Clinical Diagnostic Sequencing of Structural Variation

 描述(由申请人提供)：该项目提出了一种创新的、低成本的全基因组测序(WGS)测试，用于全基因组结构变异(SV)的描绘，以捕捉目前通过两种较低分辨率方法检测到的致病变异的全谱。全基因组SV研究是ACMG推荐的对包括自闭症谱系障碍在内的无数先天性异常的第一级诊断筛查。诊断SV筛查依赖于染色体组型或染色体微阵列(CMA)。核型分析可以在显微分辨率下检测到平衡的染色体重排(BCR)，但对较小的改变不敏感，而CMA可以检测到拷贝数变异(CNV)，但不能检测到BCR。目前，还没有一种有效的全基因组方法可以在一次诊断测试中同时识别BCR和CMA分辨率的CNV，这就留下了不可避免的盲区，这取决于所选择的技术。此外，亚显微的BCR对于所有传统的诊断来说都是棘手的，并且代表了基因组变异中最后未被探索的空间之一。我们已经证明，大插入的WGS或“跳跃”文库可以在研究能力中描绘BCR和CNV。我们最近还通过提供宫内产前诊断展示了它的临床潜力(Talkowski等人，2012，N Engl J Med)。在我们连续发表的一篇关于产前测序的论文中，Co-I Wapner及其同事通过NICHD的一个由4,340份同时进行核型分析和CMA的产前样本联盟，验证了CMA是产前诊断的首选方法(Wapner等人，2012，N Engl J Med)。在这里，我们建议在这些特征良好的产前样本中验证跳跃文库测序用于常规SV检测。我们将在目标1中执行关键验证，以确定我们的测序方法的敏感性，以捕获通过核型分析和CMA检测到的所有致病SVS，从而为基因发现提供精确的序列解析。在目标2中，我们将从常规方法未能检测到致病突变的最高产量诊断队列(超声缺陷)中，校准至少400个三联体中隐蔽SVS的附加诊断价值。我们的初步数据表明，隐蔽的SVS占致病突变的5.3-9.4%；这是诊断产量的一个重要组成部分，目前尚不清楚。在目标3中，我们将把来自学术和商业诊断网站联盟的CMA数据与博德研究所的外显子组聚合项目整合在一起，这将共同代表&gt；20万个受试者的融合。我们将比较传统标准的诊断效率和基于基因组数据集收敛的定量风险评分。最终产品将是单一测序平台的验证，以克服两种较低分辨率方法的局限性，根据目前尚未确定的基因组变异类别确定临床产量，以及创建可公开访问的基因组注释资源。该项目可能对基因诊断实践产生立竿见影的变革性影响。

 DESCRIPTION (provided by applicant): This project proposes an innovative, low-cost whole-genome sequencing (WGS) test for the genome-wide delineation of structural variation (SV) to capture the full spectrum of pathogenic variation that is currently detected by two lower-resolution methods. Genome-wide SV studies are the ACMG recommended first-tier diagnostic screen for a myriad of congenital anomalies, including autism spectrum disorder. Diagnostic SV screening relies on karyotyping or chromosomal microarray (CMA). Karyotyping can detect balanced chromosomal rearrangements (BCRs) at microscopic resolution but is insensitive to smaller alterations, whereas CMA can detect copy number variants (CNVs) but not BCRs. At present, no validated genome-wide method can identify both BCRs and CMA-resolution CNVs in a single diagnostic test, leaving inevitable blind spots depending on the technology chosen. Moreover, submicroscopic, or `cryptic', BCRs are intractable to all conventional diagnostics and represent one of the last unexplored spaces of genomic variation. We have shown that large-insert WGS, or `jumping' libraries, can delineate both BCRs and CNVs in a research capacity. We have also recently demonstrated its clinical potential by providing an in utero prenatal diagnosis (Talkowski et al., 2012, N Engl J Med). In a paper published back-to-back with our prenatal sequencing, Co-I Wapner and colleagues validated CMA as the preferred method for prenatal diagnostics through an NICHD consortium of 4,340 prenatal samples with both karyotyping and CMA (Wapner et al., 2012, N Engl J Med). Here, we propose to validate jumping library sequencing for routine SV detection in these well-characterized prenatal samples. We will perform a critical validation in Aim 1 to determine the sensitivity of our sequencing method to capture all pathogenic SVs detected by karyotyping and CMA, with the benefit of precise sequence resolution for gene discovery. In Aim 2, we will calibrate the added diagnostic value of cryptic SVs in at least 400 trios from the highest yield diagnostic cohort (ultrasound defects) for which conventional methods failed to detect a causative mutation. Our preliminary data suggest that cryptic SVs account for 5.3-9.4% of pathogenic mutations; an important component of the diagnostic yield that is presently uncharacterized. In Aim 3, we will integrate CMA data from a consortium of academic and commercial diagnostic sites with the exome aggregation project at the Broad Institute, which will collectively represent an amalgamation of >200,000 subjects. We will compare diagnostic yield from conventional criteria to a quantitative risk score based on the convergence of genomics datasets. The final product will be the validation of a single sequencing platform to overcome the limitations of two lower-resolution methods, the determination of clinical yield from a currently uncharacterized class of genomic variation, and the creation of a publicly accessible genome annotation resource. This project could have an immediate and transformative impact on genetic diagnostic practice.