Byrne Alexandra B, Weirauch Matthew T, Wong Victoria, Koeva Martina, Dixon Scott J, Stuart Joshua M, Roy Peter J
Department of Medical Genetics and Microbiology, The Terrence Donnelly Centre for Cellular and Biomolecular Research, 160 College St, University of Toronto, Toronto, ON, M5S 3E1, Canada.
J Biol. 2007;6(3):8. doi: 10.1186/jbiol58. Epub 2007 Sep 26.
Understanding gene function and genetic relationships is fundamental to our efforts to better understand biological systems. Previous studies systematically describing genetic interactions on a global scale have either focused on core biological processes in protozoans or surveyed catastrophic interactions in metazoans. Here, we describe a reliable high-throughput approach capable of revealing both weak and strong genetic interactions in the nematode Caenorhabditis elegans.
We investigated interactions between 11 'query' mutants in conserved signal transduction pathways and hundreds of 'target' genes compromised by RNA interference (RNAi). Mutant-RNAi combinations that grew more slowly than controls were identified, and genetic interactions inferred through an unbiased global analysis of the interaction matrix. A network of 1,246 interactions was uncovered, establishing the largest metazoan genetic-interaction network to date. We refer to this approach as systematic genetic interaction analysis (SGI). To investigate how genetic interactions connect genes on a global scale, we superimposed the SGI network on existing networks of physical, genetic, phenotypic and coexpression interactions. We identified 56 putative functional modules within the superimposed network, one of which regulates fat accumulation and is coordinated by interactions with bar-1(ga80), which encodes a homolog of beta-catenin. We also discovered that SGI interactions link distinct subnetworks on a global scale. Finally, we showed that the properties of genetic networks are conserved between C. elegans and Saccharomyces cerevisiae, but that the connectivity of interactions within the current networks is not.
Synthetic genetic interactions may reveal redundancy among functional modules on a global scale, which is a previously unappreciated level of organization within metazoan systems. Although the buffering between functional modules may differ between species, studying these differences may provide insight into the evolution of divergent form and function.
理解基因功能和遗传关系是我们更好地理解生物系统所做努力的基础。先前在全球范围内系统描述遗传相互作用的研究，要么聚焦于原生动物的核心生物过程，要么调查后生动物中的灾难性相互作用。在此，我们描述了一种可靠的高通量方法，该方法能够揭示线虫秀丽隐杆线虫中弱和强的遗传相互作用。
我们研究了保守信号转导途径中的11个“查询”突变体与数百个因RNA干扰（RNAi）而功能受损的“靶标”基因之间的相互作用。鉴定出比对照生长更缓慢的突变体-RNAi组合，并通过对相互作用矩阵进行无偏全局分析推断出遗传相互作用。发现了一个由1246个相互作用组成的网络，建立了迄今为止最大的后生动物遗传相互作用网络。我们将这种方法称为系统遗传相互作用分析（SGI）。为了研究遗传相互作用如何在全球范围内连接基因，我们将SGI网络叠加到现有的物理、遗传、表型和共表达相互作用网络上。我们在叠加网络中鉴定出56个推定的功能模块，其中一个调节脂肪积累，并通过与编码β-连环蛋白同源物的bar-1(ga80)的相互作用进行协调。我们还发现SGI相互作用在全球范围内连接不同的子网。最后，我们表明遗传网络的特性在秀丽隐杆线虫和酿酒酵母之间是保守的，但当前网络内相互作用的连通性并非如此。
合成遗传相互作用可能在全球范围内揭示功能模块之间的冗余性，这是后生动物系统中一个以前未被认识到的组织层次。尽管功能模块之间的缓冲在不同物种间可能有所不同，但研究这些差异可能有助于深入了解不同形态和功能进化。
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