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Predicting the impact of promoter variability on regulatory outputs

The increased availability of whole genome sequences calls for quantitative models of global gene expression, yet predicting gene expression patterns directly from genome sequence remains a challenge. We examine the contributions of an individual regulator, the ferrous iron-responsive regulatory ele...

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Detalles Bibliográficos
Autores principales: Kreamer, Naomi N., Phillips, Rob, Newman, Dianne K., Boedicker, James Q.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682146/
https://www.ncbi.nlm.nih.gov/pubmed/26675057
http://dx.doi.org/10.1038/srep18238
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author Kreamer, Naomi N.
Phillips, Rob
Newman, Dianne K.
Boedicker, James Q.
author_facet Kreamer, Naomi N.
Phillips, Rob
Newman, Dianne K.
Boedicker, James Q.
author_sort Kreamer, Naomi N.
collection PubMed
description The increased availability of whole genome sequences calls for quantitative models of global gene expression, yet predicting gene expression patterns directly from genome sequence remains a challenge. We examine the contributions of an individual regulator, the ferrous iron-responsive regulatory element, BqsR, on global patterns of gene expression in Pseudomonas aeruginosa. The position weight matrix (PWM) derived for BqsR uncovered hundreds of likely binding sites throughout the genome. Only a subset of these potential binding sites had a regulatory consequence, suggesting that BqsR/DNA interactions were not captured within the PWM or that the broader regulatory context at each promoter played a greater role in setting promoter outputs. The architecture of the BqsR operator was systematically varied to understand how binding site parameters influence expression. We found that BqsR operator affinity was predicted by the PWM well. At many promoters the surrounding regulatory context, including overlapping operators of BqsR or the presence of RhlR binding sites, were influential in setting promoter outputs. These results indicate more comprehensive models that include local regulatory contexts are needed to develop a predictive understanding of global regulatory outputs.
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spelling pubmed-46821462015-12-18 Predicting the impact of promoter variability on regulatory outputs Kreamer, Naomi N. Phillips, Rob Newman, Dianne K. Boedicker, James Q. Sci Rep Article The increased availability of whole genome sequences calls for quantitative models of global gene expression, yet predicting gene expression patterns directly from genome sequence remains a challenge. We examine the contributions of an individual regulator, the ferrous iron-responsive regulatory element, BqsR, on global patterns of gene expression in Pseudomonas aeruginosa. The position weight matrix (PWM) derived for BqsR uncovered hundreds of likely binding sites throughout the genome. Only a subset of these potential binding sites had a regulatory consequence, suggesting that BqsR/DNA interactions were not captured within the PWM or that the broader regulatory context at each promoter played a greater role in setting promoter outputs. The architecture of the BqsR operator was systematically varied to understand how binding site parameters influence expression. We found that BqsR operator affinity was predicted by the PWM well. At many promoters the surrounding regulatory context, including overlapping operators of BqsR or the presence of RhlR binding sites, were influential in setting promoter outputs. These results indicate more comprehensive models that include local regulatory contexts are needed to develop a predictive understanding of global regulatory outputs. Nature Publishing Group 2015-12-17 /pmc/articles/PMC4682146/ /pubmed/26675057 http://dx.doi.org/10.1038/srep18238 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Kreamer, Naomi N.
Phillips, Rob
Newman, Dianne K.
Boedicker, James Q.
Predicting the impact of promoter variability on regulatory outputs
title Predicting the impact of promoter variability on regulatory outputs
title_full Predicting the impact of promoter variability on regulatory outputs
title_fullStr Predicting the impact of promoter variability on regulatory outputs
title_full_unstemmed Predicting the impact of promoter variability on regulatory outputs
title_short Predicting the impact of promoter variability on regulatory outputs
title_sort predicting the impact of promoter variability on regulatory outputs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682146/
https://www.ncbi.nlm.nih.gov/pubmed/26675057
http://dx.doi.org/10.1038/srep18238
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