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zenodo40/100

Data from: Stochastic phenotypic switching arises in response to directional selection in experimentally evolved multicellular yeast.

This BBC_2025__README.txt file was generated on 2025-09-24 by Beatriz Baselga Cervera GENERAL INFORMATION <ol> <li>Title of Dataset and code: Data from: Stochastic phenotypic switching arises in response to directional selection in experimentally evolved multicellular yeast.</li> </ol>   2. Author Information             Corresponding Investigator                         Name: Ph.D. Beatriz Baselga-Cervera                         Institution: University of Minnesota Twin cities, Minnesota, US.                         Email: <a href="mailto:bbaselga@umn.edu">bbaselga@umn.edu</a>; beabaselga@gmail.com             Co-investigator 1                         Name: Ph.D. Nahui Olin Medina-Chávez                         Institution: University of Minnesota Twin cities, Minnesota, US.                         Email: nmedinac@umn.edu             Co-investigator 2                         Name: Ph.D. Noah Gettle                         Institution: Wellcome Sanger Institute, Hinxton, UK.                         Email: nbgettle@gmail.com Co-investigator 3                         Name: Ph.D. Michael Travisano                         Institution: University of Minnesota Twin cities, Minnesota, US.                         Email: travisan@umn.edu     3. Data collectors: Ph.D. Beatriz Baselga-Cervera, Ph.D. Nahui Olin Medina-Chávez & Ph.D. Noah Gettle.   4. Date of data collection: 2022-2024   5. Geographic location of data collection: Saint Paul, US   6. Funding sources that supported the collection of the data: Fundación Alfonso Martín Escudero, Madrid, Spain (BBC).   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.     DATA & FILE OVERVIEW   8. Description of dataset 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 Saccharomyces cerevisiae 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 Saccharomyces cerevisiae 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).   9. File list: ●      Coulter Counter size distribution data:  o   File 1 name:  File_1_Coulter_Counter_Counts_20h.csv o   File 1 description: Size distributions of Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 20-hours growth. Data for: Fig. 1A, Fig. 3A and Fig. S2, Table S2 and Table S3.   o   File 2 name:  File_2_Coulter_Counter_Counts_24h.csv o   File 2 description: Size distributions of Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 24-hours growth. Data for: Fig. 1A, Fig. 3A, Fig. S2, Table S2 and Table S3.   o   File 3 name:  File_3_Coulter_Counter_Counts_48h.csv o   File 3 description: Size distributions of Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 48-hours growth. Data for: Fig. 1, Fig. 3A, Fig. S2, Table S2 and Table S3.   o   File name:  File_4_Coulter_Counter_Counts_Constructed_strains_diversity.csv o   File 4 description: Size distributions of the constructed ACE2 knockout and a strain containing the homozygous missense mutation (ACE2 c.1934 A>T) 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.   o   File 5 name:  File_5_Coulter_Counter_Counts_Selection_Experiment.xlsx o   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.   o   File 6 name:  File_6_Coulter_Counter_Counts_12h.xlsx o   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 c.1934 A>T) in YPD at 12-hours growth. Data for: Fig. 3A and Fig. S3.     ●      FlowCam data: o   File 7 name: File_7_Rawdata_FlowCam_all.csv o   File 7 description: FlowCam data from Saccharomyces cerevisiae 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.     ●      Data generated statistically: o   File 8 name: File_8_C1W8.2_overlapPairs_Selection_Experiment.csv o   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.   o   File 9 name: File_9_C1W8.1_overlapPairs_Selection_Experiment.csv o   File 9 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data o   of the C1W8.1 derived strain over the selection experiment. Data for: Fig. S6C.     o   File 10 name: File_10_ overlapPairs_Constructed_strains_diversity.xlsx o   File 10 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data of the constructed ACE2 knockout and a strain containing the homozygous missense mutation (ACE2 c.1934 A>T) 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.   ●      Data from ImageJ: o   File 11 name: File_11_ImageJ_analyses.xlsx o   File 11 description: ImageJ analyses of the microphotographs from Saccharomyces cerevisiae 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). 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.  Microphotographs of each condition and strain were obtained with a Nikon TE2000 microscope using 10x objective.   ●      Pictures: o   File 12 name: File_12_ FlowCam_Pictures.zip o   File 12 description FlowCam IMAGES from Saccharomyces cerevisiae 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. 1B.   o   File 13 name: File_13_Microphotography_controled_experimental_conditions.zip o   File 13 description: Microphotographs from Saccharomyces cerevisiae 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). 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.     ●      Mathematical Model o   File 14 name: File_14_Mathematical_model.zip o   File 14 description: Mathematical model R code and generated values.   ●      ARN data o   File 15 name: File_15_rnaseq-final-results-Top_v_Bottom.xlsx o   File 15 description: RNA analyses final results Top vs Bottom phenotypic subdistributions. Top is used as control. o   File 16 name: File_16_Variant_Call_format_file.vcf o   File 16 description: Variant Calling analyses of the sample ARN sample Top 1. Adhesion number: SRR32105384.   ●      Time-lapse videos o   File 17 name: Supp. Video 1. C1W8.1 from 17 to 22 hours growth o   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. o   File 18 name: Supp. Video 2. Ace2x2KO over 26 hours growth. o   File 18 description: Supplementary Video 2. ace2Δ knockout constructed strain growth — time-lapse video of a single large multicellular cluster over 26 hours. o   File 19 name: Supp. Video 3. C1W8.1 over 6 hours growth o   File 19 description: Supplementary Video 3. Experimentally evolved multicellular yeast growth between 6 and 12 hours of growth (C1W8.1-derived strain). o   File 20 name: Supp. Video 4. C1W8.1 over 24 hours growth o   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. o   File 21 name: Supp. Video 5. Ace2x2KO over 24 hours growth o   File 21 description: Supplementary Video 5. ace2Δ knockout constructed strain growth — time-lapse video of multiple large multicellular clusters over 24 hours. o   File 22 name: Supp. Video 6. Ace2x2missense from 0 to 3h45m hours growth o   File 22 description: Supplementary Video 6. ace2Δ missense constructed strain growth — time-lapse video of multiple large multicellular clusters up to 3 hours 45 min.   METHODOLOGICAL INFORMATION 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 c.1934 A>T). 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). 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. 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.     10. Detailed description ●      Coulter Counter size distribution data of all the populations:  o   File 1 name:  File_1_Coulter_Counter_Counts_20h.csv o   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. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Columns 3 to the last column: strains counts.   o   File 2 name:  File_2_Coulter_Counter_Counts_24h.csv o   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. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Columns 3 to the last column: strains counts.   o   File 3 name:  File_3_Coulter_Counter_Counts_48h.csv o   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. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Column 3 to the last column: strains counts.   o   File_4_Coulter_Counter_Counts_Constructed_strains_diversity.csv o   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. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Column 3 to the last column: strains counts.   o   File_5_Coulter_Counter_Counts_Selection_Experiment.xlsx o   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. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Column 3 to the last column: strains counts.   o   File 6 name:  File_6_Coulter_Counter_Counts_12h.xlsx o   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 c.1934 A>T) in YPD at 12-hours growth. Data for: Fig. 3A and Fig. S3. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Column 3: Time Column 4: replicate Column 5: Strain name (strain_f) Column 6: Isolate (isolate_f)         o   File 7 name: File_3_Rawdata_Flowcam_all.csv o   File 7 description: strains naming convention; ace2_isolate= ACE2 knockout; Ace2m_isolate= strain containing the ACE2 missense mutation (ACE2 c.1934 A>T); c1w82_isolate=C1W8.2 evolved multicellular strain; C1W81_isoalte C1W8.1 evolved multicellular strain; Y55_isolate=ancestral strain. §  Page 1:                                                                         Column 1: Particle ID                                                                         Column 2: Area ABD                                                                         Column 3: Aspect Ratio (Width/Length)                                                                         Column 4: Circle Fit                                                                         Column 5: Area base Diameter (ABD)                                                                         Column 6: Equivalent Spherical Diameter (ESD)                                                                         Column 7: Elongation                                                                         Column 8: Perimeter                                                                         Column 9: Roughness                         Column 10: Volume ABD-based                                                                         Column 11: Volume ESD-based                                                                         Column 12: Width                                                                         Column 13: Source. Name of the sample.   o   File 8 name: File_8_C1W8.2_overlapPairs_Selection_Experiment.csv o   File 8 description: C1W8.2 _lineage_selection.cycle= C1W8.2 evolved multicellular strain, lineage (A=ancestral, M1= lineage 1,  M2= lineage 2 , M3= lineage 3) and selection cycle  (0, 1, 2 and 3). §  Page 1: Column 1: Var1= strain 1 Column 2: Var2= strain 2 Column 3: overlap value of both strains compared.   o   File 9 name: File_9_C1W8.1_overlapPairs_Selection_Experiment.csv o   File 9 description: C1W8.1 _lineage_selection.cycle =C1W8.1 evolved multicellular strain, lineage (A=ancestral, M1= lineage 1,  M2= lineage 2 , M3= lineage 3) and selection cycle  (0, 1, 2 and 3). §  Page 1: Column 1: Var1= strain 1 Column 2: Var2= strain 2 Column 3: overlap value of both strains compared.   o   File 10 name: File_10_overlapPairs_Constructed_strains_diversity.xlsx o   File 10 description: variables naming convention; strain _isolate_colony.number. Strains; ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout. Isolate; 1,2 and 3. Colony.number; Initial=initial population and colony number (1,2,3,4 and 5). §  Page 1: Column 1: Var1= strain 1 Column 2: Var2= strain 2 Column 3: overlap value of both strains compared.   o   File 11 name: File_11_ ImageJ _analyses.xlsx o   File 11 description: ImageJ analyses of the microphotographs from Saccharomyces cerevisiae 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). 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.  Microphotographs of each condition and strain were obtained with a Nikon TE2000 microscope using 10x objective. §  Page 1: Column 1: Var1= strain 1 Column 2: Var2 = strain 2 Column 3: overlap value of both strains compared.     o   File 12 name: File_12_ FlowCam_Pictures.zip o   File 12 description: FlowCam runs, images, and raw data of Saccharomyces cerevisiae 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. 1B.   o   File 13 name: File_13_Microphotography_controled_experimental_conditions.zip o   File 13 description: 149 microphotographs. § Folder 1:  Images of Erlenmeyer flasks with 30ml of YPD § Folder 2:  Images of Erlenmeyer’s and tubes with 10ml of YPD   o   File 14 name: File_14_Mathematical_model.zip o   File 14 description: Mathematical model, R code, and generated values. §  Document 1:  R code of the model §  Document 2:  Resulted data from the mathematical model with different inset values of k, alpha, and beta. §  Document 2:  Resulted data from the mathematical model with different inset values of k, alpha, gamma, and beta.       o   File 15 name: File_15_rnaseq-final-results-Top_v_Bottom.xlsx o   File 15 description: §  Page 1: Column 1: number Column 2: ID Column 3: protID             Column 4: gene_symbol                     Column 5: chr             Column 6: chr_latin Column 7: location Column 8: baseMean             Column 9: log2FoldChange Column 10: lfcSE Column 11: stat             Column 12: pvalue     padj Column 13: test Column 14: log10padj             Column 15: log10baseMean Column 16: blast_pident Column 17: transcript_length             Column 18: blast_evalue Column 19: blast_bitscore Column 20: rnaID             Column 21: feature Column 22: accession Column 23: strain             Column 24: gene_accession   o   File 16 name: File_16_Variant_Call_format_file.vcf o   File 16 description: Variant Calling analyses of the  ARN sample Top 1. Adhesion number: SRR32105384.   o   File 17 name: Supp. Video 1. C1W8.1 from 17 to 22 hours growth o   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. 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.  o   File 18 name: Supp. Video 2. Ace2x2KO over 26 hours of growth. o   File 18 description: Supplementary Video 2. ace2Δ knockout constructed strain growth — time-lapse video of a single large multicellular cluster over 26 hours. 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.   o   File 19 name: Supp. Video 3. C1W8.1 over 6 hours growth o   File 19 description: Supplementary Video 3. Experimentally evolved multicellular yeast growth between 6 and 12 hours of growth (C1W8.1-derived strain). 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 —no separation is observed— 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. o   File 20 name: Supp. Video 4. C1W8.1 over 24 hours growth o   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. 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.  o   File 21 name: Supp. Video 5. Ace2x2KO over 24 hours growth o   File 21 description: Supplementary Video 5. ace2Δ knockout constructed strain growth — time-lapse video of multiple large multicellular clusters over 24 hours. 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.  o   File 22 name: Supp. Video 6. Ace2x2missense from 0 to 3h45m hours growth o   File 22 description: Supplementary Video 6. ace2Δ missense constructed strain growth — time-lapse video of multiple large multicellular clusters up to 3 hours 45 min. The video shows multiple large multicellular clusters fragmenting into large clusters, generating two small ancestral-like propagules before being dragged by Brownian motion and evaporation of the sample. Microphotographs were obtained at 3-minute intervals under the 10x objective.

opencc-by-4.0Sep 2024View details →

dryad40/100

Body size modulates the extent of seasonal diet switching by large mammalian herbivores in Yellowstone National Park

<div> Large mammalian herbivores vary their diets markedly with changes in resource availability yet the ways that seasonal changes in individual foraging behaviors scale up to reconfigure complex trophic networks are poorly understood. Two years of dietary DNA data enabled us to quantify fine-grained dietary variation within and among populations of five large herbivore species at Yellowstone National Park, revealing remarkably strong and significant correlations between body size and five key indicators of diet seasonality (R2 = 0.71–0.80). Data from GPS collars implicated seasonal changes in each species' movement- and habitat-use patterns as potential determinants of foraging constraints and specializations that give rise to the strong allometry in diet composition. Bison and elk showed relatively muted seasonal changes compared to smaller species that exhibited stronger switches. Whereas the taxonomic breadth of individual diets contracted for all species in winter, larger species generally consumed a greater functional diversity of plants and thus maintained more unique dietary niches under resource limitations. </div>

opencc-zeroNov 2023View details →

zenodo40/100

Linking diet switching to reproductive performance across populations of two Critically Endangered mammalian herbivores

Data associated with Harvey Sky, N., Britnell, J., Antwis, R. et al. Linking diet switching to reproductive performance across populations of two critically endangered mammalian herbivores. Commun Biol 7, 333 (2024). https://doi.org/10.1038/s42003-024-05983-3 The data deposited here includes raw metabarcoding output fasta files and some processed metabarcoding and sample data in xslx files. We include a more detailed description of each file below. Data regarding Kenyan black rhino and Grevy’s zebra are treated as sensitive and confidential. There are therefore restrictions on the data that we can make available. Due to these confidentiality considerations, the sample data stored here does not include locations of sample collection within each reserve for either species, or the identity or breeding data for black rhino. It also only includes the final processed values for NDVI and rainfall. The remote sensing data is available from the repositories cited in the methods, but we cannot provide the shapefiles or other data used to calculate the final values for each sample.  Raw fasta files_plants.zip A zipped folder containing the raw fasta files which were the output from the MiSeq sequencing of dietary plants in the faecal samples for both black rhino and Grevy's zebra. Within the zipped folder, the first part of the title of each fasta.gz file is the sample code (S1, S2, S3 etc), which allows you to cross reference these files with the sample data and processed sequencing data in the xslx files. Files with R1 in the title are foward reads, and R2 are reverse reads.  Raw fasta files_bacteria.zip A zipped folder containing the raw fasta files which were the output from the MiSeq sequencing of microbiome bateria in the faecal samples for both black rhino and Grevy's zebra. Within the zipped folder, the first part of the title of each fasta.gz file is the sample code (S1, S2, S3 etc), which allows you to cross reference these files with the sample data and processed sequencing data in the xslx files. Files with R1 in the title are foward reads, and R2 are reverse reads.  Sample data and processed metabarcoding data_Black rhino.xlsx Sample data tab The data that we are able to share that is associated with each black rhino sample. SampleID - The code used to identiy each sample which allows it be cross-referenced with other tabs and the fasta files.  IndividualID - We are not able to share rhino names or other identifiers, but we have given each individual a unique number so that it can be seen which samples came from the same individuals.  NDVI - Mean NDVI of each individual's area of utilisation in the 10-day period  within which the sample was collected. The method used to calculate this is described in the methods of the article.  Rainfall - Cumulative rainfall over the 30 days previous to sample collection for the 0.05 degree pixel under the sample. The method used to calculate this is described in the methods of the article.  Season - Post is the post-rain sampling season June-July 2018. Pre is the pre-rain sampling season January-March 2019.  Reserve - The reserve that the sample was collected on.  Date - The date of sample collection.  Dietary breadth - Shannon-Wiener index of dietary alpha diversity. The method used to calculate this is described in the methods of the article. NA signifies that the number of reads returned for that sample was under the threshold that signified sequencing failure for the dietary plant metabarcoding. Poaceae, Fabaceae, Ebenaceae - The relative abundance of each of these three dietary plant families that were the focus of our analyses. The method used to calculate these is described in the methods of the article. NA signifies that the number of reads returned for that sample was under the threshold that signified sequencing failure for the dietary plant metabarcoding. Bacteria numbers of reads The number of reads assigned to each bacterial ASV found in each sample.  Bacteria sequences and reads The sequence of each ASV, and the taxa assigned to each sequence in the microbiome metabarcoding. The method for taxonomic assignment is described in the methods of the article.  Plant numbers of reads The number of reads assigned to each dietary plant ASV found in each sample.  Plant sequences and reads The sequence of each ASV, and the taxa assigned to each sequence in the dietary plant metabarcoding. The method for taxonomic assignment is described in the methods of the article.    Sample data and processed metabarcoding data_Grevy's zebra.xlsx Sample data tab The data that we are able to share that is associated with each Grevy's zebra sample. Sample ID - The code used to identiy each sample which allows it be cross-referenced with other tabs and the fasta files.  NDVI - Mean NDVI of each individual's area of utilisation in the 10-day period  within which the sample was collected. The method used to calculate this is described in the methods of the article.  Rainfall - Cumulative rainfall over the 30 days previous to sample collection for the 0.05 degree pixel under the sample. The method used to calculate this is described in the methods of the article.  Reserve - The reserve that the sample was collected on.  Season - Post is the post-rain sampling season July-August 2018. Pre is the pre-rain sampling season January-February 2019.  Date - The date of sample collection.  Dietary breadth - Shannon-Wiener index of dietary alpha diversity. The method used to calculate this is described in the methods of the article.  Poaceae, Fabaceae - The relative abundance of each of these two dietary plant families that were the focus of our analyses. The method used to calculate these is described in the methods of the article. NA signifies that the number of reads returned for that sample was under the threshold that signified sequencing failure for the dietary plant metabarcoding. Indigofera - The relative abundance of each of this Fabaceae genus was included in our analyses. The method used to calculate these is described in the methods of the article. NA signifies that the number of reads returned for that sample was under the threshold that signified sequencing failure for the dietary plant metabarcoding. Bacteria numbers of reads The number of reads assigned to each bacterial ASV found in each sample.  Bacteria sequences and reads The sequence of each ASV, and the taxa assigned to each sequence in the microbiome metabarcoding. The method for taxonomic assignment is described in the methods of the article.   Plant numbers of reads The number of reads assigned to each dietary plant ASV found in each sample.  Plant sequences and reads The sequence of each ASV, and the taxa assigned to each sequence in the dietary plant metabarcoding. The method for taxonomic assignment is described in the methods of the article.

opencc-by-4.0Jan 2024View details →

zenodo40/100

Data from: Topological nano-switches in higher-order topological insulators

This repository provides data underlying the figures in the manuscript titled 'Topological nano-switches in higher-order topological insulators'. The data is given in CSV-format and the data files are named after their respective figures. The data corresponding to figure 2 is provided separately for the four field orientations in each panel of the figure, and contains the probability density on each site of the discretized system as a 2D array.  Similarly, the data for figure C1 is provided separately. The other files contain the scattering matrix elements in columns labeled 'ij', with each row corresponding to an orientation of the magnetic field in the range [0, 2π] listed in the column labeled 'theta'.  The data was generated using Kwant, a free (open source), powerful, and easy to use Python package for numerical calculations on tight-binding models. An example of how the studied systems were constructed is included in 'higher_order_ti_nano_switches.py', and contains the code to calculate the corresponding scattering matricies for a chosen set of parameters. The probability density included in the data related to figure 2 can similarly be extracted from the discretized system. See '<a href="https://kwant-project.org/">kwant-project.org</a>' for additional details.

opencc-by-4.0Feb 2024View details →

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Dataset of "Switching Response in Organic Electrochemical Transistors by Ionic Diffusion and Electronic Transport"

This dataset underpins the following article published in the Advanced Science: "Switching Response in Organic Electrochemical Transistors by Ionic Diffusion and Electronic Transport"   Raw and processed data for the article "Switching Response in Organic Electrochemical Transistors by Ionic Diffusion and Electronic Transport". For further details see the readme.txt file.

opencc-by-4.0Apr 2024View details →

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Dataset of the publication: Spin-crossover nanoparticles anchored on MoS2 layers for heterostructures with tunable strain driven by thermal or light-induced spin switching

Dataset of the publication:  <div>Spin-crossover nanoparticles anchored on MoS2 layers for heterostructures with tunable strain driven by thermal or light-induced spin switching</div> <div> <div>https://doi.org/10.1038/s41557-021-00795-y</div> <div>R. Torres-Cavanillas, M. Morant-Giner, G. Escorcia-Ariza, J. Dugay, J. Canet-Ferrer, S. Tatay, S. Cardona-Serra, M. Giménez-Marqués, M. Galbiati, A. Forment-Aliaga, E. Coronado, Nat Chem 2021, 13, 1101.</div> </div>

opencc-by-4.0Nov 2024View details →

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Dataset of the publication: Strain Switching in van der Waals Heterostructures Triggered by a Spin-Crossover Metal–Organic Framework

Dataset of the publication: Strain Switching in van der Waals Heterostructures Triggered by a Spin-Crossover Metal–Organic Framework DOI: 10.1002/adma.202110027 Boix-Constant, Carla; Garcia-Lopez, Victor; Navarro-Moratalla, Efren; Clemente-Leon, Miguel; Zafra, Jose Luis; Casado, Juan; Guinea, Francisco; Manas-Valero, Samuel; Coronado, Eugenio  Adv. Mater. 34, 2110027 (2022)

opencc-by-4.0Nov 2024View details →

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Dataset of the publication: Multistep magnetization switching in orthogonally twisted ferromagnetic monolayers

Dataset of the publication: Multistep magnetization switching in orthogonally twisted ferromagnetic monolayers DOI: 10.1038/s41563-023-01735-6 Boix-Constant, C; Jenkins, S; Rama-Eiroa, R; Santos, EJG; Mañas-Valero, S; Coronado, E Nat. Mater. 23, 212–218 (2024)

opencc-by-4.0Nov 2024View details →

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Dataset of the publication: Sublimable complexes with spin switching: Chemical design, processing as thin films and integration in graphene-based devices

Dataset of the publication: Sublimable complexes with spin switching: Chemical design, processing as thin films and integration in graphene-based devices DOI: 10.1039/d2tc04120k M. Guevara-Edo, F. J. Valverde-Muñoz, R. Cordoba, M. C. Muñoz, J. Herrero-Martín, J. A. Real, E. Coronado J. Mater. Chem. C, 11, 24, 8107-8120 (2023)

opencc-by-4.0Dec 2024View details →

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Data for Falgenhauer, et al., "Transcriptional interference in toehold switch-based RNA circuits"

Contains DNA sequences of the gene specific primers for RT-qPCR, the RT-qPCR raw data and output files used in "Transcriptional interference in toehold switch-based RNA circuits" by Falgenhauer et al.

opencc-by-4.0Mar 2022View details →

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A Large Scale Fabrication of Graphene Based Nano-electromechanical Contact Switches With Ultra-low Pull-in Voltage [Dataset]

Original data set for the 'A Large Scale Fabrication of Graphene Based Nano-electromechanical Contact Switches With Ultra-low Pull-in Voltage' is uploaded.

opencc-by-4.0Dec 2021View details →

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Strand-switching mechanism of Pif1 helicase induced by its collision with a G-quadruplex embedded in dsDNA_data_NAR

This document includes data corresponding to the paper entitled :"Strand-switching mechanism of Pif1 helicase induced by its collision with a G-quadruplex embedded in dsDNA" published in Nucleic Acid Research, 2022. The link to the zenodo depository of the homemade software to open the data is given in the readme.txt file as well as the way the data files are organized

opencc-by-4.0Jul 2022View details →

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Figure 1 in How Spiromesifen affects some biological parameters and switching behavior of predatory mite Amblyseius swirskii (Acari: Phytoseiidae) when feeding on different ratios of mixed preys

Figure 1. Linear relation between initial number of Bemisia tabaci (left)/ Tetranychus urticae (right) treated with recommended concentration of Spiromesifen and number of preys eaten by predatory mite Amblyseius swirskii.

opencc-by-4.0Jul 2019View details →

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Figure 2 in How Spiromesifen affects some biological parameters and switching behavior of predatory mite Amblyseius swirskii (Acari: Phytoseiidae) when feeding on different ratios of mixed preys

Figure 2. Fitted regression equation between the proportion of consumed mite to total preys and preference index (β) of Amblyseius swirskii.

opencc-by-4.0Jul 2019View details →

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Survival-associated cellular response maintained in pancreatic ductal adenocarcinoma (PDAC) switched between soft and stiff 3D microgel culture

<div> <div> <div> <div> Pancreatic ductal adenocarcinoma (PDAC) accounts for about 90% of all pancreatic cancer cases. Five-year survival rates have remained below 12% since the 1970s, in part due to the difficulty in detection before metastasis (migration and invasion into neighboring organs and glands). Mechanical memory is a concept that has emerged over the past decade that may provide a path towards understanding how invading PDAC cells "remember" the mechanical properties of their diseased ("stiff," elastic modulus, E ≈ 10 kPa) microenvironment even whilst invading a healthy ("soft," E ≈ 1 kPa) microenvironment. Here, we investigated the role of mechanical priming by culturing a dilute suspension of PDAC (FG) cells within a 3D, rheologically tunable microgel platform from hydrogels with tunable mechanical properties. We conducted a suite of acute (short-term) priming studies where we cultured PDAC cells in either a soft (E ≈ 1 kPa) or stiff (E ≈ 10 kPa) environment for 6 h, then removed and placed them into a new soft or stiff 3D environment for another 18 h. Following these steps, we conducted RNA-seq analyses to quantify gene expression. Initial priming in 3D culture showed persistent gene expression for the duration of the study, regardless of the subsequent environments (stiff or soft). Stiff 3D culture was associated with the down-regulation of tumor suppressors (LATS1, BCAR3, CDKN2C ), as well as the up-regulation of cancer-associated genes (RAC3). Immunofluorescence staining (BCAR3, RAC3) further supported the persistence of this cellular response, with BCAR3 upregulated in soft culture, and RAC3 upregulated in stiff-primed culture. Stiff-primed genes were stratified against patient data found in The Cancer Genome Atlas (TCGA). Upregulated genes in stiff-primed 3D culture were associated with decreased survival in patient data, suggesting a link between patient survival and mechanical priming. </div> </div> </div> </div>

opencc-zeroApr 2024View details →

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Dataset for "Self-heating effects and switching dynamics in graphene multiterminal Josephson junctions"

Dataset containing raw measurement data and simulation results for the manuscript "Self-heating effects and switching dynamics in graphene multiterminal Josephson junctions".

opencc-by-4.0Jun 2024View details →

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Reactivity Switch of Platinum with Gallium: From Reverse Water Gas Shift to Methanol Synthesis

The development of efficient catalysts for the hydrogenation of CO2 to methanol using “green” H2 is foreseen to be a key step to close the carbon cycle. In this study, we show that small and narrowly distributed alloyed PtGa nanoparticles supported on silica, prepared via a surface organometallic chemistry (SOMC) approach, display notable activity for the hydrogenation of CO2 to methanol, reaching 7.2 mol h-1 molPt-1 methanol formation rate with a 54% intrinsic CH3OH selectivity. This reactivity sharply contrasts with what is expected for Pt, which favors the reverse water gas shift reaction, albeit with a poor activity (2.6 mol h-1 molPt-1). In situ XAS studies indicate that ca. 50% of Ga is reduced to Ga0 yielding alloyed PtGa nanoparticles, while the remaining 50% persist as isolated GaIII sites. The PtGa catalyst slightly dealloys under CO2 hydrogenation conditions and displays redox dynamics with PtGa-GaOx interfaces, responsible for promoting both CO2 hydrogenation activity and methanol selectivity. Further tailoring the catalyst interface by using a carbon support in place of silica enables to improve the methanol formation rate by a factor of ~5.

opencc-by-4.0Apr 2024View details →

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Pre- and post-association barriers to host switching in sympatric mutualists

Coevolution between mutualists can lead to reciprocal specialization, potentially causing barriers to host switching. In the present study, we conducted assays to identify pre- and post-association barriers to host switching by endosymbiotic bacteria, both within and between two sympatric nematode clades. In nature, Steinernema nematodes and Xenorhabdus bacteria form an obligate mutualism. Free-living juvenile nematodes carry Xenorhabdus in a specialized intestinal receptacle. When nematodes enter an insect, they release the bacteria into the insect hemocoel. The bacteria aid in killing the insect and facilitate nematode reproduction. Prior to dispersing from the insect, juvenile nematodes must form an association with their symbionts; the bacteria must adhere to the intestinal receptacle. We tested for pre-association barriers by comparing the effects of bacterial strains on native verses non-native nematodes via their virulence towards, nutritional support of, and ability to associate with different nematode species. We then assessed post-association barriers by measuring the relative fitness of nematodes carrying each strain of bacteria. We found evidence for both pre- and post-association barriers between nematode clades. Specifically, some bacteria were highly virulent to nonnative hosts, and some nematode hosts carried fewer cells of nonnative bacteria, leading to pre-association barriers. In addition, reduced infection success and lower nematode reproduction were identified as post-association barriers. No barriers to symbiont switching were detected between nematode species within the same clade. Overall, our study suggests a framework that could be used to generate predictions for the evolution of barriers to host switching in this and other systems.

opencc-zeroJun 2024View details →

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FIGURE 1 in Coming out of your shell or crawling back in: multiple interphylum host switching events within a clade of bivalve- and ascidian-associated shrimps (Caridea: Palaemonidae)

FIGURE 1 An overview of the diversity in morphology, colouration, and host-associations of the studied clade. A, Anchiopontonia hurii (Holthuis, 1981) in the spiny oyster Spondylus sp.; B, Ascidonia quasipusilla (Chace, 1972) in a solitary ascidian; C, Conchodytes meleagrinae Peters, 1852 in the spiny oyster Spondylus sp.; D, Conchodytes pteriae Fransen, 1994 in the pearl oyster Pteria loveni (Dunker, 1879); E, male-female pair of Dactylonia ascidicola (Borradaile, 1898) from the solitary ascidian Ascidia sp.; F, Odontonia katoi (Kubo, 1940) in the solitary ascidian Polycarpa aurata (Quoy & Gaimard, 1834); G, Odontonia plurellicola De Gier & Fransen, 2018 in the colonial ascidian Plurella sp.; H, Odontonia sibogae (Bruce, 1973) in the solitary ascidian Polycarpa sp.; I, Platypontonia hyotis Hipeau-Jacquotte, 1971 in the giant honeycomb oyster Hyotissa hyotis (Linnaeus, 1758); J, Pontonia manningi Fransen, 2000 in the spiny oyster Spondylus americanus Hermann, 1781. PHOTO CREDIT: C.H.J.M. FRANSEN

opencc-by-4.0May 2022View details →

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FIGURE 5 in Coming out of your shell or crawling back in: multiple interphylum host switching events within a clade of bivalve- and ascidian-associated shrimps (Caridea: Palaemonidae)

FIGURE 5 Phylogeny based on the RAxML tree topology of the TE approach (fig. 4), with ancestral biogeographic range reconstructions on the internal nodes (probabilities are shown as pie charts). Indo-West Pacific genera simplified as genus names, except for Odontonia kerangcaris Fransen, Groenhof & De Gier, 2021 due to its position outside of the genus. Colours indicate distribution ranges, both for the species as well as the ancestral distribution ranges. Species/genera of which only morphological data was analysed are indicated with an asterisk (*).

opencc-by-4.0May 2022View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record