Nature CommunicationsGenomicsPeer-reviewed journal article
Drug-induced cis-regulatory elements in human hepatocytes affect molecular phenotypes associated with adverse reactions
Saki Gotoh-SaitoiD, Ryoko WadaiD, Tomoe Nishimura, Hideya KawajiiD
Abstract
BackgroundGenomic variations contribute to the phenotypic diversity of individuals. A number of polymorphisms in protein-coding regions that alter drug efficacy or lead to adverse reactions have been characterized; however, noncoding regions that affect drug responses are largely overlooked, except for a limited number of well-studied enhancers. ResultsWe conducted a quantitative assessment of cis-regulatory elements (CREs) based on transcription initiation profiling of mRNAs and noncoding RNAs, including enhancer RNAs, by using CAGE (Cap Analysis of Gene Expression). Candidate CREs identified in a hepatocellular carcinoma HepG2 cell line with stable expression of drug-responsive transcription factor pregnane X receptor (PXR) were further narrowed down by integrating data of PXR-binding sites in human primary hepatocytes and genome-wide association studies. We found more than 100-fold enrichments of the candidates to genetically associated loci with circulating levels of bilirubin and vitamin D, which implicated a link to adverse reactions of PXR ligands. We uncovered novel enhancers of UGT1A1 and TSKU through CRISPR/Cas9 knockout experiments. We identified alleles altering regulatory activities of UGT1A1 and CYP24A1enhancers by using luciferase reporter assay. Furthermore, our siRNA experiments revealed an unexpected impact of TSKU on the expression of vitamin D-metabolizing enzymes. ConclusionsOur transcriptome-based assessment of CREs expanded the list of drug-inducible and PXR-mediated enhancers and super-enhancers. We identified regulatory alleles that alter drug-induced gene expressions, and discovered a novel molecular cascade associated with an adverse reaction. Our results contribute a precise understanding of the noncoding elements of the human genome underlying drug responses.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 7
- FWCI
- 6.75
- Field percentile
- top 3%
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