Systems Approaches to Identifying Gene Regulatory Networks in Plants

1Department of Biology, Duke University, Durham, North Carolina 27708, USA.
Annual Review of Cell and Developmental Biology (Impact Factor: 16.66). 08/2008; 24(1):81-103. DOI: 10.1146/annurev.cellbio.24.110707.175408
Source: PubMed


Complex gene regulatory networks are composed of genes, noncoding RNAs, proteins, metabolites, and signaling components. The availability of genome-wide mutagenesis libraries; large-scale transcriptome, proteome, and metabalome data sets; and new high-throughput methods that uncover protein interactions underscores the need for mathematical modeling techniques that better enable scientists to synthesize these large amounts of information and to understand the properties of these biological systems. Systems biology approaches can allow researchers to move beyond a reductionist approach and to both integrate and comprehend the interactions of multiple components within these systems. Descriptive and mathematical models for gene regulatory networks can reveal emergent properties of these plant systems. This review highlights methods that researchers are using to obtain large-scale data sets, and examples of gene regulatory networks modeled with these data. Emergent properties revealed by the use of these network models and perspectives on the future of systems biology are discussed.

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    • "This functional diversity makes it difficult to elucidate the individual influences of each family member of bZIP TFs within their various regulatory networks [56]. Bioinformatics in a high-throughput mode and molecular modelling approaches can be employed to identify the components of bZIP TFs regulatory networks [59]. Continued research to identify the biological roles of bZIP TFs and molecular mechanisms of their function is essential before effective GE of crop plants can be undertaken. "
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    ABSTRACT: Background: Basic leucine zipper (bZIP) genes encode transcription factors (TFs) that control important biochemical and physiological processes in plants and all other eukaryotic organisms. Scope of review: Here we present (i) the homo-dimeric structural model of bZIP consisting of basic leucine zipper and DNA binding regions, in complex with the synthetic Abscisic Acid-Responsive Element (ABREsyn); (ii) discuss homo- and hetero-dimerisation patterns of bZIP TFs; (iii) summarise the current progress in understanding the molecular mechanisms of function of bZIP TFs, including features determining the specificity of their binding to DNA cis-elements, and (iv) review information on interaction partners of bZIPs during plant development and stress response, as well as on types and roles of post-translational modifications, and regulatory aspects of protein-degradation mediated turn-over. Finally, we (v) recapitulate on the recent advances regarding functional roles of bZIP factors in major agricultural crops, and discuss the potential significance of bZIP-based genetic engineering in improving crop yield and tolerance to abiotic stresses. Major conclusions: An accurate analysis and understanding of roles of plant bZIP TFs in different biological processes requires the knowledge of interacting partners, time and location of expression in plant organs, and the information on mechanisms of homo- and hetero-dimerisation of bZIP TFs. General significance: Studies on molecular mechanisms of plant bZIP TFs at the atomic levels will provide novel insights into the regulatory processes during plant development, and responses to abiotic and biotic stresses.
    Biochimica et Biophysica Acta 10/2015; DOI:10.1016/j.bbagen.2015.10.014 · 4.66 Impact Factor
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    • "ns , representing a binary phase transition study , in nongerminating ( or dormant ) and germinating Arabidopsis thaliana seeds ( Bassel et al . , 2011 ) . Integration of the ex - pression data at the resolution of developmental stages and in different environmental contexts is expected to generate a high confidence dynamic gene regulatory model ( Long et al . , 2008 ) ."
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    The Plant Cell 09/2015; DOI:10.1105/tpc.15.00632 · 9.34 Impact Factor
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    • "To fully understand the transcriptional regulation of a developmental process, it is necessary to determine the binding of individual transcription factors to their target genes. Transcription factor binding data can be used in modeling of transcriptional regulatory networks, which provide precise specifications of complex interdependencies underpinning these biological systems (Ideker et al., 2001; Long et al., 2008; Van de Poel et al., 2014). The putative target genes for a given transcription factor can be estimated using a variety of techniques. "
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