Trigenic interactions in yeast link bioprocesses To dissect the genotype-phenotype landscape of a cell, it is necessary to understand interactions between genes. Building on the digenic protein-protein interaction network, Kuzmin et al. created a trigenic landscape of yeast by using a synthetic genetic array (see the Perspective by Walhout). Triple-mutant analyses indicated that the majority of genes with trigenic associations functioned within the same biological processes. These converged on networks identified in the digenic interaction landscape. Although the overall effects were weaker for trigenic than for digenic interactions, trigenic interactions were more likely to bridge biological processes in the cell. Science, this issue p. eaao1729; see also p. 269 Trigenic interactions in yeast link bioprocesses are explored. INTRODUCTION Genetic interactions occur when mutations in different genes combine to result in a phenotype that is different from expectation based on those of the individual mutations. Negative genetic interactions occur when a combination of mutations leads to a fitness defect that is more exacerbated than expected. For example, synthetic lethality occurs when two mutations, neither of which is lethal on its own, generate an inviable double mutant. Alternatively, positive genetic interactions occur when genetic perturbations combine to generate a double mutant with a greater fitness than expected. Global digenic interaction studies have been useful for understanding the functional wiring diagram of the cell and may also provide insight into the genotype-to-phenotype relationship, which is important for tracking the missing heritability of human health and disease. Here we describe a network of higher-order trigenic interactions and explore its implications. RATIONALE Variation in phenotypic outcomes in different individuals is caused by genetic determinants that act as modifiers. Modifier loci are prevalent in human populations, but knowledge regarding how variants interact to modulate phenotype in different individuals is lacking. Similarly, in yeast, traits including conditional essentiality—in which certain genes are essential in one genetic background but nonessential in another—often result from an interplay of multiple modifier loci. Because complex modifiers may underlie the genetic basis of physiological states found in natural populations, it is critical to understand the landscape of higher-order genetic interactions. RESULTS To survey trigenic interactions, we designed query strains that sampled key features of the global digenic interaction network: (i) digenic interaction strength, (ii) average number of digenic interactions, and (iii) digenic interaction profile similarity. In total, we tested ~400,000 double and ~200,000 triple mutants for fitness defects and identified ~9500 digenic and ~3200 trigenic negative interactions. Although trigenic interactions tend to be weaker than digenic interactions, they were both enriched for functional relationships. About one-third of trigenic interactions identified “novel” connections that were not observed in our digenic control network, whereas the remaining approximately two-thirds of trigenic interactions “modified” a digenic interaction, suggesting that the global digenic interaction network is important for understanding the trigenic interaction network. Despite their functional enrichment, trigenic interactions also bridged distant bioprocesses. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance. CONCLUSION The extensive network of trigenic interactions and their ability to generate functionally diverse phenotypes suggest that higher-order genetic interactions may play a key role in the genotype-to-phenotype relationship, genome size, and speciation. Systematic analysis of trigenic interactions. We surveyed for trigenic interactions and found that they are ~100 times as prevalent as digenic interactions, often modify a digenic interaction, and connect functionally related genes as well as genes in more diverse bioprocesses (multicolored nodes). PPI, protein-protein interaction. To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship.

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复杂遗传相互作用的系统分析


酵母中的三基因相互作用连接生物过程为了剖析细胞的基因型-表型景观，有必要了解基因之间的相互作用。 Kuzmin 等人以双基因蛋白质-蛋白质相互作用网络为基础。通过使用合成基因阵列创建了酵母的三基因景观（参见 Walhout 的观点）。三重突变分析表明，大多数具有三基因关联的基因在相同的生物过程中发挥作用。这些汇聚在双基因相互作用景观中确定的网络上。尽管三基因相互作用的总体效果比双基因相互作用弱，但三基因相互作用更有可能桥接细胞中的生物过程。科学，本期第 14 页。 eaao1729;另见 p.第269章 探索酵母环节生物过程中的三基因相互作用。引言 当不同基因的突变结合起来产生与基于单个突变的预期不同的表型时，就会发生遗传相互作用。当突变组合导致健康缺陷比预期更加严重时，就会发生负面的遗传相互作用。例如，当两个突变（两者本身都不致命）产生不可生存的双突变体时，就会发生合成致死。或者，当遗传扰动结合起来产生比预期更适合的双突变体时，就会发生积极的遗传相互作用。全局双基因相互作用研究有助于理解细胞的功能接线图，也可能提供对基因型与表型关系的深入了解，这对于追踪人类健康和疾病缺失的遗传性非常重要。 在这里，我们描述了高阶三基因相互作用的网络并探讨了其含义。基本原理 不同个体表型结果的差异是由充当修饰因子的遗传决定因素引起的。修饰位点在人群中普遍存在，但缺乏关于变异如何相互作用以调节不同个体表型的知识。同样，在酵母中，包括条件必要性在内的性状（其中某些基因在一种遗传背景中是必需的，但在另一种遗传背景中是非必需的）通常是由多个修饰基因座的相互作用产生的。由于复杂的修饰因子可能是自然群体中生理状态的遗传基础的基础，因此了解高阶遗传相互作用的景观至关重要。结果为了调查三基因相互作用，我们设计了对全球双基因相互作用网络的关键特征进行采样的查询菌株：（i）二基因相互作用强度，（ii）二基因相互作用的平均数量，以及（iii）双基因相互作用概况相似性。总的来说，我们测试了约 400,000 个双突变体和约 200,000 个三突变体的适应性缺陷，并鉴定了约 9500 个双基因和约 3200 个三基因负相互作用。尽管三基因相互作用往往比二基因相互作用弱，但它们的功能关系都丰富了。大约三分之一的三基因相互作用识别出在我们的双基因控制网络中未观察到的“新”连接，而其余约三分之二的三基因相互作用“修改”了双基因相互作用，这表明全局双基因相互作用网络对于理解非常重要三基因相互作用网络。尽管功能丰富，三基因相互作用也桥接了遥远的生物过程。 我们估计全局三基因相互作用网络大约是全局双基因网络的 100 倍，这凸显了复杂的遗传相互作用影响遗传生物学的潜力。结论 三基因相互作用的广泛网络及其产生功能多样化表型的能力表明，高阶遗传相互作用可能在基因型与表型关系、基因组大小和物种形成中发挥关键作用。三基因相互作用的系统分析。我们调查了三基因相互作用，发现它们的普遍性约为双基因相互作用的 100 倍，经常修改双基因相互作用，并连接功能相关的基因以及更多样化的生物过程（彩色节点）中的基因。 PPI，蛋白质-蛋白质相互作用。为了系统地探索复杂的遗传相互作用，我们构建了约 200,000 个酵母三重突变体，并对负三基因相互作用进行了评分。我们在广泛的生物过程中选择了双突变查询基因，涵盖了全球双基因相互作用网络的一系列定量特征，并测试了与第三个突变的遗传相互作用。三基因相互作用经常发生在功能相关的基因之间，而必需基因是三基因网络的枢纽。尽管其功能丰富，但三基因相互作用倾向于连接遥远生物过程中的基因，并且表现出比二基因相互作用更弱的程度。我们估计全局三基因相互作用网络大约是全局双基因网络的 100 倍，这凸显了复杂的遗传相互作用影响遗传生物学的潜力，包括基因型与表型的关系。