Abstract

BackgroundHistone epigenome data determined by chromatin immunoprecipitation sequencing (ChIP-seq) is used in identifying transcript regions and estimating expression levels. However, this estimation does not always correlate with eventual RNA expression levels measured by RNA sequencing (RNA-seq). Part of the inconsistency may arise from the variance in RNA stability, where the transcripts that are more or less abundant than predicted RNA expression from histone epigenome data are inferred to be more or less stable. However, there is little systematic analysis to validate this assumption. Here, we used stability data of whole transcriptome measured by 5′-bromouridine immunoprecipitation chase sequencing (BRIC-seq), which enabled us to determine the half-lives of whole transcripts including lincRNAs, and we integrated BRIC-seq with ChIP-seq to achieve better estimation of the eventual transcript levels and to understand the importance of post-transcriptional regulation that determine the eventual transcript levels.ResultsWe identified discrepancies between the RNA abundance estimated by ChIP-seq and measured RNA expression from RNA-seq; for number of genes and estimated that the expression level of 865 genes was controlled at the level of RNA stability in HeLa cells. ENCODE data analysis supported the idea that RNA stability control aids to determine transcript levels in multiple cell types. We identified UPF1, EXOSC5 and STAU1, well-studied RNA degradation factors, as controlling factors for 8% of cases. Computational simulations reasonably explained the changes of eventual mRNA levels attributable to the changes in the rates of mRNA half-lives. In addition, we propose a feedback circuit that includes the regulated degradation of mRNAs encoding transcription factors to maintain the steady state level of RNA abundance. Intriguingly, these regulatory mechanisms were distinct between mRNAs and lincRNAs.ConclusionsIntegrative analysis of ChIP-seq, RNA-seq and our BRIC-seq showed that transcriptional regulation and RNA degradation are independently regulated. In addition, RNA stability is an important determinant of eventual transcript levels. RNA binding proteins, such as UPF1, STAU1 and EXOSC5 may play active roles in such controls.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1358-y) contains supplementary material, which is available to authorized users.

Highlights

  • Histone epigenome data determined by chromatin immunoprecipitation sequencing (ChIP-seq) is used in identifying transcript regions and estimating expression levels

  • Correlation between Chromatin immunoprecipitation (ChIP)-seq and RNA sequencing (RNA-seq) data First we analyzed the relationship between levels of the transcripts and the strength of active chromatin marks by performing ChIP-seq analysis of Histone H3 tri-methylated lysine 4 (H3K4me3) and pol RNA polymerase II RNA (II) on the Illumina HiSeq2000 platform

  • In the cases where the peaks were not identified, the ChIP-seq tags were mostly at the noise level; if peaks were identified, we associated the signal intensities of ChIP-seq of H3K4me3 and RNA-seq gene expression levels to the gene

Read more

Summary

Introduction

Histone epigenome data determined by chromatin immunoprecipitation sequencing (ChIP-seq) is used in identifying transcript regions and estimating expression levels. This estimation does not always correlate with eventual RNA expression levels measured by RNA sequencing (RNA-seq). Transcription initiation is regulated by Maekawa et al BMC Genomics (2015) 16:154 active regions and estimation of transcript levels in a given cell at a given state [4] This partly reflects the fact that advances in generation sequencing have enabled easy characterization of the sites bound by H3K4me sites using chromatin immunoprecipitation sequencing (ChIP-seq) [5]. It is evident that ChIP-seq data is not sufficient enough to model the steady-state RNA expression levels for a number of genes, and regulatory mechanisms other than transcription initiation needs to be considered to understand the RNA expression

Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.