Abstract
Genome-wide epigenomic maps revealed millions of regions showing signatures of enhancers, promoters, and other gene-regulatory elements1. However, high-throughput experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited in their scale and length of regions tested. Here, we present a new method, HiDRA (High-Definition Reporter Assay), that overcomes these limitations by combining components of Sharpr-MPRA2 and STARR-Seq3 with genome-wide selection of accessible regions from ATAC-Seq4. We used HiDRA to test ~7 million DNA fragments preferentially selected from accessible chromatin in the GM12878 lymphoblastoid cell line. By design, accessibility-selected fragments were highly overlapping (up to 370 per region), enabling us to pinpoint driver regulatory nucleotides by exploiting subtle differences in reporter activity between partially-overlapping fragments, using a new machine learning model SHARPR2. Our resulting maps include ~65,000 regions showing significant enhancer function and enriched for endogenous active histone marks (including H3K9ac, H3K27ac), regulatory sequence motifs, and regions bound by immune regulators. Within them, we discover ~13,000 high-resolution driver elements enriched for regulatory motifs and evolutionarily-conservednucleotides, and help predict causal genetic variants underlying disease from genome-wide association studies. Overall, HiDRA provides a general, scalable, high-throughput, and high-resolution approach for experimental dissection of regulatory regions and driver nucleotides in the context of human biology and disease.
