Spell Rachelle Miller, Jinks-Robertson Sue
Department of Biology, Emory University, Atlanta, GA, USA.
Methods Mol Biol. 2004;262:3-12. doi: 10.1385/1-59259-761-0:003.
The study of recombination in Saccharomyces cerevisiae benefits from the availability of assay systems that select for recombinants, allowing the study of spontaneous events that represent natural assaults on the genome. However, the rarity of such spontaneous recombination requires selection of events that occur over many generations in a cell culture, and the number of recombinants increases exponentially following a recombination event. To avoid inflation of the average number of recombinants by jackpots arising from an event early in a culture, the distribution of the number of recombinants in independent cultures (fluctuation analysis) must be used to estimate the mean number of recombination events. Here we describe two statistical analyses (method of the median and the method of p0) to estimate the true mean of the number of events to be used to calculate the recombination rate. The use of confidence intervals to depict the error in such experiments is also discussed. The application of these methods is illustrated using the intron-based inverted repeat recombination reporter system developed in our lab to study the regulation of homeologous recombination.
酿酒酵母中重组的研究受益于可用于选择重组体的检测系统,这使得对代表基因组自然攻击的自发事件进行研究成为可能。然而,这种自发重组的稀有性要求选择在细胞培养的许多代中发生的事件,并且重组事件发生后重组体的数量呈指数增长。为了避免因培养早期事件产生的“头奖”导致重组体平均数虚增,必须使用独立培养物中重组体数量的分布(波动分析)来估计重组事件的平均数。在此,我们描述了两种统计分析方法(中位数法和p0法)来估计用于计算重组率的事件数的真实平均数。还讨论了使用置信区间来描述此类实验中的误差。使用我们实验室开发的基于内含子的反向重复重组报告系统来研究同源重组的调控,说明了这些方法的应用。