1
|
Budnick A, Franklin MJ, Utley D, Edwards B, Charles M, Hornstein ED, Sederoff H. Long- and short-read sequencing methods discover distinct circular RNA pools in Lotus japonicus. THE PLANT GENOME 2024; 17:e20429. [PMID: 38243772 DOI: 10.1002/tpg2.20429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/21/2023] [Accepted: 12/27/2023] [Indexed: 01/21/2024]
Abstract
Circular RNAs (circRNAs) are covalently closed single-stranded RNAs, generated through a back-splicing process that links a downstream 5' site to an upstream 3' end. The only distinction in the sequence between circRNA and their linear cognate RNA is the back splice junction. Their low abundance and sequence similarity with their linear origin RNA have made the discovery and identification of circRNA challenging. We have identified almost 6000 novel circRNAs from Lotus japonicus leaf tissue using different enrichment, amplification, and sequencing methods as well as alternative bioinformatics pipelines. The different methodologies identified different pools of circRNA with little overlap. We validated circRNA identified by the different methods using reverse transcription polymerase chain reaction and characterized sequence variations using nanopore sequencing. We compared validated circRNA identified in L. japonicus to other plant species and showed conservation of high-confidence circRNA-expressing genes. This is the first identification of L. japonicus circRNA and provides a resource for further characterization of their function in gene regulation. CircRNAs identified in this study originated from genes involved in all biological functions of eukaryotic cells. The comparison of methodologies and technologies to sequence, identify, analyze, and validate circRNA from plant tissues will enable further research to characterize the function and biogenesis of circRNA in L. japonicus.
Collapse
Affiliation(s)
- Asa Budnick
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
| | - Megan J Franklin
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
| | - Delecia Utley
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
| | - Brianne Edwards
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
| | - Melodi Charles
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
| | - Eli D Hornstein
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
| | - Heike Sederoff
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, USA
| |
Collapse
|
2
|
Chiang TW, Jhong SE, Chen YC, Chen CY, Wu WS, Chuang TJ. FL-circAS: an integrative resource and analysis for full-length sequences and alternative splicing of circular RNAs with nanopore sequencing. Nucleic Acids Res 2024; 52:D115-D123. [PMID: 37823705 PMCID: PMC10767854 DOI: 10.1093/nar/gkad829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/26/2023] [Accepted: 10/02/2023] [Indexed: 10/13/2023] Open
Abstract
Circular RNAs (circRNAs) are RNA molecules with a continuous loop structure characterized by back-splice junctions (BSJs). While analyses of short-read RNA sequencing have identified millions of BSJ events, it is inherently challenging to determine exact full-length sequences and alternatively spliced (AS) isoforms of circRNAs. Recent advances in nanopore long-read sequencing with circRNA enrichment bring an unprecedented opportunity for investigating the issues. Here, we developed FL-circAS (https://cosbi.ee.ncku.edu.tw/FL-circAS/), which collected such long-read sequencing data of 20 cell lines/tissues and thereby identified 884 636 BSJs with 1 853 692 full-length circRNA isoforms in human and 115 173 BSJs with 135 617 full-length circRNA isoforms in mouse. FL-circAS also provides multiple circRNA features. For circRNA expression, FL-circAS calculates expression levels for each circRNA isoform, cell line/tissue specificity at both the BSJ and isoform levels, and AS entropy for each BSJ across samples. For circRNA biogenesis, FL-circAS identifies reverse complementary sequences and RNA binding protein (RBP) binding sites residing in flanking sequences of BSJs. For functional patterns, FL-circAS identifies potential microRNA/RBP binding sites and several types of evidence for circRNA translation on each full-length circRNA isoform. FL-circAS provides user-friendly interfaces for browsing, searching, analyzing, and downloading data, serving as the first resource for discovering full-length circRNAs at the isoform level.
Collapse
Affiliation(s)
- Tai-Wei Chiang
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Song-En Jhong
- Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan
| | - Yu-Chen Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Wei-Sheng Wu
- Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan
| | | |
Collapse
|
3
|
Robic A, Hadlich F, Costa Monteiro Moreira G, Louise Clark E, Plastow G, Charlier C, Kühn C. Innovative construction of the first reliable catalogue of bovine circular RNAs. RNA Biol 2024; 21:52-74. [PMID: 38989833 PMCID: PMC11244336 DOI: 10.1080/15476286.2024.2375090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/26/2024] [Indexed: 07/12/2024] Open
Abstract
The aim of this study was to compare the circular transcriptome of divergent tissues in order to understand: i) the presence of circular RNAs (circRNAs) that are not exonic circRNAs, i.e. originated from backsplicing involving known exons and, ii) the origin of artificial circRNA (artif_circRNA), i.e. circRNA not generated in-vivo. CircRNA identification is mostly an in-silico process, and the analysis of data from the BovReg project (https://www.bovreg.eu/) provided an opportunity to explore new ways to identify reliable circRNAs. By considering 117 tissue samples, we characterized 23,926 exonic circRNAs, 337 circRNAs from 273 introns (191 ciRNAs, 146 intron circles), 108 circRNAs from small non-coding genes and nearly 36.6K circRNAs classified as other_circRNAs. Furthermore, for 63 of those samples we analysed in parallel data from total-RNAseq (ribosomal RNAs depleted prior to library preparation) with paired mRNAseq (library prepared with poly(A)-selected RNAs). The high number of circRNAs detected in mRNAseq, and the significant number of novel circRNAs, mainly other_circRNAs, led us to consider all circRNAs detected in mRNAseq as artificial. This study provided evidence of 189 false entries in the list of exonic circRNAs: 103 artif_circRNAs identified by total RNAseq/mRNAseq comparison using two circRNA tools, 26 probable artif_circRNAs, and 65 identified by deep annotation analysis. Extensive benchmarking was performed (including analyses with CIRI2 and CIRCexplorer-2) and confirmed 94% of the 23,737 reliable exonic circRNAs. Moreover, this study demonstrates the effectiveness of a panel of highly expressed exonic circRNAs (5-8%) in analysing the tissue specificity of the bovine circular transcriptome.
Collapse
Affiliation(s)
- Annie Robic
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet-Tolosan, France
| | - Frieder Hadlich
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | | | | | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, AB, Canada
| | - Carole Charlier
- Unit of Animal Genomics, GIGA Institute, University of Liège, Liège, Belgium
- Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Christa Kühn
- Institute of Genome Biology, Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
- Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany
- Friedrich Loeffler Institute, Federal Research Institute for Animal Health, Greifswald – Insel Riems, Germany
| |
Collapse
|
4
|
Ma XK, Zhai SN, Yang L. Approaches and challenges in genome-wide circular RNA identification and quantification. Trends Genet 2023; 39:897-907. [PMID: 37839990 DOI: 10.1016/j.tig.2023.09.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 09/13/2023] [Accepted: 09/15/2023] [Indexed: 10/17/2023]
Abstract
Numerous circular RNAs (circRNAs) produced from back-splicing of exon(s) have been recently revealed on a genome-wide scale across species. Although generally expressed at a low level, some relatively abundant circRNAs can play regulatory roles in various biological processes, prompting continuous profiling of circRNA in broader conditions. Over the past decade, distinct strategies have been applied in both transcriptome enrichment and bioinformatic tools for detecting and quantifying circRNAs. Understanding the scope and limitations of these strategies is crucial for the subsequent annotation and characterization of circRNAs, especially those with functional potential. Here, we provide an overview of different transcriptome enrichment, deep sequencing and computational approaches for genome-wide circRNA identification, and discuss strategies for accurate quantification and characterization of circRNA.
Collapse
Affiliation(s)
- Xu-Kai Ma
- Center for Molecular Medicine, Children's Hospital, Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
| | - Si-Nan Zhai
- Center for Molecular Medicine, Children's Hospital, Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China; Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Li Yang
- Center for Molecular Medicine, Children's Hospital, Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
| |
Collapse
|
5
|
Chen YC, Chen CY, Chiang TW, Chan MH, Hsiao M, Ke HM, Tsai I, Chuang TJ. Detecting intragenic trans-splicing events from non-co-linearly spliced junctions by hybrid sequencing. Nucleic Acids Res 2023; 51:7777-7797. [PMID: 37497782 PMCID: PMC10450196 DOI: 10.1093/nar/gkad623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 07/14/2023] [Indexed: 07/28/2023] Open
Abstract
Trans-spliced RNAs (ts-RNAs) are a type of non-co-linear (NCL) transcripts that consist of exons in an order topologically inconsistent with the corresponding DNA template. Detecting ts-RNAs is often interfered by experimental artifacts, circular RNAs (circRNAs) and genetic rearrangements. Particularly, intragenic ts-RNAs, which are derived from separate precursor mRNA molecules of the same gene, are often mistaken for circRNAs through analyses of RNA-seq data. Here we developed a bioinformatics pipeline (NCLscan-hybrid), which integrated short and long RNA-seq reads to minimize false positives and proposed out-of-circle and rolling-circle long reads to distinguish between intragenic ts-RNAs and circRNAs. Combining NCLscan-hybrid screening and multiple experimental validation steps successfully confirmed that four NCL events, which were previously regarded as circRNAs in databases, originated from trans-splicing. CRISPR-based endogenous genome modification experiments further showed that flanking intronic complementary sequences can significantly contribute to ts-RNA formation, providing an efficient/specific method to deplete ts-RNAs. We also experimentally validated that one ts-RNA (ts-ARFGEF1) played an important role for p53-mediated apoptosis through affecting the PERK/eIF2a/ATF4/CHOP signaling pathway in breast cancer cells. This study thus described both bioinformatics procedures and experimental validation steps for rigorous characterization of ts-RNAs, expanding future studies for identification, biogenesis, and function of these important but understudied transcripts.
Collapse
Affiliation(s)
- Yu-Chen Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Tai-Wei Chiang
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Ming-Hsien Chan
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Michael Hsiao
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Huei-Mien Ke
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
- Department of Microbiology, Soochow University, Taipei, Taiwan
| | | | | |
Collapse
|
6
|
Vromman M, Anckaert J, Bortoluzzi S, Buratin A, Chen CY, Chu Q, Chuang TJ, Dehghannasiri R, Dieterich C, Dong X, Flicek P, Gaffo E, Gu W, He C, Hoffmann S, Izuogu O, Jackson MS, Jakobi T, Lai EC, Nuytens J, Salzman J, Santibanez-Koref M, Stadler P, Thas O, Vanden Eynde E, Verniers K, Wen G, Westholm J, Yang L, Ye CY, Yigit N, Yuan GH, Zhang J, Zhao F, Vandesompele J, Volders PJ. Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision. Nat Methods 2023; 20:1159-1169. [PMID: 37443337 PMCID: PMC10870000 DOI: 10.1038/s41592-023-01944-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 06/12/2023] [Indexed: 07/15/2023]
Abstract
The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed using computational tools. Numerous such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools detected more than 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were validated using three orthogonal methods. Generally, tool-specific precision is high and similar (median of 98.8%, 96.3% and 95.5% for qPCR, RNase R and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant differentiators. Of note, precision values are lower when evaluating low-abundance circRNAs. We also show that the tools can be used complementarily to increase detection sensitivity. Finally, we offer recommendations for future circRNA detection and validation.
Collapse
Affiliation(s)
- Marieke Vromman
- OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Jasper Anckaert
- OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | | | - Alessia Buratin
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei City, Taiwan
| | - Qinjie Chu
- Institute of Crop Science and Institute of Bioinformatics, Zhejiang University, Zhejiang, China
| | | | - Roozbeh Dehghannasiri
- Department of Biomedical Data Science and of Biochemistry, Stanford University, Stanford, CA, USA
| | - Christoph Dieterich
- Klaus Tschira Institute for Integrative Computational Cardiology, Department of Internal Medicine III, University Hospital Heidelberg, German Center for Cardiovascular Research (DZHK), Heidelberg, Germany
| | - Xin Dong
- School of Basic Medical Science, Department of Medical Genetics, Wuhan University, Wuhan, China
| | | | - Enrico Gaffo
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Wanjun Gu
- Collaborative Innovation Center of Jiangsu Province of Cancer Prevention and Treatment of Chinese Medicine, School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing, China
| | - Chunjiang He
- School of Basic Medical Science, Department of Medical Genetics, Wuhan University, Wuhan, China
| | - Steve Hoffmann
- Computational Biology Group, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | | | - Michael S Jackson
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, UK
| | - Tobias Jakobi
- Translational Cardiovascular Research Center, University of Arizona - College of Medicine Phoenix, Phoenix, AZ, USA
| | - Eric C Lai
- Sloan Kettering Institute, New York, NY, USA
| | - Justine Nuytens
- OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Julia Salzman
- Department of Biomedical Data Science and of Biochemistry, Stanford University, Stanford, CA, USA
| | | | - Peter Stadler
- Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Universität Leipzig, Leipzig, Germany
| | - Olivier Thas
- Data Science Institute, I-Biostat, Hasselt University, Hasselt, Belgium
| | - Eveline Vanden Eynde
- OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Kimberly Verniers
- OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Guoxia Wen
- State Key Laboratory of Bioelectronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China
| | - Jakub Westholm
- Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Li Yang
- Center for Molecular Medicine, Children's Hospital, Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Fudan, China
| | - Chu-Yu Ye
- Institute of Crop Science and Institute of Bioinformatics, Zhejiang University, Zhejiang, China
| | - Nurten Yigit
- OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Guo-Hua Yuan
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jinyang Zhang
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, China
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, China
| | - Jo Vandesompele
- OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
| | - Pieter-Jan Volders
- OncoRNALab, Cancer Research Institute Ghent (CRIG), Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| |
Collapse
|
7
|
Verwilt J, Mestdagh P, Vandesompele J. Artifacts and biases of the reverse transcription reaction in RNA sequencing. RNA (NEW YORK, N.Y.) 2023; 29:889-897. [PMID: 36990512 DOI: 10.1261/rna.079623.123] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
RNA sequencing has spurred a significant number of research areas in recent years. Most protocols rely on synthesizing a more stable complementary DNA (cDNA) copy of the RNA molecule during the reverse transcription reaction. The resulting cDNA pool is often wrongfully assumed to be quantitatively and molecularly similar to the original RNA input. Sadly, biases and artifacts confound the resulting cDNA mixture. These issues are often overlooked or ignored in the literature by those that rely on the reverse transcription process. In this review, we confront the reader with intra- and intersample biases and artifacts caused by the reverse transcription reaction during RNA sequencing experiments. To fight the reader's despair, we also provide solutions to most issues and inform on good RNA sequencing practices. We hope the reader can use this review to their advantage, thereby contributing to scientifically sound RNA studies.
Collapse
Affiliation(s)
- Jasper Verwilt
- OncoRNALab, Cancer Research Institute Ghent, 9000 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
- Center for Medical Genetics, Ghent University, 9000 Ghent, Belgium
| | - Pieter Mestdagh
- OncoRNALab, Cancer Research Institute Ghent, 9000 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
- Center for Medical Genetics, Ghent University, 9000 Ghent, Belgium
| | - Jo Vandesompele
- OncoRNALab, Cancer Research Institute Ghent, 9000 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9000 Ghent, Belgium
- Center for Medical Genetics, Ghent University, 9000 Ghent, Belgium
| |
Collapse
|
8
|
Haas BJ, Dobin A, Ghandi M, Van Arsdale A, Tickle T, Robinson JT, Gillani R, Kasif S, Regev A. Targeted in silico characterization of fusion transcripts in tumor and normal tissues via FusionInspector. CELL REPORTS METHODS 2023; 3:100467. [PMID: 37323575 PMCID: PMC10261907 DOI: 10.1016/j.crmeth.2023.100467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 02/28/2023] [Accepted: 04/14/2023] [Indexed: 06/17/2023]
Abstract
Here, we present FusionInspector for in silico characterization and interpretation of candidate fusion transcripts from RNA sequencing (RNA-seq) and exploration of their sequence and expression characteristics. We applied FusionInspector to thousands of tumor and normal transcriptomes and identified statistical and experimental features enriched among biologically impactful fusions. Through clustering and machine learning, we identified large collections of fusions potentially relevant to tumor and normal biological processes. We show that biologically relevant fusions are enriched for relatively high expression of the fusion transcript, imbalanced fusion allelic ratios, and canonical splicing patterns, and are deficient in sequence microhomologies between partner genes. We demonstrate that FusionInspector accurately validates fusion transcripts in silico and helps characterize numerous understudied fusions in tumor and normal tissue samples. FusionInspector is freely available as open source for screening, characterization, and visualization of candidate fusions via RNA-seq, and facilitates transparent explanation and interpretation of machine-learning predictions and their experimental sources.
Collapse
Affiliation(s)
- Brian J. Haas
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Graduate Program in Bioinformatics, Boston University, Boston, MA 02215, USA
| | | | | | - Anne Van Arsdale
- Department of Obstetrics and Gynecology and Women’s Health, Albert Einstein Montefiore Medical Center, Bronx, NY 10461, USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Timothy Tickle
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - James T. Robinson
- School of Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Riaz Gillani
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Cancer Program, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA 02215, USA
- Boston Children’s Hospital, Boston, MA 02115, USA
| | - Simon Kasif
- Graduate Program in Bioinformatics, Boston University, Boston, MA 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| |
Collapse
|
9
|
Chuang TJ, Chiang TW, Chen CY. Assessing the impacts of various factors on circular RNA reliability. Life Sci Alliance 2023; 6:6/5/e202201793. [PMID: 36849251 PMCID: PMC9971162 DOI: 10.26508/lsa.202201793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 02/15/2023] [Accepted: 02/15/2023] [Indexed: 03/01/2023] Open
Abstract
Circular RNAs (circRNAs) are non-polyadenylated RNAs with a continuous loop structure characterized by a non-colinear back-splice junction (BSJ). Although millions of circRNA candidates have been identified, it remains a major challenge for determining circRNA reliability because of various types of false positives. Here, we systematically assess the impacts of numerous factors related to circRNA identification, conservation, biogenesis, and function on circRNA reliability by comparisons of circRNA expression from mock and the corresponding colinear/polyadenylated RNA-depleted datasets based on three different RNA treatment approaches. Eight important indicators of circRNA reliability are determined. The relative contribution to variability explained analyses reveal that the relative importance of these factors in affecting circRNA reliability in descending order is the conservation level of circRNA, full-length circular sequences, supporting BSJ read count, both BSJ donor and acceptor splice sites at the same colinear transcript isoforms, both BSJ donor and acceptor splice sites at the annotated exon boundaries, BSJs detected by multiple tools, supporting functional features, and both BSJ donor and acceptor splice sites undergoing alternative splicing. This study thus provides a useful guideline and an important resource for selecting high-confidence circRNAs for further investigations.
Collapse
Affiliation(s)
| | - Tai-Wei Chiang
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| |
Collapse
|
10
|
Dorney R, Dhungel BP, Rasko JEJ, Hebbard L, Schmitz U. Recent advances in cancer fusion transcript detection. Brief Bioinform 2022; 24:6918739. [PMID: 36527429 PMCID: PMC9851307 DOI: 10.1093/bib/bbac519] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/11/2022] [Accepted: 10/31/2022] [Indexed: 12/23/2022] Open
Abstract
Extensive investigation of gene fusions in cancer has led to the discovery of novel biomarkers and therapeutic targets. To date, most studies have neglected chromosomal rearrangement-independent fusion transcripts and complex fusion structures such as double or triple-hop fusions, and fusion-circRNAs. In this review, we untangle fusion-related terminology and propose a classification system involving both gene and transcript fusions. We highlight the importance of RNA-level fusions and how long-read sequencing approaches can improve detection and characterization. Moreover, we discuss novel bioinformatic tools to identify fusions in long-read sequencing data and strategies to experimentally validate and functionally characterize fusion transcripts.
Collapse
Affiliation(s)
- Ryley Dorney
- epartment of Molecular & Cell Biology, College of Public Health, Medical & Vet Sciences, James Cook University, Douglas, QLD 4811, Australia,Centre for Tropical Bioinformatics and Molecular Biology, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns 4878, Australia
| | - Bijay P Dhungel
- Gene and Stem Cell Therapy Program Centenary Institute, The University of Sydney, Camperdown, NSW 2050, Australia,Faculty of Medicine & Health, The University of Sydney, Camperdown, NSW 2006, Australia,Centre for Tropical Bioinformatics and Molecular Biology, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns 4878, Australia
| | - John E J Rasko
- Gene and Stem Cell Therapy Program Centenary Institute, The University of Sydney, Camperdown, NSW 2050, Australia,Faculty of Medicine & Health, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Lionel Hebbard
- epartment of Molecular & Cell Biology, College of Public Health, Medical & Vet Sciences, James Cook University, Douglas, QLD 4811, Australia,Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, New South Wales, Australia
| | - Ulf Schmitz
- Corresponding author. Ulf Schmitz, Department of Molecular and Cell Biology, College of Public Health, Medical and Vet Sciences, James Cook University, Douglas, QLD 4811, Australia. E-mail:
| |
Collapse
|
11
|
Abstract
Covalently closed, single-stranded circular RNAs can be produced from viral RNA genomes as well as from the processing of cellular housekeeping noncoding RNAs and precursor messenger RNAs. Recent transcriptomic studies have surprisingly uncovered that many protein-coding genes can be subjected to backsplicing, leading to widespread expression of a specific type of circular RNAs (circRNAs) in eukaryotic cells. Here, we discuss experimental strategies used to discover and characterize diverse circRNAs at both the genome and individual gene scales. We further highlight the current understanding of how circRNAs are generated and how the mature transcripts function. Some circRNAs act as noncoding RNAs to impact gene regulation by serving as decoys or competitors for microRNAs and proteins. Others form extensive networks of ribonucleoprotein complexes or encode functional peptides that are translated in response to certain cellular stresses. Overall, circRNAs have emerged as an important class of RNAmolecules in gene expression regulation that impact many physiological processes, including early development, immune responses, neurogenesis, and tumorigenesis.
Collapse
Affiliation(s)
- Li Yang
- Center for Molecular Medicine, Children's Hospital, Fudan University and Shanghai Key Laboratory of Medical Epigenetics, International Laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai, China;
| | - Jeremy E Wilusz
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Therapeutic Innovation Center, Baylor College of Medicine, Houston, Texas, USA;
| | - Ling-Ling Chen
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China;
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
- School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China
| |
Collapse
|
12
|
Nielsen AF, Bindereif A, Bozzoni I, Hanan M, Hansen TB, Irimia M, Kadener S, Kristensen LS, Legnini I, Morlando M, Jarlstad Olesen MT, Pasterkamp RJ, Preibisch S, Rajewsky N, Suenkel C, Kjems J. Best practice standards for circular RNA research. Nat Methods 2022; 19:1208-1220. [PMID: 35618955 PMCID: PMC9759028 DOI: 10.1038/s41592-022-01487-2] [Citation(s) in RCA: 63] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 03/16/2022] [Indexed: 12/26/2022]
Abstract
Circular RNAs (circRNAs) are formed in all domains of life and via different mechanisms. There has been an explosion in the number of circRNA papers in recent years; however, as a relatively young field, circRNA biology has an urgent need for common experimental standards for isolating, analyzing, expressing and depleting circRNAs. Here we propose a set of guidelines for circRNA studies based on the authors' experience. This Perspective will specifically address the major class of circRNAs in Eukarya that are generated by a spliceosome-catalyzed back-splicing event. We hope that the implementation of best practice principles for circRNA research will help move the field forward and allow a better functional understanding of this fascinating group of RNAs.
Collapse
Affiliation(s)
- Anne F Nielsen
- Interdisciplinary Nanoscience Center, Aarhus University, Aarhus, Denmark
- Center for Cellular Signal Patterns (CellPAT), Aarhus University, Aarhus, Denmark
| | - Albrecht Bindereif
- Department of Biology and Chemistry, Institute of Biochemistry, Justus Liebig University of Giessen, Giessen, Germany
| | - Irene Bozzoni
- Department of Biology and Biotechnology, Charles Darwin, and Center for Life Nano- & Neuro-Science, Fondazione Istituto Italiano di Tecnologia (IIT), Sapienza University of Rome, Rome, Italy
| | - Mor Hanan
- Department of Biological Chemistry, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Thomas B Hansen
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
- TargoVax - Clinical Science, Oslo, Norway
| | - Manuel Irimia
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- ICREA, Barcelona, Spain
| | | | | | - Ivano Legnini
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Mariangela Morlando
- Department of Pharmaceutical Sciences, 'Department of Excellence 2018-2022', University of Perugia, Perugia, Italy
| | | | - R Jeroen Pasterkamp
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Stephan Preibisch
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- HHMI Janelia Research campus, Ashburn, VA, USA
| | - Nikolaus Rajewsky
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Christin Suenkel
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Lonza - Drug Product Services, Basel, Switzerland
| | - Jørgen Kjems
- Interdisciplinary Nanoscience Center, Aarhus University, Aarhus, Denmark.
- Center for Cellular Signal Patterns (CellPAT), Aarhus University, Aarhus, Denmark.
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
| |
Collapse
|
13
|
Mi Z, Zhongqiang C, Caiyun J, Yanan L, Jianhua W, Liang L. Circular RNA detection methods: A minireview. Talanta 2022; 238:123066. [PMID: 34808570 DOI: 10.1016/j.talanta.2021.123066] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 11/11/2021] [Accepted: 11/12/2021] [Indexed: 12/21/2022]
Abstract
Circular RNA (circRNA), a novel type of covalently closed RNA, is implicated in several developmental and metabolic disease processes. CircRNAs exhibit tissue-specific expression, and are stable, abundant, and highly conserved, making them ideal biomarkers for diagnosis and prognosis. Accurate profiling of circRNA, however, is a prerequisite for their clinical application. Traditional methods such as northern blotting, RT-qPCR, and microarray analysis provide useful but limited information. To address these issues, a number of novel assays have recently emerged, such as droplet digital PCR (ddPCR), isothermal exponential amplification, and rolling cycle amplification, which increase the sensitivity and specificity of circRNA detection. Herein, we summarize the advantages and limitations of the new detection methods and discuss the challenges as well as future directions.
Collapse
Affiliation(s)
- Zhang Mi
- Department of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Chen Zhongqiang
- School of Medicine, Jianghan University, Wuhan, 430056, China
| | - Jiang Caiyun
- Department of Pharmacy, The Third Affiliate Hospital of Sun Yat-Sen University, Guangzhou, 510630, China
| | - Liu Yanan
- Department of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Wu Jianhua
- Department of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Liu Liang
- Department of Pharmacy, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
| |
Collapse
|
14
|
Ma XK, Xue W, Chen LL, Yang L. CIRCexplorer pipelines for circRNA annotation and quantification from non-polyadenylated RNA-seq datasets. Methods 2021; 196:3-10. [PMID: 33588028 DOI: 10.1016/j.ymeth.2021.02.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/02/2021] [Accepted: 02/05/2021] [Indexed: 01/01/2023] Open
Abstract
Covalently closed circular RNAs (circRNAs) produced by back-splicing of exon(s) are co-expressed with their cognate linear RNAs from the same gene loci. Most circRNAs are fully overlapped with their cognate linear RNAs in sequences except the back-spliced junction (BSJ) site, thus challenging the computational detection, experimental validation and hence functional evaluation of circRNAs. Nevertheless, specific bioinformatic pipelines were developed to identify fragments mapped to circRNA-featured BSJ sites, and circRNAs were pervasively identified from non-polyadenylated RNA-seq datasets in different cell lines/tissues and across species. Precise identification and quantification of circRNAs provide a basis to further understand their functions. Here, we describe detailed computational steps to annotate and quantify circRNAs using a series of CIRCexplorer pipelines.
Collapse
Affiliation(s)
- Xu-Kai Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Wei Xue
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Ling-Ling Chen
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China; School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Li Yang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Shanghai 201210, China.
| |
Collapse
|
15
|
Taniue K, Akimitsu N. Fusion Genes and RNAs in Cancer Development. Noncoding RNA 2021; 7:10. [PMID: 33557176 PMCID: PMC7931065 DOI: 10.3390/ncrna7010010] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/02/2021] [Accepted: 02/03/2021] [Indexed: 02/07/2023] Open
Abstract
Fusion RNAs are a hallmark of some cancers. They result either from chromosomal rearrangements or from splicing mechanisms that are non-chromosomal rearrangements. Chromosomal rearrangements that result in gene fusions are particularly prevalent in sarcomas and hematopoietic malignancies; they are also common in solid tumors. The splicing process can also give rise to more complex RNA patterns in cells. Gene fusions frequently affect tyrosine kinases, chromatin regulators, or transcription factors, and can cause constitutive activation, enhancement of downstream signaling, and tumor development, as major drivers of oncogenesis. In addition, some fusion RNAs have been shown to function as noncoding RNAs and to affect cancer progression. Fusion genes and RNAs will therefore become increasingly important as diagnostic and therapeutic targets for cancer development. Here, we discuss the function, biogenesis, detection, clinical relevance, and therapeutic implications of oncogenic fusion genes and RNAs in cancer development. Further understanding the molecular mechanisms that regulate how fusion RNAs form in cancers is critical to the development of therapeutic strategies against tumorigenesis.
Collapse
Affiliation(s)
- Kenzui Taniue
- Isotope Science Center, The University of Tokyo, 2-11-16, Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
- Cancer Genomics and Precision Medicine, Division of Gastroenterology and Hematology/Oncology, Department of Medicine, Asahikawa Medical University, 2-1 Midorigaoka Higashi, Asahikawa, Hokkaido 078-8510, Japan
| | - Nobuyoshi Akimitsu
- Isotope Science Center, The University of Tokyo, 2-11-16, Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
| |
Collapse
|
16
|
Zong T, Yang Y, Zhao H, Li L, Liu M, Fu X, Tang G, Zhou H, Aung LHH, Li P, Wang J, Wang Z, Yu T. tsRNAs: Novel small molecules from cell function and regulatory mechanism to therapeutic targets. Cell Prolif 2021; 54:e12977. [PMID: 33507586 PMCID: PMC7941233 DOI: 10.1111/cpr.12977] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 12/07/2020] [Accepted: 12/18/2020] [Indexed: 12/18/2022] Open
Abstract
tsRNAs are small fragments of RNAs with specific lengths that are generated by particular ribonucleases, such as dicer and angiogenin (ANG), clipping on the rings of transfer RNAs (tRNAs) in specific cells and tissues under specific conditions. Depending on where the splicing site is, tsRNAs can be segmented into two main types, tRNA‐derived stress‐induced RNAs (tiRNAs) and tRNA‐derived fragments (tRFs). Many studies have shown that tsRNAs are functional molecules, not the random degradative products of tRNAs. Notably, due to their regulatory mechanism in regulating mRNA stability, transcription, ribosomal RNA (rRNA) synthesis and RNA reverse transcription, tsRNAs are significantly involved in the cell function, such as cell proliferation, migration, cycle and apoptosis, as well as the occurrence and development of a variety of diseases. In addition, tsRNAs may represent a new generation of clinical biomarkers or therapeutic targets because of their stable structures, high conservation and widely distribution, particularly in the peripheral tissues, bodily fluids and exosomes. In this review, we describe the generation, function and mechanism of tsRNAs and illustrate the current research progress of tsRNAs in various diseases, highlight their potentials as biomarkers and therapeutic targets in clinical application. Although our understanding of tsRNAs is still in infancy, the application prospects shown in this field deserve further exploration.
Collapse
Affiliation(s)
- Tingyu Zong
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yanyan Yang
- Department of Immunology, School of Basic Medicine, Qingdao University, Qingdao, China
| | - Hui Zhao
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lin Li
- Department of Vascular surgery, Qingdao Hiser Medical Center, Qingdao, China
| | - Meixin Liu
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiuxiu Fu
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Guozhang Tang
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hong Zhou
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lynn Htet Htet Aung
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Peifeng Li
- Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jianxun Wang
- Department of Immunology, School of Basic Medicine, Qingdao University, Qingdao, China
| | - Zhibin Wang
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tao Yu
- Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China.,Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China
| |
Collapse
|
17
|
Chen H, Shan G. The physiological function of long-noncoding RNAs. Noncoding RNA Res 2020; 5:178-184. [PMID: 32959025 PMCID: PMC7494506 DOI: 10.1016/j.ncrna.2020.09.003] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 09/15/2020] [Indexed: 12/11/2022] Open
Abstract
The physiological processes of cells and organisms are regulated by various biological macromolecules, including long-noncoding RNAs (lncRNAs), which cannot be translated into protein and are different from small-noncoding RNAs on their length. In animals, lncRNAs are involved in development, metabolism, reproduction, aging and other life events by cis or trans effects. For many functional lncRNAs, there is growing evidence that they play different roles on cellular level and organismal level. On the other hand, many annotated lncRNAs are not essential and could be transcription noises. In this minireview, we investigate the physiological function of lncRNAs in cells and focus on their functions and functional mechanisms on the organismal level. The studies on lncRNAs using different classic animal models such as worms and flies are summarized and discussed in this article.
Collapse
Affiliation(s)
- He Chen
- CAS Key Laboratory of Innate Immunity and Chronic Disease, CAS Center for Excellence in Molecular Cell Science, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, 230027, China
| | - Ge Shan
- CAS Key Laboratory of Innate Immunity and Chronic Disease, CAS Center for Excellence in Molecular Cell Science, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui Province, 230027, China
| |
Collapse
|
18
|
Xu B, Meng Y, Jin Y. RNA structures in alternative splicing and back-splicing. WILEY INTERDISCIPLINARY REVIEWS-RNA 2020; 12:e1626. [PMID: 32929887 DOI: 10.1002/wrna.1626] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 08/14/2020] [Accepted: 08/22/2020] [Indexed: 12/12/2022]
Abstract
Alternative splicing greatly expands the transcriptomic and proteomic diversities related to physiological and developmental processes in higher eukaryotes. Splicing of long noncoding RNAs, and back- and trans- splicing further expanded the regulatory repertoire of alternative splicing. RNA structures were shown to play an important role in regulating alternative splicing and back-splicing. Application of novel sequencing technologies made it possible to identify genome-wide RNA structures and interaction networks, which might provide new insights into RNA splicing regulation in vitro to in vivo. The emerging transcription-folding-splicing paradigm is changing our understanding of RNA alternative splicing regulation. Here, we review the insights into the roles and mechanisms of RNA structures in alternative splicing and back-splicing, as well as how disruption of these structures affects alternative splicing and then leads to human diseases. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.
Collapse
Affiliation(s)
- Bingbing Xu
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Zhejiang, Hangzhou, China
| | - Yijun Meng
- College of Life and Environmental Sciences, Hangzhou Normal University, Zhejiang, Hangzhou, China
| | - Yongfeng Jin
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Zhejiang, Hangzhou, China
| |
Collapse
|
19
|
Chen YJ, Chen CY, Mai TL, Chuang CF, Chen YC, Gupta SK, Yen L, Wang YD, Chuang TJ. Genome-wide, integrative analysis of circular RNA dysregulation and the corresponding circular RNA-microRNA-mRNA regulatory axes in autism. Genome Res 2020; 30:375-391. [PMID: 32127416 PMCID: PMC7111521 DOI: 10.1101/gr.255463.119] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 02/24/2020] [Indexed: 02/07/2023]
Abstract
Circular RNAs (circRNAs), a class of long noncoding RNAs, are known to be enriched in mammalian neural tissues. Although a wide range of dysregulation of gene expression in autism spectrum disorder (ASD) have been reported, the role of circRNAs in ASD remains largely unknown. Here, we performed genome-wide circRNA expression profiling in postmortem brains from individuals with ASD and controls and identified 60 circRNAs and three coregulated modules that were perturbed in ASD. By integrating circRNA, microRNA, and mRNA dysregulation data derived from the same cortex samples, we identified 8170 ASD-associated circRNA-microRNA-mRNA interactions. Putative targets of the axes were enriched for ASD risk genes and genes encoding inhibitory postsynaptic density (PSD) proteins, but not for genes implicated in monogenetic forms of other brain disorders or genes encoding excitatory PSD proteins. This reflects the previous observation that ASD-derived organoids show overproduction of inhibitory neurons. We further confirmed that some ASD risk genes (NLGN1, STAG1, HSD11B1, VIP, and UBA6) were regulated by an up-regulated circRNA (circARID1A) via sponging a down-regulated microRNA (miR-204-3p) in human neuronal cells. Particularly, alteration of NLGN1 expression is known to affect the dynamic processes of memory consolidation and strengthening. To the best of our knowledge, this is the first systems-level view of circRNA regulatory networks in ASD cortex samples. We provided a rich set of ASD-associated circRNA candidates and the corresponding circRNA-microRNA-mRNA axes, particularly those involving ASD risk genes. Our findings thus support a role for circRNA dysregulation and the corresponding circRNA-microRNA-mRNA axes in ASD pathophysiology.
Collapse
Affiliation(s)
- Yen-Ju Chen
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan.,Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Te-Lun Mai
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Chih-Fan Chuang
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Yu-Chen Chen
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Sachin Kumar Gupta
- Department of Pathology and Immunology.,Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Laising Yen
- Department of Pathology and Immunology.,Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Yi-Da Wang
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Trees-Juen Chuang
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan.,Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| |
Collapse
|
20
|
Balamurali D, Gorohovski A, Detroja R, Palande V, Raviv-Shay D, Frenkel-Morgenstern M. ChiTaRS 5.0: the comprehensive database of chimeric transcripts matched with druggable fusions and 3D chromatin maps. Nucleic Acids Res 2020; 48:D825-D834. [PMID: 31747015 PMCID: PMC7145514 DOI: 10.1093/nar/gkz1025] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Revised: 10/18/2019] [Accepted: 10/26/2019] [Indexed: 12/11/2022] Open
Abstract
Chimeric RNA transcripts are formed when exons from two genes fuse together, often due to chromosomal translocations, transcriptional errors or trans-splicing effect. While these chimeric RNAs produce functional proteins only in certain cases, they play a significant role in disease phenotyping and progression. ChiTaRS 5.0 (http://chitars.md.biu.ac.il/) is the latest and most comprehensive chimeric transcript repository, with 111 582 annotated entries from eight species, including 23 167 known human cancer breakpoints. The database includes unique information correlating chimeric breakpoints with 3D chromatin contact maps, generated from public datasets of chromosome conformation capture techniques (Hi-C). In this update, we have added curated information on druggable fusion targets matched with chimeric breakpoints, which are applicable to precision medicine in cancers. The introduction of a new section that lists chimeric RNAs in various cell-lines is another salient feature. Finally, using text-mining techniques, novel chimeras in Alzheimer's disease, schizophrenia, dyslexia and other diseases were collected in ChiTaRS. Thus, this improved version is an extensive catalogue of chimeras from multiple species. It extends our understanding of the evolution of chimeric transcripts in eukaryotes and contributes to the analysis of 3D genome conformational changes and the functional role of chimeras in the etiopathogenesis of cancers and other complex diseases.
Collapse
Affiliation(s)
- Deepak Balamurali
- Laboratory of Cancer Genomics and Biocomputing of Complex Diseases, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Alessandro Gorohovski
- Laboratory of Cancer Genomics and Biocomputing of Complex Diseases, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Rajesh Detroja
- Laboratory of Cancer Genomics and Biocomputing of Complex Diseases, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Vikrant Palande
- Laboratory of Cancer Genomics and Biocomputing of Complex Diseases, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Dorith Raviv-Shay
- Laboratory of Cancer Genomics and Biocomputing of Complex Diseases, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Milana Frenkel-Morgenstern
- Laboratory of Cancer Genomics and Biocomputing of Complex Diseases, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| |
Collapse
|
21
|
LaRoche-Johnston F, Monat C, Cousineau B. Detection of Group II Intron-Generated Chimeric mRNAs in Bacterial Cells. Methods Mol Biol 2020; 2079:95-107. [PMID: 31728964 DOI: 10.1007/978-1-4939-9904-0_7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Chimeric RNAs are the transcripts composed of exons from two separate genes or transcripts. Although the presence of these joined RNA molecules have mainly been documented in a variety of eukaryotes, we recently demonstrated that the Ll.LtrB group II intron, from the gram-positive bacterium Lactococcus lactis, can generate chimeric mRNAs through a novel intergenic trans-splicing pathway. Here we describe the detailed experimental procedures to detect group II intron-generated mRNA-mRNA chimeras from total RNA extracts using stringent reverse transcription conditions along with a reverse splicing-deficient group II intron as a negative control.
Collapse
Affiliation(s)
| | - Caroline Monat
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
| | - Benoit Cousineau
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada.
| |
Collapse
|
22
|
Xiao MS, Wilusz JE. An improved method for circular RNA purification using RNase R that efficiently removes linear RNAs containing G-quadruplexes or structured 3' ends. Nucleic Acids Res 2019; 47:8755-8769. [PMID: 31269210 PMCID: PMC6895279 DOI: 10.1093/nar/gkz576] [Citation(s) in RCA: 126] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 06/05/2019] [Accepted: 06/20/2019] [Indexed: 01/08/2023] Open
Abstract
Thousands of eukaryotic protein-coding genes generate circular RNAs that have covalently linked ends and are resistant to degradation by exonucleases. To prove their circularity as well as biochemically enrich these transcripts, it has become standard in the field to use the 3′-5′ exonuclease RNase R. Here, we demonstrate that standard protocols involving RNase R can fail to digest >20% of all highly expressed linear RNAs, but these shortcomings can largely be overcome. RNAs with highly structured 3′ ends, including snRNAs and histone mRNAs, are naturally resistant to RNase R, but can be efficiently degraded once a poly(A) tail has been added to their ends. In addition, RNase R stalls in the body of many polyadenylated mRNAs, especially at G-rich sequences that have been previously annotated as G-quadruplex (G4) structures. Upon replacing K+ (which stabilizes G4s) with Li+ in the reaction buffer, we find that RNase R is now able to proceed through these sequences and fully degrade the mRNAs in their entirety. In total, our results provide important improvements to the current methods used to isolate circular RNAs as well as a way to reveal RNA structures that may naturally inhibit degradation by cellular exonucleases.
Collapse
Affiliation(s)
- Mei-Sheng Xiao
- Department of Biochemistry and Biophysics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Jeremy E Wilusz
- Department of Biochemistry and Biophysics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| |
Collapse
|
23
|
Chuang TJ, Chen YJ, Chen CY, Mai TL, Wang YD, Yeh CS, Yang MY, Hsiao YT, Chang TH, Kuo TC, Cho HH, Shen CN, Kuo HC, Lu MY, Chen YH, Hsieh SC, Chiang TW. Integrative transcriptome sequencing reveals extensive alternative trans-splicing and cis-backsplicing in human cells. Nucleic Acids Res 2019; 46:3671-3691. [PMID: 29385530 PMCID: PMC6283421 DOI: 10.1093/nar/gky032] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Accepted: 01/13/2018] [Indexed: 01/16/2023] Open
Abstract
Transcriptionally non-co-linear (NCL) transcripts can originate from trans-splicing (trans-spliced RNA; 'tsRNA') or cis-backsplicing (circular RNA; 'circRNA'). While numerous circRNAs have been detected in various species, tsRNAs remain largely uninvestigated. Here, we utilize integrative transcriptome sequencing of poly(A)- and non-poly(A)-selected RNA-seq data from diverse human cell lines to distinguish between tsRNAs and circRNAs. We identified 24,498 NCL events and found that a considerable proportion (20-35%) of them arise from both tsRNAs and circRNAs, representing extensive alternative trans-splicing and cis-backsplicing in human cells. We show that sequence generalities of exon circularization are also observed in tsRNAs. Recapitulation of NCL RNAs further shows that inverted Alu repeats can simultaneously promote the formation of tsRNAs and circRNAs. However, tsRNAs and circRNAs exhibit quite different, or even opposite, expression patterns, in terms of correlation with the expression of their co-linear counterparts, expression breadth/abundance, transcript stability, and subcellular localization preference. These results indicate that tsRNAs and circRNAs may play different regulatory roles and analysis of NCL events should take the joint effects of different NCL-splicing types and joint effects of multiple NCL events into consideration. This study describes the first transcriptome-wide analysis of trans-splicing and cis-backsplicing, expanding our understanding of the complexity of the human transcriptome.
Collapse
Affiliation(s)
- Trees-Juen Chuang
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan.,Genome and Systems Biology Degree Program, National Taiwan University, Taipei 10617 & Academia Sinica, Taipei 11529, Taiwan
| | - Yen-Ju Chen
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan.,Genome and Systems Biology Degree Program, National Taiwan University, Taipei 10617 & Academia Sinica, Taipei 11529, Taiwan
| | - Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Te-Lun Mai
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Yi-Da Wang
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Chung-Shu Yeh
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan.,Institute of Biochemistry and Molecular Biology, National Yang-Ming University, Taipei 11221, Taiwan
| | - Min-Yu Yang
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Yu-Ting Hsiao
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | | | - Tzu-Chien Kuo
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Hsin-Hua Cho
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Chia-Ning Shen
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Hung-Chih Kuo
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei 11529, Taiwan
| | - Mei-Yeh Lu
- High Throughput Genomics Core, Biodiversity Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Yi-Hua Chen
- High Throughput Genomics Core, Biodiversity Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Shan-Chi Hsieh
- Institute of Cellular and Organismic Biology, Academia Sinica, Taipei 11529, Taiwan
| | - Tai-Wei Chiang
- Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| |
Collapse
|
24
|
Chen CY, Chuang TJ. Comment on "A comprehensive overview and evaluation of circular RNA detection tools". PLoS Comput Biol 2019; 15:e1006158. [PMID: 31150384 PMCID: PMC6544197 DOI: 10.1371/journal.pcbi.1006158] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 03/17/2018] [Indexed: 11/18/2022] Open
Affiliation(s)
- Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | | |
Collapse
|
25
|
Pervouchine DD. Circular exonic RNAs: When RNA structure meets topology. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2019; 1862:194384. [PMID: 31102674 DOI: 10.1016/j.bbagrm.2019.05.002] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 05/08/2019] [Accepted: 05/08/2019] [Indexed: 12/12/2022]
Abstract
Although RNA circularization was first documented in the 1990s, the extent to which it occurs was not known until recent advances in high-throughput sequencing enabled the widespread identification of circular RNAs (circRNAs). Despite this, many aspects of circRNA biogenesis, structure, and function yet remain obscure. This review focuses on circular exonic RNAs, a subclass of circRNAs that are generated through backsplicing. Here, I hypothesize that RNA secondary structure can be the common factor that promotes both exon skipping and spliceosomal RNA circularization, and that backsplicing of double-stranded regions could generate topologically linked circRNA molecules. CircRNAs manifest themselves by the presence of tail-to-head exon junctions, which were previously attributed to post-transcriptional exon permutation and repetition. I revisit these observations and argue that backsplicing does not automatically imply RNA circularization because tail-to-head exon junctions give only local information about transcript architecture and, therefore, they are in principle insufficient to determine globally circular topology. This article is part of a Special Issue entitled: RNA structure and splicing regulation edited by Francisco Baralle, Ravindra Singh and Stefan Stamm.
Collapse
Affiliation(s)
- Dmitri D Pervouchine
- Skolkovo Institute of Science and Technology, 3 Nobel St, Moscow 143026, Russia; Faculty of Bioengineering and Bioinformatics, Moscow State University, Leninskiye Gory 1-73, Moscow 119234, Russia.
| |
Collapse
|
26
|
Chen CY, Chuang TJ. NCLcomparator: systematically post-screening non-co-linear transcripts (circular, trans-spliced, or fusion RNAs) identified from various detectors. BMC Bioinformatics 2019; 20:3. [PMID: 30606103 PMCID: PMC6318855 DOI: 10.1186/s12859-018-2589-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 12/21/2018] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Non-co-linear (NCL) transcripts consist of exonic sequences that are topologically inconsistent with the reference genome in an intragenic fashion (circular or intragenic trans-spliced RNAs) or in an intergenic fashion (fusion or intergenic trans-spliced RNAs). On the basis of RNA-seq data, numerous NCL event detectors have been developed and detected thousands of NCL events in diverse species. However, there are great discrepancies in the identification results among detectors, indicating a considerable proportion of false positives in the detected NCL events. Although several helpful guidelines for evaluating the performance of NCL event detectors have been provided, a systematic guideline for measurement of NCL events identified by existing tools has not been available. RESULTS We develop a software, NCLcomparator, for systematically post-screening the intragenic or intergenic NCL events identified by various NCL detectors. NCLcomparator first examine whether the input NCL events are potentially false positives derived from ambiguous alignments (i.e., the NCL events have an alternative co-linear explanation or multiple matches against the reference genome). To evaluate the reliability of the identified NCL events, we define the NCL score (NCLscore) based on the variation in the number of supporting NCL junction reads identified by the tools examined. Of the input NCL events, we show that the ambiguous alignment-derived events have relatively lower NCLscore values than the other events, indicating that an NCL event with a higher NCLscore has a higher level of reliability. To help selecting highly expressed NCL events, NCLcomparator also provides a series of useful measurements such as the expression levels of the detected NCL events and their corresponding host genes and the junction usage of the co-linear splice junctions at both NCL donor and acceptor sites. CONCLUSION NCLcomparator provides useful guidelines, with the input of identified NCL events from various detectors and the corresponding paired-end RNA-seq data only, to help users selecting potentially high-confidence NCL events for further functional investigation. The software thus helps to facilitate future studies into NCL events, shedding light on the fundamental biology of this important but understudied class of transcripts. NCLcomparator is freely accessible at https://github.com/TreesLab/NCLcomparator .
Collapse
Affiliation(s)
- Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei, 11529 Taiwan
| | | |
Collapse
|
27
|
Disruption of INOS, a Gene Encoding myo-Inositol Phosphate Synthase, Causes Male Sterility in Drosophila melanogaster. G3-GENES GENOMES GENETICS 2018; 8:2913-2922. [PMID: 29991509 PMCID: PMC6118315 DOI: 10.1534/g3.118.200403] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Inositol is a precursor for the phospholipid membrane component phosphatidylinositol (PI), involved in signal transduction pathways, endoplasmic reticulum stress, and osmoregulation. Alterations of inositol metabolism have been implicated in human reproductive issues, the therapeutic effects of drugs used to treat epilepsy and bipolar disorder, spinal cord defects, and diseases including diabetes and Alzheimer’s. The sole known inositol synthetic enzyme is myo-inositol synthase (MIPS), and the homolog in Drosophilia melanogaster is encoded by the Inos gene. Three identical deletion strains (inosΔDF/CyO) were constructed, confirmed by PCR and sequencing, and homozygotes (inosΔDF/inosΔDF) were shown to lack the transcript encoding the MIPS enzyme. Without inositol, homozygous inosΔDF deletion fertilized eggs develop only to the first-instar larval stage. When transferred as pupae to food without inositol, however, inosΔDF homozygotes die significantly sooner than wild-type flies. Even with dietary inositol the homozygous inosΔDF males are sterile. An inos allele, with a P-element inserted into the first intron, fails to complement this male sterile phenotype. An additional copy of the Inos gene inserted into another chromosome rescues all the phenotypes. These genetic and phenotypic analyses establish D. melanogaster as an excellent model organism in which to examine the role of inositol synthesis in development and reproduction.
Collapse
|
28
|
He Y, Yuan C, Chen L, Lei M, Zellmer L, Huang H, Liao DJ. Transcriptional-Readthrough RNAs Reflect the Phenomenon of "A Gene Contains Gene(s)" or "Gene(s) within a Gene" in the Human Genome, and Thus Are Not Chimeric RNAs. Genes (Basel) 2018; 9:E40. [PMID: 29337901 PMCID: PMC5793191 DOI: 10.3390/genes9010040] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 12/29/2017] [Accepted: 01/07/2018] [Indexed: 02/06/2023] Open
Abstract
Tens of thousands of chimeric RNAs, i.e., RNAs with sequences of two genes, have been identified in human cells. Most of them are formed by two neighboring genes on the same chromosome and are considered to be derived via transcriptional readthrough, but a true readthrough event still awaits more evidence and trans-splicing that joins two transcripts together remains as a possible mechanism. We regard those genomic loci that are transcriptionally read through as unannotated genes, because their transcriptional and posttranscriptional regulations are the same as those of already-annotated genes, including fusion genes formed due to genetic alterations. Therefore, readthrough RNAs and fusion-gene-derived RNAs are not chimeras. Only those two-gene RNAs formed at the RNA level, likely via trans-splicing, without corresponding genes as genomic parents, should be regarded as authentic chimeric RNAs. However, since in human cells, procedural and mechanistic details of trans-splicing have never been disclosed, we doubt the existence of trans-splicing. Therefore, there are probably no authentic chimeras in humans, after readthrough and fusion-gene derived RNAs are all put back into the group of ordinary RNAs. Therefore, it should be further determined whether in human cells all two-neighboring-gene RNAs are derived from transcriptional readthrough and whether trans-splicing truly exists.
Collapse
Affiliation(s)
- Yan He
- Key Lab of Endemic and Ethnic Diseases of the Ministry of Education of China in Guizhou Medical University, Guiyang 550004, Guizhou, China.
| | - Chengfu Yuan
- Department of Biochemistry, China Three Gorges University, Yichang City 443002, Hubei, China.
| | - Lichan Chen
- Hormel Institute, University of Minnesota, Austin, MN 55912, USA.
| | - Mingjuan Lei
- Hormel Institute, University of Minnesota, Austin, MN 55912, USA.
| | - Lucas Zellmer
- Masonic Cancer Center, University of Minnesota, 435 E. River Road, Minneapolis, MN 55455, USA.
| | - Hai Huang
- School of Clinical Laboratory Science, Guizhou Medical University, Guiyang 550004, Guizhou, China.
| | - Dezhong Joshua Liao
- Key Lab of Endemic and Ethnic Diseases of the Ministry of Education of China in Guizhou Medical University, Guiyang 550004, Guizhou, China.
- Department of Pathology, Guizhou Medical University Hospital, Guiyang 550004, Guizhou, China.
| |
Collapse
|
29
|
Jiao J, Gao T, Shi H, Sheng A, Xiang Y, Shu Y, Li G. A method to directly assay circRNA in real samples. Chem Commun (Camb) 2018; 54:13451-13454. [DOI: 10.1039/c8cc08319c] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
‘MicroRNA sponge’ and duplex-specific nuclease (DSN)-assisted signal amplification were employed to propose a method for direct assay of circular RNA (circRNA) in real samples, which is rapid, sensitive, and easy to operate.
Collapse
Affiliation(s)
- Jin Jiao
- State Key Laboratory of Pharmaceutical Biotechnology and Collaborative Innovation Center of Chemistry for Life Sciences
- Department of Biochemistry
- Nanjing University
- Nanjing 210093
- P. R. China
| | - Tao Gao
- State Key Laboratory of Pharmaceutical Biotechnology and Collaborative Innovation Center of Chemistry for Life Sciences
- Department of Biochemistry
- Nanjing University
- Nanjing 210093
- P. R. China
| | - Hai Shi
- State Key Laboratory of Pharmaceutical Biotechnology and Collaborative Innovation Center of Chemistry for Life Sciences
- Department of Biochemistry
- Nanjing University
- Nanjing 210093
- P. R. China
| | - Anzhi Sheng
- Center for Molecular Recognition and Biosensing
- School of Life Sciences
- Shanghai University
- Shanghai
- P. R. China
| | - Yang Xiang
- State Key Laboratory of Pharmaceutical Biotechnology and Collaborative Innovation Center of Chemistry for Life Sciences
- Department of Biochemistry
- Nanjing University
- Nanjing 210093
- P. R. China
| | - Yongqian Shu
- Department of Oncology
- The First Affiliated Hospital of Nanjing Medical University
- Nanjing 210029
- P. R. China
| | - Genxi Li
- State Key Laboratory of Pharmaceutical Biotechnology and Collaborative Innovation Center of Chemistry for Life Sciences
- Department of Biochemistry
- Nanjing University
- Nanjing 210093
- P. R. China
| |
Collapse
|
30
|
The circular RNA circBIRC6 participates in the molecular circuitry controlling human pluripotency. Nat Commun 2017; 8:1149. [PMID: 29074849 PMCID: PMC5658440 DOI: 10.1038/s41467-017-01216-w] [Citation(s) in RCA: 232] [Impact Index Per Article: 33.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Accepted: 08/29/2017] [Indexed: 12/24/2022] Open
Abstract
Accumulating evidence indicates that circular RNAs (circRNAs) are abundant in the human transcriptome. However, their involvement in biological processes, including pluripotency, remains mostly undescribed. We identified a subset of circRNAs that are enriched in undifferentiated human embryonic stem cells (hESCs) and demonstrated that two, circBIRC6 and circCORO1C, are functionally associated with the pluripotent state. Mechanistically, we found that circBIRC6 is enriched in the AGO2 complex and directly interacts with microRNAs, miR-34a, and miR-145, which are known to modulate target genes that maintain pluripotency. Correspondingly, circBIRC6 attenuates the downregulation of these target genes and suppresses hESC differentiation. We further identified hESC-enriched splicing factors (SFs) and demonstrated that circBIRC6 biogenesis in hESCs is promoted by the SF ESRP1, whose expression is controlled by the core pluripotency-associated factors, OCT4 and NANOG. Collectively, our data suggest that circRNA serves as a microRNA “sponge” to regulate the molecular circuitry, which modulates human pluripotency and differentiation. Circular RNAs are abundant in the transcriptome and are implicated in the regulation of a range of biological processes. Here the authors identify circBIRC6 as a microRNA sponge that helps modulate human pluripotency and early lineage differentiation.
Collapse
|
31
|
Latysheva NS, Oates ME, Maddox L, Flock T, Gough J, Buljan M, Weatheritt RJ, Babu MM. Molecular Principles of Gene Fusion Mediated Rewiring of Protein Interaction Networks in Cancer. Mol Cell 2017; 63:579-592. [PMID: 27540857 PMCID: PMC5003813 DOI: 10.1016/j.molcel.2016.07.008] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Revised: 06/14/2016] [Accepted: 07/14/2016] [Indexed: 11/26/2022]
Abstract
Gene fusions are common cancer-causing mutations, but the molecular principles by which fusion protein products affect interaction networks and cause disease are not well understood. Here, we perform an integrative analysis of the structural, interactomic, and regulatory properties of thousands of putative fusion proteins. We demonstrate that genes that form fusions (i.e., parent genes) tend to be highly connected hub genes, whose protein products are enriched in structured and disordered interaction-mediating features. Fusion often results in the loss of these parental features and the depletion of regulatory sites such as post-translational modifications. Fusion products disproportionately connect proteins that did not previously interact in the protein interaction network. In this manner, fusion products can escape cellular regulation and constitutively rewire protein interaction networks. We suggest that the deregulation of central, interaction-prone proteins may represent a widespread mechanism by which fusion proteins alter the topology of cellular signaling pathways and promote cancer.
Collapse
Affiliation(s)
- Natasha S Latysheva
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK.
| | - Matt E Oates
- Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK
| | - Louis Maddox
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Tilman Flock
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Julian Gough
- Department of Computer Science, University of Bristol, Bristol BS8 1UB, UK
| | - Marija Buljan
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Robert J Weatheritt
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK; The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - M Madan Babu
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK.
| |
Collapse
|
32
|
Chwalenia K, Facemire L, Li H. Chimeric RNAs in cancer and normal physiology. WILEY INTERDISCIPLINARY REVIEWS-RNA 2017; 8. [DOI: 10.1002/wrna.1427] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 04/27/2017] [Accepted: 04/28/2017] [Indexed: 12/20/2022]
Affiliation(s)
- Katarzyna Chwalenia
- Department of Pathology, School of Medicine; University of Virginia; Charlottesville VA USA
| | - Loryn Facemire
- Department of Pathology, School of Medicine; University of Virginia; Charlottesville VA USA
| | - Hui Li
- Department of Pathology, School of Medicine; University of Virginia; Charlottesville VA USA
- Department of Biochemistry and Molecular Genetics, School of Medicine; University of Virginia; Charlottesville VA USA
| |
Collapse
|
33
|
Abstract
The pervasive expression of circular RNAs (circRNAs) is a recently discovered feature of gene expression in highly diverged eukaryotes. Numerous algorithms that are used to detect genome-wide circRNA expression from RNA sequencing (RNA-seq) data have been developed in the past few years, but there is little overlap in their predictions and no clear gold-standard method to assess the accuracy of these algorithms. We review sources of experimental and bioinformatic biases that complicate the accurate discovery of circRNAs and discuss statistical approaches to address these biases. We conclude with a discussion of the current experimental progress on the topic.
Collapse
|
34
|
Gorohovski A, Tagore S, Palande V, Malka A, Raviv-Shay D, Frenkel-Morgenstern M. ChiTaRS-3.1-the enhanced chimeric transcripts and RNA-seq database matched with protein-protein interactions. Nucleic Acids Res 2016; 45:D790-D795. [PMID: 27899596 PMCID: PMC5210585 DOI: 10.1093/nar/gkw1127] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2016] [Revised: 10/26/2016] [Accepted: 10/30/2016] [Indexed: 12/17/2022] Open
Abstract
Discovery of chimeric RNAs, which are produced by chromosomal translocations as well as the joining of exons from different genes by trans-splicing, has added a new level of complexity to our study and understanding of the transcriptome. The enhanced ChiTaRS-3.1 database (http://chitars.md.biu.ac.il) is designed to make widely accessible a wealth of mined data on chimeric RNAs, with easy-to-use analytical tools built-in. The database comprises 34 922 chimeric transcripts along with 11 714 cancer breakpoints. In this latest version, we have included multiple cross-references to GeneCards, iHop, PubMed, NCBI, Ensembl, OMIM, RefSeq and the Mitelman collection for every entry in the ‘Full Collection’. In addition, for every chimera, we have added a predicted chimeric protein–protein interaction (ChiPPI) network, which allows for easy visualization of protein partners of both parental and fusion proteins for all human chimeras. The database contains a comprehensive annotation for 34 922 chimeric transcripts from eight organisms, and includes the manual annotation of 200 sense-antiSense (SaS) chimeras. The current improvements in the content and functionality to the ChiTaRS database make it a central resource for the study of chimeric transcripts and fusion proteins.
Collapse
Affiliation(s)
- Alessandro Gorohovski
- Faculty of Medicine in Galilee, Bar-Ilan University, Henrietta Szold 8, Safed 13195, Israel
| | - Somnath Tagore
- Faculty of Medicine in Galilee, Bar-Ilan University, Henrietta Szold 8, Safed 13195, Israel
| | - Vikrant Palande
- Faculty of Medicine in Galilee, Bar-Ilan University, Henrietta Szold 8, Safed 13195, Israel
| | - Assaf Malka
- Faculty of Medicine in Galilee, Bar-Ilan University, Henrietta Szold 8, Safed 13195, Israel
| | - Dorith Raviv-Shay
- Faculty of Medicine in Galilee, Bar-Ilan University, Henrietta Szold 8, Safed 13195, Israel
| | - Milana Frenkel-Morgenstern
- Faculty of Medicine in Galilee, Bar-Ilan University, Henrietta Szold 8, Safed 13195, Israel. Corresponding author:
| |
Collapse
|
35
|
Abstract
Circular RNA from backspliced exons (or exonic circular RNA, circRNA) is a type of covalently closed non-colinear RNA that was recently rediscovered in eukaryotes. Although circRNAs are often expressed at low levels, emerging evidence indicates that many circRNAs are linked to physiological development and various diseases. Notably, circRNAs have been shown to serve as oncogenic stimuli or tumor suppressors in cancer. circRNAs may regulate gene expression through different mechanisms. In addition, circRNAs have been shown to be useful as biomarkers of diseases due to their stability, specific expression and relation to diseases both in cells and in extracellular fluid. This review summarizes current knowledge of human circRNAs and discusses the emerging role and clinical implication of these multifarious transcripts.
Collapse
Affiliation(s)
- Dongbin Lyu
- a Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University , Shanghai , China.,b Department of Oncology , Shanghai Medical College, Fudan University , Shanghai , China
| | - Shenglin Huang
- a Fudan University Shanghai Cancer Center and Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University , Shanghai , China.,b Department of Oncology , Shanghai Medical College, Fudan University , Shanghai , China
| |
Collapse
|
36
|
Latysheva NS, Babu MM. Discovering and understanding oncogenic gene fusions through data intensive computational approaches. Nucleic Acids Res 2016; 44:4487-503. [PMID: 27105842 PMCID: PMC4889949 DOI: 10.1093/nar/gkw282] [Citation(s) in RCA: 110] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Accepted: 03/24/2016] [Indexed: 12/21/2022] Open
Abstract
Although gene fusions have been recognized as important drivers of cancer for decades, our understanding of the prevalence and function of gene fusions has been revolutionized by the rise of next-generation sequencing, advances in bioinformatics theory and an increasing capacity for large-scale computational biology. The computational work on gene fusions has been vastly diverse, and the present state of the literature is fragmented. It will be fruitful to merge three camps of gene fusion bioinformatics that appear to rarely cross over: (i) data-intensive computational work characterizing the molecular biology of gene fusions; (ii) development research on fusion detection tools, candidate fusion prioritization algorithms and dedicated fusion databases and (iii) clinical research that seeks to either therapeutically target fusion transcripts and proteins or leverages advances in detection tools to perform large-scale surveys of gene fusion landscapes in specific cancer types. In this review, we unify these different-yet highly complementary and symbiotic-approaches with the view that increased synergy will catalyze advancements in gene fusion identification, characterization and significance evaluation.
Collapse
Affiliation(s)
- Natasha S Latysheva
- MRC Laboratory of Molecular Biology, Francis Crick Ave, Cambridge CB2 0QH, United Kingdom
| | - M Madan Babu
- MRC Laboratory of Molecular Biology, Francis Crick Ave, Cambridge CB2 0QH, United Kingdom
| |
Collapse
|
37
|
Lei Q, Li C, Zuo Z, Huang C, Cheng H, Zhou R. Evolutionary Insights into RNA trans-Splicing in Vertebrates. Genome Biol Evol 2016; 8:562-77. [PMID: 26966239 PMCID: PMC4824033 DOI: 10.1093/gbe/evw025] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Pre-RNA splicing is an essential step in generating mature mRNA. RNA trans-splicing combines two separate pre-mRNA molecules to form a chimeric non-co-linear RNA, which may exert a function distinct from its original molecules. Trans-spliced RNAs may encode novel proteins or serve as noncoding or regulatory RNAs. These novel RNAs not only increase the complexity of the proteome but also provide new regulatory mechanisms for gene expression. An increasing amount of evidence indicates that trans-splicing occurs frequently in both physiological and pathological processes. In addition, mRNA reprogramming based on trans-splicing has been successfully applied in RNA-based therapies for human genetic diseases. Nevertheless, clarifying the extent and evolution of trans-splicing in vertebrates and developing detection methods for trans-splicing remain challenging. In this review, we summarize previous research, highlight recent advances in trans-splicing, and discuss possible splicing mechanisms and functions from an evolutionary viewpoint.
Collapse
Affiliation(s)
- Quan Lei
- Department of Genetics, College of Life Sciences, Wuhan University, P.R. China
| | - Cong Li
- Department of Genetics, College of Life Sciences, Wuhan University, P.R. China
| | - Zhixiang Zuo
- Department of Genetics, College of Life Sciences, Wuhan University, P.R. China
| | - Chunhua Huang
- Department of Cell Biology, College of Life Sciences, Wuhan University, P.R. China
| | - Hanhua Cheng
- Department of Cell Biology, College of Life Sciences, Wuhan University, P.R. China
| | - Rongjia Zhou
- Department of Genetics, College of Life Sciences, Wuhan University, P.R. China
| |
Collapse
|
38
|
Izuogu OG, Alhasan AA, Alafghani HM, Santibanez-Koref M, Elliott DJ, Elliot DJ, Jackson MS. PTESFinder: a computational method to identify post-transcriptional exon shuffling (PTES) events. BMC Bioinformatics 2016; 17:31. [PMID: 26758031 PMCID: PMC4711006 DOI: 10.1186/s12859-016-0881-4] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 01/06/2016] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Transcripts, which have been subject to Post-transcriptional exon shuffling (PTES), have an exon order inconsistent with the underlying genomic sequence. These have been identified in a wide variety of tissues and cell types from many eukaryotes, and are now known to be mostly circular, cytoplasmic, and non-coding. Although there is no uniformly ascribed function, several have been shown to be involved in gene regulation. Accurate identification of these transcripts can, however, be difficult due to artefacts from a wide variety of sources. RESULTS Here, we present a computational method, PTESFinder, to identify these transcripts from high throughput RNAseq data. Uniquely, it systematically excludes potential artefacts emanating from pseudogenes, segmental duplications, and template switching, and outputs both PTES and canonical exon junction counts to facilitate comparative analyses. In comparison with four existing methods, PTESFinder achieves highest specificity and comparable sensitivity at a variety of read depths. PTESFinder also identifies between 13 % and 41.6 % more structures, compared to publicly available methods recently used to identify human circular RNAs. CONCLUSIONS With high sensitivity and specificity, user-adjustable filters that target known sources of false positives, and tailored output to facilitate comparison of transcript levels, PTESFinder will facilitate the discovery and analysis of these poorly understood transcripts.
Collapse
Affiliation(s)
- Osagie G Izuogu
- Institute of Genetic Medicine, Newcastle University, Newcastle Upon Tyne, UK.
| | - Abd A Alhasan
- Institute of Genetic Medicine, Newcastle University, Newcastle Upon Tyne, UK.
| | - Hani M Alafghani
- Security Forces Hostpital, P. O. Box 2748-24268-8541, Makkah, Kingdom of Saudi Arabia.
| | | | | | - David J Elliot
- Institute of Genetic Medicine, Newcastle University, Newcastle Upon Tyne, UK.
| | - Michael S Jackson
- Institute of Genetic Medicine, Newcastle University, Newcastle Upon Tyne, UK.
| |
Collapse
|
39
|
Circular RNA enrichment in platelets is a signature of transcriptome degradation. Blood 2015; 127:e1-e11. [PMID: 26660425 DOI: 10.1182/blood-2015-06-649434] [Citation(s) in RCA: 150] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 12/01/2015] [Indexed: 02/07/2023] Open
Abstract
In platelets, splicing and translation occur in the absence of a nucleus. However, the integrity and stability of mRNAs derived from megakaryocyte progenitor cells remain poorly quantified on a transcriptome-wide level. As circular RNAs (circRNAs) are resistant to degradation by exonucleases, their abundance relative to linear RNAs can be used as a surrogate marker for mRNA stability in the absence of transcription. Here we show that circRNAs are enriched in human platelets 17- to 188-fold relative to nucleated tissues and 14- to 26-fold relative to samples digested with RNAse R to selectively remove linear RNA. We compare RNAseq read depths inside and outside circRNAs to provide in silico evidence of transcript circularity, show that exons within circRNAs are enriched on average 12.7 times in platelets relative to nucleated tissues and identify 3162 genes significantly enriched for circRNAs, including some where all RNAseq reads appear to be derived from circular molecules. We also confirm that this is a feature of other anucleate cells through transcriptome sequencing of mature erythrocytes, demonstrate that circRNAs are not enriched in cultured megakaryocytes, and demonstrate that linear RNAs decay more rapidly than circRNAs in platelet preparations. Collectively, these results suggest that circulating platelets have lost >90% of their progenitor mRNAs and that translation in platelets occurs against the backdrop of a highly degraded transcriptome. Finally, we find that transcripts previously classified as products of reverse transcriptase template switching are both enriched in platelets and resistant to decay, countering the recent suggestion that up to 50% of rearranged RNAs are artifacts.
Collapse
|
40
|
Chuang TJ, Wu CS, Chen CY, Hung LY, Chiang TW, Yang MY. NCLscan: accurate identification of non-co-linear transcripts (fusion, trans-splicing and circular RNA) with a good balance between sensitivity and precision. Nucleic Acids Res 2015; 44:e29. [PMID: 26442529 PMCID: PMC4756807 DOI: 10.1093/nar/gkv1013] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Accepted: 09/24/2015] [Indexed: 12/19/2022] Open
Abstract
Analysis of RNA-seq data often detects numerous ‘non-co-linear’ (NCL) transcripts, which comprised sequence segments that are topologically inconsistent with their corresponding DNA sequences in the reference genome. However, detection of NCL transcripts involves two major challenges: removal of false positives arising from alignment artifacts and discrimination between different types of NCL transcripts (trans-spliced, circular or fusion transcripts). Here, we developed a new NCL-transcript-detecting method (‘NCLscan’), which utilized a stepwise alignment strategy to almost completely eliminate false calls (>98% precision) without sacrificing true positives, enabling NCLscan outperform 18 other publicly-available tools (including fusion- and circular-RNA-detecting tools) in terms of sensitivity and precision, regardless of the generation strategy of simulated dataset, type of intragenic or intergenic NCL event, read depth of coverage, read length or expression level of NCL transcript. With the high accuracy, NCLscan was applied to distinguishing between trans-spliced, circular and fusion transcripts on the basis of poly(A)- and nonpoly(A)-selected RNA-seq data. We showed that circular RNAs were expressed more ubiquitously, more abundantly and less cell type-specifically than trans-spliced and fusion transcripts. Our study thus describes a robust pipeline for the discovery of NCL transcripts, and sheds light on the fundamental biology of these non-canonical RNA events in human transcriptome.
Collapse
Affiliation(s)
- Trees-Juen Chuang
- Division of Physical and Computational Genomics, Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Chan-Shuo Wu
- Division of Physical and Computational Genomics, Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Chia-Ying Chen
- Division of Physical and Computational Genomics, Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Li-Yuan Hung
- Division of Physical and Computational Genomics, Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Tai-Wei Chiang
- Division of Physical and Computational Genomics, Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| | - Min-Yu Yang
- Division of Physical and Computational Genomics, Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan
| |
Collapse
|
41
|
Chen I, Chen CY, Chuang TJ. Biogenesis, identification, and function of exonic circular RNAs. WILEY INTERDISCIPLINARY REVIEWS-RNA 2015; 6:563-79. [PMID: 26230526 PMCID: PMC5042038 DOI: 10.1002/wrna.1294] [Citation(s) in RCA: 299] [Impact Index Per Article: 33.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2015] [Revised: 06/11/2015] [Accepted: 06/16/2015] [Indexed: 01/20/2023]
Abstract
Circular RNAs (circRNAs) arise during post-transcriptional processes, in which a single-stranded RNA molecule forms a circle through covalent binding. Previously, circRNA products were often regarded to be splicing intermediates, by-products, or products of aberrant splicing. But recently, rapid advances in high-throughput RNA sequencing (RNA-seq) for global investigation of nonco-linear (NCL) RNAs, which comprised sequence segments that are topologically inconsistent with the reference genome, leads to renewed interest in this type of NCL RNA (i.e., circRNA), especially exonic circRNAs (ecircRNAs). Although the biogenesis and function of ecircRNAs are mostly unknown, some ecircRNAs are abundant, highly expressed, or evolutionarily conserved. Some ecircRNAs have been shown to affect microRNA regulation, and probably play roles in regulating parental gene transcription, cell proliferation, and RNA-binding proteins, indicating their functional potential for development as diagnostic tools. To date, thousands of ecircRNAs have been identified in multiple tissues/cell types from diverse species, through analyses of RNA-seq data. However, the detection of ecircRNA candidates involves several major challenges, including discrimination between ecircRNAs and other types of NCL RNAs (e.g., trans-spliced RNAs and genetic rearrangements); removal of sequencing errors, alignment errors, and in vitro artifacts; and the reconciliation of heterogeneous results arising from the use of different bioinformatics methods or sequencing data generated under different treatments. Such challenges may severely hamper the understanding of ecircRNAs. Herein, we review the biogenesis, identification, properties, and function of ecircRNAs, and discuss some unanswered questions regarding ecircRNAs. We also evaluate the accuracy (in terms of sensitivity and precision) of some well-known circRNA-detecting methods.
Collapse
Affiliation(s)
- Iju Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Chia-Ying Chen
- Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | | |
Collapse
|
42
|
Szabo L, Morey R, Palpant NJ, Wang PL, Afari N, Jiang C, Parast MM, Murry CE, Laurent LC, Salzman J. Statistically based splicing detection reveals neural enrichment and tissue-specific induction of circular RNA during human fetal development. Genome Biol 2015; 16:126. [PMID: 26076956 PMCID: PMC4506483 DOI: 10.1186/s13059-015-0690-5] [Citation(s) in RCA: 425] [Impact Index Per Article: 47.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2015] [Accepted: 06/08/2015] [Indexed: 02/06/2023] Open
Abstract
Background The pervasive expression of circular RNA is a recently discovered feature of gene expression in highly diverged eukaryotes, but the functions of most circular RNAs are still unknown. Computational methods to discover and quantify circular RNA are essential. Moreover, discovering biological contexts where circular RNAs are regulated will shed light on potential functional roles they may play. Results We present a new algorithm that increases the sensitivity and specificity of circular RNA detection by discovering and quantifying circular and linear RNA splicing events at both annotated and un-annotated exon boundaries, including intergenic regions of the genome, with high statistical confidence. Unlike approaches that rely on read count and exon homology to determine confidence in prediction of circular RNA expression, our algorithm uses a statistical approach. Using our algorithm, we unveiled striking induction of general and tissue-specific circular RNAs, including in the heart and lung, during human fetal development. We discover regions of the human fetal brain, such as the frontal cortex, with marked enrichment for genes where circular RNA isoforms are dominant. Conclusions The vast majority of circular RNA production occurs at major spliceosome splice sites; however, we find the first examples of developmentally induced circular RNAs processed by the minor spliceosome, and an enriched propensity of minor spliceosome donors to splice into circular RNA at un-annotated, rather than annotated, exons. Together, these results suggest a potentially significant role for circular RNA in human development. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0690-5) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Linda Szabo
- Stanford Department of Biochemistry and Stanford Cancer Institute, Stanford, CA, USA.
| | - Robert Morey
- UC San Diego Department of Reproductive Medicine, San Diego, CA, USA.
| | - Nathan J Palpant
- Center for Cardiovascular Biology, Institute for Stem Cell and Regenerative Medicine, Departments of Pathology, Bioengineering and Medicine/Cardiology, University of Washington, Seattle, WA, 98109, USA.
| | - Peter L Wang
- Stanford Department of Biochemistry and Stanford Cancer Institute, Stanford, CA, USA.
| | - Nastaran Afari
- UC San Diego Department of Reproductive Medicine, San Diego, CA, USA.
| | - Chuan Jiang
- UC San Diego Department of Reproductive Medicine, San Diego, CA, USA.
| | - Mana M Parast
- UC San Diego Department of Pathology, San Diego, CA, USA.
| | - Charles E Murry
- Center for Cardiovascular Biology, Institute for Stem Cell and Regenerative Medicine, Departments of Pathology, Bioengineering and Medicine/Cardiology, University of Washington, Seattle, WA, 98109, USA.
| | - Louise C Laurent
- UC San Diego Department of Reproductive Medicine, San Diego, CA, USA.
| | - Julia Salzman
- Stanford Department of Biochemistry and Stanford Cancer Institute, Stanford, CA, USA.
| |
Collapse
|
43
|
Pan K, Lee JTH, Huang Z, Wong CM. Coupling and coordination in gene expression processes with pre-mRNA splicing. Int J Mol Sci 2015; 16:5682-96. [PMID: 25768347 PMCID: PMC4394499 DOI: 10.3390/ijms16035682] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2014] [Revised: 02/28/2015] [Accepted: 03/04/2015] [Indexed: 12/13/2022] Open
Abstract
RNA processing is a tightly regulated and highly complex pathway which includes transcription, splicing, editing, transportation, translation and degradation. It has been well-documented that splicing of RNA polymerase II medicated nascent transcripts occurs co-transcriptionally and is functionally coupled to other RNA processing. Recently, increasing experimental evidence indicated that pre-mRNA splicing influences RNA degradation and vice versa. In this review, we summarized the recent findings demonstrating the coupling of these two processes. In addition, we highlighted the importance of splicing in the production of intronic miRNA and circular RNAs, and hence the discovery of the novel mechanisms in the regulation of gene expression.
Collapse
|
44
|
Frenkel-Morgenstern M, Gorohovski A, Vucenovic D, Maestre L, Valencia A. ChiTaRS 2.1--an improved database of the chimeric transcripts and RNA-seq data with novel sense-antisense chimeric RNA transcripts. Nucleic Acids Res 2014; 43:D68-75. [PMID: 25414346 PMCID: PMC4383979 DOI: 10.1093/nar/gku1199] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Chimeric RNAs that comprise two or more different transcripts have been identified in many cancers and among the Expressed Sequence Tags (ESTs) isolated from different organisms; they might represent functional proteins and produce different disease phenotypes. The ChiTaRS 2.1 database of chimeric transcripts and RNA-Seq data (http://chitars.bioinfo.cnio.es/) is the second version of the ChiTaRS database and includes improvements in content and functionality. Chimeras from eight organisms have been collated including novel sense–antisense (SAS) chimeras resulting from the slippage of the sense and anti-sense intragenic regions. The new database version collects more than 29 000 chimeric transcripts and indicates the expression and tissue specificity for 333 entries confirmed by RNA-seq reads mapping the chimeric junction sites. User interface allows for rapid and easy analysis of evolutionary conservation of fusions, literature references and experimental data supporting fusions in different organisms. More than 1428 cancer breakpoints have been automatically collected from public databases and manually verified to identify their correct cross-references, genomic sequences and junction sites. As a result, the ChiTaRS 2.1 collection of chimeras from eight organisms and human cancer breakpoints extends our understanding of the evolution of chimeric transcripts in eukaryotes as well as their functional role in carcinogenic processes.
Collapse
Affiliation(s)
- Milana Frenkel-Morgenstern
- Structural Biology and BioComputing Program, Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain
| | - Alessandro Gorohovski
- Structural Biology and BioComputing Program, Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain
| | - Dunja Vucenovic
- Structural Biology and BioComputing Program, Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain
| | - Lorena Maestre
- Monoclonal Antibodies Unit, Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain
| | - Alfonso Valencia
- Structural Biology and BioComputing Program, Spanish National Cancer Research Centre (CNIO), Madrid 28029, Spain.
| |
Collapse
|