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(T1D)是一种自身免疫性疾病，其症状和并发症导致 发病率、死亡率和对胰岛素的终生依赖。1型糖尿病遗传联盟(T1DGC， Stephen Rich，Pi)进行了最大规模的T1D GWASMeta分析，确定了40多个T1D风险基因。这个 T1DGC通过与免疫芯片进行精细定位并构建99%可信的集合来提炼T1D风险变量 每个基因座的单核苷酸多态(SNPs)。T1D相关可信基因的生物信息学分析 SNPs在免疫相关细胞类型(CD4和CD8)的基因调控区域发现了丰富 T细胞、CD19 B细胞)。尽管有这些关于T1D基因基础的发现，但定义T1D的机制 与T1D相关的SNPs如何影响疾病易感性尚不清楚。在这里，我们提出一种 强大而创新的方法来定义与T1D相关的SNP的功能并确定它们的目标、原因 通过整合分析T1D相关组织的效应基因。我们将(目标1)生成一个集成的3D 用ATAC-seq、RNA-seq和全长序列构建T1D易感性基因调控结构图 基因组启动子聚焦的纯化人类细胞群体的Capture-C分析(目标2)进行单细胞 单细胞RNA-SEQ CITE-SEQ用于T1DGC的免疫表型和eQTL分析 以DNA条形码抗体为导向的免疫细胞亚群鉴定方法 在目标1中确定，使我们能够专注于受监管并可能导致T1D风险的SNPs；以及(Aim 3)使用CRISPR/Cas9基因组编辑进行T1D SNP基因调控效应的功能验证 以直接测试这些SNPs是否位于T1D基因所需的区域 使用Cas9介导的编辑进行表达。我们优秀的研究团队提供了互补和 了解调节T1D遗传风险的功能和基因靶点的协同方法。 我们将共同建立与T1D相关的SNPs在炎症中的潜在作用机制 基因调控，并通过在3D中揭示SNP-增强子-基因链接，有望发现新的分子 治疗或预防T1D的治疗干预的靶点。