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      Closing the circle: current state and perspectives of circular RNA databases

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          Abstract

          Circular RNAs (circRNAs) are covalently closed RNA molecules that have been linked to various diseases, including cancer. However, a precise function and working mechanism are lacking for the larger majority. Following many different experimental and computational approaches to identify circRNAs, multiple circRNA databases were developed as well. Unfortunately, there are several major issues with the current circRNA databases, which substantially hamper progression in the field. First, as the overlap in content is limited, a true reference set of circRNAs is lacking. This results from the low abundance and highly specific expression of circRNAs, and varying sequencing methods, data-analysis pipelines, and circRNA detection tools. A second major issue is the use of ambiguous nomenclature. Thus, redundant or even conflicting names for circRNAs across different databases contribute to the reproducibility crisis. Third, circRNA databases, in essence, rely on the position of the circRNA back-splice junction, whereas alternative splicing could result in circRNAs with different length and sequence. To uniquely identify a circRNA molecule, the full circular sequence is required. Fourth, circRNA databases annotate circRNAs’ microRNA binding and protein-coding potential, but these annotations are generally based on presumed circRNA sequences. Finally, several databases are not regularly updated, contain incomplete data or suffer from connectivity issues. In this review, we present a comprehensive overview of the current circRNA databases and their content, features, and usability. In addition to discussing the current issues regarding circRNA databases, we come with important suggestions to streamline further research in this growing field.

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          Most cited references54

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          Circular RNAs are a large class of animal RNAs with regulatory potency.

          Circular RNAs (circRNAs) in animals are an enigmatic class of RNA with unknown function. To explore circRNAs systematically, we sequenced and computationally analysed human, mouse and nematode RNA. We detected thousands of well-expressed, stable circRNAs, often showing tissue/developmental-stage-specific expression. Sequence analysis indicated important regulatory functions for circRNAs. We found that a human circRNA, antisense to the cerebellar degeneration-related protein 1 transcript (CDR1as), is densely bound by microRNA (miRNA) effector complexes and harbours 63 conserved binding sites for the ancient miRNA miR-7. Further analyses indicated that CDR1as functions to bind miR-7 in neuronal tissues. Human CDR1as expression in zebrafish impaired midbrain development, similar to knocking down miR-7, suggesting that CDR1as is a miRNA antagonist with a miRNA-binding capacity ten times higher than any other known transcript. Together, our data provide evidence that circRNAs form a large class of post-transcriptional regulators. Numerous circRNAs form by head-to-tail splicing of exons, suggesting previously unrecognized regulatory potential of coding sequences.
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            Circular RNAs are abundant, conserved, and associated with ALU repeats.

            Circular RNAs composed of exonic sequence have been described in a small number of genes. Thought to result from splicing errors, circular RNA species possess no known function. To delineate the universe of endogenous circular RNAs, we performed high-throughput sequencing (RNA-seq) of libraries prepared from ribosome-depleted RNA with or without digestion with the RNA exonuclease, RNase R. We identified >25,000 distinct RNA species in human fibroblasts that contained non-colinear exons (a "backsplice") and were reproducibly enriched by exonuclease degradation of linear RNA. These RNAs were validated as circular RNA (ecircRNA), rather than linear RNA, and were more stable than associated linear mRNAs in vivo. In some cases, the abundance of circular molecules exceeded that of associated linear mRNA by >10-fold. By conservative estimate, we identified ecircRNAs from 14.4% of actively transcribed genes in human fibroblasts. Application of this method to murine testis RNA identified 69 ecircRNAs in precisely orthologous locations to human circular RNAs. Of note, paralogous kinases HIPK2 and HIPK3 produce abundant ecircRNA from their second exon in both humans and mice. Though HIPK3 circular RNAs contain an AUG translation start, it and other ecircRNAs were not bound to ribosomes. Circular RNAs could be degraded by siRNAs and, therefore, may act as competing endogenous RNAs. Bioinformatic analysis revealed shared features of circularized exons, including long bordering introns that contained complementary ALU repeats. These data show that ecircRNAs are abundant, stable, conserved and nonrandom products of RNA splicing that could be involved in control of gene expression.
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              The Biogenesis, Functions, and Challenges of Circular RNAs

              Covalently closed circular RNAs (circRNAs) are produced by precursor mRNA back-splicing of exons of thousands of genes in eukaryotes. circRNAs are generally expressed at low levels and often exhibit cell-type-specific and tissue-specific patterns. Recent studies have shown that their biogenesis requires spliceosomal machinery and can be modulated by both cis complementary sequences and protein factors. The functions of most circRNAs remain largely unexplored, but known functions include sequestration of microRNAs or proteins, modulation of transcription and interference with splicing, and even translation to produce polypeptides. However, challenges exist at multiple levels to understanding of the regulation of circRNAs because of their circular conformation and sequence overlap with linear mRNA counterparts. In this review, we survey the recent progress on circRNA biogenesis and function and discuss technical obstacles in circRNA studies.
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                Author and article information

                Journal
                Brief Bioinform
                Brief Bioinform
                bib
                Briefings in Bioinformatics
                Oxford University Press
                1467-5463
                1477-4054
                January 2021
                30 January 2020
                30 January 2020
                : 22
                : 1
                : 288-297
                Affiliations
                [1 ] department of Biomolecular Medicine at Ghent University and a member of the Cancer Research Institute Ghent
                [2 ] department of Biomolecular Medicine at Ghent University and a group leader at the Cancer Research Institute Ghent
                [3 ] department of Biomolecular Medicine at Ghent University and at the Flemish Institute for Biotechnology, and a member of the Cancer Research Institute Ghent
                Author notes
                Corresponding authors: Marieke Vromman and Pieter-Jan Volders, Department of Biomolecular Medicine; Ghent University, 9000, Ghent, Belgium. Tel.: +32-9-332-1951. E-mail: marieke.vromman@ 123456ugent.be ; Pieter-Jan Volders, Department of Biomolecular Medicine; Ghent University, 9000, Ghent, Belgium. Tel.: +32-9-332-1951. E-mail: pieterjan.volders@ 123456ugent.be
                Article
                bbz175
                10.1093/bib/bbz175
                7820840
                31998941
                beaea8b1-cde5-4fe4-be34-f64c818ec6cc
                © The Author(s) 2020. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 November 2019
                : 16 December 2019
                : 21 November 2019
                Page count
                Pages: 10
                Funding
                Funded by: Foundation Against Cancer, DOI 10.13039/501100013845;
                Award ID: STK F/2018/1267
                Funded by: Standup Against Cancer;
                Award ID: STIVLK2018000601
                Funded by: Concerted Research Action of Ghent University;
                Award ID: BOF16/GOA/023
                Categories
                AcademicSubjects/SCI01060
                Review Article

                Bioinformatics & Computational biology
                circrna,circrna databases
                Bioinformatics & Computational biology
                circrna, circrna databases

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