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359 results for “trait associations”
Genome-wide association implicates numerous genes underlying ecological trait variation in natural populations of Populus trichocarpa
In order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS). We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29 355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions. We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P < 1.7 × 10−6). Markers were found across 19 chromosomes, explained 1–13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes). The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.
Data from: Trait-fitness associations via fecundity and competition in a two-million-year-long fossil record
<p>The evolution of phenotypic traits is usually studied on generational times or across species on million-year timescales. We bridge this conceptual gap by using high density sampling of a species lineage, <em>Microporella agonistes </em>(Bryozoa, Cheilostomatida), over 2 million years of its evolutionary history, to ask if trait-fitness associations are consistent with evolutionary trait models often applied to phenotypic time series. We use average fecundity and competitive outcome as two different fitness components, where competitive outcome is a proxy for partial survival. Examining three quantitative traits in multivariate analyses, we present evidence that some traits experienced substantial selective pressures, in part controlled by past environments. A complex interplay of resource competition with an altering set of competitors and past temperatures, has contributed to the changing patterns of phenotypes within the focal species. A comparison with congeneric species living in the same regional community suggests that size traits are more temporally variable and less constrained than shape traits. Our analyses also show that while controls on phenotypes are complex and varied in time, ecological and evolutionary processes that unfold on shorter time scales are not inconsistent with macroevolutionary patterns observed on longer timescales.</p>
Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits
<p><strong>Introduction</strong></p> <p>These are the <em>Summary Level-data</em> as presented in:</p> <p>"Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits". Eur J Hum Genet. 2019 Jan 24. doi: 10.1038/s41431-018-0295-z.<em> [Epub ahead of print]</em></p> <p>If you use these data please cite the corresponding manuscript, which can be downloaded here: <a href="http://em.rdcu.be/wf/click?upn=lMZy1lernSJ7apc5DgYM8eFz0euOx0-2B13Abimi4Sb0A-3D_2NNavOiAD9A7CPFnsa04dGla3sU002fLfkDtL-2FhGlad0GuoM-2B3OlDb0C5GiEhwIvtH7ba4KKF45ipTOFodx6CqvVvoP2GQ992sPGoV9ZPWIe04tUd8-2BGWey0In0TXPII5zK-2Bfp8Wk9TpEqEcSd-2BEmywqZc8o5TW4xGPXZqmchfUH8chy3P4SEtpzHXMG1LwsIYrKfwegqTXG85RAJPr-2B21Tk9SobtpvFs0frMkJ4ekKsl33ryoZfFPk1byjQunJYn4-2BB0iqMgGs6cXv0AOgAxg-3D-3D">https://rdcu.be/bh8mu</a>. When you have any questions or comments regarding this study or these files, please contact me via:</p> <p>Jessica van Setten, PhD | <em>Department of Cardiology, University Medical Center Utrecht, Utrecht University</em> | j.vansetten [at] umcutrecht [dot] nl</p> <p> </p> <p><strong>Files and description</strong></p> <p>There are four files available:</p> <ol> <li>RR_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for RR interval</li> <li>PR_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for PR interval</li> <li>QT_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for QT interval</li> <li>QRS_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for QRS duration</li> </ol> <p>All these files have the same lay-out and are gzipped. The reference used for meta-analysis of GWAS was Genome of the Netherlands v4. </p> <ul> <li><em>SNP</em> - variantID (rsID), please note that few hundred variants do not have an rsID, but are NA instead. These can still be identified by chromosome and position.</li> <li><em>CHR</em> - chromosome numbers [1-22 and X].</li> <li><em>POS</em> - base pair position, hg19 / build37.</li> <li><em>CODED_ALLELE</em> - coded allele, <em>i.e.</em> the effect allele, as represented (and harmonized) across cohorts. Note that this is not necessarily the minor allele.</li> <li><em>NON_CODED_ALLELE</em> - the other allele, <em>i.e.</em> the non-effect allele.</li> <li><em>CODED_ALLELE_FREQ</em> - coded allele frequency, <em>i.e.</em> the effect allele frequency. Note that this is not necessarily the minor allele frequency.</li> <li><em>BETA</em> - beta from the fixed-effects model.</li> <li><em>SE </em>- standard error from the fixed-effects model.</li> <li><em>P </em>- P-value from the fixed-effects model.</li> <li><em>NEAREST_GENE</em> - the gene closest to the respective variant.</li> </ul> <p> </p>
Summary statistics - Imputed gene associations identify replicable trans-acting genes enriched in transcription pathways and complex traits
<p>Summary statistics for all trans-acting/target gene pairs tested in our manuscript.</p> <p>Preprint available: <a href="https://doi.org/10.1101/471748">https://doi.org/10.1101/471748</a></p>
Agronomic performance of cultivar mixtures and pure stands of 8 winter wheat varieties, obtained from mixture field trials in Switzerland from 2021 to 2023, together with associated functional traits measurements
<p>This dataset contains agronomic performance data for 8 Swiss winter wheat cultivars, grown in pure stands and in mixtures at 3 locations in Switzerland during 3 growing seasons (2021-2023). The dataset has been used to analyse the effects of cultivar mixtures on agronomic performance and stability, which is published in <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.eja.2024.127504" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.eja.2024.127504</a>. </p> <p>The dataset contains notably grain yield, protein content, thousand kernel weight, specific weight, and Zeleny sedimentation value, as well as functional traits measured at flowering for each mixture and pure stand plot. </p> <p>The field trials were performed under the Swiss Extenso (low input) conditions, conducted by Agroscope and DSP. </p> <h3>Methods </h3> <p> <em>Field trials </em></p> <div>Field trials were set up over the course of three growing seasons – 2020/2021, 2021/2022 and 2022/2023 – in three sites across the Swiss Central Plateau. The experimental sites were located in Changins (46°19′ N 6°14′ E, 455m a.s.l), Delley (46°55′ N 6°58′ E, 494m a.s.l) and Utzenstorf (47°97′ N 7°33′ E, 483m a.s.l.). </div> <div>Experimental communities consisted of pure stand plots, 2-cultivars mixtures, and one plot with the 8 cultivars mixed. We sowed every possible combination of 2-cultivar mixtures, amounting to a total of 28 2-cultivar mixtures treatments, to which we added the 8-cultivar mixture. Each community was grown in a plot of 7.1 m<sup>2</sup> (1.5m∗4.7m). We used a complete randomized block design, with 3 replicates, the plots being randomized at each site within each block. Sowing was performed with a small plot drill (Wintersteiger plotseed TC). Density of sowing was 350 viable seeds/m<sup>2</sup>. For the mixtures, seeds were mixed beforehand at a 2 × 50 % mass ratio for 2-cultivars mixtures and 8 × 12.5 % for the 8-cultivar mixture. We chose this method of mixing as this is what is commonly done by farmers in Switzerland. Plots were sowed mechanically each autumn and fertilized with ammonium nitrate at a rate of 140 N/ha in 3 applications (40 N/ha at tillering stage/BBCH 22–29; 60 N/ha at the beginning of stem elongation/BBCH 30–31; 40 N/ha at booting stage/BBCH 45–47). The trials were grown according to the Swiss <em>Extenso</em> scheme, i.e. without any fungicide, insecticide, and growth regulator. Weeds were regulated twice or thrice per season with the application of herbicides commonly used in Switzerland.</div> <div> </div> <div><em>Ear density</em></div> <div> </div> <div>Before harvest, we manually harvested horizontal bands of 1.5 × 0.3 square meters per plot. The location of the band was randomly chosen but we avoided plot edges (i.e. the band was located at more than 0.5 m from the lower and upper edge of each plot). We counted the heads, and obtained ear density from the head counts.</div> <div> </div> <div><em>Trait measurements </em></div> <div> </div> <div>At flowering time, we randomly sampled 6 healthy leaves per plot. We immediately wrapped this leaf in moist cotton; this was stored overnight at room temperature in open plastic bags. The following day, we removed excess surface water on the leaf and weighted it to obtain its water saturated weight. This leaf was then scanned with a flatbed scanner (Perfection V39II, Epson), oven-dried in a paper envelope at 80°C for 72 hours, and subsequently weighed again to obtain its dry weight. Leaf Dry Matter Content (LDMC) was calculated as the ratio of leaf dry mass (g) to water saturated leaf mass (g). Using the leaf scans, we measured leaf area with the image processing software ImageJ. Specific Leaf Area (SLA) was calculated as the ratio of leaf area (cm2) to leaf dry mass (g).</div> <div> </div> <div><em>Phenology and height </em></div> <div> </div> <div>For each plot, we recorded the heading date as the day of the year, in which 50 % of the ears of the plot had fully emerged from the flag leaf. Plant height was measured in each plot at BBCH 59–75, by taking the average height in centimeters from the ground to the top of five random ears, excluding awns.</div> <div> </div> <p><em>Harvest and post harvest measurements</em></p> <p>At maturity, we harvested each plot with a combine harvester (Zürn 150, Schontal-Westernhausen, Switzerland). The harvested grains were dried when needed, weighed a first time, then sorted and cleaned by air and with a sieve cleaner, and subsequently weighted again. We measured hectoliter weight (test weight, HLW, kg/hl) and water content at the plot level using a Dickey-John machine (GAC 2100). Grain yield was subsequently standardized to 15 % of humidity. Protein content (% of dry matter) was measured at the site level with a near-infrared instrument (ProxiMate™, Büchi instruments). Thousand kernel weight (TKW, g) was measured at the plot level with a Marvin seed analyzer (GTA Sensorik, Neubrandenburg, Germany). Zeleny sedimentation value was measured by the laboratory of Delley Seeds and Plants. </p> <p> </p>
Environmental context and herbivore traits mediate the strength of associational effects in a meta-analysis of crop diversity
<p>1. Crop diversification offers a promising solution to meet expanding global food demands while maintaining ecosystem services. Diversification strategies that employ mixed planting to reduce pest damage (e.g., intercropping), termed "associational effects" (AE) in the ecological literature, can decrease (associational resistance) or increase (associational susceptibility) herbivore abundance on a focal plant. While application of AE to agroecosystems typically reduces pest abundance, the range of outcomes varies widely.</p> <p>2. We conducted a meta-analysis using 272 estimates of insect herbivore abundance on crops neighbored by a conspecific or heterospecific from 44 studies undertaken on six continents. We focus on four agricultural crops well-represented from sites across the globe to test hypotheses related to understanding how herbivore traits (diet breadth, feeding guild, origin), plant traits (crop type, phylogenetic distance to neighbor), and environmental context (climate, experimental design) contribute to variation in the outcomes of associational effects.</p> <p>3. Overall, bicultures provided a strong reduction of insect abundance on the focal crop. Climate and interactions between herbivore traits, particularly diet breadth and origin, and plant traits or environmental context mediated the strength of associational effects.</p> <p>4. Bicultures provided the strongest reductions in insect abundance at low latitudes and this effect decreased at higher latitudes, but only for insects with certain traits. Abundance of generalist herbivores and globally distributed pests tended to be most strongly negatively affected by bicultures, under certain contexts, whereas specialist herbivores and native pests were less affected by neighbors.</p> <p>5. Synthesis and application. This meta-analysis highlights that variability in AE is determined in part by the interactive effects of herbivore traits and environmental context and provides guidance for incorporating beneficial ecological interactions into integrated pest management strategies.</p>
Data from: Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms
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Code for: A century of wild bee sampling: historical data and neural network analysis reveal ecological traits associated with species loss
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Data from: Trait-fitness associations via fecundity and competition in a two-million-year-long fossil record
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Data from: Wolbachia impacts microbiome diversity and fitness-associated traits for Drosophila melanogaster in a seasonally fluctuating environment
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Code and datasets associated with: A sex-linked supergene with large effects on sperm traits has little impact on reproductive traits in female zebra finches
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Homophily in social and demographic traits predict association patterns in female western and mountain gorillas
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Growth traits of a tropical timber species at Southeast Asia, Shorea macrophylla, and scripts for genome wide association study and genomic prediction
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Environmental context and herbivore traits mediate the strength of associational effects in a meta-analysis of crop diversity
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Data from: The genetic basis of traits associated with the evolution of serpentine endemism in monkeyflowers
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The evolutionary loss of paternal care is associated with shifts in female life history traits
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Data from: The effect of root-associated microbes on plant growth and chemical defence traits across two contrasted elevations,
<p>1. Ecotypic differences in plant growth and anti-herbivore defence phenotypes are determined by the complex interactions between the abiotic and the biotic environment.</p> <p>2. Root-associated microbes (RAMs) are pervasive in nature, vary over climatic gradients, and have been shown to influence the expression of multiple plant functional traits related to biomass accumulation and biotic interactions. We addressed how variation in climatic conditions between lowland and sub-alpine habitats in the Alps and RAMs can independently or interactively affect plant growth and anti-herbivore defence trait expression.</p> <p>3. To address the contribution of climate and RAMs on growth and chemical defences of high- and low-elevation Plantago major ecotypes, we performed a full-factorial reciprocal transplant field experiment at two elevations. We coupled it with plant functional trait measurements and metabolomics analyses.</p> <p>4. We found that local growing climatic conditions mostly influenced how the ecotypes grew, but we also found that the high- and low-elevation ecotypes improved biomass accumulation if in the presence of their own-elevation RAMs. Second, we found that while chemical defence expression was affected by climate, they were also more highly expressed when plants were inoculated with low elevation RAMs.</p> <p>5. Synthesis – Our research demonstrated that RAMs from contrasted elevations impact how plants grow or synthesize toxic secondary metabolites. At low elevation, where biotic interactions are stronger, RAMs enhance plant biomass accumulation and the production of toxic secondary metabolites.</p>
Trait-fitness associations do not predict within-species phenotypic evolution over 2 million years
Long-term patterns of phenotypic change are the cumulative results of tens of thousands to millions of years of evolution. Yet, empirical and theoretical studies of phenotypic selection are largely based on contemporary populations. The challenges in studying phenotypic evolution, in particular trait-fitness associations in the deep past, are barriers to linking micro- and macroevolution. Here, we capitalize on the unique opportunity offered by a marine colonial organism commonly preserved in the fossil record to investigate trait-fitness associations over 2 million years. We use the density of female polymorphs in colonies of <em>Antartothoa tongima</em> as a proxy for fecundity, a fitness component, and investigate multivariate signals of trait-fitness associations in six time intervals on the backdrop of Pleistocene climatic shifts. We detect negative trait-fitness associations for feeding polymorph (autozooid) sizes, positive associations for autozooid shape but no particular relationship between fitness and brood chamber size. In addition, we demonstrate that long-term trait patterns are explained by palaeoclimate and to a lesser extent by ecological interactions. Our analyses show that macroevolutionary outcomes of trait evolution are not a simple scaling-up from the trait-fitness associations.
A codon model for associating phenotypic traits with altered selective patterns of sequence evolution
<p>Detecting the signature of selection in coding sequences and associating it with shifts in phenotypic states can unveil genes underlying complex traits. Of the various signatures of selection exhibited at the molecular level, changes in the pattern of selection at protein coding genes have been of main interest. To this end, phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. Many of these methods rely on a pre-specified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that phenotypic transitions have occurred only at speciation events. Here we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the primate SEMG2 gene in polygynandrous species compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from a free-living to an endosymbiotic lifestyle.</p>
Data from Stranger Things: Organismal traits of two octocorals associated with singular Symbiodiniaceae in a high-latitude coral community from northern Taiwan
<p>Scrutinizing the traits of octocorals that could affect their physiological performance becomes increasingly important as several of these species are observed to become dominant on reefs pressured by the Anthropocene. In the present study, we compare the organismal traits of two branching octocorals <em>Litophyton</em><em> </em>sp. and <em>Stereonephthya</em><em> </em>sp. commonly populating in sympatry the high-latitude coral communities of northern Taiwan. Using 13 traits, we describe and compare performance traits in these two symbiotic species that we discuss in light of the association they maintain with their algal partners. <em>Litophyton</em><em> </em>sp. and <em>Stereonephthya</em><em> </em>sp. hosted <em>Durusdinium</em><em> </em>and <em>Gerakladium</em>, respectively. Both genera represent singular associations, with the latter further establishing the first solid report of <em>Gerakladium</em><em> </em>in octocorals. Traits distinguished two groups explained by the two partnerships considered. <em>Litophyton</em><em> </em>sp. associated with <em>Durusdinium</em><em> </em>had significantly higher organic matter, chlorophyll (chl) <em>a</em>, total lipid and lower chl <em>c</em>/chl <em>a</em> ratio than <em>Stereonephthya</em><em> </em>sp. associated with <em>Gerakladium</em>. The δ<sup><sup>15</sup></sup>N in the host and algae, as well as δ<sup><sup>13</sup></sup>C in the host were also higher in <em>Litophyton</em><em> </em>species. Although no significant difference was observed in the δ<sup><sup>13</sup></sup>C of the algae, <em>Litophyton</em><em> </em>sp. presented a significantly higher variance for this trait and for chl <em>a</em> content than <em>Stereonephthya</em><em> </em>species. Altogether, the traits examined suggested contrasting performances among the two octocorals. Both octocoral species clearly deviate from an autotrophic diet. <em>Litophyton</em><em> </em>sp. appears to complement its heterotrophic diet with photosynthetically acquired energy, while <em>Stereonephthya</em><em> </em>sp. tends to be more specialized and benefits relatively little from its symbiotic relationship. Our study calls for greater consideration of the individual variation in octocoral physiology and in the definition of their ecological strategies.</p> <p> </p>
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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)
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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.