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
Link To Document :
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