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

摘要 多发性硬化症（MS）是一种自身免疫性疾病， 致病的理解和没有治愈。全基因组关联研究 （GWAS）在MS上鉴定了>200个MS相关基因座。这些位点代表了 数以千计的遗传变异，通常在单核苷酸多态性 （SNP），连锁不平衡（LD）。然而，GWAS并没有告诉我们 它们是每个基因座中的因果/功能SNP（fSNP）。这种技术缺陷 在GWAS和特定机制之间留下了一个“缺口”， 生物学洞察和治疗干预的机会有限。到 为了克服这一局限性，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下拉（FREP）。fSNP-seq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， 因此代表fSNP。FREP使用fSNP序列作为“诱饵”来识别 以半高通量的方式检测相关的调节蛋白。使用这些 技术，我们已经确定了MS相关的CD 40基因座上的三个fSNP， 已通过EMSA（等位基因特异性荧光素酶报告基因测定）证实， CRISPR/Cas9，我们还确定了四种调节CD 40的调节蛋白， 通过这些fSNPs表达。根据这些初步数据，我们提出 两个目标是将我们的新方法应用于MS上的整个GWAS数据。首先，我们将 使用我们对CD 40基因座的新见解来定义潜在的靶向CD 40 调节蛋白复合物。其次，我们将使用fSNP-seq进行高- 在LD的4573个SNPs中，通过196个风险位点识别fSNPs， 女士我们将使用FREP系统地鉴定调控蛋白， 通过MS fSNP表达MS相关基因， MS相关的抗原呈递基因，如CD 86、CD 80和MHCI， R21应用。总之，这些研究将帮助我们产生一个MS- 相关的信号转导和等位基因特异性转录网络（MS- STAST网络），目的是确定MS治疗的新靶点。

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.