Data from: Strength of selection potentiates distinct adaptive responses in an evolution experiment with outcrossing yeast
Data files
Jan 09, 2026 version files 128.45 MB
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Phillips_2025_Yeast_Eth_dataset.zip
128.44 MB
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README.md
7.54 KB
Abstract
Selection intensity is expected to influence the magnitude and genetic architecture of adaptive responses, yet it is rarely evaluated as a standalone variable in experimental evolution studies. Here, we evolved outcrossing populations of Saccharomyces cerevisiae for ~200 generations across a spectrum of environmental stress from zero to moderate to high ethanol exposure, to examine how genomic responses vary with stress intensity. Across treatments, adaptation proceeded through many subtle allele and haplotype frequency shifts rather than large changes at single loci, consistent with a highly polygenic response. At loci associated with ethanol adaptation, the high stress treatment led to larger allele frequency changes compared to the moderate or no ethanol stress treatments, with the genomic architecture of adaptation becoming increasingly polygenic as selection intensity decreased. Moderate and high stress conditions engaged partially distinct biological pathways, indicating that selection intensity shapes both the magnitude and targets of adaptive change. Within this stress continuum, we also observed substantial, ongoing adaptation in control populations despite extensive prior domestication. Many alleles associated with this adaptation showed reduced or absent responses under ethanol stress, consistent with antagonistic pleiotropy. Consequently, laboratory adaptation can represent a major component of evolutionary change and may confound treatment-specific inferences when not explicitly accounted for. Broadly, our results demonstrate that selection intensity structures adaptive responses in experimental evolution and that continued laboratory adaptation remains an important force in these studies. Our findings underscore the importance of clearly defined controls and careful consideration of selection intensity when interpreting or comparing across experimental evolution studies.
Authors
Mark A. Phillips, Megan Sandoval-Powers, Rupinderjit K. Briar, Marcus Scaffo, Shenghao Zhou, Molly K. Burke
Corresponding Authors
Mark A. Phillips (corresponding author)
Email: philmark@oregonstate.edu
Megan Sandoval-Powers (co-corresponding author)
Email: sandovme@oregonstate.edu
Molly K. Burke (co-corresponding authors)
Email: molly.burke@oregonstate.edu
Description
This dataset contains data associated with the manuscript: Strength of selection potentiates distinct adaptive responses in an evolution experiment with outcrossing yeast
The data are organized into subfolders by analysis category and contain major input and results files used to support the analyses and generate figures presented in the manuscript. These resources are intended to be used in conjunction with analysis scripts available on GitHub (see below).
File Structure
The Dryad repository consists of a single compressed (zipped) folder titled Phillips_2025_Yeast_Eth_dataset.zip with the following structure:
Phillips_2025_Yeast_Eth_dataset/
├── Growth_Rate_Analysis/
│ ├── Eth_48_hr_timepoint_0.txt
│ ├── High_ethanol_2021.txt
│ ├── Moderate_ethanol_2021.txt
│ ├── Plain_ypd_2021.txt
├── Haplotype_Analysis/
│ ├── Founders_12.txt
│ ├── Input_hapcaller_ethanol.txt
├── Selection_Coefficient_Analysis/
│ ├── Control_BaitER_results.txt
│ ├── High_BaitER_results.txt
│ ├── Moderate_BaitER_results.txt
├── Candidate_SNP_Identification/
│ ├── CMH_Results_Controls_1v15.txt
│ ├── CMH_Results_High_1v15.txt
│ ├── CMH_Results_Moderate_1v15.txt
├── SNP_Tables/
│ ├── SNPtable_50X_scaled.txt
│ ├── SNPtable_raw.txt
Folder and File Descriptions
Growth_Rate_Analysis
This folder contains input growth rate data from experimental yeast populations. Data files include:
Eth_48_hr_timepoint_0.txt— data from a plate reader assay measuring growth in the ancestral population across all media types for 48 hours.Plain_ypd_2021.txt— data from a plate reader assay measuring growth in the ancestral population and experimental populations during cycle 15 in plain YPD.Moderate_ypd_2021.txt— data from a plate reader assay measuring growth in the ancestral population and experimental populations during cycle 15 in 6% ethanol YPD.High_ypd_2021.txt— data from a plate reader assay measuring growth in the ancestral population and experimental populations during cycle 15 in 10% ethanol YPD.
Columns generally include:
- Column 1: Time in which OD600 absorbance was measured in minutes (time)
- Column 2: OD600 absorbance measurements for blank media wells (blank)
- Columns 3-**: OD600 absorbance measurements for experimental and/or ancestral populations at each timepoint.
Haplotype_Analysis
This folder contains input files used to estimate and analyze haplotype frequencies.
Founders_12.txt- lists the 12 founder haplotypes used in the experiment, with each line containing the full haplotype identifier name in the first column, and a short label in the second column.input_hapcaller_ethanol.txt- major input file for haplotype analysis. Contains coverage and allele frequencies of alternative haplotypes at each variant site for the founder strains and experimental populations across each sequenced timepoint.
Columns include:
- Column 1: Chromosome (CHROM)
- Column 2: Position (POS)
- Column 3: Reference allele (ref)
- Column 4: Alternate allele (alt)
- Columns 5-28: Alternating allele frequency (alt_ETH_hap_X_Y_00) and coverage (N_ETH_X_Y_00) for founder haplotypes and X and Y are the haplotype identifiers.
- Columns 29-30: Alternating allele frequency (alt_ETH_anc_12SH_12) and coverage (N_ETH_anc_12SH_12) for the ancestral population.
- Columns 31-390: Alternating allele frequency (alt_ETH_X_Y) and coverage (N_ETH_X_Y) for experimental populations where and X is the replicate number and Y is the timepoint/cycle.
Selection_Coefficient_Analysis
This folder contains Bait-ER output files with estimated selection coefficients for SNPs in each treatment group. Inputs for Bait-ER were generated by extracting relevant portions of the filtered SNP table available in the SNP_Tables folder and converting them to sync format.
Output files include:
control_BaitER_results.txtmoderate_BaitER_results.txthigh_BaitER_results.txt
Columns in the output files include:
- Column 1: Chromosome identifier (chromosome)
- Column 2: SNP position on the chromosome (position)
- Column 3: Reference allele (reference)
- Column 4: Standard error of the selection estimate (sigma)
- Column 5: Log Bayes Factor for selection (logBF)
- Column 6: Alpha parameter from Bait-ER model (alpha)
- Column 7: Beta parameter from Bait-ER model (beta)
Candidate_SNP_Identification
This folder contains output files from an adapted CMH (Cochran-Mantel-Haenszel) test to identify candidate SNPs under selection across timepoints for each treatment.
Output files include:
CMH_Results_Controls_1v15.txt- CMH results comparing control populations between cycles 1 and 15.CMH_Results_High_1v15.txt- CMH results comparing high ethanol populations between cycles 1 and 15.CMH_Results_Moderate_1v15.txt- CMH results comparing moderate ethanol populations between cycles 1 and 15.
Columns in the output files include:
- Column 1: Chromosome identifier (chr)
- Column 2: SNP position on the chromosome (pos)
- Column 3: P-value indicating significance of allele frequency change (pval)
SNP_Tables
This folder contains tables of SNPs identified across the ancestral and experimental populations at each sequenced timepoint.
Output files include:
SNPtable_raw.txt- Raw SNP frequency table. This table was generated by converting the merged VCF file and is provided here so that all filtering steps and SNP-level analyses can be fully reproduced.SNPtable_50X_scaled.txt- Filtered and scaled SNP table adjusted for coverage, retaining only high-confidence sites. This SNP table serves as the primary input for most downstream genomic analyses.
Columns include:
- Column 1: Chromosome (chr)
- Column 2: Position (pos)
- Column 3: Reference allele (ref)
- Column 4: Alternate allele (alt)
- Columns 5-12: Alternating allele frequency (alt_ETH_anc_X_Y) and coverage (N_ETH_anc_X_Y) for the ancestral population where X is the ancestral population identifier and Y is cycle number.
- Columns 13-372: Alternating allele frequency (alt_ETH_X_Y) and coverage (N_ETH_X_Y) for experimental populations where and X is the replicate number and Y is the timepoint/cycle.
Data File Formats
- File format(s): TXT
- Missing values are indicated as: NA
Relationship to Analysis Code
The data in this Dryad repository are intended to be used with analysis scripts available on GitHub:
GitHub repository:
[https://github.com/mphillips67/Genomics-Ethanol-Stress-Outcrossing-Yeast]
Software Requirements
Reproducing the analyses requires:
- R version 4.0.4
A complete list of required packages is provided in the GitHub repository
Data is from an evolution experiment with outcrossing yeast populations derived from the "S12" base population, which originated from 12 haploid founder strains. Sixty replicate populations were established: 20 control (C), 20 moderate ethanol stress (M, 6% ethanol), and 20 high ethanol stress (H, 10% ethanol). Populations underwent weekly outcrossing and batch culture for 15 cycles, corresponding to approximately 200 generations. Growth rate assays were conducted at the end of the experiment to quantify adaptation by measuring optical density over 48 hours in control and treatment-specific media. DNA was extracted from pooled populations at three timepoints (cycles 1, 7, and 15) and sequenced using Illumina PE150. Raw reads were aligned to the S. cerevisiae S288C reference genome, and SNPs were called using GATK. Variant tables were filtered to retain high-confidence polymorphic sites. Candidate SNPs responding to selection were identified using a modified Cochran-Mantel-Haenszel (CMH) test, and selection coefficients were estimated genome-wide using Bait-ER. Haplotype frequencies were estimated with a sliding-window haplotype caller to assess the contributions of rare and founder-specific variants. More specific details on population maintenance, phenotyping, and sequencing can be found in the manuscript entitled “Increased time sampling in an evolve-and-resequence experiment with outcrossing Saccharomyces cerevisiae reveals multiple paths of adaptive change”. These datasets include growth measurements, SNP tables, CMH results, selection coefficient estimates, and haplotype frequency data for ancestral and evolved populations across treatments and timepoints (see ReadMe file for details).
