Identification of non-canonical peptides with moPepGen
Proteogenomics is limited by the challenge of modeling the complexities of gene expression. We create moPepGen, a graph-based algorithm that comprehensively generates non-canonical peptides in linear time. moPepGen works with multiple technologies, in multiple species and on all types of genetic and transcriptomic data. In human cancer proteomes, it enumerates previously unobservable noncanonical peptides arising from germline and somatic genomic variants, noncoding open reading frames, RNA fusions and RNA circularization.
Authors
- Annie Ha (ORCID: https://orcid.org/0000-0002-8740-4125)
- Paul C. Boutros (ORCID: https://orcid.org/0000-0003-0553-7520)
- Takafumi N. Yamaguchi (ORCID: https://orcid.org/0000-0003-1082-3871)
- Thomas Kislinger (ORCID: https://orcid.org/0000-0003-3525-5540)
- Yash Patel (ORCID: https://orcid.org/0000-0003-3113-7010)
- Julie Livingstone (ORCID: https://orcid.org/0000-0002-8424-3768)
- Chenghao Zhu (ORCID: https://orcid.org/0000-0003-1674-4533)
- Rupert Hugh-White (ORCID: https://orcid.org/0000-0003-3351-8925)
- Helen He Zhu (ORCID: https://orcid.org/0000-0003-0290-5527)
- Lydia Liu (ORCID: https://orcid.org/0000-0001-6026-3169)
Institutions
- University Health Network (CA)
- University of California, Los Angeles (US)
- University of Toronto (CA)
- UCLA Health (US)
- Princess Margaret Cancer Centre (CA)
- Vector Institute (CA)
Publication Details
- Journal
- Nature Biotechnology
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1038/s41587-025-02701-0
- Citations
- 5
- Primary Topic
- RNA and protein synthesis mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 4.03
Funders
- Canadian Cancer Society Research Institute
- National Cancer Institute