Increased time sampling in an evolve-and-resequence experiment with outcrossing Saccharomyces cerevisiae reveals multiple paths of adaptive change
Data files
Oct 02, 2020 version files 463.24 MB
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All_S.txt
4.08 MB
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CMH_Results.txt
2.85 MB
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DBVPG6044_hap_freqs_10kb.txt
19.81 MB
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DBVPG6765_hap_freqs_10kb.txt
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DS13_S.txt
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DS4_S.txt
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DS8_S.txt
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Pval_table_13tp_ModelA.txt
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Pval_table_17tp_All_Models.txt
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Pval_table_4tp_ModelA.txt
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Pval_table_8tp_ModelA.txt
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ReadMe.txt
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SNP_table.txt
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Y12_hap_freqs_10kb.txt
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YPS128_hap_freqs_10kb.txt
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Abstract
“Evolve and resequence” (E&R) studies combine experimental evolution and whole-genome sequencing to interrogate the genetics underlying adaptation. Due to ease of handling, E&R work with asexual organisms like bacteria can employ optimized experimental design, with large experiments and many generations of selection. By contrast, E&R experiments with sexually reproducing organisms are more difficult to implement, and design parameters vary dramatically among studies. Thus, efforts have been made to assess how these differences, such as number of independent replicates, or size of experimental populations, impact inference. We add to this work by investigating the role of time sampling – the number of discrete timepoints sequence data is collected from evolving populations. Using data from an E&R experiment with outcrossing Saccharomyces cerevisiae in which populations were sequenced 17 times over ~540 generations, we address the following questions: (i) do more timepoints improve the ability to identify candidate regions underlying selection? And (ii) does high-resolution sampling provide unique insight into evolutionary processes driving adaptation? We find that while time sampling does not improve the ability to identify candidate regions, high-resolution sampling does provide valuable opportunities to characterize evolutionary dynamics. Increased time sampling reveals three distinct trajectories for adaptive alleles: one consistent with classic population genetic theory (i.e. models assuming constant selection coefficients), and two where trajectories suggest more context-dependent responses (i.e. models involving dynamic selection coefficients). We conclude that while time sampling has limited impact on candidate region identification, sampling 8 or more timepoints has clear benefits for studying complex evolutionary dynamics.
Methods
Data is from an evolve and resequence experimental featuring Saccharomyces cerevisiae. Briefly, 12 populations were exposed to an outcrossing regime and allowed to evolve for 540 generations. Samples were taken from each population at 17 timepoints for DNA sequencing. Details for population maintenance 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" published in Molecular Ecology. This entry includes a SNP table, haplotype frequency tables, and tables with various statistical results (See ReadMe file for details).