alternative ORFs; alternative proteins; database; multicoding; precision medicine; proteogenomics; variants; Proteins; Peptides; Humans; Databases, Protein; Open Reading Frames; Peptides/genetics; Peptides/analysis; Proteomics/methods; Proteins/genetics; Chemistry (all); Biochemistry; General Chemistry
Abstract :
[en] Proteomic diversity in biological samples can be characterized by mass spectrometry (MS)-based proteomics using customized protein databases generated from sets of transcripts previously detected by RNA-seq. This diversity has only been increased by the recent discovery that many translated alternative open reading frames rest unannotated at unsuspected locations of mRNAs and ncRNAs. These novel protein products, termed alternative proteins, have been left out of all previous custom database generation tools. Consequently, genetic variations that impact alternative open reading frames and variant peptides from their translated proteins are not detectable with current computational workflows. To fill this gap, we present OpenCustomDB, a bioinformatics tool that uses sample-specific RNaseq data to identify genomic variants in canonical and alternative open reading frames, allowing for more than one coding region per transcript. In a test reanalysis of a cohort of 16 patients with acute myeloid leukemia, 5666 peptides from alternative proteins were detected, including 201 variant peptides. We also observed that a significant fraction of peptide-spectrum matches previously assigned to peptides from canonical proteins got better scores when reassigned to peptides from alternative proteins. Custom protein libraries that include sample-specific sequence variations of all possible open reading frames are promising contributions to the development of proteomics and precision medicine. The raw and processed proteomics data presented in this study can be found in PRIDE repository with accession number PXD029240.
Disciplines :
Biochemistry, biophysics & molecular biology
Author, co-author :
Guilloy, Noé; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, Québec J1E 4K8, Canada ; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Montreal, Québec H2X 3Y7, Canada
Brunet, Marie A; Department of Pediatrics, Université de Sherbrooke, Sherbrooke, Québec J1E 4K8, Canada
Leblanc, Sébastien; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, Québec J1E 4K8, Canada ; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Montreal, Québec H2X 3Y7, Canada
Jacques, Jean-François; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, Québec J1E 4K8, Canada ; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Montreal, Québec H2X 3Y7, Canada
Hardy, Marie-Pierre; Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Québec H3C 3J7, Canada
Ehx, Grégory ; Université de Liège - ULiège > Département des sciences cliniques
Lanoix, Joël; Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Québec H3C 3J7, Canada
Thibault, Pierre ; Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Québec H3C 3J7, Canada
Perreault, Claude ; Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Québec H3C 3J7, Canada ; Department of Medicine, Université de Montréal, Montreal, Québec H3C 3J7, Canada
Roucou, Xavier ; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, Québec J1E 4K8, Canada ; PROTEO, Quebec Network for Research on Protein Function, Structure, and Engineering, Montreal, Québec H2X 3Y7, Canada
Language :
English
Title :
OpenCustomDB: Integration of Unannotated Open Reading Frames and Genetic Variants to Generate More Comprehensive Customized Protein Databases.
CIHR - Canadian Institutes of Health Research FRQS - Fonds de Recherche du Québec - Santé UdeM - Université de Montréal LLSC - Leukemia and Lymphoma Society of Canada Canadian Cancer Society
Funding text :
Computing resources from Digital Research Alliance of Canada are gratefully acknowledged. We thank Raphaelle Lambert and Jennifer Huber at the genomics facility for RNA-seq, Patrick Gendron, Eric Audemard, and Genevieve Boucher at the bioinformatic platform for assistance with RNA-seq analysis, the Institute for Research in Immunology and Cancer of the Université de Montréal. We acknowledge the work of Claude Rondeau and all members of the Quebec Leukemia Cell Bank. This work was supported by a grant from the Canadian Institutes of Health Research (CIHR, PJT-175322) to X.R. M.A.B., a Canada research chair to X.R., a grant from the Canadian Cancer Society (705604) to C.P. and P.T., a grant from the Leukemia and Lymphoma Society of Canada to C.P. and a grant from The Oncopole to C.P., P.T., and X.R. M.A.B. is a Junior 1 research fellow from the Fonds de Recherche du Québec–Santé. G.E. is supported by postdoctoral fellowships from the Institute for Research in Immunology and Cancer of the Université de Montréal, the Fonds de Recherche du Québec–Santé, and the Cole Foundation. Operation of the mp2 supercomputer is funded by the Canada Foundation of Innovation (CFI), le ministère de l’Économie, de la science et de l’innovation du Québec (MESI), and les Fonds de Recherche du Québec.
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