title: Bayesian prediction of RNA translation from ribosome profiling.
abstract: Ribosome profiling via high-throughput sequencing (ribo-seq) is a promising new technique for characterizing the occupancy of ribosomes on messenger RNA (mRNA) at base-pair resolution. The ribosome is responsible for translating mRNA into proteins, so information about its occupancy offers a detailed view of ribosome density and position which could be used to discover new translated open reading frames (ORFs), among other things. In this work, we propose Rp-Bp, an unsupervised Bayesian approach to predict translated ORFs from ribosome profiles. We use state-of-the-art Markov chain Monte Carlo techniques to estimate posterior distributions of the likelihood of translation of each ORF. Hence, an important feature of Rp-Bp is its ability to incorporate and propagate uncertainty in the prediction process. A second novel contribution is automatic Bayesian selection of read lengths and ribosome P-site offsets (BPPS). We empirically demonstrate that our read length selection technique modestly improves sensitivity by identifying more canonical and non-canonical ORFs. Proteomics- and quantitative translation initiation sequencing-based validation verifies the high quality of all of the predictions. Experimental comparison shows that Rp-Bp results in more peptide identifications and proteomics-validated ORF predictions compared to another recent tool for translation prediction.
authors.affiliation: Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III and Klaus Tschira Institute for Integrative Computational Cardiology, University of Heidelberg, 69120 Heidelberg, Germany.|DZHK (German Centre for Cardiovascular Research), Partner site Heidelberg/Mannheim, 69120 Heidelberg, Germany.
authors.forename: Brandon
authors.initials: B
authors.lastname: Malone
authors.affiliation: Max Plank Institute for the Biology of Ageing, 50931 Köln, Germany.
authors.forename: Ilian
authors.initials: I
authors.lastname: Atanassov
authors.affiliation: Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland.|Faculty of Science, University of Basel, 4056 Basel, Switzerland.
authors.forename: Florian
authors.initials: F
authors.lastname: Aeschimann
authors.affiliation: Max Plank Institute for the Biology of Ageing, 50931 Köln, Germany.
authors.forename: Xinping
authors.initials: X
authors.lastname: Li
authors.affiliation: Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland.
authors.forename: Helge
authors.initials: H
authors.lastname: Großhans
authors.affiliation: Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III and Klaus Tschira Institute for Integrative Computational Cardiology, University of Heidelberg, 69120 Heidelberg, Germany.|DZHK (German Centre for Cardiovascular Research), Partner site Heidelberg/Mannheim, 69120 Heidelberg, Germany.
authors.forename: Christoph
authors.initials: C
authors.lastname: Dieterich
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D017173:Caenorhabditis elegans / Q000235:genetics; D003198:Computer Simulation; D057809:HEK293 Cells; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D051379:Mice; D016366:Open Reading Frames; D010455:Peptides / Q000737:chemistry; D014176:Protein Biosynthesis; D040901:Proteomics; D012270:Ribosomes / Q000737:chemistry* / Q000378:metabolism; D017423:Sequence Analysis, RNA / Q000379:methods*
chemical_list: D010455:Peptides