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• W2120090059 abstract "Genetic variants identified by mapping are biased toward large phenotypic effects because of methodologic challenges for detecting genetic variants with small phenotypic effects. Recently, bulk segregant analysis combined with next-generation sequencing (BSA-seq) was shown to be a powerful and cost-effective way to map small effect variants in natural populations. Here, we examine the power of BSA-seq for efficiently mapping small effect mutations isolated from a mutagenesis screen. Specifically, we determined the impact of segregant population size, intensity of phenotypic selection to collect segregants, number of mitotic generations between meiosis and sequencing, and average sequencing depth on power for mapping mutations with a range of effects on the phenotypic mean and standard deviation as well as relative fitness. We then used BSA-seq to map the mutations responsible for three ethyl methanesulfonate-induced mutant phenotypes in Saccharomyces cerevisiae. These mutants display small quantitative variation in the mean expression of a fluorescent reporter gene (-3%, +7%, and +10%). Using a genetic background with increased meiosis rate, a reliable mating type marker, and fluorescence-activated cell sorting to efficiently score large segregating populations and isolate cells with extreme phenotypes, we successfully mapped and functionally confirmed a single point mutation responsible for the mutant phenotype in all three cases. Our simulations and experimental data show that the effects of a causative site not only on the mean phenotype, but also on its standard deviation and relative fitness should be considered when mapping genetic variants in microorganisms such as yeast that require population growth steps for BSA-seq." @default.
• W2120090059 created "2016-06-24" @default.
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• W2120090059 date "2014-07-01" @default.
• W2120090059 modified "2023-10-16" @default.
• W2120090059 title "Mapping Small Effect Mutations in<i>Saccharomyces cerevisiae</i>: Impacts of Experimental Design and Mutational Properties" @default.
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• W2120090059 doi "https://doi.org/10.1534/g3.114.011783" @default.
• W2120090059 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4455770" @default.
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• W2120090059 hasPublicationYear "2014" @default.
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