High throughput methods for Synthetic Genetic Array Analysis in C. elegans

描述(由申请人提供)： 线虫的2万多个基因中，只有一小部分适用于传统的遗传学研究方法。在酵母对双突变体的系统研究中，利用酵母缺失集合，揭示了整个基因组中基因之间的相互作用，并允许推断大多数原本未知功能的基因的功能。在这里，我们建议开发方法，以便在线虫中进行类似的研究。我们将开发最近完成的测序突变菌株资源，该资源包含基因组中几乎每个基因的非同义变化。这些菌株将暴露在RNAi中，以寻找与野生型和其他突变菌株的RNAi或在没有RNAi的情况下的RNAi的差异所反映的相互作用。为了提高效率和简化比较，这些菌株将在100人或更多的池中相互竞争，利用生长作为一系列表型的替代品。将使用分子反转探针(MIP)跟踪池中单个菌株的丰度，以寻找通过高通量测序量化的独特突变。通过比较对照、其他RNAs和群体遗传模型的丰度，我们将确定哪些菌株与每个RNAi显示出显著的正或负相互作用。为了确定每个菌株中的哪些突变是与RNAi相互作用的基础，我们将每个相互作用的菌株与一个多标记菌株杂交，在一个池中与RNAi竞争后代，并使用批量分离分析来确定相互作用的基因座。我们将使用一组RNAi来测试这些方法，这些基因来自文献中包括阳性和阴性对照的基因，来自TWK-钾通道家族的基因(充当二聚体但单独是可有可无的)，以及来自广泛代表基因组的基因，以评估方法的整体效率。这些方法的成功实施将为在整个蠕虫基因组中系统研究SGA铺平道路，为了解未知功能的基因的作用提供了有价值的见解。它还将为对这些基因和网络进行更详细的研究提供一个框架。这也可能启发对更复杂的生物体开发类似的方法。更全面地了解后生动物模型中的遗传相互作用，可以反过来为人类可能的基因-基因相互作用提供洞察力。

DESCRIPTION (provided by applicant): Only a fraction of the more than 20,000 genes in the nematode C. elegans have been amenable to traditional methods of genetic study. In yeast systematic investigations of double mutants, exploiting the yeast deletion collection, have revealed interactions between genes across the genome and have permitted inference of function for most genes of otherwise unknown function. Here we propose to develop methods that will permit analogous studies in C. elegans. We will exploit a recently completed resource of sequenced mutant strains that contains nonsynonymous changes in almost every gene in the genome. These strains will be exposed to RNAi to look for interactions as reflected in differences compared to the RNAi against wild type and other mutant strains or the strain in the absence of RNAi. To increase the efficiency and simplify comparison, the strains will be competed against one another in pools of 100 or more, using growth as a surrogate for a host of phenotypes. The abundance of individual strains in the pools will be followed using molecular inversion probes (MIPs) for the unique mutations quantified by high-throughput sequencing. By comparing the abundance relative to controls, other RNAs and population genetic models, we will determine which strains show a significant positive or negative interaction with each RNAi. To determine which of the various mutations within each strain underlie the interaction with the RNAi, we will cross each interacting strain with a multiply marked strain, compete the progeny in a pool with the RNAi and use bulk segregant analysis to identify the interacting loci. We will test the methods using a battery of RNAi's from genes that include positive and negative controls from the literature, from genes of the twk- family of potassium channels that act as dimers but are individually dispensable, and from genes broadly representative of the genome to assess the overall efficiency of the methods. The successful implementation of these methods will pave the way for systematic investigation of SGA across the worm genome, providing valuable insight into the role of genes without previously known function. It will also provide a framework for more detailed investigations of these genes and networks. It may also inspire the development of analogous methods for still more complex organisms. A more comprehensive understanding of genetic interactions in this model metazoan can in turn provide insight into likely gene-gene interactions in human.