confronted with duos of high and low fecundity. Humans guessed correctly in 58% of the cases (95% confidence interval [CI] 50–66%) indicating that differences in female condition were not highly obvious to humans. Zebra finch males preferred the high-fecundity female in 59% of choice tests that lasted 20 min (CI 52–66%). When extending such choice tests over several days, male "success" in associating with the high-fecundity female was still modest (61% correct choices, CI 44–76%). Overall, male zebra finches seem to have only limited abilities to identify the better mate when faced with a choice between extremes in terms of female fecundity. We found no male preference for heavier females. We speculate that such a preference may not have evolved because, in contrast to many ectothermic species, predicting fecundity from female weight is not sufficiently accurate (r2 = 0.04) for the benefits to outweigh the costs of increased male–male competition for heavy females.
Data from: The trouble with triplets in biodiversity informatics: a data-driven case against current identifier practices
The biodiversity informatics community has discussed aspirations and approaches for assigning globally unique identifiers (GUIDs) to biocollections for nearly a decade. During that time, and despite misgivings, the de facto standard identifier has become the "Darwin Core Triplet", which is a concatenation of values for institution code, collection code, and catalog number associated with biocollections material. Our aim is not to rehash the challenging discussions regarding which GUID system in theory best supports the biodiversity informatics use case of discovering and linking digital data across the Internet, but how well we can link those data together at this moment, utilizing the current identifier schemes that have already been deployed. We gathered Darwin Core Triplets from a subset of VertNet records, along with vertebrate records from GenBank and the Barcode of Life Data System, in order to determine how Darwin Core Triplets are deployed "in the wild". We asked if those triplets follow the recommended structure and whether they provide an easy and unambiguous means to track from specimen records to genetic sequence records. We show that Darwin Core Triplets are often riddled with semantic and syntactic errors when deployed and curated in practice, despite specifications about how to construct them. Our results strongly suggest that Darwin Core Triplets that have not been carefully curated are not currently serving a useful role for relinking data. We briefly consider needed next steps to overcome current limitations.
Data from: Large-scale functional networks identified from resting-state EEG using spatial ICA
Several methods have been applied to EEG or MEG signals to detect functional networks. In recent works using MEG/EEG and fMRI data, temporal ICA analysis has been used to extract spatial maps of resting-state networks with or without an atlas-based parcellation of the cortex. Since the links between the fMRI signal and the electromagnetic signals are not fully established, and to avoid any bias, we examined whether EEG alone was able to derive the spatial distribution and temporal characteristics of functional networks. To do so, we propose a two-step original method: 1) An individual multi-frequency data analysis including EEG-based source localisation and spatial independent component analysis, which allowed us to characterize the resting-state networks. 2) A group-level analysis involving a hierarchical clustering procedure to identify reproducible large-scale networks across the population. Compared with large-scale resting-state networks obtained with fMRI, the proposed EEG-based analysis revealed smaller independent networks thanks to the high temporal resolution of EEG, hence hierarchical organization of networks. The comparison showed a substantial overlap between EEG and fMRI networks in motor, premotor, sensory, frontal, and parietal areas. However, there were mismatches between EEG-based and fMRI-based networks in temporal areas, presumably resulting from a poor sensitivity of fMRI in these regions or artefacts in the EEG signals. The proposed method opens the way for studying the high temporal dynamics of networks at the source level thanks to the high temporal resolution of EEG. It would then become possible to study detailed measures of the dynamics of connectivity.
Data from: An active-radio-frequency-identification system capable of identifying co-locations and social-structure: validation with a wild free-ranging animal
Behavioural events that are important for understanding sociobiology and movement ecology are often rare, transient and localised, but can occur at spatially distant sites e.g. territorial incursions and co-locating individuals. Existing animal tracking technologies, capable of detecting such events, are limited by one or more of: battery life; data resolution; location accuracy; data security; ability to co-locate individuals both spatially and temporally. Technology that at least partly resolves these limitations would be advantageous. European badgers (Meles meles L.), present a challenging test-bed, with extra-group paternity (apparent from genotyping) contradicting established views on rigid group territoriality with little social-group mixing. In a proof of concept study we assess the utility of a fully automated active-radio-frequency-identification (aRFID) system combining badger-borne aRFID-tags with static, wirelessly-networked, aRFID-detector base-stations to record badger co-locations at setts (burrows) and near notional border latrines. We summarise the time badgers spent co-locating within and between social-groups, applying network analysis to provide evidence of co-location based community structure, at both these scales. The aRFID system co-located animals within 31.5 m (adjustable) of base-stations. Efficient radio transmission between aRFIDs and base-stations enables a 20 g tag to last for 2–5 years (depending on transmission interval). Data security was high (data stored off tag), with remote access capability. Badgers spent most co-location time with members of their own social-groups at setts; remaining co-location time was divided evenly between intra- and inter-social-group co-locations near latrines and inter-social-group co-locations at setts. Network analysis showed that 20–100% of tracked badgers engaged in inter-social-group mixing per week, with evidence of trans-border super-groups, that is, badgers frequently transgressed notional territorial borders. aRFID occupies a distinct niche amongst established tracking technologies. We validated the utility of aRFID to identify co-locations, social-structure and inter-group mixing within a wild badger population, leading us to refute the conventional view that badgers (social-groups) are territorial and to question management strategies, for controlling bovine TB, based on this model. Ultimately aRFID proved a versatile system capable of identifying social-structure at the landscape scale, operating for years and suitable for use with a range of species.
Data from: Monarch butterfly population decline in North America: identifying the threatening processes
The monarch butterfly (Danaus plexippus) population in North America has sharply declined over the last two decades. Despite rising concern over the monarch butterfly's status, no comprehensive study of the factors driving this decline has been conducted. Using partial least-squares regressions and time-series analysis, we investigated climatic and habitat-related factors influencing monarch population size from 1993 to 2014. Potential threats included climatic factors, habitat loss (milkweed and overwinter forest), disease and agricultural insecticide use (neonicotinoids). While climatic factors, principally breeding season temperature, were important determinants of annual variation in abundance, our results indicated strong negative relationships between population size and habitat loss variables, principally glyphosate use, but also weaker negative effects from the loss of overwinter forest and breeding season use of neonicotinoids. Further declines in population size because of glyphosate application are not expected. Thus, if remaining threats to habitat are mitigated we expect climate-induced stochastic variation of the eastern migratory population of monarch butterfly around a relatively stationary population size.
Data from: Evaluation of an acoustic telemetry transmitter designed to identify predation events
The field of acoustic telemetry has evolved rapidly and now permits the remote sensing of animal behaviour, movement, physiology and survival in environments and species not previously possible. However, an inability to detect when a telemetered animal is consumed by a predator can complicate accurate interpretation of telemetry data. Here, we describe efforts to test two generations of a novel prototype acoustic telemetry transmitter designed specifically to detect predation. Testing involved either staged predation events where tagged prey (Rainbow Trout Oncorhynchus mykiss and Yellow Perch Perca flavescens) were fed to captive Largemouth Bass Micropterus salmoides, or false positive testing where prey fish were tagged and held without risk of predation. Metrics of interest were (a) the rate of correctly identifying predation events, (b) signal lag (i.e. the time required to detect a predation event), (c) tag retention time in the predator's gut, and (d) the rate of false positive triggering in both live and dead prey fishes. Staged predation events were successfully identified in 61/65 and 52/55 trials for generation 1 and 2 tags, respectively. Signal lag time was reduced in generation 1 tags (generally between 1 - 9 hours) relative to generation 2 (3 - 29 hours); although signal lag was highly variable. A generalized linear mixed model indicated strong evidence that signal lag and tag retention were both negatively correlated with water temperature, but were not affected by prey species and only slightly by individual predator traits. There was preliminary evidence that prey size may be an important determinant of both signal lag and tag retention. False positives in live fish were absent after 120 days for generation 1 tags (n=31), however rates were significantly higher (10/44) after only 66 days for generation 2 tags. False positives in dead fish suggested that 20% of generation 2 predation tags would falsely trigger 2-3 days post-mortem. Testing of the novel predation tags was encouraging however further testing is recommended. Predation tags will be an important contribution to the field of acoustic telemetry; permitting improved data interpretation and less subjective estimates of predation rates in biotelemetry studies.
Data from: Combining animal personalities with transcriptomics resolves individual variation within a wild-type zebrafish population and identifies underpinning molecular differences in brain function
Resolving phenotype variation within a population in response to environmental perturbation is central to understanding biological adaptation. Relating meaningful adaptive changes at the level of the transcriptome requires the identification of processes that have a functional significance for the individual. This remains a major objective towards understanding the complex interactions between environmental demand and an individual's capacity to respond to such demands. The interpretation of such interactions and the significance of biological variation between individuals from the same or different populations remain a difficult and under-addressed question. Here, we provide evidence that variation in gene expression between individuals in a zebrafish population can be partially resolved by a priori screening for animal personality and accounts for >9% of observed variation in the brain transcriptome. Proactive and reactive individuals within a wild-type population exhibit consistent behavioural responses over time and context that relates to underlying differences in regulated gene networks and predicted protein–protein interactions. These differences can be mapped to distinct regions of the brain and provide a foundation towards understanding the coordination of underpinning adaptive molecular events within populations.
Data from: Identifying homomorphic sex chromosomes from wild-caught adults with limited genomic resources
We demonstrate a genotyping-by-sequencing approach to identify homomorphic sex chromosomes and their homolog in a distantly related reference genome, based on noninvasive sampling of wild-caught individuals, in the moor frog Rana arvalis. Double-digest RADseq libraries were generated using buccal swabs from 30 males and 21 females from the same population. Search for sex-limited markers from the unfiltered data set (411 446 RAD tags) was more successful than searches from a filtered data set (33 073 RAD tags) for markers showing sex differences in heterozygosity or in allele frequencies. Altogether, we obtained 292 putatively sex-linked RAD loci, 98% of which point to male heterogamety. We could map 15 of them to the Xenopus tropicalis genome, all but one on chromosome pair 1, which seems regularly co-opted for sex determination among amphibians. The most efficient mapping strategy was a three-step hierarchical approach, where R. arvalis reads were first mapped to a low-coverage genome of Rana temporaria (17 My divergence), then the R. temporaria scaffolds to the Nanorana parkeri genome (90 My divergence), and finally the N. parkeri scaffolds to the X. tropicalis genome (210 My). We validated our conclusions with PCR primers amplifying part of Dmrt1, a candidate sex determination gene mapping to chromosome 1: a sex-diagnostic allele was present in all 30 males but in none of the 21 females. Our approach is likely to be productive in many situations where biological samples and/or genomic resources are limited.
The origin and genetic variability of vegetatively propagated clones identified from old planted trees and plantations of Thujopsis dolabrata var. hondae in Ishikawa Prefecture, Japan
<p class="Keywords"><span><a name="_Hlk10084612">Clonal plantations of <i>Thujopsis dolabrata</i> var. <i>hondae </i>have been established in Ishikawa Prefecture, Japan, since at least the 1800s. Historical planting of the species has led to the development of vegetatively propagated local cultivars, which originated from 'donor' trees that have often been conserved in sacred groves or avenues at shrines and temples. These donor trees must have been selected from natural populations. In this study we estimated the origin and genetic variability of clones identified among old planted trees and clonal plantations of<i> T. dolabrata </i>var. <i>hondae</i>, using 19 microsatellite markers. We discovered 12 clones among old planted trees, including five identical to members of a set of 14 we previously identified in plantations (giving 21 clones in total). Based on analyses combining assignment and exclusion tests, we inferred origins of eight of those 21 clones: six may have originated from a natural population distributed in Ishikawa, one from Hokkaido & Aomori, and the other from Iwate & Yamagata, suggesting the clones constituting cultivars have multiple origins. The clones identified in plantations have significantly lower genetic variability, and higher relatedness, indicating that clones of cultivars have a much narrower genetic base than those of natural populations. We suggest new clones selected from natural populations</a> elsewhere, as well as Ishikawa, are needed for future breeding of <i>T. dolabrata</i> var. <i>hondae</i> to develop clonal forestry for this species.</span></p>
Data from: Using sensitivity analysis to identify key factors for the propagation of a plant epidemic
Identifying the key factors underlying the spread of a disease is an essential but challenging prerequisite to design management strategies. To tackle this issue, we propose an approach based on sensitivity analyses of a spatiotemporal stochastic model simulating the spread of a plant epidemic. This work is motivated by the spread of sharka, caused by Plum pox virus, in a real landscape. We first carried out a broad-range sensitivity analysis, ignoring any prior information on six epidemiological parameters, to assess their intrinsic influence on model behaviour. A second analysis benefited from the available knowledge on sharka epidemiology and was thus restricted to more realistic values. The broad-range analysis revealed that the mean duration of the latent period is the most influential parameter of the model, whereas the sharka-specific analysis uncovered the strong impact of the connectivity of the first infected orchard. In addition to demonstrating the interest of sensitivity analyses for a stochastic model, this study highlights the impact of variation ranges of target parameters on the outcome of a sensitivity analysis. With regard to sharka management, our results suggest that sharka surveillance may benefit from paying closer attention to highly-connected patches whose infection could trigger serious epidemics.
Data from: Tracking the origins of fly invasions; using mitochondrial haplotype diversity to identify potential source populations in two genetically intertwined fruit fly species (Bactrocera carambolae and Bactrocera dorsalis [Diptera: Tephritidae])
Bactrocera carambolae Drew and Hancock and B. dorsalis (Hendel) (Diptera: Tephritidae) are important pests of many fruits. These flies have been spread across the world through global travel and trade, and new areas are are at risk of invasion. Whenever new invasive populations are discovered, quick and accurate identification is needed to mitigate the damage they can cause. Determining invasive pathways can prevent further spread of pests as well as subsequent reinvasions through the same pathway. Molecular markers can be used for both species identification and pathway analysis. We analyzed 1601 individuals from 18 populations using 765 base pairs of the mitochondrial cytochrome oxidase I (COI) gene to infer the haplotype diversity and population structure within these flies from across their native and invasive ranges. We analyzed these samples by either grouping by species or geographic populations due to the genetic similarity in the mitochondrial genome. We found no genetic structure between B. dorsalis and B. carambolae and our findings suggest recent and most likely ongoing, genetic exchange between these two species in the wild. Hyper-diverse mitochondrial genetic diversity in the native range suggests large population sizes and relatively high mutation rates. Only 52% of the haplotypes found in the trap captures from California are shared with haplotypes from flies found in our global survey, indicating significant genetic diversity in the native range that is missing from our samples. However, these results provide a foundation for the accurate determination of the provenance of invasive populations around the world.
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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.