Using High Throughput Approach to Identify/Characterize Functional Variants on MS

使用高通量方法在 MS 上识别/表征功能变异

• 批准号: 9670361
• 负责人: Gang Li
• 金额: $ 16.23万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-20 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9670361
• 关键词: Using; Throughput; Approach; Identify; Characterize

Abstract Multiple sclerosis (MS) is an autoimmune disease for which there is limited pathogenic understanding and no cure. Genome wide association studies (GWAS) on MS have identified >200 MS-associated loci. These loci represent thousands of genetic variants, usually in single nucleotide polymorphisms (SNPs), in linkage disequilibrium (LD). However, GWAS doesn't tell which one of them is the causal/functional SNP (fSNP) in each locus. This technical drawback leaves a “gap” between GWAS and specific mechanism that translates into limited opportunities for biological insight and therapeutic intervention. To overcome this limitation, we have developed two novel techniques: functional Single Nucleotide Polymorphism-seq (fSNP-seq) and Flanking Restriction Enzyme-mediated DNA Pulldown (FREP). fSNP-seq is a high throughput method to identify experimentally which SNPs are likely to bind regulatory proteins and therefore to represent fSNPs. FREP uses an fSNP sequence as “bait” to identify associated regulatory proteins in a semi high throughput way. Using these techniques, we have identified three fSNPs on a MS-associated CD40 locus that have been confirmed by EMSA, an allele-specific luciferase reporter assay and CRISPR/Cas9, and we also identified four regulatory proteins that regulate CD40 expression via these fSNPs. On the basis of these preliminary data, we propose two aims to apply our new methods to the entire GWAS data on MS. First, we will use our new insights into CD40 locus to define a potentially targetable CD40 regulatory protein complex. Second, we will employ fSNP-seq to undertake high- throughput identification of fSNPs among 4573 SNPs in LD with 196 risk loci for MS. We will use FREP to systematically identify regulatory proteins that control the expression of MS-associated genes via the MS fSNPs by focusing on the MS-associated antigen presenting genes such as CD86, CD80 and MHCI for this R21 application. Together, these studies will help us to generate a MS- associated signal transduction and allele-specific transcription network (MS- STAST network), with the goal of identifying novel targets for MS therapy.

抽象的 多发性硬化症 (MS) 是一种自身免疫性疾病，其治疗手段有限 致病性了解和无治愈方法的全基因组关联研究。 MS 的 GWAS 已鉴定出超过 200 个 MS 相关基因座。 数千个遗传变异，通常是单核苷酸多态性 （SNP），连锁不平衡（LD） 然而，GWAS 并没有告诉我们是哪一个。 它们是每个位点的因果/功能性 SNP (fSNP)。 在 GWAS 和转化为具体机制之间留下了“差距” 生物学洞察和治疗干预的机会有限。 为了克服这个限制，我们开发了两种新技术： 单核苷酸多态性-seq (fSNP-seq) 和侧翼限制 酶介导的 DNA Pulldown (FREP) 是一种高通量方法。 通过实验确定哪些 SNP 可能与调节蛋白结合 因此，为了表示 fSNP，FREP 使用 fSNP 序列作为“诱饵”来识别。 以半高通量方式使用相关的调节蛋白。 技术，我们在 MS 相关 CD40 基因座上鉴定了三个 fSNP， 已被 EMSA（一种等位基因特异性荧光素酶报告基因检测）证实，并且 CRISPR/Cas9，我们还鉴定了四种调节CD40的调节蛋白 基于这些初步数据，我们提出了通过这些 fSNP 的表达。 两个目标是将我们的新方法应用于 MS 的整个 GWAS 数据。 利用我们对 CD40 基因座的新见解来定义潜在的可靶向 CD40 其次，我们将利用fSNP-seq进行高通量测序。 LD 中 4573 个 SNP 中的 fSNP 的通量识别（具有 196 个风险位点） MS。我们将使用 FREP 系统地识别控制的调节蛋白。 通过 MS fSNP 表达 MS 相关基因 MS 相关抗原呈递基因，例如 CD86、CD80 和 MHCI R21 应用程序一起，这些研究将帮助我们生成 MS- 相关信号转导和等位基因特异性转录网络（MS- STAST 网络），目标是确定多发性硬化症治疗的新靶点。