title: PROTEOFORMER: deep proteome coverage through ribosome profiling and MS integration.
abstract: An increasing amount of studies integrate mRNA sequencing data into MS-based proteomics to complement the translation product search space. However, several factors, including extensive regulation of mRNA translation and the need for three- or six-frame-translation, impede the use of mRNA-seq data for the construction of a protein sequence search database. With that in mind, we developed the PROTEOFORMER tool that automatically processes data of the recently developed ribosome profiling method (sequencing of ribosome-protected mRNA fragments), resulting in genome-wide visualization of ribosome occupancy. Our tool also includes a translation initiation site calling algorithm allowing the delineation of the open reading frames (ORFs) of all translation products. A complete protein synthesis-based sequence database can thus be compiled for mass spectrometry-based identification. This approach increases the overall protein identification rates with 3% and 11% (improved and new identifications) for human and mouse, respectively, and enables proteome-wide detection of 5'-extended proteoforms, upstream ORF translation and near-cognate translation start sites. The PROTEOFORMER tool is available as a stand-alone pipeline and has been implemented in the galaxy framework for ease of use.
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
authors.forename: Jeroen
authors.initials: J
authors.lastname: Crappé
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium Department of Medical Protein Research, Flemish Institute of Biotechnology, Ghent, Belgium Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
authors.forename: Elvis
authors.initials: E
authors.lastname: Ndah
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
authors.forename: Alexander
authors.initials: A
authors.lastname: Koch
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
authors.forename: Sandra
authors.initials: S
authors.lastname: Steyaert
authors.affiliation: Department of Medical Protein Research, Flemish Institute of Biotechnology, Ghent, Belgium Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
authors.forename: Daria
authors.initials: D
authors.lastname: Gawron
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
authors.forename: Sarah
authors.initials: S
authors.lastname: De Keulenaer
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
authors.forename: Ellen
authors.initials: E
authors.lastname: De Meester
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
authors.forename: Tim
authors.initials: T
authors.lastname: De Meyer
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium.
authors.forename: Wim
authors.initials: W
authors.lastname: Van Criekinge
authors.affiliation: Department of Medical Protein Research, Flemish Institute of Biotechnology, Ghent, Belgium Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
authors.forename: Petra
authors.initials: P
authors.lastname: Van Damme
authors.affiliation: Lab of Bioinformatics and Computational Genomics, Department of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium gerben.menschaert@ugent.be.
authors.forename: Gerben
authors.initials: G
authors.lastname: Menschaert
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D002478:Cells, Cultured; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D016678:Genome / Q000235:genetics; D045325:HCT116 Cells; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D051379:Mice; D008969:Molecular Sequence Data; D016366:Open Reading Frames / Q000235:genetics; D014176:Protein Biosynthesis / Q000235:genetics; D020543:Proteome / Q000235:genetics / Q000378:metabolism*; D040901:Proteomics / Q000379:methods*; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D012270:Ribosomes / Q000235:genetics / Q000378:metabolism*; D017386:Sequence Homology, Amino Acid
chemical_list: D020543:Proteome; D012333:RNA, Messenger