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.
168
datasets available to search
ShareScore release 0.9.0
Dataset results
168 results for “evolutionary genetics”
Data from: Genetic divergence between two phenotypically distinct bottlenose dolphin ecotypes suggests separate evolutionary trajectories
Open the record for dataset details and reuse information.
Data from: The power of evolutionary rescue is constrained by genetic load
Open the record for dataset details and reuse information.
Data from: Evolutionary epidemiology of schistosomiasis: linking parasite genetics with disease phenotype in humans
Open the record for dataset details and reuse information.
The evolutionary genetics of paternal care: how good genes and extra-pair copulation affect the trade-off between paternal care and mating success
Open the record for dataset details and reuse information.
Supplementary material 1 from: Patterson BD, Webala PW, Lavery TH, Agwanda BR, Goodman SM, Kerbis Peterhans JC, Demos TC (2020) Evolutionary relationships and population genetics of the Afrotropical leaf-nosed bats (Chiroptera, Hipposideridae). ZooKeys 929: 117-161. https://doi.org/10.3897/zookeys.929.50240
Figure S1. Geographic distribution of voucher specimens used in this analysis
Figure 2 from: Patterson BD, Webala PW, Lavery TH, Agwanda BR, Goodman SM, Kerbis Peterhans JC, Demos TC (2020) Evolutionary relationships and population genetics of the Afrotropical leaf-nosed bats (Chiroptera, Hipposideridae). ZooKeys 929: 117-161. https://doi.org/10.3897/zookeys.929.50240
Figure 2 Parts A and B. Phylogeny of Hipposideridae based on Bayesian analysis of 303 cyt-b sequences. Colored lines denote well supported clades and symbols denote nodal support: red circles, BS ≥ 70%, PP ≥ 0.95; black circles BS ≥ 70%, PP ≤ 0.95; open circles BS ≤ 70%, PP ≥ 0.95.
Figure 1 from: Patterson BD, Webala PW, Lavery TH, Agwanda BR, Goodman SM, Kerbis Peterhans JC, Demos TC (2020) Evolutionary relationships and population genetics of the Afrotropical leaf-nosed bats (Chiroptera, Hipposideridae). ZooKeys 929: 117-161. https://doi.org/10.3897/zookeys.929.50240
Figure 1 Type localities for Afrotropical hipposiderids: Doryrhina, blue symbols; Hipposideros, white symbols; Macronycteris, black symbols. Stars denote valid species, whereas circles indicate taxa considered as subspecies or synonyms. Localities are projected onto the biome map of Olson et al. (2001). Taxa depicted are: Hipposideros abae J. A. Allen,1917; †Hipposideros (Pseudorhinolophus) amenhotepos Gunnell, Winkler, Miller, Head, El-Barkooky, Gawad, Sanders & Gingerich, 2015; Phyllorhina angolensis Seabra, 1898; Hipposideros caffer var. aurantiaca De Beaux, 1924; Hipposideros beatus K. Andersen, 1906; †Hipposideros besaoka Samonds, 2007; Phyllorrhina bicornis Heuglin, 1861; Hipposideros braima Monard, 1939; Hipposideros caffer Sundevall, 1846; Phyllorhina caffra Peters, 1852; Hipposideros camerunensis Eisentraut, 1956; Hipposideros caffer centralis K. Andersen, 1906; Rhinolophus Commersonii É. Geoffroy, 1813; Hipposideros cryptovalorona Goodman, Schoeman, Rakotoarivelo & Willows-Munro, 2016; Hipposideros curtus G. M. Allen, 1921; Phyllorrhina cyclops Temminck, 1853; Phyllorrhina fuliginosa Temminck, 1853; Hipposideros gigas gambiensis K. Andersen, 1906; Rhinolophus gigas Wagner, 1845; Phyllorrhina gracilis Peters, 1852; Hipposideros caffer guineensis K. Andersen, 1906; Hipposideros jonesi Hayman, 1947; †Hipposideros kaumbului Wesselman, 1984; Hipposideros lamottei Brosset, 1985; Hipposideros langi J. A. Allen, 1917; Hipposideros marisae Aellen, 1954; Phyllorhina Commersoni, var. marungensis Noack, 1887; Hipposideros beatus maximus Verschuren, 1957; Phyllorrhina megalotis Heuglin, 1861; Rhinolophus micaceus de Winton, 1897; HipposiderosCommersoni mostellum Thomas, 1904; Hipposideros nanus J. A. Allen, 1917; Hipposideros gigas niangarae J. A. Allen, 1917; Hipposideros caffer niapu J. A. Allen, 1917; Phyllorrhina rubra Noack, 1893; Hipposideros sandersoni Sanderson, 1937; Hipposideros tephrus Cabrera, 1906; Phyllorhina Commersoni, var. thomensis Bocage, 1891; Hipposideros gigas viegasi Monard, 1939; Phyllorhina vittata Peters, 1852.
GECCO Industrial Challenge 2015 Dataset: A heating system dataset for the 'Recovering missing information in heating system operating data' competition at the Genetic and Evolutionary Computation Conference 2015, Madrid, Spain
<p>Dataset of the 'Industrial Challenge: Recovering missing information in heating system operating data' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 11th-15th 2015, Madrid, Spain</p> <p> </p> <p>The task of the competition was to recover (impute) missing information in heating system operation time series'.</p> <p> </p> <p>Included in zenodo: </p> <p>- dataset of heating system operational time series with missing values</p> <p>- additional material and descriptions provided for the competition</p> <p> </p> <p>The competition was organized by:</p> <p>M. Friese, A. Fischbach, C. Schlitt, T. Bartz-Beielstein (TH Köln)</p> <p> </p> <p>The dataset was provided by:</p> <p>Major German heating systems supplier (S. Moritz)</p> <p> </p> <p> </p> <p>Industrial Challenge: Recovering missing information in heating system operating data</p> <p> </p> <p>The Industrial Challenge will be held in the competition session at the Genetic and Evolutionary Computation Conference. It poses difficult real-world problems provided by industry partners from various fields. Highlights of the Industrial Challenge include interesting problem domains, real-world data and realistic quality measurement</p> <p>Overview</p> <p>In times of accelerating climate change and rising energy costs, increasing energy efficiency and reducing expenses becomes a high priority goal for businesses and private households alike. Modern heating systems record detailed operating data and report this data to a central system. Here, the operating data can be correlated and analyzed to detect potential optimization opportunities or anomalies like unusually high energy consumption. Due to various difficulties this data might be incomplete which makes accurate forecasting even harder.</p> <p>Goal of the GECCO 2015 Industrial Challenge is to develop capable procedures to recover missing information in heating system operating data. Adequate recovery of the missing data enables more accurate forecastings which allow for intelligent control of the heating systems, and therefore contributes to a positive energy balance and reduced expenses.</p> <p> </p> <p><strong>Submission deadline:</strong><br> June 22, 2015</p> <p><strong>Official Webpage:</strong><br> <a href="http://www.spotseven.de/gecco-challenge/gecco-challenge-2015/">www.spotseven.de/gecco-challenge/gecco-challenge-2015/</a></p> <p> </p>
GECCO Industrial Challenge 2018 Dataset: A water quality dataset for the 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' competition at the Genetic and Evolutionary Computation Conference 2018, Kyoto, Japan.
<p>Dataset of the 'Internet of Things: Online Anomaly Detection for Drinking Water Quality' competition hosted at The Genetic and Evolutionary Computation Conference (GECCO) July 15th-19th 2018, Kyoto, Japan</p> <p> </p> <p>The task of the competition was to develop an anomaly detection algorithm for a water- and environmental data set.</p> <p> </p> <p>Included in zenodo: </p> <p>- dataset of water quality data</p> <p>- additional material and descriptions provided for the competition</p> <p> </p> <p>The competition was organized by:</p> <p>F. Rehbach, M. Rebolledo, S. Moritz, S. Chandrasekaran, T. Bartz-Beielstein (TH Köln)</p> <p> </p> <p>The dataset was provided by:</p> <p>Thüringer Fernwasserversorgung and IMProvT research project</p> <p> </p> <p>GECCO Industrial Challenge: 'Internet of Things: Online Anomaly Detection for Drinking Water Quality'</p> <p>Description:</p> <p>For the 7th time in GECCO history, the SPOTSeven Lab is hosting an industrial challenge in cooperation with various industry partners. This years challenge, based on the 2017 challenge, is held in cooperation with "Thüringer Fernwasserversorgung" which provides their real-world data set. The task of this years competition is to develop an anomaly detection algorithm for the water- and environmental data set. Early identification of anomalies in water quality data is a challenging task. It is important to identify true undesirable variations in the water quality. At the same time, false alarm rates have to be very low.<br> Additionally to the competition, for the first time in GECCO history we are now able to provide the opportunity for all participants to submit 2-page algorithm descriptions for the GECCO Companion. Thus, it is now possible to create publications in a similar procedure to the Late Breaking Abstracts (LBAs) directly through competition participation!</p> <p> </p> <p>Accepted Competition Entry Abstracts<br> - Online Anomaly Detection for Drinking Water Quality Using a Multi-objective Machine Learning Approach (Victor Henrique Alves Ribeiro and Gilberto Reynoso Meza from the Pontifical Catholic University of Parana)<br> - Anomaly Detection for Drinking Water Quality via Deep BiLSTM Ensemble (Xingguo Chen, Fan Feng, Jikai Wu, and Wenyu Liu from the Nanjing University of Posts and Telecommunications and Nanjing University)<br> - Automatic vs. Manual Feature Engineering for Anomaly Detection of Drinking-Water Quality (Valerie Aenne Nicola Fehst from idatase GmbH)</p> <p>Official webpage:</p> <p><a href="http://www.spotseven.de/gecco/gecco-challenge/gecco-challenge-2018/">http://www.spotseven.de/gecco/gecco-challenge/gecco-challenge-2018/</a></p>
Genetic variation in parental effects contributes to the evolutionary potential of prey responses to predation risk
<p class="CxSpFirst">Despite the ubiquity of parental effects and their potential impact on evolutionary dynamics, their contribution to the evolution of predator-prey interactions remains poorly understood. Using quantitative genetics, here we demonstrate that parental effects substantially contribute to the evolutionary potential of larval antipredator responses in a leaf<i> </i>beetle (<em>Leptinotarsa</em> <i>decemlineata</i>). Previous research showed that larger <em>L.</em> <i>decemlineata</i> larvae elicit stronger antipredator responses, and mothers perceiving predators improved offspring responses by increasing intraclutch cannibalism –an extreme form of offspring provisioning. We now report substantial additive genetic variation underlying maternal ability to induce intraclutch cannibalism, indicating the potential of this adaptive maternal effect to evolve by natural selection. We also show that paternal size, a heritable trait, impacted larval responses to predation risk, but that larval responses themselves had little additive genetic variation. Together, these results demonstrate how larval responses to predation risk can evolve via two types of parental effects, both of which provide indirect sources of genetic variation for offspring traits.<b> </b></p>
Evolutionary rate and genetic load in an emblematic Mediterranean tree following an ancient and prolonged population collapse
Severe bottlenecks significantly diminish the amount of genetic diversity and the speed at which it accumulates (i.e. evolutionary rate). They further compromise the efficiency of natural selection to eliminate deleterious variants, which may reach fixation in the surviving populations. Consequently, expanding and adapting to new environments may pose a significant challenge when strong bottlenecks result in genetic pauperization. Herein, we surveyed the patterns of nucleotide diversity, molecular adaptation and genetic load across hundreds of loci in a circum-Mediterranean conifer (<i>Pinus pinea</i> L.) that represents one of the most extreme cases of genetic pauperization in widespread outbreeding taxa. We found very little genetic variation in both hypervariable non-coding (nuSSRs) and gene-coding loci, which translated into genetic diversity estimates one order of magnitude lower than those previously reported for pines. Such values were consistent with a strong population decline that began some ~1Ma. Comparisons with the related and partially parapatric maritime pine revealed reduced rates of adaptive evolution (<i>α</i> and <i>ω</i><sub>a</sub>) and a significant accumulation of genetic load. These did not appear to result from differences in mutation rates or linkage disequilibrium between the two species; instead they are the likely outcome of contrasting demographic histories affecting both the speed at which these taxa accumulate genetic diversity, and the global efficacy of selection. Future studies, and programs for conservation and management, should thus start testing for the effects of genetic load on fitness and integrating such effects into predictive models.
Ancestral genetic variation in phenotypic plasticity underlies rapid evolutionary changes in resurrected populations of waterfleas
<p>The role that phenotypic plasticity plays in adaptive evolution has been debated for decades. This is because the strength of natural selection is dependent upon the direction and magnitude of phenotypic responses to environmental signals. Therefore, the connection between plasticity and adaptation will depend on the patterns of plasticity harbored by ancestral populations prior to a change in the environment. Yet, few studies have directly assessed ancestral variation in plasticity and tracked phenotypic changes over time. Here we resurrected historic propagules of <i>Daphnia</i> spanning multiple species and lakes in Wisconsin following the invasion and proliferation of a novel predator (spiny waterflea, <i>Bythotrephes</i> <i>longimanus</i>)<i>. </i>This approach revealed extensive genetic variation in predator-induced plasticity in ancestral populations of <i>Daphnia</i>. It is unlikely that the standing patterns of plasticity shielded <i>Daphnia</i> from selection to permit long-term coexistence with a novel predator. Instead, this variation in plasticity provided the raw materials for <i>Bythotrephes</i>-mediated selection to drive rapid shifts in <i>Daphnia</i> behavior and life history. Surprisingly, there was little evidence for the evolution of trait plasticity as genetic variation in plasticity was maintained in the face of a novel predator. Such results provide new insights into the link between plasticity and adaptation and highlight the importance of quantifying genetic variation in plasticity when evaluating the drivers of evolutionary change in the wild. </p>
Evolutionary stability, landscape heterogeneity, and human land-usage shape population genetic connectivity in the Cape Floristic Region biodiversity hotspot
<p>As human-induced change eliminates natural habitats, it impacts genetic diversity and population connectivity for local biodiversity. The South African Cape Floristic Region (CFR) is the most diverse extratropical area for plant biodiversity, and much of its habitat is protected as a UNESCO World Heritage site. There has long been great interest in explaining the underlying factors driving this unique diversity, especially as much of the CFR is endangered by urbanization and other anthropogenic activity. Here, we use a population and landscape genetic analysis of SNP data from the CFR endemic plant <i>Leucadendron salignum</i> or "common sunshine conebush" as a model to address the evolutionary and environmental factors shaping the vast CFR diversity. We found that high population structure, along with relatively deeper and older genealogies, are characteristic of the southwestern CFR, whereas, low population structure and more recent lineage coalescence depicts the eastern CFR. Population network analyses show genetic connectivity is facilitated in areas of lower elevation and higher seasonal precipitation. These population genetic signatures corroborate CFR species-level patterns consistent with high Pleistocene biome stability and landscape heterogeneity in the southwest, but with coincident instability in the east. Finally, we also find evidence of human land-usage as a significant gene flow barrier, especially in severely-threatened lowlands where genetic connectivity has been historically the highest. These results help identify areas where conservation plans can prioritize protecting high genetic diversity threatened by contemporary human activities within this unique cultural UNESCO site.</p>
Data from: Evolutionary rates for multivariate traits: the role of selection and genetic variation
A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders' equation, which predicts evolutionary change for a suite of phenotypic traits as a product of directional selection acting on them (β) and the genetic variance–covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and β to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are, in part, due to genetic architecture. We find some evidence that sexually selected traits exhibit faster rates of evolution compared with life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G, we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.
Data from: A test of genetic models for the evolutionary maintenance of same-sex sexual behaviour
The evolutionary maintenance of same-sex sexual behaviour (SSB) has received increasing attention because it is perceived to be an evolutionary paradox. The genetic basis of SSB is almost wholly unknown in non-human animals, though this is key to understanding its persistence. Recent theoretical work has yielded broadly applicable predictions centred on two genetic models for SSB: overdominance and sexual antagonism. Using Drosophila melanogaster, we assayed natural genetic variation for male SSB and empirically tested predictions about the mode of inheritance and fitness consequences of alleles influencing its expression. We screened 50 inbred lines derived from a wild population for male–male courtship and copulation behaviour, and examined crosses between the lines for evidence of overdominance and antagonistic fecundity selection. Consistent variation among lines revealed heritable genetic variation for SSB, but the nature of the genetic variation was complex. Phenotypic and fitness variation was consistent with expectations under overdominance, although predictions of the sexual antagonism model were also supported. We found an unexpected and strong paternal effect on the expression of SSB, suggesting possible Y-linkage of the trait. Our results inform evolutionary genetic mechanisms that might maintain low but persistently observed levels of male SSB in D. melanogaster, but highlight a need for broader taxonomic representation in studies of its evolutionary causes.
Data from: Evolutionary history and genetic parallelism affect correlated responses to evolution
We investigated the relationship between genomic and phenotypic evolution among replicate populations of Escherichia coli evolved for 1000 generations in four different environments. By re-sequencing evolved genomes, we identified parallel changes in genes encoding transcription regulators within and between environments. Depending on both the environment and the altered gene, genetic parallelism at the gene level involved mutations that either repeatedly affected identical codons or domains or were more widely distributed within the relevant genes. Evolved clones were characterized by parallel phenotypic changes in their respective evolution environments but also in the three alternative environments. Phenotypic parallelism for both traits was high for clones that evolved in the same environment, even in the absence of genetic parallelism. By contrast, clones that evolved in different environments revealed a higher parallelism in correlated responses when they shared mutated genes. Altogether, this work shows that after an environmental change or the colonization of a new habitat, similar ecological performances might be expected for individuals that shared mutated genes or experienced similar past selective pressures.
Data from: A dedicated target capture approach reveals variable genetic markers across micro- and macro-evolutionary time scales in palms
Understanding the genetics of biological diversification across micro- and macro-evolutionary time scales is a vibrant field of research for molecular ecologists as rapid advances in sequencing technologies promise to overcome former limitations. In palms, an emblematic, economically and ecologically important plant family with high diversity in the tropics, studies of diversification at the population and species levels are still hampered by a lack of genomic markers suitable for the genotyping of large numbers of recently diverged taxa. To fill this gap, we used a whole genome sequencing approach to develop target sequencing for molecular markers in 4,184 genome regions, including 4,051 genes and 133 non-genic putatively neutral regions. These markers were chosen to cover a wide range of evolutionary rates allowing future studies at the family, genus, species and population levels. Special emphasis was given to the avoidance of copy number variation during marker selection. In addition, a set of 149 well-known sequence regions previously used as phylogenetic markers by the palm biological research community were included in the target regions, to open the possibility to combine and jointly analyse already available data sets with genomic data to be produced with this new toolkit. The bait set was effective for species belonging to all three palm subfamilies tested (Arecoideae, Ceroxyloideae and Coryphoideae), with high mapping rates, specificity and efficiency. The number of high quality Single Nucleotide Polymorphisms (SNPs) detected at both the subfamily and population levels facilitates efficient analyses of genomic diversity across micro- and macro-evolutionary time scales.
Data from: Ploidy tug-of-war: evolutionary and genetic environments influence the rate of ploidy drive in a human fungal pathogen
Variation in baseline ploidy is seen throughout the tree of life, yet the factors that determine why one ploidy level is maintained over another remain poorly understood. Experimental evolution studies using asexual fungal microbes with manipulated ploidy levels intriguingly reveals a propensity to return to the historical baseline ploidy, a phenomenon that we term 'ploidy drive'. We evolved haploid, diploid, and polyploid strains of the human fungal pathogen Candida albicans under three different nutrient limitation environments to test whether these conditions, hypothesized to select for low ploidy levels, could counteract ploidy drive. Strains generally maintained or acquired smaller genome sizes size (measured as total nuclear DNA through flow cytometry) in minimal medium and under phosphorus depletion compared to in a complete medium, while mostly maintained or acquired increased genome sizes under nitrogen depletion. Improvements in fitness often ran counter to changes in genome size; in a number of scenarios lines that maintained their original genome size often increased in fitness more than lines that converged towards diploidy. Combined, this work demonstrates a role for both the environment and genotype in determination of the rate of ploidy drive, and highlights questions that remain about the force(s) that cause genome size variation.
Data from: The evolutionary genetics of acquisition and allocation in the wing dimorphic cricket, Gryllus firmus.
The evolutionary trajectories of trade-offs are ultimately governed by the evolution of the underlying physiological processes of the acquisition and subsequent allocation of resources. In this study, we focused directly on acquisition and allocation as traits and estimated their genetic architecture in the trade-off between flight capability and reproduction in the cricket, Gryllus firmus. To determine the evolutionary genetics of acquisition and allocation both within and between resource environments we performed a large-scale quantitative genetic breeding experiment in which families were split over several resource levels. Our findings were fourfold: 1) there was substantial genetic variance in acquisition and allocation; 2) contrary to the assumption of independence between acquisition and allocation, there was a significant genetic correlation between them; 3) the genetic covariance between acquisition and allocation was significantly different in the different food environments, 4) the trade-off, as measured by the genetic correlation between flight muscle mass and ovary mass, was only significant in the food restriction environments. However, when measured directly as the genetic correlation between reproductive allocation and flight allocation, we found a consistent strong negative genetic correlation, demonstrating that when allocation is measured independently of acquisition we find evidence for the trade-off.
Data from: Rate of evolutionary change in cranial morphology of the marsupial genus Monodelphis is constrained by the availability of additive genetic variation
We tested the hypothesis that the rate of marsupial cranial evolution is dependent on the distribution of genetic variation in multivariate space. To do so, we carried out a genetic analysis of cranial morphological variation in laboratory strains of Monodelphis domestica and used estimates of genetic covariation to analyze the morphological diversification of the Monodelphis brevicaudata species group. We found that within-species genetic variation is concentrated in only a few axes of the morphospace and that this strong genetic covariation influenced the rate of morphological diversification of the brevicaudata group, with between-species divergence occurring fastest when occurring along the genetic line of least resistance. Accounting for the geometric distribution of genetic variation also increased our ability to detect the selective regimen underlying species diversification, with several instances of selection only being detected when genetic covariances were taken into account. Therefore, this work directly links patterns of genetic covariation among traits to macroevolutionary patterns of morphological divergence. Our findings also suggest that the limited distribution of Monodelphis species in morphospace is the result of a complex interplay between the limited dimensionality of available genetic variation and strong stabilizing selection along two major axes of genetic variation.
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.