Using long-range technologies as a multi-omic approach to understand Alzheimer’s disease in brain tissue

项目概要/摘要 我们的长期目标是帮助开发有意义的治疗和症状前诊断 对于阿尔茨海默病来说，因为虽然改变疾病的治疗方法是必要的，但它不会 无需在症状出现前进行诊断即可识别疾病。我们力求 通过帮助识别特定的分子修饰来为这些长期目标做出贡献，并且 因此，使用长距离光学 DNA 作图驱动疾病的特定机制 测序技术。不幸的是，大多数阿尔茨海默病基因仅与 通过常见的非功能性变异，目前尚不清楚大多数阿尔茨海默病是如何 基因与疾病有关。同样，患病大脑中的单个 RNA 同工型 人们对阿尔茨海默病基因及其与疾病的关系知之甚少。功能性 患病脑组织中异构体水平的变异和 RNA 测序将提供特定的 治疗和诊断的靶向机制。大型短读长测序工作是 已经在鉴定与阿尔茨海默病相关的小功能变异，但结构变异 DNA 变异（其中许多直接影响下游 RNA 和蛋白质）也会导致 神经退行性疾病。我们假设未发现的 SV 和异常的 RNA 亚型 在阿尔茨海默病中发挥直接作用。使用远程技术对患病大脑进行彻底研究 DNA 和 RNA 技术将补充当前的短读长努力，提供重要的 疾病见解。

PROJECT SUMMARY/ABSTRACT Our long-term goal is to help develop a meaningful therapeutic and pre-symptomatic diagnostic for Alzheimer’s disease because, while a disease-altering therapeutic is essential, it will not be sufficient without a diagnostic that identifies disease before symptoms onset. We seek to contribute to these long-term goals by helping identify specific molecular modifications, and therefore specific mechanisms, driving disease using long-range optical DNA mapping and sequencing technologies. Unfortunately, most Alzheimer’s disease genes are only implicated through common non-functional variants, and it is still unclear how most Alzheimer’s disease genes are involved in disease. Likewise, individual RNA isoforms in diseased brains for top Alzheimer’s disease genes and their involvement in disease are poorly understood. Functional variants and RNA sequencing at the isoform level in diseased brain tissue will provide specific mechanisms to target for therapeutics and diagnostics. Large short-read sequencing efforts are already ongoing to identify small functional variants involved in Alzheimer’s disease, but structural DNA variants—many of which directly affect downstream RNA and proteins—also cause neurodegenerative diseases. We hypothesize that undiscovered SVs and aberrant RNA isoforms play a direct role in Alzheimer’s disease. A thorough study in diseased brain using long-range DNA and RNA technologies will complement current short-read efforts, providing important disease insights.