henhaobio
Sign in

Nature CommunicationsGenomicsPeer-reviewed journal article

High-resolution genome-wide functional dissection of transcriptional regulatory regions in human

Xinchen WangiD, Liang HeiD, Sarah M. GogginiD, Alham Saadat, Li WangiD, Nasa Sinnott-ArmstrongiD, Melina ClaussnitzeriD, M KellisiD

PDFDOIPreprint
Citations
159
FWCI
6.49
Field percentile
top 2%

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.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISHansen '22Wang '25Li '17Zhang '26Umarov '21Meuleman '20
55% semantic matchGenomics
Tyler J. Hansen, Emily C. Hodges·Genome Research·Aug 1, 2022· 67 citations