Jungers Center for Neurosciences, Oregon Health and Science University, Portland, Oregon 97239.
Department of Neurology, Oregon Health and Science University, Portland, Oregon 97239.
Genetics. 2018 Aug;209(4):1345-1356. doi: 10.1534/genetics.118.301119. Epub 2018 Jun 15.
Disease phenotypes can be highly variable among individuals with the same pathogenic mutation. There is increasing evidence that background genetic variation is a strong driver of disease variability in addition to the influence of environment. To understand the genotype-phenotype relationship that determines the expressivity of a pathogenic mutation, a large number of backgrounds must be studied. This can be efficiently achieved using model organism collections such as the Genetic Reference Panel (DGRP). Here, we used the DGRP to assess the variability of locomotor dysfunction in a LRRK2 G2019S model of Parkinson's disease (PD). We find substantial variability in the LRRK2 G2019S locomotor phenotype in different DGRP backgrounds. A genome-wide association study for candidate genetic modifiers reveals 177 genes that drive wide phenotypic variation, including 19 top association genes. Genes involved in the outgrowth and regulation of neuronal projections are enriched in these candidate modifiers. RNAi functional testing of the top association and neuronal projection-related genes reveals that , , , and significantly modify age-related dopamine neuron loss and associated locomotor dysfunction in the LRRK2 G2019S model. These results demonstrate how natural genetic variation can be used as a powerful tool to identify genes that modify disease-related phenotypes. We report novel candidate modifier genes for LRRK2 G2019S that may be used to interrogate the link between LRRK2, neurite regulation and neuronal degeneration in PD.
具有相同致病性突变的个体之间的疾病表型可能高度不同。越来越多的证据表明,除了环境的影响外,背景遗传变异也是疾病变异性的一个重要驱动因素。为了了解决定致病性突变表达的基因型-表型关系,必须研究大量的背景。这可以通过使用遗传参考面板(DGRP)等模式生物集合来有效地实现。在这里,我们使用 DGRP 来评估 LRRK2 G2019S 帕金森病(PD)模型中运动功能障碍的可变性。我们发现不同 DGRP 背景下 LRRK2 G2019S 运动表型存在很大差异。候选遗传修饰物的全基因组关联研究揭示了 177 个驱动广泛表型变异的基因,包括 19 个顶级关联基因。参与神经元突起的生长和调节的基因在这些候选修饰物中富集。对顶级关联和神经元突起相关基因的 RNAi 功能测试表明, 、 、 和 显著修饰了 LRRK2 G2019S 模型中与年龄相关的多巴胺神经元丢失和相关运动功能障碍。这些结果表明,自然遗传变异如何可作为识别修饰疾病相关表型的基因的有力工具。我们报告了 LRRK2 G2019S 的新候选修饰基因,这些基因可能用于探究 LRRK2、神经突调节和 PD 中神经元退化之间的联系。