Incomplete Penetrance via Edgetic Suppression

摘要 在人类基因组序列公布15年后，我们对人类基因组的理解有多好？ 基因型-表型关系的分子机制？重要的是，当我们产生- 越来越多的基因组序列来自患病的，但也健康的个体，我们如何预测， 从基因型的信息中推断出个体的表型？我们越了解 人类基因组，我们似乎越偏离简单的模型：“基因X的突变导致 基因产物X的扰动，其导致疾病A”。在最流行和最神秘的 从这个简单的模型的偏差是：（i）不完全的遗传，其中只有一个子集的个人携带 突变受疾病影响，和（ii）可变的表达性，其中不是所有受突变影响的个体都受疾病影响。 突变的影响是一样的。这两个相互关联的现象最近引起了关注 由于健康个体的外显子组和基因组测序显示出意想不到的负担， 破坏性突变，平均约300个破坏性变体和>50个导致孟德尔遗传的变体。 紊乱这种破坏性变异的负担表明了一种迄今未被认识到的遗传弹性水平。 基因产物在复杂的相互作用组网络中发挥作用，这一点越来越清楚 需要考虑到充分阐明基因型-表型关系。蛋白质组规模系统 相互作用组图谱，它将这些分子组分的网络和它们之间的相互作用建模为 “节点”和“边缘”分别迅速变得可用于启动这样的方法。我们已经开始 剖析疾病相关突变如何损害相互作用网络的背景下的相互作用。我们 他们发现，虽然来自健康个体的常见变异很少影响蛋白质-蛋白质相互作用， 在DNA-蛋白质相互作用中，大多数疾病相关等位基因干扰相互作用，约有一半 对应于我们所称的“边缘特异性”或“边缘性”等位基因，即影响单个或多个等位基因的等位基因。 相互作用的子集，同时保持其他相互作用不受干扰。 这项拨款申请的重点是了解基于基因-基因相互作用的不完全遗传。 我们的中心假设是，不完全的边缘等位基因通常可以最好地解释， 在基因上被相互作用的伴侣中的补偿等位基因抑制。由于巨大的限制， 为了在人类中检验这种“边缘抑制”假设，我们将首先集中于S。 酿酒酵母作为一个模式生物，发展必要的概念，方法和工具。我们将利用 最近发布了约1，000个酵母基因组序列，以识别和表征大量的 这些自然变异个体具有破坏性，但却具有协同作用。制定的战略和 所发现的一般机制将直接适用于解决人类的不完全昏迷。

Abstract A decade and a half after the release of the human genome sequence, how well do we understand the molecular mechanisms underlying genotype-phenotype relationships? Importantly, as we generate ever- increasing numbers of genome sequences from diseased but also healthy individuals, how well can we predict the phenotype of an individual from information available about their genotype? The more we learn about the human genome, the further we seem to deviate from the simple model: “mutation in gene X leads to perturbation of gene product X, which leads to disease A”. Among the most prevailing and mysterious deviations from this simple model are: (i) incomplete penetrance, whereby only a subset of individuals carrying a mutation are affected by the disease, and (ii) variable expressivity, whereby not all individuals affected by a given mutation are affected equally. These two interconnected phenomena have recently attracted attention because sequencing of exomes and genomes of healthy individuals shows an unanticipated burden of damaging mutations, with an average of ~300 damaging variants and >50 variants causing Mendelian disorders. This burden of damaging variants suggests a heretofore-unrecognized level of genetic resilience. It is becoming increasingly clear that gene products function in the context of complex interactome networks that need to be considered to fully illuminate genotype-phenotype relationships. Proteome-scale systematic interactome maps, which model these networks of molecular components and interactions between them as “nodes” and “edges”, respectively, are rapidly becoming available to initiate such approaches. We have started to dissect how disease-associated mutations impair interactions in the context of interactome networks. We have found that while common variants from healthy individuals rarely affect protein-protein interactions or DNA-protein interactions, a majority of disease-associated alleles perturb interactions, with about half corresponding to what we refer to as “edge-specific” or ``edgetic'' alleles, i.e. alleles affecting a single or a subset of interactions while leaving other interactions unperturbed. This grant application is focused on understanding incomplete penetrance based on gene-gene interactions. Our central hypothesis is that incomplete penetrance can very often be best explained by edgetic alleles that are genetically suppressed by compensatory alleles in interacting partners. Due to a huge limitation in statistical power to test this “edgetic suppression” hypothesis in human, we will first concentrate on S. cerevisiae as a model organism to develop the necessary concepts, methods and tools. We will leverage the recent release of ~1,000 yeast genome sequences to identify and characterize large numbers of pairs of natural variants that are damaging individually, but cooperatively functional. The strategies developed and general mechanisms discovered will be directly applicable to solving incomplete penetrance in humans.