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6,234 results for “phenotypes”
One of these things is not like the other: mixed predator cues result in lopsided phenotypic responses in a Neotropical tadpole
<p>Many organisms have evolved to produce different phenotypes in response to environmental variation. <em>Dendropsophus</em> <em>ebraccatus</em> tadpoles develop opposing shifts in morphology and coloration when they are exposed to invertebrate vs vertebrate predators. Each of these alternate phenotypes is adaptive, conferring a survival advantage against the predator with which tadpoles were reared but imposing a survival cost with the mismatched predator. Here, we measured the phenotypic response of tadpoles to graded cues and mixed cues of both fish and dragonfly nymphs. Prey species like <em>D. ebraccatus</em> commonly co-occur with both of these types of predators, amongst many others as well. In our first experiment, tadpoles increased investment in defensive phenotypes in response to increasing concentrations of predator cues. Whereas morphology only differed in the strongest cue predator, tail spot coloration differed even at the lowest cue concentration. In our second experiment, tadpoles reared with cues from both predators developed an intermediate yet skewed phenotype that was most similar to the fish-induced phenotype. Fish are more lethal than dragonfly larvae and thus tadpoles responded most strongly to the more dangerous predator, even though cues of each predator were evenly mixed. We demonstrate that not only do tadpoles assess predation risk via the concentration of predation cues in the water, but they also produce a stronger response to a more lethal predator even when the strength of cues is identical.</p>
Dataset for "On Developing an ML-Based Approach for the Automatic Characterization of Behavioral Phenotypes for Dairy Cows Relevant to Thermotolerance"
<p>This dataset consists of 3,421 videos filmed at T & K Dairy in Snyder, TX, over a 24-hour period on March 12-13, 2023. These videos were then used to train, validate, and evaluate a computer vision algorithm that is capable of automatically identifying cows using their coat patterns.</p>
NNX12AB54G phenotype database
<p>NNX12AB54G phenotype database</p> <p>This is a compiled database of tumor, cataract, and neurobehavioral phenotyping data collected from HZE ion and gamma ray irradiated outbred mice and unirradiated controls in NASA Grant NNX12AB54G (Characterization of the Tumor Spectrum Arising in HZE Ion Irradiated Outbred Mice). These data have been used in the following publications: PMID 38245354, PMID 32494593, PMID 30356920, and PMID 28535153.</p>
Data from: Phenotypic selection on an ornamental trait is not modulated by breeding density in a pied flycatcher population
<p>Most studies of phenotypic selection in the wild have focused on morphological and life-history traits and looked at abiotic (climatic) variation as the main driver of selection. Consequently, our knowledge of the effects of biotic environmental variation on phenotypic selection on sexual traits is scarce. Population density can be considered a proxy for the intensity of intra- and inter-sexual competition and could therefore be a key factor influencing the covariation between individual fitness and the expression of sexual traits. Here, we used an individual-based data set from a population of pied flycatchers (<em>Ficedula hypoleuca</em>) monitored over 24 years to analyse the effect of breeding density on phenotypic selection on dorsal plumage colouration, a heritable and sexually selected ornament in males of this species. Using the number of recruits as a fitness proxy, our results show overall stabilizing selection on male dorsal colouration, with intermediate phenotypes being favoured over extremely dark and dull individuals. However, our results did not support the hypothesis that breeding density mediates phenotypic selection on this sexual trait. We discuss the possible role of other biotic factors influencing selection on ornamental plumage.</p>
Human population dynamics in Upper Paleolithic Europe inferred from fossil dental phenotypes
<p>Despite extensive archaeological research, our knowledge of the human population history of Upper Paleolithic Europe remains limited, primarily due to the scarce availability and poor molecular preservation of fossil remains. As teeth dominate the fossil record and preserve genetic signatures in their morphology, we compiled a large dataset of 450 dentitions dating between ~47-7 thousand years ago (kya), outnumbering existing skeletal and paleogenetic datasets. We tested a range of competing demographic scenarios using a newly developed coalescent-based machine-learning Approximate Bayesian Computation (ABC) framework designed specifically for use with phenotypic data. Mostly in agreement with, but also challenging some of the hitherto available evidence, we identified a population turnover in western Europe at ~28 kya, isolates in western and eastern refugia between ~28-14.7 kya, and bottlenecks during the Last Glacial Maximum. Methodologically, this study marks the pioneering application of ABC to skeletal phenotypes, paving the way for exciting new research avenues.</p>
Considering decoupled phenotypic diversification between ontogenetic phases in macroevolution: An example using Triggerfishes (Balistidae)
<p>Across the Tree of Life, most studies of phenotypic disparity and diversification have been restricted to adult organisms. However, many lineages have distinct ontogenetic phases that differ from their adult forms in morphology and ecology. Focusing disproportionately on the evolution of adult forms unnecessarily hinders our understanding of the pressures shaping evolution over time. Non-adult disparity patterns are particularly important to consider for coastal ray-finned fishes, which often have juvenile phases with distinct phenotypes. These juvenile forms are often associated with sheltered nursery environments, with phenotypic shifts between adults and juvenile stages that are readily apparent in locomotor morphology. Whether this ontogenetic variation in locomotor morphology reflects a decoupling of diversification dynamics between life stages remains unknown. Here we investigate the evolutionary dynamics of locomotor morphology between adult and juvenile triggerfishes. We integrate a time-calibrated phylogenetic framework with geometric morphometric approaches and measurement data of fin aspect ratio and incidence and reveal a mismatch between morphospace occupancy, the evolution of morphological disparity, and the tempo of trait evolution between life stages. Collectively, our results illuminate how the heterogeneity of morpho-functional adaptations can decouple the mode and tempo of morphological diversification between ontogenetic stages.</p>
Fig. 6 in The origin and diversification of the Entorrhizales: deep evolutionary roots but recent speciation with a phylogenetic and phenotypic split between associates of the Cyperaceae and Juncaceae
Fig. 6 Spores of Entorrhiza fuirenae (holotype) seen by light microscopy. Scale bar = 10 μm
Fundus vessel phenotypes
<p>Related publication (2024): <a href="https://www.nature.com/articles/s41467-024-52334-1">https://www.nature.com/articles/s41467-024-52334-1</a></p> <p><strong>Sumstat column information</strong></p> <ul> <li>beta: refers to the effect of having an extra copy of A2</li> <li>af: frequency of A2</li> <li>A2 is not necessarily the minor allele</li> <li>The sumstats are curated bgenie output. official bgenie manual: https://jmarchini.org/bgenie/#output-file-options</li> </ul> <p><strong>Label map </strong>(maps names used in the paper to the sumstat labels)</p> <p>tif_dict = { 'A temporal angle': 'mean_angle_taa', 'V temporal angle': 'mean_angle_tva', 'V tortuosity': 'tau1_vein', 'A tortuosity': 'tau1_artery', 'ratio tortuosity': 'ratio_AV_DF', 'A central retinal eq': 'eq_CRAE', 'ratio central retinal eq': 'ratio_CRAE_CRVE', 'A std diameter': 'D_A_std', 'V std diameter': 'D_V_std', 'V central retinal eq': 'eq_CRVE', 'ratio vascular density': 'ratio_VD', 'A vascular density': 'VD_orig_artery', 'bifurcations': 'bifurcations', 'V vascular density': 'VD_orig_vein', 'A median diameter': 'medianDiameter_artery', 'V median diameter': 'medianDiameter_vein', 'ratio median diameter': 'ratio_AV_medianDiameter' }</p>
Summary-level data from meta-analysis of fat distribution phenotypes in UK Biobank and GIANT
<p>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~</p> <p>Summary-level data as presented in:</p> <p>"Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry." Pulit, SL et al. bioRxiv, 2018. https://www.biorxiv.org/content/early/2018/04/18/304030</p> <p>**If you use these data, please cite the above preprint.</p> <p>If you have any questions or comments regarding these files, please contact me:</p> <p>Sara L Pulit<br> spulit@well.ox.ac.uk or s.l.pulit@umcutrecht.nl</p> <p>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~</p> <p><strong>(1) Data files</strong></p> <p><em>i. whradjbmi.giant-ukbb.meta-analysis.combined.23May2018.txt</em><br> Meta-analysis of waist-to-hip ratio adjusted for body mass index (whradjbmi) in UK Biobank and GIANT data. Combined set of samples, max N = 694,649.</p> <p><em>ii. whradjbmi.giant-ukbb.meta-analysis.females.23May2018.txt</em><br> Meta-analysis of whradjbmi in UK Biobank and GIANT data. Female samples only, max N = 379,501.</p> <p><em>iii. whradjbmi.giant-ukbb.meta-analysis.males.23May2018.txt</em><br> Meta-analysis of whradjbmi in UK Biobank and GIANT data. Male samples only, max N = 315,284.</p> <p><em>iv. whr.giant-ukbb.meta-analysis.combined.23May2018.txt</em><br> Meta-analysis of waist-to-hip ratio (whr) in UK Biobank and GIANT data. Combined set of samples, max N = 697,734.</p> <p><em>v. whr.giant-ukbb.meta-analysis.females.23May2018.txt</em><br> Meta-analysis of whr in UK Biobank and GIANT data. Female samples only, max N = 381,152.</p> <p><em>vi. whr.giant-ukbb.meta-analysis.males.23May2018.txt</em><br> Meta-analysis of whr in UK Biobank and GIANT data. Male samples only, max N = 316,772.</p> <p><em>vii. bmi.giant-ukbb.meta-analysis.combined.23May2018.txt</em><br> Meta-analysis of body mass index (bmi) in UK Biobank and GIANT data. Combined set of samples, max N = 806,834.</p> <p><em>viii. bmi.giant-ukbb.meta-analysis.females.23May2018.txt</em><br> Meta-analysis of bmi in UK Biobank and GIANT data. Female samples only, max N = 434,794.</p> <p><em>ix. bmi.giant-ukbb.meta-analysis.males.23May2018.txt</em><br> Meta-analysis of bmi in UK Biobank and GIANT data. Male samples only, max N = 374,756.</p> <p><strong>(2) Data file format</strong></p> <p>CHR: Chromosome</p> <p>POS: Chromosomal position of the SNP, build hg19</p> <p>SNP: the dbSNP151 identifier of the SNP, followed by the first allele and second allele of the SNP, delimited with a colon. A small number of SNPs (<9,000) from the GIANT data had no dbSNP151 identifier, and are left as just an rsID. Note that these SNPs are also missing chromosome and position information (not provided in the GIANT data).</p> <p>Tested_Allele: the allele for which all association statistics are reported</p> <p>Other_Allele: the other allele at the SNP</p> <p>Freq_Tested_Allele: frequency of the tested allele</p> <p>BETA: the effect size of the tested allele</p> <p>SE: the standard error of the beta</p> <p>P: the p-value of the SNP, as reported from the inverse variance-weighted fixed effects meta-analysis</p> <p>N: the total sample size for this SNP</p> <p>INFO: the imputation quality (info score) of the SNP, as reported by UK Biobank. A number between 0 and 1 indicating quality of imputation (0, poor quality; 1, high quality or genotyped). Note that the summary-level GIANT data does not report info score, so SNPs appearing only in the GIANT analysis do not have info scores.</p>
Phenotype-Informed Noncoding Element Scoring
<p>Functional characterization of the noncoding genome is essential for the biological understanding of gene regulation and disease. Here, we introduce the computational framework PINES (Phenotype-Informed Noncoding Element Scoring) which predicts the functional impact of noncoding variants by integrating epigenetic annotations in a phenotype-dependent manner. A unique feature of PINES is that analyses may be customized towards genomic annotations from cell types of the highest relevance given the phenotype of interest. We illustrate that PINES identifies functional noncoding variation more accurately than methods that do not use phenotype-weighted knowledge, while at the same time being flexible and easy to use via a dedicated web portal.</p>
Supplemental Material from: Immune Profiling of Thyroid Carcinomas Suggests the Existence of Two Major Phenotypes: an ATC-like and a PDTC-like
<p>Supplemental Material from: Immune Profiling of Thyroid Carcinomas Suggests the Existence of Two Major Phenotypes: an ATC-like and a PDTC-like</p>
PathoPhenoDB: a database of pathogen-phenotype associations
<p>PathoPhenoDB is a database containing pathogen-to-phenotype associations mined from the scientific literature. PathoPhenoDB relies on manual curation of pathogen-disease relations, and on ontology-based text mining to associate phenotypes with infectious disease. Using Semantic Web technologies, PathoPhenoDB also links to knowledge about drug resistance mechanisms and drugs used in the treatment of infectious diseases. The information in PathoPhenoDB can provide background knowledge about known pathogens, diseases, and phenotypes, and the drugs to which they respond; it therefore provides a tool for research on infectious diseases and drug mechanisms. PathoPhenoDB is accessible at http://patho.phenomebrowser.net/, and the data is freely available through a public SPARQL endpoint.</p>
Zebrafish Phenotype Ontology
<p>Current release of Zebrafish Phenotype Ontology</p>
Phenotype profile of monocytes differentiated in the presence of semen Fucosylated Clusterin
<p>Having shown that fucosylated clusterin effectively interacts with macrophages via DC-SIGN, we then analyzed its influence on the phenotype of macrophages. In these experiments, monocytes were cultured for 5 days with M-CSF, in the absence or presence of semen fucosylated clusterin. Then, the cells were cultured for additional 24 hours with or without LPS and the phenotype were analyzed. Fucosylated clusterin-treated macrophages failed to upregulate the expression of HLA-DR and CD86 induced by LPS but not the expression of CD40, CD80 and PDL-1. These results are represented on Figure 6 from the publication: Aberrant fucosylation enables breast cancer clusterin to interact with dendritic cell-specific ICAM-grabbing non-integrin (DC-SIGN). </p>
data set related to article Broad phenotypic spectrum and genotype-phenotype correlations in GMPPB-related dystroglycanopathies: an Italian cross-sectional study
<p>This record contains raw data related to article Broad phenotypic spectrum and genotype-phenotype correlations in GMPPB-related dystroglycanopathies: an Italian cross-sectional study</p>
The Ubiquitin Ligase WWP1 Contributes to Shifts in Matrix Proteolytic Profiles and a Myocardial Ageing Phenotype with Diastolic Heart Failure
<p><strong><em>Aims</em></strong>. Ubiquitylation is a key event that regulates protein turnover, and induction of the ubiquitin ligase E3 WWP1 has been associated with age. Left ventricular hypertrophy (LVH) commonly occurs as a function of age and can cause heart failure with a preserved ejection fraction (EF; HFpEF). We hypothesized that overexpression (O/E) of WWP1 in the heart would cause LVH as well as functional and structural changes consistent with the ageing HFpEF phenotype.</p> <p><strong><em>Methods and Results.</em></strong> Global WWP1 O/E was achieved in mice (n=11) and echocardiography (40 MHz) performed to measure LV mass, EF, Doppler velocities (early-E, late/atrial-A), myocardial relaxation (E’), and isovolumetric relaxation time (IVRT) at 4, 6, and 8 weeks. Age matched wild type animals (n=15) were included as referent controls. LV EF was identical (60+1% vs 60+1%, p>0.90) with no difference in LV mass (67+3 vs 75+5, p>0.25) at 4 weeks. LVH and diastolic dysfunction occurred with WWP1 O/E wherein LV mass increased by over two-fold, E/A fell (impaired passive filling), and E/E’ was lower and IVRT prolonged (impaired LV relaxation). Collagen percent area increased by over two-fold with WWP1 O/E and increased expression of determinants of fibrosis and growth (qPCR) were also concomitantly increased.</p> <p><strong><em>Conclusion.</em></strong> Inducing WWP1 expression caused LVH with significant diastolic dysfunction, consistent with the HFpEF phenotype. Thus, targeting the WWP1 pathway may be a novel therapeutic target for this intractable form of HF associated with ageing</p>
Zea mays MAGIC RIL population - field trial phenotyping data
<p>MIAPPE compliant ISA-tab files of the Zea mays MAGIC RIL population derived from eight genetically diverse founder lines.</p>
Zea mays MAGIC RIL population - growth chamber phenotyping data
<p>MIAPPE compliant ISA-tab files of 197 recombinant inbred lines of two different maize (Zea mays) populations including indepth phenotyping of the fourth leaf at later stages of development.</p>
Fig. 1 in Linking phenotypic to genotypic metacestodes from Octopus maya of the Yucatan Peninsula
Fig. 1. Sampling localities where specimens of Octopus maya were collected in Yucatan, Mexico.
R codes prepared for the manuscript, entitled "The roles of Y chromosomal genes in mouse sex spectrum phenotypes"
<p>R codes for the manuscript, entitled "The roles of Y chromosomal genes in mouse sex spectrum phenotypes" </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)
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.