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在全基因组范围内对酵母的适合度和遗传相互作用进行定量分析。

Quantitative analysis of fitness and genetic interactions in yeast on a genome scale.

机构信息

Banting and Best Department of Medical Research, Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada.

出版信息

Nat Methods. 2010 Dec;7(12):1017-24. doi: 10.1038/nmeth.1534. Epub 2010 Nov 14.

Abstract

Global quantitative analysis of genetic interactions is a powerful approach for deciphering the roles of genes and mapping functional relationships among pathways. Using colony size as a proxy for fitness, we developed a method for measuring fitness-based genetic interactions from high-density arrays of yeast double mutants generated by synthetic genetic array (SGA) analysis. We identified several experimental sources of systematic variation and developed normalization strategies to obtain accurate single- and double-mutant fitness measurements, which rival the accuracy of other high-resolution studies. We applied the SGA score to examine the relationship between physical and genetic interaction networks, and we found that positive genetic interactions connect across functionally distinct protein complexes revealing a network of genetic suppression among loss-of-function alleles.

摘要

全局遗传交互作用定量分析是一种强大的方法,可用于解析基因的作用并绘制途径之间的功能关系。我们使用菌落大小作为适合度的替代物,从合成遗传阵列 (SGA) 分析生成的酵母双突变体高密度阵列中开发了一种基于适合度的遗传交互作用的测量方法。我们确定了几个系统变异的实验来源,并开发了归一化策略来获得准确的单突变体和双突变体适合度测量值,其准确度可与其他高分辨率研究相媲美。我们应用 SGA 评分来检查物理和遗传相互作用网络之间的关系,我们发现正的遗传相互作用跨越功能上不同的蛋白质复合物连接,揭示了功能丧失等位基因之间遗传抑制的网络。

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