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193 results for “trait analysis”
Data from: Assessing the vulnerability of Africa's freshwater fishes to climate change: a continent-wide trait-based analysis
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Data from: Independent and interactive effects of plant genotype and environment on plant traits and insect herbivore performance: a meta-analysis with Salicaceae
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Genetic variation, genotypic and phenotypic correlation, heritability, and path coefficient analysis of yield and yield related traits in bread wheat (Triticum aestivum L.) varieties at Gitilo Dale, western Ethiopia
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Data from: Seed dispersal by ungulates as an ecological filter: a trait-based meta-analysis
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Data from: Genetic heterogeneity underlying variation in a locally adaptive clinal trait in Pinus sylvestris revealed by a Bayesian multipopulation analysis
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Data from: Trait-based functional dietary analysis provides a better insight into the foraging ecology of bats
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Data from: Ecology drives natural variation in an extreme antipredator trait: a cost-benefits analysis integrating modeling and field data
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Data from: Multiple-trait genome-wide association study based on principal component analysis for residual covariance matrix
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Data from: A meta-analysis of whole genome duplication and the effects on flowering traits in plants
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Data from: Genome analysis reveals genetic admixture and signature of selection for productivity and environmental traits in Iraqi cattle
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Data and scripts from: Exploratory analysis of multi-trait coadaptations in the light of population history
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Analysis of independent cohorts of outbred CFW mice reveals novel loci for behavioral and physiological traits and identifies factors determining reproducibility
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Data from: CLIP test: a new fast, simple and powerful method to distinguish between linked or pleiotropic quantitative trait loci in linkage disequilibria analysis
An important question arises when mapping quantitative trait loci (QTLs) for genetically correlated traits: is the correlation due to pleiotropy (a single QTL affecting more than one trait) and/or close linkage (different QTLs that are physically close to each other and influence the traits)? In this article, we propose the Close Linkage versus Pleiotropism (CLIP) test, a fast, simple and powerful method to distinguish between these two situations. The CLIP test is based on the comparison of the square of the observed correlation between a combination of apparent effects at the marker level to the minimal value it can take under the pleiotropic assumption. A simulation study was performed to estimate the power and alpha risk of the CLIP test and compare it to a test that evaluated whether the confidence intervals of the two QTLs overlapped or not (CI test). On average, the CLIP test showed a higher power (68%) to detect close-linked QTLs than the CI test (43%) and a same alpha risk (4%).
Data from: Genome-wide association analysis for blood lipid traits measured in three pig populations revealed a substantial level of genetic heterogeneity
Serum lipids are associated with myocardial infarction and cardiovascular disease in humans. Here we dissected the genetic architecture of blood lipid traits by applying genome-wide association studies (GWAS) in 1,256 pigs from Laiwu, Erhualian and Duroc × (Landrace × Yorkshire) populations, and a meta-analysis of GWAS in more than 2,400 pigs from five diverse populations. A total of 22 genomic loci surpassing the suggestive significance level were detected on 11 pig chromosomes (SSC) for six blood lipid traits. Meta-analysis of GWAS identified 5 novel loci associated with blood lipid traits. Comparison of GWAS loci across the tested populations revealed a substantial level of genetic heterogeneity for porcine blood lipid levels. We further evaluated the causality of nine polymorphisms nearby or within the APOB gene on SSC3 for serum LDL-C and TC levels. Of the 9 polymorphisms, an indel showed the most significant association with LDL-C and TC in Laiwu pigs. But the significant association was not identified in the White Duroc × Erhualian F2 resource population, in which the QTL for LDL-C and TC was also detected on SSC3. This indicates that population-specific signals may exist for the SSC3 QTL. Further investigations are warranted to validate this assumption.
Data from: An SNP-based second-generation genetic map of Daphnia magna and its application to QTL analysis of phenotypic traits
Background: Although Daphnia is increasingly recognized as a model for ecological genomics and biomedical research, there is, as of yet, no high-resolution genetic map for the genus. Such a map would provide an important tool for mapping phenotypes and assembling the genome. Here we estimate the genome size of Daphnia magna and describe the construction of an SNP array based linkage map. We then test the suitability of the map for life history and behavioural trait mapping. The two parent genotypes used to produce the map derived from D. magna populations with and without fish predation, respectively and are therefore expected to show divergent behaviour and life-histories. Results: Using flow cytometry we estimated the genome size of D. magna to be about 238 mb. We developed an SNP array tailored to type SNPs in a D. magna F2 panel and used it to construct a D. magna linkage map, which included 1,324 informative markers. The map produced ten linkage groups ranging from 108.9 to 203.6 cM, with an average distance between markers of 1.13 cM and a total map length of 1,483.6 cM (Kosambi corrected). The physical length per cM is estimated to be 160 kb. Mapping infertility genes, life history traits and behavioural traits on this map revealed several significant QTL peaks and showed a complex pattern of underlying genetics, with different traits showing strongly different genetic architectures. Conclusions: The new linkage map of D. magna constructed here allowed us to characterize genetic differences among parent genotypes from populations with ecological differences. The QTL effect plots are partially consistent with our expectation of local adaptation under contrasting predation regimes. Furthermore, the new genetic map will be an important tool for the Daphnia research community and will contribute to the physical map of the D. magna genome project and the further mapping of phenotypic traits. The clones used to produce the linkage map are maintained in a stock collection and can be used for mapping QTLs of traits that show variance among the F2 clones.
Data from: Identification of X-linked quantitative trait loci affecting cold tolerance in Drosophila melanogaster and fine-mapping by selective sweep analysis
Drosophila melanogaster is a cosmopolitan species that colonizes a great variety of environments. One trait that shows abundant evidence for naturally segregating genetic variance in different populations of D. melanogaster is cold tolerance. Previous work has found quantitative trait loci (QTL) exclusively on the second and the third chromosomes. To gain insight into the genetic architecture of cold tolerance on the X chromosome and to compare the results with our analyses of selective sweeps, a mapping population was derived from a cross between substitution lines that solely differed in the origin of their X chromosome: one originates from a European inbred line, the other one from an African inbred line. We found a total of six QTL for cold tolerance factors on the X chromosome of D. melanogaster. Although the composite interval mapping revealed slightly different QTL profiles between sexes, a coherent model suggests that most QTL overlapped between sexes and each explained around 5-14% of the genetic variance (which may be slightly overestimated). The allelic effects were largely additive, but we also detected two significant interactions. Taken together, this provides evidence for multiple QTL that are spread along the entire X chromosome and whose effects range from low to intermediate. One detected transgressive QTL influences cold tolerance in different ways for the two sexes. While females benefit from the European allele increasing their cold tolerance, males tend to do better with the African allele. Finally, using selective sweep mapping the candidate gene CG16700 for cold tolerance co-localizing with a QTL was identified.
Data from: Genome-wide association analysis of stalk biomass and anatomical traits in maize
Background: Maize stover is an important source of crop residues and a promising sustainable energy source in the United States. Stalk is the main component of stover, representing about half of stover dry weight. Characterization of genetic determinants of stalk traits provide a foundation to optimize maize stover as a biofuel feedstock. We investigated maize natural genetic variation in genome-wide association studies (GWAS) to detect candidate genes associated with traits related to stalk biomass (stalk diameter and plant height) and stalk anatomy (rind thickness, vascular bundle density and area). Results: Using a panel of 942 diverse inbred lines, 899,784 RNA-Seq derived single nucleotide polymorphism (SNP) markers were identified. Stalk traits were measured on 800 members of the panel in replicated field trials across years. GWAS revealed 16 candidate genes associated with four stalk traits. Most of the detected candidate genes were involved in fundamental cellular functions, such as regulation of gene expression and cell cycle progression. Two of the regulatory genes (Zmm22 and an ortholog of Fpa) that were associated with plant height were previously shown to be involved in regulating the vegetative to floral transition. The association of Zmm22 with plant height was confirmed using a transgenic approach. Transgenic lines with increased expression of Zmm22 showed a significant decrease in plant height as well as tassel branch number, indicating a pleiotropic effect of Zmm22. Conclusion: Substantial heritable variation was observed in the association panel for stalk traits, indicating a large potential for improving useful stalk traits in breeding programs. Genome-wide association analyses detected several candidate genes associated with multiple traits, suggesting common regulatory elements underlie various stalk traits. Results of this study provide insights into the genetic control of maize stalk anatomy and biomass.
Data from: A meta-analysis of the agents of selection on floral traits
Floral traits are hypothesized to evolve primarily in response to selection by pollinators. However, selection can also be mediated by other environmental factors. To understand the relative importance of pollinator-mediated selection and its variation among trait and pollinator types, we analyzed directional selection gradients on floral traits from experiments that manipulated the environment to identify agents of selection. Pollinator-mediated selection was stronger than selection by other biotic factors (e.g. herbivores), but similar in strength to selection by abiotic factors (e.g. soil water), providing partial support for the hypothesis that floral traits evolve primarily in response to pollinators. Pollinator-mediated selection was stronger on pollination efficiency traits than on other trait types, as expected if efficiency traits affect fitness via interactions with pollinators, but other trait types also affect fitness via other environmental factors. In addition to varying among trait types, pollinator-mediated selection varied among pollinator taxa: selection was stronger when bees, long-tongued flies, or birds were the primary visitors than when the primary visitors were Lepidoptera or multiple animal taxa. Finally, reducing pollinator access to flowers had a relatively small effect on selection on floral traits, suggesting that anthropogenic declines in pollinator populations would initially have modest effects on floral evolution.
A meta-analysis of natural selection on plant functional traits
<p>A common assumption in plant physiological ecology is that variation in functional traits reflects the adaptation of organisms to their abiotic environment. This assumption can be tested by estimating natural selection as the relationship between a functional trait and a fitness component (i.e. survival or reproduction) within a population. To understand how natural selection operates on plant functional traits, we compiled directional selection gradients (<i>β</i><span><span></span></span>), which estimate direct selection, and differentials (<i>S</i><span><span></span></span>), which estimate both direct and indirect selection, from studies conducted in manipulated and unmanipulated environments. We found that relative to manipulating biotic factors, manipulating abiotic factors had a ~5.7´ larger effect on <i>β </i><span><span></span></span>and a ~16´ larger effect on <i>S</i><span><span></span></span>, suggesting that functional traits primarily evolve in response to the abiotic environment. We found that the strength of selection on functional traits <i>(</i><span></span><i>β</i><i>)</i><span><span></span></span> did not vary with trait type, performance/fitness component, or measurement context (i.e. common garden vs. natural population). However, the direction of selection did differ between some trait types: <i>β</i><span><span></span></span> was positive for plant size traits, but negative for phenology traits. Lastly, we found that the absolute value of selection differentials (<span></span><i>S</i><span><span></span></span>) was ~2´ larger than the absolute value of selection gradients (<span></span><i>β</i><span><span></span></span>), indicating that there was indirect selection on functional traits. Overall, our meta-analysis illustrates that natural selection on plant functional traits is common, and that estimates of selection on these traits in experimentally manipulated environments can be used effectively to test hypotheses about the causes of adaptation.</p>
Data from: Living in a high CO2 world: a global meta-analysis shows multiple trait-mediated responses of fish to ocean acidification
Understanding how marine organisms will be affected by global change is of primary importance to ensure ecosystem functioning and nature contributions to people. This study meets the call for addressing how life-history traits mediate effects of ocean acidification on fish. We built a database of overall and trait-mediated responses of teleost fish to future CO2 levels by searching the scientific literature. Using a meta-analytical approach, we investigated the effects of projected CO2 levels by IPCC for 2050-2070 and 2100 on fish eco-physiology and behavior from 320 contrasts on 42 species, stemming from polar to tropical regions. Moreover, since organisms may experience a mosaic of carbonate chemistry in coastal environments (e.g. in estuaries, upwelling zones and intertidal habitats), which may have higher pCO2 values than open ocean waters, we assessed responses from additional 103 contrasts on 21 fish species using pCO2 levels well above IPCC projections. Under mid- and end-of-century CO2 emission scenarios, we found multiple CO2-dose dependent effects on calcification, resting metabolic rate, yolk, behavioral performances, along with increased predation risk and decreased foraging, particularly for larvae. Importantly, many of the traits considered will not confer fish tolerance to elevated CO2 and far-reaching ecological consequences on fish population replenishment and community structure will likely occur. Extreme CO2 levels well above IPCC projections showed effects on fish mortality and calcification, while growth, metabolism and yolk were unaffected. CO2 exposures in short-term experiments increased fish mortality, which in turn decreased in longer-term exposures. Whatever the elevated CO2 levels considered, some key biological processes (e.g. reproduction, development, habitat choice) resulted critically understudied. Fish are an important resource for livelihoods in coastal communities and a key component for stability of marine ecosystems. Given the multiple trait-mediated effects evidenced here, we stress the need to fill the knowledge gap on important eco-physiological processes and to expand the number and duration of ocean acidification studies to multi-generational, multiple stressor (e.g. warming, hypoxia, fishing) and species interactions experiments to better elucidate complex ecosystem-level changes and how these changes might alter provisioning of ecosystem services.
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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.