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Computational approaches for circular RNA analysis

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Circular RNAs (circRNAs) are a recent addition to the expanding universe of RNA species and originate through back‐splicing events from linear primary transcripts. CircRNAs show specific expression profiles with regards to cell type and developmental stage. Importantly, only few circRNAs have been functionally characterized to date. The detection of circRNAs from RNA sequencing data is a complex computational workflow that, depending on tissue and condition typically yields candidate sets of hundreds or thousands of circRNA candidates. Here, we provide an overview on different computational analysis tools and pipelines that became available throughout the last years. We outline technical and experimental requirements that are common to all approaches and point out potential pitfalls during the computational analysis. Although computational prediction of circRNAs has become quite mature in recent years, we provide a set of valuable validation strategies, in silico as well as in vitro‐based approaches. In addition to circRNA detection via back‐splicing junction, we present available analysis pipelines for delineating the primary sequence and for predicting possible functions of circRNAs. Finally, we outline the most important web resources for circRNA research. This article is categorized under: RNA Methods > RNA Analyses in vitro and In Silico RNA Evolution and Genomics > Computational Analyses of RNA
CircRNA biogenesis and functions. (a) Pre‐mRNA is spliced to a mature linear transcript by removing intronic sequences. (b) Back‐splicing of the green and purple exon is facilitated if splicing donor and acceptor site are in close proximity to one another. Additionally, a short linear transcript consisting of the short blue and red exons may emerge. (c) Reverse complementary matches (RCMs), consisting for example of ALU repeats have been shown to play a role in promoting the circularization process. (d) ADAR1 has been shown to be an antagonist of circRNA biogenesis by weakening the base pairing energy in the RCM region through A → I editing. (e) The RNA binding protein QKI was shown to promote the circularization process. (f) Circularized circRNA with additional exon (yellow) as part of the circle that could be produced from the back‐splicing event shown in (b). (g) Two‐exon circRNA that also could be produced from the back‐splicing event shown in (b). (h) CircRNA with retained intronic sequence, termed EIciRNA (exon intron ciRNA). (i) Intron lariat structure purely consisting of intronic sequences. (j) CircRNA with binding sites for microRNAs, a so‐called microRNA sponge that could be shown for few circRNAs. (k) CircRNA with binding sites for RBPs also exerting a sponge effect. (l) CircRNA with open reading frame that can be translated. (m) Circular transcripts and linear transcripts are competing for splicing from the same pre‐mRNA
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Screenshots of the web interface of different circRNA web databases. (a) circBase. (b) StarBase3. (c) circInteractome
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Computational detection of circRNAs and possible verification mechanisms. (a) Standard work flow of library preparation for circRNA RNA‐seq setups. The total RNA pool is depleted of ribosomal rRNA in a first step, subsequently the optional digestion step with RNase R can be performed that removes linear RNAs from the treated portion of the library while the other portion of the library is not treated with RNase R. (b) After sequencing and data acquisition it is recommended to remove remaining sequencing adapter residues from all reads. (c) General read mapping step, all reads are aligned to a reference genome, colored exons depicted in the bottom. Reads can be categorized into reads mapping within exons (gray), reads that span exon‐exon junctions (blue, connected by dashed lines) and chimeric reads potentially indicative for circRNAs. (d) A circRNA with chimeric reads covering the BSJ (red) and a regular read (gray) that cannot be assigned exclusively to neither circRNA or linear RNA. (e) A genomic rearrangement that may yield scrambled exons mimicking the true positive junction shown in (d). (f) A tandem duplication on genome level that leads to potential false positive scrambled junctions similar to the true positive shown in (d). (g) Trans‐splicing events may yield false positive scrambled exon junctions that are similar to the true positive junctions of (d). (h) Overlapping paired‐end reads on a circRNA, not covering the BSJ. Since this kind of overlap only can occur if the template was circular, such read mappings can also be indicative of circRNAs. (i) Classical two‐phase circRNA detection approach. After a first mapping step, only non‐mapping reads are kept, the flanking read regions are extracted and mapped again in a second phase to detect potential chimeric read alignments. (j) More recent circRNA detection setups can employ direct approaches that are able to output chimeric reads in a one‐pass strategy. (k) Similar to paired‐end reads shown in (h) paired‐end reads mapping both to the BSJ are highly indicative for circRNAs. (l) Validation of circRNAs by qPCR with specific, inward‐facing primers that exclusively produce a PCR product if the circular transcript exists. The potential false positive scrambled exon junctions shown in (e–g) however, will also result in a PCR product. (m) Prediction of circRNA features like miRNA sponge binding sites are depending on knowledge of the complete sequence of the circRNA. Removed exons may result in large differences between predicted binding sites and actual circRNA sequence
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RNA Evolution and Genomics > Computational Analyses of RNA
RNA Methods > RNA Analyses In Vitro and In Silico

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