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289 results for “natural variation”
Data from: Natural variation in the zinc-finger-encoding exon of Prdm9 affects hybrid sterility phenotypes in mice
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Ecology and evolution of competitive trait variation in natural phytoplankton communities under selection
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Data from: Length variation in short tandem repeats affects gene expression in natural populations of Arabidopsis thaliana
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Data from: Corralling a black swan: natural range of variation in a forest landscape driven by rare, extreme events
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A modified fluctuation assay reveals a natural mutator phenotype that drives mutation spectrum variation within Saccharomyces cerevisiae
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Natural and anthropogenic sources of habitat variation influence exploration behaviour, stress response, and brain morphology in a coastal fish
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Natural selection shapes variation in genome-wide recombination rate in Drosophila pseudoobscura
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Extreme natural size variation in both sexes of a sexually cannibalistic mantidfly
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Data from: Using controlled subsurface releases to investigate the effect of leak variation on above-ground natural gas detection
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Natural variation in a cortex/epidermis-specific transcription factor bZIP89 determines lateral root development and drought resilience in maize
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Data from: Nature and significance of intraspecific variation in the early Cambrian oryctocephalid trilobite Oryctocephalites palmeri Sundberg and McCollum, 1997
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Data from: Variation in DNA methylation transmissibility, genetic heterogeneity and fecundity-related traits in natural populations of the perennial herb Helleborus foetidus
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Origin of the natural variation in the storage of dietary carotenoids in freshwater amphipod crustaceans
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Natural variation in root exudate composition in the genetically structured Arabidopsis thaliana in the Iberian Peninsula
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Supplementary dataset to "A new genome allows the identification of genes associated with natural variation in aluminium tolerance in Brachiaria grasses"
<p>SUPPLEMENTARY DATASETS TO:</p> <p><strong>A new genome allows the identification of genes associated with natural variation in aluminium tolerance in <em>Brachiaria </em>grasses</strong></p> <ul> <li><strong>Supplementary File 1:</strong> Cumulative root length (RL), root biomass (RB), and root tip diameter (RD) during Al<sup>3+</sup> stress (A) and control (C) conditions, and the ratio (R) between stress and control values, in the interspecific progeny between CIAT 606 and BXR 44-02.</li> <li><strong>Supplementary File 2: </strong>Gene annotation in GFF3 format.</li> <li><strong>Supplementary File 3: </strong>Functional annotation of the genes, including GO terms and homologous proteins in NCBI nr database, Uniprot, <em>A. thaliana</em>, rice, <em>P. halli</em>, <em>S. italica</em> and <em>S. viridis</em><em>.</em></li> <li><strong>Supplementary File 4: </strong>Assignment of the proteins in the Poaceae family to eggNOG orthologous groups to identify shared clusters of proteins among these species.</li> <li><strong>Supplementary File 5:</strong> Anchoring 21,145 <em>Brachiaria ruziziensis</em> scaffolds longer than 10 Kbp or with at least one annotated gene (533.9 Mbp) in <em>S. italica </em>nine chromosomes.</li> <li><strong>Supplementary File 6:</strong> Chromosomal position of the 41,974 transcripts in <em>Brachiaria ruziziensis</em> based on the synteny with the <em>S. italica</em> genome. In BED5 format.</li> <li><strong>Supplementary File 7: </strong>Genetic map with 4,427 markers placed at LOD 10 in 18 linkage groups, including the position of each marker in the genetic map and genome assembly.</li> <li><strong>Supplementary File 8:</strong> Functional annotation of the 84 DE genes within QTLs.</li> <li><strong>Supplementary File 9:</strong> Enrichment analysis of the GO terms (full ontology) over-represented among DE genes in each species with the biological processes (BP) and molecular functions (MF).</li> <li><strong>Supplementary File 10:</strong> Enrichment analysis of the GO SLIM terms (reduced ontology) over-represented among DE genes in each species with the biological processes (BP) and molecular functions (MF).</li> </ul> <p> </p> <ul> </ul> <p>Margaret Worthington<sup>1#</sup>, Juan Guillermo Perez<sup>1</sup>, Saule Mussurova<sup>2</sup>, Alexander Silva-Cordoba<sup>1</sup>, Valheria Castiblanco<sup>1</sup>, Juan Andres Cardoso Arango<sup>1</sup>, Charlotte Jones<sup>3</sup>, Narcis Fernandez-Fuentes<sup>3</sup>, Leif Skot<sup>3</sup>, Sarah Dyer<sup>2&</sup>, Joe Tohme<sup>1</sup>, Federica Di Palma<sup>2</sup>, Jacobo Arango<sup>1</sup>, Ian Armstead<sup>3</sup>, Jose J De Vega<sup>2</sup></p> <p> </p> <p>1. International Center for Tropical Agriculture (CIAT), A.A. 6713, Cali, Colombia.</p> <p>2. Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK.</p> <p>3. Institute of Biological, Environmental and Rural Sciences (IBERS), Aberystwyth University, Aberystwyth, UK.</p> <p> </p> <p> </p>
Dataset - A complex network of additive and epistatic quantitative trait loci underlies natural variation of Arabidopsis thaliana quantitative disease resistance to Ralstonia solanacearum under heat stress
<p>Plant immunity is often negatively impacted by heat stress. However, the underlying molecular mechanisms remain poorly characterized. Based on a genome-wide association mapping approach, this study aims to identify in <em>Arabidopsis thaliana</em> the genetic bases of robust resistance mechanisms to the devastating pathogen<em> Ralstonia solanacearum</em> under heat stress. A local mapping population was phenotyped against the <em>R. solanacearum</em> GMI1000 strain at 27 and 30 °C. To obtain a precise description of the genetic architecture underlying natural variation of quantitative disease resistance (QDR), we applied a genome-wide local score analysis. Alongside an extensive genetic variation found in this local population at both temperatures, we observed a playful dynamics of quantitative trait loci along the infection stages. In addition, a complex genetic network of interacting loci could be detected at 30 °C. As a first step to investigate the underlying molecular mechanisms, the atypical meiotic cyclin <em>SOLO DANCERS</em> gene was validated by a reverse genetic approach as involved in QDR to <em>R. solanacearum </em>at 30 °C. In the context of climate change, the complex genetic architecture underlying QDR under heat stress in a local mapping population revealed candidate genes with diverse molecular functions.</p>
Behavioral variation in natural contests: integrating plasticity and personality
<p>Animals often interact aggressively when competing over limited resources. Aggressive decisions can be complex, and may result from multiple sources of behavioral variation. The outcome of contests may be explained through contest theory and personality, by considering conjointly plasticity and individual consistency. This integrative approach also allows investigating individual differences in responsiveness to environmental changes. Here we observed multiple agonistic interactions occurring among eastern chipmunks (Tamias striatus) competing for food resources supplied at different distances from their burrows. Using an individual reaction norm approach, we found that the probability of winning a contest depended on an individual's own intrinsic characteristics (mass, age, but not sex) but was also adjusted to characteristics of its opponents. Winning a contest also depended on extrinsic environmental characteristics such as distance to the contestants' burrows, but not the order of arrival at the feeding patch. We found consistent individual differences in the probability of winning, potentially related to differences in aggressiveness and territoriality. We also found that individuals differed in their plasticity level in response to changes in different characteristics of their social and physical environments. Plasticity, personality and individual differences in responsiveness may thus all play a role in predicting contest outcome and in the evolution of animal contests.</p>
Data from: Genetic variation in resistance and fecundity tolerance in a natural host-pathogen interaction
Individuals vary in their ability to defend against pathogens. Determining how natural selection maintains this variation is often difficult, in part because there are multiple ways that organisms defend themselves against pathogens. One important distinction is between mechanisms of resistance that fight off infection, and mechanisms of tolerance that limit the impact of infection on host fitness without influencing pathogen growth. Theory predicts variation among genotypes in resistance, but not necessarily in tolerance. Here, we study variation among pea aphid (Acyrthosiphon pisum) genotypes in defense against the fungal pathogen Pandora neoaphidis. It has been well established that pea aphids can harbor symbiotic bacteria that protect them from fungal pathogens. However, it is unclear whether aphid genotypes vary in defense against Pandora in the absence of protective symbionts. We therefore measured resistance and tolerance to fungal infection in aphid lines collected without symbionts, and found variation among lines in survival and in the percent of individuals that formed a sporulating cadaver. We also found evidence of variation in tolerance to the effects of pathogen infection on host fecundity, but no variation in tolerance of pathogen-induced mortality. We discuss these findings in light of theoretical predictions about host-pathogen coevolution.
Data from: SNP-skimming: a fast approach to map loci generating quantitative variation in natural populations
Genome-wide association mapping (GWAS) is a method to estimate the contribution of segregating genetic loci to trait variation. A major challenge for applying GWAS to non-model species has been generating dense genome-wide markers that satisfy the key requirement that marker data is error-free. Here we present an approach to map loci within natural populations using inexpensive shallow genome sequencing. This 'SNP skimming' approach involves two steps: an initial genome-wide scan to identify putative targets followed by deep sequencing for confirmation of targeted loci. We apply our method to a test dataset of floral dimension variation in the plant Penstemon virgatus, a member of a genus that has experienced dynamic floral adaptation that reflects repeated transitions in primary pollinator. The ability to detect SNPs that generate phenotypic variation depends on population genetic factors such as population allele frequency, effect size, and epistasis as well as sampling effects contingent on missing data and genotype uncertainty. However, both simulations and the Penstemon data suggest that the most significant tests from the initial SNP skim are likely to be true positives – loci with subtle but significant quantitative effects on phenotype. We discuss the promise and limitations of this method and consider optimal experimental design for a given sequencing effort. Simulations demonstrate that sampling a larger number of individual at the expense of average read depth per individual maximizes the power to detect loci.
Data from: Tropical tree height and crown allometries for the Barro Colorado Nature Monument, Panama: a comparison of alternative hierarchical models incorporating interspecific variation in relation to life history traits
Tree allometric relationships are widely employed for estimating forest biomass and production and are basic building blocks of dynamic vegetation models. In tropical forests, allometric relationships are often modeled by fitting scale-invariant power functions to pooled data from multiple species, an approach that fails to capture changes in scaling during ontogeny and physical limits to maximum tree size and that ignores interspecific differences in allometry. Here, we analyzed allometric relationships of tree height (9884 individuals) and crown area (2425) with trunk diameter for 162 species from the Barro Colorado Nature Monument, Panama. We fit nonlinear, hierarchical models informed by species traits – wood density, mean sapling growth, or sapling mortality – and assessed the performance of three alternative functional forms: the scale-invariant power function and the saturating Weibull and generalized Michaelis–Menten (gMM) functions. The relationship of tree height with trunk diameter was best fit by a saturating gMM model in which variation in allometric parameters was related to interspecific differences in sapling growth rates, a measure of regeneration light demand. Light-demanding species attained taller heights at comparatively smaller diameters as juveniles and had shorter asymptotic heights at larger diameters as adults. The relationship of crown area with trunk diameter was best fit by a power function model incorporating a weak positive relationship between crown area and species-specific wood density. The use of saturating functional forms and the incorporation of functional traits in tree allometric models is a promising approach for improving estimates of forest biomass and productivity. Our results provide an improved basis for parameterizing tropical plant functional types in vegetation models.
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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.