Systematic in vivo characterization of disease-associated regulatory variants

疾病相关调控变异的系统体内表征

• 批准号: 10472058
• 负责人: Michael Isaiah Love
• 金额: $ 184.86万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 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/10472058
• 关键词: Achievement; Affect; Algorithms; Alleles; Bar Codes; Biological Assay; Blood Circulation; Brain; Catalogs; Cells; Clinical Research; Code; Communities; Complex; Controlled Study; DNA; Data; Data Collection; Disease; Environment; Exhibits; Female; Frequencies; Future; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Variation; Genetic study; Genomic Segment; Genomics; Goals; Health; Heart; Heterogeneity; Human; Human Genetics; Individual; Inflammatory; Lead; Libraries; Link; Liver; Lung; Measurement; Mus; Muscle; Organ; Physiological; Physiology; Positioning Attribute; Process; Protocols documentation; RNA Sequences; Rare Diseases; Regulator Genes; Regulatory Element; Reporter; Reporting; Research Personnel; Signal Transduction; Testing; Tissues; Transcriptional Regulation; Untranslated RNA; Validation; Variant; Viral; Work; adeno-associated viral vector; base; cell type; disorder risk; experimental study; gene environment interaction; genetic variant; genome wide association study; genomic locus; genomic variation; human genomics; in vivo; male; member; network models; new therapeutic target; prediction algorithm; predictive modeling; public health relevance; risk variant; sex; trait; transcription factor

ABSTRACT Thousands of genetic loci are associated with human traits or disease risk, and these loci each typically contain tens to hundreds of variants, most of which are non-coding and lack direct evidence of effects on genes. Experimental tests of genomic variants are needed to identify functional effects, which can be specific to one sex, tissue, and/or perturbed environmental context. Testing effects of risk variants on gene regulation requires an ability to quantify the potentially modest consequences of thousands of alleles in a carefully controlled study. Our overarching goal is to systematically characterize the impact of human genetic variation on gene regulation via massively parallel reporter assays (MPRA). We will select variants based primarily on genome-wide association studies (GWAS) for common diseases and complex traits relevant to the brain, liver, lung, muscle, and/or heart. We will examine all plausible functional candidates at prioritized GWAS loci to provide data for tests of regulatory variant prediction algorithms, positive control variants, and variants prioritized based on regulatory element annotations. The gene regulatory effect of ~500,000 variant alleles will be interrogated in five organs (brain, liver, lung, muscle and heart) using systemic circulation of adeno-associated viral (AAV) MPRA libraries. We will repeat this experiment in a perturbed inflammatory state to evaluate gene-environment interactions. As a result, we will comprehensively characterize variant effects on regulatory function by analyses of variants in the physiological conditions of multiple tissues, in both sexes, with and without perturbation typical of disease environments. Selected variants will be edited into human pluripotent cells for validation. As members of the Impact of Genomic Variation on Function (IGVF) Consortium, we will generate a regulatory variant catalog for the community, and enable future studies through data collection and predictive models. Successful completion of these aims will provide ~10 million allelic effect data points that encompass tissue-, sex-, and perturbation- specific regulatory effects. We will work with the IGVF consortium to finalize selection of variants, organs, and perturbations to generate a comprehensive catalog. The expertise of the study investigators in GWAS, statistical and computational genetics, human genomics, AAV delivery, and mouse physiology make achievement of these aims feasible and likely highly informative to understand how genomic variation impacts human health and disease.

摘要 数以千计的遗传基因与人类的特征或疾病风险有关，这些基因座中的每一个通常都含有 数十到数百个变种，其中大多数是非编码的，缺乏对基因影响的直接证据。 需要对基因组变异进行实验测试，以确定功能效应，这可能是一种特有的效应 性别、组织和/或受干扰的环境背景。检测风险变异对基因调控的影响需要 在一项精心控制的研究中，能够量化数千个等位基因的潜在适度后果。 我们的首要目标是系统地描述人类基因变异对基因调控的影响。 通过大规模平行报告分析(MPRA)。我们将主要根据全基因组范围来选择变异 与脑、肝、肺、肌肉相关的常见疾病和复杂特征的关联研究(GWAS) 和/或心脏。我们将按优先顺序检查所有可能的功能候选，以便为测试提供数据 基于调控变量预测算法、阳性对照变量和基于调控变量的优先顺序的变量 元素注释。将在五个器官中询问~50万个变异等位基因的基因调控效应 (脑、肝、肺、肌肉和心脏)使用腺相关病毒(AAV)MPRA文库的体循环。 我们将在不安的炎症状态下重复这一实验，以评估基因与环境的相互作用。AS 因此，我们将通过对变异体的分析来全面描述对调节功能的变异体的影响 多种组织的生理状态，无论男女，都有或没有疾病的典型干扰 环境。选定的变种将被编辑成人类多能细胞进行验证。作为该委员会的成员 基因组变异对功能的影响(IGVF)联盟，我们将为 通过数据收集和预测模型，使今后的研究成为可能。成功完成 这些目标中将提供约1000万个等位基因效应数据点，包括组织、性别和扰动- 具体的监管效果。我们将与IGVF联盟合作，最终确定变异体、器官和 扰动，以生成一个全面的目录。这项研究的研究人员的专业知识在GWAS，统计 而计算遗传学、人类基因组学、AAV递送和老鼠生理学都取得了这些成就 旨在了解基因组变异如何影响人类健康和 疾病。