Recent evidence suggests that many endogenous circular RNAs (circRNAs) may play 
roles in biological processes. However, the expression patterns and functions of 
circRNAs in human diseases are not well understood. Computationally identifying 
circRNAs from total RNA-seq data is a primary step in studying their expression 
pattern and biological roles. In this work, we have developed a computational 
pipeline named UROBORUS to detect circRNAs in total RNA-seq data. By applying 
UROBORUS to RNA-seq data from 46 gliomas and normal brain samples, we detected 
thousands of circRNAs supported by at least two read counts, followed by 
successful experimental validation on 24 circRNAs from the randomly selected 27 
circRNAs. UROBORUS is an efficient tool that can detect circRNAs with low 
expression levels in total RNA-seq without RNase R treatment. The circRNAs 
expression profiling revealed more than 476 circular RNAs differentially 
expressed in control brain tissues and gliomas. Together with parental gene 
expression, we found that circRNA and its parental gene have diversified 
expression patterns in gliomas and control brain tissues. This study establishes 
an efficient and sensitive approach for predicting circRNAs using total RNA-seq 
data. The UROBORUS pipeline can be accessed freely for non-commercial purposes 
at http://uroborus.openbioinformatics.org/.