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The Escherichia coli transcriptome mostly consists of independently regulated modules
Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse comp...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892915/ https://www.ncbi.nlm.nih.gov/pubmed/31797920 http://dx.doi.org/10.1038/s41467-019-13483-w |
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author | Sastry, Anand V. Gao, Ye Szubin, Richard Hefner, Ying Xu, Sibei Kim, Donghyuk Choudhary, Kumari Sonal Yang, Laurence King, Zachary A. Palsson, Bernhard O. |
author_facet | Sastry, Anand V. Gao, Ye Szubin, Richard Hefner, Ying Xu, Sibei Kim, Donghyuk Choudhary, Kumari Sonal Yang, Laurence King, Zachary A. Palsson, Bernhard O. |
author_sort | Sastry, Anand V. |
collection | PubMed |
description | Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome. |
format | Online Article Text |
id | pubmed-6892915 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68929152019-12-06 The Escherichia coli transcriptome mostly consists of independently regulated modules Sastry, Anand V. Gao, Ye Szubin, Richard Hefner, Ying Xu, Sibei Kim, Donghyuk Choudhary, Kumari Sonal Yang, Laurence King, Zachary A. Palsson, Bernhard O. Nat Commun Article Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome. Nature Publishing Group UK 2019-12-04 /pmc/articles/PMC6892915/ /pubmed/31797920 http://dx.doi.org/10.1038/s41467-019-13483-w Text en © The Author(s) 2019 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 Sastry, Anand V. Gao, Ye Szubin, Richard Hefner, Ying Xu, Sibei Kim, Donghyuk Choudhary, Kumari Sonal Yang, Laurence King, Zachary A. Palsson, Bernhard O. The Escherichia coli transcriptome mostly consists of independently regulated modules |
title | The Escherichia coli transcriptome mostly consists of independently regulated modules |
title_full | The Escherichia coli transcriptome mostly consists of independently regulated modules |
title_fullStr | The Escherichia coli transcriptome mostly consists of independently regulated modules |
title_full_unstemmed | The Escherichia coli transcriptome mostly consists of independently regulated modules |
title_short | The Escherichia coli transcriptome mostly consists of independently regulated modules |
title_sort | escherichia coli transcriptome mostly consists of independently regulated modules |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892915/ https://www.ncbi.nlm.nih.gov/pubmed/31797920 http://dx.doi.org/10.1038/s41467-019-13483-w |
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