Discovery of novel circular RNAs through integration of short- and long-read RNA sequencing
Circular RNAs (circRNAs) are associated with crucial hallmarks of tumorigenesis. Select circRNAs contain circular open reading frames (cORFs) and impact tumorigenesis through encoded small peptides. However, current circRNA detection approaches bias towards using short-read RNA-seq for detecting circRNA backsplice junctions (BSJs) without reliably reconstructing complete circRNA sequences, inhibiting accurate cORF prediction. To address these challenges, we performed long-read sequencing to enrich for full-length circRNAs that could serve as a guide for short-read alignment. This approach “rescued” circRNAs eluding existing tools focused on circRNA detection from short reads and enabled the development of an open-source bioinformatics workflow that characterizes and rescues circRNAs by integrating short- and long-read RNA-seq: CHRIS (CHaracterizing CircRNAs by Integrative Sequencing). Application of the approach to colorectal cancer (CRC) cell lines and patient samples revealed 6,445 non-canonical isoforms of known circRNAs of which 69 were altered during cancer metastasis. Validation experiments in CRC cell lines confirmed endogenous expression of 11 high-confidence circRNAs rescued by CHRIS. Next, proteogenomic analysis using 67,326 circRNAs detected by CHRIS and mass spectrometry data from 261 CRC patients from Clinical Proteomic Tumor Analysis Consortium (CPTAC) identified 6,848 peptides encoded by circRNAs, including 994 only detectable with long-read integration and 914 potential neoantigens. Overall, this research develops an approach that can facilitate circRNA detection and provide valuable resources for future circRNA tumor biology research. Overall design: Integrative analysis using both short-read and long-read RNA-seq to profile novel circRNAs in CRC cell lines and patient samples