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Human genome-wide measurement of drug-responsive regulatory activity.

Graham D Johnson | Alejandro Barrera | Ian C McDowell | Anthony M D'Ippolito | William H Majoros | Christopher M Vockley | Xingyan Wang | Andrew S Allen | Timothy E Reddy
Nature communications | 2018

Environmental stimuli commonly act via changes in gene regulation. Human-genome-scale assays to measure such responses are indirect or require knowledge of the transcription factors (TFs) involved. Here, we present the use of human genome-wide high-throughput reporter assays to measure environmentally-responsive regulatory element activity. We focus on responses to glucocorticoids (GCs), an important class of pharmaceuticals and a paradigmatic genomic response model. We assay GC-responsive regulatory activity across >108 unique DNA fragments, covering the human genome at >50×. Those assays directly detected thousands of GC-responsive regulatory elements genome-wide. We then validate those findings with measurements of transcription factor occupancy, histone modifications, chromatin accessibility, and gene expression. We also detect allele-specific environmental responses. Notably, the assays did not require knowledge of GC response mechanisms. Thus, this technology can be used to agnostically quantify genomic responses for which the underlying mechanism remains unknown.

Pubmed ID: 30575722

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: NIDDK NIH HHS, United States
    Id: F32 DK115188
  • Agency: NIH HHS, United States
    Id: S10 OD018164
  • Agency: NHGRI NIH HHS, United States
    Id: U01 HG007900

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ChIP-seq (tool)

RRID:SCR_001237

Set of software modules for performing common ChIP-seq data analysis tasks across the whole genome, including positional correlation analysis, peak detection, and genome partitioning into signal-rich and signal-poor regions. The tools are designed to be simple, fast and highly modular. Each program carries out a well defined data processing procedure that can potentially fit into a pipeline framework. ChIP-Seq is also freely available on a Web interface.

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RRID:SCR_002105

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RRID:SCR_008452

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RRID:SCR_012802

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RRID:CVCL_0023

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