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Differential protein occupancy profiling of the mRNA transcriptome

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Item Type:Article
Title:Differential protein occupancy profiling of the mRNA transcriptome
Creators Name:Schueler, M. and Munschauer, M. and Gregersen, L.H. and Finzel, A. and Loewer, A. and Chen, W. and Landthaler, M. and Dieterich, C.
Abstract:BACKGROUND: RNA-binding proteins (RBPs) mediate mRNA biogenesis, translation and decay. We recently developed an approach to profile transcriptome-wide RBP contacts on polyadenylated transcripts by next-generation sequencing. A comparison of such profiles from different biological conditions has the power to unravel dynamic changes in protein-contacted cis-regulatory mRNAs regions without a priori knowledge of the regulatory protein component. RESULTS: We compared protein occupancy profiles of polyadenylated transcripts in MCF7 and HEK293 cells. Briefly, we developed a bioinformatics workflow to identify differential crosslinking sites in cDNA reads of 4-thiouridine crosslinked polyadenylated RNA samples. We identified 30,000 differential crosslinking sites between MCF7 and HEK293 cells at an estimated false-discovery rate of 10%. 73% of all reported differential protein-RNA contact sites cannot be explained by local changes in exon usage as indicated by complementary RNA-seq data. The majority of differentially crosslinked positions are located in 3[prime] UTRs, show distinct secondary-structure characteristics and overlap with binding sites of known RBPs, such as ELAVL1. Importantly, mRNA transcripts with the most significant occupancy changes show elongated mRNA half-lives in MCF7 cells. CONCLUSIONS: We present a global comparison of protein occupancy profiles from different cell types, and provide evidence for altered mRNA metabolism as a result of differential protein-RNA contacts. Additionally, we introduce POPPI, a bioinformatics workflow for the analysis of protein occupancy profiling experiments. Our work demonstrates the value of protein occupancy profiling for assessing cis-regulatory RNA sequence space and its dynamics in growth, development and disease.
Keywords:Computational Biology, Gene Expression Regulation, Genetic Transcription, HEK293 Cells, High-Throughput Nucleotide Sequencing, MCF-7 Cells, Messenger RNA, RNA-Binding Proteins, RNA Sequence Analysis, Transcriptome
Source:Genome Biology
ISSN:1465-6906
Publisher:BioMed Central
Volume:15
Number:1
Page Range:R15
Date:13 January 2014
Official Publication:https://doi.org/10.1186/gb-2014-15-1-r15
PubMed:View item in PubMed

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