CircParser: a novel streamlined pipeline for circular RNA structure and host gene prediction in non-model organisms

Artem Nedoluzhko; Fedor Sharko; Md Golam Rbbani; Anton Teslyuk; Ioannis Konstantinidis; Jorge M O Fernandes

doi:10.7717/peerj.8757

CircParser: a novel streamlined pipeline for circular RNA structure and host gene prediction in non-model organisms

PeerJ. 2020 Mar 16:8:e8757. doi: 10.7717/peerj.8757. eCollection 2020.

Authors

Artem Nedoluzhko^#¹, Fedor Sharko^#^{2

3}, Md Golam Rbbani¹, Anton Teslyuk², Ioannis Konstantinidis¹, Jorge M O Fernandes¹

Affiliations

¹ Faculty of Biosciences and Aquaculture, Nord University, Bodø, Bodø, Norway.
² Complex of NBICS Technologies, National Research Centre "Kurchatov Institute", Moscow, Russia.
³ Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia, Russia.

^# Contributed equally.

Abstract

Circular RNAs (circRNAs) are long noncoding RNAs that play a significant role in various biological processes, including embryonic development and stress responses. These regulatory molecules can modulate microRNA activity and are involved in different molecular pathways as indirect regulators of gene expression. Thousands of circRNAs have been described in diverse taxa due to the recent advances in high throughput sequencing technologies, which led to a huge variety of total RNA sequencing being publicly available. A number of circRNA de novo and host gene prediction tools are available to date, but their ability to accurately predict circRNA host genes is limited in the case of low-quality genome assemblies or annotations. Here, we present CircParser, a simple and fast Unix/Linux pipeline that uses the outputs from the most common circular RNAs in silico prediction tools (CIRI, CIRI2, CircExplorer2, find_circ, and circFinder) to annotate circular RNAs, assigning presumptive host genes from local or public databases such as National Center for Biotechnology Information (NCBI). Also, this pipeline can discriminate circular RNAs based on their structural components (exonic, intronic, exon-intronic or intergenic) using a genome annotation file.

Keywords: Annotation; Circular RNAs; Host gene; Prediction; Structural components.

Grants and funding

This study has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no 683210) and from the Research Council of Norway under the Toppforsk programme (grant agreement no 250548/F20). Fedor Sharko was supported by the RFBR (Russian Foundation for Basic Research) Grant no 19-54-54004. This work was partially carried out in Kurchatov Center for Genome Research and supported by Ministry of Science and Higher Education of Russian Federation, grant #075-15-2019-1659. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.