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：
10295739
负责人：
JESSE M ENGREITZ
金额：
$ 94.16万
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/10295739
关键词：
ATAC-seq Adult Affect Biological Biological Assay Biological Models CRISPR interference CRISPR screen CRISPR/Cas technology 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 Maps Measures Methods Modeling Molecular Mus Mutagenesis National Human Genome Research Institute Nucleotides Phenotype Protocols documentation RNA Regulatory Element Smooth Muscle Myocytes Surveys Technology Testing Tissues Universities Untranslated RNA Variant Work cardiovascular disorder risk causal variant cell type data sharing design disorder risk experimental study functional genomics genetic element genetic variant genome wide association study genome-wide genomic tools genomic variation human disease human pluripotent stem cell improved in vivo innovation innovative technologies insight macrophage new technology novel strategies predictive modeling 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.

项目摘要现在，全基因组关联研究已经发现了数以万计的非编码变体人类疾病和特征。解释这些关联已被证明是挑战。大多数因果变体位于非编码基因组中，似乎影响DNA顺式调节元素，这些元素控制基因的逻辑表达并可能指出新的细胞类型，基因和疾病途径。但是，我们缺乏系统地表征这些顺式调节变体和元素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了创新的单细胞，CRISPR映射和计算可以识别和功能表征数千个元素和变体的技术直接在人类基因组中。这些工具包括单细胞ATAC-SEQ以识别细胞中的候选元素和组织；敏感的CRISPR平铺方法将数千个元素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，以预测疾病变体如何调节基因表达。这些技术共同提出了一种系统连接DNA变体的新策略以及功能和表型的元素。在这里，我们将与基因组变异对NHGRI的影响合作应用这些新技术功能财团。我们将使用从人类多能干细胞得出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开发的单细胞图来选择成人和儿童心脏病的元素和风险变异可能控制心血管细胞功能。其次，我们将应用单细胞CRISPR工具来衡量成千上万的公正元素和基因表达的变体，并将优先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校准和完善计算在许多人类细胞类型和疾病中构建变体元素 - 表型目录的模型。第四，我们将通过共享数据，协议和软件以及进行系统评估来实现未来的研究 CRISPR技术和计算模型将变体连接到表型。这些研究将在一起促进我们对DNA变体和元素如何影响基因组功能的理解并证明一种新颖利用高通量基因组工具来了解人类疾病的生物学机制的策略。