Sign in
BioinformaticsbioRxiv
Preprint

Accurate Reconstruction of Circular RNAs from Complex Rolling Circular Long Reads with CircPlex

Tasfia ZahiniD, Irtesam Mahmud KhaniD, Mingfu ShaoiD

Abstract

Rolling circle amplification (RCA) coupled with long-read sequencing has emerged as a powerful strategy for detecting full-length circular RNAs (circRNAs). Such protocols produce long reads that are normally composed of several tandemly repeated copies of the original circRNA. The circRNA sequence can be reconstructed through detecting the repeating unit of the long reads, which are aligned to the genome to validate and to identify back-splice junctions (BSJs). We revealed a previously unrecognized phenomenon: a substantial fraction of long reads contain complex repeat patterns in which the repeating unit consists of a sequence combined with its partial reverse complement. In these cases, only the original sequence corresponds to the true circRNA, while the concatenated pattern may produce false circRNAs and misidentify correct circRNAs. We present a new approach CircPlex that extracts the authentic circRNA sequence from these complex repeat units, overcoming the limitations of standard repeat-based consensus prediction. Comparison with isoCirc annotations and circRNA database demonstrates that a significant number of BSJs and full-length sequences, previously ignored, can be recovered. Our results suggest that leveraging partially repetitive reads from RCA-based sequencing can substantially increase circRNA detection sensitivity and uncover novel isoforms, providing a more comprehensive view of the circular transcriptome.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISLiu '21Zahin '24Humphreys '19Sekar '20Gaffo '21Tang '18
66% semantic matchMolecular Biology
Zelin Liu, Changyu Tao, Shiwei Li+6 more·eLife·Oct 14, 2021· 59 citations