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

By Lorenzo Calviello, Neelanjan Mukherjee, Emanuel Wyler, Henrik Zauber, Antje Hirsekorn, Matthias Selbach, Markus Landthaler, Benedikt Obermayer, Uwe Ohler

Posted 13 Nov 2015
bioRxiv DOI: 10.1101/031625 (published DOI: 10.1038/nmeth.3688)

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.

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