Computational Prioritization of Coding and Non-Coding Variants in Congenital Heart Disease

项目概要： 先天性心脏病（CHD）是出生时最常见的异常，影响1%的婴儿。损伤基因 变异对CHD风险有显著影响，但仅在50%的患者中确定了可能的遗传原因。的 其余一半CHD的遗传基础尚不清楚。加布里埃拉米勒儿童第一（GMKF）和TOPMed 项目资助的全基因组测序（WGS）来测试我们的假设，即全基因组测序未检测到的变异。 外显子组测序（WES）有助于CHD。来自1813例CHD三人组的WGS（受影响的先证者和父母） 提供了一个独特的机会来定义额外的编码和非编码变异，传达冠心病的风险。 首先，将全面分析CHD测序数据中的编码变体。WGS允许改进 检测WES未检测到的破坏性编码变异，包括结构变异和变异 在WES捕获区域之外。因此，在目标1中，破坏性结构、嵌合体和单核苷酸变体 将在WGS数据中识别。新的CHD基因与CHD中的破坏性编码变体相比 将确定非CHD队列。冠心病心肌组织基因表达与WGS的整合 数据将优先考虑可能影响发育基因调控的非编码变异。目标2a评估了 心脏表达数量性状基因座（eQTL）附近的罕见非编码变异对 冠心病在一个平行的方法中，Aim 2b将利用430个人类心脏发育功能基因组， 注释，包括从人诱导多能干细胞在整个分化过程中确定的那些注释 转化为心肌细胞。人类心脏表观遗传景观可能更成功地定义遗传 因此，本发明的目的在于揭示典型人类CHD的显性CHD的机制，因为小鼠CHD通常是隐性表型。 可用的注释包括组蛋白甲基化和乙酰化状态，以及染色质可及性 （ATACseq）、染色体构象（Hi-C）和RNA表达。将在CHD eQTL上训练神经网络 变体以鉴定能够将eQTL与非eQTL基因座分开的注释子集。优先 将使用功能注释来计算整个基因组的每个碱基的调控得分（EpiCard），以及 将查询CHD队列中的负担评分阈值。最后，目标3涉及共同的作用 CHD风险和表型变异的遗传变异。利用三人结构的力量，共同 将鉴定过度传播给CHD先证者的变体。然后将评估过度传播的基因座， 在第二个CHD队列的病例对照研究中，优先化的功能建模 基因、变异和基因座是必不可少的;坚定的合作者已经在进行初步研究。 这项提案将采用创新的计算方法来优先考虑变异和基因座 与CHD有关。这些结果将有助于实现了解 心脏发育和人类遗传疾病的基本分子基础，以改善诊断，更好地 定义不良结局和复发的风险，并激发CHD患者的新治疗方法。

PROJECT SUMMARY: Congenital heart disease (CHD) is the most common anomaly at birth, affecting 1% of infants. Damaging genic variants contribute significantly to CHD risk but a likely genetic cause is identified in only 50% of patients. The genetic basis for the remaining half of CHD is unknown. The Gabriella Miller Kids First (GMKF) and TOPMed programs funded whole genome sequencing (WGS) to tests our hypothesis that variants undetected by whole exome sequencing (WES) contribute to CHD. WGS from 1813 CHD trios (affected probands and parents) provides a unique opportunity to define additional coding and noncoding variants that convey CHD risk. First, coding variants in CHD sequencing data will be comprehensively analyzed. WGS allows for improved detection of damaging coding variants that are not detected by WES, including structural variants and variants outside WES capture regions. Therefore, in Aim 1, damaging structural, mosaic and single nucleotide variants will be identified in WGS data. Novel CHD genes with a burden of damaging coding variants in CHD compared to non-CHD cohorts will be identified. Second, integration of CHD cardiac tissue gene expression with WGS data will to prioritize noncoding variants likely to impact developmental gene regulation. Aim 2a assesses the potential contribution of rare noncoding variants adjacent to cardiac expression quantitative trait loci (eQTLs) to CHD. In a parallel approach, Aim 2b will leverage 430 human cardiac developmental functional genomic annotations including those ascertained from human induced pluripotent stem cells throughout differentiation into cardiomyocytes. Human cardiac epigenetic landscape may be more successful in defining genetic mechanisms of the dominant CHD that typifies human CHD, as mouse CHD is typically a recessive phenotype. Available annotations include histone methylation and acetylation states, as well as chromatin accessibility (ATACseq), chromosome conformation (Hi-C), and RNA expression. A neural net will be trained on CHD eQTL variants to identify a subset of annotations that are able to separate eQTL from non-eQTL loci. Prioritized functional annotations will be used to calculate a per-base regulatory score across the genome (EpiCard), and score thresholds will be queried for a burden in the CHD cohort. Finally, Aim 3 addresses the role of common genetic variants in CHD risk and phenotypic variance. Leveraging the power of the trio structure, common variants over-transmitted to CHD probands will be identified. Over-transmitted loci will then be assessed for association with CHD in a case-control study in a second CHD cohort. Functional modeling of prioritized genes, variants and loci is essential; committed collaborators are already engaged in preliminary studies. Together this proposal will employ innovative computational approaches to prioritize variants and loci associated with CHD. These results will contribute towards the long-term objective of understanding the fundamental molecular basis of heart development and human genetic disease to improve diagnosis, better define risks for adverse outcomes and recurrence, and inspire novel treatments for CHD patients.