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

因果 eQTL 变异的高通量筛选和干细胞建模

• 批准号: 9242768
• 负责人: Kiran Musunuru
• 金额: $ 34.15万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9242768
• 关键词: 1p13; Adipocytes; Adipose tissue; Affect; Alleles; Binding Sites; Biological Assay; Biology; CCAAT-Enhancer-Binding Proteins; Cardiovascular Diseases; Cause of Death; Cell Line; Cell model; Cholesterol; Chromosomes; Complex; DNA; DNA Sequence; Disease; Family; Gene Expression; Genes; Genetic; Genetic Transcription; Genetic study; Genomics; Genotype; Health; Hepatic; Hepatocyte; High Density Lipoprotein Cholesterol; Histocompatibility Testing; Human; Human Genetics; Human Genome; LDL Cholesterol Lipoproteins; Lead; Linkage Disequilibrium; Lipids; Lipoproteins; Liver; Measures; Methodology; Minor; Molecular; Operative Surgical Procedures; Patients; Phase; Phenotype; Pluripotent Stem Cells; Quantitative Trait Loci; Reporter; Reporter Genes; Research Personnel; Risk; Single Nucleotide Polymorphism; Site; Stem cells; Technology; Tissue Sample; Triglycerides; Untranslated RNA; Validation; Variant; Work; base; blood lipid; cardiovascular disorder risk; disorder risk; effective therapy; gene function; genome editing; genome wide association study; genomic variation; high throughput screening; human tissue; innovation; insight; lipid metabolism; next generation; next generation sequencing; novel; novel therapeutics; nuclease; prevent; research study; success; transcription activator-like effector nucleases

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.

描述（由申请人提供）：发现新的和有效的治疗人类心血管疾病（CVD）的方法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，无偏倚的全基因组关联研究（GWAS）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）血脂水平相关的基因座，它们与心血管疾病的风险密切相关。将这些新的关联转化为功能见解，并最终开发出降低心血管疾病风险的治疗方法，还需要做很多工作。关键的一步是确定这些基因位点如何影响与脂质代谢相关的人类组织类型的表型，主要是肝脏和脂肪。我们对患者手术肝脏和脂肪组织样本的基因型与基因表达进行了表达数量性状位点（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性（SNPs）与肝脏或脂肪附近基因的表达有很强的相关性。这些观察结果表明，连锁不平衡（LD）中的致病snp与标签snp直接影响导致人类血脂水平变化的致病基因的表达。识别这些致病snp和致病基因将有助于深入了解DNA变异驱动肝脏和脂肪表型变化的分子机制，并最终影响疾病风险。我们的总体策略是结合几种创新来识别偶然的snp。我们将：(1)使用一种新型的大规模平行报告基因试验（MPRA），对eQTL位点的候选snp进行高通量筛选，以改变适当组织类型的报告基因表达，优先考虑snp以供进一步研究；(2)利用尖端的TAL效应核酸酶（TALEN）技术进行人类基因组编辑，改变人类多能干细胞（hPSCs）中的每个高优先SNP，从而产生仅在SNP上存在差异的等基因细胞系；(3)将等基因hPSCs分化为合适的组织类型；(4)测量附近基因表达，确认SNP确实是导致该eQTL的原因。我们建议对人类肝脏和脂肪中57个与脂质相关的eqtl位点实施这一通用策略。该项目的成功完成不仅将为脂质代谢生物学提供新的见解，而且还将建立一个新的方法范式，通过该范式，研究人员可以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。