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Most non-canonical proteins uniquely populate the proteome or immunopeptidome.

ABSTRACT: Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated as efficiently as canonical proteins, have more predicted disordered residues and lower stability, and critically generate MHC-I peptides 5-fold more efficiently per translation event. Translating 5' "untranslated" regions hinders downstream translation of genes involved in transcription, translation, and antiviral responses. Novel protein isoforms show strong enrichment for signaling pathways deregulated in cancer. Only a small fraction of cryptic proteins detected in the proteome contribute to the MHC-I immunopeptidome, demonstrating the high preferential access of cryptic defective ribosomal products to the class I pathway.

SUBMITTER: Ruiz Cuevas MV

PROVIDER: S-EPMC8040094 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Most non-canonical proteins uniquely populate the proteome or immunopeptidome.

Ruiz Cuevas Maria Virginia MV Hardy Marie-Pierre MP Hollý Jaroslav J Bonneil Éric É Durette Chantal C Courcelles Mathieu M Lanoix Joël J Côté Caroline C Staudt Louis M LM Lemieux Sébastien S Thibault Pierre P Perreault Claude C Yewdell Jonathan W JW

Cell reports 20210301 10

Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated ...[more]

PMID: 33691108

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Project description:Ribosome profiling (Ribo-seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of non-canonical sites of ribosome translation outside of the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7,000 non-canonical open reading frames (ORFs) are translated, which, at first glance, has the potential to expand the number of human protein-coding sequences by 30%, from ∼19,500 annotated CDSs to over 26,000. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of non-canonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome, but searching for guidance on how to proceed. Here, we discuss the current state of non-canonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein-coding".In briefThe human genome encodes thousands of non-canonical open reading frames (ORFs) in addition to protein-coding genes. As a nascent field, many questions remain regarding non-canonical ORFs. How many exist? Do they encode proteins? What level of evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-seq) as a method to discern genome-wide ribosome occupancy, and immunopeptidomics as a method to detect peptides that are processed and presented by MHC molecules and not observed in traditional proteomics experiments. This article provides a synthesis of the current state of non-canonical ORF research and proposes standards for their future investigation and reporting.HighlightsCombined use of Ribo-seq and proteomics-based methods enables optimal confidence in detecting non-canonical ORFs and their protein products.Ribo-seq can provide more sensitive detection of non-canonical ORFs, but data quality and analytical pipelines will impact results.Non-canonical ORF catalogs are diverse and span both high-stringency and low-stringency ORF nominations.A framework for standardized non-canonical ORF evidence will advance the research field.

Dataset Information

Most non-canonical proteins uniquely populate the proteome or immunopeptidome.

Publications

Most non-canonical proteins uniquely populate the proteome or immunopeptidome.

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