Mapping small effect mutations in Saccharomyces cerevisiae: impacts of experimental design and mutational properties.
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.
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048 fduveau@umich.edu wittkopp@umich.edu.
Fabien
F
Duveau
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048.
Brian P H
BP
Metzger
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048.
Jonathan D
JD
Gruber
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048.
Katya
K
Mack
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048.
Natasha
N
Sood
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048.
Tiffany E
TE
Brooks
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048 Department of Molecular, Cellular, & Developmental Biology, University of Michigan, Ann Arbor, Michigan 48109-1048 Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan 48109-2218 fduveau@umich.edu wittkopp@umich.edu.
Patricia J
PJ
Wittkopp
D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D002874:Chromosome Mapping; D017930:Genes, Reporter; D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing; D008164:Luminescent Proteins / Q000235:genetics / Q000378:metabolism; D016297:Mutagenesis, Site-Directed; D012107:Research Design; D012441:Saccharomyces cerevisiae / Q000235:genetics*; D017422:Sequence Analysis, DNA
D001426:Bacterial Proteins; D008164:Luminescent Proteins; C054562:yellow fluorescent protein, Bacteria
Bulk Segregant Analysis; FASTER MT; Mutagenesis screen; Next Generation Sequencing; TDH3