Circular RNAs (circRNAs) are noncoding and single-stranded RNA transcripts able to form covalently circular-closed structures. They are generated through alternative splicing events and widely expressed from human to viruses. CircRNAs have been appointed as potential regulators of microRNAs (miRNAs), RNA-binding proteins (RPBs), and lineal protein-coding transcripts. Although their mechanism of action remains unclear, the deregulation of circular RNAs has been confirmed in different diseases such as Alzheimer or cancer.The introduction of high-throughput next-generation sequencing (NGS) technology provides millions of short RNA sequences at single-nucleotide level, allowing an accurate and proficient method to measure circular RNAs. Novel protocols based on non-polyadenylated RNAs, rRNA-depleted, and RNA exonuclease-based enrichment approaches (RNase R) have taken even further the possibility of detecting circRNAs.Besides, the identification of circRNAs presence requires the development of specific bioinformatics tools to detect junction-spanning sequences from transcriptome deep-sequencing samples. Thus, recently established bioinformatics' approaches have permitted the discovery of an elevated number of different circRNAs in diverse organisms. In that sense, recent studies have compared different methods and advocate the simultaneous use of more than one prediction tool. For that reason, we want to highlight pipelines such as miARma-Seq that is able to execute various circular RNA identification algorithms in an easy way, without the tedious installation of third-party prerequisites.
Keywords: CircRNA RNA-seq; CircRNA prediction tools; CircRNAs.