The determination of whether a gene is protein coding or not is a key goal of genome annotation projects. Peptide mass spectrometry is a powerful tool for detecting cellular expression of proteins and therefore is an attractive approach for verifying the protein coding potential of genes. However, a range of technical difficulties limit the coverage from proteomics experiments, with the highest recorded coverage of the human proteome being approximately 50\% of human genes . Here we map the peptides detected in 7 large-scale proteomics studies to the GENCODE v12 annotation of the human genome and identify almost 60\% of the protein coding genes  . We find that there are surprisingly strong correlations between peptide detection and cross-species conservation, gene age and the presence of protein-like features. The age of the gene  and its conservation across vertebrate species are key indicators of whether a peptide will be detected in proteomics experiments. We find peptides for most highly conserved genes and for practically all genes that evolved before bilateria. At the same time there is little or no evidence for protein expression for genes that have appeared since primates or that do not have any protein-like features or conservation. Based on our results we describe a set of 2,001 genes that have no protein features and poor conservation, or have ambiguous annotations in gene or protein databases. We suggest that many of the genes that lack supporting evidence and that are not detected in proteomics experiments, do not code for proteins under normal circumstances and that they should not be included in the human protein coding gene catalogue.
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 experiments . Here we map the peptides detected in 7 large-scale proteomics studies to almost 60\% of the protein coding genes in the GENCODE annotation the human genome . We find the age of the gene family and its conservation across vertebrate species are key indicators of whether a peptide will be detected in proteomics experiments. We find peptides for most highly conserved genes and for practically all genes that evolved before bilateria. At the same time there is little or no evidence of protein expression for novel genes, those that have appeared since primates , or genes that do not have any protein-like features or cross-species conservation. We identify 19 non-protein like features such as weak conservation, no protein-like features or ambiguous annotations in the major databases that are indicators of low peptide detection rates. We use these features to describe a set of 2,001 genes that are potentially non-coding, and show that many of these genes behave more like non-coding genes than protein-coding genes. We detect peptides for just 3\% of these genes. We suggest that many of these 2,001 genes do not code for proteins under normal circumstances and that they should not be included in the human protein coding gene catalogue.
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projects. Peptide mass spectrometry is a powerful tool for detecting cellular expression of proteins and therefore is an attractive approach for verifying the
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of genes. However, a range of technical difficulties limit the coverage from proteomics experiments, with the highest recorded coverage of the human proteome being approximately 50\% of human genes
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the GENCODE v12 annotation of the human genome and identify
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that there are surprisingly strong correlations between peptide detection and cross-species conservation, gene age and the presence of protein-like features. The
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conservation. Based on our results we
cross-species conservation. We identify 19 non-protein like features such as weak conservation, no protein-like features or ambiguous annotations in the major databases that are indicators of low peptide detection rates. We use these features to
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have no protein features and poor conservation, or have ambiguous annotations in gene or protein databases. We
are potentially non-coding, and show that many of these genes behave more like non-coding genes than protein-coding genes. We detect peptides for just 3\% of these genes. We
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the genes that lack supporting evidence and that are not detected in proteomics experiments,
these 2,001 genes