Circular RNAs (circRNAs) are evolutionarily conserved RNA species that are formed when exons "back-splice" to each other. Current computational algorithms to detect these back-splicing junctions produce divergent results, and hence there is a need for a method to distinguish true-positive circRNAs. To this end, we developed Assembly based CircRNA Validator (ACValidator) for in silico verification of circRNAs. ACValidator extracts reads from a user-defined window on either side of a circRNA junction and assembles them to generate contigs. These contigs are aligned against the circRNA sequence to find contigs spanning the back-spliced junction. When evaluated on simulated datasets, ACValidator achieved over ∼80% sensitivity on datasets with an average of 10 circRNA-supporting reads and with read lengths of at least 100 bp. In experimental datasets, ACValidator produced higher verification percentages for samples treated with ribonuclease R compared to nontreated samples. Our workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for prioritizing experimental validations. All workflow scripts are freely accessible on our GitHub page https://github.com/tgen/ACValidator along with detailed instructions to set up and run ACValidator.
Keywords: CircRNAs; RNA expression; RNAseq.
© The Author(s) 2020. Published by Oxford University Press.