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

项目总结： 先天性心脏病(CHD)是最常见的出生畸形，影响1%的婴儿。破坏性基因 变异对冠心病风险有很大影响，但只有50%的患者发现了可能的遗传原因。这个 其余一半冠心病的遗传基础尚不清楚。加布里埃拉·米勒儿童优先(GMKF)和TOPMed 资助全基因组测序(WGS)的程序来验证我们的假设，即变异没有被整体检测到 外显子组测序(WES)与CHD有关。1813年冠心病三人组(受影响的先证者和父母)的WGS 提供了一个独特的机会来定义传递CHD风险的其他编码和非编码变体。 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体，包括结构变体和变体 在WES捕获区之外。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数据中确定。CHD中存在编码变异损伤负担的新基因比较 到非冠心病队列的研究将被确定。第二，冠心病心脏组织基因表达与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体。Aim 2a评估 心脏表达数量性状基因座(EQTL)附近罕见的非编码变异对 先心病。在一种平行的方法中，Aim 2b将利用430个人类心脏发育功能基因组 包括从人诱导的多能干细胞分化过程中确定的那些注释 转化为心肌细胞。人类心脏表观遗传学图景可能更成功地定义基因 人类典型的显性CHD的机制，如小鼠CHD是典型的隐性表型。 可用的注释包括组蛋白甲基化和乙酰化状态，以及染色质的可及性 (ATACseq)、染色体构象(Hi-C)和RNA表达。将对CHD eQTL进行神经网络训练 用于识别能够区分eQTL和非eQTL基因座的注释子集的变体。确定优先顺序 功能注释将用于计算基因组(EpiCard)中每个碱基的调控分数，以及 对于CHD队列中的负担，将查询得分阈值。最后，目标3解决了共同的作用 冠心病风险的遗传变异和表型变异。利用三人组结构的力量，常见的 过度传递给先证者的变异将被识别。然后将对过度传输的基因座进行评估 在第二个冠心病队列中的病例对照研究中与冠心病的相关性。优先顺序的功能建模 基因、变种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。 总之，这项提案将采用创新的计算方法来确定变异和基因座的优先顺序 与冠心病相关。这些结果将有助于实现理解 心脏发育和人类遗传病的基本分子基础提高诊断，更好 明确不良后果和复发的风险，并启发冠心病患者的新治疗方法。

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.