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209 results for “phenotypic selection”

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edi48/100

Selection for phenotypic plasticity in Rana sylvatica tadpoles, 1998.

The hypothesis that phenotypic plasticity is an adaptation to environmental variation rests on the two assumptions that plasticity improves the performance of individuals that possess it, and that it evolved in response to selection imposed in heterogeneous environments. The first assumption has been upheld by studies showing the beneficial nature of plasticity. The second assumption is difficult to test since it requires knowing about selection acting in the past. However, it can be tested in its general form by asking whether natural selection currently acts to maintain phenotypic plasticity. We adopted this approach in a study of plastic morphological traits in larvae of the wood frog, Rana sylvatica. First we reared tadpoles in artificial ponds for 18 days, in either the presence or absence of Anax dragonfly larvae (confined within cages to prevent them from killing the tadpoles). These conditioning treatments produced dramatic differences in size and shape: tadpoles from ponds with predators were smaller and had relatively short bodies and deep tail fins. We estimated selection by Anax on the two kinds of tadpoles by testing for non-random mortality in overnight predation trials. Dragonflies imposed strong selection by preferentially killing individuals with relatively shallow and short tail fins, and narrow tail muscles. The same traits that exhibited the strongest plasticity were under the strongest selection, except that tail muscle width exhibited no plasticity but experienced strong increasing selection. A laboratory competition experiment, testing for selection in the absence of predators, showed that tadpoles with deep tail fins grew relatively slowly. In the cattle tanks, where there were also no free predators, the predator-induced phenotype survived more poorly and developed slowly, but this cost was apparently not associated with particular morphological traits. These results indicate that selection is currently promoting morphological plasticity in

openCC (other)Jul 2024View details →

zenodo44/100

Figures S1-S7. SMR-HEIDI analysis results for 8q24.21 locus between BP and selected phenotypes.

Supplementary Figures S1-S7. SMR-HEIDI analysis results for rs6651255 between BP and selected phenotypes. This project contains the following figures: <ul> <li> Figure S1. SMR-HEIDI analysis results for rs6651255 between BP and LDH. </li> <li> Figure S2. SMR-HEIDI analysis results for rs6651255 between BP and GSDMC expression in skeletal muscle (GTEx v6). </li> <li> Figure S3. SMR-HEIDI analysis results for rs6651255 between BP and FAM49B expression in Brain anterior cingulate cortex BA24 (GTEx v6). </li> <li> Figure S4. SMR-HEIDI analysis results for rs6651255 between BP and FAM49B expression in CD8 cell line (CEDAR). </li> <li> Figure S5. SMR-HEIDI analysis results for rs6651255 between BP and heel bone mineral density (UKBB). </li> <li> Figure S6. SMR-HEIDI analysis results for rs6651255 between BP and disc problem phenotype (UKBB) </li> <li> Figure S7. SMR-HEIDI analysis results for rs6651255 between BP and height (UKBB). </li> </ul>   Figures legend: Each figure consists of four parts (1 – top left; 2- top right; 3- bottom left; 4 – bottom right): <ol> <li> Regional association plots for GWAS-1 (in our case BP GWAS) and GWAS-2 (expression or complex trait). Blue triangles represent SNPs used to calculate HEIDI test. Crossed triangle is leading SNP for which SMR test was computed. </li> <li> Z-Z plot (GWAS-1 on y-axis and GWAS-2 on x-axis). </li> <li> Visualization of LD matrix for SNPs used in calculation of HEIDI test. </li> <li> Plot of SMR regression coefficient estimates. The plot visualizes the heterogeneity of SMR coefficient. Blue color represents SNPs used to calculate HEIDI test. </li> </ol>

opencc-by-4.0Mar 2020View details →

zenodo40/100

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

This BBC_2025__README.txt file was generated on 2025-09-24 by Beatriz Baselga Cervera GENERAL INFORMATION <ol> <li>Title of Dataset and code: Data from: Stochastic phenotypic switching arises in response to directional selection in experimentally evolved multicellular yeast.</li> </ol>   2. Author Information             Corresponding Investigator                         Name: Ph.D. Beatriz Baselga-Cervera                         Institution: University of Minnesota Twin cities, Minnesota, US.                         Email: <a href="mailto:bbaselga@umn.edu">bbaselga@umn.edu</a>; beabaselga@gmail.com             Co-investigator 1                         Name: Ph.D. Nahui Olin Medina-Chávez                         Institution: University of Minnesota Twin cities, Minnesota, US.                         Email: nmedinac@umn.edu             Co-investigator 2                         Name: Ph.D. Noah Gettle                         Institution: Wellcome Sanger Institute, Hinxton, UK.                         Email: nbgettle@gmail.com Co-investigator 3                         Name: Ph.D. Michael Travisano                         Institution: University of Minnesota Twin cities, Minnesota, US.                         Email: travisan@umn.edu     3. Data collectors: Ph.D. Beatriz Baselga-Cervera, Ph.D. Nahui Olin Medina-Chávez & Ph.D. Noah Gettle.   4. Date of data collection: 2022-2024   5. Geographic location of data collection: Saint Paul, US   6. Funding sources that supported the collection of the data: Fundación Alfonso Martín Escudero, Madrid, Spain (BBC).   7. Recommended citation for this dataset: Baselga-Cervera et al. (2024), Data from: Stochastic phenotypic switching arises in response to directional selection in experimentally evolved multicellular yeast.     DATA & FILE OVERVIEW   8. Description of dataset In this study, we address whether stochastic phenotypic switching can shape biological diversity contributing to evolutionary change across the transition from singles cells to multicellular clutters in Saccharomyces cerevisiae multicellular yeast system. Populations characterization was conducted with a Coulter Counter multisize 4, a FlowCam 3, under the optic microscope, via ACE2 gene sequencing and RNA sequencing and mathematical modeling. The populations studied were the genetically uniform diploid wild-type Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 c.1934 A>T).   9. File list: ●      Coulter Counter size distribution data:  o   File 1 name:  File_1_Coulter_Counter_Counts_20h.csv o   File 1 description: Size distributions of Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 20-hours growth. Data for: Fig. 1A, Fig. 3A and Fig. S2, Table S2 and Table S3.   o   File 2 name:  File_2_Coulter_Counter_Counts_24h.csv o   File 2 description: Size distributions of Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 24-hours growth. Data for: Fig. 1A, Fig. 3A, Fig. S2, Table S2 and Table S3.   o   File 3 name:  File_3_Coulter_Counter_Counts_48h.csv o   File 3 description: Size distributions of Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 48-hours growth. Data for: Fig. 1, Fig. 3A, Fig. S2, Table S2 and Table S3.   o   File name:  File_4_Coulter_Counter_Counts_Constructed_strains_diversity.csv o   File 4 description: Size distributions of the constructed ACE2 knockout and a strain containing the homozygous missense mutation (ACE2 c.1934 A>T) in YPD at 24h growth. Size distributions were obtained from populations before (initial) and five resuspended colonies obtained from small-size particles by plating the top fraction of the population after gravitational selection from three isolates per strain. Data for: Fig. 1, Fig. S2, Table S2 and Table S3.   o   File 5 name:  File_5_Coulter_Counter_Counts_Selection_Experiment.xlsx o   File 5 description: Size distributions of C1W8.1 and C1W8.2 multicellular evolved strains in YPD at 24h growth. Size distributions from the selection experiment for small-size particles by plating the top fraction of the population after gravitational selection over three cycles of selection. Data for: Fig. 2B and Fig. S6.   o   File 6 name:  File_6_Coulter_Counter_Counts_12h.xlsx o   File 6 description: Size distributions of C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 12-hours growth. Data for: Fig. 3A and Fig. S3.     ●      FlowCam data: o   File 7 name: File_7_Rawdata_FlowCam_all.csv o   File 7 description: FlowCam data from Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 24h growth. Data for: Fig. S4.     ●      Data generated statistically: o   File 8 name: File_8_C1W8.2_overlapPairs_Selection_Experiment.csv o   File 8 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data of the C1W8.2 derived strain over the selection experiment. Data for: Fig. S6D.   o   File 9 name: File_9_C1W8.1_overlapPairs_Selection_Experiment.csv o   File 9 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data o   of the C1W8.1 derived strain over the selection experiment. Data for: Fig. S6C.     o   File 10 name: File_10_ overlapPairs_Constructed_strains_diversity.xlsx o   File 10 description: overlapping indexes (η) of the KDE distributions were computed using the R-package ‘overlapping’ from the Coulter Counter data of the constructed ACE2 knockout and a strain containing the homozygous missense mutation (ACE2 c.1934 A>T) in YPD at 24h growth. Size distributions were obtained from populations before (initial) and after gravitational selection of five resuspended colonies from three isolates per strain. Data for: Fig. S7.   ●      Data from ImageJ: o   File 11 name: File_11_ImageJ_analyses.xlsx o   File 11 description: ImageJ analyses of the microphotographs from Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 c.1934 A>T). Cultures were grown in culture tubes with 10 ml of media, 50 mL Erlenmeyer flasks with 10 mL and 30 mL of media, in YPD under non-shaking and shaking at 250 rpm. YPD media was used across all conditions. Cultures were assessed after 24 hours growth at 30°C.  Microphotographs of each condition and strain were obtained with a Nikon TE2000 microscope using 10x objective.   ●      Pictures: o   File 12 name: File_12_ FlowCam_Pictures.zip o   File 12 description FlowCam IMAGES from Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 24h growth. Data for: Fig. 1B.   o   File 13 name: File_13_Microphotography_controled_experimental_conditions.zip o   File 13 description: Microphotographs from Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 c.1934 A>T). Cultures were grown in culture tubes with 10 mL of media, 50 mL Erlenmeyer flasks with 10 mL and 30 mL of media, in YPD under non-shaking and shaking at 250 rpm. YPD media was used across all conditions. Cultures were assessed after 24 hours of growth at 30°C. Pictures were obtained with a Nikon TE2000 microscope using 10x objective.     ●      Mathematical Model o   File 14 name: File_14_Mathematical_model.zip o   File 14 description: Mathematical model R code and generated values.   ●      ARN data o   File 15 name: File_15_rnaseq-final-results-Top_v_Bottom.xlsx o   File 15 description: RNA analyses final results Top vs Bottom phenotypic subdistributions. Top is used as control. o   File 16 name: File_16_Variant_Call_format_file.vcf o   File 16 description: Variant Calling analyses of the sample ARN sample Top 1. Adhesion number: SRR32105384.   ●      Time-lapse videos o   File 17 name: Supp. Video 1. C1W8.1 from 17 to 22 hours growth o   File 17 description: Supplementary Video 1. Experimentally evolved multicellular yeast video between 17 and 22 hours of growth (C1W8.1-derived strain) — time-lapse video of the formation of a single-cell propagule from a multicellular cluster. o   File 18 name: Supp. Video 2. Ace2x2KO over 26 hours growth. o   File 18 description: Supplementary Video 2. ace2Δ knockout constructed strain growth — time-lapse video of a single large multicellular cluster over 26 hours. o   File 19 name: Supp. Video 3. C1W8.1 over 6 hours growth o   File 19 description: Supplementary Video 3. Experimentally evolved multicellular yeast growth between 6 and 12 hours of growth (C1W8.1-derived strain). o   File 20 name: Supp. Video 4. C1W8.1 over 24 hours growth o   File 20 description: Supplementary Video 4. Experimentally evolved multicellular yeast growth over 24 hours (C1W8.1-derived strain) — cell division stops in small ancestral-like phenotypes. o   File 21 name: Supp. Video 5. Ace2x2KO over 24 hours growth o   File 21 description: Supplementary Video 5. ace2Δ knockout constructed strain growth — time-lapse video of multiple large multicellular clusters over 24 hours. o   File 22 name: Supp. Video 6. Ace2x2missense from 0 to 3h45m hours growth o   File 22 description: Supplementary Video 6. ace2Δ missense constructed strain growth — time-lapse video of multiple large multicellular clusters up to 3 hours 45 min.   METHODOLOGICAL INFORMATION Strains: ancestral wildtype (Y55 strains), C1W8.1 and C1W8.2 multicellular derived strains isolated after 60 days of selection in YPD media, constructed ACE2 gene knockouts, and strains containing the ACE2 missense mutation (ACE2 c.1934 A>T). Media: Growth media used in this study were Yeast Peptone Dextrose media (YPD; 1% (v/w) yeast extract, 2% (v/w) peptone, 2% (v/w) D-glucose, pH 5.8). Phenotypic characterization of the different strains was conducted in a Coulter Counter Multisizer 4 and FlowCam® 3.0 Fluid Imaging Technologies, optic microscopy and a mathematical model. Replicate populations of different individual isolates per strain were analyzed to obtain the population distributions in YPD media. RNA was extracted using an Invitrogen® PureLink RNA Mini Kit. Three out of four extracted samples per treatment with the highest RNA integrity score were submitted for TrueSeq Stranded RNA-Seq.     10. Detailed description ●      Coulter Counter size distribution data of all the populations:  o   File 1 name:  File_1_Coulter_Counter_Counts_20h.csv o   File 1 description: strains naming convention; strain_Isolate_run.pseudoreplicate. Strains: ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout; C1W8.1= C1W8.1 evolved multicellular strain; C1W8.2= C1W8.2 evolved multicellular strain; Y55= ancestral strain. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Columns 3 to the last column: strains counts.   o   File 2 name:  File_2_Coulter_Counter_Counts_24h.csv o   File 2 description: strains naming convention; strain_Isolate_run.pseudoreplicate. Strains: ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout; C1W8.1= C1W8.1 evolved multicellular strain; C1W8.2= C1W8.2 evolved multicellular strain; Y55= ancestral strain. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Columns 3 to the last column: strains counts.   o   File 3 name:  File_3_Coulter_Counter_Counts_48h.csv o   File 3 description: strains naming convention; strain_Isolate_run.pseudoreplicate. Strains: ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout; C1W8.1= C1W8.1 evolved multicellular strain; C1W8.2= C1W8.2 evolved multicellular strain; Y55= ancestral strain. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Column 3 to the last column: strains counts.   o   File_4_Coulter_Counter_Counts_Constructed_strains_diversity.csv o   File 4 description: strains naming convention; strain_Isolate_colony_run.pseudoreplicate. Strains: ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Column 3 to the last column: strains counts.   o   File_5_Coulter_Counter_Counts_Selection_Experiment.xlsx o   File 5 description: strains naming convention; strain_colony.phenotype_selection.cycle_run.pseudoreplicate. Strains: C1W8.2= C1W8.2 evolved multicellular strain and C1W8.1= C1W8.1 evolved multicellular strain. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Column 3 to the last column: strains counts.   o   File 6 name:  File_6_Coulter_Counter_Counts_12h.xlsx o   File 6 description: Size distributions of C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockout, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 12-hours growth. Data for: Fig. 3A and Fig. S3. §  Page 1: Column 1: Volume (um3) Column 2: Diameter (um2) Column 3: Time Column 4: replicate Column 5: Strain name (strain_f) Column 6: Isolate (isolate_f)         o   File 7 name: File_3_Rawdata_Flowcam_all.csv o   File 7 description: strains naming convention; ace2_isolate= ACE2 knockout; Ace2m_isolate= strain containing the ACE2 missense mutation (ACE2 c.1934 A>T); c1w82_isolate=C1W8.2 evolved multicellular strain; C1W81_isoalte C1W8.1 evolved multicellular strain; Y55_isolate=ancestral strain. §  Page 1:                                                                         Column 1: Particle ID                                                                         Column 2: Area ABD                                                                         Column 3: Aspect Ratio (Width/Length)                                                                         Column 4: Circle Fit                                                                         Column 5: Area base Diameter (ABD)                                                                         Column 6: Equivalent Spherical Diameter (ESD)                                                                         Column 7: Elongation                                                                         Column 8: Perimeter                                                                         Column 9: Roughness                         Column 10: Volume ABD-based                                                                         Column 11: Volume ESD-based                                                                         Column 12: Width                                                                         Column 13: Source. Name of the sample.   o   File 8 name: File_8_C1W8.2_overlapPairs_Selection_Experiment.csv o   File 8 description: C1W8.2 _lineage_selection.cycle= C1W8.2 evolved multicellular strain, lineage (A=ancestral, M1= lineage 1,  M2= lineage 2 , M3= lineage 3) and selection cycle  (0, 1, 2 and 3). §  Page 1: Column 1: Var1= strain 1 Column 2: Var2= strain 2 Column 3: overlap value of both strains compared.   o   File 9 name: File_9_C1W8.1_overlapPairs_Selection_Experiment.csv o   File 9 description: C1W8.1 _lineage_selection.cycle =C1W8.1 evolved multicellular strain, lineage (A=ancestral, M1= lineage 1,  M2= lineage 2 , M3= lineage 3) and selection cycle  (0, 1, 2 and 3). §  Page 1: Column 1: Var1= strain 1 Column 2: Var2= strain 2 Column 3: overlap value of both strains compared.   o   File 10 name: File_10_overlapPairs_Constructed_strains_diversity.xlsx o   File 10 description: variables naming convention; strain _isolate_colony.number. Strains; ace2x2m=strains containing the ACE2 missense mutation (ACE2 c.1934 A>T); ace2x2= ACE2 knockout. Isolate; 1,2 and 3. Colony.number; Initial=initial population and colony number (1,2,3,4 and 5). §  Page 1: Column 1: Var1= strain 1 Column 2: Var2= strain 2 Column 3: overlap value of both strains compared.   o   File 11 name: File_11_ ImageJ _analyses.xlsx o   File 11 description: ImageJ analyses of the microphotographs from Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 c.1934 A>T). Cultures were grown in culture tubes with 10 mL of media, 50 mL Erlenmeyer flasks with 10 mL and 30 mL of media, in YPD under non-shaking and shaking at 250 rpm. YPD media was used across all conditions. Cultures were assessed after 24 hours growth at 30°C.  Microphotographs of each condition and strain were obtained with a Nikon TE2000 microscope using 10x objective. §  Page 1: Column 1: Var1= strain 1 Column 2: Var2 = strain 2 Column 3: overlap value of both strains compared.     o   File 12 name: File_12_ FlowCam_Pictures.zip o   File 12 description: FlowCam runs, images, and raw data of Saccharomyces cerevisiae Y55 strain clones, C1W8.1 and C1W8.2 multicellular evolved strains, constructed ACE2 gene knockouts, and strains containing the missense mutation (ACE2 c.1934 A>T) in YPD at 24h growth. Data for: Fig. 1B.   o   File 13 name: File_13_Microphotography_controled_experimental_conditions.zip o   File 13 description: 149 microphotographs. § Folder 1:  Images of Erlenmeyer flasks with 30ml of YPD § Folder 2:  Images of Erlenmeyer’s and tubes with 10ml of YPD   o   File 14 name: File_14_Mathematical_model.zip o   File 14 description: Mathematical model, R code, and generated values. §  Document 1:  R code of the model §  Document 2:  Resulted data from the mathematical model with different inset values of k, alpha, and beta. §  Document 2:  Resulted data from the mathematical model with different inset values of k, alpha, gamma, and beta.       o   File 15 name: File_15_rnaseq-final-results-Top_v_Bottom.xlsx o   File 15 description: §  Page 1: Column 1: number Column 2: ID Column 3: protID             Column 4: gene_symbol                     Column 5: chr             Column 6: chr_latin Column 7: location Column 8: baseMean             Column 9: log2FoldChange Column 10: lfcSE Column 11: stat             Column 12: pvalue     padj Column 13: test Column 14: log10padj             Column 15: log10baseMean Column 16: blast_pident Column 17: transcript_length             Column 18: blast_evalue Column 19: blast_bitscore Column 20: rnaID             Column 21: feature Column 22: accession Column 23: strain             Column 24: gene_accession   o   File 16 name: File_16_Variant_Call_format_file.vcf o   File 16 description: Variant Calling analyses of the  ARN sample Top 1. Adhesion number: SRR32105384.   o   File 17 name: Supp. Video 1. C1W8.1 from 17 to 22 hours growth o   File 17 description: Supplementary Video 1. Experimentally evolved multicellular yeast video between 17 and 22 hours of growth (C1W8.1-derived strain) — time-lapse video of the formation of a single-cell propagule from a multicellular cluster. The time-lapse video captures growth dynamics over this period, highlighting the formation of a single-cell propagule from a multicellular cluster on two occasions (visible in the lower left region of the frame). Images were acquired every 15 minutes using a 10x objective lens.  o   File 18 name: Supp. Video 2. Ace2x2KO over 26 hours of growth. o   File 18 description: Supplementary Video 2. ace2Δ knockout constructed strain growth — time-lapse video of a single large multicellular cluster over 26 hours. The video captures large, multicellular clusters that produce both large, multicellular and small, ancestral-like clusters. The video shows a single large multicellular cluster fragmenting into two large multicellular clusters at ~ 13 hours of growth (from 02:09 to 02:10 minutes in the time-lapse) and generating two small ancestral-like propagules at ~19 hours of growth (from 03:07 to 03:09 minutes in the time-lapse). Microphotographs were obtained at 3-minute intervals under a 10x objective over 26 hours.   o   File 19 name: Supp. Video 3. C1W8.1 over 6 hours growth o   File 19 description: Supplementary Video 3. Experimentally evolved multicellular yeast growth between 6 and 12 hours of growth (C1W8.1-derived strain). The time-lapse video captures large, multicellular clusters of the C1W8.1 strains, which produce both large, multicellular and small, ancestral-like clusters. Additionally, small ancestral-like clusters are observed undergoing cellular division —no separation is observed— during the first 2 to 3 hours, followed by a cessation of division for the remainder of the time-lapse. Images were acquired every 30 seconds using a 10x objective lens. o   File 20 name: Supp. Video 4. C1W8.1 over 24 hours growth o   File 20 description: Supplementary Video 4. Experimentally evolved multicellular yeast growth over 24 hours (C1W8.1-derived strain) — cell division stops in small ancestral-like phenotypes. The footage captures multiple large multicellular clusters undergoing fragmentation into propagules. Additionally, a small ancestral-like cluster is observed undergoing division during the first 2 to 3 hours, followed by a cessation of division for the remainder of the time-lapse (visible in the lower left region of the frame). This early division phase is evident during the first 10 seconds of the video. Images were acquired every 5 minutes using a 10x objective lens.  o   File 21 name: Supp. Video 5. Ace2x2KO over 24 hours growth o   File 21 description: Supplementary Video 5. ace2Δ knockout constructed strain growth — time-lapse video of multiple large multicellular clusters over 24 hours. The video shows multiple large multicellular clusters fragmenting into large clusters and several small ancestral-like clusters being dragged by Brownian motion and evaporation of the sample. Microphotographs were obtained at fixed intervals of 3 minutes under the 10x objective over 24 hours.  o   File 22 name: Supp. Video 6. Ace2x2missense from 0 to 3h45m hours growth o   File 22 description: Supplementary Video 6. ace2Δ missense constructed strain growth — time-lapse video of multiple large multicellular clusters up to 3 hours 45 min. The video shows multiple large multicellular clusters fragmenting into large clusters, generating two small ancestral-like propagules before being dragged by Brownian motion and evaporation of the sample. Microphotographs were obtained at 3-minute intervals under the 10x objective.

opencc-by-4.0Sep 2024View details →

dryad40/100

The interplay between prior selection, mild intermittent exposure, and acute severe exposure in phenotypic and transcriptional response to hypoxia

Hypoxia has profound and diverse effects on aerobic organisms, disrupting oxidative phosphorylation and activating several protective pathways. Predictions have been made that exposure to mild intermittent hypoxia may be protective against more severe exposure and may extend lifespan. Both effects are likely to depend on prior selection on phenotypic and transcriptional plasticity in response to hypoxia, and may therefore show signs of local adaptation. Here we report the lifespan effects of chronic, mild, intermittent hypoxia (CMIH) and short-term survival in acute severe hypoxia (ASH) in four clones of Daphnia magna originating from either permanent or intermittent habitats, the latter regularly drying up with frequent hypoxic conditions. We show that CMIH extended the lifespan in the two clones originating from intermittent habitats but had the opposite effect in the two clones from permanent habitats, which also showed lower tolerance to ASH. Exposure to CMIH did not protect against ASH; to the contrary, Daphnia from the CMIH treatment had lower ASH tolerance than normoxic controls. Few transcripts changed their abundance in response to the CMIH treatment in any of the clones. After 12 hours of ASH treatment, the transcriptional response was more pronounced, with numerous protein-coding genes with functionality in mitochondrial and respiratory metabolism, oxygen transport, and, unexpectedly, gluconeogenesis showing up-regulation. While clones from intermittent habitats showed somewhat stronger differential expression in response to ASH than those from permanent habitats, there were no significant hypoxia-by-habitat of origin or CMIH-by-ASH interactions. GO enrichment analysis revealed a possible hypoxia tolerance role by accelerating the molting cycle and regulating neuron survival through up-regulation of cuticular proteins and neurotrophins, respectively.

opencc-zeroSep 2022View details →

dryad40/100

Data from: Floral scents of a deceptive plant are hyperdiverse and under population-specific phenotypic selection

Floral scent is a key mediator in plant–pollinator interactions; however, little is known to what extent intraspecific scent variation is shaped by phenotypic selection, with no information yet in deceptive plants. We recorded 289 scent compounds in deceptive moth fly-pollinated Arum maculatum from various populations north vs. south of the Alps, the highest number so far reported in a single plant species. Scent and fruit set differed between regions, and some, but not all differences in scent could be explained by differential phenotypic selection in northern vs. southern populations. Our study is the first to provide evidence that phenotypic selection is involved in shaping geographic patterns of floral scent in deceptive plants. The hyperdiverse scent of A. maculatum might result from the plant's imitation of various brood substrates of its pollinators.

opencc-zeroSep 2021View details →

zenodo40/100

Spring temperature drives phenotypic selection on plasticity of flowering time

Data on field observations of flowering time and fitness of the perennial forest herb Lathyrus vernus and on spring temperature from weather station data. The dataset includes 22 years of data (1987–1996 and 2006–2017) from a L. vernus population located in a deciduous forest in Tullgarn, SE Sweden (58.9496 N, 17.6097 E). It includes records from 837 individuals (607 from 1987 to 1996, and 230 from 2006 to 2017), and from 2478 flowering events. The dataset includes the following variables: year: year of the recording id_nr: numeric plant id id: unique plant id (combination of numeric plant id and period) fcode: flowering code (1 if the plant flowered on that year, 0 if not) FFD: First Flowering Date n_fl: number of flowers n_fr: number of fruits totseed: total number of seeds intactseed: total number of intact seeds (not damaged by seed predator beetles) shoot_vol: shoot volume period: old (1987–1996) or new (2006–2017) n_years_fl_fitness: number of years when data on flowering and fitness is available n_years_study: number of years when the plant was included in the study mean_4: Average daily mean temperature of April (calculated from nearby meteorological station data) cmean_4: Mean-centred average daily mean temperature of April

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Spring temperature drives phenotypic selection on plasticity of flowering time

In seasonal environments, a high responsiveness of development to increasing temperatures in spring can infer benefits in terms of a longer growing season, but also costs in terms of an increased risk of facing unfavourable weather conditions. Still, we know little about how climatic conditions influence the optimal plastic response. Using 22 years of field observations for the perennial forest herb Lathyrus vernus, we assessed phenotypic selection on among-individual variation in reaction norms of flowering time to spring temperature, and examined if among-year variation in selection on plasticity was associated with spring temperature conditions. We found significant among-individual variation in mean flowering time and flowering time plasticity, and that plants that flowered earlier also had a more plastic flowering time. Selection favoured individuals with an earlier mean flowering time and a lower thermal plasticity of flowering time. Less plastic individuals were more strongly favoured in colder springs, indicating that spring temperature influenced optimal flowering time plasticity. Our results show how selection on plasticity can be linked to climatic conditions, and illustrate how we can understand and predict evolutionary responses of organisms to changing environmental conditions.

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