Duveau Fabien, Metzger Brian P H, Gruber Jonathan D, Mack Katya, Sood Natasha, Brooks Tiffany E, Wittkopp Patricia J
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109-1048.
G3 (Bethesda). 2014 Apr 29;4(7):1205-16. doi: 10.1534/g3.114.011783.
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.
通过定位鉴定出的遗传变异倾向于具有较大的表型效应,这是因为检测具有小表型效应的遗传变异存在方法学上的挑战。最近,群体分离分析法结合下一代测序(BSA-seq)被证明是在自然群体中定位小效应变异的一种强大且经济高效的方法。在此,我们研究了BSA-seq在有效定位从诱变筛选中分离出的小效应突变方面的能力。具体而言,我们确定了分离群体大小、收集分离株的表型选择强度、减数分裂与测序之间的有丝分裂代数以及平均测序深度对定位具有一系列影响表型均值、标准差以及相对适合度的突变的能力的影响。然后,我们使用BSA-seq来定位酿酒酵母中三种甲磺酸乙酯诱导的突变表型所对应的突变。这些突变体在荧光报告基因的平均表达上表现出小的定量变化(-3%、+7%和+10%)。利用减数分裂率增加的遗传背景、可靠的交配型标记以及荧光激活细胞分选来有效评分大型分离群体并分离具有极端表型的细胞,我们成功地在所有三个案例中定位并功能验证了一个导致突变表型的单点突变。我们的模拟和实验数据表明,在对酵母等微生物进行遗传变异定位时,当需要群体生长步骤进行BSA-seq时,不仅应考虑致病位点对平均表型的影响,还应考虑其对标准差和相对适合度的影响。