Long-read DNA and RNA sequencing to identify disease-causing genetic variation and streamline testing

项目总结/摘要 临床基因检测，包括外显子组测序，已诊断出许多罕见和新型遗传疾病。 这些诊断有助于指导治疗，提出新的或精确的治疗方法，并提供长期的治疗。 个人及其家庭的预后信息。然而，至少有50%的人怀疑 遗传性疾病在完整临床评估后仍未确诊，这可能需要数年时间才能完成。 有两个主要的技术原因，这种低解决率。首先，结构变异，如大缺失， 插入，倒置和重复扩展占未解决案件的很大一部分，但它们 使用传统的短读测序技术进行分析具有挑战性。其次，许多变体存在于 最近复制的基因组区域难以使用短读测序技术进行评估。 近年来，对人类基因组进行全基因组长读段测序（LRS）在经济上已经变得可行。 这些基因组具有足够的覆盖范围来分析这些复杂的基因组区域。这提供了一个机会， 系统评价LRS在当前检测方法上的增量诊断率，并应用LRS 这项技术应用于一大群患有未解决的遗传疾病的个体。此外，LRS的独特之处在于， 它有可能取代几乎所有现有的临床基因检测（微阵列，外显子组，甲基化）。 研究），使得可以使用单个基因组在几天到几周内进行完整的临床遗传评估。 数据集。该项目的总体目标是建立一个框架，用于临床采用长读段DNA， 通过对疑似或未解决的遗传性疾病个体进行系统评估进行RNA测序。到 为了实现这一目标，LRS将对50名危重新生儿及其父母进行非诊断性检查， 三人短读全基因组测序（WGS）和来自同一队列的25名诊断性WGS的三人组 (Aim 1）。这将有助于建立LRS相对于短读WGS的增量诊断率。评价 由于LRS技术优于传统临床检测，我将对50名疑似 至少在临床外显子组测序后仍未解决的遗传性疾病（Aim 2）。最多20人， 在LRS后仍然未被诊断，长读RNA测序将用于识别高优先级区域， 影响基因表达或剪接以用于进一步分析。然后，我将评估LRS的灵敏度作为一个单一的 通过对50名接受典型门诊临床评估的个体进行测序进行基因检测（目标3）。 证明LRS可用作单一数据源将有助于简化当前的逐步方法 临床检测，从而提高诊断率，并为卫生系统节省整体成本 通过减少检测和诊所访问。总的来说，本提案中概述的目标将使患者受益， 通过提高基因诊断率，减少诊断时间， 致病机制，这将导致更好地了解人类疾病的原因。

PROJECT SUMMARY/ABSTRACT Clinical genetic testing, including exome sequencing, has diagnosed many rare and novel genetic disorders. These diagnoses have helped guide treatment, suggest novel or precision therapies, and provide long-term prognostic information for individuals and their families. However, at least 50% of individuals with a suspected genetic disorder remain undiagnosed after a complete clinical evaluation, which can take years to complete. There are two major technical reasons for this low solve rate. First, structural variants such as large deletions, insertions, inversions, and repeat expansions account for a significant fraction of unsolved cases, but they are challenging to analyze using traditional short-read sequencing technologies. Second, many variants lie in recently duplicated genomic regions that are difficult to evaluate using short-read sequencing technologies. Recently, it has become economically feasible to pursue whole-genome long-read sequencing (LRS) of human genomes with sufficient coverage to analyze these complex genomic regions. This presents an opportunity to systematically evaluate the incremental diagnostic rate of LRS over current testing approaches and apply LRS technology to a large cohort of individuals with unsolved genetic disorders. Moreover, LRS is unique in that as a single test it has the potential to replace nearly all existing clinical genetic testing (microarray, exome, methylation studies), making it possible to perform a complete clinical genetic evaluation in days to weeks using a single dataset. The overall goal of this project is to establish a framework for the clinical adoption of long-read DNA and RNA sequencing by systematic evaluation of individuals with suspected or unsolved genetic disorders. To achieve this goal, LRS will be performed on 50 critically ill neonates and their parents who had nondiagnostic trio short-read whole-genome sequencing (WGS) and 25 trios from the same cohort who had diagnostic WGS (Aim 1). This will help establish the incremental diagnostic rate of LRS over short-read WGS. To evaluate the technical advantages of LRS over traditional clinical testing, I will sequence 50 individuals with a suspected genetic disorder who remain unsolved after at least clinical exome sequencing (Aim 2). In up to 20 persons that remain undiagnosed after LRS, long-read RNA sequencing will be used to identify high-priority regions that influence gene expression or splicing for further analysis. I will then evaluate the sensitivity of LRS as a single genetic test by sequencing 50 individuals undergoing a typical outpatient clinical evaluation (Aim 3). Demonstrating that LRS can be used as a single data source will help streamline the current stepwise approach to clinical testing, leading to an increase in the diagnostic rate and an overall cost savings to the health system through reduced testing and clinic visits. Overall, the aims outlined in this proposal will benefit patients and families by increasing the rate of genetic diagnosis, decreasing the time to diagnosis, and identifying novel disease-causing mechanisms, which will lead to a better understanding of the causes of human disease.