Incomplete Penetrance via Edgetic Suppression

摘要 在人类基因组序列公布15年后，我们对 基因-表型关系的分子机制？重要的是，当我们产生- 越来越多的来自疾病和健康个体的基因组序列，我们能预测得有多好 一个人的表型是从关于他们的基因的信息中获得的吗？我们了解的越多， 人类基因组，我们似乎越背离简单的模型：X基因突变导致 基因产物X的扰动，导致疾病A“。在最流行和最神秘的 与这一简单模型的偏差是：(I)不完全外显，即只有一部分人携带 突变会受到疾病的影响，以及(Ii)可变的表达能力，在这种情况下，并非所有受 给定的突变同样会受到影响。这两个相互关联的现象最近引起了人们的注意。 因为健康个体的外显子和基因组的测序显示了一种意想不到的负担 破坏性突变，平均约300个破坏性变异和50个导致孟德尔突变的变异 精神错乱。这种破坏性变异的负担表明了迄今未被认识到的遗传韧性水平。 越来越清楚的是，基因产物在复杂的相互作用组网络中发挥作用 需要考虑这一点，以充分阐明基因-表型之间的关系。蛋白质组尺度系统 相互作用组图，它将这些分子组成的网络和它们之间的相互作用建模为 “节点”和“边”分别正迅速成为可用于启动此类方法的工具。我们已经开始了 剖析疾病相关突变如何损害相互作用组网络中的相互作用。我们 已经发现，虽然来自健康个体的常见变体很少影响蛋白质-蛋白质相互作用或 DNA-蛋白质相互作用，大多数与疾病相关的等位基因干扰相互作用，约有一半 对应于我们所说的“边缘特定的”或“边缘的”等位基因，即影响单个或一个 交互的子集，同时保持其他交互不受干扰。 这项资助申请的重点是了解基于基因-基因相互作用的不完全外显。 我们的中心假设是，不完全外显通常可以用边缘等位基因来最好地解释 在相互作用的伴侣中被补偿等位基因所抑制。由于存在巨大的限制， 为了检验这一“边缘抑制”假说在人类身上的统计能力，我们首先将重点放在S。 酿酒酵母作为模式生物，需要发展必要的概念、方法和工具。我们将利用 最近公布了~1,000个酵母基因组序列，以鉴定和表征大量的 单独具有破坏性，但具有协同功能的自然变异。制定的战略和 已发现的一般机制将直接适用于解决人类的不完全外显问题。

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.