Literature DB >> 25014374

Construction and analysis of microRNA-transcription factor regulation network in Arabidopsis.

Lie Tang1, Zhao Zhang2, Peizhen Gu3, Ming Chen2.   

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.

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Year:  2014        PMID: 25014374      PMCID: PMC8687243          DOI: 10.1049/iet-syb.2013.0024

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  53 in total

Review 1.  Cell-fate specification in the epidermis: a common patterning mechanism in the root and shoot.

Authors:  John Schiefelbein
Journal:  Curr Opin Plant Biol       Date:  2003-02       Impact factor: 7.834

2.  DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions.

Authors:  Ioannis Xenarios; Lukasz Salwínski; Xiaoqun Joyce Duan; Patrick Higney; Sul-Min Kim; David Eisenberg
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

3.  Arabidopsis microRNA167 controls patterns of ARF6 and ARF8 expression, and regulates both female and male reproduction.

Authors:  Miin-Feng Wu; Qing Tian; Jason W Reed
Journal:  Development       Date:  2006-10-04       Impact factor: 6.868

4.  The sequential action of miR156 and miR172 regulates developmental timing in Arabidopsis.

Authors:  Gang Wu; Mee Yeon Park; Susan R Conway; Jia-Wei Wang; Detlef Weigel; R Scott Poethig
Journal:  Cell       Date:  2009-08-21       Impact factor: 41.582

Review 5.  The major clades of MADS-box genes and their role in the development and evolution of flowering plants.

Authors:  Annette Becker; Günter Theissen
Journal:  Mol Phylogenet Evol       Date:  2003-12       Impact factor: 4.286

6.  Construction and analysis of an integrated regulatory network derived from high-throughput sequencing data.

Authors:  Chao Cheng; Koon-Kiu Yan; Woochang Hwang; Jiang Qian; Nitin Bhardwaj; Joel Rozowsky; Zhi John Lu; Wei Niu; Pedro Alves; Masaomi Kato; Michael Snyder; Mark Gerstein
Journal:  PLoS Comput Biol       Date:  2011-11-17       Impact factor: 4.475

7.  ATTED-II: a database of co-expressed genes and cis elements for identifying co-regulated gene groups in Arabidopsis.

Authors:  Takeshi Obayashi; Kengo Kinoshita; Kenta Nakai; Masayuki Shibaoka; Shinpei Hayashi; Motoshi Saeki; Daisuke Shibata; Kazuki Saito; Hiroyuki Ohta
Journal:  Nucleic Acids Res       Date:  2006-11-27       Impact factor: 16.971

8.  A microRNA as a translational repressor of APETALA2 in Arabidopsis flower development.

Authors:  Xuemei Chen
Journal:  Science       Date:  2003-07-31       Impact factor: 47.728

9.  MicroRNAs inhibit the translation of target mRNAs on the endoplasmic reticulum in Arabidopsis.

Authors:  Shengben Li; Lin Liu; Xiaohong Zhuang; Yu Yu; Xigang Liu; Xia Cui; Lijuan Ji; Zhiqiang Pan; Xiaofeng Cao; Beixin Mo; Fuchun Zhang; Natasha Raikhel; Liwen Jiang; Xuemei Chen
Journal:  Cell       Date:  2013-04-25       Impact factor: 41.582

10.  Strong negative self regulation of prokaryotic transcription factors increases the intrinsic noise of protein expression.

Authors:  Dov J Stekel; Dafyd J Jenkins
Journal:  BMC Syst Biol       Date:  2008-01-18
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