Chromatin measurements reveal contributions of synthesis and decay to steady‐state mRNA levels

Molecular Systems Biology

Sylvia C Tippmann³  Robert Ivanek³  Dimos Gaidatzis³  Anne Schöler³  Leslie Hoerner³  Erik van Nimwegen²  Peter F Stadler¹  Michael B Stadler³ 

[1] Department of Theoretical Chemistry, University of Vienna, Wien, Austria;Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, Basel, Switzerland;Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland

关键词: chromatin;    histone modifications;    microRNA;    RNA decay;    transcriptional regulation;   

DOI  :  10.1038/msb.2012.23

来源: Wiley

【 摘 要 】

Abstract

Messenger RNA levels in eukaryotes are controlled by multiple consecutive regulatory processes, which can be classified into two layers: primary transcriptional regulation at the chromosomal level and secondary, co- and post-transcriptional regulation of the mRNA. To identify the individual contribution of these layers to steady-state RNA levels requires separate quantification. Using mouse as a model organism, we show that chromatin features are sufficient to model RNA levels but with different sensitivities in dividing versus postmitotic cells. In both cases, chromatin-derived transcription rates explain over 80% of the observed variance in measured RNA levels. Further inclusion of measurements of mRNA half-life and microRNA expression data enabled the identification of a low quantitative contribution of RNA decay by either microRNA or general differential turnover to final mRNA levels. Together, this establishes a chromatin-based quantitative model for the contribution of transcriptional and post-transcriptional processes to steady-state levels of messenger RNA.

Synopsis

Histone modification, polymerase binding, mRNA half-life, and miRNA abundance measurements in mouse cells are used to dissect the relative contribution of each to mRNA levels, revealing control primarily at the level of transcription, with minor contributions from post-transcriptional processes.

• A linear model of three histone modifications and RNAP II occupancy can predict >80% of the variance in mRNA levels.
• mRNA half-life explains an additional 1.4% variance in mRNA levels.
• miRNA-mediated silencing does not explain any variance on a genome-wide scale.
• H3K36me3 has different predictive power in dividing and non-dividingcells.

【 授权许可】

CC BY-NC-ND   
Copyright © 2012 EMBO and Macmillan Publishers Limited

Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.