(Epi)Genomics Core

(Epi)基因组学核心

• 批准号: 10827533
• 负责人: Marcelo A. Nobrega
• 金额: $ 86.94万
• 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/10827533
• 关键词: Epi; Genomics; Core

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.

概括 虽然GWAS已经确定了至少150个基因座的遗传变异，与哮喘和 过敏性疾病（AAD），将这些发现转化为对哮喘病因的更好理解 滞后。这部分是由于以下事实，即大多数AAD相关的变体都在非编码中 序列，通常与基因距离很远。基本共识是许多这些变体 通过破坏监管因素的调节特性，例如 增强剂和促进者。从GWAS中有效提取假设生成信息的挑战 基因座包括i）识别每个GWAS基因座中的因果变体，ii）确定调节的类型 这些变体被映射的元素，iii）推断这些调节元件的组织特异性，iv） 定义这些调节元素的靶基因，v）证明了这些元素的表型效应 变体。该中心建议旨在开发一个计算和实验框架来解决所有这些 出色的挑战。在项目1中，将开发创新的统计和计算框架 链接AAD相关局部的功能注释，以识别候选变异，调节序列和 介导遗传关联的基因。这些注释将是从获得的细胞中产生的 项目2，迭代也将能够测试在体外和IN中从项目1做出的一些预测 体内模型。功能注释的产生有必要使用几个最先进的 基因组学策略。 （EPI）基因组核心（EGC）的目标是作为基因组数据生成 该中心的集线器。我们建议t在多个与哮喘相关的初级中携带500多个全基因组测定 在项目2中获得的细胞类型。在AIM 1中，我们将生成转录和染色质可访问性图 这些细胞在基线和刺激条件下。我们将使用一套完整的套件 染色质可及性评估，包括ATAC-SEQ，KAS-SEW和整个基因组Bisulfite测序 除RNA-Seq外，还可以在每个细胞系中生成动态转录图，以响应特定的刺激。在 AIM 2我们将利用染色质构象捕获将其目标基因“线”调节元件“线”。最后， 我们将测试项目1中数千个候选变体的调节潜力 平行记者测定。多种细胞类型中的综合功能注释的组合以及 各国代表了雄心勃勃的偏见，从传统的努力链接变体以在单个基因座中起作用到一个 系统的方法一次询问整个基因组。我们预计我们的研究策略将 产生大量的特定假设，这些假设将以与我们提出的类似方式进行 项目2。因此，EGC将作为连接两个单独项目的实验节点。