Reconstruction of circular RNAs using Illumina and Nanopore RNA-seq datasets.

High-throughput RNA sequencing has enabled the extensive detection of circular RNAs (circRNAs) in eukaryotic organisms. However, most circRNAs are derived from exonic regions and possess sequences that are highly overlapped to their cognate linear mRNAs, which makes the reconstruction of the internal structure and full-length circular transcripts a challenging aspect in circRNA studies. To solve this problem, we provide a step-by-step protocol for the full-length reconstruction of circRNAs using CIRI-full and CIRI-long in Illumina and Nanopore RNA-seq libraries. By combining experimental and computational methods, we are able to effectively characterize the full-length landscape of circRNAs, which provide an important basis to explore the biogenesis and biological function of circRNAs.

Ryuto: network-flow based transcriptome reconstruction.

BACKGROUND: The rapid increase in High-throughput sequencing of RNA (RNA-seq) has led to tremendous improvements in the detection and reconstruction of both expressed coding and non-coding RNA transcripts. Yet, the complete and accurate annotation of the complex transcriptional output of not only the human genome has remained elusive. One of the critical bottlenecks in this endeavor is the computational reconstruction of transcript structures, due to high noise levels, technological limits, and other biases in the raw data. RESULTS: We introduce several new and improved algorithms in a novel workflow for transcript assembly and quantification. We propose an extension of the common splice graph framework that combines aspects of overlap and bin graphs and makes it possible to efficiently use both multi-splice and paired-end information to the fullest extent. Phasing information of reads is used to further resolve loci. The decomposition of read coverage patterns is modeled as a minimum-cost flow problem to account for the unavoidable non-uniformities of RNA-seq data. CONCLUSION: Its performance compares favorably with state of the art methods on both simulated and real-life datasets. Ryuto calls 1-4% more true transcripts, while calling 5-35% less false predictions compared to the next best competitor.

Reconstruction of full-length circular RNAs enables isoform-level quantification.

Currently, circRNA studies are shifting from the identification of circular transcripts to understanding their biological functions. However, such endeavors have been limited by large-scale determination of their full-length sequences and also by the inability of accurate quantification at the isoform level. Here, we propose a new feature, reverse overlap (RO), for circRNA detection, which outperforms back-splice junction (BSJ)-based methods in identifying low-abundance circRNAs. By combining RO and BSJ features, we present a novel approach for effective reconstruction of full-length circRNAs and isoform-level quantification from the transcriptome. We systematically compared the difference between the BSJ-level and isoform-level differential expression analyses using human liver tumor and normal tissues and highlight the necessity of deepening circRNA studies to the isoform-level resolution. The CIRI-full software can be accessed at https://sourceforge.net/projects/ciri .

Detection and Reconstruction of Circular RNAs from Transcriptomic Data.

Recent studies have shown that circular RNAs (circRNAs) are a novel class of abundant, stable, and ubiquitous noncoding RNA molecules in eukaryotic organisms. Comprehensive detection and reconstruction of circRNAs from high-throughput transcriptome data is an initial step to study their biogenesis and function. Several tools have been developed to deal with this issue, but they require many steps and are difficult to use. To solve this problem, we provide a protocol for researchers to detect and reconstruct circRNA by employing CIRI2, CIRI-AS, and CIRI-full. This protocol can not only simplify the usage of above tools but also integrate their results.