title: Multiple evidence strands suggest that there may be as few as 19,000 human protein-coding genes.
abstract: Determining the full complement of protein-coding genes is a key goal of genome annotation. The most powerful approach for confirming protein-coding potential is the detection of cellular protein expression through peptide mass spectrometry (MS) experiments. Here, we mapped peptides detected in seven large-scale proteomics studies to almost 60% of the protein-coding genes in the GENCODE annotation of the human genome. We found a strong relationship between detection in proteomics experiments and both gene family age and cross-species conservation. Most of the genes for which we detected peptides were highly conserved. We found peptides for >96% of genes that evolved before bilateria. At the opposite end of the scale, we identified almost no peptides for genes that have appeared since primates, for genes that did not have any protein-like features or for genes with poor cross-species conservation. These results motivated us to describe a set of 2001 potential non-coding genes based on features such as weak conservation, a lack of protein features, or ambiguous annotations from major databases, all of which correlated with low peptide detection across the seven experiments. We identified peptides for just 3% of these genes. We show that many of these genes behave more like non-coding genes than protein-coding genes and suggest that most are unlikely to code for proteins under normal circumstances. We believe that their inclusion in the human protein-coding gene catalogue should be revised as part of the ongoing human genome annotation effort.
authors.affiliation: Unidad de Proteómica and.
authors.forename: Iakes
authors.initials: I
authors.lastname: Ezkurdia
authors.affiliation: Structural Biology and Bioinformatics Programme and.
authors.forename: David
authors.initials: D
authors.lastname: Juan
authors.affiliation: National Bioinformatics Institute (INB), Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro, 3, 28029, Madrid, Spain.
authors.forename: Jose Manuel
authors.initials: JM
authors.lastname: Rodriguez
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Trust Campus, Hinxton, Cambridge CB10 1SA, UK and.
authors.forename: Adam
authors.initials: A
authors.lastname: Frankish
authors.affiliation: Center for Biomolecular Science and Engineering, School of Engineering, University of California Santa Cruz (UCSC), 1156 High Street, Santa Cruz, CA 95064, USA.
authors.forename: Mark
authors.initials: M
authors.lastname: Diekhans
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Trust Campus, Hinxton, Cambridge CB10 1SA, UK and.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Harrow
authors.affiliation: Laboratorio de Proteómica Cardiovascular, Centro Nacional de Investigaciones Cardiovasculares, CNIC, Melchor Fernández Almagro, 3, 28029, Madrid, Spain.
authors.forename: Jesus
authors.initials: J
authors.lastname: Vazquez
authors.affiliation: Structural Biology and Bioinformatics Programme and, National Bioinformatics Institute (INB), Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro, 3, 28029, Madrid, Spain, mtress@cnio.es valencia@cnio.es.
authors.forename: Alfonso
authors.initials: A
authors.lastname: Valencia
authors.affiliation: Structural Biology and Bioinformatics Programme and, mtress@cnio.es valencia@cnio.es.
authors.forename: Michael L
authors.initials: ML
authors.lastname: Tress
mesh_terms: D019295:Computational Biology; D015894:Genome, Human; D006801:Humans; D016366:Open Reading Frames; D010455:Peptides / Q000235:genetics; D011506:Proteins / Q000235:genetics* / Q000378:metabolism; D040901:Proteomics
chemical_list: D010455:Peptides; D011506:Proteins