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      Understanding microRNA-mediated gene regulatory networks through mathematical modelling

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        1 , * , 2 , 3 , 1 , *
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          The discovery of microRNAs (miRNAs) has added a new player to the regulation of gene expression. With the increasing number of molecular species involved in gene regulatory networks, it is hard to obtain an intuitive understanding of network dynamics. Mathematical modelling can help dissecting the role of miRNAs in gene regulatory networks, and we shall here review the most recent developments that utilise different mathematical modelling approaches to provide quantitative insights into the function of miRNAs in the regulation of gene expression. Key miRNA regulation features that have been elucidated via modelling include: (i) the role of miRNA-mediated feedback and feedforward loops in fine-tuning of gene expression; (ii) the miRNA–target interaction properties determining the effectiveness of miRNA-mediated gene repression; and (iii) the competition for shared miRNAs leading to the cross-regulation of genes. However, there is still lack of mechanistic understanding of many other properties of miRNA regulation like unconventional miRNA–target interactions, miRNA regulation at different sub-cellular locations and functional miRNA variant, which will need future modelling efforts to deal with. This review provides an overview of recent developments and challenges in this field.

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          Nature, nurture, or chance: stochastic gene expression and its consequences.

          Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
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            Ago HITS-CLIP decodes miRNA-mRNA interaction maps

            Summary MicroRNAs (miRNAs) play critical roles in the regulation of gene expression. However, since miRNA activity requires base pairing with only 6-8 nucleotides of mRNA, predicting target mRNAs is a major challenge. Recently, high-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP) has identified functional protein-RNA interaction sites. Here we use HITS-CLIP to covalently crosslink native Argonaute (Ago) protein-RNA complexes in mouse brain. This produced two simultaneous datasets—Ago-miRNA and Ago-mRNA binding sites—that were combined with bioinformatic analysis to identify miRNA-target mRNA interaction sites. We validated genome-wide interaction maps for miR-124, and generated additional maps for the 20 most abundant miRNAs present in P13 mouse brain. Ago HITS-CLIP provides a general platform for exploring the specificity and range of miRNA action in vivo, and identifies precise sequences for targeting clinically relevant miRNA-mRNA interactions.
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              Roles for microRNAs in conferring robustness to biological processes.

              Biological systems use a variety of mechanisms to maintain their functions in the face of environmental and genetic perturbations. Increasing evidence suggests that, among their roles as posttranscriptional repressors of gene expression, microRNAs (miRNAs) help to confer robustness to biological processes by reinforcing transcriptional programs and attenuating aberrant transcripts, and they may in some network contexts help suppress random fluctuations in transcript copy number. These activities have important consequences for normal development and physiology, disease, and evolution. Here, we will discuss examples and principles of miRNAs that contribute to robustness in animal systems. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                27 July 2016
                17 June 2016
                17 June 2016
                : 44
                : 13
                : 6019-6035
                Affiliations
                [1 ]Laboratory of Systems Tumour Immunology, Department of Dermatology, Erlangen University Hospital and Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, 91054, Germany
                [2 ]Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, 18051, Germany
                [3 ]Stellenbosch Institute for Advanced Study, Wallenberg Research Centre at Stellenbosch University, 7600, South Africa
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +49 913 1854 5888; Fax: +49 913 1853 3874; Email: xin.lai@ 123456uk-erlangen.de
                Correspondence may also be addressed to Julio Vera. Tel: +49 913 1854 5876; Fax: +49 913 1853 2780; Email: julio.vera-gonzalez@ 123456uk-erlangen.de
                Author information
                http://orcid.org/0000-0003-4913-5822
                http://orcid.org/0000-0002-3076-5122
                Article
                10.1093/nar/gkw550
                5291278
                27317695
                784b6d57-e158-4245-aa57-258f9d40272f
                © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 06 June 2016
                : 02 June 2016
                : 29 December 2015
                Page count
                Pages: 17
                Categories
                Survey and Summary
                Custom metadata
                27 July 2016

                Genetics
                Genetics

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