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      Circular RNAs: Biogenesis, Function, and a Role as Possible Cancer Biomarkers

      review-article
      1 , 1 , 2 , 1 ,
      International Journal of Genomics
      Hindawi

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          Abstract

          Circular RNAs (circRNAs) are a class of noncoding RNAs (ncRNAs) that form covalently closed continuous loop structures, lacking the terminal 5′ and 3′ ends. CircRNAs are generated in the process of back-splicing and can originate from different genomic regions. Their unique circular structure makes circRNAs more stable than linear RNAs. In addition, they also display insensitivity to ribonuclease activity. Generally, circRNAs function as microRNA (miRNA) sponges and have a regulatory role in transcription and translation. They may be also translated in a cap-independent manner in vivo, to generate specific proteins. In the last decade, next-generation sequencing techniques, especially RNA-seq, have revealed great abundance and also dysregulation of many circRNAs in various diseases, suggesting their involvement in disease development and progression. Regarding their high stability and relatively specific differential expression patterns in tissues and extracellular environment (e.g., body fluids), they are regarded as promising novel biomarkers in cancer. Therefore, we focus this review on describing circRNA biogenesis, function, and involvement in human cancer development and address the potential of circRNAs to be effectively used as novel cancer diagnostic and prognostic biomarkers.

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          CIRI: an efficient and unbiased algorithm for de novo circular RNA identification

          Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals. Comprehensive detection of circRNAs from high-throughput transcriptome data is an initial and crucial step to study their biogenesis and function. Here, we present a novel chiastic clipping signal-based algorithm, CIRI, to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. By applying CIRI to ENCODE RNA-seq data, we for the first time identify and experimentally validate the prevalence of intronic/intergenic circRNAs as well as fragments specific to them in the human transcriptome. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0571-3) contains supplementary material, which is available to authorized users.
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            Genome-wide analysis of drosophila circular RNAs reveals their structural and sequence properties and age-dependent neural accumulation.

            Circularization was recently recognized to broadly expand transcriptome complexity. Here, we exploit massive Drosophila total RNA-sequencing data, >5 billion paired-end reads from >100 libraries covering diverse developmental stages, tissues, and cultured cells, to rigorously annotate >2,500 fruit fly circular RNAs. These mostly derive from back-splicing of protein-coding genes and lack poly(A) tails, and the circularization of hundreds of genes is conserved across multiple Drosophila species. We elucidate structural and sequence properties of Drosophila circular RNAs, which exhibit commonalities and distinctions from mammalian circles. Notably, Drosophila circular RNAs harbor >1,000 well-conserved canonical miRNA seed matches, especially within coding regions, and coding conserved miRNA sites reside preferentially within circularized exons. Finally, we analyze the developmental and tissue specificity of circular RNAs and note their preferred derivation from neural genes and enhanced accumulation in neural tissues. Interestingly, circular isoforms increase substantially relative to linear isoforms during CNS aging and constitute an aging biomarker. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
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              PhyloCSF: a comparative genomics method to distinguish protein coding and non-coding regions

              Motivation: As high-throughput transcriptome sequencing provides evidence for novel transcripts in many species, there is a renewed need for accurate methods to classify small genomic regions as protein coding or non-coding. We present PhyloCSF, a novel comparative genomics method that analyzes a multispecies nucleotide sequence alignment to determine whether it is likely to represent a conserved protein-coding region, based on a formal statistical comparison of phylogenetic codon models. Results: We show that PhyloCSF's classification performance in 12-species Drosophila genome alignments exceeds all other methods we compared in a previous study. We anticipate that this method will be widely applicable as the transcriptomes of many additional species, tissues and subcellular compartments are sequenced, particularly in the context of ENCODE and modENCODE, and as interest grows in long non-coding RNAs, often initially recognized by their lack of protein coding potential rather than conserved RNA secondary structures. Availability and Implementation: The Objective Caml source code and executables for GNU/Linux and Mac OS X are freely available at http://compbio.mit.edu/PhyloCSF Contact: mlin@mit.edu; manoli@mit.edu
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                Author and article information

                Contributors
                Journal
                Int J Genomics
                Int J Genomics
                IJG
                International Journal of Genomics
                Hindawi
                2314-436X
                2314-4378
                2017
                4 December 2017
                : 2017
                : 6218353
                Affiliations
                1Department of Molecular Genetics, Institute of Pathology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
                2Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
                Author notes

                Academic Editor: Davide Barbagallo

                Author information
                http://orcid.org/0000-0002-3716-4215
                http://orcid.org/0000-0001-9912-3331
                Article
                10.1155/2017/6218353
                5733622
                29349062
                1a9ecb1f-6d67-4b55-a2a2-309a9bc0fa3c
                Copyright © 2017 Luka Bolha et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 12 May 2017
                : 29 August 2017
                : 28 September 2017
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