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A spectral analysis approach to detect actively translated open reading frames in high-resolution ribosome profiling data

Item Type:Preprint
Title:A spectral analysis approach to detect actively translated open reading frames in high-resolution ribosome profiling data
Creators Name:Calviello, L. and Mukherjee, N. and Wyler, E. and Zauber, H. and Hirsekorn, A. and Selbach, M. and Landthaler, M. and Obermayer, B. and Ohler, U.
Abstract:RNA sequencing protocols allow for quantifying gene expression regulation at each individual step, from transcription to protein synthesis. Ribosome Profiling (Ribo-seq) maps the positions of translating ribosomes over the entire transcriptome. Despite its great potential, a rigorous statistical approach to identify translated regions by means of the characteristic three-nucleotide periodicity of Ribo-seq data is not yet available. To fill this gap, we developed RiboTaper, which quantifies the significance of periodic Ribo-seq reads via spectral analysis methods. We applied RiboTaper on newly generated, deep Ribo-seq data in HEK293 cells, to derive an extensive map of translation that covers Open Reading Frame (ORF) annotations for more than 11,000 protein- coding genes. We also find distinct ribosomal signatures for several hundred detected upstream ORFs and ORFs in annotated non-coding genes (ncORFs). Mass spectrometry data confirms that RiboTaper achieves excellent coverage of the cellular proteome and validates dozens of novel peptide products. Collectively, RiboTaper (available at https://ohlerlab.mdc-berlin.de/software/ ) is a powerful method for comprehensive de novo identification of actively used ORFs in the human genome.
Source:bioRxiv
Publisher:Cold Spring Habor Laboratory (U.S.A.)
Article Number:031625
Date:13 November 2015
Official Publication:https://doi.org/10.1101/031625
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https://edoc.mdc-berlin.de/15245/Final version

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