Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1782405846215426048 |
---|---|
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. |
format | Online Article Text |
id | pubmed-4682146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT kreamernaomin predictingtheimpactofpromotervariabilityonregulatoryoutputs AT phillipsrob predictingtheimpactofpromotervariabilityonregulatoryoutputs AT newmandiannek predictingtheimpactofpromotervariabilityonregulatoryoutputs AT boedickerjamesq predictingtheimpactofpromotervariabilityonregulatoryoutputs |