GWAS cannot identify functional SNPs (fSNP) from disease-associated SNPs in linkage disequilibrium (LD). Here, we report developing three sequential methodologies including Reel-seq (Regulatory element-sequencing) to identify fSNPs in a high-throughput fashion, SDCP-MS (SNP-specific DNA competition pulldown-mass spectrometry) to identify fSNP-bound proteins and AIDP-Wb (allele-imbalanced DNA pulldown-Western blot) to detect allele-specific protein:fSNP binding. We first apply Reel-seq to screen a library containing 4316 breast cancer-associated SNPs and identify 521 candidate fSNPs. As proof of principle, we verify candidate fSNPs on three well-characterized loci: FGFR2, MAP3K1 and BABAM1. Next, using SDCP-MS and AIDP-Wb, we rapidly identify multiple regulatory factors that specifically bind in an allele-imbalanced manner to the fSNPs on the FGFR2 locus. We finally demonstrate that the factors identified by SDCP-MS can regulate risk gene expression. These data suggest that the sequential application of Reel-seq, SDCP-MS, and AIDP-Wb can greatly help to translate large sets of GWAS data into biologically relevant information.

GWAS 无法从连锁不平衡 (LD) 中的疾病相关 SNP 中识别功能性 SNP (fSNP)。在此，我们报告开发了三种连续方法，包括用于以高通量方式识别 fSNP 的 Reel-seq（调节元件测序）、用于识别 fSNP 结合蛋白的 SDCP-MS（SNP 特异性 DNA 竞争下拉质谱）和 AIDP -Wb（等位基因不平衡 DNA Pulldown-Western blot）检测等位基因特异性蛋白：fSNP 结合。我们首先应用 Reel-seq 筛选包含 4316 个乳腺癌相关 SNP 的文库，并鉴定出 521 个候选 fSNP。作为原理证明，我们验证了三个特征明确的基因座上的候选 fSNP： FGFR2 、 MAP3K1和BABAM1 。接下来，使用 SDCP-MS 和 AIDP-Wb，我们快速识别了以等位基因不平衡方式与FGFR2基因座上的 fSNP 特异性结合的多个调控因子。我们最终证明 SDCP-MS 识别的因素可以调节风险基因表达。这些数据表明，Reel-seq、SDCP-MS 和 AIDP-Wb 的顺序应用可以极大地帮助将大量 GWAS 数据转化为生物学相关信息。