Massively-parallel functional interrogation of genetic variation in LGMD-associated sarcoglycan genes

项目总结 α-，β-，γ-和δ-肌糖蛋白的突变导致肌糖病，这是肢体带状肌营养不良症的一个子集 (LGMD)对患者有毁灭性的影响，包括肌肉萎缩，进行性虚弱，变性 骨骼肌经常过早死亡。症状出现前对LGMD患者的准确诊断 或在病程早期有可能使用预防性基因疗法或其他 在大多数情况下，只有在症状前病例中才能通过基因检测进行治疗。 然而，当在患者身上观察到这些基因中的一个新的dna变异时，通常是不够的。 将其归类为致病的证据。在这项研究中，我们将使用一种新的方法来表达和描述 SGCA、SGCB、SGCg和SGCD基因中每一个可能的错义变异，以促进我们对 提高对SGC基因遗传变异的解释，促进LGMD的发展 护理和治疗。我们将使用深度突变扫描，这是一种测量大规模 一种蛋白质同时存在多个错义变体。我们将表达一个包含所有可能的SGC错义的库 并通过利用一个简单但健壮的特征来测量每个变体的效果 致病的SGC基因变异，扰乱正常的蛋白质运输。我们的两个目标是：1)量化 几乎所有可能的SGC错义变体对SGC蛋白运输和膜定位的影响 2)预测和验证每个可能的SGC错义变体的致病性 来自目标1的功能分析，为每个变体创建致病评分，并通过确认变体 使用LGMD VUS患者的组织样本进行生化预测。这些目标将揭示每个目标如何 SGC基因可能的错义变异影响表达、运输、功能或与其他SGC的相互作用 蛋白质。我们生成的功能数据、我们提出的分析以及我们构建的工具将转变 SGC变异体的特征。它们还将成为更好地了解肌聚糖生物学的资源， 利用遗传信息改进肌糖症和LGMD的临床翻译，并向新的 治疗。

PROJECT SUMMARY Mutations in α-, β-, γ-, and δ-sarcoglycan cause sarcoglyanopathies, a subset of limb-girdle muscular dystrophy (LGMD) with devastating effects for patients including muscle wasting, progressive weakness, degeneration of skeletal muscle and often premature death. Accurately diagnosing patients with LGMD before symptom onset or early in the course of the disease has the potential to enable the use of preventative gene therapy or other therapeutics and in the majority of cases can only be done in presymptomatic cases through genetic testing. When a new DNA variant in one of these genes is observed in a patient, however, there is often insufficient evidence to classify it as pathogenic. Within this study, we will use a new approach to express and characterize every possible missense variant in the SGCA, SGCB, SGCG and SGCD genes to advance our understanding of sarcoglycan biology, improve the interpretation of genetic variation in the SGC genes, and advance LGMD care and treatments. We will employ deep mutational scanning, a method for measuring the effects of massive numbers of missense variants of a protein simultaneously. We will express a library of all possible SGC missense variants in cultured human cells and measure the effect of each by exploiting a simple but robust characteristic of pathogenic SGC gene variants, disruption of proper protein trafficking. Our two aims are: 1) Quantifying the effect of nearly every possible SGC missense variant on SGC protein trafficking and membrane localization, and 2) Predict and validate the pathogenicity of every possible SGC missense variant by integrating multiple functional assays from Aim 1 to create a pathogenicity score for each variant and by confirming variant predictions biochemically using tissue samples from LGMD patients with VUS. These aims will reveal how each possible missense variant in SGC genes impact expression, transport, function or interaction with other SGC proteins. The functional data we generate, the analyses we propose, and tools we build will transform the characterization of SGC variants. They will also serve as a resource to better understand sarcoglycan biology, improve the clinical translation of sarcoglycanopathies and LGMD using genetic information, and inform new treatments.