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A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity

MicroRNAs (miRNAs) regulate a majority of protein-coding genes, affecting nearly all biological pathways. However, the quantitative dimensions of miRNA-based regulation are not fully understood. In particular, the implications of miRNA target site location, composition rules for multiple target site...

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Autores principales: Gam, Jeremy J., Babb, Jonathan, Weiss, Ron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6014984/
https://www.ncbi.nlm.nih.gov/pubmed/29934631
http://dx.doi.org/10.1038/s41467-018-04575-0
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author Gam, Jeremy J.
Babb, Jonathan
Weiss, Ron
author_facet Gam, Jeremy J.
Babb, Jonathan
Weiss, Ron
author_sort Gam, Jeremy J.
collection PubMed
description MicroRNAs (miRNAs) regulate a majority of protein-coding genes, affecting nearly all biological pathways. However, the quantitative dimensions of miRNA-based regulation are not fully understood. In particular, the implications of miRNA target site location, composition rules for multiple target sites, and cooperativity limits for genes regulated by many miRNAs have not been quantitatively characterized. We explore these aspects of miRNA biology at a quantitative single-cell level using a library of 620 miRNA sensors and reporters that are regulated by many miRNA target sites at different positions. Interestingly, we find that miRNA target site sets within the same untranslated region exhibit combined miRNA activity described by an antagonistic relationship while those in separate untranslated regions show synergy. The resulting antagonistic/synergistic computational model enables the high-fidelity prediction of miRNA sensor activity for sensors containing many miRNA targets. These findings may help to accelerate the development of sophisticated sensors for clinical and research applications.
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spelling pubmed-60149842018-06-25 A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity Gam, Jeremy J. Babb, Jonathan Weiss, Ron Nat Commun Article MicroRNAs (miRNAs) regulate a majority of protein-coding genes, affecting nearly all biological pathways. However, the quantitative dimensions of miRNA-based regulation are not fully understood. In particular, the implications of miRNA target site location, composition rules for multiple target sites, and cooperativity limits for genes regulated by many miRNAs have not been quantitatively characterized. We explore these aspects of miRNA biology at a quantitative single-cell level using a library of 620 miRNA sensors and reporters that are regulated by many miRNA target sites at different positions. Interestingly, we find that miRNA target site sets within the same untranslated region exhibit combined miRNA activity described by an antagonistic relationship while those in separate untranslated regions show synergy. The resulting antagonistic/synergistic computational model enables the high-fidelity prediction of miRNA sensor activity for sensors containing many miRNA targets. These findings may help to accelerate the development of sophisticated sensors for clinical and research applications. Nature Publishing Group UK 2018-06-22 /pmc/articles/PMC6014984/ /pubmed/29934631 http://dx.doi.org/10.1038/s41467-018-04575-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Gam, Jeremy J.
Babb, Jonathan
Weiss, Ron
A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity
title A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity
title_full A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity
title_fullStr A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity
title_full_unstemmed A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity
title_short A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity
title_sort mixed antagonistic/synergistic mirna repression model enables accurate predictions of multi-input mirna sensor activity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6014984/
https://www.ncbi.nlm.nih.gov/pubmed/29934631
http://dx.doi.org/10.1038/s41467-018-04575-0
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