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.
62
datasets available to search
ShareScore release 0.9.0
Dataset results
62 results for “Rate Adaptation”
Orthodontic Reduction of an Increased Overbite in Adolescents - the Mechanism and Rate of Occlusal Adaptation
ClinicalTrials.gov study NCT02925468. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Trial to Study Intubation Rates of Non-invasive Ventilation Using Pressure Support Ventilation (PSV) Versus Adaptive Support Ventilation (ASV) Mode in Patients With Acute Exacerbation of Chronic Obstr
ClinicalTrials.gov study NCT02877524. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Data from: Maternal effects in a wild songbird are environmentally plastic but only marginally alter the rate of adaptation
Open the record for dataset details and reuse information.
Data from: Cold adaptation increases rates of nutrient flow and metabolic plasticity during cold exposure in Drosophila melanogaster
Open the record for dataset details and reuse information.
Data from: Elevated evolutionary rates of biting biomechanics reveal patterns of extraordinary cranio-dental adaptations in some herbivorous dinosaurs
Open the record for dataset details and reuse information.
Data from: Plastic but not adaptive: habitat-driven differences in metabolic rate despite no differences in selection between habitats
Open the record for dataset details and reuse information.
Temporal and sociocultural effects of human colonisation on native biodiversity: Filtering and rates of adaptation
Open the record for dataset details and reuse information.
Data from: Evolutionary rescue and local adaptation under different rates of temperature increase: a combined analysis of changes in phenotype expression and genotype frequency in Paramecium microcosms
Evolutionary Rescue (ER) occurs when populations, which have declined due to rapid environmental change, recover through genetic adaptation. The success of this process and the evolutionary trajectory of the population strongly depend on the rate of environmental change. Here we investigated how different rates of temperature increase (from 23°C to 32°C) affect population persistence and evolutionary change in experimental microcosms of the protozoan Paramecium caudatum. Consistent with theory on ER, we found that those populations experiencing the slowest rate of temperature increase were the least likely to become extinct and tended to be the best adapted to the new temperature environment. All high-temperature populations were more tolerant to severe heat stress (35°C, 37°C), indicating a common mechanism of heat protection. High-temperature populations also had superior growth rates at optimum temperatures, leading to the absence of a pattern of local adaptation to control (23°C) and high-temperature (32°C) environments. However, high-temperature populations had reduced growth at low temperatures (5-9°C), causing a shift in the temperature niche. In part, the observed evolutionary change can be explained by selection from standing variation. Using mitochondrial markers, we found complete divergence between control and high-temperature populations in the frequencies of six initial founder genotypes. Our results confirm basic predictions of ER and illustrate how adaptation to an extreme local environment can produce positive as well as negative correlated responses to selection over the entire range of the ecological niche.
Data from: The effect of bacterial mutation rate on the evolution of CRISPR-Cas adaptive immunity
CRISPR-Cas immune systems are present in around half of bacterial genomes. Given the specificity and adaptability of this immune mechanism, it is perhaps surprising that they are not more widespread. Recent insights into the requirement for specific host factors for the function of some CRISPR-Cas subtypes, as well as the negative epistasis between CRISPR-Cas and other host genes, have shed light on potential reasons for the partial distribution of this immune strategy in bacteria. In this study, we examined how mutations in the bacterial mismatch repair system, which are frequently observed in natural and clinical isolates and cause elevated host mutation rates, influence the evolution of CRISPR-Cas–mediated immunity. We found that hosts with a high mutation rate very rarely evolved CRISPR-based immunity to phage compared to wild-type hosts. We explored the reason for this effect and found that the higher frequency at which surface mutants pre-exist in the mutator host background causes them to rapidly become the dominant phenotype under phage infection. These findings suggest that natural variation in bacterial mutation rates may, therefore, influence the distribution of CRISPR-Cas adaptive immune systems.
Data from: Mutation rate dynamics in a bacterial population reflect tension between adaptation and genetic load
Mutations are the ultimate source of heritable variation for evolution. Understanding how mutation rates themselves evolve is thus essential for quantitatively understanding many evolutionary processes. According to theory, mutation rates should be minimized for well-adapted populations living in stable environments, whereas hypermutators may evolve if conditions change. However, the long-term fate of hypermutators is unknown. Using a phylogenomic approach, we found that an adapting Escherichia coli population that first evolved a mutT hypermutator phenotype was later invaded by two independent lineages with mutY mutations that reduced genome-wide mutation rates. Applying neutral theory to synonymous substitutions, we dated the emergence of these mutations and inferred that the mutT mutation increased the point-mutation rate by ~150-fold, while the mutY mutations reduced the rate by ~40-60%, with a corresponding decrease in the genetic load. Thus, the long-term fate of the hypermutators was governed by the selective advantage arising from a reduced mutation rate as the potential for further adaptation declined.
Data from: Rate of novel host invasion affects adaptability of evolving RNA virus lineages
Although differing rates of environmental turnover should be consequential for the dynamics of adaptive change, this idea has been rarely examined outside of theory. In particular, the importance of RNA viruses in disease emergence warrants experiments testing how differing rates of novel host invasion may impact the ability of viruses to adaptively shift onto a novel host. To test whether the rate of environmental turnover influences adaptation, we experimentally evolved 144 Sindbis virus lineages in replicated tissue-culture environments, which transitioned from being dominated by a permissive host cell type to a novel host cell type. The rate at which the novel host 'invaded' the environment varied by treatment. The fitness (growth rate) of evolved virus populations was measured on each host type, and molecular substitutions were mapped via whole genome consensus sequencing. Results showed that virus populations more consistently reached high fitness levels on the novel host when the novel host 'invaded' the environment more gradually, and gradual invasion resulted in less variable genomic outcomes. Moreover, virus populations that experienced a rapid shift onto the novel host converged upon different genotypes than populations that experienced a gradual shift onto the novel host, suggesting a strong effect of historical contingency.
Data from: Overestimation of the adaptive substitution rate in fluctuating populations
Estimating the proportion of adaptive substitutions (α) is of primary importance to uncover the determinants of adaptation in comparative genomic studies. Several methods have been proposed to estimate α from patterns polymorphism and divergence in coding sequences. However, estimators of α can be biased when the underlying assumptions are not met. Here we focus on a potential source of bias, i.e., variation through time in the long term population size (N) of the considered species. We show via simulations that ancient demographic fluctuations can generate severe overestimations of α, and this irrespective of the recent population history.
Data from: High mutation rates limit evolutionary adaptation in Escherichia coli
Mutation is fundamental to evolution, because it generates the genetic variation on which selection can act. In nature, genetic changes often increase the mutation rate in systems that range from viruses and bacteria to human tumors. Such an increase promotes the accumulation of frequent deleterious or neutral alleles, but it can also increase the chances that a population acquires rare beneficial alleles. Here, we study how up to 100-fold increases in Escherichia coli's genomic mutation rate affect adaptive evolution. To do so, we evolved multiple replicate populations of asexual E. coli strains engineered to have four different mutation rates for 3000 generations in the laboratory. We measured the ability of evolved populations to grow in their original environment and in more than 90 novel chemical environments. In addition, we subjected the populations to whole genome population sequencing. Although populations with higher mutation rates accumulated greater genetic diversity, this diversity conveyed benefits only for modestly increased mutation rates, where populations adapted faster and also thrived better than their ancestors in some novel environments. In contrast, some populations at the highest mutation rates showed reduced adaptation during evolution, and failed to thrive in all of the 90 alternative environments. In addition, they experienced a dramatic decrease in mutation rate. Our work demonstrates that the mutation rate changes the global balance between deleterious and beneficial mutational effects on fitness. In contrast to most theoretical models, our experiments suggest that this tipping point already occurs at the modest mutation rates that are found in the wild.
Data from: Evidence for locally adaptive metabolic rates among ant populations along an elevation gradient
1. As global temperatures rise, the mechanistic links between temperature, physiology and behavior will increasingly define predictions of ecological change. However, for many taxa, we currently lack consensus about how thermal performance traits vary within and across populations, and whether and how locally adaptive trait plasticity can buffer warming effects. 2. The metabolic cold adaptation hypothesis posits that cold environments (e.g. high elevations and latitudes) select for high metabolic rates (MR), even after controlling for body size differences, and that this enables high activity levels when an organism is near its cold lower thermal limits. Steep MR reaction norms are further predicted at cold temperatures to enable rapid behavioral activation with rising temperatures needed to exploit brief thermal windows suitable for performing eco-evolutionary tasks. 3. We tested these predictions by performing common garden experiments comparing thermal reaction norms of MR (from 15°C to 32°C) and behavior (from 10°C to 40°C) across populations of the ant Aphaenogaster iberica sampled from a 2 km elevation gradient in the Sierra Nevada Mountains of southern Spain. 4. As predicted, high-elevation ants had higher MR and steeper MR-temperature reaction norms. However, higher rates of energy use did not yield the predicted benefits of steeper activity-level reaction norms. 5. The evidence for locally adaptive metabolic physiology only became apparent at intermediate temperatures, highlighting the importance of testing thermal performance hypotheses across thermal gradients, rather than focusing only on performance at thermal limits (i.e. critical thermal values) 6. The partial support for the metabolic cold adaptation hypothesis highlights that while organisms likely show a wealth of unexplored metabolic temperature plasticity, the physiological mechanisms and eco-evolutionary tradeoffs underlying such local adaptation remain obscure.
Safety and Effectiveness Study of the Precision SCS Systems Adapted for High-Rate Spinal Cord Stimulation
ClinicalTrials.gov study NCT02093793. IPD Sharing: Not stated. Countries: 1. Publications: 0.
APPROPRIATE - Rate Adaptive Pacing Sensor
ClinicalTrials.gov study NCT00757666. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Evidence for locally adaptive metabolic rates among ant populations along an elevation gradient
Open the record for dataset details and reuse information.
Data from: Negative effects of pesticides under global warming can be counteracted by a higher degradation rate and thermal adaptation
Open the record for dataset details and reuse information.
Data from: Overdominance interacts with linkage to determine the rate of adaptation to a new optimum
Open the record for dataset details and reuse information.
Data from: Overestimation of the adaptive substitution rate in fluctuating populations
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.