(Epi)Genomics Core

(Epi)基因组学核心

• 批准号: 10261989
• 负责人: Marcelo A. Nobrega
• 金额: $ 52.73万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-19 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10261989
• 关键词: ATAC-seq; Alleles; Allergic Disease; Asthma; Biological; Biological Assay; Biology; Candidate Disease Gene; Cell Line; Cells; Chromatin; Computing Methodologies; Consensus; DNA Methylation; Data; Development; Dissection; Distant; Enhancers; Etiology; Generations; Genes; Genetic; Genetic Transcription; Genome; Genomic Segment; Genomic approach; Genomics; Goals; Heritability; Hi-C; Human; Immunologics; In Vitro; Individual; Length; Link; Maps; Measures; Mediating; Modeling; Pathogenesis; Phenotype; Property; Publishing; RNA; Regulator Genes; Regulatory Element; Reporter; Research; Rest; Specificity; Statistical Methods; Stimulus; Testing; Tissues; Transcriptional Regulation; Translations; Untranslated RNA; Variant; Work; bisulfite sequencing; causal variant; cell type; chromosome conformation capture; combinatorial; computer framework; design; disorder risk; epigenomics; experimental study; genetic association; genetic variant; genome wide association study; genome-wide; genomic data; in vitro testing; in vivo; in vivo Model; innovation; new therapeutic target; novel; promoter; response; transcription factor; transcriptome sequencing; whole genome

SUMMARY While GWAS have identified hundreds of genetic variants in at least 150 loci associated with asthma and allergic diseases (AAD), the translation of those findings into a better understanding of asthma etiology have lagged significantly. This is due, in part, to the fact that most AAD-associated variants are in noncoding sequences, often at great distance from genes. The underlying consensus is that a number of these variants impart their effects in disease risk by disrupting the regulatory properties of regulatory elements, such as enhancers and promoters. The challenges to efficiently extract hypothesis-generating information from GWAS loci include i) identifying the causal variant(s) in each GWAS locus, ii) determining the type of regulatory element in which these variants are mapped, iii) inferring the tissue-specificity of these regulatory elements, iv) defining the target genes for these regulatory elements, and v) demonstrating a phenotypic effect of these variants. This Center proposal aims to develop a computational and experimental framework to tackle all these outstanding challenges. In Project 1, an innovative statistical and computational framework will be developed to link functional annotations in AAD-associated loci to identify candidate variants, regulatory sequences and genes that are mediating the genetic association. These annotations will be generated from cells obtained in Project 2, which iteratively will also be able to test some of the predictions made from Project 1 in in vitro and in vivo models. The generation of the functional annotations necessitate the use of several state-of-the-art genomics strategies. The goal of the (Epi)Genomics Core (EGC) is to serve as the genomics data generation hub for this Center. We propose t carry over 500 whole-genome assays in multiple asthma-relevant primary cell types obtained in Project 2. In Aim 1 we will generate transcription and chromatin accessibility maps for each of these cells under baseline and stimulated conditions. We will utilize a suite of complementary chromatin accessibility assays, including ATAC-seq, KAS-sew and whole genome bisulfite sequencing, in addition to RNA-seq to generate dynamic transcription maps in each cell line in response to specific stimuli. In Aim 2 we will “wire” regulatory elements to their target genes, utilizing chromatin conformation capture. Finally, we will test the regulatory potential of thousands of candidate variants identified in Project 1 in a massively parallel reporter assay. The combination of comprehensive functional annotations in multiple cell types and states represent an ambitious departure from the traditional efforts to link variants to function in single loci to a systematic approach that interrogates the whole genome at once. We anticipate that our research strategy will generate a large number of specific hypothesis that will be pursued in similar ways to what we propose in Project 2. As such, the EGC will serve as an experimental node connecting the 2 individual projects.

摘要 而GWAS已经在至少150个与哮喘和哮喘相关的基因座上发现了数百个基因变异 过敏性疾病(AAD)，将这些发现转化为对哮喘病因的更好理解 明显落后。这在一定程度上是因为大多数与AAD相关的变体都是非编码的 序列，通常距离基因很远。潜在的共识是，这些变体中的一些 通过扰乱监管要素的监管性质来传递它们在疾病风险方面的影响，例如 促进剂和促进剂。如何有效地从GWAS中提取假设生成信息面临的挑战 基因座包括：i)识别每个Gwas基因座中的因果变量(S)；ii)确定调控基因的类型 这些变异体被定位的元素，iii)推断这些调控元素的组织特异性，iv) 定义这些调控元件的目标基因，以及v)展示这些元件的表型效应 变种。该中心的提案旨在开发一个计算和实验框架来解决所有这些问题 突出的挑战。在项目1中，将制定一个创新的统计和计算框架 连接AAD相关基因座中的功能注释以确定候选变异体、调控序列和 调节基因关联的基因。这些批注将从中获取的像元生成 项目2，它还将能够反复地在体外和在 活体模型。函数注释的生成需要使用几种最先进的技术 基因组学策略。(Epi)基因组学核心(EGC)的目标是作为基因组学数据的生成 该中心的枢纽。我们建议在多个与哮喘相关的原发病例中进行500多项全基因组分析。 在项目2中获得的细胞类型。在目标1中，我们将生成转录和染色质可及性图 这些细胞中的每一个都处于基线和刺激条件下。我们将利用一套互补的 染色质可及性分析，包括ATAC-SEQ、KAS-SEW和全基因组亚硫酸盐测序 添加到RNA-seq以在每个细胞系中生成响应特定刺激的动态转录图谱。在……里面 目标2我们将利用染色质构象捕捉，将调控元件与其目标基因“连接”。最后， 我们将大规模测试项目1中确定的数千个候选变体的调控潜力 平行报告试验。多种单元格类型中的综合功能批注和 各州代表着与传统努力的雄心勃勃的背道而驰，这些努力将单基因座中起作用的变异与 一次询问整个基因组的系统化方法。我们预计我们的研究战略将 生成大量特定的假设，这些假设将以类似于我们在 因此，EGC将作为连接两个单独项目的实验节点。