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Stanford Center for Connecting DNA Variants to Function and Phenotype

斯坦福大学 DNA 变异与功能和表型关联中心

基本信息

批准号：
10633286
负责人：
JESSE M ENGREITZ
金额：
$ 188.25万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-03 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10633286
关键词：
ATAC-seq Adult Affect Biological Biological Assay Biological Models Biology CRISPR interference CRISPR screen CRISPR/Cas technology Calibration Cardiac Cardiac Myocytes Cardiovascular Diseases Cardiovascular system Catalogs Cell Differentiation process Cell physiology Cells Child Chromatin Clustered Regularly Interspaced Short Palindromic Repeats Collaborations Complex Computer Models Computer software DNA Data Data Set Development Disease Disease Pathway Disease model Elements Endothelial Cells Enhancers Evaluation Future Gene Expression Gene Expression Regulation Genes Genetic Genetic Transcription Genome Genome engineering Heart Diseases Human Human Genetics Human Genome Learning Logic Macrophage Maps Measures Methods Modeling Molecular Mus Mutagenesis National Human Genome Research Institute Nucleotides Phenotype Printing Protocols documentation RNA Regulatory Element Smooth Muscle Myocytes Surveys Technology Testing Tissues Universities Untranslated RNA Variant Work candidate identification cardiovascular disorder risk causal variant cell type data sharing design disorder risk experimental study functional genomics genetic element genetic variant genome wide association study genomic tools genomic variation human disease human pluripotent stem cell improved in vivo innovation innovative technologies insight new technology novel strategies predictive modeling prime editing promoter risk variant tool trait

项目摘要

PROJECT SUMMARY Genome-wide association studies have now discovered tens of thousands of noncoding variants associated with human diseases and traits. It has proven challenging to interpret these associations. A majority of causal variants lie in the noncoding genome and appear to affect DNA cis-regulatory elements, which control the logic of gene expression and could point us to new cell types, genes, and pathways for disease. However, we have lacked the tools needed to systematically characterize how these cis-regulatory variants and elements impact genome function and phenotype. Our team at Stanford University has now developed innovative single-cell, CRISPR mapping, and computational technologies that will enable identifying and functionally characterizing many thousands of elements and variants directly in the human genome. These tools include single-cell ATAC-seq to identify candidate elements in cells and tissues; sensitive CRISPR tiling methods to connect thousands of elements and variants to effects on gene expression and cellular phenotypes; and the ABC and BPNet models to predict how disease variants regulate gene expression. Together, these technologies suggest a new strategy to systematically connect DNA variants and elements to function and phenotype. Here we will apply these new technologies in collaboration with the NHGRI Impact of Genomic Variation on Function Consortium. We will use four cardiovascular cell types derived from human pluripotent stem cells as model systems. First, we will leverage single-cell maps of cardiac differentiation and development to select elements and risk variants for adult and children’s heart diseases likely to control cardiovascular cell function. Second, we will apply single-cell CRISPR tools to measure the effects of thousands of unbiased elements and variants on gene expression, and connect prioritized disease variants to target genes, cellular phenotypes, and tissue phenotypes. Third, we will leverage these experimental datasets to calibrate and refine computational models to build a variant-element-phenotype catalog across many human cell types and diseases. Fourth, we will enable future studies by sharing data, protocols, and software, and by conducting systematic evaluations of CRISPR technologies and computational models to connect variants to phenotypes. Together, these studies will advance our understanding of how DNA variants and elements impact genome function and demonstrate a novel strategy to leverage high-throughput genomic tools to understand biological mechanisms of human diseases.

项目摘要全基因组关联研究现在已经发现了数万种与基因组相关的非编码变异。人类疾病和特征。事实证明，解释这些关联具有挑战性。大多数因果变量位于非编码基因组中，似乎影响DNA顺式调节元件，这些元件控制基因的逻辑表达，并可能为我们指出新的细胞类型，基因和疾病途径。然而，我们缺乏系统地描述这些顺式调节变体和元件如何影响基因组所需的工具功能和表型。我们在斯坦福大学的团队现在已经开发出创新的单细胞，CRISPR映射和计算这些技术将能够识别和功能表征成千上万的元素和变体，直接在人类基因组中。这些工具包括单细胞ATAC-seq，用于识别细胞中的候选元件敏感的CRISPR平铺方法，将数千个元件和变体连接到对基因的影响表达和细胞表型;以及ABC和BPNet模型来预测疾病变体如何调节基因表达。总之，这些技术提出了一种系统地连接DNA变体的新策略和功能和表型的元素。在这里，我们将应用这些新技术与NHGRI基因组变异的影响，功能联盟。我们将使用来自人类多能干细胞的四种心血管细胞类型，模型系统首先，我们将利用心脏分化和发育的单细胞图谱来选择成人和儿童心脏病的风险因素和风险变量可能控制心血管细胞功能。其次，我们将应用单细胞CRISPR工具来测量数千个无偏元素的影响，基因表达的变异，并将优先考虑的疾病变异与靶基因、细胞表型和组织表型第三，我们将利用这些实验数据集来校准和改进计算。模型，以建立跨许多人类细胞类型和疾病的变异元件表型目录。四是将通过共享数据、协议和软件，并通过进行系统的评估， CRISPR技术和计算模型将变体与表型联系起来。这些研究将推进我们对DNA变异和元件如何影响基因组功能的理解，并展示了一种新的利用高通量基因组工具了解人类疾病的生物学机制的战略。