High-quality peptide evidence for annotating non-canonical open reading frames as human proteins.

Area of Science:

• Genomics and Proteomics
• Human Health and Disease

Background:

• The protein-coding genome is crucial for studying human health, but prior analyses may have missed significant components.
• Non-canonical open reading frames (ncORFs) have been observed across human cells and diseases, with potential implications for proteomics, genomics, and clinical science.
• A large-scale understanding of ncORF contributions to the human proteome has been lacking, limiting their impact.

Purpose of the Study:

• To establish a consensus landscape of protein-level evidence for ncORFs through collaborative efforts.
• To determine the extent of translation from a defined set of ncORFs and characterize the resulting peptides.
• To develop a framework for annotating ncORFs and create accessible public tools for researchers.

Main Methods:

• Integrated data from proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation.
• Analyzed 3.8 billion mass spectra from 95,520 experiments in a pan-proteome analysis.
• Developed an annotation framework and public tools (GENCODE, PeptideAtlas) for ncORF research.

Main Results:

• Protein-level evidence was found for at least 25% of 7,264 investigated ncORFs.
• Over 3,000 unique peptides were identified from translated ncORFs.
• A comprehensive dataset and annotation framework for ncORFs were established.

Conclusions:

• This work significantly advances the understanding of the human proteome by characterizing ncORF-derived proteins.
• The developed resources provide a platform for future biomedical discoveries utilizing ncORF data.
• The findings have implications for human health research and extend to ncORF observations in other organisms.