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Global analysis of Drosophila Cys2-His2 zinc finger proteins reveals a multitude of novel recognition motifs and binding determinants

    • 1Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA;
    • 2Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA;
    • 3Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA;
    • 4Department of Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA;
    • 5Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA;
    • 6Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA;
    • 7Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA;
    • 8Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA
Published March 7, 2013. Vol 23 Issue 6, pp. 928-940. https://doi.org/10.1101/gr.151472.112
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Abstract

Cys2-His2 zinc finger proteins (ZFPs) are the largest group of transcription factors in higher metazoans. A complete characterization of these ZFPs and their associated target sequences is pivotal to fully annotate transcriptional regulatory networks in metazoan genomes. As a first step in this process, we have characterized the DNA-binding specificities of 129 zinc finger sets from Drosophila using a bacterial one-hybrid system. This data set contains the DNA-binding specificities for at least one encoded ZFP from 70 unique genes and 23 alternate splice isoforms representing the largest set of characterized ZFPs from any organism described to date. These recognition motifs can be used to predict genomic binding sites for these factors within the fruit fly genome. Subsets of fingers from these ZFPs were characterized to define their orientation and register on their recognition sequences, thereby allowing us to define the recognition diversity within this finger set. We find that the characterized fingers can specify 47 of the 64 possible DNA triplets. To confirm the utility of our finger recognition models, we employed subsets of Drosophila fingers in combination with an existing archive of artificial zinc finger modules to create ZFPs with novel DNA-binding specificity. These hybrids of natural and artificial fingers can be used to create functional zinc finger nucleases for editing vertebrate genomes.

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