Comprehensive characterization of variants underlying heart and blood diseases with CRISPR base editing

通过 CRISPR 碱基编辑全面表征心脏和血液疾病的变异

• 批准号: 10296877
• 负责人: Daniel Evan Bauer
• 金额: $ 103.31万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10296877
• 关键词: Address; Biological; Biological Assay; Blood; Blood Cells; Blood Platelets; Blood Pressure; CRISPR interference; CRISPR screen; CRISPR/Cas technology; Cardiovascular Diseases; Cardiovascular system; Catalogs; Cell Line; Cell physiology; Cells; Cellular Assay; Chromatin; Clustered Regularly Interspaced Short Palindromic Repeats; Communities; Computing Methodologies; Coronary Arteriosclerosis; Data; Data Collection; Data Set; Development; Disease; Disease susceptibility; Dissection; Dyslipidemias; Elements; Epigenetic Process; Equilibrium; Erythrocytes; Ethnic Origin; Etiology; Fetal Hemoglobin; Frequencies; Gene Expression; Gene Frequency; Genes; Genetic; Genetic Variation; Genome; Genotype; Goals; Gold; Heart Diseases; Hematological Disease; Hematology; Hemoglobin concentration result; High Density Lipoprotein Cholesterol; Human; Human Genetics; Hypertension; Individual; LDL Cholesterol Lipoproteins; Leukocytes; Link; Machine Learning; Measures; Methods; Modeling; Molecular; Patients; Phenotype; Positioning Attribute; Probability; Regulatory Element; Reporting; Research; Risk; Risk Factors; Scheme; Serum; Technology; Testing; Validation; Variant; Writing; base; blood lipid; causal variant; computational pipelines; data sharing; design; disorder risk; follow-up; functional genomics; genetic association; genetic variant; genome editing; genome wide association study; genomic variation; high throughput screening; human disease; multi-ethnic; multimodality; neutrophil; next generation; novel therapeutic intervention; open source; precise genome editing; predictive modeling; programs; screening; sex; single-cell RNA sequencing; trait; working group

Project Summary How genomic variation influences cellular function is a fundamental problem with tremendous importance for human disease. While it has traditionally been difficult to study the effects of specific sequence variants in an experimentally controlled manner, precise genome editing technologies such as CRISPR base editing enable “writing” of trait-associated variants to cells to unravel their function. In this proposal, we will perform multi-modal genome editing-based functional characterization of a total of 72,000 genomic variants associated with cardiovascular diseases (CVDs) and hematological traits. CVD and blood traits are uniquely suited to functional dissection because cardiovascular (coronary artery disease, high blood pressure, dyslipidemia) and blood traits have among the best-powered multi-ethnic GWAS of any traits, and a substantial component of trait variability can be captured in cellular assays that can be scaled to perform high-throughput screening. We have assembled an interdisciplinary team of world-class experts to provide a generalizable pipeline to unravel the functional impact of CVD and blood trait variants by integrating: (1) rich and ancestry-diverse human genetic discoveries, (2) broadly targetable CRISPR base editors and efficient delivery to primary human cells, (3) high-content assays to profile phenotypes at the levels of chromatin, gene expression and cellular function, and (4) computational methods to design, interpret, visualize, and share experimental results. In Aim 1, we will employ a robust, three-tiered variant prioritization scheme that incorporates evidence for disease association from large, multi-ethnic GWAS as well as probability of causality to nominate variants for functional assessment. Through this scheme, we will select variants associated with red blood cell and neutrophil traits, coronary artery disease, blood pressure, and HDL and LDL cholesterol that span a range of allelic frequencies and likely causality to test in high-throughput cellular assays. In Aim 2, we will perform systematic cellular phenotype-based screens using base editors to install candidate variants as well as CRISPR epigenetic inhibition and activation to explore variant-containing regulatory elements. We will use eight established, scalable cellular phenotypic readouts, each of which will enable us to assess which of 12,000 variants and variant-centered elements alter CVD and blood trait-associated cellular phenotypes. We will additionally employ a high-throughput, genome-integrated chromatin accessibility assay to assess which variants alter chromatin accessibility in trait-relevant cell lines. We will follow up with targeted single cell RNA-seq of 5,600 variants in primary cells from donors of different sex and ethnicity. In Aim 3, we will produce a catalog of validated variants and their association with phenotypes for each of the proposed screens. We will collaborate with other IGVF groups to utilize these data to optimize models that predict functional variants, regulatory elements and disease-causing biological mechanisms, ultimately leading to more complete understanding of the genetic underpinnings of cardiovascular and blood disease risk.

项目摘要 基因组变异如何影响细胞功能是一个基本问题，对 人类疾病。传统上很难研究特定序列变体在 实验控制的方式，精确的基因组编辑技术，例如CRISPR基础编辑启用 特征相关的变体“写入”细胞揭示其功能。在此提案中，我们将执行多模式 基于基因组编辑的功能表征，共72,000种基因组变体 心血管疾病（CVD）和血液学特征。 CVD和血液特征独特地适合功能 解剖是因为心血管（冠状动脉疾病，高血压，血脂异常）和血液特征 具有任何特征的最佳多种族GWA，并且是特质可变性的重要组成部分 可以在细胞测定中捕获，可以缩放以进行高通量筛选。 我们已经组建了一个跨学科的世界一流专家团队，以提供可推广的管道 通过整合：（1）富裕和祖先多样性人类的CVD和血液特质变体的功能影响 遗传发现，（2）广泛目标的CRISPR基础编辑和有效传递到原代人类细胞， （3）在染色质，基因表达和细胞功能的水平上对表型的高含量Assas， （4）设计，解释，可视化和共享实验结果的计算方法。 在AIM 1中，我们将采用强大的三层变体优先级方案，该方案纳入了疾病的证据 从大型，多种族的GWA以及偶然性的概率的关联到提名功能的变体 评估。通过该方案，我们将选择与红细胞和中性粒细胞性状相关的变体， 冠状动脉疾病，血压以及HDL和LDL胆固醇，这些胆固醇跨越一系列等位基因频率 并可能在高通量细胞测定中进行测试。 在AIM 2中，我们将使用基本编辑器执行系统的基于蜂窝表型的屏幕来安装候选者 变体以及CRISPR表观遗传学抑制和激活，以探索具有变体的调节元件。 我们将使用八个已建立的，可扩展的蜂窝表型读数，每个读数将使我们能够评估 在12,000个变体和以变体为中心的元素中，哪个改变了CVD和血液特质相关的细胞 表型。我们还将采用高通量，基因组集成的染色质可及性测定法 评估哪些变体改变了与特征相关的细胞系中的染色质可及性。我们将跟进有针对性的单曲 来自不同性别和种族的供体的原代细胞中5,600种变体的细胞RNA-seq。 在AIM 3中，我们将生成经过验证的变体目录及其与每个表型的关联 建议的屏幕。我们将与其他IGVF组合作利用这些数据来优化预测的模型 功能变异，调节元件和引起疾病的生物学机制，最终导致更多 完全了解心血管和血液疾病风险的遗传基础。