Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
25
datasets available to search
ShareScore release 0.9.0
Dataset results
25 results for “tsetse fly”
Fig. 4 in Molecular screening of tsetse flies and cattle reveal different Trypanosoma species including T. grayi and T. theileri in northern Cameroon
Fig. 4 Dcmtlcbutcon of Trypanosoma mpeccem cn tmetme flcem. a Relatcve abundance of tlspanomomal DNA bs mpeccem cn the gut. b Relatcve abundance of tlspanomomal DNA bs mpeccem cn plobomccm. c Collelatcon of tlspanomomal DNA cn gut and plobomccm. Abbreviations: Tg, T. grayi; Tc, T. congolense; Tb, T. brucei mmp.; Tv, T. vivax. If no amplccon wam detected, the fls wam conmcdeled to be negatcve
Fig. 3 in Molecular screening of tsetse flies and cattle reveal different Trypanosoma species including T. grayi and T. theileri in northern Cameroon
Fig. 3 The mequence of an amplccon obtacned flom tmetme fls gut wcth plcmelm mpeccfcc fol T. grayi. Speccfcc plcmelm (TGR-In plcmel met) talgeted agacnmt T. grayi amplcfced a 525 bp flagment (MG234546, Addctconal fcle 1: Table S4) flom tmetme fls gut mample (ID 237-51-00211-1-40-10, G. tachinoides, Addctconal fcle 1: Table S4). The flagment wam mequenced and alcgned wcth the collempondcng flagment of genomcc DNA flom T. grayi ANR4 (JMRU01000589)
Figure 2 in Genetic structure of Trypanosoma congolense "forest type" circulating in domestic animals and tsetse flies in the South-West region of Cameroon
Figure 2. NJ Tree based on Cavalli-Sforza and Edwards chord distance matrix of T. congolense "forest type" circulating in tsetse flies and domestic animals of Fontem.
Tsetse fly wing landmark data for morphometrics (Vol 20, 21)
<p>Single-wing images were captured from 14,354 pairs of field-collected tsetse wings of species <em>Glossina</em> <em>pallidipes</em> and <em>G</em>. <em>m</em>. <em>morsitans</em> and analysed together with relevant biological data. To answer research questions regarding these flies, we need to locate 11 anatomical landmark coordinates on each wing. The manual location of landmarks is time-consuming, prone to error, and simply infeasible given the number of images. Automatic landmark detection has been proposed to locate these landmark coordinates. We developed a two-tier method using deep learning architectures to classify images and make accurate landmark predictions. The first tier used a classification convolutional neural network to remove most wings that were missing landmarks. The second tier provided landmark coordinates for the remaining wings. For the second tier, compared direct coordinate regression using a convolutional neural network and segmentation using a fully convolutional network. For the resulting landmark predictions, we evaluate shape bias using Procrustes analysis. We employ a data-centric approach paying particular attention to consistent labelling and data augmentations in training data to improve model performance. The classification model used for the first tier achieved perfect classification on the test set. For an image size of 1024×1280, data augmentation reduced the mean pixel distance error from 8.3 (95% CI [4.4,10.3]) to 5.34 (95% CI [3,7]) for the regression model. For the segmentation model, data augmentation did not alter the mean pixel distance error of 3.43 (95% CI [1.9,4.4]). Segmentation had a higher computational complexity and some large outliers. Both models showed minimal shape bias. We chose to deploy the regression model on complete unannotated data since the regression model had a lower computational cost and more stable predictions than the segmentation model. The resulting landmark dataset was provided for future morphometric analysis.</p>
Tsetse flies (Glossina m. morsitans) choose birthing sites guided by substrate cues with no evidence for a role of pheromones
<p>Tsetse flies significantly impact public health and economic development in sub-Saharan African countries by transmitting the fatal disease African trypanosomiasis. Unusually, instead of laying eggs, tsetse birth a single larva that immediately burrows into the soil to pupate. Where the female chooses to larviposit is therefore crucial for offspring survival. Previous laboratory studies suggested that a putative larval pheromone, n-pentadecane, attracts gravid female <em>Glossina morsitans</em> <em>morsitans</em> to appropriate larviposition sites. However, this attraction could not be reproduced in field experiments. Here, we resolve this disparity by designing naturalistic laboratory experiments that closely mimic the physical characteristics found in the wild. We show that gravid <em>G.</em> <em>m. morsitans</em> were neither attracted to the putative pheromone nor, interestingly, to pupae placed in the soil. In contrast, females appear to choose larviposition sites based on environmental substrate cues. We conclude that, among the many cues that likely contribute to larviposition choice in nature, substrate features are a main determinant, while we failed to find evidence of a role of pheromones.</p>
Data from: How do host age and nutrition affect density regulation of obligate versus facultative bacterial symbionts? Insights from the tsetse fly
Open the record for dataset details and reuse information.
Tsetse fly wing landmark data for morphometrics (Vol 20, 21)
Open the record for dataset details and reuse information.
Tsetse flies (Glossina m. morsitans) choose birthing sites guided by substrate cues with no evidence for a role of pheromones
Open the record for dataset details and reuse information.
Figure 1 in Genetic structure of Trypanosoma congolense "forest type" circulating in domestic animals and tsetse flies in the South-West region of Cameroon
Figure 1. Allelic frequency at each locus by host.
Interpreting morphological adaptations associated with viviparity in the Tsetse fly (Glossina morsitans) by three-dimensional analysis
Open the record for dataset details and reuse information.
A machine learning approach to integrating genetic and ecological data in tsetse flies (Glossina pallidipes) for spatially explicit vector control planning
Open the record for dataset details and reuse information.
Data from: The population genomics of multiple tsetse fly (Glossina fuscipes fuscipes) admixture zones in Uganda
Understanding the mechanisms that enforce, maintain, or reverse the process of speciation is an important challenge in evolutionary biology. This study investigates the patterns of divergence and discusses the processes that form and maintain divergent lineages of the tsetse fly Glossina fuscipes fuscipes in Uganda. We sampled 251 flies from 18 sites spanning known genetic lineages and the four admixture zones between them. We apply population genomics, hybrid zone, and approximate Bayesian computation to the analysis of three types of genetic markers: 55,267 double digest restriction-site associated DNA (ddRAD) SNPs to assess genome wide admixture, 16 microsatellites to provide continuity with published data and accurate biogeographic modeling, and a 491 bp fragment of mitochondrial cytochrome oxidase I and II to infer maternal inheritance patterns. Admixture zones correspond with regions impacted by the reorganization of Uganda's river networks that occurred during the formation of the West African Rift system over the last several hundred thousand years. Because tsetse fly population distributions are defined by rivers, admixture zones likely represent both old and new regions of secondary contact. Our results indicate that older hybrid zones contain mostly parental types, while younger zones contain variable hybrid types resulting from multiple generations of interbreeding. These findings suggest that reproductive barriers are nearly complete in the older admixture zones, while nearly absent in the younger admixture zones. Findings are consistent with predictions of hybrid zone theory: Populations in zones of secondary contact transition rapidly from early to late stages of speciation, or collapse all together.
Data from: Laboratory colonisation and genetic bottlenecks in the tsetse fly Glossina pallidipes
Background: The IAEA colony is the only one available for mass rearing of Glossina pallidipes, a vector of human and animal African trypanosomiasis in eastern Africa. This colony is the source for Sterile Insect Technique (SIT) programs in East Africa. The source population of this colony is unclear and its genetic diversity has not previously been evaluated and compared to field populations. Methodology/Principal Findings: We examined the genetic variation within and between the IAEA colony and its potential source populations in north Zimbabwe and the Kenya/Uganda border at 9 microsatellites loci to retrace the demographic history of the IAEA colony. We performed classical population genetics analyses and also combined historical and genetic data in a quantitative analysis using Approximate Bayesian Computation (ABC). There is no evidence of introgression from the north Zimbabwean population into the IAEA colony. Moreover, the ABC analyses revealed that the foundation and establishment of the colony was associated with a genetic bottleneck that has resulted in a loss of 35.7% of alleles and 54% of expected heterozygosity compared to its source population. Also, we show that tsetse control carried out in the 1990's is likely reduced the effective population size of the Kenya/Uganda border population. Conclusions/Significance: All the analyses indicate that the area of origin of the IAEA colony is the Kenya/Uganda border and that a genetic bottleneck was associated with the foundation and establishment of the colony. Genetic diversity associated with traits that are important for SIT may potentially have been lost during this genetic bottleneck which could lead to a suboptimal competitiveness of the colony males in the field. The genetic diversity of the colony is lower than that of field populations and so, studies using colony flies should be interpreted with caution when drawing general conclusions about G. pallidipes biology.
Data from: Genetic diversity and population structure of the tsetse fly Glossina fuscipes fuscipes (Diptera: Glossinidae) in Northern Uganda: implications for vector control
Uganda is the only country where the chronic and acute forms of human African Trypanosomiasis (HAT) or sleeping sickness both occur and are separated by < 100 km in areas north of Lake Kyoga. In Uganda, Glossina fuscipes fuscipes is the main vector of the Trypanosoma parasites responsible for these diseases as well for the animal African Trypanosomiasis (AAT), or Nagana. We used highly polymorphic microsatellite loci and a mitochondrial DNA (mtDNA) marker to provide fine scale spatial resolution of genetic structure of G. f. fuscipes from 42 sampling sites from the northern region of Uganda where a merger of the two disease belts is feared. Based on microsatellite analyses, we found that G. f. fuscipes in northern Uganda are structured into three distinct genetic clusters with varying degrees of interconnectivity among them. Based on genetic assignment and spatial location, we grouped the sampling sites into four genetic units corresponding to northwestern Uganda in the Albert Nile drainage, northeastern Uganda in the Lake Kyoga drainage, western Uganda in the Victoria Nile drainage, and a transition zone between the two northern genetic clusters characterized by high level of genetic admixture. An analysis using HYBRIDLAB supported a hybrid swarm model as most consistent with tsetse genotypes in these admixed samples. Results of mtDNA analyses revealed the presence of 30 haplotypes representing three main haplogroups, whose location broadly overlaps with the microsatellite defined clusters. Migration analyses based on microsatellites point to moderate migration among the northern units located in the Albert Nile, Achwa River, Okole River, and Lake Kyoga drainages, but not between the northern units and the Victoria Nile drainage in the west. Effective population size estimates were variable with low to moderate sizes in most populations and with evidence of recent population bottlenecks, especially in the northeast unit of the Lake Kyoga drainage. Our microsatellite and mtDNA based analyses indicate that G. f. fuscipes movement along the Achwa and Okole rivers may facilitate northwest expansion of the Rhodesiense disease belt in Uganda. We identified tsetse migration corridors and recommend a rolling carpet approach from south of Lake Kyoga northward to minimize disease dispersal and prevent vector re-colonization. Additionally, our findings highlight the need for continuing tsetse monitoring efforts during and after control.
Data from: Population sizes and dispersal pattern of tsetse flies: rolling on the river?
Open the record for dataset details and reuse information.
Data from: Genetic diversity and population structure of the tsetse fly Glossina fuscipes fuscipes (Diptera: Glossinidae) in Northern Uganda: implications for vector control
Open the record for dataset details and reuse information.
Data from: A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda
Open the record for dataset details and reuse information.
Data from: Temporal genetic differentiation in Glossina pallidipes tsetse fly populations in Kenya
Open the record for dataset details and reuse information.
Data from: The population genomics of multiple tsetse fly (Glossina fuscipes fuscipes) admixture zones in Uganda
Open the record for dataset details and reuse information.
Data from: Laboratory colonisation and genetic bottlenecks in the tsetse fly Glossina pallidipes
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.