Payen C~Dunham MJ, 2016

Pubmed ID 27727276
Title High-Throughput Identification of Adaptive Mutations in Experimentally Evolved Yeast Populations.
Authors Celia Payen, Anna B Sunshine, Giang T Ong, Jamie L Pogachar, Wei Zhao, Maitreya J Dunham
Abstract High-throughput sequencing has enabled genetic screens that can rapidly identify mutations that occur during experimental evolution. The presence of a mutation in an evolved lineage does not, however, constitute proof that the mutation is adaptive, given the well-known and widespread phenomenon of genetic hitchhiking, in which a non-adaptive or even detrimental mutation can co-occur in a genome with a beneficial mutation and the combined genotype is carried to high frequency by selection. We approximated the spectrum of possible beneficial mutations in Saccharomyces cerevisiae using sets of single-gene deletions and amplifications of almost all the genes in the S. cerevisiae genome. We determined the fitness effects of each mutation in three different nutrient-limited conditions using pooled competitions followed by barcode sequencing. Although most of the mutations were neutral or deleterious, ~500 of them increased fitness. We then compared those results to the mutations that actually occurred during experimental evolution in the same three nutrient-limited conditions. On average, ~35% of the mutations that occurred during experimental evolution were predicted by the systematic screen to be beneficial. We found that the distribution of fitness effects depended on the selective conditions. In the phosphate-limited and glucose-limited conditions, a large number of beneficial mutations of nearly equivalent, small effects drove the fitness increases. In the sulfate-limited condition, one type of mutation, the amplification of the high-affinity sulfate transporter, dominated. In the absence of that mutation, evolution in the sulfate-limited condition involved mutations in other genes that were not observed previously-but were predicted by the systematic screen. Thus, gross functional screens have the potential to predict and identify adaptive mutations that occur during experimental evolution.
Citation PLoS Genet. 2016; 12:e1006339

Datasets

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Paper Phenotype Condition Medium Collection Tested mutants Data Details
Payen C~Dunham MJ, 2016 growth (relative abundance in pooled culture) standard SD + phosphate limitation hap a N/A Quantitative
Payen C~Dunham MJ, 2016 growth (relative abundance in pooled culture) standard SD + glucose limitation hap a N/A Quantitative
Payen C~Dunham MJ, 2016 growth (relative abundance in pooled culture) standard SD + sulfate limitation het N/A Quantitative
Payen C~Dunham MJ, 2016 growth (relative abundance in pooled culture) standard SD + glucose limitation het N/A Quantitative
Payen C~Dunham MJ, 2016 growth (relative abundance in pooled culture) standard SD + phosphate limitation het N/A Quantitative

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