Integrated approach for the identification of human hepatocyte nuclear factor 4α target genes using protein binding microarrays

Authors

  • Eugene Bolotin,

    1. Genetics, Genomics and Bioinformatics Graduate Program, University of California Riverside, Riverside, CA
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  • Hailing Liao,

    1. Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, CA
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  • Tuong Chi Ta,

    1. Cell, Molecular, and Developmental Biology Graduate Program, University of California Riverside, Riverside, CA
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  • Chuhu Yang,

    1. Genetics, Genomics and Bioinformatics Graduate Program, University of California Riverside, Riverside, CA
    Current affiliation:
    1. Roche Diagnostics Shanghai Limited, 1045 Central Huaihai Road, Shanghai 200031, China
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  • Wendy Hwang-Verslues,

    1. Environmental Toxicology Graduate Program, University of California Riverside, Riverside, CA
    Current affiliation:
    1. Genomics Research Center, Academia Sinica, No. 128 Academia Road, Section 2, Nankang District, Taipei 115, Taiwan
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  • Jane R. Evans,

    1. Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, CA
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  • Tao Jiang,

    1. Department of Computer Science and Engineering, University of California Riverside, Riverside, CA
    2. Institute for Integrated Genome Biology (also at UCR)
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  • Frances M. Sladek

    Corresponding author
    1. Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, CA
    2. Institute for Integrated Genome Biology (also at UCR)
    • Professor of Cell Biology, Department of Cell Biology and Neuroscience, 2115 Biological Sciences, University of California, Riverside, Riverside, CA 92521-0314===

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    • fax: 951-827-3087


  • Potential conflict of interest: Nothing to report.

Abstract

Hepatocyte nuclear factor 4 alpha (HNF4α), a member of the nuclear receptor superfamily, is essential for liver function and is linked to several diseases including diabetes, hemophilia, atherosclerosis, and hepatitis. Although many DNA response elements and target genes have been identified for HNF4α, the complete repertoire of binding sites and target genes in the human genome is unknown. Here, we adapt protein binding microarrays (PBMs) to examine the DNA-binding characteristics of two HNF4α species (rat and human) and isoforms (HNF4α2 and HNF4α8) in a high-throughput fashion. We identified ∼1400 new binding sequences and used this dataset to successfully train a Support Vector Machine (SVM) model that predicts an additional ∼10,000 unique HNF4α-binding sequences; we also identify new rules for HNF4α DNA binding. We performed expression profiling of an HNF4α RNA interference knockdown in HepG2 cells and compared the results to a search of the promoters of all human genes with the PBM and SVM models, as well as published genome-wide location analysis. Using this integrated approach, we identified ∼240 new direct HNF4α human target genes, including new functional categories of genes not typically associated with HNF4α, such as cell cycle, immune function, apoptosis, stress response, and other cancer-related genes. Conclusion: We report the first use of PBMs with a full-length liver-enriched transcription factor and greatly expand the repertoire of HNF4α-binding sequences and target genes, thereby identifying new functions for HNF4α. We also establish a web-based tool, HNF4 Motif Finder, that can be used to identify potential HNF4α-binding sites in any sequence. (HEPATOLOGY 2009.)

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