High-throughput screening and stem cell modeling of causal eQTL variants

描述(由申请人提供)：人类心血管疾病(CVD)新的有效治疗方法的发现需要识别和验证新的疾病机制。近年来，基因组变异的研究进入了一个新的阶段，无偏全基因组关联研究可以识别与常见疾病相关的新的遗传位点。我们最近描述了95个与血脂水平相关的基因座--低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)或甘油三酯(TG)，它们与心血管疾病的风险密切相关。要将新的关联转化为功能洞察力，并最终转化为降低心血管疾病风险的疗法，还需要做大量的工作。关键的一步是确定这些遗传位点如何影响与脂肪代谢相关的人类组织类型的表型，主要是肝脏和脂肪。我们对来自患者的外科肝脏和脂肪组织样本中的基因型和基因表达进行了表达数量性状基因座(EQTL)分析；从这项工作中，我们发现许多脂质相关标签单核苷酸多态(SNPs)与邻近基因的肝脏或脂肪表达密切相关。这些观察表明，连锁不平衡(LD)中的因果SNPs与标签SNPs直接影响导致人类血脂水平变化的因果基因的表达。识别这些因果SNPs和因果基因将有助于深入了解DNA变异导致肝脏和脂肪表型变化并最终影响疾病风险的分子机制。我们的总体策略是结合几种创新来识别随意的SNP。我们将：(1)使用新型大规模平行报告分析(MPRA)高通量筛选eQTL基因座候选SNP以改变报告基因在适当组织类型中的表达，以确定SNPs的优先顺序进行进一步研究；(2)使用人类基因组编辑和尖端TAL效应核酸酶(TALEN)技术来改变人类多能干细胞(HPSCs)中的每个高优先级SNP，以产生仅在SNP上存在差异的等基因细胞系；(3)将等基因hPSCs区分为适当的组织类型；以及(4)测量附近的基因表达以确认该SNP确实是eQTL的原因。我们建议对人体肝脏和脂肪中57个与eQTL相关的脂类基因座实施这一总体策略。该项目的成功完成不仅将为脂类代谢生物学提供新的见解，还将建立一种新的方法学范式，研究人员可以通过它来确定在下一代人类遗传研究中发现的哪些DNA序列变异是复杂表型的遗传基础。

DESCRIPTION (provided by applicant): The discovery of new and effective treatments for human cardiovascular disease (CVD) requires the identification and validation of novel disease mechanisms. Recently, studies of genomic variation entered a new phase, in which unbiased genome-wide association studies (GWAS) can identify novel genetic loci associated with common diseases. We have recently described 95 loci associated with blood lipid levels LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), or triglycerides (TG), which are strongly associated with risk for CVD. Much work will be needed to convert the novel associations into functional insights and, ultimately, therapies to reduce the risk of CVD. A key step is to determine how these genetic loci affect phenotypes in human tissue types relevant to lipid metabolism, principally liver and adipose. We have performed expression quantitative trait locus (eQTL) analyses of genotype vs. gene expression in surgical liver and adipose tissue samples from patients; from this work, we found strong associations between a number of lipid-associated tag single nucleotide polymorphisms (SNPs) and either hepatic or adipose expression of nearby genes. These observations suggest that causal SNPs in linkage disequilibrium (LD) with the tag SNPs directly influence the expression of causal genes that are responsible for changes in blood lipid levels in humans. Identifying these causal SNPs and causal genes would lead to insights into the molecular mechanisms by which the DNA variants drive phenotypic changes in liver and adipose and, ultimately, affect the risk of disease. Our general strategy is to combine several innovations to identify casual SNPs. We will: (1) perform high- throughput screening of candidate SNPs in eQTL loci for alteration of reporter gene expression in the appropriate tissue type, using a novel massively parallel reporter assay (MPRA), to prioritize SNPs for further study; (2) use human genome editing with cutting-edge TAL effector nuclease (TALEN) technology to alter each high-priority SNP in human pluripotent stem cells (hPSCs), so as to generate isogenic cell lines that differ only at the SNP; (3) differentiate the isogenic hPSCs into the appropriate tissue type; and (4) measure nearby gene expression to confirm that the SNP is truly causal for the eQTL. We propose to implement this general strategy for 57 lipid-associated loci with eQTLs in human liver and adipose. Success in completing this project will not only provide fresh new insights into the biology of lipid metabolism, but will also establish a new methodological paradigm by which investigators can determine which DNA sequence variants identified in next-generation human genetic studies underlie the genetic basis of complex phenotypes.