Functional Mechanisms of T1D Risk Variants and their Target Genes using 3D Epigenomics and Single Cell Approaches

使用 3D 表观基因组学和单细胞方法研究 T1D 风险变异及其靶基因的功能机制

• 批准号: 10398021
• 负责人: Struan F A Grant
• 金额: $ 97.74万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10398021
• 关键词: 3-Dimensional; ATAC-seq; Alleles; Antibodies; Architecture; Autoimmune Diseases; B-Lymphocytes; Bar Codes; Bioinformatics; CD19 gene; CD8-Positive T-Lymphocytes; CRISPR/Cas technology; Cell Lineage; Cells; Cellular Indexing of Transcriptomes and Epitopes by Sequencing; Chromatin; Coupled; DNA; Dependence; Disease susceptibility; Enhancers; Epitopes; Gene Expression; Gene Expression Regulation; Gene Targeting; Genes; Genetic; Genetic Risk; Genetic Transcription; Genetic Variation; Genome; Genotype; Genotype-Tissue Expression Project; Helper-Inducer T-Lymphocyte; Human; Human Genome; Immune; Immunophenotyping; Individual; Inflammatory; Insulin; Insulin-Dependent Diabetes Mellitus; Life; Link; Maps; Mediating; Memory; Meta-Analysis; Morbidity - disease rate; Natural Killer Cells; Nature; Nucleic Acid Regulatory Sequences; Peripheral Blood Mononuclear Cell; Phenotype; Population; Predisposition; Regulator Genes; Regulatory T-Lymphocyte; Research; Resolution; Rest; Role; Sampling; Single Nucleotide Polymorphism; Site; Specificity; Surface; Susceptibility Gene; Symptoms; T cell differentiation; T-Lymphocyte; Testing; Therapeutic Intervention; Tissues; Tonsil; Validation; Variant; base; biobank; cell type; diabetes mellitus genetics; diabetes risk; epigenomics; gene function; gene interaction; genome editing; genome wide association study; genome-wide; immunoregulation; indexing; innovation; molecular targeted therapies; monocyte; mortality; novel; prevent; promoter; risk variant; single-cell RNA sequencing; transcriptome; transcriptome sequencing; whole genome

ABSTRACT Type 1 diabetes (T1D) is an autoimmune disease, whose symptoms and complications result in increased morbidity, mortality, and life-long dependence on insulin. The Type 1 Diabetes Genetics Consortium (T1DGC, Stephen Rich, PI) conducted the largest T1D GWAS meta-analysis and identified over 40 T1D risk loci. The T1DGC refined the T1D risk variants by fine mapping with the ImmunoChip and constructing sets of 99% credible single nucleotide polymorphisms (SNPs) within each locus. Bioinformatic analyses of T1D-associated credible SNPs discovered enrichment in regions involved in gene regulation of immune-relevant cell types (CD4 and CD8 T cells, CD19 B cells). Despite these discoveries on the genetic basis of T1D, the mechanisms that define how T1D-associated SNPs contribute to disease susceptibility remain unclear. Here, we propose a powerful and innovative approach to define function of the T1D-associated SNPs and identify their target, causal effector genes through integrated analyses of T1D-relevant tissues. We will (Aim 1) generate an integrated 3D map of the gene regulatory architecture of T1D susceptibility by conducting ATAC-seq, RNA-seq and whole- genome promoter-focused Capture-C analysis on purified human cell populations; (Aim 2) perform single-cell immunophenotyping and eQTL analysis of T1DGC samples using CITE-seq, a single-cell RNA-seq approach guided by DNA-barcoded antibodies against lineage markers to characterize the immune cell subsets identified in Aim 1, allowing us to focus on SNPs that are regulatory and likely contribute to T1D risk; and (Aim 3) conduct functional validation of T1D SNP-gene regulatory effects using CRISPR/Cas9 genome editing in human immune cells to directly test whether these SNPs reside in regions that are required for T1D gene expression using Cas9-mediated editing. Our outstanding research team provides complementary and synergistic approaches to understanding the function and gene targets that modulate genetic risk of T1D. Together, we will establish the mechanisms underlying contribution of T1D-associated SNPs to inflammatory gene regulation and, by revealing the SNP-enhancer-gene link in 3D, are poised to discover novel molecular targets for therapeutic intervention to treat or prevent T1D.

摘要 1型糖尿病（T1 D）是一种自身免疫性疾病，其症状和并发症导致糖尿病患者的血糖升高。 发病率、死亡率和对胰岛素的终身依赖。1型糖尿病遗传学联盟（T1 DGC， Stephen Rich，PI）进行了最大的T1 D GWAS荟萃分析，并确定了40多个T1 D风险位点。的 T1 DGC通过使用免疫芯片进行精细定位并构建99%可信的T1 D风险变异集， 每个基因座内的单核苷酸多态性（SNP）。T1 D相关可信的生物信息学分析 在参与免疫相关细胞类型（CD 4和CD 8）基因调控的区域发现了SNP富集 T细胞、CD 19 B细胞）。尽管这些发现的遗传基础上的T1 D，机制，定义 T1 D相关SNPs如何影响疾病易感性仍不清楚。在这里，我们提出一个 一种强有力的创新方法来定义T1 D相关SNP的功能，并确定其靶点，因果关系， 效应基因通过T1 D相关组织的综合分析。我们将（目标1）生成集成的3D 通过进行ATAC-seq、RNA-seq和全基因测序， 对纯化的人细胞群进行基因组启动子聚焦的Capture-C分析;（目的2）进行单细胞 使用CITE-seq（单细胞RNA-seq）对T1 DGC样品进行免疫表型分析和eQTL分析 由针对谱系标志物的DNA条形码抗体指导的表征免疫细胞亚群的方法 目标1中确定的SNP，使我们能够专注于监管和可能导致T1 D风险的SNP;以及（目标 3)使用CRISPR/Cas9基因组编辑进行T1 D SNP基因调控效应的功能验证 在人类免疫细胞中直接测试这些SNP是否位于T1 D基因所需的区域， 使用Cas9介导的编辑表达。我们优秀的研究团队提供互补和 协同方法来理解调节T1 D遗传风险的功能和基因靶点。 总之，我们将建立T1 D相关SNP对炎症反应的潜在作用机制。 基因调控，并通过在3D中揭示SNP-增强子-基因连接，有望发现新的分子 用于治疗或预防T1 D的治疗性干预的靶点。