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Differential protein occupancy profiling of the mRNA transcriptome

Markus Schueler1, Mathias Munschauer1, Lea Haarup Gregersen1, Ana Finzel1, Alexander Loewer1, Wei Chen1, Markus Landthaler1* and Christoph Dieterich12*

Author Affiliations

1 Max-Delbrück-Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, 13125 Berlin, Germany

2 Current address: Max Planck Institute for Biology of Ageing, 50931 Cologne, Germany

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Genome Biology 2014, 15:R15  doi:10.1186/gb-2014-15-1-r15

Published: 13 January 2014

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 mRNA 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′ 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.