circFL-seq reveals full-length circular RNAs with rolling circular reverse transcription and nanopore sequencing
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.
The circFL-seq and RNA-seq data produced by this study have been deposited in SRA (PRJNA722575). The information of circRNAs detected by circFL-seq is available in the figshare repository (https://doi.org/10.6084/m9.figshare.14265650.v1). The computational software circfull can be accessed from https://github.com/yangence/circfull.
isoCirc catalogs full-length circular RNA isoforms in human transcriptomesNCBI Gene Expression Omnibus, GSE141693.
Comprehensive profiling of circular RNAs with nanopore sequencing and CIRI-longNGDC Genome Sequence Archive, CRA003317.
Article and author information
Beijing Municipal Science and Technology Commission of China (7212065,Z181100001518005)
- Ence Yang
Chinese Institute for Brain Research, Beijing (2020-NKX-XM-01)
- Ence Yang
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Gene W Yeo, University of California, San Diego, United States
- Received: April 15, 2021
- Preprint posted: July 5, 2021 (view preprint)
- Accepted: October 13, 2021
- Accepted Manuscript published: October 14, 2021 (version 1)
- Version of Record published: October 26, 2021 (version 2)
© 2021, Liu et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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