Biophysical and functional characterization of immune-related regulatory elements and noncoding variants

项目摘要 对多种免疫疾病的易感性与影响免疫系统的遗传差异有关。 基因表达。了解这些遗传差异导致疾病的机制 是基因组研究的中心目标，旨在描述疾病机制和识别 治疗性治疗的目标。虽然大规模的研究已经确定了数千种基因 与免疫疾病相关的差异，在大多数情况下，不知道哪些变体是 有因果关系的和无因果关系的乘客变体。这对许多人来说是一个相当大的问题 存在于基因组非编码区的变体，其功能难以预测。因此，在本发明中， 迫切需要高通量的实验方法来表征该功能 以及与免疫疾病相关的许多非编码变体的机制。解决这个 挑战，我们将使用两种互补的高通量方法来研究遗传学的影响。 免疫基因表达的变异。我们将使用MPRA（大规模平行报告基因测定）， 研究遗传变异对基因表达的影响。我们将使用我们最近开发的 CASCADE（DNA元件复杂组装的综合评估）方法， 结合基于质谱的研究，分析遗传变异对TF的影响， 辅因子复合物结合。我们将使用这些方法来描述（1）遗传因素的影响 约30种免疫基因调控元件上的变异，以及（2）发现约5000种遗传变异， 与免疫疾病或基因表达改变有关。将这些方法结合起来， 解决细胞和刺激特异性遗传变异的功能和生物物理机制 方式此外，由于许多调节辅因子可以被药物抑制，因此TF-1的特征是： 与遗传变异体结合的辅因子复合物提供了鉴定治疗剂的机会， 抵消其影响。总之，通过整合互补的高通量方法， 直接解释细胞类型和细胞刺激的影响，拟议的研究将确定 非编码变体影响基因表达和免疫疾病的机制。 此外，这些研究将为将大规模遗传研究转化为 免疫疾病的治疗方法。

Project Summary Susceptibility to diverse immune diseases has been associated with genetic differences that affect gene expression. Understanding the mechanisms by which these genetic differences lead to disease has been a central goal of genomic efforts aimed at describing disease mechanisms and identifying targets for therapeutic treatments. While large-scale studies have identified thousands of genetic differences associated with immune diseases, in most cases, it is not known which variants are causal and which are non-causal passenger variants. This is a considerable problem for the many variants that exists in non-coding regions of the genome for which function is difficult to predict. Thus, there is a critical need for the high-throughput experimental approaches to characterize the function and mechanism of the many non-coding variants associated with immune diseases. To tackle this challenge, we will use two complementary high-throughput approaches to study the impact of genetic variants on immune gene expression. We will use MPRAs (Massively Parallel Reporter Assays) to study the impact of genetic variants on gene expression. We will use our recently developed CASCADE (Comprehensive Assessment of Complex Assembly at DNA Elements) approach, in conjunction with mass spectrometry-based studies, to profile the impact of genetic variants on TF- cofactor complex binding. We will use these approaches to characterize (1) the impact of genetic variants on ~30 immune gene regulatory elements, and (2) ~5000 genetic variants found to be associated with immune disease or altered gene expression. Combining these approaches will address both function and biophysical mechanism of genetic variants in a cell- and stimulus-specific manner. Furthermore, as many regulatory cofactors can be inhibited with drugs, characterizing TF- cofactor complexes bound at genetic variants provides an opportunity to identify therapeutics to counteract their effects. Altogether, by integrating complementary, high-throughput approaches that directly account for effects of cell type and cell stimulation, the proposed studies will identify the mechanisms by which non-coding variants affect gene expression and immune diseases. Furthermore, these studies will lay a foundation for translating large-scale genetic studies into therapeutic approaches to treat for immune diseases.