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1,363 results for “phenotypic data”
Data from: Visual pigment chromophore usage in Nicaraguan Midas cichlids: Phenotypic plasticity and genetic assimilation of cyp27c1 expression
<p>Code and Data associated with "Visual pigment chromophore usage in Nicaraguan Midas cichlids: Phenotypic plasticity and genetic assimilation of <em>cyp27c1</em> expression"</p> <h2><span>Abstract</span></h2> <p><span>The wide-ranging photic conditions found across aquatic habitats may act as selective pressures potentially driving rapid evolution and diversity in the visual system of teleost fishes. Fine-tuning of visual sensitivities in many fish species relies on regulating the two components of visual pigments, the opsin protein and the chromophore. Many studies have focused on opsin gene expression or opsin sequence divergence in fishes inhabiting contrasting habitats. However, variation in chromophore usage across photic habitats has received less attention. Species from the Nicaraguan Midas cichlid complex, <em>Amphilophus </em>cf <em>citrinellus </em>[Günther 1864], have independently colonized seven isolated crater lakes of varying photic conditions resulting in repeated examples of small adaptive radiations. Here, we investigate variation in <em>cyp27c1</em>, the main enzyme involved in chromophore exchange, in response to photic environments in the wild, we measure its genetic component using laboratory-reared fish and test the effect of different rearing light conditions on <em>cyp27c1</em> expression. We found that photic environments significantly predict variation in <em>cyp27c1</em> expression in wild populations and that this variation seems to be genetically assimilated in two populations. We found that light-induced <em>cyp27c1</em> expression is variable across populations (i.e., genotype-by-environment interactions) and correlated with local photic conditions thus highlighting <em>cyp27c1</em> as a key factor of visual ecology in cichlid fishes.</span></p> <p><span>Keywords: <em>cyp27c1 </em>gene expression, sensory ecology, visual plasticity, Neotropical cichlids </span></p>
Data: DEAE-Dextran enhances the lentiviral transduction of primary human mesenchymal stromal cells from all major tissue sources without affecting their proliferation and phenotype
<p>This data set includes all the raw data collected for the following article: "DEAE-Dextran enhances the lentiviral transduction of primary human mesenchymal stromal cells from all major tissue sources without affecting their proliferation and phenotype"</p>
Highly multiplexed histology reveals phenotypic and spatial characteristics of human Innate Lymphoid Cells in chronic inflammation - MELC tonsil data-set
<p><strong>53 marker MELC Run in human tonsil</strong>. Each image depicts the same field of view, sequentially stained with the depicted fluorescence-labelled antibodies. Images contain 2048 x 2048 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have not been normalized and intensities have not been adjusted.</p> <p> </p>
Data from: Genetic admixture increases phenotypic diversity in the nectar yeast Metschnikowia reukaufii,
<p>Raw data and supplementary files for the manuscript "Genetic admixture increases phenotypic diversity in the nectar yeast <em>Metschnikowia reukaufii</em>."</p> <p>-------------------</p> <p><strong>Table S5.xlsx </strong>-- Pairwise correlations between phenotypic traits of <em>Metschnikowia reukaufii</em>.</p> <p><strong>Table S6.xlsx</strong> -- Detailed results obtained in tests of phylogenetic signal for different phenotypic traits and indices of overall performance of <em>Metschnikowia reukaufii</em>.</p> <p><strong>Table S7.xlsx</strong> -- Detailed model fitting results obtained for phenotypic traits and indices of overall performance of <em>Metschnikowia reukaufii</em>.</p> <p><strong>mronlyvcf-renamed.vcf</strong> -- High coverage SNPs obtained from whole genome mapping of 73 <em>Metschnikowia reukaufii</em> strains to diploid reference (mean coverage = 47.9×, range 23 – 116×).</p> <p><strong>MR_phenotypes.xlsx</strong> -- Phenotypic data obtained for 73 <em>Metschnikowia reukaufii</em> strains.</p>
Supporting data for "The methylome of Biomphalaria glabrata and other mollusks: enduring modification of epigenetic landscape and phenotypic traits by a new DNA methylation inhibitor"
<p>Methylome of the fresh water snail <em>Biomphalaria glabrata</em>. DNA was extracted from the feet of 10 individuals of <em>B. glabrata</em> originally isolated from Brazil. These snails have been cultivated in the laboratory since 1960. Tissue were grinded at 4°C and incubated in 1 ml volume of lysis buffer (20 mM TRIS pH 8; 1 mM EDTA; 100 mM NaCl; 0.5% SDS), with 0.3 mg of proteinase K at 55°C for 1 night. Afterwards, lysate was purified with phenol-chloroform and DNA was isopropanol precipitated. The extracted DNA (around 138ng/µL) was poled in equivalent amounts and Whole Genome Bisulfite Sequencing was done by GATC-biotech (www.gatc-biotech.com). The principle of this treatment is to convert non-methylated cytosines of gDNA into deoxy-uracil, whereas methylated cytosines remain intact. WGBS was done according to the Lister protocol (sequence 2 forward strands only). The reference genome (Biomphalaria-glabrata-BB02_SCAFFOLDS_BglaB1.fa) and annotation (Biomphalaria-glabrata-BB02_BASEFEATURES_BglaB1.3.gff3) used in this project are available on VectorBase (https://www.vectorbase.org/). To align our short reads, we chose to use two specific bisulfite mapping tools, BSMAP 1.0.0 (https://code.google.com/p/bsmap/) and Bismark 0.10.2 (www.bioinformatics.babraham.ac.uk /projects/bismark/), to compare their efficiency and convenience to finally work with the more suitable one on our datasets. IGV (Interactive Genomics Viewer, https://www.broadinstitute.org/igv/) was used to visualized final alignments.<br> BSMAP performed better than Bismark and was used for downstream analyses. Without default parameters alignement efficiency for BSMAP is 47.1%, allowing for 2 mismatches increases it to 55.6%. Methylation occurs predominantly in CpGs. (C methylated in CpG context: 12.4%, C methylated in CHG context: 0.5%, C methylated in CHH context: 0.5%) The major part of CpG sites, 95.7% were unmethylated, of the remaining 4.3% of CpG sites around 3.8% had low methylation, and 0.5% were completely methylated. Methylation is of the mosaic type. Methylation is relatively low with 1.2% of total cytosines. Our analyses suggested that conserved genes and genes with stable expression are localized in high methylated regions of the genome. Finally, we see that repetitive sequences were predominantly situated in low methylated regions of <em>B. glabrata</em>. </p> <p>Wiggle files were generated for CpG pairs only.</p> <p>Produced at IHPE (http://ihpe.univ-perp.fr/)</p>
Phenotypic data related to genetic architecture of transmission stage production and virulence in schistosome parasites
<p>These data were generated related to the study of the <strong>Genetic architecture of transmission stage production and virulence in schistosome parasites</strong>.</p> <p><strong>Abstract:</strong> Both theory and experimental data from multiple pathogens suggest that the production of transmission stages should be strongly associated with virulence, but the genetic bases of parasite transmission/virulence traits are poorly understood. In the blood fluke <em>Schistosoma mansoni</em>, parasite genotypes show extensive variation in numbers of cercariae larvae shed from infected snails. Furthermore, high shedding parasites cause high mortality to snails while low shedding parasites cause low mortality, consistent with expected trade-offs between parasite transmission and virulence. To understand the genetic basis of transmission stage production/virulence, we conducted reciprocal crosses between schistosomes from two laboratory populations that differ 8-fold in cercarial shedding and in their virulence to inbred snail hosts. Each parasite generation, we determined four-week cercarial shedding profiles in inbred <em>Biomphalaria glabrata</em> snails infected with single parasite larvae. We sequenced the whole genome of the F0 parents and the exome of the F1 progeny and 188 F2 progeny from each cross, and used linkage mapping to reveal quantitative trait loci (QTLs) underlying transmission stage production. Cercarial production is polygenic: we found three major QTLs on chromosome 1, 3 and 5 (Log-of-the-odds (LOD) = 5.61, 8.19, 6.25) and two minor QTLs on chromosome 2 and 4. These QTLs act additively and explained 28.56% of the phenotypic variation in cercarial shedding. Alleles inherited from the high and low shedding parents were co-dominant at all QTLs, except for chr. 1 and chr. 4 where the “high cercarial shedding” allele is recessive. These results demonstrate that the genetic architecture of key traits directly relevant to schistosome ecology can be dissected using classical linkage mapping approaches, and set the stage for fine mapping and functional validation of the genes involved using the growing armory of functional and cell biology tools available for this parasite.</p> <p> </p> <p>This dataset is made of 4 tables:</p> <ul> <li>F0_parental_populations.csv</li> <li>F1.csv</li> <li>F2.csv</li> <li>sex.tsv</li> </ul> <p> </p> <p><strong>F0_parental_populations.csv</strong></p> <p> </p> <p>This table contains the number of cercariae produced by each individual <em>Biomphalaria glabrata</em> Bg26 snails infected with single genotypes of <em>Schistosoma mansoni</em> parasite. We have compared the transmission stage production between two different populations of <em>S. mansoni</em> parasite. This dataset was originally published in Le Clec'h et al., 2019 (Striking differences in virulence, transmission and sporocyst growth dynamics between two schistosome populations. Parasites and Vectors. 2019 Oct 16;12(1):485. doi: 10.1186/s13071-019-3741-z).</p> <p> </p> <p>This table is made of 9 columns:</p> <ul> <li><strong>id</strong>: the unique identifier of each sample.</li> <li><strong>schistosoma_population</strong>: the population of schistosome used for the infection of the snail. Each snail was infected with a single parasite genotype. We have used SmLE (high shedder/highly virulent population) and SmBRE (low shedding/low virulent population).</li> <li><strong>Shed.1</strong>: the number of cercariae produced by each parasite genotype at the first shedding week (4 weeks after exposure to parasite).</li> <li><strong>Shed.2</strong>: the number of cercariae produced by each parasite genotype at the second shedding week (5 weeks after exposure to parasite).</li> <li><strong>Shed.3</strong>: the number of cercariae produced by each parasite genotype at the third shedding week (6 weeks after exposure to parasite).</li> <li><strong>Shed.4</strong>: the number of cercariae produced by each parasite genotype at the fourth shedding week (7 weeks after exposure to parasite).</li> <li><strong>sum</strong>: the sum of the cercariae produced by each parasite genotype over the 4 weeks of shedding (Shed.1 + Shed.2 + Shed.3 + Shed.4).</li> <li><strong>average</strong>: the average number of cercariae produced by each parasite genotype over the 4 weeks of shedding.</li> <li><strong>sex</strong>: the sex of each parasite genotype determined by PCR <sup>1</sup>.</li> </ul> <p> </p> <p><strong>F1.csv</strong></p> <p> </p> <p>This table contains the number of cercariae produced by each individual <em>Biomphalaria glabrata</em> Bg26 snails infected with single genotypes of F1 progeny from the cross SmLE x SmBRE (see the manuscript for details).</p> <p> </p> <p>This table is made of 11 columns:</p> <ul> <li><strong>id</strong>: the unique identifier of each sample.</li> <li><strong>cross</strong>: F1A or F1B cross. Each snail was infected with a single parasite genotype from either F1A or F1B progeny.</li> <li><strong>Shed.1</strong>: the number of cercariae produced by each parasite genotype at the first shedding week (4 weeks after exposure to parasite).</li> <li><strong>Shed.2</strong>: the number of cercariae produced by each parasite genotype at the second shedding week (5 weeks after exposure to parasite).</li> <li><strong>Shed.3</strong>: the number of cercariae produced by each parasite genotype at the third shedding week (6 weeks after exposure to parasite).</li> <li><strong>Shed.4</strong>: the number of cercariae produced by each parasite genotype at the fourth shedding week (7 weeks after exposure to parasite).</li> <li><strong>sum</strong>: the sum of the cercariae produced by each parasite genotype over the 4 weeks of shedding (Shed.1 + Shed.2 + Shed.3 + Shed.4).</li> <li><strong>average</strong>: the average number of cercariae produced by each parasite genotype over the 4 weeks of shedding.</li> <li><strong>PO</strong>: the total phenoloxidase activity in infected snail hemolymph, measured at 7.5 weeks post-exposure <sup>2</sup>.</li> <li><strong>Hb</strong>: the hemoglobin rate in infected snail hemolymph, measured at 7.5 weeks post-exposure <sup>3</sup>.</li> <li><strong>sex</strong>: the sex of each parasite genotype determined by PCR <sup>1</sup>.</li> </ul> <p> </p> <p><strong>F2.csv</strong></p> <p>This table contains the number of cercariae produced by each individual <em>Biomphalaria glabrata</em> Bg26 snails infected with single genotypes of F2 progeny from the cross SmLE x SmBRE (see the manuscript for details).</p> <p> </p> <p>This table is made of 10 columns:</p> <ul> <li><strong>id</strong>: the unique identifier of each sample.</li> <li><strong>cross</strong>: F2A or F2B cross. Each snail was infected with a single parasite genotype from either F2A or F2B progeny.</li> <li><strong>Shed.1</strong>: the number of cercariae produced by each parasite genotype at the first shedding week (4 weeks after exposure to parasite).</li> <li><strong>Shed.2</strong>: the number of cercariae produced by each parasite genotype at the second shedding week (5 weeks after exposure to parasite).</li> <li><strong>Shed.3</strong>: the number of cercariae produced by each parasite genotype at the third shedding week (6 weeks after exposure to parasite).</li> <li><strong>Shed.4</strong>: the number of cercariae produced by each parasite genotype at the fourth shedding week (7 weeks after exposure to parasite).</li> <li><strong>sum</strong>: the sum of the cercariae produced by each parasite genotype over the 4 weeks of shedding (Shed.1 + Shed.2 + Shed.3 + Shed.4)</li> <li><strong>average</strong>: the average number of cercariae produced by each parasite genotype over the 4 weeks of shedding.</li> <li><strong>PO</strong>: the total phenoloxidase activity in infected snail hemolymph, measured at 7.5 weeks post-exposure <sup>2</sup>.</li> <li><strong>Hb</strong>: the hemoglobin rate in infected snail hemolymph, measured at 7.5 weeks post-exposure <sup>3</sup>.</li> </ul> <p> </p> <p><strong>sex.csv</strong></p> <p> </p> <p>This table contains the <em>in silico</em> sexing of F0 parents, F1 parents and F2 progeny of <em>S. mansoni</em> parasites.</p> <p>This table is made of 4 columns:</p> <ul> <li><strong>id</strong>: the unique identifier of each sample</li> <li><strong>read_depth</strong>: the read depth ratio between the Z-linked and pseudo-autosomal regions.</li> <li><strong>ratio</strong>: computed ratio between the Z-linked and pseudo-autosomal regions.</li> <li><strong>sex</strong>: the sex of each parasite genotype determined <em>in silico</em>: a ratio around 1 corresponds to a male carrying two Z chromosomes while a ratio around 0.5 corresponds to a female carrying only one Z chromosome.</li> </ul> <p><strong>Notes:</strong></p> <p><sup>1</sup>. Le Clec’h W, Chevalier F et al. Real-time PCR for sexing Schistosoma mansoni cercariae. Mol Biochem Parasitol. Jan-Feb 2016; 205(1-2):35-8.doi: 10.1016/j.molbiopara.2016.03.010. Epub 2016 Mar 26.</p> <p><sup>2</sup>. Le Clec’h W et al. Characterization of hemolymph phenoloxidase activity in two Biomphalaria snail species and impact of Schistosoma mansoni infection. Parasit Vectors. 2016 Jan 22; 9:32.doi: 10.1186/s13071-016-1319-6.</p> <p><sup>3</sup>. Le Clec'h et al. Striking differences in virulence, transmission and sporocyst growth dynamics between two schistosome populations. Parasit Vectors. 2019 Oct 16; 12(1):485. doi: 10.1186/s13071-019-3741-z.</p>
Phenotype data for Sussex LHM Drosophila melanogaster reproductive fitness GWAS
<p>Input data, code, logs, graphs and output data for the Sussex LHM Drosophila melanogaster hemiclones.</p> <p>Aim is to generate single, standardised values of female and male reproductive fitness for each hemiclone genome, for using in genome-wide association test using Plink software.</p> <p>Notes on how to run are provided in the code.</p>
Data from: Chronic Rapamycin administration via drinking water mitigates the pathological phenotype in a Krabbe disease mouse model through autophagy activation.
<p>ABSTRACT </p><p>Krabbe disease (KD) is a rare disorder caused by a deficiency of the lysosomal enzyme galactosylceramidase (GALC), resulting in the accumulation of the cytotoxic metabolite psychosine (PSY) in the nervous system. This accumulation triggers demyelination and neurodegeneration. Despite ongoing research, the underlying pathogenic mechanisms remain incompletely understood, and there is currently no cure available.</p><p>Previous studies from our lab revealed the presence of autophagy dysfunctions in KD pathogenesis, as evidenced by the presence of p62-tagged protein aggregates in the brains of KD mice and increased p62 levels in the KD sciatic nerve. We also demonstrated that the autophagy inducer Rapamycin (RAPA) can partially restore the wild-type (WT) phenotype in KD primary cells by reducing the number of p62 aggregates.</p><p>In this study, we tested RAPA in the Twitcher (TWI) mouse, a spontaneous KD mouse model. We administered the drug ad libitum via drinking water (15 mg/L) starting from post-natal day (PND) 21-23. We longitudinally monitored the motor performance of the mice through grip strength and rotarod tests, along with various biochemical parameters related to KD pathogenesis (i.e. autophagy markers expression, myelination, astrogliosis, and PSY accumulation).</p><p>Our findings demonstrate that RAPA significantly enhances motor functions at specific treatment time points and reduces astrogliosis in TWI brain, spinal cord, and sciatic nerves. Using western blot and immunohistochemistry, we observed a decrease in p62 aggregates in TWI nervous tissues, which corroborates our earlier in-vitro results. Furthermore, RAPA treatment partially reduces PSY levels in the spinal cord.</p><p>In conclusion, our results support the consideration of RAPA as a supportive therapy for KD. Importantly, as RAPA is already available in pharmaceutical formulations for clinical use, its potential for KD treatment can be promptly evaluated in clinical trials.</p>
GWAS Summary Statistics for Publication: Identifying novel genetic and phenotypic associations to genomic features by leveraging off-target reads in exome sequencing data
<p>This dataset contains summary statistics for genome-wide association studies (GWAS) conducted on genomic features derived from off-target reads in whole-exome sequencing (WES) data. The study utilized tools like Seeing Beyond the Target (SBT) and ImReP to construct novel phenotypic features from unmapped reads in ~50,000 participants in the UK Biobank. Features include mitochondrial DNA (mtDNA) copy number, ribosomal DNA (rDNA) copy number (5S, 18S, 28S), immune repertoire metrics (e.g., T-cell receptor alpha diversity), and microvial genome load (viral and fungal).</p> <p>Summary statistics can be used for replication studies, meta-analyses, or further exploration of these phenotypes.</p>
Data for "Phenotypic responses to climate change are significantly dampened in big-brained birds"
<p>Anthropogenic climate change is rapidly altering local environments and threatening biodiversity throughout the world. Although many wildlife responses to this phenomenon appear largely idiosyncratic, a wealth of basic research on this topic is enabling the identification of general patterns across taxa. Here we expand those efforts by investigating how avian responses to climate change are affected by the ability to cope with ecological variation through behavioral flexibility (as measured by relative brain size). After accounting for the effects of phylogenetic uncertainty and interspecific variation in adaptive potential, we confirm that although climate warming is generally correlated with major body size reductions in North American migrants, these responses are significantly weaker in species with larger relative brain sizes. Our findings suggest that cognition can play an important role in organismal responses to global change by actively buffering individuals from the environmental effects of warming temperatures.</p>
Data for: Heat induces multiomic and phenotypic stress propagation in zebrafish embryos
<p>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 <em>Danio rerio </em>at 1 day and 4 days of development.</p> <p>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.</p>
Phenotypic differences between interfertile Chlamydomonas species- focus-filtered timelapse data and measurements
<p>This repository contains focus-filtered timelapse microscopy data of two interfertile <i>Chlamydomonas</i> 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 <i>Chlamydomonas</i> 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 <i>C. reinhardtii </i>or C<i>. smithii </i>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>.</p><h4>Reference</h4><p><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 <i>Chlamydomonas </i>species</a></p><h4>Notes</h4><p>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.</p><p>"Cr" indicates <i>Chlamydomonas reinhardtii</i></p><p>"Cs" indicates <i>Chlamydomonas smithii</i></p><p>Frame rate: 20 frames per second (fps)</p><p>Pixel size: 0.6398 microns/pixel</p>
Open data repository, Boehm-Sturm et al., Phenotyping placental oxygenation in Lgals1 deficient mice using 19F MRI
<p>Open data repository of journal article "Phenotyping placental oxygenation in Lgals1 deficient mice using <sup>19</sup>F MRI"</p>
Code and Data for: "Signs of local adaptation and phenotypic plastic response to elevation shifted between environmental backgrounds in Snapdragon plants"
<p>Code and data for manuscript: "Signs of local adaptation and phenotypic plastic response to elevation shifted between environmental backgrounds in Snapdragon plants"</p>
Data from: Discordant patterns of genetic and phenotypic differentiation in five grasshopper species co-distributed across a microreserve network
<p>Conservation plans can be greatly improved when information on the evolutionary and demographic consequences of habitat fragmentation is available for several co-distributed species. Here, we study spatial patterns of phenotypic and genetic variation among five grasshopper species that are co-distributed across a network of microreserves but show remarkable differences in dispersal-related morphology (body size and wing length), degree of habitat specialization and extent of fragmentation of their respective habitats in the study region. In particular, we tested the hypothesis that species with preferences for highly fragmented microhabitats show stronger genetic and phenotypic structure than co-distributed generalist taxa inhabiting a continuous matrix of suitable habitat. We also hypothesized a higher resemblance of spatial patterns of genetic and phenotypic variability among species that have experienced a higher degree of habitat fragmentation due to their more similar responses to the parallel large-scale destruction of their natural habitats. In partial agreement with our first hypothesis, we found that genetic structure, but not phenotypic differentiation, was higher in species linked to highly fragmented habitats. We did not find support for congruent patterns of phenotypic and genetic variability among any studied species, indicating that they show idiosyncratic evolutionary trajectories and distinctive demographic responses to habitat fragmentation across a common landscape. This suggests that conservation practices in networks of protected areas require detailed ecological and evolutionary information on target species in order to focus management efforts on those taxa that are more sensitive to the effects of habitat fragmentation.</p>
Supporting data: Reporting phenotypes in model organisms when considering body size as a potential confounder.
<p>This directory contains the data and associated scripts used to generate the figures in the manuscript "Reporting phenotypes in model organisms when considering body size as a potential confounder." submitted to the Journal of Biomedical Semantics</p>
Root phenotyping data
<p>Dataset presenting the root phenotyping analysis performed in the paper:</p> <blockquote> <p>Bouché F, D’Aloia M, Tocquin P, Lobet G, Detry N, Périlleux C. 2016. Integrating roots into a whole plant network of flowering time genes in Arabidopsis thaliana. Scientific Reports.</p> </blockquote> <p>The dataset contains:</p> <p>- <strong>01-raw_images.zip</strong>: the orignal images of the petri dishes used for the analysis. The scale is 370 DPI</p> <p>- <strong>02-processed_images.zip</strong>: images enhanced, cropped and renamed for the analysis. Analysis was performed using SmartRoot (Lobet et al. 2011). Each image has its corresponding RSML file containing the root architecture data. </p> <p>- <strong>plate_image_treatment.ijm</strong>: ImageJ macro for a pre-processing of the images, before the SmartRoot analysis </p> <p>- <strong>root_architecture_analysis.R</strong>: R script used for the architecture data analysis</p> <p>- <strong>root_architecture_data.csv</strong> : architecture data exported from SmartRoot.</p> <p>- <strong>images.zip</strong>: the plots generated using the R script</p> <p> </p>
Data and R script for Neville, Andrews, Nettle and Bateson, 'Dissociating the effects of alternative early-life feeding schedules on the development of adult depression-like phenotypes'
<p>The R script and raw data files for the paper 'Dissociating the effects of alternative early-life feeding schedules on the development of adult depression-like phenotypes', by Vikki Neville, Clare Andrews, Daniel Nettle and Melissa Bateson.</p>
Data from: Stochastic phenotypic switching arises in response to directional selection in experimentally evolved multicellular yeast.
<p><span lang="EN">This BBC_2025__README.txt file was generated on 2025-09-24 by Beatriz Baselga Cervera</span></p> <p><span lang="EN">GENERAL INFORMATION</span></p> <ol> <li><span lang="EN">Title of Dataset and code: Data from: Stochastic phenotypic switching arises in response to directional selection in experimentally evolved multicellular yeast.</span></li> </ol> <p><span lang="EN"> </span></p> <p><span lang="EN">2. Author Information</span></p> <p><span lang="EN"> Corresponding Investigator</span></p> <p><span lang="EN"> Name: Ph.D. Beatriz Baselga-Cervera</span></p> <p><span lang="EN"> Institution: University of Minnesota Twin cities, Minnesota, US.</span></p> <p><span lang="EN"> Email: <a href="mailto:bbaselga@umn.edu"><span>bbaselga@umn.edu</span></a>; beabaselga@gmail.com</span></p> <p><span lang="EN"> Co-investigator 1</span></p> <p><span lang="EN"> Name: Ph.D. Nahui <span>Olin Medina-Chávez</span></span></p> <p><span lang="EN"> Institution: University of Minnesota Twin cities, Minnesota, US.</span></p> <p><span lang="EN"> Email: nmedinac@umn.edu</span></p> <p><span lang="EN"> Co-investigator 2</span></p> <p><span lang="EN"> Name: Ph.D. Noah Gettle</span></p> <p><span lang="EN"> Institution: Wellcome Sanger Institute, Hinxton, UK.</span></p> <p><span lang="EN"> Email: nbgettle@gmail.com </span></p> <p><span lang="EN">Co-investigator 3</span></p> <p><span lang="EN"> Name: Ph.D. Michael Travisano</span></p> <p><span lang="EN"> Institution: University of Minnesota Twin cities, Minnesota, US.</span></p> <p><span lang="EN"> Email: travisan@umn.edu</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">3. Data collectors: Ph.D. Beatriz Baselga-Cervera, Ph.D. Nahui Olin Medina-Chávez & Ph.D. Noah Gettle.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">4. Date of data collection: 2022-2024</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">5. Geographic location of data collection: Saint Paul, US</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">6. Funding sources that supported the collection of the data: Fundación Alfonso Martín Escudero, Madrid, Spain (BBC).</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">7. Recommended citation for this dataset: Baselga-Cervera et al. (2024), Data from: Stochastic phenotypic switching arises in response to directional selection in experimentally evolved multicellular yeast.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">DATA & FILE OVERVIEW</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">8. Description of dataset</span></p> <p><span lang="EN">In this study, we address whether stochastic phenotypic switching can shape biological diversity contributing to evolutionary change across the transition from singles cells to multicellular clutters in <em>Saccharomyces cerevisiae </em>multicellular yeast system. Populations characterization was conducted with a Coulter Counter multisize 4, a FlowCam 3, under the optic microscope, via ACE2 gene sequencing and RNA sequencing and mathematical modeling. The populations studied were the genetically uniform diploid wild-type <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>). </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">9. File list:</span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">Coulter Counter size distribution data: </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 1 name: File_1_Coulter_Counter_Counts_20h.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 1 description: Size distributions of <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 20-hours growth. Data for: Fig. 1A, Fig. 3A and Fig. S2, Table S2 and Table S3.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 2 name: File_2_Coulter_Counter_Counts_24h.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 2 description: Size distributions of <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 24-hours growth. Data for: Fig. 1A, Fig. 3A, Fig. S2, Table S2 and Table S3. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 3 name: File_3_Coulter_Counter_Counts_48h.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 3 description: Size distributions of <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 48-hours growth. Data for: Fig. 1, Fig. 3A, Fig. S2, Table S2 and Table S3.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File name: File_4_Coulter_Counter_Counts_Constructed_strains_diversity.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 4 description: Size distributions of the constructed ACE2 knockout and a strain containing the homozygous missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 24h growth. Size distributions were obtained from populations before (initial) and five resuspended colonies obtained from small-size particles by plating the top fraction of the population after gravitational selection from three isolates per strain. Data for: Fig. 1, Fig. S2, Table S2 and Table S3.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 5 name: File_5_Coulter_Counter_Counts_Selection_Experiment.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 5 description: Size distributions of C1W8.1 and C1W8.2 multicellular evolved strains in YPD at 24h growth. Size distributions from the selection experiment for small-size particles by plating the top fraction of the population after gravitational selection over three cycles of selection. Data for: Fig. 2B and Fig. S6.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 6 name: File_6_Coulter_Counter_Counts_12h.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 6 description: Size distributions of C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 12-hours growth. Data for: Fig. 3A and Fig. S3. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">FlowCam data:</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 7 name: File_7_Rawdata_FlowCam_all.csv </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 7 description: FlowCam data from <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 24h growth. Data for: Fig. S4. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">Data generated statistically:</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 8 name: File_8_C1W8.2_overlapPairs_Selection_Experiment.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 8 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data of the C1W8.2 derived strain over the selection experiment. Data for: Fig. S6D.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 9 name: File_9_C1W8.1_overlapPairs_Selection_Experiment.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 9 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">of the C1W8.1 derived strain over the selection experiment. Data for: Fig. S6C.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 10 name: File_10_ overlapPairs_Constructed_strains_diversity.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 10 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data</span></p> <p><span lang="EN">of the constructed ACE2 knockout and a strain containing the homozygous missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 24h growth. Size distributions were obtained from populations before (initial) and after gravitational selection of five resuspended colonies from three isolates per strain. Data for: Fig. S7.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">Data from ImageJ:</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 11 name: File_11_ImageJ_analyses.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 11 description: ImageJ analyses of the microphotographs from <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>). Cultures were grown in culture tubes with 10 ml of media, 50 mL Erlenmeyer flasks with 10 mL and 30 mL of media, in YPD under non-shaking and shaking at 250 rpm. YPD media was used across all conditions. Cultures were assessed after 24 hours growth at 30°C.<span> </span>Microphotographs of each condition and strain were obtained with a Nikon TE2000 microscope using 10x objective.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">Pictures:</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 12 name: File_12_ FlowCam_Pictures.zip</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 12 description FlowCam IMAGES from <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 24h growth. Data for: Fig. 1B. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 13 name: File_13_Microphotography_controled_experimental_conditions.zip</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 13 description: Microphotographs<em> </em>from <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>). Cultures were grown in culture tubes with 10 mL of media, 50 mL Erlenmeyer flasks with 10 mL and 30 mL of media, in YPD under non-shaking and shaking at 250 rpm. YPD media was used across all conditions. Cultures were assessed after 24 hours of growth at 30°C. Pictures were obtained with a Nikon TE2000 microscope using 10x objective.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">Mathematical Model</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 14 name: File_14_Mathematical_model.zip</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 14 description: Mathematical model R code and generated values. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">ARN data</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 15 name: File_15_rnaseq-final-results-Top_v_Bottom.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 15 description: RNA analyses final results Top vs Bottom phenotypic subdistributions. Top is used as control. </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 16 name: File_16_Variant_Call_format_file.vcf</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 16 description: Variant Calling analyses of the sample ARN sample <em>Top 1. </em>Adhesion number: SRR32105384. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">Time-lapse videos</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 17 name: Supp. Video 1. C1W8.1 from 17 to 22 hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 17 description: Supplementary Video 1. Experimentally evolved multicellular yeast video between 17 and 22 hours of growth (C1W8.1-derived strain) — time-lapse video of the formation of a single-cell propagule from a multicellular cluster<strong>. </strong></span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 18 name: Supp. Video 2. Ace2x2KO over 26 hours growth.</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 18 description: Supplementary Video 2. <em>ace2Δ knockout</em> constructed strain growth — time-lapse video of a single large multicellular cluster over 26 hours. </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 19 name: Supp. Video 3. C1W8.1 over 6 hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 19 description: Supplementary Video 3. Experimentally evolved multicellular yeast growth between 6 and 12 hours of growth (C1W8.1-derived strain). </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 20 name: Supp. Video 4. C1W8.1 over 24 hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 20 description: Supplementary Video 4. Experimentally evolved multicellular yeast growth over 24 hours (C1W8.1-derived strain) — cell division stops in small ancestral-like phenotypes. </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 21 name: Supp. Video 5. Ace2x2KO over 24 hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 21 description: Supplementary Video 5. <em>ace2Δ knockout</em> constructed strain growth — time-lapse video of multiple large multicellular clusters over 24 hours. </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 22 name: Supp. Video 6. Ace2x2missense from 0 to 3h45m hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 22 description: Supplementary Video 6. <em>ace2Δ missense</em> constructed strain growth — time-lapse video of multiple large multicellular clusters up to 3 hours 45 min. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">METHODOLOGICAL INFORMATION</span></p> <p><span lang="EN">Strains: ancestral wildtype (Y55 strains), C1W8.1 and C1W8.2 multicellular derived strains isolated after 60 days of selection in YPD media, constructed ACE2 gene knockouts, and strains containing the ACE2 missense mutation (ACE2 <sup>c.1934 A>T</sup>).</span></p> <p><span lang="EN">Media: Growth media used in this study were Yeast Peptone Dextrose media (YPD; 1% (v/w) yeast extract, 2% (v/w) peptone, 2% (v/w) D-glucose, pH 5.8).</span></p> <p><span lang="EN">Phenotypic characterization of the different strains was conducted in a Coulter Counter Multisizer 4 and FlowCam® 3.0 Fluid Imaging Technologies, optic microscopy and a mathematical model. Replicate populations of different individual isolates per strain were analyzed to obtain the population distributions in YPD media.</span></p> <p><span lang="EN">RNA was extracted using an Invitrogen® PureLink RNA Mini Kit. Three out of four extracted samples per treatment with the highest RNA integrity score were submitted for TrueSeq Stranded RNA-Seq. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN">10. Detailed description</span></p> <p><span lang="EN"><span>●<span> </span></span></span><span lang="EN">Coulter Counter size distribution data of all the populations: </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 1 name: File_1_Coulter_Counter_Counts_20h.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 1 description: strains naming convention; strain_Isolate_run.pseudoreplicate. Strains: ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout; C1W8.1= C1W8.1 evolved multicellular strain; C1W8.2= C1W8.2 evolved multicellular strain; Y55= ancestral strain.</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Volume (um3)</span></p> <p><span lang="EN">Column 2: Diameter (um2)</span></p> <p><span lang="EN">Columns 3 to the last column: strains counts.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 2 name: File_2_Coulter_Counter_Counts_24h.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 2 description: strains naming convention; strain_Isolate_run.pseudoreplicate. Strains: ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout; C1W8.1= C1W8.1 evolved multicellular strain; C1W8.2= C1W8.2 evolved multicellular strain; Y55= ancestral strain.</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Volume (um3)</span></p> <p><span lang="EN">Column 2: Diameter (um2)</span></p> <p><span lang="EN">Columns 3 to the last column: strains counts.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 3 name: File_3_Coulter_Counter_Counts_48h.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 3 description: strains naming convention; strain_Isolate_run.pseudoreplicate. Strains: ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout; C1W8.1= C1W8.1 evolved multicellular strain; C1W8.2= C1W8.2 evolved multicellular strain; Y55= ancestral strain.</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Volume (um3)</span></p> <p><span lang="EN">Column 2: Diameter (um2)</span></p> <p><span lang="EN">Column 3 to the last column: strains counts.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File_4_Coulter_Counter_Counts_Constructed_strains_diversity.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 4 description: strains naming convention; strain_Isolate_colony_run.pseudoreplicate. Strains: ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout.</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Volume (um3)</span></p> <p><span lang="EN">Column 2: Diameter (um2)</span></p> <p><span lang="EN">Column 3 to the last column: strains counts.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File_5_Coulter_Counter_Counts_Selection_Experiment.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 5 description: strains naming convention; strain_colony.phenotype_selection.cycle_run.pseudoreplicate. Strains: C1W8.2= C1W8.2 evolved multicellular strain and C1W8.1= C1W8.1 evolved multicellular strain.</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Volume (um3)</span></p> <p><span lang="EN">Column 2: Diameter (um2)</span></p> <p><span lang="EN">Column 3 to the last column: strains counts.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 6 name: File_6_Coulter_Counter_Counts_12h.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 6 description: Size distributions of C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 12-hours growth. Data for: Fig. 3A and Fig. S3. </span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Volume (um3)</span></p> <p><span lang="EN">Column 2: Diameter (um2)</span></p> <p><span lang="EN">Column 3: Time</span></p> <p><span lang="EN">Column 4: replicate</span></p> <p><span lang="EN">Column 5: Strain name (strain_f)</span></p> <p><span lang="EN">Column 6: Isolate (isolate_f)</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 7 name: File_3_Rawdata_Flowcam_all.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 7 description: strains naming convention; ace2_isolate= ACE2 knockout;</span></p> <p><span lang="EN">Ace2m_isolate= strain containing the ACE2 missense mutation (ACE2 <em>c.1934 A>T</em>); c1w82_isolate=C1W8.2 evolved multicellular strain; C1W81_isoalte C1W8.1 evolved multicellular strain; Y55_isolate=ancestral strain. </span></p> <p><span lang="EN">§ Page 1:</span></p> <p><span lang="EN"> Column 1: Particle ID</span></p> <p><span lang="EN"> Column 2: Area ABD</span></p> <p><span lang="EN"> Column 3: Aspect Ratio (Width/Length)</span></p> <p><span lang="EN"> Column 4: Circle Fit</span></p> <p><span lang="EN"> Column 5: Area base Diameter (ABD)</span></p> <p><span lang="EN"> Column 6: Equivalent Spherical Diameter (ESD)</span></p> <p><span lang="EN"> Column 7: Elongation</span></p> <p><span lang="EN"> Column 8: Perimeter</span></p> <p><span lang="EN"> Column 9: Roughness</span></p> <p><span lang="EN"><span> </span><span> </span>Column 10: Volume ABD-based</span></p> <p><span lang="EN"> Column 11: Volume ESD-based</span></p> <p><span lang="EN"> Column 12: Width</span></p> <p><span lang="EN"> Column 13: Source. Name of the sample.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 8 name: File_8_C1W8.2_overlapPairs_Selection_Experiment.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 8 description: C1W8.2 _lineage_selection.cycle= C1W8.2 evolved multicellular strain, lineage (A=ancestral, M1= lineage 1,<span> </span>M2= lineage 2 , M3= lineage 3) and selection cycle<span> </span>(0, 1, 2 and 3).</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Var1= strain 1</span></p> <p><span lang="EN">Column 2: Var2= strain 2</span></p> <p><span lang="EN">Column 3: overlap value of both strains compared.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 9 name: File_9_C1W8.1_overlapPairs_Selection_Experiment.csv</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 9 description: C1W8.1 _lineage_selection.cycle =C1W8.1 evolved multicellular strain, lineage (A=ancestral, M1= lineage 1,<span> </span>M2= lineage 2 , M3= lineage 3) and selection cycle<span> </span>(0, 1, 2 and 3).</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Var1= strain 1</span></p> <p><span lang="EN">Column 2: Var2= strain 2</span></p> <p><span lang="EN">Column 3: overlap value of both strains compared.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 10 name: File_10_overlapPairs_Constructed_strains_diversity.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 10 description: variables naming convention; strain _isolate_colony.number. Strains; ace2x2m=strains containing the ACE2 missense mutation (ACE2 <sup>c.1934 A>T</sup>); ace2x2= ACE2 knockout. Isolate; 1,2 and 3. Colony.number; Initial=initial population and colony number (1,2,3,4 and 5).</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Var1= strain 1</span></p> <p><span lang="EN">Column 2: Var2= strain 2</span></p> <p><span lang="EN">Column 3: overlap value of both strains compared.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 11 name: File_11_ ImageJ _analyses.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 11 description: ImageJ analyses of the microphotographs from <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>). Cultures were grown in culture tubes with 10 mL of media, 50 mL Erlenmeyer flasks with 10 mL and 30 mL of media, in YPD under non-shaking and shaking at 250 rpm. YPD media was used across all conditions. Cultures were assessed after 24 hours growth at 30°C.<span> </span>Microphotographs of each condition and strain were obtained with a Nikon TE2000 microscope using 10x objective.</span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: Var1= strain 1</span></p> <p><span lang="EN">Column 2: </span><span lang="EN">Var2 =<span> strain 2</span></span></p> <p><span lang="EN">Column 3: overlap value of both strains compared.</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 12 name: File_12_ FlowCam_Pictures.zip</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 12 description: FlowCam runs, images, and raw data of <em>Saccharomyces cerevisiae</em> Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 <sup>c.1934 A>T</sup>) in YPD at 24h growth. Data for: Fig. 1B. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 13 name: File_13_Microphotography_controled_experimental_conditions.zip</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 13 description: 149 microphotographs. </span></p> <p><span lang="EN">§ Folder 1:<span> </span>Images </span><span lang="EN">of Erlenmeyer flasks<span> with 30ml of YPD</span></span></p> <p><span lang="EN">§ Folder 2:<span> </span>Images </span><span lang="EN">of <span>Erlenmeyer’s and tubes with 10ml of YPD</span></span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 14 name: File_14_Mathematical_model.zip</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 14 description: Mathematical model, R code, and generated values. </span></p> <p><span lang="EN">§ Document 1:<span> </span>R code of the model</span></p> <p><span lang="EN">§ Document 2:<span> </span>Resulted data from </span><span lang="EN">the <span>mathematical model with different inset</span> <span>values of <em>k</em>, alpha</span>,<span> and beta. </span></span></p> <p><span lang="EN">§ Document 2:<span> </span>Resulted data from the mathematical model with different inset values of <em>k</em>, alpha, gamma, and beta. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 15 name: File_15_rnaseq-final-results-Top_v_Bottom.xlsx</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 15 description: </span></p> <p><span lang="EN">§ Page 1: </span></p> <p><span lang="EN">Column 1: number</span></p> <p><span lang="EN">Column 2: ID</span></p> <p><span lang="EN">Column 3: protID</span></p> <p><span lang="EN"><span> </span>Column 4: gene_symbol<span> </span></span></p> <p><span lang="EN"><span> </span>Column 5: chr</span></p> <p><span lang="EN"><span> </span>Column 6: chr_latin</span></p> <p><span lang="EN">Column 7: location </span></p> <p><span lang="EN">Column 8: baseMean</span></p> <p><span lang="EN"><span> </span>Column 9: log2FoldChange</span></p> <p><span lang="EN">Column 10: lfcSE</span></p> <p><span lang="EN">Column 11: stat</span></p> <p><span lang="EN"><span> </span>Column 12: pvalue<span> </span>padj</span></p> <p><span lang="EN">Column 13: test</span></p> <p><span lang="EN">Column 14: log10padj</span></p> <p><span lang="EN"><span> </span>Column 15: log10baseMean</span></p> <p><span lang="EN">Column 16: blast_pident</span></p> <p><span lang="EN">Column 17: transcript_length</span></p> <p><span lang="EN"><span> </span>Column 18: blast_evalue</span></p> <p><span lang="EN">Column 19: blast_bitscore</span></p> <p><span lang="EN">Column 20: rnaID</span></p> <p><span lang="EN"><span> </span>Column 21: feature</span></p> <p><span lang="EN">Column 22: accession</span></p> <p><span lang="EN">Column 23: strain</span></p> <p><span lang="EN"><span> </span>Column 24: gene_accession</span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 16 name: File_16_Variant_Call_format_file.vcf</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 16 description: Variant Calling analyses of the<span> </span>ARN sample <em>Top 1. </em>Adhesion number: SRR32105384. </span></p> <p><span lang="EN"> </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 17 name: Supp. Video 1. C1W8.1 from 17 to 22 hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 17 description: <strong>Supplementary Video 1. Experimentally evolved multicellular yeast video between 17 and 22 hours of growth (C1W8.1-derived strain) — time-lapse video of the formation of a single-cell propagule from a multicellular cluster. </strong>The time-lapse video captures growth dynamics over this period, highlighting the formation of a single-cell propagule from a multicellular cluster on two occasions (visible in the lower left region of the frame). Images were acquired every 15 minutes using a 10x objective lens. </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 18 name: Supp. Video 2. Ace2x2KO over 26 hours </span><span lang="EN">of <span>growth.</span></span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 18 description: <strong>Supplementary Video 2. <em>ace2Δ knockout</em></strong> <strong>constructed strain growth</strong> <strong>— time-lapse video of a single large multicellular cluster over 26 hours.</strong> The video captures large, multicellular clusters that produce both large, multicellular and small, ancestral-like clusters. The video shows a single large multicellular cluster fragmenting into two large multicellular clusters at ~ 13 hours of growth (from 02:09 to 02:10 minutes in the time-lapse) and generating two small ancestral-like propagules at ~19 hours of growth (from 03:07 to 03:09 minutes in the time-lapse). Microphotographs were obtained at 3-minute intervals under a 10x objective over 26 hours. </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 19 name: Supp. Video 3. C1W8.1 over 6 hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 19 description: <strong>Supplementary Video 3. Experimentally evolved multicellular yeast growth between 6 and 12 hours of growth (C1W8.1-derived strain). </strong>The time-lapse video captures large, multicellular clusters of the C1W8.1 strains, which produce both large, multicellular and small, ancestral-like clusters. Additionally, small ancestral-like clusters are observed undergoing cellular division <strong>—</strong>no separation is observed<strong>—</strong> during the first 2 to 3 hours, followed by a cessation of division for the remainder of the time-lapse. Images were acquired every 30 seconds using a 10x objective lens.</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 20 name: Supp. Video 4. C1W8.1 over 24 hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 20 description: <strong>Supplementary Video 4. Experimentally evolved multicellular yeast growth over 24 hours (C1W8.1-derived strain) — cell division stops in small ancestral-like phenotypes. </strong>The footage captures multiple large multicellular clusters undergoing fragmentation into propagules. Additionally, a small ancestral-like cluster is observed undergoing division during the first 2 to 3 hours, followed by a cessation of division for the remainder of the time-lapse (visible in the lower left region of the frame). This early division phase is evident during the first 10 seconds of the video. Images were acquired every 5 minutes using a 10x objective lens. </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 21 name: Supp. Video 5. Ace2x2KO over 24 hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 21 description: <strong>Supplementary Video 5. <em>ace2Δ knockout</em> constructed strain growth</strong> <strong>— time-lapse video of multiple large multicellular clusters over 24 hours.</strong> The video shows multiple large multicellular clusters fragmenting into large clusters and several small ancestral-like clusters being dragged by Brownian motion and evaporation of the sample. Microphotographs were obtained at fixed intervals of 3 minutes under the 10x objective over 24 hours. </span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 22 name: Supp. Video 6. Ace2x2missense from 0 to 3h45m hours growth</span></p> <p><span lang="EN"><span>o<span> </span></span></span><span lang="EN">File 22 description: <strong>Supplementary Video 6. <em>ace2Δ missense</em> constructed strain growth</strong> <strong>— time-lapse video of multiple large multicellular clusters up to 3 hours 45 min.</strong> The video shows multiple large multicellular clusters fragmenting into large clusters</span><span lang="EN">,<span> generating two small ancestral-like propagules before being dragged by Brownian motion and evaporation of the sample. Microphotographs were obtained at </span>3-minute intervals <span>under the 10x objective. </span></span></p> <p><span lang="EN"> </span></p> <p> </p>
Phenotypic differences between interfertile Chlamydomonas species- timelapse microscopy data, part 2
<p>This repository contains timelapse microscopy data of two interfertile <i>Chlamydomonas</i> 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 <i>Chlamydomonas</i> 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. Timelapse data of <i>C. reinhardtii </i>or C<i>. smithii </i>cells in agar microchamber wells from experiments "3" and "4" are shared here.</p><h4>Reference</h4><p><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 <i>Chlamydomonas </i>species</a></p><h4>Notes</h4><p>Experiment 3, performed on 230519: DIC timelapse data of <i>Chlamydomonas</i> cells swimming in agar microchamber wells. In some of the wells, external fluid movement modified the cell motility patterns.</p><p>Experiment 4, performed on 230523: DIC timelapse data of <i>Chlamydomonas </i>cells swimming in agar microchamber wells.</p><p>"Cr" indicates <i>Chlamydomonas reinhardtii</i></p><p>"Cs" indicates <i>Chlamydomonas smithii</i></p><p>Timelapse frames: 3601 frames</p><p>Frame rate: 20 frames per second (fps)</p><p>Pixel size: 0.6398 microns/pixel</p>
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