• DocumentCode
    27278
  • Title

    Construction and analysis of microRNA-transcription factor regulation network in arabidopsis

  • Author

    Lie Tang ; Zhao Zhang ; Peizhen Gu ; Ming Chen

  • Author_Institution
    Dept. of Bioinf., Coll. of Life Sci., Hangzhou, China
  • Volume
    8
  • Issue
    3
  • fYear
    2014
  • fDate
    6 2014
  • Firstpage
    76
  • Lastpage
    86
  • Abstract
    Transcription factors (TFs) and microRNAs (miRNAs) are two major types of regulators of gene expression, at transcriptional and post-transcriptional levels, respectively. By gathering their gene regulatory relationships, gene regulatory networks (GRNs) could be formed. A network motif is a type of connection pattern among a set of nodes which appears significantly more frequently than in random networks. Investigations of the network motifs often yield biological insights into the nature of the network. The previous study on miRNA-TF regulation networks concentrated on animals, and relied heavily on computational predictions. The authors collected data concerning miRNA regulation and transcriptional regulation relationships in Arabidopsis from publicly available databases, and further incorporated them with the protein-protein interaction data. All the data in the author´s collection are supported by experiments. They screened the network motifs, whose size ranges between 1 and 4. The biological implications of the motifs were further analysed, and a flower development related network was constructed as an example. In this example, they illustrated the relevance of the network with the given process, and proposed the association of several genes with flowers by a network cluster identification. In this study, they analysed the properties of the GRN in Arabidopsis, and discussed their biological implications, as well as their potential applications.
  • Keywords
    RNA; bioinformatics; botany; cellular biophysics; genetics; molecular biophysics; proteins; Arabidopsis; GRN; flower development related network; gene expression; gene regulatory networks; gene regulatory relationships; miRNA; microRNA-transcription factor regulation network; network cluster identification; network motifs; post-transcriptional levels; protein-protein interaction data; transcriptional levels;
  • fLanguage
    English
  • Journal_Title
    Systems Biology, IET
  • Publisher
    iet
  • ISSN
    1751-8849
  • Type

    jour

  • DOI
    10.1049/iet-syb.2013.0024
  • Filename
    6823381