Integration of functional data and GWAS to elucidate genetic basis of diseases

 描述(申请人提供)：现代人类遗传学的中心问题之一是理解遗传变异对功能的影响。在人类千百万个不同的DNA位置中，哪些位置实际上影响了人类的表型和疾病？越来越清楚的是，影响基因调控的非编码变异在疾病的遗传学中发挥着核心作用，但这些变异仍然很难解释。在这个项目中，我们将使用类风湿性关节炎作为解决这些问题的模型系统，使用计算和实验技术的组合。在计算方面，我们将开发统计方法，将来自全基因组分析的功能信息与来自复杂特征的GWAS研究的数据相结合。我们的工作将使我们能够推断哪些细胞类型对任何给定的疾病最重要，提高绘图能力，并提高我们识别最可能的因果变异的能力。我们还提出了新的验证方法，基于测量分类免疫细胞的细胞表型和执行特定位置的基因组编辑。我们期待着我们的工作将导致新的RA基因座的检测和验证，以及在这一领域具有普遍实用价值的新技术。

 DESCRIPTION (provided by applicant): One of the central problems in modern human genetics is to understand the functional impact of genetic variation. Of the millions of DNA positions that vary among humans, which sites actually impact human phenotypes and disease? It is becoming increasingly clear that noncoding variants that impact gene regulation play central roles in the genetics of disease, yet these variants remain difficult to interpret. Inthis project we will use rheumatoid arthritis as a model system for tackling these problems, using a combination of computational and experimental techniques. On the computational side, we will develop statistical approaches for integrating functional information from genome-wide assays with data from GWAS studies for complex traits. Our work will allow us to infer which cell-types are most important for any given disease, to improve mapping power, and to improve our ability to identify the most likely causal variants. We also propose novel approaches to validation, based on measuring cellular phenotypes in sorted immune cells and performing genome editing of specific sites. We anticipate that our work will lead to detection and validation of novel RA loci, as well as new techniques of general utility in this field.