A Combination of Transcriptional and MicroRNA Regulation Improves the Stability of the Relative Concentrations of Target Genes
Identifieur interne : 000072 ( Pmc/Curation ); précédent : 000071; suivant : 000073A Combination of Transcriptional and MicroRNA Regulation Improves the Stability of the Relative Concentrations of Target Genes
Auteurs : Andrea Riba [Italie] ; Carla Bosia [Italie] ; Mariama El Baroudi [Italie] ; Laura Ollino [Italie] ; Michele Caselle [Italie]Source :
- PLoS Computational Biology [ 1553-734X ] ; 2014.
Abstract
It is well known that, under suitable conditions, microRNAs are able to fine tune the relative concentration of their targets to any desired value. We show that this function is particularly effective when one of the targets is a Transcription Factor (TF) which regulates the other targets. This combination defines a new class of feed-forward loops (FFLs) in which the microRNA plays the role of master regulator. Using both deterministic and stochastic equations, we show that these FFLs are indeed able not only to fine-tune the TF/target ratio to any desired value as a function of the miRNA concentration but also, thanks to the peculiar topology of the circuit, to ensure the stability of this ratio against stochastic fluctuations. These two effects are due to the interplay between the direct transcriptional regulation and the indirect TF/Target interaction due to competition of TF and target for miRNA binding (the so called “sponge effect”). We then perform a genome wide search of these FFLs in the human regulatory network and show that they are characterized by a very peculiar enrichment pattern. In particular, they are strongly enriched in all the situations in which the TF and its target have to be precisely kept at the same concentration notwithstanding the environmental noise. As an example we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and miR-17 family as master regulator. These FFLs ensure a tight control of the E2F/RB ratio which in turns ensures the stability of the transition from the G0/G1 to the S phase in quiescent cells.
Url:
DOI: 10.1371/journal.pcbi.1003490
PubMed: 24586138
PubMed Central: 3937125
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A Combination of Transcriptional and MicroRNA Regulation Improves the Stability of the Relative Concentrations of Target Genes</title><author><name sortKey="Riba, Andrea" sort="Riba, Andrea" uniqKey="Riba A" first="Andrea" last="Riba">Andrea Riba</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Physics and INFN, University of Torino, Torino, Italy</addr-line></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Physics and INFN, University of Torino, Torino</wicri:regionArea></affiliation></author><author><name sortKey="Bosia, Carla" sort="Bosia, Carla" uniqKey="Bosia C" first="Carla" last="Bosia">Carla Bosia</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Physics and INFN, University of Torino, Torino, Italy</addr-line></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Physics and INFN, University of Torino, Torino</wicri:regionArea></affiliation></author><author><name sortKey="El Baroudi, Mariama" sort="El Baroudi, Mariama" uniqKey="El Baroudi M" first="Mariama" last="El Baroudi">Mariama El Baroudi</name><affiliation wicri:level="1"><nlm:aff id="aff3"><addr-line>National Research Council (CNR), Institute of Informatics and Telematics (IIT) and Institute of Clinical Physiology (IFC), Laboratory for Integrative System Medicine (LISM), Pisa, Italy</addr-line></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>National Research Council (CNR), Institute of Informatics and Telematics (IIT) and Institute of Clinical Physiology (IFC), Laboratory for Integrative System Medicine (LISM), Pisa</wicri:regionArea></affiliation></author><author><name sortKey="Ollino, Laura" sort="Ollino, Laura" uniqKey="Ollino L" first="Laura" last="Ollino">Laura Ollino</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Physics and INFN, University of Torino, Torino, 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uniqKey="Bosia C" first="Carla" last="Bosia">Carla Bosia</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Physics and INFN, University of Torino, Torino, Italy</addr-line></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Physics and INFN, University of Torino, Torino</wicri:regionArea></affiliation></author><author><name sortKey="El Baroudi, Mariama" sort="El Baroudi, Mariama" uniqKey="El Baroudi M" first="Mariama" last="El Baroudi">Mariama El Baroudi</name><affiliation wicri:level="1"><nlm:aff id="aff3"><addr-line>National Research Council (CNR), Institute of Informatics and Telematics (IIT) and Institute of Clinical Physiology (IFC), Laboratory for Integrative System Medicine (LISM), Pisa, Italy</addr-line></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>National Research Council (CNR), Institute of Informatics and Telematics (IIT) and Institute of Clinical Physiology (IFC), Laboratory for Integrative System Medicine (LISM), Pisa</wicri:regionArea></affiliation></author><author><name sortKey="Ollino, Laura" sort="Ollino, Laura" uniqKey="Ollino L" first="Laura" last="Ollino">Laura Ollino</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Physics and INFN, University of Torino, Torino, Italy</addr-line></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Physics and INFN, University of Torino, Torino</wicri:regionArea></affiliation></author><author><name sortKey="Caselle, Michele" sort="Caselle, Michele" uniqKey="Caselle M" first="Michele" last="Caselle">Michele Caselle</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Physics and INFN, University of Torino, Torino, Italy</addr-line></nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Physics and INFN, University of Torino, Torino</wicri:regionArea></affiliation></author></analytic><series><title level="j">PLoS Computational Biology</title><idno type="ISSN">1553-734X</idno><idno type="eISSN">1553-7358</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>It is well known that, under suitable conditions, microRNAs are able to fine tune the relative concentration of their targets to any desired value. We show that this function is particularly effective when one of the targets is a Transcription Factor (TF) which regulates the other targets. This combination defines a new class of feed-forward loops (FFLs) in which the microRNA plays the role of master regulator. Using both deterministic and stochastic equations, we show that these FFLs are indeed able not only to fine-tune the TF/target ratio to any desired value as a function of the miRNA concentration but also, thanks to the peculiar topology of the circuit, to ensure the stability of this ratio against stochastic fluctuations. These two effects are due to the interplay between the direct transcriptional regulation and the indirect TF/Target interaction due to competition of TF and target for miRNA binding (the so called “sponge effect”). We then perform a genome wide search of these FFLs in the human regulatory network and show that they are characterized by a very peculiar enrichment pattern. In particular, they are strongly enriched in all the situations in which the TF and its target have to be precisely kept at the same concentration notwithstanding the environmental noise. As an example we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and miR-17 family as master regulator. 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article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS Comput Biol</journal-id><journal-id journal-id-type="iso-abbrev">PLoS Comput. Biol</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">ploscomp</journal-id><journal-title-group><journal-title>PLoS Computational Biology</journal-title></journal-title-group><issn pub-type="ppub">1553-734X</issn><issn pub-type="epub">1553-7358</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">24586138</article-id><article-id pub-id-type="pmc">3937125</article-id><article-id pub-id-type="publisher-id">PCOMPBIOL-D-13-01213</article-id><article-id pub-id-type="doi">10.1371/journal.pcbi.1003490</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biology</subject><subj-group><subject>Biophysics</subject></subj-group><subj-group><subject>Computational Biology</subject></subj-group></subj-group></article-categories><title-group><article-title>A Combination of Transcriptional and MicroRNA Regulation Improves the Stability of the Relative Concentrations of Target Genes</article-title><alt-title alt-title-type="running-head">Combining MicroRNA and Transcriptional Regulation</alt-title></title-group><contrib-group><contrib contrib-type="author" equal-contrib="yes"><name><surname>Riba</surname><given-names>Andrea</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" equal-contrib="yes"><name><surname>Bosia</surname><given-names>Carla</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author"><name><surname>El Baroudi</surname><given-names>Mariama</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Ollino</surname><given-names>Laura</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author"><name><surname>Caselle</surname><given-names>Michele</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff1"><label>1</label><addr-line>Department of Physics and INFN, University of Torino, Torino, Italy</addr-line></aff><aff id="aff2"><label>2</label><addr-line>Human Genetics Foundation (HuGeF), Torino, Italy</addr-line></aff><aff id="aff3"><label>3</label><addr-line>National Research Council (CNR), Institute of Informatics and Telematics (IIT) and Institute of Clinical Physiology (IFC), Laboratory for Integrative System Medicine (LISM), Pisa, Italy</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Zhou</surname><given-names>Xianghong Jasmine</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>University of Southern California, United States of America</addr-line></aff><author-notes><corresp id="cor1">* E-mail: <email>riba@to.infn.it</email> (AR); <email>carla.bosia@hugef-torino.org</email> (CB)</corresp><fn fn-type="conflict"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type="con"><p>Wrote the paper: AR CB MEB LO MC. Designed research and analyzed data: AR CB. Performed the bioinformatic analysis: LO MEB. Designed and supervised research: MC.</p></fn></author-notes><pub-date pub-type="collection"><month>2</month><year>2014</year></pub-date><pub-date pub-type="epub"><day>27</day><month>2</month><year>2014</year></pub-date><volume>10</volume><issue>2</issue><elocation-id>e1003490</elocation-id><history><date date-type="received"><day>9</day><month>7</month><year>2013</year></date><date date-type="accepted"><day>18</day><month>12</month><year>2013</year></date></history><permissions><copyright-statement>© 2014 Riba et al</copyright-statement><copyright-year>2014</copyright-year><copyright-holder>Riba et al</copyright-holder><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.</license-p></license></permissions><abstract><p>It is well known that, under suitable conditions, microRNAs are able to fine tune the relative concentration of their targets to any desired value. We show that this function is particularly effective when one of the targets is a Transcription Factor (TF) which regulates the other targets. This combination defines a new class of feed-forward loops (FFLs) in which the microRNA plays the role of master regulator. Using both deterministic and stochastic equations, we show that these FFLs are indeed able not only to fine-tune the TF/target ratio to any desired value as a function of the miRNA concentration but also, thanks to the peculiar topology of the circuit, to ensure the stability of this ratio against stochastic fluctuations. These two effects are due to the interplay between the direct transcriptional regulation and the indirect TF/Target interaction due to competition of TF and target for miRNA binding (the so called “sponge effect”). We then perform a genome wide search of these FFLs in the human regulatory network and show that they are characterized by a very peculiar enrichment pattern. In particular, they are strongly enriched in all the situations in which the TF and its target have to be precisely kept at the same concentration notwithstanding the environmental noise. As an example we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and miR-17 family as master regulator. These FFLs ensure a tight control of the E2F/RB ratio which in turns ensures the stability of the transition from the G0/G1 to the S phase in quiescent cells.</p></abstract><abstract abstract-type="summary"><title>Author Summary</title><p>Gene expression is controlled by a complex network of regulatory interactions which may be organized in two complementary subnetworks: the transcriptional one, mediated by Transcription Factors (TF), and the post-transcriptional one, in which a central role is played by microRNAs. In this paper we add a further step in the study of synergistic role of these layers of regulation: a stable fine tuning of the relative expression of target genes is obtained by a combination of transcriptional and post-transcriptional interactions, and such a combination ensures robustness against stochastic fluctuations. We show that optimal fine tuning is reached when the microRNA plays the role of master regulator and one of its targets is a TF which regulates the other microRNA targets. This combination defines a new class of feed-forward loops. We show that such circuitries are strongly enriched when the TF and its targets have to be precisely kept at the same concentration notwithstanding the environmental noise. We complete our analysis with a detailed description, using both deterministic and stochastic equations, of the steady state concentrations of the genes involved in the motifs as a function of the miRNA concentration and of the miRNA-target interaction strength.</p></abstract><funding-group><funding-statement>This work was partially funded by the FSP grant GeneRNet. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement></funding-group><counts><page-count count="12"></page-count></counts></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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