PLoS Genetics · 2016 · 50 citations · 59 references
MedicineMolecular BiologyMolecular GeneticsEpigeneticsGene ExpressionTranscriptional RegulationDiabetes Mellitus BiochemistryHepatic PathophysiologyLiver DiseaseLiver PhysiologyMetabolic Liver DiseaseAtaxia-telangiectasia Mutated SignalingAtaxia-telangiectasia SignalingCell Type-specific Enhancer ActivityCrispr ActivationExpression Quantitative Trait Locus AnalysisExpression Quantitative Trait Locus DiscoveryHepatic Metabolic SignalingInduction In Hepatocytes
Metformin is used as a first-line therapy for type 2 diabetes (T2D) and prescribed for numerous other diseases. However, its mechanism of action in the liver has yet to be characterized in a systematic manner. To comprehensively identify genes and regulatory elements associated with metformin treatment, we carried out RNA-seq and ChIP-seq (H3K27ac, H3K27me3) on primary human hepatocytes from the same donor treated with vehicle control, metformin or metformin and compound C, an AMP-activated protein kinase (AMPK) inhibitor (allowing to identify AMPK-independent pathways). We identified thousands of metformin responsive AMPK-dependent and AMPK-independent differentially expressed genes and regulatory elements. We functionally validated several elements for metformin-induced promoter and enhancer activity. These include an enhancer in an ataxia telangiectasia mutated (ATM) intron that has SNPs in linkage disequilibrium with a metformin treatment response GWAS lead SNP (rs11212617) that showed increased enhancer activity for the associated haplotype. Expression quantitative trait locus (eQTL) liver analysis and CRISPR activation suggest that this enhancer could be regulating ATM, which has a known role in AMPK activation, and potentially also EXPH5 and DDX10, its neighboring genes. Using ChIP-seq and siRNA knockdown, we further show that activating transcription factor 3 (ATF3), our top metformin upregulated AMPK-dependent gene, could have an important role in gluconeogenesis repression. Our findings provide a genome-wide representation of metformin hepatic response, highlight important sequences that could be associated with interindividual variability in glycemic response to metformin and identify novel T2D treatment candidates.
59
BEDTools: a flexible suite of utilities for comparing genomic features
Aaron R. Quinlan, Ira M. Hall · Bioinformatics · 2010 · 30.4K citations · Full text
HTSeq—a Python framework to work with high-throughput sequencing data
Simon Anders, Paul Theodor Pyl, Wolfgang Huber · Bioinformatics · 2014 · 22.7K citations · Full text