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.
13
datasets available to search
ShareScore release 0.9.0
Dataset results
13 results for “evolved mechanisms”
Data from: Ecological mechanism of climate-mediated selection in a rapidly evolving invasive species
Open the record for dataset details and reuse information.
Data from: Highest plasticity of carbon concentrating mechanisms in earliest evolved phytoplankton
Phytoplankton photosynthesis strongly relies on the operation of carbon‐concentrating mechanisms (CCMs) to accumulate CO2 around their carboxylating enzyme ribulose‐1,5‐bisphosphate carboxylase/oxygenase (RuBisCO). Earlier evolved phytoplankton groups were shown to exhibit higher CCM activities to compensate for their RuBisCO with low CO2 specificities. Here, we tested whether earlier evolved phytoplankton groups also exhibit a higher CCM plasticity. To this end, we collected data from literature and applied a Bayesian linear meta‐analytic model. Our results show that with elevated pCO2, photosynthetic CO2 affinities decreased strongest and most consistent for the earlier evolved groups, i.e., cyanobacteria and dinoflagellates, while CO2‐dependent changes in affinities for haptophytes and diatoms were smaller and less consistent. In addition, responses of maximum photosynthetic rates toward elevated pCO2 were generally small and inconsistent across species. Our results demonstrate that phytoplankton groups with an earlier origin possess a high CCM plasticity, whereas more recently evolved groups do not, which likely results from evolved differences in the CO2 specificity of RuBisCO.
Data from: Correlation between sequence divergence and polymorphism reveals similar evolutionary mechanisms acting across multiple timescales in a rapidly evolving plastid genome
Open the record for dataset details and reuse information.
Data from: Highest plasticity of carbon concentrating mechanisms in earliest evolved phytoplankton
Open the record for dataset details and reuse information.
Data from: Can plants evolve tolerance mechanisms to heterospecific pollen effects? An experimental test of the adaptive potential in Clarkia species
Flowering plants do not occur alone and often grow in mixed-species communities where pollinator sharing is high and interactions via pollinators can occur at pre- and post-pollination stages. While the causes and consequences of pre-pollination interactions have been well studied little is known about post-pollination interactions via heterospecific pollen (HP) receipt, and even less about the evolutionary implications of these interactions. In particular, the degree to which plants can evolve tolerance mechanisms to the negative effects of HP receipt has received little attention. Here, we aim to fill this gap in our understanding of post-pollination interactions by experimentally testing whether two co-flowering Clarkia species can evolve HP tolerance, and whether tolerance to specific HP 'genotypes' (fine-scale local adaptation to HP) occurs. We find that Clarkia species vary in their tolerance to HP effects. Furthermore, conspecific pollen performance and the magnitude of HP effects were related to the recipient's history of exposure to HP in C. xantiana but not in C. speciosa. Specifically, better conspecific pollen performance and smaller HP effects were observed in populations of C. xantiana plants with previous exposure to HP compared to populations without such exposure. These results suggest that plants may have the potential to evolve tolerance mechanisms to HP effects but that these may occur not from the female (stigma, style) but from the male (pollen) perspective, a possibility that is often overlooked. We find no evidence for fine-scale local adaptation to HP receipt. Studies that evaluate the adaptive potential of plants to the negative effects of HP receipt are an important first step in understanding the evolutionary consequences of plant–plant post-pollination interactions. Such knowledge is in turn crucial for deciphering the role of plant–pollinator interactions in driving floral evolution and the composition of co-flowering communities.
Combining metabolomics and experimental evolution reveals key mechanisms underlying longevity differences in laboratory evolved Drosophila melanogaster populations
<p>Experimental evolution with Drosophila melanogaster has been used extensively for decades to study aging and longevity. In recent years, the addition of DNA and RNA sequencing to this framework has allowed researchers to leverage the statistical power inherent to experimental evolution to study the genetic basis of longevity itself. Here, we incorporated metabolomic data into to this framework to generate even deeper insights into the physiological and genetic mechanisms underlying longevity differences in three groups of experimentally evolved D. melanogaster populations with different aging and longevity patterns. Our metabolomic analysis found that aging alters mitochondrial metabolism through increased consumption of NAD<sup>+</sup> and increased usage of the TCA cycle. Combining our genomic and metabolomic data produced a list of biologically relevant candidate genes. Among these candidates, we found significant enrichment for genes and pathways associated with neurological development and function, and carbohydrate metabolism. While we do not explicitly find enrichment for aging canonical genes, neurological dysregulation and carbohydrate metabolism are both known to be associated with accelerated aging and reduced longevity. Taken together, our results provide plausible genetic mechanisms for what might be driving longevity differences in this experimental system. More broadly, our findings demonstrate the value of combining multiple types of omic data with experimental evolution when attempting to dissect mechanisms underlying complex and highly polygenic traits such as aging.</p>
Combining metabolomics and experimental evolution reveals key mechanisms underlying longevity differences in laboratory evolved Drosophila melanogaster populations
Open the record for dataset details and reuse information.
Data from: More than one way to evolve a weed: Parallel evolution of U.S. weedy rice through independent genetic mechanisms
Open the record for dataset details and reuse information.
Data from: Can plants evolve tolerance mechanisms to heterospecific pollen effects? An experimental test of the adaptive potential in Clarkia species
Open the record for dataset details and reuse information.
Global pleiotropic effects in adaptively evolved Escherichia coli lacking CRP reveal molecular mechanisms that define growth physiology
GEO Series GSE152214. Escherichia coli str. K-12 substr. MG1655. 24 samples. Type: Expression profiling by high throughput sequencing.
Data from: How mechanisms of habitat preference evolve and promote divergence with gene flow
Habitat preference may promote adaptive divergence and speciation, yet the conditions under which this is likely are insufficiently explored. We use individual-based simulations to study the evolution and consequence of habitat preference during divergence with gene flow, considering four different underlying genetically-based behavioral mechanisms: natal habitat imprinting, phenotype-dependent, competition-dependent, and direct genetic habitat preference. We find that the evolution of habitat preference generally requires initially high dispersal, is facilitated by asymmetry in population sizes between habitats, and is hindered by an increasing number of underlying genetic loci. Moreover, the probability of habitat preference to emerge and promote divergence differs greatly among the underlying mechanisms. Natal habitat imprinting evolves most easily and can allow full divergence in parameter ranges where no divergence is possible in the absence of habitat preference. The reason is that imprinting represents a one-allele mechanism of assortative mating linking dispersal behavior very effectively to local selection. At the other extreme, direct genetic habitat preference, a two-allele mechanism, evolves under restricted conditions only, and even then facilitates divergence weakly. Overall, our results indicate that habitat preference can be a strong reproductive barrier promoting divergence with gene flow, but that this is highly contingent on the underlying preference mechanism.
Data from: How mechanisms of habitat preference evolve and promote divergence with gene flow
Open the record for dataset details and reuse information.
The Legionella pneumophila genome evolved to accommodate multiple regulatory mechanisms controlled by the CsrA-system
GEO Series GSE94068. Legionella pneumophila str. Paris. 10 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
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.