Non-coding Variants Predisposing to Age-related Macular Degeneration

 描述（由申请人提供）：每个个体的基因组含有数百万个核苷酸变异，主要挑战是了解这些变异如何导致群体中的表型变异。我们提出了一个计算和实验相结合的框架，用于识别影响细胞和生理性状的非编码变体，其目标是建立计算模型，该模型可以预测从非编码基因组区域的序列中表现出生理性状的概率。该框架涉及通过实验对模型假设和参数进行迭代细化。为了开发框架并验证预测模型，我们将重点关注与疾病相关的黄斑变性（AMD），这是该国老年人失明的主要原因。先前的研究已经确定了许多与AMD强烈相关的序列变异。我们将开发计算模型来预测（或缩小）导致疾病表型的非编码序列变异集。作为实验评估，我们将在患者来源的诱导多能干细胞（iPSC）中进行基因组编辑，以测试在细胞培养物和啮齿动物模型中去除或引入此类序列变体对分子和细胞表型的影响。虽然所提出的方法是为AMD开发的，但一般方法预计将适用于其他遗传性疾病。

 DESCRIPTION (provided by applicant): The genome of each individual harbors millions of nucleotide variants, and a major challenge is to understand how these variants contribute to phenotypic variations in the population. We propose a combined computational and experimental framework for identifying non-coding variants that affect cellular and physiological traits, with the goal to establish computational models that can predict the probability of exhibiting a physiological trait from the sequences of non-coding genomic regions. This framework involves iterative refinement of model assumptions and parameters with experimentation. To develop the framework and validate the predictive models, we will focus on the disease Age-related Macular Degeneration (AMD), the leading cause of blindness among the elderly in the country. Previous studies have identified a number of sequence variants strongly associated with AMD. We will develop computational models to predict (or narrow down) the set of non-coding sequence variants that contribute to the disease phenotype. As experimental assessment, we will perform genome editing in patient-derived induced pluripotent stem cells (iPSC) to test the consequence of removing or introducing such sequence variants on molecular and cellular phenotypes in cell culture and in rodent models. While the proposed method is developed for AMD, the general approach is expected to apply to other genetic diseases.