Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant,stable and ubiquitous noncoding RNA molecules in animals,and some of them function as microRNA sponges.A comprehensive detection of circRNAs from high throughput RNA transcriptome data is an initial and crucial step to study the biogenesis and function of circular RNAs.We present a novel chiastic clipping signal based algorithm to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies.In addition,by combining a novel computational algorithm with long-read sequencing data as well as experimental validation,we for the first time comprehensively investigated internal components of circRNAs in ten human cell lines and 62 fruit fly samples.Our results revealed the prevalence of alternative splicing events within circRNAs and their distinction from corresponding mRNAs.We further found that alternative splicing events in circRNAs have an obvious preference towards nucleus localization,and exhibit a strong tissue-and developmental stage-specific expression pattern.