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. Author manuscript; available in PMC: 2022 Jul 20.
Published in final edited form as: Wiley Interdiscip Rev RNA. 2021 Aug 2;13(1):e1685. doi: 10.1002/wrna.1685

Circular RNA translation, a path to hidden proteome

Tanvi Sinha 1,#, Chirag Panigrahi 1,#, Debojyoti Das 1,2,#, Amaresh Chandra Panda 1,✉
PMCID: PMC7613019  EMSID: EMS146540  PMID: 34342387

Abstract

Functional proteins in the cell are translated from the messenger RNA (mRNA) molecules, constituting less than 5% of the cellular transcriptome. The majority of the RNA molecules in the cell are noncoding RNAs, including rRNA, tRNA, snRNA, piRNA, lncRNA, microRNA, and poorly characterized circular RNAs (circRNAs). Recent studies established that circRNAs regulate gene expression by associating with RNA-binding proteins and microRNAs. With the growing understanding of circRNA functions, a subset of circRNAs has been reported to translate into proteins. Interestingly, the presence of Open Reading Frames (ORFs), N6-methyladenosine (m6A) modifications, and internal ribosomal entry sites (IRES) in the circRNA sequences indicate their coding potential through the cap-independent translation initiation mechanism. The purpose of this review is to highlight the mechanism of circRNA translation and the importance of circRNA-encoded proteins (circ-proteins) in cellular physiology and pathology. Here, we discuss the computational and molecular methods currently utilized to systematically identify translatable cir-cRNAs and the functional characterization of the circ-proteins. We foresee that the ongoing and future studies on circRNA translation will uncover the hidden proteome and their therapeutic implications in human health.

This article is categorized under:

  • RNA Methods > RNA Analyses in Cells

  • Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs

  • Translation > Mechanisms

Keywords: cap-independent translation, circRNA, IRES, m6A, polypeptide

1. Introduction

Circular RNAs (circRNAs) are a special class of covalently closed noncoding RNA molecules without the 5′ and 3′ ends. Initially, circular RNAs (circRNAs) were discovered to be uncoated, infectious RNA molecules pathogenic to plants (Sanger et al., 1976). Soon after their discovery, the expression of circRNA was also confirmed in eukaryotic cells (Hsu & Coca-Prados, 1979). A few subsequent studies discovered misarranged exons and circRNAs in various samples (Capel et al., 1993; Cocquerelle et al., 1993; Nigro et al., 1991). However, they were thought to be accidental byproducts arising from splicing errors until the next-generation sequencing (NGS) technologies were developed. Recent NGS and novel computational tools revealed the ubiquitous expression of circRNAs throughout the eukaryotic tree of life (Jeck et al., 2013; Ji et al., 2019; Salzman et al., 2012). The length of circRNAs varies from less than 100 nucleotides to several thousand nucleotides (Glazar et al., 2014; W. Wu et al., 2020). Furthermore, circRNAs are abundant and conserved RNA molecules and show cell-specific, tissue-specific spatial expression pattern (Jeck et al., 2013; Salzman et al., 2013; Salzman et al., 2012; S. Xia et al., 2017). These findings indicate that circRNAs are not accidental byproducts of splicing errors.

The circRNAs are usually very stable due to their resistance to exonuclease-mediated degradation (Jeck et al., 2013; Salzman et al., 2012). Recent studies have provided evidence that circRNAs are critical regulators of various pathologies and cellular physiologies by modulating gene expression. A few circRNAs are known to regulate the transcription of parental genes (Z. Li et al., 2015; Y. Zhang et al., 2013). CircRNAs also regulate posttranscriptional gene expression by acting as sponges for RBPs and microRNAs (Abdelmohsen et al., 2017; Hansen et al., 2013; A. Huang et al., 2020; Panda, 2018). Altered circRNA expression in various diseases led to identifying circRNAs that can serve as diagnostic and prognostic biomarkers (Z. Zhang, Yang, & Xiao, 2018). A growing body of research suggested that circRNAs can also be translated into proteins (Prats et al., 2020). However, the complete understanding of the molecular mechanism of circRNA translation and the function of circRNA-encoded proteins (circ-proteins) are yet to be characterized, which may enlighten us about the new roles of these biomolecules in the progression and prevention of diseases. This review attempts to shed light on some of the enigmas related to circRNA translation, which may provide researchers with ideas to develop and design future experiments to explore the novel proteins derived from circRNAs.

2. Circular RNA Biogenesis and Functions

In the last few years, the mechanism of circRNA biogenesis has been well studied (L. L. Chen & Yang, 2015). Primarily, the exonic circRNAs are derived from the pre-mRNA by a process called backsplicing (Eger et al., 2018; Jeck et al., 2013; Kelly et al., 2015). Backsplicing is an unconventional head-to-tail splicing event where the upstream 5′ splicing acceptor site is covalently linked to a downstream 3′ splicing donor site to form a covalently closed RNA circle (Eger et al., 2018). Another class of circRNA containing both exonic and intronic sequences is also generated by back-splicing and is termed exon–intron circRNA (EIcircRNA) (Z. Li et al., 2015). There is still debate regarding its role and the conditions in which backsplicing is favored in place of canonical linear splicing. Although backsplicing is considered a noncanonical splicing mechanism, it depends on canonical splicing machinery (Starke et al., 2015). Several studies suggested that RBPs, including QK1, NF90/110, ADAR, SRSF3, and FUS, among many others, modulate the biogenesis of circRNAs (A. Huang et al., 2020). In addition, the inverted repeat sequences on the flanking introns were found to be critical in the backsplicing of circRNAs (Jeck et al., 2013; D. Liang & Wilusz, 2014). Moreover, the exact mechanism of backsplicing and the factors regulating it has been elusive. Some of the intronic lariats generated during splicing are resistant to the debranching enzyme, generating stable circular intronic RNAs (ciRNAs) or stable intronic sequence RNAs (sisRNAs) (Gardner et al., 2012; Y. Zhang et al., 2013). Currently, more than a million circRNAs have been identified in humans, and hundreds of conserved circRNAs across various species suggest that the expression of circRNAs is far from being a splicing artifact (Jeck et al., 2013; Ji et al., 2019; Vromman et al., 2021; W. Wu et al., 2020).

All these classes of circRNAs regulate gene expression by interacting with cellular factors or by translating into proteins. Two exciting studies reported that circRNA Sry and ciRS-7 (CDR1-AS) harbor multiple miRNA binding sites, acting as a natural sponge for miR-138 and miR-7 to regulate the downstream target gene expression (Hansen et al., 2013; Memczak et al., 2013). Numerous studies established that circRNAs can act as miRNA sponges to regulate gene expression in various diseases (Lee et al., 2019; Panda, 2018). Furthermore, circRNAs can also interact with RBPs and modulate their availability to influence mRNA splicing, stability, or translation (A. Huang et al., 2020). For instance, a circRNA generated from poly(A)-binding protein nuclear 1 (circPABPN1) regulates PABPN1 mRNA translation by acting as a decoy for HuR (Abdelmohsen et al., 2017). Furthermore, Li et al. reported two nuclear-localized EIcircRNAs that interact with the U1 snRNP and RNA Pol II complex to increase the transcription of the parental genes (Z. Li et al., 2015). Some intronic ciRNAs are reported to localize in the nucleus and interact with the RNA polymerase II complex to regulate transcription (Y. Zhang et al., 2013). A few reports suggested that circRNAs harboring the binding sites for enzymes and substrates may act as a protein scaffold (A. Huang et al., 2020). For example, circ-Foxo3 interacts with MDM2 and p53 and induces ubiquitination-mediated degradation of p53 by MDM2 (Du et al., 2017). Recently, some circRNAs have been reported to translate into proteins through cap-independent mechanisms, opening a whole new research and development area (Das et al., 2018; Pamudurti et al., 2017; Yang et al., 2017). Through various molecular mechanisms and the circRNA-encoded proteins, circRNAs have emerged as critical regulatory players of gene expression.

3. Mechanism of Circular RNA Translation

Eukaryotic mRNA translation requires the 5′ m7GpppN cap and the 3′ poly-A tail (Gallie, 1991). The circularization of the mRNA by the interaction of 5′ cap associated with translation initiation factor (eIF4F) and the PABP associated with 3′ poly-A tail enhances the translation process (Gallie, 1991; Wells et al., 1998). However, translation can also occur through the cap-independent mechanisms that require internal ribosome entry sites (IRES) or an N6-methyladenosine (m6A) modified sequence (Johannes & Sarnow, 1998; Meyer et al., 2015). The IRES was first discovered in viruses, followed by their identification in various eukaryotic mRNAs (Johannes & Sarnow, 1998; Lamphear et al., 1995; Pelletier & Sonenberg, 1988). IRES sequences are complex RNA scaffolds that interact with the translational initiation machinery and initiate the translation process without the 5′ cap (Johannes & Sarnow, 1998). Another mechanism of cap-independent translational initiation is mediated by the m6A that interacts with YTH domain family protein 3 (YTHD3) and recruits eIF4G2 to start the translation (Coots et al., 2017; Jiang et al., 2021; Meyer et al., 2015). The m6A site in the 5′ UTR initiates the ribosome scanning and subsequent selection of start codon for translation initiation (Meyer et al., 2015).

Due to the lack of the 5′ cap and the poly-A tail, circRNAs were believed to be noncoding in nature. Some of the initial studies could not validate the association of circRNAs with the polyribosomes and concluded that circRNAs might not be translated (Guo et al., 2014; Jeck et al., 2013; Schneider et al., 2016). Recent evidence suggested that some cir-cRNAs are associated with polyribosomes and contain ORFs, IRES elements, m6A modified nucleotide sequences that are critical for cap-independent translation initiation (Figure 1) (Legnini et al., 2017; Pamudurti et al., 2017; Yang et al., 2017). These pieces of evidence indicate that the cap-independent translation mechanisms possibly mediate the translation of circRNAs. The first report published in 1995 suggested that circRNA can initiate translation through IRES (C. Y. Chen & Sarnow, 1995). A recent study estimated that about 15% of circRNA in HEK293 cells co-sediment with polyribosomes implying their translation potential and association with ribosomes (Pamudurti et al., 2017; Ragan et al., 2019). Also, polyribosome profiling studies identified circRNA back-splicing junction sequences among the ribosome protected fragments (RPFs), further confirming the coding potential of circRNAs (Legnini et al., 2017; Pamudurti et al., 2017; van Heesch et al., 2019). From 2017 to date, a handful of circRNAs have been reported to encode functional proteins (Table 1). These results strongly indicate that many more endogenous circRNAs with coding potential remain to be discovered.

Figure 1. The mechanisms of cap-independent translation of circRNAs.

Figure 1

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(a) CircRNAs with IRES can initiate translation by interacting with the translation initiation complex. (b) The m6A modifications on circRNA can associate with YTHD3 and recruit the translation initiation complex to initiate the translation

Table 1. List of translated circRNAs and their circ-proteins.

circRNAs Cell type/tissue Cap-independent translation mechanism Protein size Function References
circZNF609 myoblast IRES 250 aa Proliferation of myoblast Legnini et al. (2017)
circMbl1 Drosophila head IRES 10 kDa - Pamudurti et al. (2017)
circMbl3 Drosophila head IRES 37 kDa - Pamudurti et al. (2017)
circSfl Drosophila head and muscle - 25 kDa Increases drosophila lifespan Weigelt et al. (2020)
circβ-catenin Hepatocellular carcinoma cells IRES 370 aa Activates Wnt/β-catenin signaling by inhibiting the ubiquitination of β-catenin W. C. Liang et al. (2019)
circPPP1R12A Colon cells IRES 73 aa Activates hippo-YAP signaling pathway X. Zheng, Chen, et al. (2019)
circ-SHPRH Glioblastoma cells IRES 146 aa Protect full-length SHPRH from proteasome-mediated degradation M. Zhang, Huang, et al. (2018)
circPINTexon2 Glioblastoma cells IRES 87 aa Inhibits transcription elongation Zhang, Zhao, et al. (2018)
circ-AKT3 Glioblastoma cells IRES 174 aa Inhibits tumorigenicity X. Xia et al. (2019)
circ-FBXW7 Glioblastoma cells, TNBC IRES 185 aa Inhibition of c-Myc-mediated proliferation Yang et al. (2018); Ye et al. (2019)
circGprc5a Bladder cancer - - Promote bladder cancer metastasis Gu et al. (2018)
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4. Coding Circular RNAS and Their Proteins

The role of circRNAs as miRNA and RBP sponge has been well characterized in normal physiology and several pathologies (Panda, Grammatikakis, et al., 2017). Recent work on circRNA functions has discovered many surprises, including the association of circRNAs with polyribosomes and their translation into proteins through cap-independent mechanism (Pamudurti et al., 2017; van Heesch et al., 2019; Yang et al., 2017) (Table 1; Figure 2). The mechanism of translation of reported circRNAs and the function of the circ-proteins are discussed below.

Figure 2. Protein-coding circRNAs and their circ-proteins in various tissues or disease models.

Figure 2

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4.1. circZNF609

The exon 2 of zinc-finger protein 609 (ZNF606) pre-mRNA generates a 874 nucleotide long cytoplasmic circular ZNF609 (circZNF609) by backsplicing. Interestingly, circZNF609/circZfp609 was conserved in human muscle myoblasts and mouse C2C12 cells (Legnini et al., 2017). Legnini et al. discovered that the endogenous circZNF609 is associated with polyribosomes and generates a protein through splicing-dependent and IRES-mediated translation mechanisms (Figure 2). Furthermore, the circ-protein of circZNF609 uses the same AUG start codon as the linear mRNA and a stop codon three nucleotides downstream of the backsplice junction generating a 250 amino-acid (aa) protein. Overexpression of circZNF609 with 3xFLAG confirmed the translation of another protein from an in-frame AUG present 150 nt downstream of the first AUG. They found that circ-protein generated from circZNF609 regulates muscle cell proliferation (Legnini et al., 2017).

4.2. circMbl

Another study performed the ribosome footprinting assay in the Drosophila heads and identified a group of ribosome-associated circRNAs (ribo-circRNAs), including circRNAs generated from the exon 2 to exon 8 of muscleblind gene(circMbl) (Pamudurti et al., 2017). Interestingly, circMbl isoforms contain the same translation start site as the Mbl mRNA and are translated through the IRES activity of the UTR sequence of circMbl. Mass spectrometry analysis from Drosophila head extracts confirmed the expression of 10 and 37 kDa proteins generated through cap-independent translation from circMbl1 and circMbl3 isoforms, respectively (Pamudurti et al., 2017).

4.3. circSfl

Weigelt et al. reported that the sulfateless (Sfl) gene has two splice variants RA and RB, where RB lacks the 37-bp exon 2 in the 5′ UTR. The exon 3 of Sfl RA (exon 2 of RB) generates the circular circSfl, which contains an ORF with the same start codon of the Sfl gene and a stop codon immediately after the backsplice junction. Interestingly, upregulation of circSfl expression in Drosophila heads of dilp 2–3,5 mutants positively correlates with Sfl RB expression, but not with Sfl RA. In addition, circSfl is upregulated in the Drosophila brain and muscle of long-lived insulin mutants without altered expression of Sfl RA and RB (Weigelt et al., 2020). Interestingly, circSfl overexpression alone is sufficient to increase the lifespan of flies and translate into a 25 kDa protein that shares the N-terminus of the full-length Sulfateless protein (Weigelt et al., 2020).

4.4. circβ-catenin

Liang et al. reported that a 1129 nucleotide long circular RNA, circ-0004194 (circβ-catenin) was generated from six exons (exon 2 to exon 7) of the β-catenin gene. The circβ-catenin was found to be upregulated in the liver cancer tissues and localized into the cytoplasm. Interestingly, circβ-catenin translates through IRES-mediated translation into a novel 370 aa protein (circβ-catenin-370aa) that starts with the same AUG as the linear β-catenin mRNA (W. C. Liang et al., 2019). The authors show that circβ-catenin-370aa expression promotes liver cell growth and malignant phenotypes by stabilizing β-catenin through inhibition of GSK3β-induced β-catenin phosphorylation and degradation.

4.5. circPPP1R12A

Another exciting study discovered an 1138 nucleotide long hsa_circ_0000423 (termed as circPPP1R12A) generated from the exon 24 and exon 25 of PPP1R12A pre mRNA. Moreover, circPPP1R12A was significantly upregulated in colon cancer tissues and is critical for the malignant phenotype (X. Zheng, Chen, et al., 2019). circPPP1R12A contains an ORF from 367 to 585 nt that encodes a novel 73 aa polypeptide (circPPP1R12A-73aa) confirmed by LC–MS/MS. Furthermore, circPPP1R12A-73aa, not circPPP1R12A, enhances colon cancer growth and metastasis by activating the Hippo-YAP signaling pathway.

4.6. circ-SHPRH

Another study identified an abundantly expressed circRNA in the human brain generated from the exon 26 to exon 29 of SNF2 histone linker PHD RING helicase (SHPRH) and named circ-SHPRH. The 440 nucleotide long circ-SHPRH contains an ORF, which has an overlapping start-stop codon and translates into a 146 aa polypeptide (SHPRH-146aa) through IRES-mediated mechanisms (M. Zhang, Huang, et al., 2018). The SHPRH-146aa was downregulated in most of the glioblastoma tissue samples compared with the adjacent normal tissue. Overexpression of the SHPRH-146aa in the glioblastoma cells suppresses tumorigenic activity by protecting the endogenous SHPRH from proteasome-mediated degradation.

4.7. circPINTexon2

Another study by Zhang et al. identified a 1084 nucleotide long circRNA (hsa_circ-0082389) generated from the exon 2 of long intergenic non-protein-coding RNA p53-induced transcript (LINC-PINT) and termed as circPINTexon2. circPINTexon2 is primarily localized in the cytoplasmic fractions of human neural stem cells and downregulated in cell lines of brain tumor initiating cells. Interestingly, ribosome nascent-chain complex-bound RNA sequencing (RNC-seq) identified an 87 aa polypeptide (PINT-87aa) encoded by circPINTexon2. Moreover, circPINTexon2 contains an IRES that promotes cap-independent translation of PINT-87aa from circPINTexon2, but not linear LINC-PINT (M. Zhang, Zhao, et al., 2018). This study found that PINT-87aa inhibits glioblastoma cell proliferation by interacting with polymerase-associated factor complex (PAF1c) that suppresses transcriptional elongation of various oncogenes.

4.8. circ-AKT3

Xia et al. reported that circ-AKT3 (hsa_circ_0017250) with a length of 524 nucleotides is generated from exon 3 to exon 7 of AKT3 gene. The circ-AKT3 is downregulated in the glioblastoma compared with normal brain tissues. Interestingly, ORF with overlapping start-stop codon of circ-AKT3 uses IRES-mediated translation to produce a novel 174 aa polypeptide termed AKT3-174aa (X. Xia et al., 2019). The overexpression of AKT3-174aa in glioblastoma cells reduced the radiation resistance and cell proliferation. The authors suggest that competitive interaction of AKT3-174aa with phosphorylated PDK1 leads to reduced AKT-thr308 phosphorylation that negatively modulates the PI3K/AKT regulatory axis (X. Xia et al., 2019).

4.9. circ-FBXW7

The 620 nucleotide long novel circ_022705 is generated from the exon 3 and exon 4 of the FBXW7 gene and termed circ-FBXW7. circ-FBXW7 is downregulated in glioma samples and encodes a 185 aa protein in the brain tissues through the IRES-mediated translation termed FBXW7-185aa (Yang et al., 2018). Both the circ-FBXW7 and circ-FBXW7-185aa are downregulated in glioblastoma compared with normal adjacent tissue. Moreover, FBXW7-185aa expression positively correlates with glioblastoma patient survival and negatively correlates with malignant phenotypes by inhibiting USP28-induced c-Myc stabilization (Yang et al., 2018). Another exciting study by Ye et al. suggested that the FBXW7-185aa expression inhibited the tumorigenic properties of triple-negative breast cancer (TNBC) by increasing the abundance of FBXW7 and inducing c-Myc degradation (Ye et al., 2019).

4.10. circGprc5a

Recently, Gu et al. reported that hsa_circ_02838 is upregulated in bladder tumors and cancer stem cells. Since hsa_circ_02838-encoded circ-protein interacts with Gprc5a, the authors termed this circRNA as circGprc5a. Interestingly, circGprc5a was found to translate into a peptide termed as circGprc5a-peptide (Gu et al., 2018). Knockdown of circGprc5a inhibited the tumorigenic property of bladder CSCs through circGprc5a-peptide that interacts with the surface protein Gprc5a.

5. Methods to Study the Translation of Circular RNA

Recent studies have demonstrated the translation of circRNAs into proteins, which are involved in critical cellular functions. To better understand how such novel circRNA mediated gene regulation contributes to translatome complexity, comprehensive identification of circRNAs with protein-coding potential becomes inevitable. Here we outline a methodological pipeline for systematic identification and characterization of coding-circRNAs and circ-proteins.

5.1. CircRNA expression analysis in cells/tissue of interest

Previous studies reported that circRNAs could be translated through cap-independent translation mechanisms (C. Y. Chen & Sarnow, 1995; Pamudurti et al., 2017; Yang et al., 2017). Unless the circRNA of interest is reported to be translated in previous studies, an unbiased approach may be taken to identify and characterize the translating circRNAs in a given pathophysiological condition. CircRNAs are identified from RNA-seq data using various computational tools developed in recent years (L. Chen et al., 2021; X. O. Zhang et al., 2016; Zheng, Ji, et al., 2019). However, circRNA enrichment before RNA-seq and specific circRNA analysis tools such as CIRCexplorer2, CIRI2, circAST, and FcircSEC, can provide the spliced sequence of circRNAs (Hossain et al., 2020; J. Wu et al., 2019; X. O. Zhang et al., 2016; Y. Zheng, Ji, et al., 2019). After identifying circRNAs and their abundance, it is crucial to identify all the circRNAs with translation potential.

5.2. High-throughput identification of coding circRNAs

One of the approaches to identify translatable circRNAs is to screen circRNAs associated with the polyribosomes (Figure 3). Polyribosome profiling estimates the translational output of any transcript depending on the degree of association with different polysome fractions (Panda, Martindale, & Gorospe, 2017). Polyribosome fractionation followed by isolation and enrichment of circRNAs in different fractions and high-throughput sequencing could provide a list of potentially translatable circRNAs (Bartsch et al., 2018; Yang et al., 2017). Furthermore, Ribosome footprinting followed by RNA-seq (Ribo-seq) of ribosome protected fragments (RPF) could identify the precise position of an active ribosome on the translating RNAs (Michel & Baranov, 2013; van Heesch et al., 2019; H. Wang et al., 2019). RPFs on circRNA bac-ksplice junction help in identification of the translating circRNAs as well as help predict their translational efficiency and regulation (Michel & Baranov, 2013; van Heesch et al., 2019). One of the abundant RNA modifications, m6A, promotes cap-independent translation initiation (Jiang et al., 2021). RNA immunoprecipitation with m6A antibody followed by enrichment of circRNAs and RNA-seq can identify circRNAs having m6A sites. CircRNAs with m6A sites identified through RNA-seq could provide additional data supporting putative translatable circRNAs (Coots et al., 2017; Jiang et al., 2021; Yang et al., 2017).

Figure 3. Methods pipeline for systematic identification and characterization of protein-coding circRNAs and their circ-proteins.

Figure 3

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Currently, a few tools are available to identify coding circRNAs from high-throughput RNA-seq or Ribo-seq data sets (Table 2). In 2017, CircPro was first developed as an integrated circRNA detection pipeline designed for finding translatable junction reads from RNA-seq data (Meng et al., 2017). CircPro utilizes total or non-poly-A RNA-seq datasets for circRNA identification, followed by mapping onto Ribo-seq reads and parallel assessment using the coding potential calculator approach based on the presence of ORFs. CircPro provides an output file containing information about the genomic position, coding classification, CPC score, ORF length, and junction read count from RNA-seq/Ribo-seq for each putative coding circRNA (Meng et al., 2017). CircCode is another tool for comprehensively predicting circRNA coding ability using the Ribo-seq/RPF-based approach irrespective of the presence of conventional ORFs (Sun & Li, 2019). Recently, a user-friendly R package, Rcirc, was developed that can identify circRNAs from RNA-seq data as well as helps in identifying the coding potential of circRNAs and their visualization (Sun et al., 2020).

Table 2. List of software or web tools required for identification of protein-coding circRNAs.

Tools Description Link References
RPFdb v2.0 An open-source repository of ribosome profiling data sets http://sysbio.gzzoc.com/rpfdb/ H. Wang et al. (2019)
CircPro A tool to identify protein-coding circRNAs using Ribo-Seq data http://bis.zju.edu.cn/CircPro/ Meng et al. (2017)
CircCode An advanced command-line-based tool to identify the coding circRNAs https://github.com/PSSUN/CircCode Sun & Li (2019)
Rcirc R package for detecting circRNAs and their coding potential https://github.com/PSSUN/Rcirc Sun et al. (2020)
ORF Finder Finds all possible ORFs in a given sequence https://www.ncbi.nlm.nih.gov/orffinder/
CPC2 Determine the protein-coding potential of a given transcript http://cpc2.cbi.pku.edu.cn Kang et al. (2017)
CPAT An align-free algorithm to analyze the coding potential of a given sequence http://code.google.com/p/cpat/ L. Wang et al. (2013)
PhyloCSF Identify conserved protein-coding sequences http://compbio.mit.edu/PhyloCSF Lin et al. (2011)
TISdb Database of TIS positions and ORFs based on GTI-seq data http://tisdb.human.cornell.edu/ Wan and Qian (2014)
preTIS Identify non-canonical translation initiation sites in the 5' UTR http://service.bioinformatik.uni-saarland.de/pretis Reuter et al. (2016)
TITER Identify all ORFs with AUG as well as non-AUG start codons https://github.com/zhangsaithu/titer S. Zhang et al. (2017)
IRESite Database of experimentally validated viral and cellular IRES regions http://www.iresite.org Mokrejs et al. (2010)
IRESbase Database of experimentally verified IRES elements http://reprod.njmu.edu.cn/cgi-bin/iresbase/index.php Zhao et al. (2020)
REPIC A database of N6-methyladenosine modifications https://repicmod.uchicago.edu/repic/ S. Liu et al. (2020)
circAtlas Database of circRNAs with IRES and ORF information http://circatlas.biols.ac.cn/ W. Wu et al. (2020)
circBank Database of human circRNAs m6A and proteincoding potential information http://www.circbank.cn/ M. Liu et al. (2019)
circRNADb Database of human circRNAs that includes information about translatable circRNAs http://reprod.njmu.edu.cn/circrnadb X. Chen et al. (2016)
TransCirc A database of human circRNAs with protein-coding potential https://www.biosino.org/transcirc/ W. Huang et al. (2021)
riboCirc Database of translatable circRNAs and their encoded proteins http://www.ribocirc.com/index.html H. Li et al. (2021)
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5.3. Characterization of coding circRNAs

Although the above high-throughput RNA-seq and bioinformatics tools can identify a large number of potentially translatable circRNAs, a subset of abundant circRNAs may be selected for further analysis. Once a subset of translating cir-cRNAs are identified, other features such as ORF, CPC, IRES, and m6A sites need to be verified before conducting further experiments to reduce the false positives (Table 2). To find the coding potential of the selected circRNAs, the circRNA mature sequence can be placed in tandem repeats (×2 or ×3) to get the backsplice junction sequences that are critical for identifying circRNA specific peptides. ORFs spanning the circRNA backsplice junction can be identified using ORF Finder, a graphical tool to identify all possible ORFs with the start codon or alternative initiation codons. CPC2 is another algorithm that can identify the coding potential of the given sequence using the pairwise homology search for protein features (Kang et al., 2017). Coding potential assessment tool (CPAT) uses an alignment-free algorithm to quickly and accurately identify the coding potential of the given sequences (L. Wang et al., 2013). PhyloCSF is a multispecies sequence alignment tool to identify a conserved protein-coding region using formal statistical comparison of phylogenetic codon models (Lin et al., 2011). TISdb is a database of translation initiation sites (TIS) using the global translation initiation sequencing (GTI-seq) data, which can reveal an accurate and unambiguous translation initiation site on a given sequence and the associated ORFs (Wan & Qian, 2014). Since the AUG-methionine translation initiation site is not always the start for all eukaryotic proteins, ORFs generated from non-AUG start codons may be considered for circRNAs. The GTI-seq data was used to develop preTIS software to predict noncanonical ORFs starting with AUG or its near-cognate codons in the 5′ UTR (Reuter et al., 2016). Recently, another tool called TITER (Translation Initiation siTE detectoR) has been developed for accurate prediction of the ORFs with AUG as well as alternative non-AUG TISs using GTI-seq and quantitative translation initiation sequencing (QTI-seq) (S. Zhang et al., 2017). After analyzing the coding potential of the circRNA of interest, it is essential to identify features that help in cap-independent translation, such as IRES and m6A modifications. Endogenous IRES elements in shortlisted cir-cRNAs can be checked using IRESite and IRESbase (Mokrejs et al., 2010; Zhao et al., 2020). Furthermore, the presence of m6A modifications on a target circRNA can be searched in the REPIC (RNA EPItranscriptome Collection) database (S. Liu et al., 2020). Although any of the above tools can identify circRNAs with translation potential, using multiple tools to analyze the coding potential of target circRNAs can lead to accurate identification of translatable circRNAs.

Besides individual software to analyze the coding potential of circRNAs, several databases have been developed that include a list of circRNAs with protein-coding possibilities. CircRNAs with the potential to code for circ-proteins based on the presence of IRES sequences, ORFs, mass spectrometry evidence has been listed in a few publications and databases, including circInteractome, circBank, circRNADd, and circAtlas (X. Chen et al., 2016; Dudekula et al., 2016; M. Liu et al., 2019; W. Wu et al., 2020). The TransCirc database of human circRNAs with translation potential was recently developed by integrating seven pieces of evidence of circRNA translation, including ribosome profiling, translation initiation site map, IRES, m6A modification, ORF, sequence compositions score, and mass spectrometry (MS) data (W. Huang et al., 2021). TransCirc is an excellent resource for identifying translatable human circRNAs and their circRNA-encoded proteins. Similarly, riboCIRC is another database of protein-coding circRNAs that enlists computationally predicted, experimentally validated, and cross-species conserved translatable circRNAs (H. Li et al., 2021). Although TransCirc and riboCIRC provide extensive information, including circRNA sequence, coding-potential, localization, structure, and potential function of the circ-proteins, it is essential to validate the translation of circ-proteins and their role in normal physiology and pathological conditions.

5.4. Elucidating biological functions of circ-proteins

It is worth noting that one cannot conclude the translation of circRNA and predict the function of circ-proteins identified using computational tools. The translatability of a circRNA must be confirmed by repeating the polyribosome fractionation with or without EDTA treatment followed by RT-qPCR analysis of circRNAs in various fractions (Panda, Martindale, & Gorospe, 2017; Pandey et al., 2020). Direct evidence of circRNA-encoded peptides can be studied by performing mass spectrometry and analyzing peptides derived from the backsplice junction sequence (Legnini et al., 2017; W. C. Liang et al., 2019; Pamudurti et al., 2017). Furthermore, the antibody against the circ-protein must be used for western blot analysis to study the size and differential expression of the circRNA-proteins. Direct interaction of endogenous proteins or RNAs with circ-protein can be checked by pulldown of the circ-protein complex using an antibody that recognizes circ-protein (W. C. Liang et al., 2019; Pandey et al., 2020; M. Zhang, Zhao, et al., 2018). The proteins associated with circ-protein can be identified by mass spectrometry or western blotting. The RNA molecules interacting with the circ-protein can be identified with RNA sequencing or RT-qPCR analysis. The physiological significance of the circ-protein can be analyzed by overexpression or silencing of the protein-coding circRNA (Pandey et al., 2020). In sum, with the advent of additional biochemical methods and computational tools to identify translatable circRNAs, we hope the methods pipeline described here will help in the accurate identification of protein-coding circRNAs and the physiological relevance of their circ-proteins.

6. Discussions and Closing Remarks

Numerous studies in the last decade established that circRNAs can regulate gene expression by modulating transcription, splicing, translation, and protein function (Panda, Grammatikakis, et al., 2017). Although the number and novel functions of circRNAs are expanding, most known circRNAs remain to be characterized (Vromman et al., 2021). In the last couple of years, many circRNAs have been identified to have IRES, m6A modification, and ribosome-protected sequences, suggesting their translation by cap-independent mechanisms (Pamudurti et al., 2017; van Heesch et al., 2019; Yang et al., 2017). Although mRNAs are linear, the interaction of cap-binding protein eIF4G with PABP promote the circularization of mRNAs for efficient translation through the closed-loop assisted re-initiation (CLAR) or ribosome recycling mechanism (Gallie, 1991; Wells et al., 1998). Since circRNAs are inherently circular, successive re-initiation of circRNA translation by CLAR mechanism could be an efficient way to produce a higher quantity of protein for a longer time. Given that circRNAs are stable and closed-loop structures, engineered exogenous circRNA containing ORF for a gene of interest along with an IRES to start the cap-independent translation could be a novel tool for future gene therapy (Meganck et al., 2021; Wesselhoeft et al., 2018). The studies described in this review suggest that circ-pro-teins regulate various cellular events and are involved in disease development. However, the current research faces several challenges which need to be addressed in the future.

First, most circRNA annotation tools identify the backsplice junction, and the full-length sequence is assumed by considering all the annotated exons. However, the mature spliced sequence of multiexonic circRNA may vary due to alternative splicing depending on cell type or conditions (X. O. Zhang et al., 2016). Changes in the sequence of circRNA can give rise to translation of different size circ-proteins with different function. The total RNA must be enriched for cir-cRNAs before RNA-seq library preparation followed by circRNA annotation with tools like CIRCexplorer2 and CIRI-full using de novo annotation module, which can more accurately identify the full-length mature sequence of circRNAs (X. O. Zhang et al., 2016; Y. Zheng, Ji, et al., 2019). In addition, the circRNA full-length PCR method can be used to validate the full-length sequence and identify the expression of circRNA splice-variants with identical backsplice junction sequence (Das et al., 2019). Precise identification of full-length circRNA sequence and the splice variants will help in accurate prediction of circ-proteins generated from them.

Second, the information on the presence of IRES and their associated RBPs promoting circRNA translation is lacking. Several RBPs such as HuR and PTB have been shown to interact with IRES and modulate cap-independent translation (Martinez-Salas et al., 2013). Since several RBPs interact with circRNAs, there is a possibility of enhanced cap-independent translation through IRES trans-acting factors (ITAFs), which remains unexplored at present (Dudekula et al., 2016; A. Huang et al., 2020; Martinez-Salas et al., 2013). Comprehensive databases and computational tools need to be developed to identify IRES in the circRNA sequences. In addition, predicting the association of circRNAs with ITAFs will help predict the translation ability of a specific circRNAs.

Third, it has been reported that the canonical AUG-methionine translation initiation site is not always the start for all eukaryotic proteins (Kearse & Wilusz, 2017). However, most ORF or coding-potential prediction tools use AUG as the start codon. Interestingly, non-AUG translation is regulated by the translation factor eIF2A, nucleotide repeat sequences, and the secondary structures of mRNA. Computational tools like TITER may be used to find ORFs with AUG and non-AUG start site during the analysis of protein-coding circRNAs to avoid erroneous filtering of circRNAs with non-AUG translation (S. Zhang et al., 2017). In addition, GTI-seq and QTI-seq in cells of interest need to be used with the computational tools to generate a custom database of all possible canonical and non-canonical ORFs generated from circRNA to use in mass spectrometry data analysis.

The fourth and the most critical challenge is the identification of micropeptides translated from circRNAs. Although mass spectrometry combined with Ribo-seq data has been improved significantly and has become the gold standard to identify proteins, many MS fragment spectra are unidentified, which could be unannotated circ-proteins or micropeptides translated from circRNAs or other RNAs (Andrews & Rothnagel, 2014; Makarewich & Olson, 2017). Due to the inherently small size of micropeptides, they are often lost or over-digested during the sample preparation and remain unidentified in the MS data analysis. Size selection, enrichment of small size micropeptides, and careful selection of proteases followed by LC–MS/MS (liquid chromatography followed by tandem mass spectrometry) may improve detection of low abundant and small size micropeptides. Furthermore, matching the MS spectra with the custom database of circRNA ORFs with both AUG and non-AUG start codons may successfully identify novel circ-proteins.

Here, we discussed the computational tools and molecular methods required to systematically identify protein-coding circRNAs and study the function of circ-proteins. We hope the methods pipeline described here will stimulate the use of similar strategies to identify and characterize circ-proteins. We expect that many more circRNA-encoded proteins will be discovered with the emerging RNA technologies in the next few years. It is of utmost importance to understand the molecular mechanisms of circRNA translation initiation and these novel proteins' physiological relevance. We fore-see that an increasing number of studies on circRNA translation in the coming years will discover the hidden proteome and enlighten us on the importance of these novel proteins in human health and disease development.

Acknowledgements

The authors thank Sharmishtha Shyamal and Aniruddha Das for the critical reading of this manuscript. This work was supported by intramural funding from the Institute of Life Sciences, Department of Biotechnology, India and the DBT/Wellcome Trust India Alliance Fellowship (grant number: IA/I/18/2/504017) awarded to Amaresh Chandra Panda.

Funding information

DBT/Wellcome Trust India Alliance Fellowship, Grant/Award Number: IA/ I/18/2/504017; Institute of Life Sciences, Department of Biotechnology, India

Footnotes

Author contributions

Tanvi Sinha: Conceptualization; visualization; writing - original draft; writing-review & editing. Chirag Panigrahi: Conceptualization; visualization; writing - original draft; writing-review & editing. Debojyoti Das: Conceptualization; visualization; writing - original draft; writing-review & editing. Amaresh Chandra Panda: Conceptualization; funding acquisition; supervision; visualization; writing-review & editing.

Conflict of Interest

The authors have declared no conflicts of interest for this article.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

References

  1. Abdelmohsen K, Panda AC, Munk R, Grammatikakis I, Dudekula DB, De S, Kim J, Noh JH, Kim KM, Martindale JL, Gorospe M. Identification of HuR target circular RNAs uncovers suppression of PABPN1 translation by CircPABPN1. RNA Biology. 2017;14(3):361–369. doi: 10.1080/15476286.2017.1279788. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Andrews SJ, Rothnagel JA. Emerging evidence for functional peptides encoded by short open reading frames. Nature Reviews Genetics. 2014;15(3):193–204. doi: 10.1038/nrg3520. [DOI] [PubMed] [Google Scholar]
  3. Bartsch D, Zirkel A, Kurian L. In: Circular RNAs: Methods and protocols. Dieterich C, Papantonis A, editors. Springer; New York: 2018. Characterization of circular RNAs (circRNA) associated with the translation machinery; pp. 159–166. [DOI] [PubMed] [Google Scholar]
  4. Capel B, Swain A, Nicolis S, Hacker A, Walter M, Koopman P, Goodfellow P, Lovell-Badge R. Circular transcripts of the testis-determining gene Sry in adult mouse testis. Cell. 1993;73(5):1019–1030. doi: 10.1016/0092-8674(93)90279-y. [DOI] [PubMed] [Google Scholar]
  5. Chen CY, Sarnow P. Initiation of protein synthesis by the eukaryotic translational apparatus on circular RNAs. Science. 1995;268(5209):415–417. doi: 10.1126/science.7536344. [DOI] [PubMed] [Google Scholar]
  6. Chen L, Wang C, Sun H, Wang J, Liang Y, Wang Y, Wong G. The bioinformatics toolbox for circRNA discovery and analysis. Briefings in Bioinformatics. 2021;22(2):1706–1728. doi: 10.1093/bib/bbaa001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Chen LL, Yang L. Regulation of circRNA biogenesis. RNA Biology. 2015;12(4):381–388. doi: 10.1080/15476286.2015.1020271. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chen X, Han P, Zhou T, Guo X, Song X, Li Y. circRNADb: A comprehensive database for human circular RNAs with protein-coding annotations. Science Reports. 2016;6:34985. doi: 10.1038/srep34985. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Cocquerelle C, Mascrez B, Hetuin D, Bailleul B. Mis-splicing yields circular RNA molecules. The FASEB Journal. 1993;7(1):155–160. doi: 10.1096/fasebj.7.1.7678559. [DOI] [PubMed] [Google Scholar]
  10. Coots RA, Liu XM, Mao Y, Dong L, Zhou J, Wan J, Zhang X, Qian SB. M(6)a facilitates eIF4F-independent mRNA translation. Molecular Cell. 2017;68(3):504–514.:e507. doi: 10.1016/j.molcel.2017.10.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Das A, Gorospe M, Panda AC. The coding potential of circRNAs. Aging (Albany NY) 2018;10(9):2228–2229. doi: 10.18632/aging.101554. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Das A, Rout PK, Gorospe M, Panda AC. Rolling circle cDNA synthesis uncovers circular RNA splice variants. International Journal of Molecular Sciences. 2019;20(16):3988. doi: 10.3390/ijms20163988. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Du WW, Fang L, Yang W, Wu N, Awan FM, Yang Z, Yang BB. Induction of tumor apoptosis through a circular RNA enhancing Foxo3 activity. Cell Death and Differentiation. 2017;24(2):357–370. doi: 10.1038/cdd.2016.133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Dudekula DB, Panda AC, Grammatikakis I, De S, Abdelmohsen K, Gorospe M. CircInteractome: A web tool for exploring circular RNAs and their interacting proteins and microRNAs. RNA Biology. 2016;13(1):34–42. doi: 10.1080/15476286.2015.1128065. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Eger N, Schoppe L, Schuster S, Laufs U, Boeckel JN. Circular RNA Splicing. Advances in Experimental Medicine and Biology. 2018;1087:41–52. doi: 10.1007/978-981-13-1426-1_4. [DOI] [PubMed] [Google Scholar]
  16. Gallie DR. The cap and poly(A) tail function synergistically to regulate mRNA translational efficiency. Genes & Development. 1991;5(11):2108–2116. doi: 10.1101/gad.5.11.2108. [DOI] [PubMed] [Google Scholar]
  17. Gardner EJ, Nizami ZF, Talbot CC, Jr, Gall JG. Stable intronic sequence RNA (sisRNA), a new class of noncoding RNA from the oocyte nucleus of Xenopus tropicalis. Genes & Development. 2012;26(22):2550–2559. doi: 10.1101/gad.202184.112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Glazar P, Papavasileiou P, Rajewsky N. circBase: a database for circular RNAs. RNA. 2014;20(11):1666–1670. doi: 10.1261/rna.043687.113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Gu C, Zhou N, Wang Z, Li G, Kou Y, Yu S, Feng Y, Chen L, Yang J, Tian F. circGprc5a promoted bladder oncogenesis and metastasis through Gprc5a-targeting peptide. Molecular Therapy-Nucleic Acids. 2018;13:633–641. doi: 10.1016/j.omtn.2018.10.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Guo JU, Agarwal V, Guo H, Bartel DP. Expanded identification and characterization of mammalian circular RNAs. Genome Biology. 2014;15(7):409. doi: 10.1186/s13059-014-0409-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Hansen TB, Jensen TI, Clausen BH, Bramsen JB, Finsen B, Damgaard CK, Kjems J. Natural RNA circles function as efficient microRNA sponges. Nature. 2013;495(7441):384–388. doi: 10.1038/nature11993. [DOI] [PubMed] [Google Scholar]
  22. Hossain MT, Peng Y, Feng S, Wei Y. FcircSEC: An R package for full length circRNA sequence extraction and classification. International Journal of Genomics. 2020;2020:9084901. doi: 10.1155/2020/9084901. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hsu MT, Coca-Prados M. Electron microscopic evidence for the circular form of RNA in the cytoplasm of eukaryotic cells. Nature. 1979;280(5720):339–340. doi: 10.1038/280339a0. [DOI] [PubMed] [Google Scholar]
  24. Huang A, Zheng H, Wu Z, Chen M, Huang Y. Circular RNA-protein interactions: Functions, mechanisms, and identification. Theranostics. 2020;10(8):3503–3517. doi: 10.7150/thno.42174. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Huang W, Ling Y, Zhang S, Xia Q, Cao R, Fan X, Fang Z, Wang Z, Zhang G. TransCirc: An interactive database for translatable circular RNAs based on multi-omics evidence. Nucleic Acids Research. 2021;49(D1):D236–D242. doi: 10.1093/nar/gkaa823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Jeck WR, Sorrentino JA, Wang K, Slevin MK, Burd CE, Liu J, Marzluff WF, Sharpless NE. Circular RNAs are abundant, conserved, and associated with ALU repeats. RNA. 2013;19(2):141–157. doi: 10.1261/rna.035667.112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Ji P, Wu W, Chen S, Zheng Y, Zhou L, Zhang J, Yang P, Zhao F. Expanded expression landscape and prioritization of circular RNAs in mammals. Cell Reports. 2019;26(12):3444–3460. doi: 10.1016/j.celrep.2019.02.078. [DOI] [PubMed] [Google Scholar]
  28. Jiang X, Liu B, Nie Z, Duan L, Xiong Q, Jin Z, Yang C, Chen Y. The role of m6A modification in the biological functions and diseases. Signal Transduction and Targeted Therapy. 2021;6(1):74. doi: 10.1038/s41392-020-00450-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Johannes G, Sarnow P. Cap-independent polysomal association of natural mRNAs encoding c-myc, BiP, and eIF4G conferred by internal ribosome entry sites. RNA. 1998;4(12):1500–1513. doi: 10.1017/s1355838298981080. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Kang YJ, Yang DC, Kong L, Hou M, Meng YQ, Wei L, Gao G. CPC2: A fast and accurate coding potential calculator based on sequence intrinsic features. Nucleic Acids Research. 2017;45:W12–W16. doi: 10.1093/nar/gkx428. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Kearse MG, Wilusz JE. Non-AUG translation: A new start for protein synthesis in eukaryotes. Genes & Development. 2017;31(17):1717–1731. doi: 10.1101/gad.305250.117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Kelly S, Greenman C, Cook PR, Papantonis A. Exon skipping is correlated with exon circularization. Journal of Molecular Biology. 2015;427(15):2414–2417. doi: 10.1016/j.jmb.2015.02.018. [DOI] [PubMed] [Google Scholar]
  33. Lamphear BJ, Kirchweger R, Skern T, Rhoads RE. Mapping of functional domains in eukaryotic protein synthesis initiation factor 4G (eIF4G) with picornaviral proteases. Implications for cap-dependent and cap-independent translational initiation. The Journal of Biological Chemistry. 1995;270(37):21975–21983. doi: 10.1074/jbc.270.37.21975. [DOI] [PubMed] [Google Scholar]
  34. Lee ECS, Elhassan SAM, Lim GPL, Kok WH, Tan SW, Leong EN, Tan SH, EWL C, Bhattamisra SK, Rajendran R, Candasamy M. The roles of circular RNAs in human development and diseases. Biomedicine & Pharmacotherapy. 2019;111:198–208. doi: 10.1016/j.biopha.2018.12.052. [DOI] [PubMed] [Google Scholar]
  35. Legnini I, Di Timoteo G, Rossi F, Morlando M, Briganti F, Sthandier O, Fatica A, Santini T, Andronache A, Wade M, Laneve P, et al. Circ-ZNF609 is a circular RNA that can be translated and functions in myogenesis. Molecular Cell. 2017;66(1):22–37. doi: 10.1016/j.molcel.2017.02.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Li H, Xie M, Wang Y, Yang L, Xie Z, Wang H. riboCIRC: A comprehensive database of translatable circRNAs. Genome Biology. 2021;22:79. doi: 10.1186/s13059-021-02300-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Li Z, Huang C, Bao C, Chen L, Lin M, Wang X, Zhong G, Yu B, Hu W, Dai L, Zhu P, et al. Exon-intron circular RNAs regulate transcription in the nucleus. Nature Structural & Molecular Biology. 2015;22(3):256–264. doi: 10.1038/nsmb.2959. [DOI] [PubMed] [Google Scholar]
  38. Liang D, Wilusz JE. Short intronic repeat sequences facilitate circular RNA production. Genes & Development. 2014;28(20):2233–2247. doi: 10.1101/gad.251926.114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Liang WC, Wong CW, Liang PP, Shi M, Cao Y, Rao ST, Tsui SK, Waye MM, Zhang Q, Fu WM, Zhang JF. Translation of the circular RNA circbeta-catenin promotes liver cancer cell growth through activation of the Wnt pathway. Genome Biology. 2019;20(1):84. doi: 10.1186/s13059-019-1685-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Lin MF, Jungreis I, Kellis M. PhyloCSF: A comparative genomics method to distinguish protein coding and non-coding regions. Bioinformatics. 2011;27(13):i275–i282. doi: 10.1093/bioinformatics/btr209. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Liu M, Wang Q, Shen J, Yang BB, Ding X. Circbank: A comprehensive database for circRNA with standard nomenclature. RNA Biology. 2019;16(7):899–905. doi: 10.1080/15476286.2019.1600395. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Liu S, Zhu A, He C, Chen M. REPIC: A database for exploring the N(6)-methyladenosine methylome. Genome Biology. 2020;21(1):100. doi: 10.1186/s13059-020-02012-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Makarewich CA, Olson EN. Mining for micropeptides. Trends in Cell Biology. 2017;27(9):685–696. doi: 10.1016/j.tcb.2017.04.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Martinez-Salas E, Lozano G, Fernandez-Chamorro J, Francisco-Velilla R, Galan A, Diaz R. RNA-binding proteins impacting on internal initiation of translation. International Journal of Molecular Sciences. 2013;14(11):21705–21726. doi: 10.3390/ijms141121705. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Meganck RM, Liu J, Hale AE, Simon KE, Fanous MM, Vincent HA, Wilusz JE, Moorman NJ, Marzluff WF, Asokan A. Engineering highly efficient backsplicing and translation of synthetic circRNAs. Molecular Therapy-Nucleic Acids. 2021;23:821–834. doi: 10.1016/j.omtn.2021.01.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Memczak S, Jens M, Elefsinioti A, Torti F, Krueger J, Rybak A, Maier L, Mackowiak SD, Gregersen LH, Munschauer M, Loewer A, et al. Circular RNAs are a large class of animal RNAs with regulatory potency. Nature. 2013;495(7441):333–338. doi: 10.1038/nature11928. [DOI] [PubMed] [Google Scholar]
  47. Meng X, Chen Q, Zhang P, Chen M. CircPro: An integrated tool for the identification of circRNAs with protein-coding potential. Bioinformatics. 2017;33(20):3314–3316. doi: 10.1093/bioinformatics/btx446. [DOI] [PubMed] [Google Scholar]
  48. Meyer KD, Patil DP, Zhou J, Zinoviev A, Skabkin MA, Elemento O, Pestova TV, Qian SB, Jaffrey SR. 5’ UTR m(6) a promotes cap-independent translation. Cell. 2015;163(4):999–1010. doi: 10.1016/j.cell.2015.10.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Michel AM, Baranov PV. Ribosome profiling: A hi-Def monitor for protein synthesis at the genome-wide scale. Wiley Interdisciplinary Reviews: RNA. 2013;4(5):473–490. doi: 10.1002/wrna.1172. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Mokrejs M, Masek T, Vopalensky V, Hlubucek P, Delbos P, Pospisek M. IRESite: A tool for the examination of viral and cellular internal ribosome entry sites. Nucleic Acids Research. 2010;38:D131–D136. doi: 10.1093/nar/gkp981. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Nigro JM, Cho KR, Fearon ER, Kern SE, Ruppert JM, Oliner JD, Kinzler KW, Vogelstein B. Scrambled exons. Cell. 1991;64(3):607–613. doi: 10.1016/0092-8674(91)90244-s. [DOI] [PubMed] [Google Scholar]
  52. Pamudurti NR, Bartok O, Jens M, Ashwal-Fluss R, Stottmeister C, Ruhe L, Hanan M, Wyler E, Perez-Hernandez D, Ramberger E, Shenzis S, et al. Translation of circRNAs. Molecular Cell. 2017;66(1):9–21. doi: 10.1016/j.molcel.2017.02.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Panda AC. In: Circular RNAs: Biogenesis and functions. Xiao J, editor. Springer; Singapore: 2018. Circular RNAs act as miRNA sponges; pp. 67–79. [DOI] [PubMed] [Google Scholar]
  54. Panda AC, Grammatikakis I, Munk R, Gorospe M, Abdelmohsen K. Emerging roles and context of circular RNAs. Wiley Interdisciplinary Reviews: RNA. 2017;8(2):e1386. doi: 10.1002/wrna.1386. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Panda AC, Martindale JL, Gorospe M. Polysome fractionation to analyze mRNA distribution profiles. Bio Protocol. 2017;7(3):e2126. doi: 10.21769/BioProtoc.2126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Pandey PR, Munk R, Kundu G, De S, Abdelmohsen K, Gorospe M. Methods for analysis of circular RNAs. Wiley Interdisciplinary Reviews: RNA. 2020;11(1):e1566. doi: 10.1002/wrna.1566. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Pelletier J, Sonenberg N. Internal initiation of translation of eukaryotic mRNA directed by a sequence derived from poliovirus RNA. Nature. 1988;334(6180):320–325. doi: 10.1038/334320a0. [DOI] [PubMed] [Google Scholar]
  58. Prats AC, David F, Diallo LH, Roussel E, Tatin F, Garmy-Susini B, Lacazette E. Circular RNA, the key for translation. International Journal of Molecular Sciences. 2020;21(22):8591. doi: 10.3390/ijms21228591. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Ragan C, Goodall GJ, Shirokikh NE, Preiss T. Insights into the biogenesis and potential functions of exonic circular RNA. Scientific Reports. 2019;9(1):2048. doi: 10.1038/s41598-018-37037-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Reuter K, Biehl A, Koch L, Helms V. PreTIS: A tool to predict non-canonical 5’ UTR translational initiation sites in human and mouse. PLoS Computational Biology. 2016;12(10):e1005170. doi: 10.1371/journal.pcbi.1005170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Salzman J, Chen RE, Olsen MN, Wang PL, Brown PO. Cell-type specific features of circular RNA expression. PLoS Genetics. 2013;9(9):e1003777. doi: 10.1371/journal.pgen.1003777. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Salzman J, Gawad C, Wang PL, Lacayo N, Brown PO. Circular RNAs are the predominant transcript isoform from hundreds of human genes in diverse cell types. PLoS One. 2012;7(2):e30733. doi: 10.1371/journal.pone.0030733. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Sanger HL, Klotz G, Riesner D, Gross HJ, Kleinschmidt AK. Viroids are single-stranded covalently closed circular RNA molecules existing as highly base-paired rod-like structures. Proceedings of the National Academy of Sciences of the United States of America. 1976;73(11):3852–3856. doi: 10.1073/pnas.73.11.3852. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Schneider T, Hung LH, Schreiner S, Starke S, Eckhof H, Rossbach O, Reich S, Medenbach J, Bindereif A. CircRNA-protein complexes: IMP3 protein component defines subfamily of circRNPs. Scientific Reports. 2016;6:31313. doi: 10.1038/srep31313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Starke S, Jost I, Rossbach O, Schneider T, Schreiner S, Hung LH, Bindereif A. Exon circularization requires canonical splice signals. Cell Reports. 2015;10(1):103–111. doi: 10.1016/j.celrep.2014.12.002. [DOI] [PubMed] [Google Scholar]
  66. Sun P, Li G. CircCode: A powerful tool for identifying circRNA coding ability. Frontiers in Genetics. 2019;10:981. doi: 10.3389/fgene.2019.00981. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Sun P, Wang H, Li G. Rcirc: An R package for circRNA analyses and visualization. Frontiers in Genetics. 2020;11:548. doi: 10.3389/fgene.2020.00548. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. van Heesch S, Witte F, Schneider-Lunitz V, Schulz JF, Adami E, Faber AB, Kirchner M, Maatz H, Blachut S, Sandmann CL, Kanda M, et al. The translational landscape of the human heart. Cell. 2019;178(1):242–260.:e229. doi: 10.1016/j.cell.2019.05.010. [DOI] [PubMed] [Google Scholar]
  69. Vromman M, Vandesompele J, Volders PJ. Closing the circle: Current state and perspectives of circular RNA databases. Briefings in Bioinformatics. 2021;22(1):288–297. doi: 10.1093/bib/bbz175. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Wan J, Qian SB. TISdb: A database for alternative translation initiation in mammalian cells. Nucleic Acids Research. 2014;42:D845–D850. doi: 10.1093/nar/gkt1085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Wang H, Yang L, Wang Y, Chen L, Li H, Xie Z. RPFdb v2.0: An updated database for genome-wide information of translated mRNA generated from ribosome profiling. Nucleic Acids Research. 2019;47:D230–D234. doi: 10.1093/nar/gky978. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Wang L, Park HJ, Dasari S, Wang S, Kocher JP, Li W. CPAT: Coding-potential assessment tool using an alignment-free logistic regression model. Nucleic Acids Research. 2013;41(6):e74. doi: 10.1093/nar/gkt006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Weigelt CM, Sehgal R, Tain LS, Cheng J, Esser J, Pahl A, Dieterich C, Grönke S, Partridge L. An insulin-sensitive circular RNA that regulates lifespan in Drosophila. Molecular Cell. 2020;79(2):268–279. doi: 10.1016/j.molcel.2020.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Wells SE, Hillner PE, Vale RD, Sachs AB. Circularization of mRNA by eukaryotic translation initiation factors. Molecular Cell. 1998;2(1):135–140. doi: 10.1016/s1097-2765(00)80122-7. [DOI] [PubMed] [Google Scholar]
  75. Wesselhoeft RA, Kowalski PS, Anderson DG. Engineering circular RNA for potent and stable translation in eukaryotic cells. Nature Communications. 2018;9(1):2629. doi: 10.1038/s41467-018-05096-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Wu J, Li Y, Wang C, Cui Y, Xu T, Wang C, Wang X, Sha J, Jiang B, Wang K, Hu Z, et al. CircAST: Fulllength assembly and quantification of alternatively spliced isoforms in circular RNAs. Genomics, Proteomics & Bioinformatics. 2019;17(5):522–534. doi: 10.1016/j.gpb.2019.03.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Wu W, Ji P, Zhao F. CircAtlas: An integrated resource of one million highly accurate circular RNAs from 1070 vertebrate transcriptomes. Genome Biology. 2020;21(1):101. doi: 10.1186/s13059-020-02018-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Xia S, Feng J, Lei L, Hu J, Xia L, Wang J, Xiang Y, Liu L, Zhong S, Han L, He C. Comprehensive characterization of tissue-specific circular RNAs in the human and mouse genomes. Briefings in Bioinformatics. 2017;18(6):984–992. doi: 10.1093/bib/bbw081. [DOI] [PubMed] [Google Scholar]
  79. Xia X, Li X, Li F, Wu X, Zhang M, Zhou H, Huang N, Yang X, Xiao F, Liu D, Yang L, et al. A novel tumor suppressor protein encoded by circular AKT3 RNA inhibits glioblastoma tumorigenicity by competing with active phosphoinositidedependent Kinase-1. Molecular Cancer. 2019;18(1):131. doi: 10.1186/s12943-019-1056-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Yang Y, Fan X, Mao M, Song X, Wu P, Zhang Y, Jin Y, Yang Y, Chen LL, Wang Y, Wong CC, et al. Extensive translation of circular RNAs driven by N(6)-methyladenosine. Cell Research. 2017;27(5):626–641. doi: 10.1038/cr.2017.31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Yang Y, Gao X, Zhang M, Yan S, Sun C, Xiao F, Huang N, Yang X, Zhao K, Zhou H, Huang S, et al. Novel role of FBXW7 circular RNA in repressing glioma tumorigenesis. Journal of the National Cancer Institute. 2018;110(3):304–315. doi: 10.1093/jnci/djx166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Ye F, Gao G, Zou Y, Zheng S, Zhang L, Ou X, Xie X, Tang H. circFBXW7 inhibits malignant progression by sponging miR-197-3p and encoding a 185-aa protein in triple-negative breast cancer. Molecular Therapy-Nucleic Acids. 2019;18:88–98. doi: 10.1016/j.omtn.2019.07.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Zhang M, Huang N, Yang X, Luo J, Yan S, Xiao F, Chen W, Gao X, Zhao K, Zhou H, Li Z, et al. A novel protein encoded by the circular form of the SHPRH gene suppresses glioma tumorigenesis. Oncogene. 2018;37(13):1805–1814. doi: 10.1038/s41388-017-0019-9. [DOI] [PubMed] [Google Scholar]
  84. Zhang M, Zhao K, Xu X, Yang Y, Yan S, Wei P, Liu H, Xu J, Xiao F, Zhou H, Yang X, et al. A peptide encoded by circular form of LINC-PINT suppresses oncogenic transcriptional elongation in glioblastoma. Nature Communications. 2018;9(1):4475. doi: 10.1038/s41467-018-06862-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Zhang S, Hu H, Jiang T, Zhang L, Zeng J. TITER: Predicting translation initiation sites by deep learning. Bioinformatics. 2017;33(14):i234–i242. doi: 10.1093/bioinformatics/btx247. [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Zhang XO, Dong R, Zhang Y, Zhang JL, Luo Z, Zhang J, Chen LL, Yang L. Diverse alternative back-splicing and alternative splicing landscape of circular RNAs. Genome Research. 2016;26(9):1277–1287. doi: 10.1101/gr.202895.115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Zhang Y, Zhang XO, Chen T, Xiang JF, Yin QF, Xing YH, Zhu S, Yang L, Chen LL. Circular intronic long noncoding RNAs. Molecular Cell. 2013;51(6):792–806. doi: 10.1016/j.molcel.2013.08.017. [DOI] [PubMed] [Google Scholar]
  88. Zhang Z, Yang T, Xiao J. Circular RNAs: Promising biomarkers for human diseases. eBioMedicine. 2018;34:267–274. doi: 10.1016/j.ebiom.2018.07.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Zhao J, Li Y, Wang C, Zhang H, Zhang H, Jiang B, Guo X, Song X. IRESbase: A comprehensive database of experimentally validated internal ribosome entry sites. Genomics, Proteomics & Bioinformatics. 2020;18(2):129–139. doi: 10.1016/j.gpb.2020.03.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  90. Zheng X, Chen L, Zhou Y, Wang Q, Zheng Z, Xu B, Wu C, Zhou Q, Hu W, Wu C, Jiang J. A novel protein encoded by a circular RNA circPPP1R12A promotes tumor pathogenesis and metastasis of colon cancer via hippo-YAP signaling. Molecular Cancer. 2019;18(1):47. doi: 10.1186/s12943-019-1010-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. Zheng Y, Ji P, Chen S, Hou L, Zhao F. Reconstruction of full-length circular RNAs enables isoform-level quantification. Genome Medicine. 2019;11(1):2. doi: 10.1186/s13073-019-0614-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

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