Epigenome-Guided Causal Variant Discovery and Mechanisms

项目总结 系统性红斑狼疮(SLE)是一种以调节失调为特征的自身免疫性疾病 干扰素反应和对细胞抗原的自我耐受性丧失，导致炎症过程， 最终导致全身性终末器官损伤。尽管进行了数十年的研究，但潜在的机制 系统性红斑狼疮的发病机制尚不完全清楚。全基因组关联研究 已经确定了100多种SLE风险单倍型，携带数百个功能重要性未知的SNP 在疾病的发生和发展中。区分因果SNPs和非因果SNPs，从而翻译基因 将知识转化为可操作的临床知识一直是一项费力、低效和资源密集型的任务。 我们的实验室已经开发出一种新的方法来加速因果变异的发现过程，在我们使用的地方 表观基因组，用于识别风险单倍型上可能的因果变异。我们通过识别表观遗传学来做到这一点 用芯片检测稳定和活性增强子中SNPs的等位基因不平衡足迹 测序。我们的方法能够在连锁不平衡和 通过确定等位基因的不平衡，提供了推定的因果变量具有功能性的先验证据 组蛋白标记的大小。我们还利用3D染色质拓扑数据构建了分子接线图 包含hQTL的相互作用的增强子和启动子。因为这些数据利用了不同的表观基因组 特定细胞和细胞状态的配置文件提供了有关细胞进程的重要上下文信息 表观QTL是最重要的调控基因。重新提交R01 AR073606旨在1)使用 表观基因组引导的方法从原代B细胞中识别静息和刺激依赖的hQTL；2)验证 并使用正交表大规模地确认hQTL的等位基因特异性转录调控 平行报告分析；以及3)确定hQTL如何改变基因表达和3D染色质组织 利用多重定量聚合酶链式反应和染色质检测hQTL调控网络中包含的基因 构象捕获(3C)。我们相信这个项目使我们处于因果变量的前沿 识别和风险单倍型功能特征，将有助于更好地理解 人类系统性红斑狼疮与相关自身免疫性疾病的基因和表型的关系。

PROJECT SUMMARY Systemic lupus erythematosus (SLE) is a prototypic autoimmune disease characterized by dysregulated interferon responses and loss of self-tolerance to cellular antigens, which result in inflammatory processes that ultimately lead to systemic end-organ damage. Despite decades of research, the underlying mechanisms driving the pathogenesis of SLE remain incompletely understood. Genome-wide association studies (GWAS) have identified over 100 SLE risk haplotypes carrying hundreds of SNPs with unknown functional importance in disease onset and progression. Distinguishing causal from non-causal SNPs, and thus translating genetic knowledge into actionable clinical knowledge has been a laborious, inefficient, and resource-intensive task. Our laboratory has developed a new approach to expedite the causal variant discovery process where we use the epigenome to identify likely causal variants on risk haplotypes. We do this by identifying epigenetic footprints of allelic imbalance at SNPs (“hQTLs”) in poised and active enhancers measured by ChIP- sequencing. Our approach is able to identify causal variants in the context of linkage disequilibrium and provides a priori evidence that the putative causal variant is functional by identifying allelic imbalance in the magnitude of histone marks. We also use 3D chromatin topology data to construct a molecular wiring diagram of interacting enhancers and promoters that contain hQTLs. Since these data leverage the epigenome distinct profiles in specific cells and cell states provide important contextual information about what cellular processes the epiQTL is most important in regulating. This resubmission of R01 AR073606 aims to 1) use an epigenome-guided approach to identify resting and stimulus-dependent hQTLs from primary B cells; 2) validate and confirm the allele-specific transcriptional regulation attributed to hQTLs using an orthogonal massively parallel reporter assay; and 3) determine how hQTLs modify gene expression and 3D chromatin organization of genes contained within regulatory networks of hQTLs using multiplex quantitative PCR and chromatin conformation capture (3C). We believe this project positions us at the leading edge of causal variant identification and risk haplotype functional characterization and will contribute to a better understanding of the connection between genotype and phenotype for human SLE and related autoimmune diseases.