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Journal Article

Differential protein occupancy profiling of the mRNA transcriptome

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Dieterich,  C.
Dieterich – Computational RNA Biology and Ageing, Research Groups, Max Planck Institute for Biology of Ageing, Max Planck Society;

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Citation

Schueler, M., Munschauer, M., Gregersen, L. H., Finzel, A., Loewer, A., Chen, W., et al. (2014). Differential protein occupancy profiling of the mRNA transcriptome. Genome Biol, 15(1), R15. doi:10.1186/gb-2014-15-1-r15.


Cite as: https://hdl.handle.net/21.11116/0000-000B-7222-E
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.