Circular RNA profiling reveals abundant and diverse circRNAs of SARS-CoV-2, SARS-CoV and MERS-CoV origin

ABSTRACTCircular RNAs (circRNAs) encoded by DNA genomes have been identified across host and pathogen species as parts of the transcriptome. Accumulating evidences indicate that circRNAs play critical roles in autoimmune diseases and viral pathogenesis. Here we report that RNA viruses of the Betacoronavirus genus of Coronaviridae, SARS-CoV-2, SARS-CoV and MERS-CoV, encode a novel type of circRNAs. Through de novo circRNA analyses of publicly available coronavirus-infection related deep RNA-Sequencing data, we identified 351, 224 and 2,764 circRNAs derived from SARS-CoV-2, SARS-CoV and MERS-CoV, respectively, and characterized two major back-splice events shared by these viruses. Coronavirus-derived circRNAs are more abundant and longer compared to host genome-derived circRNAs. Using a systematic strategy to amplify and identify back-splice junction sequences, we experimentally identified over 100 viral circRNAs from SARS-CoV-2 infected Vero E6 cells. This collection of circRNAs provided the first line of evidence for the abundance and diversity of coronavirus-derived circRNAs and suggested possible mechanisms driving circRNA biogenesis from RNA genomes. Our findings highlight circRNAs as an important component of the coronavirus transcriptome.SummaryWe report for the first time that abundant and diverse circRNAs are generated by SARS-CoV-2, SARS-CoV and MERS-CoV and represent a novel type of circRNAs that differ from circRNAs encoded by DNA genomes.

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Circular RNA Profiling by Illumina Sequencing via Template-Dependent Multiple Displacement Amplification

BioMed Research International ◽

10.1155/2019/2756516 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 4

Author(s):

Ashirbad Guria ◽

Kavitha Velayudha Vimala Kumar ◽

Nagesh Srikakulam ◽

Anakha Krishnamma ◽

Saibal Chanda ◽

...

Keyword(s):

Illumina Sequencing ◽

Multiple Displacement Amplification ◽

Circular Rna ◽

Circular Rnas ◽

Functional Roles ◽

Rna Profiling ◽

Competitive Edge ◽

Living Organisms ◽

First Time ◽

Human And Mouse

Circular RNAs (circRNAs) are newly discovered incipient non-coding RNAs with potential roles in disease progression in living organisms. Significant reports, since their inception, highlight the abundance and putative functional roles of circRNAs in every organism checked for, like O. sativa, Arabidopsis, human, and mouse. CircRNA expression is generally less than their linear mRNA counterparts which fairly explains the competitive edge of canonical splicing over non-canonical splicing. However, existing methods may not be sensitive enough for the discovery of low-level expressed circRNAs. By combining template-dependent multiple displacement amplification (tdMDA), Illumina sequencing, and bioinformatics tools, we have developed an experimental protocol that is able to detect 1,875 novel and known circRNAs from O. sativa. The same method also revealed 9,242 putative circRNAs in less than 40 million reads for the first time from the Nicotiana benthamiana whose genome has not been fully annotated. Supported by the PCR-based validation and Sanger sequencing of selective circRNAs, our method represents a valuable tool in profiling circRNAs from the organisms with or without genome annotation.

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circtools—a one-stop software solution for circular RNA research

Bioinformatics ◽

10.1093/bioinformatics/bty948 ◽

2018 ◽

Vol 35 (13) ◽

pp. 2326-2328 ◽

Cited By ~ 13

Author(s):

Tobias Jakobi ◽

Alexey Uvarovskii ◽

Christoph Dieterich

Keyword(s):

High Throughput Sequencing ◽

Circular Rna ◽

Statistical Testing ◽

Supplementary Information ◽

Circular Rnas ◽

Sequencing Data ◽

High Throughput Sequencing Data ◽

Multi Stage ◽

Sequence Reconstruction ◽

One Stop

Abstract Motivation Circular RNAs (circRNAs) originate through back-splicing events from linear primary transcripts, are resistant to exonucleases, are not polyadenylated and have been shown to be highly specific for cell type and developmental stage. CircRNA detection starts from high-throughput sequencing data and is a multi-stage bioinformatics process yielding sets of potential circRNA candidates that require further analyses. While a number of tools for the prediction process already exist, publicly available analysis tools for further characterization are rare. Our work provides researchers with a harmonized workflow that covers different stages of in silico circRNA analyses, from prediction to first functional insights. Results Here, we present circtools, a modular, Python-based framework for computational circRNA analyses. The software includes modules for circRNA detection, internal sequence reconstruction, quality checking, statistical testing, screening for enrichment of RBP binding sites, differential exon RNase R resistance and circRNA-specific primer design. circtools supports researchers with visualization options and data export into commonly used formats. Availability and implementation circtools is available via https://github.com/dieterich-lab/circtools and http://circ.tools under GPLv3.0. Supplementary information Supplementary data are available at Bioinformatics online.

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Novel circular RNA circNF1 acts as a molecular sponge, promoting gastric cancer by absorbing miR-16

Endocrine Related Cancer ◽

10.1530/erc-18-0478 ◽

2019 ◽

Vol 26 (3) ◽

pp. 265-277 ◽

Cited By ~ 13

Author(s):

Zhe Wang ◽

Ke Ma ◽

Steffie Pitts ◽

Yulan Cheng ◽

Xi Liu ◽

...

Keyword(s):

Cell Lines ◽

Circular Rna ◽

Gastric Carcinogenesis ◽

Luciferase Reporter ◽

Circular Rnas ◽

Limited Information ◽

Sequencing Data ◽

Downstream Target ◽

New Class ◽

Reporter Assays

Circular RNAs (circRNAs) are a new class of RNA involved in multiple human malignancies. However, limited information exists regarding the involvement of circRNAs in gastric carcinoma (GC). Therefore, we sought to identify novel circRNAs, their functions and mechanisms in gastric carcinogenesis. We analyzed next-generation RNA sequencing data from GC tissues and cell lines, identifying 75,201 candidate circRNAs. Among these, we focused on one novel circRNA, circNF1 , which was upregulated in GC tissues and cell lines. Loss- and gain-of-function studies demonstrated that circNF1 significantly promotes cell proliferation. Furthermore, luciferase reporter assays showed that circNF1 binds to miR-16, thereby derepressing its downstream target mRNAs, MAP7 and AKT3. Targeted silencing or overexpression of circNF1 had no effect on levels of its linear RNA counterpart, NF1. Taken together, these results suggest that circNF1 acts as a novel oncogenic circRNA in GC by functioning as a miR-16 sponge.

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When Less is More: "Slicing" Sequencing Data Improves Read Decoding Accuracy and De Novo Assembly Quality

10.1101/013425 ◽

2015 ◽

Cited By ~ 1

Author(s):

Stefano Lonardi ◽

Hamid Mirebrahim ◽

Steve Wanamaker ◽

Matthew Alpert ◽

Gianfranco Ciardo ◽

...

Keyword(s):

Deep Sequencing ◽

De Novo Assembly ◽

De Novo ◽

Optimal Size ◽

Sequencing Data ◽

Less Is More ◽

Bac Clones ◽

Deep Sequencing Data ◽

First Time

Since the invention of DNA sequencing in the seventies, computational biologists have had to deal with the problem de novo genome assembly with limited (or insufficient) depth of sequencing. In this work, for the first time we investigate the opposite problem, that is, the challenge of dealing with excessive depth of sequencing. Specifically, we explore the effect of ultra-deep sequencing data in two domains: (i) the problem of decoding reads to BAC clones (in the context of the combinatorial pooling design proposed by our group), and (ii) the problem of de novo assembly of BAC clones. Using real ultra-deep sequencing data, we show that when the depth of sequencing increases over a certain threshold, sequencing errors make these two problems harder and harder (instead of easier, as one would expect with error-free data), and as a consequence the quality of the solution degrades with more and more data. For the first problem, we propose an effective solution based on "divide and conquer": we "slice" a large dataset into smaller samples of optimal size, decode each slice independently, then merge the results. Experimental results on over 15,000 barley BACs and over 4,000 cowpea BACs demonstrate a significant improvement in the quality of the decoding and the final assembly. For the second problem, we show for the first time that modern de novo assemblers cannot take advantage of ultra-deep sequencing data.

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Circall: fast and accurate methodology for discovery of circular RNAs from paired-end RNA-sequencing data

BMC Bioinformatics ◽

10.1186/s12859-021-04418-8 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Dat Thanh Nguyen ◽

Quang Thinh Trac ◽

Thi-Hau Nguyen ◽

Ha-Nam Nguyen ◽

Nir Ohad ◽

...

Keyword(s):

Rna Sequencing ◽

Simulated Data ◽

High Sensitivity ◽

Circular Rna ◽

Computational Time ◽

Circular Rnas ◽

Rna Seq ◽

Sequencing Data ◽

Mapping Algorithm ◽

False Discovery Rate Method

Abstract Background Circular RNA (circRNA) is an emerging class of RNA molecules attracting researchers due to its potential for serving as markers for diagnosis, prognosis, or therapeutic targets of cancer, cardiovascular, and autoimmune diseases. Current methods for detection of circRNA from RNA sequencing (RNA-seq) focus mostly on improving mapping quality of reads supporting the back-splicing junction (BSJ) of a circRNA to eliminate false positives (FPs). We show that mapping information alone often cannot predict if a BSJ-supporting read is derived from a true circRNA or not, thus increasing the rate of FP circRNAs. Results We have developed Circall, a novel circRNA detection method from RNA-seq. Circall controls the FPs using a robust multidimensional local false discovery rate method based on the length and expression of circRNAs. It is computationally highly efficient by using a quasi-mapping algorithm for fast and accurate RNA read alignments. We applied Circall on two simulated datasets and three experimental datasets of human cell-lines. The results show that Circall achieves high sensitivity and precision in the simulated data. In the experimental datasets it performs well against current leading methods. Circall is also substantially faster than the other methods, particularly for large datasets. Conclusions With those better performances in the detection of circRNAs and in computational time, Circall facilitates the analyses of circRNAs in large numbers of samples. Circall is implemented in C++ and R, and available for use at https://www.meb.ki.se/sites/biostatwiki/circall and https://github.com/datngu/Circall.

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An Integrative Transcriptomic and Methylation Approach for Identifying Differentially Expressed Circular RNAs Associated with DNA Methylation Change

Biomedicines ◽

10.3390/biomedicines9060657 ◽

2021 ◽

Vol 9 (6) ◽

pp. 657

Author(s):

Tianyi Xu ◽

LiPing Wang ◽

Peilin Jia ◽

Xiaofeng Song ◽

Zhongming Zhao

Keyword(s):

Dna Methylation ◽

Rank Order ◽

Circular Rna ◽

Differentially Expressed ◽

Circular Rnas ◽

P Value ◽

General View ◽

Methylation Change ◽

Sequencing Data ◽

Genome Wide

Recently, accumulating evidence has supported that circular RNA (circRNA) plays important roles in tumorigenesis by regulating gene expression at transcriptional and post-transcriptional levels. Expression of circRNAs can be epigenetically silenced by DNA methylation; however, the underlying regulatory mechanisms of circRNAs by DNA methylation remains largely unknown. We explored this regulation in hepatocellular carcinoma (HCC) using genome-wide DNA methylation and RNA sequencing data of the primary tumor and matched adjacent normal tissues from 20 HCC patients. Our pipeline identified 1012 upregulated and 747 downregulated circRNAs (collectively referred to as differentially expressed circRNAs, or DE circRNAs) from HCC RNA-seq data. Among them, 329 DE circRNAs covered differentially methylated sites (adjusted p-value < 0.05, |ΔM| > 0.5) in circRNAs’ interior and/or flanking regions. Interestingly, the corresponding parental genes of 46 upregulated and 31 downregulated circRNAs did not show significant expression change in the HCC tumor versus normal samples. Importantly, 34 of the 77 DE circRNAs (44.2%) had significant correlation with DNA methylation change in HCC (Spearman’s rank-order correlation, p-value < 0.05), suggesting that aberrant DNA methylation might regulate circular RNA expression in HCC. Our study revealed genome-wide differential circRNA expression in HCC. The significant correlation with DNA methylation change suggested that epigenetic regulation might act on both mRNA and circRNA expression. The specific regulation in HCC and general view in other cancer or disease requires further investigation.

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Parsimonious scenario for the emergence of viroid-like repliconsde novo

10.1101/593640 ◽

2019 ◽

Author(s):

Pablo Catalán ◽

Santiago F. Elena ◽

José A. Cuesta ◽

Susanna Manrubia

Keyword(s):

De Novo ◽

Rna World ◽

Circular Rna ◽

Biochemical Properties ◽

Circular Rnas ◽

Sequence Motifs ◽

Rna Sequences ◽

Specific Sequence ◽

Evolutionary Pathway ◽

Rna Molecules

AbstractViroids are small, non-coding, circular RNA molecules that infect plants. Different hypotheses for their evolutionary origin have been put forward, such as an early emergence in a precellular RNA World or severalde novoindependent evolutionary origins in plants. Here we discuss the plausibility ofde novoemergence of viroid-like replicons by giving theoretical support to the likelihood of different steps along a parsimonious evolutionary pathway. While Avsunviroidae-like structures are relatively easy to obtain through evolution of a population of random RNA sequences of fixed length, rod-like structures typical of Pospiviroidae are difficult to fix. Using different quantitative approaches, we evaluate the likelihood that RNA sequences fold into a rod-like structure and bear specific sequence motifs facilitating interactions with other molecules,e.g.RNA polymerases, RNases and ligases. By means of numerical simulations, we show that circular RNA replicons analogous to Pospiviroidae emerge if evolution is seeded with minimal circular RNAs that grow through the gradual addition of nucleotides. Further, these rod-like replicons often maintain their structure if independent functional modules are acquired that impose selective constraints. The evolutionary scenario we propose here is consistent with the structural and biochemical properties of viroids described to date.

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Circular RNA Profiling and Bioinformatic Modeling Identify Its Regulatory Role in Hepatic Steatosis

BioMed Research International ◽

10.1155/2017/5936171 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13 ◽

Cited By ~ 17

Author(s):

Xing-Ya Guo ◽

Chong-Xin He ◽

Yu-Qin Wang ◽

Chao Sun ◽

Guang-Ming Li ◽

...

Keyword(s):

Hepatic Steatosis ◽

Metabolic Pathways ◽

Target Prediction ◽

Principal Component ◽

Circular Rna ◽

Circular Rnas ◽

Rna Profiling ◽

Pathway Annotation ◽

Wide Range ◽

Chain Acyl

Circular RNAs (circRNAs) exhibit a wide range of physiological and pathological activities. To uncover their role in hepatic steatosis, we investigated the expression profile of circRNAs in HepG2-based hepatic steatosis induced by high-fat stimulation. Differentially expressed circRNAs were subjected to validation using QPCR and functional analyses using principal component analysis, hierarchical clustering, target prediction, gene ontology (GO), and pathway annotation, respectively. Bioinformatic integration established the circRNA-miRNA-mRNA regulatory network so as to identify the mechanisms underlying circRNAs’ metabolic effect. Here we reported that hepatic steatosis was associated with a total of 357 circRNAs. Enrichment of transcription-related GOs, especially GO: 0006355, GO: 004589, GO: 0045944, GO: 0045892, and GO: 0000122, demonstrated their specific actions in transcriptional regulation. Lipin 1 (LPIN1) was recognized to mediate the transcriptional regulatory effect of circRNAs on metabolic pathways. circRNA-miRNA-mRNA network further identified the signaling cascade of circRNA_021412/miR-1972/LPIN1, which was characterized by decreased level of circRNA_021412 and miR-1972-based inhibition of LPIN1. LPIN1-induced downregulation of long chain acyl-CoA synthetases (ACSLs) expression finally resulted in the hepatosteatosis. These findings identify circRNAs to be important regulators of hepatic steatosis. Transcription-dependent modulation of metabolic pathways may underlie their effects, partially by the circRNA_021412/miR-1972/LPIN1 signaling.

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

Briefings in Bioinformatics ◽

10.1093/bib/bbz175 ◽

2020 ◽

Cited By ~ 5

Author(s):

Marieke Vromman ◽

Jo Vandesompele ◽

Pieter-Jan Volders

Keyword(s):

Splice Junction ◽

Circular Rna ◽

Circular Rnas ◽

Working Mechanism ◽

Comprehensive Overview ◽

Specific Expression ◽

Protein Coding ◽

Rna Molecules ◽

Current State ◽

Coding Potential

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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Circular RNA Expression and Regulation Profiling in Testicular Tissues of Immature and Mature Wandong Cattle (Bos taurus)

Frontiers in Genetics ◽

10.3389/fgene.2021.685541 ◽

2021 ◽

Vol 12 ◽

Author(s):

Ibrar Muhammad Khan ◽

Hongyu Liu ◽

Jingyi Zhuang ◽

Nazir Muhammad Khan ◽

Dandan Zhang ◽

...

Keyword(s):

Target Genes ◽

Bos Taurus ◽

Quantitative Polymerase Chain Reaction ◽

Genetic Selection ◽

Weather Conditions ◽

Circular Rna ◽

Circular Rnas ◽

Sequencing Data ◽

Testis Development ◽

Suitable Framework

Wandong cattle are an autochthonous Chinese breed used extensively for beef production. The breed tolerates extreme weather conditions and raw feed and is resistant to tick-borne diseases. However, the genetic basis of testis development and sperm production as well as breeding management is not well established in local cattle. Therefore, improving the reproductive efficiency of bulls via genetic selection is crucial as a single bull can breed thousands of cows through artificial insemination (AI). Testis development and spermatogenesis are regulated by hundreds of genes and transcriptomes. However, circular RNAs (circRNAs) are the key players in many biological developmental processes that have not been methodically described and compared between immature and mature stages in Bovine testes. In this study, we performed total RNA-seq and comprehensively analyzed the circRNA expression profiling of the testis samples of six bulls at 3 years and 3 months of developmental age. In total, 17,013 circRNAs were identified, of which 681 circRNAs (p-adjust < 0.05) were differentially expressed (DE). Among these DE circRNAs, 579 were upregulated and 103 were downregulated in calf and bull testes. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed that the identified target genes were classified into three broad functional categories, including biological process, cellular component, and molecular function, and were enriched in the lysine degradation, cell cycle, and cell adhesion molecule pathways. The binding interactions between DE circRNAs and microRNAs (miRNAs) were subsequently constructed using bioinformatics approaches. The source genes ATM, CCNA1, GSK3B, KMT2C, KMT2E, NSD2, SUCLG2, QKI, HOMER1, and SNAP91 were found to be actively associated with bull sexual maturity and spermatogenesis. In addition, a real-time quantitative polymerase chain reaction (RT-qPCR) analysis showed a strong correlation with the sequencing data. Moreover, the developed model of Bovine testes in the current study provides a suitable framework for understanding the mechanism of circRNAs in the development of testes and spermatogenesis.

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