Use of Pleiotropy to Model Genetic Interactions in a Population
Use of Pleiotropy to Model Genetic Interactions in a Population
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DOI：
10.1371/journal.pgen.1003010
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发表时间：
2012-10-01
期刊：
影响因子：
4.5
通讯作者：
Galitski, Timothy
中科院分区：
文献类型：
--
作者：
Carter, Gregory W.;Hays, Michelle;Galitski, Timothy
人类和模型系统的系统级遗传学研究越来越多地涉及高分辨率基因分型和多维定量表型。我们提出了一种新的方法来推断和解释遗传相互作用，利用互补信息在多个表型。我们将这种方法应用到一个酵母菌株的人口与随机分类的干扰五个基因参与交配。我们在分子水平上定量信息素反应和整体交配效率。这些表型进行了联合分析，以获得一个网络的遗传相互作用，映射交配途径的关系。为了确定驱动表型互补性的不同生物过程，我们分析了基因表达模式，发现信息素反应表型对细胞融合是特异性的，而交配效率是细胞融合、细胞周期阻滞和细胞代谢修饰的综合指标。我们将我们的新方法应用于全球基因表达模式，以获得表达特异性相互作用网络，并证明其适用于全球转录数据。我们的方法为解释遗传相互作用和从多表型检测的群体中产生特定假设提供了基础。
Systems-level genetic studies in humans and model systems increasingly involve both high-resolution genotyping and multi-dimensional quantitative phenotyping. We present a novel method to infer and interpret genetic interactions that exploits the complementary information in multiple phenotypes. We applied this approach to a population of yeast strains with randomly assorted perturbations of five genes involved in mating. We quantified pheromone response at the molecular level and overall mating efficiency. These phenotypes were jointly analyzed to derive a network of genetic interactions that mapped mating-pathway relationships. To determine the distinct biological processes driving the phenotypic complementarity, we analyzed patterns of gene expression to find that the pheromone response phenotype is specific to cellular fusion, whereas mating efficiency was a combined measure of cellular fusion, cell cycle arrest, and modifications in cellular metabolism. We applied our novel method to global gene expression patterns to derive an expression-specific interaction network and demonstrate applicability to global transcript data. Our approach provides a basis for interpretation of genetic interactions and the generation of specific hypotheses from populations assayed for multiple phenotypes.