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: 9987848
• 负责人: Struan F A Grant
• 金额: $ 40.92万
• 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: 2019-09-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9987848
• 关键词: 3-Dimensional; ATAC-seq; Alleles; Antibodies; Architecture; Autoimmune Diseases; B-Lymphocytes; Bioinformatics; CD19 gene; CD8-Positive T-Lymphocytes; CRISPR/Cas technology; Cell Lineage; Cells; 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.

抽象的 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 型糖尿病遗传学联盟 (T1DGC, Stephen Rich（PI）进行了最大规模的 T1D GWAS 荟萃分析，并确定了 40 多个 T1D 风险位点。这 T1DGC 通过使用免疫芯片进行精细绘图并构建 99% 可信度的集合来完善 T1D 风险变异 每个位点内的单核苷酸多态性 (SNP)。 T1D 相关可信的生物信息学分析 SNP 发现参与免疫相关细胞类型（CD4 和 CD8）基因调控的区域富集 T 细胞、CD19 B 细胞）。尽管在 T1D 的遗传基础上有这些发现，但定义其的机制 T1D 相关 SNP 如何影响疾病易感性仍不清楚。在这里，我们提出一个 强大且创新的方法来定义 T1D 相关 SNP 的功能并确定其目标、因果关系 通过对 T1D 相关组织进行综合分析来确定效应基因。我们将（目标 1）生成集成的 3D 通过 ATAC-seq、RNA-seq 和 Whole-seq 绘制 T1D 易感性基因调控架构图 对纯化的人类细胞群进行以基因组启动子为中心的 Capture-C 分析； （目标2）执行单细胞 使用 CITE-seq（一种单细胞 RNA 测序）对 T1DGC 样本进行免疫表型分型和 eQTL 分析 由针对谱系标记的 DNA 条形码抗体引导来表征免疫细胞亚群的方法 目标 1 中确定的 SNP 使我们能够重点关注具有监管性且可能导致 T1D 风险的 SNP；和（目标 3) 使用 CRISPR/Cas9 基因组编辑对 T1D SNP 基因调控效应进行功能验证 在人体免疫细胞中直接测试这些 SNP 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互补和 了解调节 T1D 遗传风险的功能和基因靶标的协同方法。 我们将共同建立 T1D 相关 SNP 对炎症的潜在作用机制 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 的治疗干预目标。