Improved Ribo-seq enables identification of cryptic translation events

Area of Science:

• Molecular Biology
• Bioinformatics
• Immunology

Background:

• Ribosome profiling identifies thousands of short open reading frames (sORFs) in eukaryotic cells.
• Experimental noise in ribosome profiling data presents challenges in accurately identifying sORFs and noncanonical translation.
• The biological relevance and presentation of sORF-derived peptides remain largely unexplored.

Purpose of the Study:

• To develop a computational method to accurately resolve overlapping sORFs and noncanonical translation initiation from noisy ribosome profiling data.
• To experimentally validate the translation and presentation of sORF-derived peptides.
• To determine the contribution of sORF-derived peptides to the Major Histocompatibility Complex class I (MHC I) antigen repertoire.

Main Methods:

• Development and application of the PRICE computational method to model and correct for experimental noise in ribosome profiling data.
• Experimental validation of predicted sORF translation using MHC I peptidomics.
• Analysis of MHC I peptidomics data to identify and quantify sORF-derived peptides.

Main Results:

• The PRICE method accurately resolves overlapping sORFs and identifies noncanonical translation initiation.
• sORF-derived peptides are efficiently processed and presented through the MHC I pathway.
• sORF-derived peptides constitute a substantial fraction of the naturally occurring antigen repertoire presented by MHC I molecules.

Conclusions:

• The PRICE computational method enhances the accuracy of sORF identification from ribosome profiling data.
• sORFs represent a significant source of antigens presented by the MHC I pathway, expanding our understanding of the T cell antigen repertoire.
• This work provides a foundation for further investigation into the functional roles of sORFs and their encoded peptides in cellular processes and immunity.