Background Circular RNAs (circRNAs) are implicated in various biological processes. As a layer of the gene regulatory network, circRNA expression is also an intermediate phenotype bridging genetic variation and phenotypic changes. Thus, analyzing circRNA expression variation will shed light on molecular fundamentals of complex traits and diseases. Results We systematically characterize 10,559 high-quality circRNAs in 589 human dorsolateral prefrontal cortex samples. We identify biological and technical factors contributing to expression heterogeneity associated with the expression levels of many circRNAs, including the well-known circRNA CDR1as. Combining the expression levels of circRNAs with genetic cis -acting SNPs, we detect 196,255 circRNA quantitative trait loci (circQTLs). By characterizing circQTL SNPs, we find that partial circQTL SNPs might influence circRNA formation by altering the canonical splicing site or the reverse complementary sequence match. Additionally, we find that a subset of these circQTL SNPs is highly linked to genome-wide association study signals of complex diseases, especially schizophrenia, inflammatory bowel disease, and type II diabetes mellitus. Conclusions Our results reveal technical, biological, and genetic factors affecting circRNA expression variation among individuals, which lead to further understanding of circRNA regulation and thus of the genetic architecture of complex traits or diseases. Electronic supplementary material The online version of this article (10.1186/s13059-019-1701-8) contains supplementary material, which is available to authorized users.

Circular RNAs (circRNAs) act through multiple mechanisms via their sequence features to fine-tune gene expression networks. Due to overlapping sequences with linear cognates, identifying internal sequences of circRNAs remains a challenge, which hinders a comprehensive understanding of circRNA functions and mechanisms. Here, based on rolling circular reverse transcription (RCRT) and nanopore sequencing, we developed circFL-seq, a full-length circRNA sequencing method, to profile circRNA at the isoform level. With a customized computational pipeline to directly identify full-length sequences from rolling circular reads, we reconstructed 77,606 high-quality circRNAs from seven human cell lines and two human tissues. circFL-seq benefits from rolling circles and long-read sequencing, and the results showed more than tenfold enrichment of circRNA reads and advantages for both detection and quantification at the isoform level compared to those for short-read RNA sequencing. The concordance of the RT-qPCR and circFL-seq results for the identification of differential alternative splicing suggested wide application prospects for functional studies of internal variants in circRNAs. Moreover, the detection of fusion circRNAs at the omics scale may further expand the application of circFL-seq. Together, the accurate identification and quantification of full-length circRNAs make circFL-seq a potential tool for large-scale screening of functional circRNAs.

Circular RNAs (circRNAs) are involved in various biological processes and disease pathogenesis. However, only a small number of functional circRNAs have been identified among hundreds of thousands of circRNA species, partly because most current methods are based on circular junction counts and overlook the fact that a circRNA is formed from the host gene by back-splicing (BS). To distinguish the expression difference originating from BS or the host gene, we present differentially expressed back-splicing (DEBKS), a software program to streamline the discovery of differential BS events between two rRNA-depleted RNA sequencing (RNA-seq) sample groups. By applying to real and simulated data and employing RT-qPCR for validation, we demonstrate that DEBKS is efficient and accurate in detecting circRNAs with differential BS events between paired and unpaired sample groups. DEBKS is available at https://github.com/yangence/DEBKS as open-source software.