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Genome-Wide Association Data Reveal a Global Map of Genetic Interactions among Protein Complexes

机译:全基因组关联数据揭示了蛋白质复合物之间遗传相互作用的全球地图。

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This work demonstrates how gene association studies can be analyzed to map a global landscape of genetic interactions among protein complexes and pathways. Despite the immense potential of gene association studies, they have been challenging to analyze because most traits are complex, involving the combined effect of mutations at many different genes. Due to lack of statistical power, only the strongest single markers are typically identified. Here, we present an integrative approach that greatly increases power through marker clustering and projection of marker interactions within and across protein complexes. Applied to a recent gene association study in yeast, this approach identifies 2,023 genetic interactions which map to 208 functional interactions among protein complexes. We show that such interactions are analogous to interactions derived through reverse genetic screens and that they provide coverage in areas not yet tested by reverse genetic analysis. This work has the potential to transform gene association studies, by elevating the analysis from the level of individual markers to global maps of genetic interactions. As proof of principle, we use synthetic genetic screens to confirm numerous novel genetic interactions for the INO80 chromatin remodeling complex.
机译:这项工作证明了如何可以分析基因关联研究,以绘制蛋白质复合物和途径之间遗传相互作用的全球概况。尽管基因关联研究的潜力巨大,但由于大多数性状很复杂,涉及许多不同基因突变的综合作用,因此对它们的分析仍具有挑战性。由于缺乏统计能力,通常只能识别最强的单个标记。在这里,我们提出了一种整合的方法,该方法可通过标记聚类和投射蛋白质复合物内部和之间的标记相互作用来大大增强功能。该方法应用于最近的酵母基因关联研究中,可确定2023个遗传相互作用,这些相互作用映射到蛋白质复合物之间的208个功能相互作用。我们表明,这种相互作用类似于通过反向遗传筛选获得的相互作用,并且它们提供了尚未通过反向遗传分析测试的区域的覆盖范围。通过将分析从单个标记物的水平提升到遗传相互作用的全球图谱,这项工作具有转化基因关联研究的潜力。作为原理的证明,我们使用合成基因筛选来确认INO80染色质重塑复合物的众多新型遗传相互作用。

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