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.
3,339
datasets available to search
ShareScore release 0.9.0
Dataset results
3,339 results for “heterogeneities”
Data from: Differential temperature sensitivity of synaptic and firing processes in a neural mass model of epileptic discharges explains heterogeneous response of experimental epilepsy to focal brain cooling
Experiments with drug-induced epilepsy in rat brains and epileptic human brain region reveal that focal cooling can suppress epileptic discharges without affecting the brain's normal neurological function. Findings suggest a viable treatment for intractable epilepsy cases via an implantable cooling device. However, precise mechanisms by which cooling suppresses epileptic discharges are still not clearly understood. Cooling experiments in vitro presented evidence of reduction in neurotransmitter release from presynaptic terminals and loss of dendritic spines at post-synaptic terminals offering a possible synaptic mechanism. We show that termination of epileptic discharges is possible by introducing a homogeneous temperature factor in a neural mass model which attenuates the post-synaptic impulse responses of the neuronal populations. This result however may be expected since such attenuation leads to reduced post-synaptic potential and when the effect on inhibitory interneurons is less than on excitatory interneurons, frequency of firing of pyramidal cells is consequently reduced. While this is observed in cooling experiments in vitro, experiments in vivo exhibit persistent discharges during cooling but suppressed in magnitude. This leads us to conjecture that reduction in the frequency of discharges may be compensated through intrinsic excitability mechanisms. Such compensatory mechanism is modelled using a reciprocal temperature factor in the firing response function in the neural mass model. We demonstrate that the complete model can reproduce attenuation of both magnitude and frequency of epileptic discharges during cooling. The compensatory mechanism suggests that cooling lowers the average and the variance of the distribution of threshold potential of firing across the population. Bifurcation study with respect to the temperature parameters of the model reveals how heterogeneous response of epileptic discharges to cooling (termination or suppression only) is exhibited. Possibility of differential temperature effects on post-synaptic potential generation of different populations is also explored.
Data from: Heterogeneity in efflux pump expression predisposes antibiotic-resistant cells to mutation
<p>Antibiotic resistance is often the result of mutations that block drug activity; however, bacteria also evade antibiotics by transiently expressing genes such as multidrug efflux pumps. A crucial question is whether transient resistance can promote permanent genetic changes. Previous studies have established that antibiotic treatment can select tolerant cells that then mutate to achieve permanent resistance. Whether these mutations result from antibiotic stress or preexist within the population is unclear. To address this question, we focused on the multidrug pump AcrAB-TolC. Using time-lapse microscopy, we found that cells with higher acrAB expression have lower expression of the DNA mismatch repair gene mutS, lower growth rates, and higher mutation frequencies. Thus, transient antibiotic resistance from elevated acrAB expression can promote spontaneous mutations within single cells.</p>
Data from: Bayesian tip dating reveals heterogeneous morphological clocks in Mesozoic birds
Recently, comprehensive morphological datasets including nearly all the well-recognized Mesozoic birds became available, making it feasible for statistically rigorous methods to unveil finer evolutionary patterns during early avian evolution. Here, we exploited the advantage of Bayesian tip dating under relaxed morphological clocks to estimate both the divergence times and evolutionary rates while accounting for their uncertainties. We further subdivided the characters into six body regions (i.e., skull, axial skeleton, pectoral girdle and sternum, forelimb, pelvic girdle, and hindlimb) to assess evolutionary rate heterogeneity both along the lineages and across partitions. We observed extremely high rates of morphological character changes during early avian evolution and the clock rates are quite heterogeneous among the six regions. The branch subtending Pygostylia shows extremely high rate in the axial skeleton, while the branches subtending Ornithothoraces and Enantiornithes show notably high rates in the pectoral girdle and sternum, and moderately high rates in the forelimb. The extensive modifications in these body regions largely correspond to refinement of the flight capability. This study reveals the power and flexibility of Bayesian tip dating implemented in MrBayes to investigate evolutionary dynamics in deep time.
Data from: Heterogeneity in local density allows a positive evolutionary relationship between self-fertilisation and dispersal
Despite empirical evidence for a positive relationship between dispersal and self-fertilisation (selfing), theoretical work predicts that these traits should always be negatively correlated, and the Good Coloniser Syndrome of high dispersal and selfing (Cf. Baker's Law) should not evolve. Critically, previous work assumes that adult density is spatiotemporally homogeneous, so selfing results in identical offspring production for all patches, eliminating the benefit of dispersal for escaping from local resource competition. We investigate the joint evolution of dispersal and selfing in a demographically structured metapopulation model where local density is spatiotemporally heterogeneous due to extinction-recolonisation dynamics. Selfing alleviates outcrossing failure due to low local density (an Allee Effect) while dispersal alleviates competition through dispersal of propagules from high- to low-density patches. Because local density is spatiotemporally heterogenous in our model, selfing does not eliminate heterogeneity in competition, so dispersal remains beneficial even under full selfing. Hence the Good Coloniser Syndrome is evolutionarily stable under a broad range of conditions, and both negative and positive relationships between dispersal and selfing are possible, depending on the environment. Our model thus accommodates positive empirical relationships between dispersal and selfing not predicted by previous theoretical work and provides additional explanations for negative relationships.
Data from: Geographical variation in the heterogeneity of mutualistic networks
Plant–animal mutualistic networks are characterized by highly heterogeneous degree distributions. The majority of species interact with few partner species, while a small number are highly connected to form network hubs that are proposed to play an important role in community stability. It has not been investigated, however, if or how the degree distributions vary among types of mutualisms or communities, or between plants and animals in the same network. Here, we evaluate the degree distributions of pollination and seed-dispersal networks, which are two major types of mutualistic networks that have often been discussed in parallel, using an index based on Pielou's evenness. Among 56 pollination networks we found strong negative correlation of the heterogeneity between plants and animals, and geographical shifts of network hubs from plants in temperate regions to animals in the tropics. For 28 seed-dispersal networks, by contrast, the correlation was positive, and there is no comparable geographical pattern. These results may be explained by evolution towards specialization in the presence of context-dependent costs that occur if plants share the animal species as interaction partner. How the identity of network hubs affects the stability and resilience of the community is an important question for future studies.
Data from: Genomic heterogeneity of historical gene flow between two species of newts inferred from transcriptome data
The role of gene flow in species formation is a major unresolved issue in speciation biology. Progress in this area requires information on the long-term patterns of gene flow between diverging species. Here, we used thousands of single-nucleotide polymorphisms derived from transcriptome resequencing and a method modeling the joint frequency spectrum of these polymorphisms to reconstruct patterns of historical gene flow between two Lissotriton newts: L. vulgaris (Lv) and L. montandoni (Lm). We tested several models of divergence including complete isolation and various scenarios of historical gene flow. The model of secondary contact received the highest support. According to this model, the species split from their common ancestor ca. 5.5 million years (MY) ago, evolved in isolation for ca. 2 MY, and have been exchanging genes for the last 3.5 MY Demographic changes have been inferred in both species, with the current effective population size of ca. 0.7 million in Lv and 0.2 million in Lm. The postdivergence gene flow resulted in two-directional introgression which affected the genomes of both species, but was more pronounced from Lv to Lm. Interestingly, we found evidence for genomic heterogeneity of interspecific gene flow. This study demonstrates the complexity of long-term gene flow between distinct but incompletely reproductively isolated taxa which divergence was initiated millions of years ago.
Data from: Food web heterogeneity and succession in created saltmarshes
Ecological restoration must achieve functional as well as structural recovery. Functional metrics for re-establishment of trophic interactions can be used to complement traditional monitoring of structural attributes. In addition, topographic effects on food web structure provide added information within a restoration context; often, created sites may require spatial heterogeneity to effectively match structure and function of natural habitats. We addressed both of these issues in our study of successional development of benthic food web structure, with focus on bottom-up-driven changes in macroinvertebrate consumer assemblages in the saltmarshes of the Venice Lagoon, Italy. We combined quantified estimates of the changing community composition with stable isotope data (13C:12C and 15N:14N) to compare the general trophic structure between created (2–14 years) marshes and reference sites and along topographic elevation gradients within saltmarshes. Macrofaunal invertebrate consumers exhibited local, habitat-specific trophic patterns. Stable isotope-based trophic structure changed with increasing marsh age, in particular with regard to mid-elevation (Salicornia) habitats. In young marshes, the mid-elevation consumer signatures resembled those of unvegetated ponds. The mid-elevation of older and natural marshes had a more distinct Salicornia zone food web, occasionally resembling that of the highest (Sarcocornia-dominated) elevation. In summary, this indicates that primary producers and availability of vascular plant detritus structure consumer trophic interactions and the flow of carbon. Functionally different consumers, subsurface-feeding detritivores (Oligochaeta) and surface grazers (Hydrobia sp.), showed distinct but converging trajectories of isotopic change over time, indicating that successional development may be asymmetric between 'brown' (detrital) guilds and 'green' (grazing) guilds in the food web. Synthesis and applications. Created marsh food webs converged into a natural state over about a decade, with successional shifts seen in both consumer community composition and stable isotope space. Strong spatial effects were noted, highlighting the utility of stable isotopes to evaluate functional equivalence in spatially heterogeneous systems. Understanding the recovery of functional properties such as food web support, and their inherent spatial variability, is key to planning and managing successful habitat restoration.
Data from: Spatial heterogeneity lowers rather than increases host-parasite specialization
Abiotic environmental heterogeneity can promote the evolution of diverse resource specialists, which in turn may increase the degree of host-parasite specialization. We coevolved Pseudomonas fluorescens and lytic phage ϕ2 in spatially structured populations, each consisting of two interconnected subpopulations evolving in the same or different nutrient media (homogeneous and heterogeneous environments, respectively). Counter to the normal expectation, host-parasite specialization was significantly lower in heterogeneous compared with homogeneous environments. This result could not be explained by dispersal homogenizing populations, as this would have resulted in the heterogeneous treatments having levels of specialization equal to or greater than that of the homogeneous environments. We argue that selection for costly generalists is greatest when the coevolving species are exposed to diverse environmental conditions and that this can provide an explanation for our results. A simple coevolutionary model of this process suggests that this can be a general mechanism by which environmental heterogeneity can reduce rather than increase host-parasite specialization.
Data from: Bulk genotyping of biopsies can create spurious evidence for heterogeneity in mutation content
When multiple samples are taken from the neoplastic tissues of a single patient, it is natural to compare their mutation content. This is often done by bulk genotyping of whole biopsies, but the chance that a mutation will be detected in bulk genotyping depends on its local frequency in the sample. When the underlying mutation count per cell is equal, homogenous biopsies will have more high-frequency mutations, and thus more detectable mutations, than heterogeneous ones. Using simulations, we show that bulk genotyping of data simulated under a neutral model of somatic evolution generates strong spurious evidence for non-neutrality, because the pattern of tissue growth systematically generates differences in biopsy heterogeneity. Any experiment which compares mutation content across bulk-genotyped biopsies may therefore suggest mutation rate or selection intensity variation even when these forces are absent. We discuss computational and experimental approaches for resolving this problem.
Data from: Evolution of virulence in heterogeneous host communities under multiple trade-offs
Many pathogens and parasites are transmitted through hosts that differ in species, sex, genotype, or immune status. In addition, virulence (here defined as disease-induced mortality) and transmission can vary during the infectious period within hosts of different state. Most models of virulence evolution assume that transmission and virulence are constant over the infectious period and that the host population is homogenous. Here, we examine a multi-species SIR model where transmission occurs within and between species, and transmission and virulence varied during the infectious period. This allows us to understand virulence evolution in a broader range of situations that characterize many emerging diseases. Because emerging pathogens are by definition new to their host populations, they should be expected to rapidly adapt after emergence. We illustrate these evolutionary effects using the framework of adaptive dynamics to examine how virulence evolves after emergence in response to the relative strength of selection on pathogen fitness and mutational variance for virulence. We illustrate the role of evolution by simulating adaptive walks to an evolutionarily stable virulence. We found that the magnitude of between-species transmission and the relative timing of transmission and mortality across species were of primary importance for determining the evolutionarily stable virulence.
Data from: Abiotic heterogeneity drives parasite local adaptation in coevolving bacteria and phages
Spatial abiotic heterogenity can result in divergent selection, hence might increase the magnitude of host-parasite local adaptation (the mean difference in fitness of sympatric versus allopatric host-parasite combinations). We explicitly tested this hypothesis by measuring local adapation in experimentally coevolved populations of bacteria and viruses evolved in the same or different nutrient media. Consistent with previous work, we found that mean levels of evolved phage infectivity and bacteria resistance varied with nutrient concentration, with maximal levels at nutrient concentrations that supported the greatest densities of bacteria. Despite this variation in evolved mean infectivity and resistance between treatments, we found that parasite local adaptation was greatly increased when measured between populations evolved in different, compared to the same, media. This pattern is likely to have resulted from different media imposing divergent selection on bacterial hosts, and phages in turn adapting to their local hosts. These results demonstrate that the abiotic environment can play a strong and predictable role in driving patterns of local adaptation.
Data from: Quantifying individual heterogeneity and its influence on life-history trajectories: different methods for different questions and contexts
Heterogeneity among individuals influences the life-history trajectories we observe at the population level because viability selection, selective immigration and emigration processes, and ontogeny change the proportion of individuals with specific trait values with increasing age. Here, we review the two main approaches that have been proposed to account for these processes in life-history trajectories, contrasting how they quantify ontogeny and selection, and proposing ways to overcome some of their limitations. Nearly all existing approaches to model individual heterogeneity assume either a single normal distribution or a priori known groups of individuals. Ontogenetic processes, however, can vary across individuals through variation in life-history tactics. We show the usefulness of describing ontogenetic processes by modelling trajectories with a mixture model that focuses on heterogeneity in life-history tactics. Additionally, most methods examine individual heterogeneity in a single trait, ignoring potential correlations among multiple traits caused by latent common sources of individual heterogeneity. We illustrate the value of using a joint modelling approach to assess the presence of a shared latent correlation and its influence on life-history trajectories. We contrast the strengths and limitations of different methods for different research questions, and we exemplify the differences among methods using empirical data from long-term studies of ungulates.
Data from: Shear-induced orientational dynamics and spatial heterogeneity in suspensions of motile phytoplankton
Fluid flow, ubiquitous in natural and man-made environments, has the potential to profoundly impact the transport of microorganisms, including phytoplankton in aquatic habitats and bioreactors. Yet, the effect of ambient flow on the swimming behavior of phytoplankton has remained poorly understood, largely due to the difficulty of observing cell-flow interactions at the microscale. Here, we present microfluidic experiments where we tracked individual cells for four species of motile phytoplankton exposed to a spatially non-uniform fluid shear rate, characteristic of many flows in natural and artificial environments. We observed that medium to high mean shear rates (1 – 25 s^-1) produce heterogeneous cell concentrations in the form of regions of accumulation and regions of depletion. The location of these regions relative to the flow depends on the cells' propulsion mechanism, body shape, and flagellar arrangement, as captured by an effective aspect ratio. Species having a large effective aspect ratio accumulated in the high-shear regions, due to shear-induced alignment of the swimming orientation with the fluid streamlines. Species having an effective aspect ratio close to unity exhibited little preferential accumulation at low to moderate flow rates, but strongly accumulated in the low-shear regions under high flow conditions, potentially due to an active, behavioral response of cells to shear. These observations demonstrate that ambient fluid flow can strongly affect the motility and spatial distribution of phytoplankton and highlight the rich dynamics emerging from the interaction between motility, morphology, and flow.
Data from: The effects of selective history and environmental heterogeneity on inbreeding depression in experimental populations of Drosophila melanogaster
Inbreeding depression varies considerably among populations, but only some aspects of this variation have been thoroughly studied. Because inbreeding depression requires genetic variation, factors that influence the amount of standing variation can affect the magnitude of inbreeding depression. Environmental heterogeneity has long been considered an important contributor to the maintenance of genetic variation, but its effects on inbreeding depression have been largely ignored by empiricists. Here we compare inbreeding depression, measured in two environments, for 20 experimental populations of Drosophila melanogaster that have been maintained under four different selection regimes, including two types of environmentally homogeneous selection and two types environmentally heterogeneous selection. In line with theory, we find considerably higher inbreeding depression in populations from heterogeneous selection regimes. We also use our data set to test whether inbreeding depression is correlated with either stress or the phenotypic coefficient of variation (CV), as suggested by some recent studies. Though both of these factors are significant predictors of inbreeding depression in our study, there is an effect of assay environment on inbreeding depression that cannot be explained by either stress or CV.
Data from: Modeling character change heterogeneity in phylogenetic analyses of morphology through the use of priors
The Mk model was developed for estimating phylogenetic trees from discrete morphological data, whether for living or fossil taxa. Like any model, the Mk model makes a number of assumptions. One assumption is that transitions between character states are symmetric (i.e., the probability of changing from 0 to 1 is the same as 1 to 0). However, some characters in a data matrix may not satisfy this assumption. Here, we test methods for relaxing this assumption in a Bayesian context. Using empirical datasets, we perform model fitting to illustrate cases in which modeling asymmetric transition rates among characters is preferable to the standard Mk model. We use simulated datasets to demonstrate that choosing the best-fit model of transition-state symmetry can improve model fit and phylogenetic estimation.
Data from: Invariant versus classical quartet inference when evolution is heterogeneous across sites and lineages
One reason why classical phylogenetic reconstruction methods fail to correctly infer the underlying topology is because they assume oversimplified models. In this paper we propose a quartet reconstruction method consistent with the most general Markov model of nucleotide substitution, which can also deal with data coming from mixtures on the same topology. Our proposed method uses phylogenetic invariants and provides a system of weights that can be used as input for quartet-based methods. We study its performance on real data and on a wide range of simulated 4-taxon data (both time-homogeneous and nonhomogeneous, with or without among-site rate heterogeneity, and with different branch length settings). We compare it to the classical methods of neighbor-joining (with paralinear distance), maximum likelihood (with different underlying models), and maximum parsimony. Our results show that this method is accurate and robust, has a similar performance to ML when data satisfies the assumptions of both methods, and outperforms the other methods when these are based on inappropriate substitution models. If alignments are long enough, then it also outperforms other methods when some of its assumptions are violated.
Data from: Demographic variability and heterogeneity among individuals within and among clonal bacteria strains
Identifying what drives individual heterogeneity has been of long interest to ecologists, evolutionary biologists and biodemographers, because only such identification provides deeper understanding of ecological and evolutionary population dynamics. In natural populations one is challenged to accurately decompose the drivers of heterogeneity among individuals as genetically fixed or selectively neutral. Rather than working on wild populations we present here data from a simple bacterial system in the lab, Escherichia coli. Our system, based on cutting-edge microfluidic techniques, provides high control over the genotype and the environment. It therefore allows to unambiguously decompose and quantify fixed genetic variability and dynamic stochastic variability among individuals. We show that within clonal individual variability (dynamic heterogeneity) in lifespan and lifetime reproduction is dominating at about 82–88%, over the 12–18% genetically (adaptive fixed) driven differences. The genetic differences among the clonal strains still lead to substantial variability in population growth rates (fitness), but, as well understood based on foundational work in population genetics, the within strain neutral variability slows adaptive change, by enhancing genetic drift, and lowering overall population growth. We also revealed a surprising diversity in senescence patterns among the clonal strains, which indicates diverse underlying cell-intrinsic processes that shape these demographic patterns. Such diversity is surprising since all cells belong to the same bacteria species, E. coli, and still exhibit patterns such as classical senescence, non-senescence, or negative senescence. We end by discussing whether similar levels of non-genetic variability might be detected in other systems and close by stating the open questions how such heterogeneity is maintained, how it has evolved, and whether it is adaptive.
Data from: Environmental heterogeneity does not affect levels of phenotypic plasticity in natural populations of three Drosophila species
Adaptation of natural populations to variable environmental conditions may occur by changes in trait means and/or in the levels of plasticity. Theory predicts that environmental heterogeneity favors plasticity of adaptive traits. Here we investigated the performance in several traits of three sympatric Drosophila species freshly collected in two environments that differ in the heterogeneity of environmental conditions. Differences in trait means within species were found in several traits, indicating that populations differed in their evolutionary response to the environmental conditions of their origin. Different species showed distinct adaptation with a very different role of plasticity across species for coping with environmental changes. However, geographically distinct populations of the same species generally displayed the same levels of plasticity as induced by fluctuating thermal regimes. This indicates a weak and trait-specific effect of environmental heterogeneity on plasticity. Furthermore, similar levels of plasticity were found in a laboratory-adapted population of Drosophila melanogaster with a common geographic origin but adapted to the laboratory conditions for more than 100 generations. Thus, this study does not confirm theoretical predictions on the degree of adaptive plasticity among populations in relation to environmental heterogeneity but shows a very distinct role of species-specific plasticity.
Data from: The influence of geographic heterogeneity in predation pressure on mating signal divergence in an Amazonian frog species complex
Sexual section plays an important role in mating signal divergence, but geographic variation in ecological factors can also contribute to divergent signal evolution. We tested the hypothesis that geographic heterogeneity in predation causes divergent selection on advertisement call complexity within the Engystomops petersi frog species complex. We conducted predator phonotaxis experiments at two sites where female choice is consistent with call trait divergence. Engystomops at one site produces complex calls, while the closely related species at the other site produces simple calls. Bats approached complex calls more than simple calls at both sites, suggesting selection against complex calls. Moreover, bat predation pressure was greater at the site with simple calls, suggesting stronger selection against complex calls and potentially precluding evolution of complex calls at this site. Our results show that geographic variation in predation may play an important role in the evolution and maintenance of mating signal divergence.
Data from: Optimal management strategy of insecticide resistance under various insect life histories: heterogeneous timing of selection and inter-patch dispersal
Although theoretical studies have shown that the mixture strategy, which uses multiple toxins simultaneously, can effectively delay the evolution of insecticide resistance, whether it is the optimal management under different insect life histories and insecticide types remains unknown. To test the robustness of the management strategy over the life histories, we developed a series of simulation models which cover almost all the diploid insect types and have the same basic structure describing pest population dynamics and resistance evolution with discrete time-steps. For each of two insecticidal toxins, one-locus two-allele autosomal inheritance of resistance was assumed. The simulations demonstrated the optimality of the mixture strategy either when insecticide efficacy was incomplete or when some part of the population disperses between patches before mating. The rotation strategy, which uses one insecticide on one pest generation and a different one on the next, did not differ from sequential usage in the time to resistance, except when dominance was low. It was the optimal strategy when insecticide efficacy was high and pre-mating selection and dispersal occur.
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.