Data from: Mutations in yeast are deleterious on average regardless of the degree of adaptation to the testing environment
Data files
Apr 23, 2024 version files 4.12 MB
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AB_Cross_1_5-13.txt
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ABcrossRef.csv
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adapt_tracker.csv
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mutfitref.csv
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README.md
Abstract
The role of spontaneous mutations in evolution depends on the distribution of their effects on fitness. Despite a general consensus that new mutations are deleterious on average, a handful of mutation accumulation experiments in diverse organisms instead suggest that of beneficial and deleterious mutations can have comparable fitness impacts, i.e., the product of their respective rates and effects can be roughly equal. We currently lack a general framework for predicting when such a pattern will occur. One idea is that beneficial mutations will be more evident in genotypes that are not well adapted to the testing environment. We tested this prediction experimentally in the laboratory yeast Saccharomyces cerevisiae by allowing nine replicate populations to adapt to novel environments with complex sets of stressors. After >1000 asexual generations interspersed with 41 rounds of sexual reproduction, we assessed the mean effect of induced mutations on yeast growth in both the environment to which they had been adapting and the alternative novel environment. The mutations were deleterious on average, with the severity depending on the testing environment. However, we find no evidence that the adaptive match between genotype and environment is predictive of mutational fitness effects.
README: Data from: Mutations in yeast are deleterious on average regardless of the degree of adaptation to the testing environment
Bao et al yeast adaptation data
[Access this dataset on Dryad]
In this dataset we have the raw reads from our growth rate assays. These assays were performed by placing 96-well plates into the Biotek assay reader which read OD over a period of time and at regular intervals. OD is used as a proxy for cell concentration and thus growth.
Description of the data and file structure:
All files provided are raw read data from the machine. Each column represents a well and the rows are the ODs over time. Each Regular Fitness Assay file is named with the date that a given assay was performed. Crossing Assays and Mutant fitness assays were the assays done to determine local adaptation and the fitness of mutagenized lines respectively. Each well's associated identity is marked in a *ref.csv file which has the well number in the first column, and the identity of what is in that well in the second.
Some other axillary data is also provided. adaptracker.csv tracks the adaptation over time. Petite counts shows the results of the test for respiration negative yeast in a 2x2 table.
Code is provided that is able to read this data, but has not been cleaned up. Growth rate was measured as the maximum growth rate over time achieved in the assay machine.