Abstract
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.
Highlights
genome-wide association studies (GWAS) cannot identify functional single nucleotide polymorphism (SNP) from disease-associated SNPs in linkage disequilibrium (LD)
There are a number of reasons for this, but one major hurdle is that SNPs used by GWAS to pinpoint genetic loci are a proxy for large stretches of DNA that contains many other SNPs in linkage disequilibrium (LD), most of which reside in noncoding DNA
Reel-seq is designed to identify functional SNPs (fSNP) based on the fact that the majority of disease-associated SNPs are located in noncoding regions of human genome[7]
Summary
GWAS cannot identify functional SNPs (fSNP) from disease-associated SNPs in linkage disequilibrium (LD). Our results revealed significant allelic differences in luciferase activity for all these 12 identified fSNPs (Fig. 3b) (Source data are provided as a Source Data file).
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