Find research datasets worth reusing

opencc-by-4.0Mar 2019View details →

Elevation modulates the phenotypic responses to light of four co-occurring Pyrenean forest tree species

Data on plant water potential for seedlings of four Pyrenean tree species planted along an elevation gradient. The dataset contains three files: <ol> <li>Biomass.txt: Data on plant biomass per fraction (leaf, stem and roots) 4 years after plantation. Included variables: - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S) - Luz (factor): whether the seedling was plantes at a gap or in the understory. Two levels: gap (O) or understroy (T) - N (numeric): number of plant in that plot - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba) - Planta (factor): code to identify uniquely each plant - File (factor): code to identify uniquely each plant - GLI (num): Global Light Index, the amount of irradiance that receives each seedling - Code (factor): code to identify uniquely each plant - PLB (numeric): total plant biomass (g) - LFB (numeric): leaf biomass (g) - STB (numeric): stem biomass (g) - RTB (numeric): root biomass (g) - LMF (numeric): leaf mass fraction (LFB/PLB) - SMF (numeric): stem mass fraction (STB/PLB) - RMF (numeric): root mass fraction (RTB/PLB) - SLA (numeric): specific leaf area - H (numeric): plant height (mm) - D (numeric): plant diameter at root collar (mm) - PB2 (numeric): total plant biomass without considering leaves (g) - SF2 (numeric): stem mass fraction without considering leaves (STB/PB2) - RF2 (numeric): root mass fraction without considering leaves (RTB/PB2)</li> <li>init_biomass.txt: for biomass at the moment of plantation - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S) - N (numeric): number of plant - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba) - Planta (factor): code to identify uniquely each plant - File (numeric): code to identify uniquely each plant - PB (numeric): total plant biomass (g) - LB (numeric): leaf biomass (g) - SB (numeric): stem biomass (g) - RB (numeric): root biomass (g)</li> <li>WaterPot.txt: data on plant water potential for seedlings of four Pyrenean tree species planted along an elevation gradient during a period of intense drought - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S) - Luz (factor): whether the seedling was plantes at a gap or in the understory. Two levels: gap (O) or understroy (T) - N (numeric): number of plant  - Parcela (factor): identifier ofthe plot - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba) - Estacion (factor): the moment for the measurement. One level: September - GLI (numeric): global light index, the ration of total irradiance received by the plant at the moment of plantation - WPt (numeric): water potential (bars)</li> </ol>

opencc-by-4.0Mar 2019View details →

Datasets of Listeria monocytogenes phenotypes colected in the EJP OH LISTADAPT project

LISTADAPT datasets This repository gathered the phenotypic datasets in the LISTADAPT project (https://onehealthejp.eu/projects/jrp7-listadapt/) It includes the Listeria monocytogenes phenotypic data associated to: - biofilm formation - MIC of antimicrobials - Growth and survival in soil microsom - Growth and survival in stressed conditions (culture medium) 200 strains: 100 isolated in main RTE foods and 100 isolated from environment/farm/animals are studied. A versionning of the files is proposed, permitting to determine the  more recent files in the repository.

opencc-by-4.0Jul 2019View details →

Contemporary phenotypic change in plant quantitative traits

This is a new version of the Gorné & Díaz 2017 database (doi:10.5281/zenodo.580095). We cheked the categorization of each case, fixed of some mistakes. Also, we disambiguated the trait type moderator and add a new (mean based) measure of change. This database included studies that provide data of changes in quantitative traits of angiosperms within a known temporal framework (<300 years). The search was performed by Scopus (www.scopus.com), up to 22 December 2015 (search strings in Gorné and Díaz 2017). The database includes studies that measured intraspecific change in a quantitative trait and which report the elapsed time when the phenotypic change occurred. The studies recorded a single population before and after a change in the environment or compared two (or more) populations by measuring a quantitative trait across two situations, where one of them was a new condition of known age. Both, by measuring change directly in the field or by performing common condition experiments (e.g. common garden experiments or reciprocal transplants). Studies reporting results from artificial selection or interspecific hybridization were excluded. The environmental changes included expansions of distributional range, soil or air pollution, exposure to herbicides, changes in salinity, pH, climate, disturbance or irrigation regime, and addition or loss of species in the local community. All data available in each study were recorded, including several observations of the same species. These procedures resulted in a database containing 1716 observations from 128 studies, with changes in populations of 152 species from 34 families, in elapsed times of < 260 years, and covering a wide range of traits, lifespan, growth forms and environmental situations. All data points were categorized according to biological properties of the study system (lifespan, growth form, trait type) and methodological ones. The amount and rate of phenotypic change is expresed as the standardized mean difference Hedges g (Hedges 1981, 1982), a rate of change which is the Hedges g over the elapsed time in years, and the log-transformation of both of them. The standardized mean difference is equal to the haldane numerator, which is a standard rate of evolution (Haldane 1949; Gingerich 1993). In addition, we upgraded the Díaz and Gorné (2017) database, computing the response ratio effect size (logRR) (Hedges et al. 1999) whenever possible. The response ratio is a mean-scaled metric equal to the darwins numerator (Haldane 1949). So that we compute a rate of change similar to darwins (time expressed as years instead of million years).   contact email address: gorneld@gmail.com

opencc-by-4.0Oct 2021View details →

Vectra Polatis image of human colorectal cancer (CRC1) from: A SIMPLI (Single-cell Identification from MultiPLexed Images) approach for spatially resolved tissue phenotyping at single-cell resolution.

Two 4 µm thick serial sections were cut from CRC1 FFPE block using a microtome. The first slide was dewaxed and rehydrated before carrying out HIER with Antigen Retrieval Reagent-Basic (R&D Systems). The tissue was then blocked and incubated with the anti-CD3 antibody (Dako, Supplementary Table 2) followed by horseradish peroxidase (HRP) conjugated anti-rabbit antibody (Dako) and stained with 3,3' diaminobenzidine (DAB) substrate (Abcam) and haematoxylin. Areas with CD3+ infiltration in the proximity of the tumour invasive margin were identified by a clinical pathologist (M. R-J.) The second slide was stained with a panel of six antibodies (CD8, PD1, Ki67, PDL1, CD68, GzB, Supplementary Table 2), Opal fluorophores and 4’,6-diamidino-2-phenylindole (DAPI) on a Ventana Discovery Ultra automated staining platform (Roche). Expected expression and cellular localisation of each marker as well as fluorophore brightness were used to minimise fluorescence spillage upon antibody-Opal pairing. Following a one-hour incubation at a 60°C, the slide was subjected to an automated staining protocol on an autostainer. The protocol involved deparaffinisation (EZ-Prep solution, Roche), HIER (DISC. CC1 solution, Roche) and seven sequential rounds of: one hour incubation with the primary antibody, 12 minutes incubation with the HRP-conjugated secondary antibody (DISC. Omnimap anti-Ms HRP RUO or DISC. Omnimap anti-Rb HRP RUO, Roche) and 16 minute incubation with the Opal reactive fluorophore (Akoya Biosciences). For the last round of staining, the slide was incubated with Opal TSA-DIG reagent (Akoya Biosciences) for 12 minutes followed by Opal 780 reactive fluorophore for our hour (Akoya Biosciences). A denaturation step (100°C for 8 minutes) was introduced between each staining round in order to remove the primary and secondary antibodies from the previous cycle without disrupting the fluorescent signal. The slide was counterstained with DAPI (Akoya Biosciences) and coverslipped using ProLong Gold antifade mounting media (Thermo Fisher Scientific). The Vectra Polaris automated quantitative pathology imaging system (Akoya Biosciences) was used to scan the labelled slide. Six fields of view, within the area selected by the pathologist, were scanned at 20x and 40x magnification using appropriate exposure times and loaded into inForm{Kramer, 2018 #23} for spectral unmixing and autofluorescence isolation using the spectral libraries. After spectral unmixing and merging of six 20x fields of view for a total of >5mm2 ROI (Table 2), one single-tiff image was extracted for each marker and its intensity was rescaled from 0 to 1 with custom R scripts.

opencc-by-4.0Dec 2022View details →

Supplementary Figure 1 Gating strategy for Treg phenotype analysis.

Supplementary Figure 1. Gating strategy for Treg phenotype analysis. | Isolated and purified cells (see Methods) were analysed by flow cytometry with (A) gating performed as indicated including the exclusion of dead cells (by Live/Dead staining kit) and analysing only CD4+CD25+ double-positive cells. (B) These cells were then stained with indicated marker antibodies. The histogram quantification areas indicated by the black bars were set against control staining performed with non-specific isotype antibodies corresponding to each marker antibody.

opencc-by-4.0Jan 2023View details →

Phenotypic diversity of root architecture and genotypic variation in durum wheat under salt stress

Supplementary data consists of Principal Components values for traits detected under salt and control conditions (S1); Markers' locations onto the durum wheat reference genome associated with QTL (S2); Markers associated with genes from NCBI database (S4); PCR results and alleles distribrution

opencc-by-4.0Apr 2023View details →

Data for: Heat induces multiomic and phenotypic stress propagation in zebrafish embryos

This contains the data for the manuscript Feugere et al., "Heat induces multiomic and phenotypic stress propagation in zebrafish embryos" (2023). Zebrafish embryos were exposed to thermal stress ("TS") and stress metabolites ("SM") released by heat-stressed conspecifics in a two-way factorial design ("TSxSM"). The folder includes raw molecular data (cortisol levels, HSP70 protein levels, and gene expression acquired with LAMP and RNA-seq) and raw phenotypic data (morphology, hatching, survival, and behaviour) of zebrafish Danio rerio at 1 day and 4 days of development. The .csv files contain all quantitative data, whilst the .tab files contain the gene count data required for gene expression analysis. The data were analysed in R using the code shared in the "TSxSM2.stats.Rmd" file. The "Metadata" document provides the reader with an extensive description of each file.

opencc-by-4.0Jul 2023View details →

Phenotypic differences between interfertile Chlamydomonas species- measurements, Cellprofiler

This repository contains 2D morphology measurements from timelapse microscopy data of two interfertile Chlamydomonas algal species. The protocol to generate this data is described in the associated publication, <a href="https://doi.org/10.57844/arcadia-35f0-3e16">"Phenotypic differences between interfertile Chlamydomonas species"</a>, and summarized here. Cells were collected from agar plates and suspended in water, then left to sit overnight to encourage gamete formation. During this time, non-motile cells settled, allowing for the enrichment of motile cells in the supernatant. These enriched cells were then loaded onto agar microchambers (100 micron diameter and 40 micron depth) for imaging. We collected videos on a Nikon Ti2-E microscope equipped with a Photometrics Kinetix digital scMos camera. We performed differential interference contrast (DIC) imaging using a Plan Apo 10× 0.45 Air objective. We collected videos with a 5.1 ms exposure with acquisition every 50 ms for three minutes. We placed a red light filter [IR longpass, 610 nm (ThorLabs)] in the light path to maintain swimming behavior of cells. The procedure was standardized and repeated four times to ensure consistency. Measurements collected with Cellprofiler of timelapse data of C. reinhardtii or C. smithii cells in agar microchamber wells are shared here.<h4>Reference</h4><a href="https://doi.org/10.57844/arcadia-35f0-3e16">Essock-Burns T, Garcia III G, MacQuarrie CD, Mets DG, York R. (2023). Phenotypic differences between interfertile Chlamydomonas species</a><h4>Notes</h4>Directory and subdirectories containing csv files of measurements of algal cells segmented from images. Directory structure: experiments_csv/{experiment}/{video_length}/objects/{species}/{microchamber AKA "pool ID"}/measurements/measurementschlamy.csv"Cr" indicates Chlamydomonas reinhardtii"Cs" indicates Chlamydomonas smithii

opencc-by-4.0Sep 2023View details →

Phenotypic differences between interfertile Chlamydomonas species- focus-filtered timelapse data and measurements

This repository contains focus-filtered timelapse microscopy data of two interfertile Chlamydomonas algal species. The protocol to generate this data is described in the associated publication, <a href="https://doi.org/10.57844/arcadia-35f0-3e16">"Phenotypic differences between interfertile Chlamydomonas species"</a>, and summarized here. Cells were collected from agar plates and suspended in water, then left to sit overnight to encourage gamete formation. During this time, non-motile cells settled, allowing for the enrichment of motile cells in the supernatant. These enriched cells were then loaded onto agar microchambers (100 micron diameter and 40 micron depth) for imaging. We collected videos on a Nikon Ti2-E microscope equipped with a Photometrics Kinetix digital scMos camera. We performed differential interference contrast (DIC) imaging using a Plan Apo 10× 0.45 Air objective. We collected videos with a 5.1 ms exposure with acquisition every 50 ms for three minutes. We placed a red light filter [IR longpass, 610 nm (ThorLabs)] in the light path to maintain swimming behavior of cells. The procedure was standardized and repeated four times to ensure consistency. Focus-filtered timelapse data of C. reinhardtii or C. smithii cells in agar microchamber wells are shared here. The code for focus-filtering and collection of measurements can be found in the <a href="https://github.com/Arcadia-Science/chlamy-comparison">associated Github repository</a>.<h4>Reference</h4><a href="https://doi.org/10.57844/arcadia-35f0-3e16">Essock-Burns T, Garcia III G, MacQuarrie CD, Mets DG, York R. (2023). Phenotypic differences between interfertile Chlamydomonas species</a><h4>Notes</h4>In addition to the raw data, the dataset includes sample images that are intermediates in the image processing pipeline, as well as 2D morphology measurements of the cells in a csv file."Cr" indicates Chlamydomonas reinhardtii"Cs" indicates Chlamydomonas smithiiFrame rate: 20 frames per second (fps)Pixel size: 0.6398 microns/pixel

openCC0Mar 2023View details →

Phenotypic trait variation of Herminium monorchis in the Qinghai-Tibetan Plateau with grazing intensity and climatic conditions

This data set contains raw data supporting the research entitled “Livestock grazing outweighs climate in driving trait variation of a widespread alpine plant” (currently under peer review), which documents how phenotypic traits of a widespread herbaceous plant in the Qinghai-Tibetan Plateau, Herminium monorchis, vary with grazing intensity and environmental conditions.

openCC (other)Jun 2024View details →

Predator- and competitor-induced plasticity: How changes in foraging morphology affect phenotypic trade-offs.

Studies of phenotypic plasticity frequently demonstrate functional trade-offs between alternative phenotypes by documenting environment-specific costs and benefits. However, the functional mechanisms underlying these trade-offs are often unknown. For example, predator-induced traits typically provide superior predator resistance but slower growth, while competitor-induced traits provide better growth but inferior predator resistance. While the mechanisms underlying predator resistance have been identified, the mechanisms underlying differential growth have remained elusive. To determine whether competitor and predator environments affect individual growth by induced changes in foraging morphology, we raised wood frog tadpoles (Rana sylvatica) under a factorial combination of competitors and predators and assessed changes in mouthparts that might affect growth. In general, competitors induced relatively larger oral discs, wider beaks, and longer tooth rows, while predators induced relatively smaller oral discs, narrower beaks, and shorter tooth rows. These effects were interactive; the largest competitor-induced responses occurred under high predator density and the largest predator-induced responses occurred under low competition. Further, one of the tooth rows that commonly appeared under low predation risk was frequently absent under high predation risk. These discoveries suggest that predator and competitor environments can have profound effects on prey foraging structures and that these effects set up growth trade-offs between phenotypes that favor the evolution of phenotypically plastic responses.

openCC (other)Jun 2024View details →

Phenotypic plasticity in response to fine-grained environmental variation in predation.

1. In nature, organisms experience environmental variability at coarse-grained (inter-generational) and fine-grained (intra-generational) scales and a common response to environmental variation is phenotypic plasticity. The emphasis of most empirical work on plasticity has been on examining coarse-grained variation with the goal of understanding the costs and benefits of plastic responses in response to a particular environment. 2. In this study, we investigated the effects of fine-grained variation in predation on the inducible defences of larval wood frogs (Rana sylvatica) by widely altering the density and feeding schedule of caged predators (Dytiscusspp.) while holding average predation constant. 3. We found that predator cues induced change in tadpole behaviour, morphology, and mass. Surprisingly, however, temporal variation in predation did not cause the tadpoles to alter their activity (compared to a constant predation treatment) or mass. Temporal variation in predation did alter tadpole tail depth, but only when experiencing our most extreme variation treatment in which the predators were fed once every 8 days. Under these conditions, the predator-induced tadpole tail was less extreme compared to environments containing constant predation. 4. While a number of previous studies have examined behavioural responses of prey to temporal variation in predation risk without holding average predation constant, this appears to be the first test of temporal variation per se. As in previous studies of organism responses to temporal variation in resources, our results suggest that fine-grained environmental variability can affect the expression of phenotypically plastic traits, but our tadpoles appear to be generally unresponsive to this finegrained variation for many of their traits.

openCC (other)Jun 2024View details →

Relyea, R. A. 2002. Local population differences in phenotypic plasticity: Predator-induced changes in wood frog tadpoles. Ecological Monographs 72:77-93

Taxa that are divided into separate populations with low levels of interpopulation dispersal have the potential to evolve genetically based differences in their phenotypes and the plasticity of those phenotypes. These differences can be due to random processes, including genetic drift and founder effects, or they can be the result of different selection pressures among populations. I investigated population-level differences in predator- induced phenotypic plasticity in eight populations of larval wood frogs (Rana sylvatica) over a small geographic scale (interpopulation distances of 0.3–8 km). Using a common-garden experiment containing predator and no-predator environments, I found population differences in behavior, morphology, and life history. These responses exhibited a habitat-related pattern: the four populations from closed-canopy ponds did not differ from each other in any of their phenotypes whereas the four populations from opencanopy ponds did differ from each other in these traits. This phenotypic pattern matches the pattern of competitors and predators found in these two types of ponds. Based on two years of pond surveys, the four closed-canopy ponds contained very similar competitor and predator assemblages while the assemblages of the four open-canopy ponds were more diverse and highly variable among open-canopy ponds. When combined with past studies, which demonstrate that predators and competitors select for alternative behavioral and morphological traits, these patterns suggest that the population differences may have arisen via natural selection and not via random mutation or drift. In a second experiment, I cross-transplanted two of the populations into each other’s ponds to determine if the populations were locally adapted to the conditions of their native pond (using low and high competition crossed with the presence or absence of a lethal predator). The populations continued to exhibit phenotypic differences, and one of the two populations t

openCC0Sep 2024View details →

Plant community richness and foliar fungicides impact soil Streptomyces inhibition, resistance, and resource use phenotypes

Data associated with "Plant community richness and foliar fungicides impact soil Streptomyces inhibition, resistance, and resource use phenotypes" (DOI: 10.3389/fmicb.2024.1452534). These data include soil resource measurements and various phenotypic measurements of associated Streptomyces isolates/populations. Specifically, these data note population level inhibition phenotypes according to Herr's Assays, isolate level antibiotic resistance phenotypes against 9 standard antibiotics, and isolate level resource use phenotypes quantified with Biolog SF-P2 96 well plates.

opencc-by-4.0Apr 2020View details →

Heatmaps of quantitative and qualitative phenotypes of zebrafish pronephroi upon compound exposure

Heatmaps of quantitative and qualitative phenotypes of embryonic zebrafish pronephroi after exposure to compounds from the Prestwick library. For further details please see: Westhoff JH, Steenbergen PJ, Thomas LSV, Heigwer J, Bruckner T, Cooper L, Tönshoff B, Hoffmann GF and Gehrig J (2020) In vivo High-Content Screening in Zebrafish for Developmental Nephrotoxicity of Approved Drugs. Front. Cell Dev. Biol. 8:583. doi: 10.3389/fcell.2020.00583 The images represent full resolution versions of the thumbnails presented in:  <ol> <li>Supplementary Figure 3 | Fully annotated heat map of quantitative features.</li> <li>Supplementary Figure 4 | Fully annotated heat map of qualitative features.</li> </ol>

opencc-by-4.0Apr 2020View details →

Individual-based plant-pollinator networks are structured by phenotypic and microsite plant traits

Dataset associated with the manuscript "Individual-based plant-pollinator networks are structured by phenotypic and microsite plant traits" (Arroyo-Correa et al. 2020), including plant-pollinator interactions, individual plant attributes and the plant polygon map created with drone flights.

Fig. 6 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)

Fig. 6. Scatter plot of PCA results on shape variables of the (A) ventral, (B) dorsal and (C) lateral sides of Meriones crassus Sundevall, 1842 specimens. Legends: ○ = Iranian Plateau, ● = Western Zagros, * = Kuwait, Δ = Arabian, ▲ = Jeddah, □ = Jordan/NW Arabia, ■ = African. Deformation grids (two times magnified) along the first principal components, representing shape differences between configurations corresponding to minimal and maximal scores, are shown to the right of each plot. For the numbering of landmarks, see Fig. 2.

Fig. 4 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)

Fig. 4. Scatter plot of the CVA results of the (A) ventral and (B) dorsal shape data of Meriones crassus Sundevall, 1842 (two groups) and M. libycus Lichtenstein, 1823. Legends: ○ = M. crassus (other than Western Zagros), ● = M. crassus of Western Zagros, □ = M. libycus. The grids below show deformation along the arrows, when moving from the M. crassus group mean shape to the Western Zagros group mean shape (A1 and B1), and from the M. libycus mean shape to the mean shape of the Western Zagros (A2 and B2) (shape differences magnified three times for better visualization). For the numbering of landmarks, see Fig. 2.

Fig. 3 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)

Fig. 3. Scatter plot of RW1 versus RW2 of the (A) ventral and (B) dorsal cranium of Meriones crassus Sundevall, 1842 and M. libycus Lichtenstein, 1823. Legends: ○ = M. crassus (other than Western Zagros), ● = M. crassus of Western Zagros, □ = M. libycus. Below: thin-plate spline deformation grids visualize shape variation as expressed by the first two RWs axes (grids represent shape difference between configurations corresponding to lowest and highest RW-values). For the numbering of landmarks, see Fig. 2.

Fig. 7 in Cranial phenotypic variation in Meriones crassus and M. libycus (Rodentia, Gerbillinae), and a morphological divergence in M. crassus from the Iranian Plateau and Mesopotamia (Western Zagros Mountains)

Fig. 7. CVA scatter plot (axes 1 and 2) on shape variables of the (A) ventral, (B) dorsal and (C) lateral side of the Meriones crassus groups (Jeddah group not included). Legends: ○ = Iranian plateau, ● = Western Zagros, Δ = Arabian and ■ = African. Grids show deformation (3 x magnified) when following the trajectory within the morphospace along the arrows and between the groups' consensus (from African to Western Zagros – A1, B1 and C1; and from Iranian plateau to Western Zagros – A2, B2 and C2). For the numbering of landmarks, see Fig. 2.