Using Common Fund datasets for prioritization of disease-associated genetic variants

使用共同基金数据集对与疾病相关的遗传变异进行优先排序

• 批准号: 10585864
• 负责人: Ferhat Ay
• 金额: $ 36.6万
• 依托单位: LA JOLLA INSTITUTE FOR IMMUNOLOGY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-20 至 2024-09-19
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10585864
• 关键词: 3-Dimensional; Alleles; Area; Atopic Dermatitis; Beta Cell; Binding; Binding Sites; Biological Process; Catalogs; Cell Line; Cell Nucleus; Cells; Chromatin; Chromatin Loop; Collection; Data; Data Set; Databases; Development; Disease; Distal; Encyclopedia of DNA Elements; Enhancers; Follow-Up Studies; Funding; Gene Expression; Gene Targeting; Genes; Genetic; Genetic Transcription; Genome; Genotype; Goals; Heritability; Hi-C; Human Genetics; Immune; Individual; Inflammatory; Insulin-Dependent Diabetes Mellitus; Investigation; Link; Linkage Disequilibrium; Maps; Methods; Motivation; Nature; Nucleic Acid Regulatory Sequences; Process; Psoriasis; Publishing; Quantitative Trait Loci; Regulatory Element; Research; Research Personnel; Resolution; Rheumatoid Arthritis; Role; Scleroderma; Signal Transduction; Single Nucleotide Polymorphism Map; Specificity; Structure; Surface; Testing; Tissues; United States National Institutes of Health; Untranslated RNA; Variant; Work; base; causal variant; cell type; epigenomics; genetic analysis; genetic variant; genome annotation; genome wide association study; interest; keratinocyte; novel; online resource; programs; promoter; skin disorder; statistics; transcription factor; web server

Abstract Genome-wide association studies (GWAS) have highlighted that disease-associated human genetic variants are prevalent in noncoding regions and for most of them the biological function or gene target remain uncharacterized. To better annotate such disease variants, NIH-funded consortia created comprehensive maps of putative regulatory elements and identified SNPs associated with gene expression (eQTLs) for different tissues and primary cell types. In parallel, breakthroughs in capturing the 3D genome structure have demonstrated the importance of cell-type-specific physical proximity between genes and their regulatory elements. This 3D view provided a new way through which disease-associations of certain variants can be explained. There is an increasing interest in utilization of chromatin loops for GWAS variant annotation, however, to the best of our knowledge, there is no comprehensive study incorporating eQTL data and high-resolution chromatin looping information across many different matched/related cell types and tissues to interpret GWAS variants identified for a large set of diseases. To goal of this proposal is to utilize NIH Common Fund datasets (GTEx and 4D Nucleome) as well as other published chromatin loop and eQTL data to carry out different integrative approaches for better annotation of disease-associated genetic variants. This will lead to the development of a framework and best practices for integrative analysis of loops, eQTLs and GWAS signals. The developed framework will be tested on a large number of diseases and disease-relevant cell types to create a substantial online resource for researchers. For a subset of the studied diseases, for which we have ongoing research interests, we will further analyze the identified novel genes, genetic variants and overlapping regulatory elements to determine potential targets that warrant further investigation.

抽象的 全基因组关联研究（GWAS）强调，与疾病相关的人类遗传变异是 在非编码区域中，并且在其中大多数地区都存在生物学功能或基因靶标的 未表征。为了更好地注释这种疾病变种，NIH资助的财团创建了全面的地图 推定的调节元件和与基因表达（EQTL）相关的SNP的不同 组织和主要细胞类型。同时，捕获3D基因组结构的突破具有 证明了基因及其调节性的细胞类型特异性物理接近的重要性 元素。这种3D视图提供了一种新的方式，通过某些变体的疾病缔约 解释了。然而，人们对使用染色质环的利用越来越兴趣 据我们所知，没有综合eqtl数据和高分辨率的全面研究 在许多不同匹配/相关的细胞类型和组织中介绍染色质循环信息以解释GWAS 为大量疾病确定的变体。该建议的目标是利用NIH普通基金数据集 （GTEX和4D核心）以及其他已发表的染色质环和EQTL数据，以执行不同的 综合方法，以更好地注释疾病相关的遗传变异。这将导致 开发框架和最佳实践，用于整合循环，EQTL和GWAS信号。这 开发的框架将在大量疾病和与疾病相关的细胞类型上进行测试，以创建 研究人员的大量在线资源。对于研究的疾病的一部分，我们正在持续 研究兴趣，我们将进一步分析已确定的新基因，遗传变异和重叠的调节 确定需要进一步研究的潜在目标的要素。