Allelic expression mapping across cellular lineages to establish impact of non‐coding SNP s

Abstract

Most complex disease‐associated genetic variants are located in non‐coding regions and are therefore thought to be regulatory in nature. Association mapping of differential allelic expression (AE) is a powerful method to identify SNPs with direct cis‐ regulatory impact ( cis‐ rSNP s). We used AE mapping to identify cis‐ rSNP s regulating gene expression in 55 and 63 HapMap lymphoblastoid cell lines from a Caucasian and an African population, respectively, 70 fibroblast cell lines, and 188 purified monocyte samples and found 40–60% of these cis ‐ rSNP s to be shared across cell types. We uncover a new class of cis ‐ rSNP s, which disrupt footprint‐derived de novo motifs that are predominantly bound by repressive factors and are implicated in disease susceptibility through overlaps with GWAS SNPs. Finally, we provide the proof‐of‐principle for a new approach for genome‐wide functional validation of transcription factor–SNP interactions. By perturbing NFκB action in lymphoblasts, we identified 489 cis ‐regulated transcripts with altered AE after NFκB perturbation. Altogether, we perform a comprehensive analysis of cis ‐variation in four cell populations and provide new tools for the identification of functional variants associated to complex diseases. image A comprehensive analysis cis ‐variation in four cell‐populations uncovers a new‐class of cis ‐regulatory SNP s associated with repressor activity. Global analysis of the role of key regulators is achieved by combining allelic expression read‐outs with targeted perturbation of transcription factors. Direct mapping of cis‐ regulatory SNP s in human tissues and populations reveals that greater than 50% of effects are shared and 5–10% of variants impact expression in regional rather than transcript‐specific manner. A new class of cis ‐ rSNP s is uncovered, which disrupts footprint‐derived de novo motifs that are predominantly bound by repressive factors and are implicated in disease susceptibility through overlaps with GWAS SNPs. A new approach is presented for the genome‐wide functional validation of transcription factor – SNP interactions using small molecule perturbation and allelic expression monitoring.