Mapping Genetically Compensatory Pathways from Synthetic Lethal Interactions in Yeast

BackgroundSynthetic lethal genetic interaction analysis has been successfully applied to predicting the functions of genes and their pathway identities. In the context of synthetic lethal interaction data alone, the global similarity of synthetic lethal interaction patterns between two genes is used to predict gene function. With physical interaction data, such as protein-protein interactions, the enrichment of physical interactions within subsets of genes and the enrichment of synthetic lethal interactions between those subsets of genes are used as an indication of compensatory pathways. ResultIn this paper, we propose a method of mapping genetically compensatory pathways from synthetic lethal interactions. Our method is designed to discover pairs of gene-sets in which synthetic lethal interactions are depleted among the genes in an individual set and where such gene-set pairs are connected by many synthetic lethal interactions. By its nature, our method could select compensatory pathway pairs that buffer the deleterious effect of the failure of either one, without the need of physical interaction data. By focusing on compensatory pathway pairs where genes in each individual pathway have a highly homogenous cellular function, we show that many cellular functions have genetically compensatory properties. ConclusionWe conclude that synthetic lethal interaction data are a powerful source to map genetically compensatory pathways, especially in systems lacking physical interaction information, and that the cellular function network contains abundant compensatory properties.研究背景：合成致死遗传相互作用分析（Synthetic lethal genetic interaction analysis）已被成功应用于预测基因功能及其通路特征。仅依托合成致死相互作用数据时，通常利用两个基因间合成致死相互作用模式的全局相似性来预测基因功能。若结合蛋白质-蛋白质相互作用（protein-protein interactions）等物理相互作用数据，则将基因子集内部物理相互作用的富集情况，以及这些基因子集间合成致死相互作用的富集情况，作为代偿通路（compensatory pathways）的判定标识。 研究结果：本文提出一种从合成致死相互作用中挖掘遗传代偿通路的方法。该方法旨在识别两类基因集对：单类基因集内部合成致死相互作用显著缺失，且此类基因集对之间存在大量合成致死相互作用。从原理上讲，该方法无需依赖物理相互作用数据，即可筛选出可相互代偿的通路对——二者功能互补，可缓冲任一通路失效所带来的有害效应。通过聚焦于单通路内基因功能高度均一的代偿通路对，本研究证实诸多细胞功能均具备遗传代偿特性。 研究结论：本研究得出如下结论：合成致死相互作用数据是挖掘遗传代偿通路的有力数据源，尤其适用于缺乏物理相互作用信息的研究体系；同时，细胞功能网络蕴含丰富的代偿特性。