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Selected data(s) from : Femtosecond direct laser writing of silver clusters in phosphate glasses for x-ray spatially-resolved dosimetry
<p>The data selected is based on the figures below, published in the linked article (see the doi).</p> <p><strong>- Figure 1.</strong> Microscopy fluorescence image of ARGOi glass sample (excitation at 365 nm) of laser-inscribed structures for the different writing irradiances at two different depths: (<strong>a</strong>) structures at 150 µm below the glass front surface, (<strong>b</strong>) structures at 550 µm below the glass front surface, and at 150 µm from the glass rear surface. <strong>(Only picture)</strong></p> <p>- <strong>Figure 2.</strong> (<strong>a</strong>) Transparent color before irradiation (ARGO glass sample), (<strong>b</strong>) yellow color after X-ray irradiation with 222 Gy (ARGO* glass sample). <strong>(Only picture)</strong></p> <p><strong>- </strong> <strong>Figure 3.</strong> (<strong>a</strong>) Absorption spectra of the ARGO and ARGO* glass sample after various X-ray doses and the difference absorption coefficient spectrum for 222 Gy vs. pristine. (<strong>b</strong>) Fit of the radiation-induced spectrum (difference between 222 Gy and pristine) considering Gaussian energy contributions for ARGO and ARGO*. (<strong>c</strong>) Absorption spectra for the GPN and GPN* glasses for X-ray doses from 5 mGy to 3 kGy [<a href="https://www.mdpi.com/2227-9040/10/3/110/htm#B39-chemosensors-10-00110">39</a>]. (<strong>d</strong>) The difference absorption coefficient spectra between different doses conditions for GPN and GPN* [<a href="https://www.mdpi.com/2227-9040/10/3/110/htm#B39-chemosensors-10-00110">39</a>]. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure3_2022-03-03_V01. <strong>Figure 3</strong></li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure3_Datas_2022-03-03_V01. Datas : <strong>wavelength, effective absorption coefficient (cm-1)</strong></li> </ol> <p>- <strong>Figure 4.</strong> Micro-luminescence of GPN* glass performed on the optically polished glass side: (<strong>a</strong>) integrated fluorescence intensity at different depths, (<strong>b</strong>) normalized spectrum evolution with depth for the 500 Gy dose [<a href="https://www.mdpi.com/2227-9040/10/3/110/htm#B39-chemosensors-10-00110">39</a>]. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure4_2022-03-03_V01. Figure 4</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure4_Datas_2022-03-03_V01. Datas</li> </ol> <p>- <strong>Figure 5.</strong> Estimated depth-dependent profiles in absolute values of the linear absorption coefficient at 405 nm. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure5_2022-03-03_V01. Figure 5</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure5_Datas_2022-03-03_V01. Datas : <strong>sample depth (mm) ; scaled linear absorption coefficient profile at 405 nm (mm-1)</strong></li> </ol> <p>- <strong>Figure 6.</strong> (<strong>a</strong>) X-ray energy spectra simulated by SpekPy for each irradiation facility, normalized by integral. (<strong>b</strong>) Geant4-simulated dose inside each sample, normalized by the surface dose; filled areas show uncertainties at 95% confidence. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure6_2022-03-03_V01. Figure 6</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure6_Datas_2022-03-03_V01. Datas : <strong>ARGO 100KV_dose ; GPN-20KV_dose ; GPN-32KV_dose</strong></li> </ol> <p>- <strong>Figure 7.</strong> Radio-photoluminescence measurement of the GPNi* glass for the inscribed structure [<a href="https://www.mdpi.com/2227-9040/10/3/110/htm#B39-chemosensors-10-00110">39</a>]. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure7_2022-03-03_V01. Figure 7</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure7_Datas_2022-03-03_V01. Datas : <strong>wavelength ; relative intensity a.u.</strong></li> </ol> <p>- <strong>Figure 8.</strong> Normalized RPL spectra excited at 325 nm: (<strong>a</strong>) for the ARGO (pristine—right axis) and ARGO* (X-ray irradiation at 222 Gy—left axis) glasses collected around 150 µm below the surface, (<strong>b</strong>,<strong>c</strong>) for the highest DLW irradiance structure for ARGOi and ARGOi* in the front- and the rear-inscribed surfaces, respectively. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure8_2022-03-03_V01. Figure 8</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure8_Datas_2022-03-03_V01. Datas : <strong>inscribed glass...</strong></li> </ol> <p>- <strong>Figure 9.</strong> (<strong>a</strong>) Differential linear absorption coefficient of the laser-inscribed structures (11 TW/cm<sup>2</sup>) for the two planes after irradiation at 222 Gy X-ray dose in the ARGOi* glass sample. (<strong>b</strong>) Average differential absorption of the inscribed structures for all DLW irradiance (as from <a href="https://www.mdpi.com/2227-9040/10/3/110/htm#fig_body_display_chemosensors-10-00110-f009">Figure 9</a>a). (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure9_2022-03-03_V01. Figure 9</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure9_Datas_2022-03-03_V01. Datas : <strong>integrated differential linear absoprtion percentage ; irradiance (TW/cm2)</strong></li> </ol> <p>- <strong>Figure 10.</strong> (<strong>a</strong>) Phase image under white light illumination of the laser inscribed structure (11 TW/cm<sup>2</sup>) before irradiation. (<strong>b</strong>) Optical path difference determined from the phase image. (<strong>c</strong>) The refractive index modification Δ<em>n</em> as a function of laser irradiance before/after 222 Gy-dose for the two planes in ARGOi, ARGOi* glass sample. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure10_2022-03-03_V01. Figure 10</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure10_Datas_2022-03-03_V01. Datas : <strong>refractive index modification ; irradiance (TW/cm2), Error bar</strong></li> </ol> <p><strong>- Figure 11.</strong> Comparison between calculated and measured Δ<em>n</em>ˆ after irradiation for a decrease in the initial value of <em>N</em><em>α</em>3 by 0.48%: (<strong>a</strong>,<strong>c</strong>) the real part Δ<em>n</em> for the front and rear surfaces, respectively; (<strong>b</strong>,<strong>d</strong>) their imaginary counterparts Δ<em>κ</em>, respectively. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure11_2022-03-03_V01. Figure 11</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure11_Datas_2022-03-03_V01. Datas : <strong>rear surface...</strong></li> </ol> <p><strong>- Figure 12.</strong> Integrated measure of the amplitude of fluorescence intensity for the different laser irradiance before and after 222 Gy-dose for the two planes in ARGOi and ARGOi* glass sample. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure12_2022-03-03_V01. Figure 12</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure12_Datas_2022-03-03_V01. Datas : <strong>integrated measure of the amplitude of fluorescence intensity ; Irradiance (TW/cm2) ; Error bar </strong></li> </ol> <p><strong>- Figure 13.</strong> (<strong>a</strong>) Composite FLIM and fluorescence intensity microscopy images of the laser-induced structure (11 TW/cm<sup>2</sup>) before and after irradiation for an emission at 425 nm from the front surface; the color-code represents the mean lifetime obtained by FAST-FLIM algorithm (color scale from 0 to 31 ns); inset: luminescence intensity only (grey-scale from 0 to 45 counts). (<strong>b</strong>) Same composite FLIM and luminescence intensity images for an emission at 510 nm. (<strong>c</strong>) Luminescence decays in arbitrary units for the emission at 425 nm of the same structure before and after irradiation for the two surfaces, and fitting curves thereof using three exponential decay functions. (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure13_2022-03-03_V01. Figure 13</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure13_Datas_2022-03-03_V01. Datas : <strong>fluorescence intensity (arbitrary units) ; time (ms)</strong></li> </ol> <p>- <strong>Figure 14.</strong> Dose-dependent evolution of the amplitude ratio of extracted spectral bands for (<strong>a</strong>) the GPNi* glass sample for DLW irradiance of 13.4 TW/cm<sup>2</sup> at 160 µm below the glass surface, (<strong>b</strong>) the ARGOi and ARGOi* glass sample for DLW irradiance of 11 TW/cm<sup>2</sup> at 550 µm below the glass surface (rear surface). (<strong>Picture, xls datas</strong>)</p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure14_2022-03-03_V01. Figure 14</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Chemosensors _Figure14_Datas_2022-03-03_V01. Datas : <strong>ratio of amplitudes of spectral bands ; doses (gy)</strong>.</li> </ol>
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>
High genetic gains in wood volume and fecundity can be both achieved by direct selection in half-sib families of Pinus yunnanensis Franch.
<p><strong><span>Experiment background</span></strong></p> <p><span>This study focused on characterizing phenotypic variation among and within provenances of <em>Pinus yunnanensis</em><span> Franch. aged 16 years in </span></span><span>a common garden</span><span>, with an emphasis on key traits such as cone production, trunk straightness, and crown health, as well as their relationships with traditional growth traits like tree height, diameter at breast height, and wood volume. Specifically, the objectives were to (1) characterize the variation of each trait within and among provenances; (2) assess inter-trait relationships, exploring patterns of co-variation and potential trade-offs; and (3) evaluate the feasibility of multi-trait selection strategies that aim for simultaneous improvements in growth, trunk straightness, and fecundity, contributing valuable insights for advancing <em>P. yunnanensis</em><span> </span>breeding efforts.</span></p> <p><strong><span>Experimental Design</span></strong></p> <p><span>This study was conducted in a common garden for <em>P. yunnanensis</em> located in Lufeng County, central Yunnan Province (102°12' E, 25°13' N) at an altitude of 1860 meters. The site lies in the transition zone between the subtropical humid climate of eastern Yunnan and the sub-humid climate of southwest Yunnan. The climate is characterized by warm and dry winters, humid and hot summers, with a mean annual temperature of 15.5°C and annual precipitation ranging between 900–1000 mm. The dry season extends from November to April, accounting for 6%-17% of the total annual precipitation.</span></p> <p><span>The common garden was established in 2006, with progeny from 179 superior trees selected from six provenance regions, including Anning County (AN), Qujing City (QJ), Yongren County (YR), Yulong County (YL), Tengchong County (TC), and Ninglang County (NL). Each provenance includes 30 families, except for one provenance with 29 families. </span></p> <p><span>The common garden has an area of about 3 ha, with a random block design, and a planting scheme of 2 m × 3 m</span><span>. </span><a name="_Hlk181695359"></a><span>To minimize environmental variation across the study site, a horizontal banding method was used for land preparation prior to planting.</span><span> </span><span>To reduce environmental variation across the study site, a horizontal banding method was used during land preparation. In each block, six provenances were randomly arranged, and families were randomly assigned within each provenance. Five plants from each family were planted in rows, and the design was replicated four times. A total of 3467 progeny from 179 superior trees across six provenances were included in the trial.</span></p> <p><strong><span>Experimental Variables</span></strong></p> <p><span>The study measured nine phenotypic traits, which included both quantitative and qualitative traits, as outlined below:</span></p> <p><span>Tree Height (H): Measured directly with a Vertex Laser instrument (DZH-30, Harbin, China) in meters (m).</span></p> <p><span>Diameter at Breast Height (D): Measured using a circumference tape in centimeters (cm).</span></p> <p><span>Crown Diameter (LCD, SCD): Long crown diameter (LCD) and short crown diameter (SCD), representing the maximum and minimum tree crown diameter, respectively, measured in meters (m) using a tower ruler.</span></p> <p><span>Height Under the Branch (TH): Measured in meters (m) using a tower ruler.</span></p> <p><span>Wood Volume (V): Estimated using the formula based on the forestry industry standard for <em>P. yunnanensis</em> (Agriculture and Forestry Ministry of China, 1977), with units in cubic meters (m³).</span></p> <p><span>Cone Production (CP): The number of open and closed cones in the canopy, including both serotinous and non-serotinous cones, recorded in counts to assess fecundity.</span></p> <p><span>Trunk Straightness (ST): A subjective visual assessment using a classification system: 1 for a highly twisted stem, 5 for a perfectly straight stem.</span></p> <p><span>Crown Health (CH): Visual assessment of the tree's crown, considering damage from abiotic and biotic stresses, with a grading scale from 1 (severely damaged) to 5 (perfectly healthy).</span></p> <p><strong><span>Data Analysis Methods</span></strong></p> <p><span>Data analysis was performed using R (version 3.6.3). The following statistical methods were employed:</span></p> <p><span>Variance Analysis: Nested variance analysis was used to evaluate the significance of differences and partition phenotypic variation among and within provenances. </span></p> <p><span>Principal Component Analysis (PCA): PCA was performed on the standardized matrix of nine phenotypic traits to reveal the dimensional structure and patterns of the data.</span></p> <p><span>Structural Equation Modeling (SEM): SEM was used to examine the direct and indirect relationships among traits, such as growth (H, D, V), crown size (LCD, SCD, TH), fecundity (CP), trunk straightness (ST), and crown health (CH). This analysis helped identify the causal pathways between the traits.</span></p> <p><span>Random Forest Analysis (RF): RF analysis was conducted to assess the importance of specific traits in predicting fecundity (CP) and trunk straightness (ST). Regression and classification methods were used for these analyses, with 1000 decision trees to ensure stable importance measures.</span></p> <p><strong><span>Dataset Description</span></strong></p> <p><span>The excel file (Raw Data) includes the following sheets: 1- Variables: Details on all the variables. 2- </span><span>Values of phenotypic traits</span><span>. 3- </span><span>Variance components </span><span>of phenotypic traits among and within provenances</span><span>. 4-</span><span> </span><span>Coefficient of variance</span><span> for phenotypic traits</span><span>. 5-</span><span> <span>The</span> <span>average membership function values (SFM) and </span>comprehensive weight of each principal component (PCA)<span> of </span></span><span>phenotypic traits</span><span>.</span></p>
Fig. 4 in Direction and timing of dispersal of Scirtothrips dorsalis (Thysanoptera: Thripidae) on select ornamental host plant species in south Florida
Fig. 4. Flight behavior of Scirtothrips dorsalis during the day. Mean hourly captures of adults at (A) greenhouse and (B) field sites of TREC and MREC by the time sampled and cumulative degree-hours. Symbols represent means ± SD. An asterisk (*) indicates a significant difference between test locations at a given time based on a t-test at P ≤ 0.05.
Fig. 2 in Direction and timing of dispersal of Scirtothrips dorsalis (Thysanoptera: Thripidae) on select ornamental host plant species in south Florida
Fig. 2. Population estimates and dispersal of Scirtothrips dorsalis to 2 hosts at TREC, 19 Jul to 27 Sep 2007. (A) Mean weekly numbers of nymphs and pupae found on buttonwood foliage. (B) Mean weekly numbers of adults washed from plant terminals with data from buttonwood and schefflera pooled. (C) Mean weekly captures of adults on yellow sticky-card traps behind buttonwood and schefflera plants. Symbols represent means ± SD. An asterisk (*) indicates a significant difference from the other weeks according to 1-way ANOVAs and t-test comparisons at P ≤ 0.05. Mean weekly temperatures (T °C) and relative humidity (RH %) for the 3 mo period are shown parallel to the X-axis (FAWN 2007).
Fig. 1 in Direction and timing of dispersal of Scirtothrips dorsalis (Thysanoptera: Thripidae) on select ornamental host plant species in south Florida
Fig. 1. Experimental setups. (A) Population estimates and dispersal from rose to buttonwood and schefflera. Darkest grey represents rose, whereas the 2 lighter grey shades represent buttonwood or schefflera with the same shade of grey representing the same plant species. (B) Flight behavior during the day. Circles represent potted rose plants in 11 L containers. Small black rectangles denote locations of yellow sticky-card traps relative to each plot.
Fig. 3 in Direction and timing of dispersal of Scirtothrips dorsalis (Thysanoptera: Thripidae) on select ornamental host plant species in south Florida
Fig. 3. Population estimates and dispersal of Scirtothrips dorsalis to 2 hosts: cumulative data for the 11 wk test period. (A) Mean damage ratings on a scale of 0 to 5. (B) On-plant densities of S. dorsalis. (C) Weekly captures of adults on yellow sticky-card traps. (D) Weekly captures of adults on yellow sticky-card traps by cardinal direction of traps from plants. Symbols represent means ± SD. An asterisk (*) indicates a significant difference at P ≤ 0.05 (A–C) between host plant species according to t-tests or (D) from the other host plant pairs at other cardinal orientations based on a 1-way ANOVA followed by a Tukey–Kramer HSD test.
The Neural Basis of Attentional Selection in Goal-Directed Memory Retrieval
<p>The provided behavioral and EEG data belongs to the publication entitled: "Neural Basis of Attentional Selection in Goal-Directed Memory Retrieval" published in the journal Scientific Reports (article DOI: 10.1038/s41598-024-71691-x). </p> <p><strong>Abstract</strong></p> <p>Goal-directed memory reactivation involves retrieving the most relevant information for the current behavioral goal. Previous research has linked this process to activations in the fronto-parietal network, but the underlying neurocognitive mechanism remains poorly understood. The current electroencephalogram (EEG) study explores attentional selection as a possible mechanism supporting goal-directed retrieval. We designed a long-term memory experiment containing three phases. First, participants learned associations between objects and two screen locations. In a following phase, we changed the relevance of some locations (selective cue condition) to simulate goal-directed retrieval. We also introduced a control condition, in which the original associations remained unchanged (neutral cue condition). Behavior performance measured during the final retrieval phase revealed faster and more confident responses in the selective vs. neutral condition. At the EEG level, we found significant differences in decoding accuracy, with above-chance effects in the selective cue condition but not in the neutral cue condition. Additionally, we observed a stronger posterior contralateral negativity and lateralized alpha power in the selective cue condition. Overall, these results suggest that attentional selection enhances task-relevant information accessibility, emphasizing its role in goal-directed memory retrieval.</p>
Populations of local direction-selective cells encode global motion patterns generated by self-motion. Data, Code and Model.
<p>Directional tuning of the population of local motion detectors T4/T5 in the visual system of the fruit fly <em>Drosophila melanogaster</em>. Direction tuning and receptive field location was measured by recording responses to visual stimuli containing dark or bright edges/stripes moving into 8 directions. All provided MATLAB scripts were used to analyze and illustrate data show in the manuscript 'Populations of local direction-selective cells encode global motion patterns generated by self-motion.'</p> <p>All data were obtained using <em>in vivo </em>two photon microscopy. Image time series were preprocessed using SIMA python software for motion alignment and further processed using custom written matlab or python code.</p> <p>Please find all relevant information to use the code in the README file.</p>
Experimental evidence for short term directional selection of epigenetic trait variation
<p>This Arabidosis data folder includes 5 folders providing the data and code associated with the publication entitled "Experimental evidence for short term directional selection of epigenetic trait variation" by Pujol et al. in Peer Community Journal:</p> <p>"in Silico 1000 resampling" folder includes two folders; one for Population 1, and one for Population 2, each including 24 files. Each file presents the 1000 lists of plant IDs that were randomly sampled to build control groups (listrand), and the corresponding lists of plant IDs selected on the basis of trait values to build the corresponding high (Top) and low (Bot) selection lines, for the strong (20) and weak (60) selection intensities.</p> <p>“phenotypic and epiril data” includes two csv files; data_pop1 and data_pop2, respectively for population 1 and 2, and a readme txt file that presents the data included in the files.</p> <p>“scripts R epigenomic selection” includes two R script files: “PCA_arabidopsis”, which includes the R code used to conduct the PCA analysis on epiRIL data and “Arabette_analysis_loop_Epigenotypes_data”, which is used to insert that epigenotype data in the analysis.</p> <p>“scripts R epigenomic validation” includes nine R scripts used to conduct tests of molecular epigenomic data validation and comparison with existing data from the literature: “Script 1 Extract 126 markers from BSMAP ouput files and apply methylkit”, “Script 2 Boxplots of the BS signal distribution for the 126 markers and their correspondence to published HMM classification”, “Script 3 Correlation between EM-seq and BS seq_published_data for the 126 markers”, “Script 4 Correlation between the BS signals of EM-seq and WGBS data for the 126markers”, “Script 5 Hierarchical clustering of the epiRILs EM-seq and published epigenomic data”, “cluster and PCA analysis of Col wt vs 24 sequenced epiRILs”, which filenames are self-explanatory. “methylkit_epiRILs_vs_Col_wt_DMCs” was used to use methylkit in order to identify Differentially Methylated Cytosines between epiRILs and in comparison to Col-0. “methylkit_tiles_script” was used to build the tiles in Methylkit. “verif DMR CHG context” was used to verify differentially methylated regions in the CHG context.</p> <p>“scripts R phenotypic selection” includes four R scripts “Arabette_analysis”, “Arabette_analysis_loop_Phenotypes_data”, “Arabette_analysis_loop_pop1_final”, “Arabette_analysis_loop_pop2_final” that were used to estimate the parameters used for comparing selection treatments, in other words, to estimate means and confidence intervals (“loop” scripts) in population 1 (“pop1” script) and population 2 (“pop2” script)</p>
Data from: Whole-genome resequencing reveals polygenic signatures of directional and balancing selection on alternative migratory life histories
Open the record for dataset details and reuse information.
An ON-type direction selective ganglion cell in primate retina
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Data from: Stable directional sexual selection and repeatable choosiness for song preference in the Pacific field cricket Teleogryllus oceanicus
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The contributions of direct and indirect selection to the evolution of mating preferences
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The role of recombination dynamics in shaping signatures of direct and indirect selection across the Ficedula flycatcher genome
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Data from: Interplay of trophic relaxation and directional selection shapes eco-evolutionary responses to selective harvest in predator-prey systems
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Data from: Goal-directed and stimulus-driven selection of internal representations
<p>Raw behavioral and eye-tracking datasets of experiments 1 and 2 reported in the manuscript "Goal-directed and stimulus-driven selection of internal representations", by Freek van Ede, Alexander G. Board, Anna C. Nobre<br> </p>
Data from: Response to joint selection on germination and flowering phenology depends on the direction of selection
Background and Aims. Flowering and germination time are components of phenology, a complex phenotype that incorporates a number of traits. In natural populations, selection is likely to occur on multiple components of phenology at once. However, we have little knowledge of how joint selection on several phenological traits influences evolutionary response. Methods. We conducted one generation of artificial selection for all combinations of early and late germination and flowering on replicated lines within two independent base populations in the herb Campanula americana. We then measured response to selection and realized heritability for each trait. Results. Response to selection and heritability were greater for flowering time than germination time, indicating greater evolutionary potential of this trait. Selection for earlier phenology, both flowering and germination, did not depend on the direction of selection on the other trait. Whereas response to selection to delay germination and flowering was greater when selection on the other trait was in the opposite direction (e.g. early germination, late flowering), indicating a negative genetic correlation between the traits. Conclusions. The extent to which correlations shaped response to selection depended on the direction of selection. Therefore the genetic correlation between timing of germination and flowering varies across the trait distributions. The negative correlation between germination and flowering time found when selecting for delayed phenology follows theoretical predictions of constraint for traits that jointly determine life history schedule. Whereas the lack of constraint found when selecting for an accelerated phenology suggests a reduction of the covariance due to strong selection favoring earlier flowering and a shorter life cycle. This genetic architecture, in turn, will facilitate further evolution of the early phenology often favored in warming climates.
Direct observation of chirality-induced spin selectivity in electron donor–acceptor molecules. Open data set
<p>Data supporting the original figures 2 and 4 of the related publication.</p>
Directional selection shifts trait distributions of planted species in dryland restoration
<p>1. The match between species trait values and local abiotic filters can restrict community membership. An often-implicit assumption of this relationship is that abiotic filters select for a single locally optimal strategy, though difficulty in isolating effects of the abiotic environment from those of dispersal limitation and biotic interactions has resulted in few empirical tests of this assumption. Similar constraints have made it difficult to assess whether the type and intensity of abiotic filters shift along gradients of environmental harshness, as predicted by the stress dominance hypothesis.</p> <p>2. We planted 9,216 plants of perennial grass and forb species that had a range of functional trait values and were assigned to a warm, intermediate, or cool temperature tolerance pools across eight sites on the Colorado Plateau. We compared the distributions of traits of surviving individuals to null distributions to evaluate whether there were shifts in trait means and variation. Borrowing from phenotypic selection concepts in evolutionary biology, we assessed support for stabilizing, directional, and disruptive abiotic filtering of trait distributions and whether these types of filtering varied with initial species pool.</p> <p>3. Functional composition was significantly different from null distributions for nearly all traits at all sites, with trait variation more restricted in harsher abiotic conditions, supporting the stress-dominance hypothesis. Contrary to expectations, we primarily found evidence for directional selection, which increased in frequency in warm species pools while disruptive selection was found more often in cool and intermediate species pools.</p> <p>4. Synthesis: This study provides a controlled experimental approach to test the effect of the abiotic environment on plant trait filtering. We found that opportunistic strategies allowing for rapid water acquisition during favorable periods improved survival at warmer sites. Species with these strategies may be expected to benefit from increasing aridity and may be selected for active management efforts. More generally, the prevalence of directional selection may have important implications for dynamic vegetation models that rely on trait distributions for translating environmental variation into ecosystem processes.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.