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309 results for “phenotypic variation”
Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations [11 cancer cell lines]
GEO Series GSE282350. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing; Other.
Single cell functional genomics reveals the importance of mitochondria in cell-to-cell phenotypic variation
GEO Series GSE104343. Saccharomyces cerevisiae. 4 samples. Type: Expression profiling by high throughput sequencing.
Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations
GEO Series GSE283335. Homo sapiens. 52 samples. Type: Expression profiling by high throughput sequencing; Other.
Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations [CRISPR screen]
GEO Series GSE311810. Homo sapiens. 46 samples. Type: Other.
Genetic variation at transcription factor binding sites largely explains phenotypic heritability in maize
GEO Series GSE294039. Zea mays. 150 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Single-cell analysis of gene expression variation and phenotype switching in melanoma
GEO Series GSE134432. Homo sapiens. 94 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Cryptic variation fuels plant phenotypic change through hierarchical epistasis
GEO Series GSE289537. Solanum lycopersicum. 8 samples. Type: Expression profiling by high throughput sequencing.
Transcriptional Signatures Predict Phenotypic Variations of Candida auris
GEO Series GSE165762. Candidozyma auris. 12 samples. Type: Expression profiling by high throughput sequencing.
Batch effect during human bone marrow stromal cell propagation prevails donor variation and culture duration impact on phenotype, transcriptome and function [MethylCap-seq]
GEO Series GSE194295. Homo sapiens. 20 samples. Type: Methylation profiling by high throughput sequencing.
Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations [scRNA-seq]
GEO Series GSE311811. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
Natural variation in non-coding regions underlying phenotypic diversity in budding yeast
GEO Series GSE69115. Saccharomyces cerevisiae. 18 samples. Type: Expression profiling by high throughput sequencing.
Phenotypic variation between stromal cells differentially impacts engineered cardiac tissue function
GEO Series GSE129058. Homo sapiens. 22 samples. Type: Expression profiling by high throughput sequencing.
Integrated Molecular-Phenotypic Profiling Reveals Metabolic Control of Morphological Variation in Stembryos
GEO Series GSE250136. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association.
GEO Series GSE48152. Homo sapiens. 705 samples. Type: Expression profiling by array.
Migration-related phenotypic divergence is associated with epigenetic variation in rainbow trout
GEO Series GSE62195. Oncorhynchus mykiss. 18 samples. Type: Methylation profiling by high throughput sequencing.
Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations [xenograft]
GEO Series GSE311813. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
Data from: Genetic divergence and phenotypic plasticity contribute to variation in cuticular hydrocarbons in the seaweed fly Coelopa frigida
Cuticular hydrocarbons (CHCs) form the boundary between insects and their environments and often act as essential cues for species, mate and kin recognition. This complex polygenic trait can be highly variable both among and within species, but the causes of this variation, especially the genetic basis, are largely unknown. In this study, we investigated phenotypic and genetic variation of CHCs in the seaweed fly, C. frigida, and found that composition was affected by both genetic (sex and population) and environmental (larval diet) factors. We subsequently conducted behavioral trials that show CHCs are likely used as a sexual signal. We identified general shifts in CHC chemistry as well as individual compounds and found that the methylated compounds, mean chain length, proportion of alkenes, and normalized total CHCs differed between sexes and populations. We combined this data with whole genome re-sequencing data to examine the genetic underpinnings of these differences. We identified 11 genes related to CHC synthesis and found population level outlier SNPs in 5 that are concordant with phenotypic differences. Together these results reveal that the CHC composition of C. frigida is dynamic, strongly affected by the larval environment, and likely under natural and sexual selection.
Data and R scripts for: Variation in phenotypic plasticity across age-at-maturity genotypes in wild Atlantic salmon
<p>Data and R-scripts underlying the statistical analyses of the study. </p>
Data from: Phenotypic variation across the first steps of experimentally evolved multicellularity.
<p>This BBC_2024__README.txt file was generated on 2024-07-15 by Beatriz Baselga Cervera</p> <p>GENERAL INFORMATION</p> <p>1. Title of Dataset and code: Data from: Phenotypic variation across the first steps of experimentally evolved multicellularity.</p> <p>2. Author Information</p> <p> Corresponding Investigator</p> <p> Name: Dr Beatriz Baselga-Cervera</p> <p> Institution: University of Minnesota Twin cities, Minnesota, US.</p> <p> Email: <a href="mailto:bbaselga@umn.edu">bbaselga@umn.edu</a>; beabaselga@gmail.com</p> <p> Co-investigator 1</p> <p> Name: Dr Noah Gettle</p> <p> Institution: Wellcome Sanger Institute, Hinxton, UK</p> <p> Email: noah.gettle@sanger.ac.uk</p> <p> Co-investigator 2</p> <p> Name: Dr Michael Travisano</p> <p> Institution: University of Minnesota Twin cities, Minnesota, US.</p> <p> Email:travisan@umn.edu</p> <p> </p> <p>4.Data collector: Dr Beatriz Baselga-Cervera</p> <p> </p> <p>5. Date of data collection: 2021-2022</p> <p> </p> <p>6. Geographic location of data collection: Saint Paul, US</p> <p> </p> <p>5. Funding sources that supported the collection of the data: Fundación Alfonso Martín Escudero, Madrid, Spain.</p> <p> </p> <p>6. Recommended citation for this dataset: Baselga-Cervera et al. (2024), Data from: Phenotypic variation across the first steps of experimentally evolved multicellularity. Zenodo. Data set.</p> <p>DATA & FILE OVERVIEW</p> <p> </p> <p>1. Description of dataset</p> <p>In this study, we study the genotype to phenotype map that provides the basis for the diverse morphologies and unique adaptations observed in nascent multicellularity carried over from their unicellular ancestors under high and low nutrient availability conditions. We carried out a NetLogo agent-based model simulation of the multicellular snowflake yeast growth. Populations characterization was conducted with a Coulter Counter multisize 4 and FlowCam 3. 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 c.1934 A>T). The population data represent the six independent isolates per strain in two different media, YPD and SD.</p> <p>2. File list:</p> <ul> <li>NetLogo Agent Base model: </li> <ul> <li>File 1 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Netlogo%20Snowflake%203D.nlogo3d?versionId=6fc2e8c0-02be-4956-875e-b4e48dd37163">Netlogo Snowflake 3D.nlogo3d</a> </li> </ul> </ul> <p> File 1 Description: Netlogo code for the 3D model/</p> <ul> <ul> <li>File name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Data_NETLOGO_model.csv?versionId=bb3e52cd-aac2-4f3e-a395-40a4995a1192">Data_NETLOGO_model.csv</a> </li> </ul> </ul> <p> File 2 Description: Data obtained from the Netlogo model.</p> <ul> <li>Coulter Counter size distribution data of all the populations: </li> <ul> <li>File 3 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Counter_Counter_Raw_data.xls?versionId=389afe4d-46c3-4569-92cb-ea73355a4ed7">Counter_Counter_Raw_data.xls</a></li> <li>File 3 description: 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 and SD at 24h growth. </li> <li>File 4 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Coulter_Counter_Raw_data_heterozygous_contructions.xlsx?versionId=e1fa6610-3f88-414c-b07a-03cc11b913e4">Coulter_Counter_Raw_data_heterozygous_contructions</a></li> <li>File 4 description: Size distributions of the heterozygous construct knockout (ACE2/<em>ace</em>2Δ) and homozygous missense (ACE2/<em>ace2Δ</em>) in YPD and SD at 24h growth. </li> </ul> <li>FlowCam image data:</li> <ul> <li>File 5 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/FlowCamPicturesData.zip?versionId=1e80636d-3022-4feb-828e-bc9552fef091">FlowCamPicturesData.zip</a></li> <li>File 5 description: Pictures generated by the FlowCam.</li> <li>File 6 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Flow_Cam_Raw%20data.xls?versionId=efd469dc-66f9-4504-8de3-f96c74f07f38">Flow_Cam_Raw data.xls</a></li> <li>File 6 desciption: 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 and SD at 24h growth. </li> </ul> <li>Data generated statistically:</li> <ul> <li>File 7 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/bootstrapped_means.csv?versionId=48184a51-e3b5-407d-8ce1-ecdf5d7e1c99">bootstrapped_means.csv</a></li> <li>File 7 description: bootstrapped means from the Coulter Counter data to calculate the relative contributions to phenotypic variation.</li> <li>File 8 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/bootstrapped_vars.csv?versionId=3ff5b6aa-6644-4264-8a6b-448c8a733689">bootstrapped_vars.csv</a></li> <li>File 8 description: bootstrapped variance from the Coulter Counter data to calculate the phenotypic noise.</li> <li>File 9 name: overlapPairs_values.xlsx </li> <li>File 9 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data.</li> </ul> <li>R codes for data generated statistically:</li> <ul> <li>File 10 name: <a href="Code%20for%20bootstrapping.docx">R_code_bootstrapping.docx</a></li> <li>File 10 description: R code to obtain bootstrapped means and variance from the <a>Counter_Counter_Raw_data.xls</a> data to calculate the relative contributions to phenotypic variation.</li> <li>File 11 name: <a href="R%20code%20Overlap%20KDE%20distributions%20from%20the%20Coulter%20Counter%20data.docx">R_code_Overlap_KDE_distributions_from _the_Coulter_Counter_data</a></li> <li>File 11 description: R code to obtain overlapping indexes (η) of the Kernel density estimations (KDE) distributions from <a>Counter_Counter_Raw_data.xls</a></li> </ul> <li>R codes for figures:</li> <ul> <li>File 12 name: R_code_Fig2.docx</li> <li>File 12 description: R code for Figure 2 panels B and C. Panels are created from <a>Data_NETLOGO_model.csv</a>.</li> <li>File 13 name: R_code_Fig3.docx</li> <li>File 13 description: R code for Figure 3 panels A to E. Panels are created from <a>Counter_Counter_Raw_data.xls</a></li> <li>File 13 name: R_code_Fig4.docx</li> <li>File 13 description: R code for Figure 4, data from <a>Counter_Counter_Raw_data.xls</a></li> <li>File 14 name: R_code_FigS1.docx</li> <li>File 14 description: R code for Figure S1. Raw data from <a>Data_NETLOGO_model.csv</a> </li> <li>File 15 name: R_code_FigS2.docx</li> <li>File 15 description: R code for Figure S2. Raw data from <a>Counter_Counter_Raw_data.xls</a></li> <li>File 16 name: R_code_FigS3.docx</li> <li>File 16 description: R code for Figure S3. Raw data from <a>Coulter_Counter_Raw_data_heterozygous_contructions</a>.xlsx</li> <li>File 16 name: R_code_FigS4.docx</li> <li>File 16 description: R code for Figure S4. Raw data from <a>Counter_Counter_Raw_data.xls</a></li> </ul> </ul> <p> </p> <p>METHODOLOGICAL INFORMATION</p> <p>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).</p> <p>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) and Standard minimal (SD; Yeast nitrogen base with amino acids (YNB w/AA) 6.7 g L-1, 0.5% (v/w) D-glucose).</p> <p>Phenotypic characterization of the different strains was conducted in a Coulter Counter Multisizer 4 and FlowCam® 3.0 Fluid Imaging Technologies. Replicate populations of different individual isolates per strain were analyzed to obtain the population distributions in both YPD and SD media.</p> <p>Agent Base Model data was generated in Netlogo (https://ccl.northwestern.edu/netlogo/).</p> <p> </p> <p>3. Detailed description</p> <ul> <li>NetLogo Agent Base model: </li> <ul> <li>File 1 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Netlogo%20Snowflake%203D.nlogo3d?versionId=6fc2e8c0-02be-4956-875e-b4e48dd37163">Netlogo Snowflake 3D.nlogo3d</a> </li> </ul> </ul> <p>o File 1 Description: Netlogo code for the 3D model.</p> <p>o File name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Data_NETLOGO_model.csv?versionId=bb3e52cd-aac2-4f3e-a395-40a4995a1192">Data_NETLOGO_model.csv</a> </p> <p>o File 2 Description: Data obtained from the Netlogo model.</p> <p>§ Page 1: Agent Base Model data generated with Netlogo.</p> <pre> Column 1: run number</pre> <pre> Column 2: size-of-turtle(cells)</pre> <p> Column 3: [step]</p> <p> Column 4: N</p> <p> Column 5: ticks(generations)</p> <pre> Column 6:distance-turtle(cells)</pre> <p> Column 7: diameter cells</p> <p> Column 8: radius cells</p> <p> Column 9: diameter cluster</p> <p> Column 10: radius cluster</p> <p> Column 11: volume</p> <p> Column 12: SAVr (surface area/volume ratio)</p> <p> Column 13: packing</p> <p> Column 14: Ratio</p> <ul> <li>Coulter Counter size distribution data of all the populations: </li> <ul> <li>File 3 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Counter_Counter_Raw_data.xls?versionId=389afe4d-46c3-4569-92cb-ea73355a4ed7">Counter_Counter_Raw_data.xls</a></li> <li>File 3 description: 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 and SD at 24h growth. </li> </ul> </ul> <p>§ Page 1: Coulter Coulter data runs at 24h</p> <p> Column 1: Volumen (um3)</p> <p> Column 2: Diameter (um2)</p> <p>Column 3: ace2Δ _k_1_SD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate one is SD media.</p> <p>Column 4: ace2Δ _k_1_YPD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate one is YPD media.</p> <p>Column 5: ace2Δ _k_2_SD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate two is SD media.</p> <p>Column 6: ace2Δ _k_2_YPD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate two is YPD media.</p> <p>Column 7: ace2Δ _k_3_SD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate three is SD media.</p> <p>Column 8: ace2Δ _k_3_YPD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate three is YPD media.</p> <p>Column 9: ace2Δ _k_4_SD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate four is SD media.</p> <p>Column 10: ace2Δ _k_4_YPD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate four is YPD media.</p> <p>Column 11: ace2Δ _k_5_SD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate five is SD media.</p> <p>Column 12: ace2Δ _k_5_YPD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate one is YPD media.</p> <p>Column 13: ace2Δ _k_6_SD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate five is SD media.</p> <p>Column 14: ace2Δ _k_6_YPD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate five is YPD media.</p> <p>Column 15: ace2Δ _m_1_SD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate one is SD media.</p> <p>Column 16: ace2Δ _m_1_YPD. Homozygous ACE2 knockout construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate one is YPD media.</p> <p>Column 17: ace2Δ _m_2_SD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate two is SD media.</p> <p>Column 18: ace2Δ _m_2_YPD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate two is YPD media.</p> <p>Column 19: ace2Δ _m_3_SD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate three is SD media.</p> <p>Column 20: ace2Δ _m_3_YPD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate three is YPD media.</p> <p>Column 21: ace2Δ _m_4_SD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate four is SD media.</p> <p>Column 22: ace2Δ _m_4_YPD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate four is YPD media.</p> <p>Column 23: ace2Δ _m_5_SD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate five is SD media.</p> <p>Column 24: ace2Δ _m_5_YPD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate one is YPD media.</p> <p>Column 25: ace2Δ _m_6_SD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate five is SD media.</p> <p>Column 26: ace2Δ _m_6_YPD. Homozygous ACE2 missense construct (<em>ace2Δ</em> /<em>ace2Δ</em>) isolate five is YPD media.</p> <p>Column 27: C1W8.1 _m_1_SD. C1W8.1 evolved strain isolate one is SD media.</p> <p>Column 28: C1W8.1 _m_1_YPD. C1W8.1 evolved strain isolate one is YPD media.</p> <p>Column 29: C1W8.1 _m_2_SD. C1W8.1 evolved strain isolate two is SD media.</p> <p>Column 30: C1W8.1 _m_2_YPD. C1W8.1 evolved strain isolate two is YPD media.</p> <p>Column 31: C1W8.1 _m_3_SD. C1W8.1 evolved strain isolate three is SD media.</p> <p>Column 32: C1W8.1 _m_3_YPD. C1W8.1 evolved strain isolate three is YPD media.</p> <p>Column 33: C1W8.1 _m_4_SD. C1W8.1 evolved strain isolate four is SD media.</p> <p>Column 34: C1W8.1 _m_4_YPD. C1W8.1 evolved strain isolate four is YPD media.</p> <p>Column 35: C1W8.1 _m_5_SD. C1W8.1 evolved strain isolate five is SD media.</p> <p>Column 36: C1W8.1 _m_5_YPD. C1W8.1 evolved strain isolate five is YPD media.</p> <p>Column 37: C1W8.1 _m_6_SD. C1W8.1 evolved strain isolate six is SD media.</p> <p>Column 38: C1W8.1 _m_6_YPD. C1W8.1 evolved strain isolate sic is YPD media.</p> <p>Column 39: C1W8.2 _m_1_SD. C1W8.2 evolved strain isolate one is SD media.</p> <p>Column 40: C1W8.2 _m_1_YPD. C1W8.2 evolved strain isolate one is YPD media.</p> <p>Column 41: C1W8.2 _m_2_SD. C1W8.2 evolved strain isolate two is SD media.</p> <p>Column 42: C1W8.2 _m_2_YPD. C1W8.2 evolved strain isolate two is YPD media.</p> <p>Column 43: C1W8.2 _m_3_SD. C1W8.2 evolved strain isolate three is SD media.</p> <p>Column 44: C1W8.2 _m_3_YPD. C1W8.2 evolved strain isolate three is YPD media.</p> <p>Column 45: C1W8.2 _m_4_SD. C1W8.2 evolved strain isolate four is SD media.</p> <p>Column 46: C1W8.2 _m_4_YPD. C1W8.2 evolved strain isolate four is YPD media.</p> <p>Column 47: C1W8.2 _m_5_SD. C1W8.2 evolved strain isolate five is SD media.</p> <p>Column 48: C1W8.2 _m_5_YPD. C1W8.2 evolved strain isolate five is YPD media.</p> <p>Column 49: C1W8.2 _m_6_SD. C1W8.2 evolved strain isolate six is SD media.</p> <p>Column 50: C1W8.2 _m_6_YPD. C1W8.2 evolved strain isolate sic is YPD media.</p> <p>Column 51: Y55_1_SD. Y55 ancestral strain isolate one is SD media.</p> <p>Column 52: Y55_1_SD. Y55 ancestral strain isolate one is YPD media.</p> <p>Column 53: Y55_2_SD. Y55 ancestral strain isolate two is SD media.</p> <p>Column 54 Y55_2_SD. Y55 ancestral strain isolate two is YPD media.</p> <p>Column 55: Y55_3_SD. Y55 ancestral strain isolate three is SD media.</p> <p>Column 56: Y55_3_SD. Y55 ancestral strain isolate three is YPD media.</p> <p>Column 57: Y55_4_SD. Y55 ancestral strain isolate four is SD media.</p> <p>Column 58: Y55_4_SD. Y55 ancestral strain isolate four is YPD media.</p> <p>Column 59: Y55_5_SD. Y55 ancestral strain isolate five is SD media.</p> <p>Column 60: Y55_5_SD. Y55 ancestral strain isolate five is YPD media.</p> <p>Column 61: Y55_6_SD. Y55 ancestral strain isolate six is SD media.</p> <p>Column 62: Y55_6_SD. Y55 ancestral strain isolate sic is YPD media.</p> <p> </p> <p> </p> <p>o File 4 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Coulter_Counter_Raw_data_heterozygous_contructions.xlsx?versionId=e1fa6610-3f88-414c-b07a-03cc11b913e4">Coulter_Counter_Raw_data_heterozygous_contructions</a></p> <ul> <ul> <li>File 4 description: Size distributions of the heterozygote construct knockout (ACE2/<em>ace</em>2Δ) and heterozygous missense construct (ACE2/<em>ace2Δ</em>) in YPD and SD at 24h growth. </li> </ul> </ul> <p>§ Page 1: Coulter Coulter data runs at 24h</p> <p> Column 1: Volumen (um3)</p> <p> Column 2: Diameter (um2)</p> <p>Column 3: ACE2/ace2Δ missense_1_SD. Heterozygous missense construct (ACE2/<em>ace2Δ</em>) isolate one is SD media.</p> <p>Column 4: ACE2/ace2Δ missense_1_YPD. Heterozygous missense construct (ACE2/<em>ace2Δ</em>) isolate one is YPD media.</p> <p>Column 5: ACE2/ace2Δ missense_2_SD. Heterozygous missense construct (ACE2/<em>ace2Δ</em>) isolate two is SD media.</p> <p>Column 6: ACE2/ace2Δ missense_2_YPD. Heterozygous missense construct (ACE2/<em>ace2Δ</em>) isolate two is YPD media.</p> <p>Column 7: ACE2/ace2Δ missense_3_SD. Heterozygous missense construct (ACE2/<em>ace2Δ</em>) isolate three is SD media.</p> <p>Column 8: ACE2/ace2Δ missense_3_YPD. Heterozygous missense construct (ACE2/<em>ace2Δ</em>) isolate three is YPD media.</p> <p>Column 9: ACE2/ace2Δ knockout_1_SD. Heterozygous knockout construct (ACE2/<em>ace2Δ</em>) isolate one is SD media.</p> <p>Column 10: ACE2/ace2Δ knockout _1_YPD. Heterozygous knockout construct (ACE2/<em>ace2Δ</em>) isolate one is YPD media.</p> <p>Column 11: ACE2/ace2Δ knockout _2_SD. Heterozygous knockout construct (ACE2/<em>ace2Δ</em>) isolate two is SD media.</p> <p>Column 12: ACE2/ace2Δ knockout _2_YPD. Heterozygous knockout construct (ACE2/<em>ace2Δ</em>) isolate two is YPD media.</p> <p>Column 13: ACE2/ace2Δ knockout _3_SD. Heterozygous knockout construct (ACE2/<em>ace2Δ</em>) isolate three is SD media.</p> <p>Column 14: ACE2/ace2Δ knockout _3_YPD. Heterozygous knockout construct (ACE2/<em>ace2Δ</em>) isolate three is YPD media.</p> <ul> <li>FlowCam image data:</li> <ul> <li>File 5 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/FlowCamPicturesData.zip?versionId=1e80636d-3022-4feb-828e-bc9552fef091">FlowCamPicturesData.zip</a></li> <li>File 5 description: Pictures generated by the FlowCam.</li> <li>File 6 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/Flow_Cam_Raw%20data.xls?versionId=efd469dc-66f9-4504-8de3-f96c74f07f38">Flow_Cam_Raw data.xls</a></li> <li>File 6 desciption: 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 and SD at 24h growth. </li> </ul> </ul> <p>§ Page 1: FlowCam data runs at 24 hours of Y55 strain.</p> <p> Column 1:Particle ID</p> <p> Column 2: Class. Classification as; single cells and mother-daughter(s).</p> <p> Column 3: Area ABD</p> <p> Column 4: Aspect Ratio (Width/Length)</p> <p> Column 5: Circle Fit</p> <p> Column 6: Area base Diameter (ABD)</p> <p> Column 7: Equivalent Spherical Diameter (ESD)</p> <p> Column 8: Elongation</p> <p> Column 9: Perimeter</p> <p> Column 10: Roughness</p> <p> Column 11: Volume ESD-based</p> <p> Column 12: Width</p> <p> Column 13: Source. Name of the sample.</p> <p> Column 14: Strain Y55.</p> <p> Column 15: media. Values: YPD and SD</p> <p> Column 16: clone. Isolate.</p> <p>§ Page 2: FlowCam data runs at 24 hours of C1W8.1 multicellular strain.</p> <p> Column 1: Particle ID</p> <p> Column 2: Area ABD</p> <p> Column 3: Aspect Ratio (Width/LEngth)</p> <p> Column 4: Circle Fit</p> <p> Column 5: Area base Diameter (ABD)</p> <p> Column 6: Equivalent Spherical Diameter (ESD)</p> <p> Column 7: Elongation</p> <p> Column 8: Perimeter</p> <p> Column 9: Roughness</p> <p> Column 10: Volume ESD-based</p> <p> Column 11: Width</p> <p> Column 12: Source. Name of the sample.</p> <p> Column 13: Strain C1W8.1.</p> <p> Column 14: media. Values: YPD and SD</p> <p> Column 15: clone. Isolate.</p> <p>§ Page 3: FlowCam data runs at 24hours of C1W8.2 multicellular strain.</p> <p> Column 1: Particle ID</p> <p> Column 2: Area ABD</p> <p> Column 3: Aspect Ratio (Width/LEngth)</p> <p> Column 4: Circle Fit</p> <p> Column 5: Area base Diameter (ABD)</p> <p> Column 6: Equivalent Spherical Diameter (ESD)</p> <p> Column 7: Elongation</p> <p> Column 8: Perimeter</p> <p> Column 9: Roughness</p> <p> Column 10: Volume ESD-based</p> <p> Column 11: Width</p> <p> Column 12: Source. Name of the sample.</p> <p> Column 13: Strain C1W8.2.</p> <p> Column 14: media. Values: YPD and SD</p> <p> Column 15: clone. Isolate.</p> <p> </p> <ul> <li>Data generated statistically:</li> <ul> <li>File 7 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/bootstrapped_means.csv?versionId=48184a51-e3b5-407d-8ce1-ecdf5d7e1c99">bootstrapped_means.csv</a></li> <li>File 7 description: bootstrapped means from the Coulter Counter data to calculate the relative contributions to phenotypic variation.</li> </ul> </ul> <p>§ Page 1: Bootstrap mean values.</p> <p> Column 1: row number</p> <p> Column 2: sample. ID of the sample from whom the value was generated.</p> <p> Column 3: diameter_um. Mean diameter (um) values.</p> <ul> <ul> <li>File 8 name: <a href="../api/files/af95c779-dc43-44c4-b833-b44788b6b539/bootstrapped_vars.csv?versionId=3ff5b6aa-6644-4264-8a6b-448c8a733689">bootstrapped_vars.csv</a></li> <li>File 8 description: bootstrapped variance from the Coulter Counter data to calculate the phenotypic noise.</li> </ul> </ul> <p>§ Page 1: Bootstrap variance values.</p> <p> Column 1: row number</p> <p> Column 2: sample. ID of the sample from whom the value was generated.</p> <p> Column 3: diameter_um. Variance in diameter (um) values.</p> <ul> <ul> <li>File 9 name: <code>overlapPairs_values.xlsx</code> </li> <li>File 9 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data.</li> </ul> </ul> <p>§ Page 1: Overlapping indexes (η) of the KDE distributions by strain, media and isolate.</p> <p> Column 1: var1. Population 1.</p> <p> Column 2: var2. Population 2.</p> <p> Column 3: value. Overlap value.</p> <p>§ Page 2: Overlapping indexes (η) of the KDE distributions by strain and media.</p> <p> Column 1: var1. Strain 1.</p> <p> Column 2: var2. Strain 2.</p> <p> Column 3: value. Overlap value.</p> <p> Column 4: media.</p> <p> </p> <p> </p>
Species wide inventory of Arabidopsis thaliana organellar variation reveals ample phenotypic variation for photosynthetic performance
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