Circular RNAs (circRNAs) are recently discovered members of the noncoding RNA family that range in length from a few hundred to thousands of nucleotides. In contrast to linear RNA transcripts, which are normally spliced tail-to-head, circRNAs are formed by the covalent bonding of their 3´ and 5´ (head-to-tail) ends. The lack of open sites at the 5´ and 3´ ends exempts circRNAs from endonuclease degradation, making them stable in cells. Additionally, studies have shown remarkable capabilities of circRNAs to sequester several miRNAs away from messenger RNA targets using shared miRNA binding sites (MRE – miRNA response elements). Depending on the number of MRE sites available, circRNAs can compete with messenger RNAs for a common pool of miRNAs, thereby regulating gene expression. Such networks of complex interactions between coding and non-coding RNAs within the cell are termed as competing endogenous RNA (ceRNA) networks. Hence, these unique features of circRNAs to remain stable and act as competing endogenous RNAs (ceRNAs) make them promising candidates to explore novel diagnostic and therapeutic targets in diseases.
Circ-Seq is an integrated bioinformatics workflow for identifying and characterizing circRNAs using high-throughput transcriptome sequencing data. Briefly, it improves the circRNA identification methodology developed by Memczak et.al 2013 by applying filters to exclude false positives from the final catalog of candidate circRNAs. . Circ-Seq also helps users prioritize the final list of circRNAs by annotating them with exon information on the location (exon boundary or within exons) of their 3’ (head) and 5’ (tail) ends. Circ-Seq processes unmapped reads of the transcriptome, obtained either from the MAP-RSeq workflow or any other RNA-Seq alignment software. These reads are checked for evidence of alignment in a circular RNA specific (3′ to 5′) fashion. Filters on expression, genomic size and in-silico validation are applied to report legitimate circRNA candidates. Circ-Seq provides a circRNA quantification report and a FASTA file that contains 50-base nucleotide sequences containing the 3´–5´ fused junction of circRNAs in the final report.
The workflow can be configured to run on a single Linux machine as well as in a cluster environment to fully leverage multiple processors.
- User Manual
- Source code for Open Grid Engine and Standalone execution.
- Example input and output files
- Reference files for circRNA annotation
Nair AA, Niu N, Tang X, Thompson KJ, Wang L, Kocher JP, Subramanian S and Kalari KR. Circular RNAs and their associations with breast cancer subtypes. Oncotarget. 2016.
For assistance, please contact Asha Nair (Nair.Asha@mayo.edu) or Krishna R. Kalari, Ph.D (Kalari.Krishna@mayo.edu)
Page last modified: March 7, 2017