Christoph Dieterich

Circular RNAs (circRNAs) are a large class of animal RNAs. To investigate possible circRNA functions, it is important to understand circRNA biogenesis. Besides human ALU repeats, sequence features that promote exon circularization are largely unknown. We experimentally identified circRNAs in C. elegans. Reverse complementary sequences between introns bracketing circRNAs were significantly enriched in comparison to linear controls. By scoring the presence of reverse complementary sequences in human introns, we predicted and experimentally validated circRNAs. We show that introns bracketing circRNAs are highly enriched in RNA editing or hyperediting events. Knockdown of the double-strand RNA-editing enzyme ADAR1 significantly and specifically upregulated circRNA expression. Together, our data support a model of animal circRNA biogenesis in which competing RNA-RNA interactions of introns form larger structures that promote circularization of embedded exons, whereas ADAR1 antagonizes circRNA expression by melting stems within these interactions.

Quantitative and systems biology approaches benefit from the unprecedented depth of next-generation sequencing. A typical experiment yields millions of short reads, which oftentimes carry particular sequence tags. These tags may be: (a) specific to the sequencing platform and library construction method (e.g., adapter sequences); (b) have been introduced by experimental design (e.g., sample barcodes); or (c) constitute some biological signal (e.g., splice leader sequences in nematodes). Our software FLEXBAR enables accurate recognition, sorting and trimming of sequence tags with maximal flexibility, based on exact overlap sequence alignment. The software supports data formats from all current sequencing platforms, including color-space reads. FLEXBAR maintains read pairings and processes separate barcode reads on demand. Our software facilitates the fine-grained adjustment of sequence tag detection parameters and search regions. FLEXBAR is a multi-threaded software and combines speed with precision. Even complex read processing scenarios might be executed with a single command line call. We demonstrate the utility of the software in terms of read mapping applications, library demultiplexing and splice leader detection. FLEXBAR and additional information is available for academic use from the website: http://sourceforge.net/projects/flexbar/.

MOTIVATION: Circular RNAs (circRNAs) are a poorly characterized class of molecules that have been identified decades ago. Emerging high-throughput sequencing methods as well as first reports on confirmed functions have sparked new interest in this RNA species. However, the computational detection and quantification tools are still limited. RESULTS: We developed the software tandem, DCC and CircTest DCC uses output from the STAR read mapper to systematically detect back-splice junctions in next-generation sequencing data. DCC applies a series of filters and integrates data across replicate sets to arrive at a precise list of circRNA candidates. We assessed the detection performance of DCC on a newly generated mouse brain data set and publicly available sequencing data. Our software achieves a much higher precision than state-of-the-art competitors at similar sensitivity levels. Moreover, DCC estimates circRNA versus host gene expression from counting junction and non-junction reads. These read counts are finally used to test for host gene-independence of circRNA expression across different experimental conditions by our R package CircTest We demonstrate the benefits of this approach on previously reported age-dependent circRNAs in the fruit fly. AVAILABILITY AND IMPLEMENTATION: The source code of DCC and CircTest is licensed under the GNU General Public Licence (GPL) version 3 and available from https://github.com/dieterich-lab/[DCC or CircTest]. CONTACT: christoph.dieterich@age.mpg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.