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A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms

To understand cellular coordination of multiple transcriptome regulation mechanisms, we simultaneously measured transcription rate (TR), mRNA abundance (RA) and translation activity (TA). This revealed multiple insights. First, the three parameters displayed systematic statistical differences. Seque...

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Autores principales: Jiang, Wen, Guo, Zhanyong, Lages, Nuno, Zheng, W. Jim, Feliers, Denis, Zhang, Fangyuan, Wang, Degeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5893539/
https://www.ncbi.nlm.nih.gov/pubmed/29636505
http://dx.doi.org/10.1038/s41598-018-24039-1
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author Jiang, Wen
Guo, Zhanyong
Lages, Nuno
Zheng, W. Jim
Feliers, Denis
Zhang, Fangyuan
Wang, Degeng
author_facet Jiang, Wen
Guo, Zhanyong
Lages, Nuno
Zheng, W. Jim
Feliers, Denis
Zhang, Fangyuan
Wang, Degeng
author_sort Jiang, Wen
collection PubMed
description To understand cellular coordination of multiple transcriptome regulation mechanisms, we simultaneously measured transcription rate (TR), mRNA abundance (RA) and translation activity (TA). This revealed multiple insights. First, the three parameters displayed systematic statistical differences. Sequentially more genes exhibited extreme (low or high) expression values from TR to RA, and then to TA; that is, cellular coordination of multiple transcriptome regulatory mechanisms leads to sequentially enhanced gene expression selectivity as the genetic information flow from the genome to the proteome. Second, contribution of the stabilization-by-translation regulatory mechanism to the cellular coordination process was assessed. The data enabled an estimation of mRNA stability, revealing a moderate but significant positive correlation between mRNA stability and translation activity. Third, the proportion of mRNA occupied by un-translated regions (UTR) exhibited a negative relationship with the level of this correlation, and was thus a major determinant of the mode of regulation of the mRNA. High-UTR-proportion mRNAs tend to defy the stabilization-by-translation regulatory mechanism, staying out of the polysome but remaining stable; mRNAs with little UTRs largely followed this regulation. In summary, we quantitatively delineated the relationship among multiple transcriptome regulation parameters, i.e., cellular coordination of corresponding regulatory mechanisms.
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spelling pubmed-58935392018-04-12 A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms Jiang, Wen Guo, Zhanyong Lages, Nuno Zheng, W. Jim Feliers, Denis Zhang, Fangyuan Wang, Degeng Sci Rep Article To understand cellular coordination of multiple transcriptome regulation mechanisms, we simultaneously measured transcription rate (TR), mRNA abundance (RA) and translation activity (TA). This revealed multiple insights. First, the three parameters displayed systematic statistical differences. Sequentially more genes exhibited extreme (low or high) expression values from TR to RA, and then to TA; that is, cellular coordination of multiple transcriptome regulatory mechanisms leads to sequentially enhanced gene expression selectivity as the genetic information flow from the genome to the proteome. Second, contribution of the stabilization-by-translation regulatory mechanism to the cellular coordination process was assessed. The data enabled an estimation of mRNA stability, revealing a moderate but significant positive correlation between mRNA stability and translation activity. Third, the proportion of mRNA occupied by un-translated regions (UTR) exhibited a negative relationship with the level of this correlation, and was thus a major determinant of the mode of regulation of the mRNA. High-UTR-proportion mRNAs tend to defy the stabilization-by-translation regulatory mechanism, staying out of the polysome but remaining stable; mRNAs with little UTRs largely followed this regulation. In summary, we quantitatively delineated the relationship among multiple transcriptome regulation parameters, i.e., cellular coordination of corresponding regulatory mechanisms. Nature Publishing Group UK 2018-04-10 /pmc/articles/PMC5893539/ /pubmed/29636505 http://dx.doi.org/10.1038/s41598-018-24039-1 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
Jiang, Wen
Guo, Zhanyong
Lages, Nuno
Zheng, W. Jim
Feliers, Denis
Zhang, Fangyuan
Wang, Degeng
A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms
title A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms
title_full A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms
title_fullStr A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms
title_full_unstemmed A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms
title_short A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms
title_sort multi-parameter analysis of cellular coordination of major transcriptome regulation mechanisms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5893539/
https://www.ncbi.nlm.nih.gov/pubmed/29636505
http://dx.doi.org/10.1038/s41598-018-24039-1
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