Comprehensive discovery of DNA motifs in 349 human cells and tissues reveals new features of motifs

    Authors

    Nucleic Acids Res.

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    Int. J. Sport Nutr. Exerc. Metab.

    Keywords

    TRANSCRIPTION FACTOR-BINDING; CHIP-SEQ DATA; HUMAN GENOME; SYSTEMATIC; IDENTIFICATION; DATABASE; CHROMATIN; EXPRESSION; UPDATE; SITES; GENE; Biochemistry & Molecular Biology

    Abstract

    Comprehensive motif discovery under experimental conditions is critical for the global understanding of gene regulation. To generate a nearly complete list of human DNA motifs under given conditions, we employed a novel approach to de novo discover significant co-occurring DNA motifs in 349 human DNase I hypersensitive site datasets. We predicted 845 to 1325 motifs in each dataset, for a total of 2684 non-redundant motifs. These 2684 motifs contained 54.02 to 75.95% of the known motifs in seven large collections including TRANSFAC. In each dataset, we also discovered 43 663 to 2 013 288 motif modules, groups of motifs with their binding sites co-occurring in a significant number of short DNA regions. Compared with known interacting transcription factors in eight resources, the predicted motif modules on average included 84.23% of known interacting motifs. We further showed new features of the predicted motifs, such as motifs enriched in proximal regions rarely overlapped with motifs enriched in distal regions, motifs enriched in 5' distal regions were often enriched in 3' distal regions, etc. Finally, we observed that the 2684 predicted motifs classified the cell or tissue types of the datasets with an accuracy of 81.29%. The resources generated in this study are available at http://server.cs.ucf.edu/predrem/.

    Subjects

    Y. Y. Zheng; X. M. Li;H. Y. Hu

    Volume

    43

    Issue/Number

    1

    Publication Date

    1-1-2014

    Document Type

    Article

    Language

    English

    First Page

    74

    Last Page

    83

    WOS Identifier

    WOS:000350207100013

    ISSN

    0305-1048

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