ArticleG3 (Bethesda, Md.)2014
Mapping small effect mutations in Saccharomyces cerevisiae: impacts of experimental design and mutational properties.
Article in G3 (Bethesda, Md.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Epistatic impacts of cis- and trans-regulatory mutations on the distribution of mutational effects for gene expression in Saccharomyces cerevisiae.Molecular biology and evolution · 2026Article
- Article
- Contributions of mutation and selection to regulatory variation: lessons from thePhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Mapping mitonuclear epistasis using a novel recombinant yeast population.PLoS genetics · 2023Article
- Next-generation sequencing-based bulked segregant analysis without sequencing the parental genomes.G3 (Bethesda, Md.) · 2022Article
- Mutational sources ofeLife · 2021Article
- Molecular and evolutionary processes generating variation in gene expression.Nature reviews. Genetics · 2021Review
- PyBSASeq: a simple and effective algorithm for bulked segregant analysis with whole-genome sequencing data.BMC bioinformatics · 2020Article
- Empirical measures of mutational effects define neutral models of regulatory evolution inProceedings of the National Academy of Sciences of the United States of America · 2019Article
- CompensatoryEvolution letters · 2019Article
- Genomics of cellular proliferation in periodic environmental fluctuations.Molecular systems biology · 2018Article
- Polymorphisms in the yeast galactose sensor underlie a natural continuum of nutrient-decision phenotypes.PLoS genetics · 2017Article
- The Genomic Landscape of Position Effects on Protein Expression Level and Noise in Yeast.Cell systems · 2016Article
- Contrasting Frequencies and Effects of cis- and trans-Regulatory Mutations Affecting Gene Expression.Molecular biology and evolution · 2016Article
- Gene Expression Evolves under a House-of-Cards Model of Stabilizing Selection.Molecular biology and evolution · 2015Article
- Plasticity of themSphereArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
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.
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Registered trials
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