1
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Digby B, Finn S, Ó Broin P. Computational approaches and challenges in the analysis of circRNA data. BMC Genomics 2024; 25:527. [PMID: 38807085 PMCID: PMC11134749 DOI: 10.1186/s12864-024-10420-0] [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: 02/13/2024] [Accepted: 05/15/2024] [Indexed: 05/30/2024] Open
Abstract
Circular RNAs (circRNA) are a class of non-coding RNA, forming a single-stranded covalently closed loop structure generated via back-splicing. Advancements in sequencing methods and technologies in conjunction with algorithmic developments of bioinformatics tools have enabled researchers to characterise the origin and function of circRNAs, with practical applications as a biomarker of diseases becoming increasingly relevant. Computational methods developed for circRNA analysis are predicated on detecting the chimeric back-splice junction of circRNAs whilst mitigating false-positive sequencing artefacts. In this review, we discuss in detail the computational strategies developed for circRNA identification, highlighting a selection of tool strengths, weaknesses and assumptions. In addition to circRNA identification tools, we describe methods for characterising the role of circRNAs within the competing endogenous RNA (ceRNA) network, their interactions with RNA-binding proteins, and publicly available databases for rich circRNA annotation.
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Affiliation(s)
- Barry Digby
- School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland.
| | - Stephen Finn
- Discipline of Histopathology, School of Medicine, Trinity College Dublin and Cancer Molecular Diagnostic Laboratory, Dublin, Ireland
| | - Pilib Ó Broin
- School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland
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2
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Masante L, Susin G, Baudet ML. Droplet Digital PCR for the Detection and Quantification of Bona Fide CircRNAs. Methods Mol Biol 2024; 2765:107-126. [PMID: 38381336 DOI: 10.1007/978-1-0716-3678-7_6] [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] [Indexed: 02/22/2024]
Abstract
CircRNAs are covalently closed RNA molecules gaining increasing attention over the years. Initially considered mere splicing errors, circRNAs are now recognized as a novel class of endogenous, conserved RNAs, expressed in many different species. The unique structure, the low levels of expression, and the almost complete sequence overlap with the cognate linear RNA make their detection and quantification challenging. Moreover, it has become crucial to prove the circular nature of the targeted transcript and unequivocally distinguish the circRNA from its linear counterpart. Nowadays, the most widely used technique to quantify circRNA expression is real-time quantitative PCR (qPCR). However, in the particular case of quantification of circles, it shows several technical shortcomings which affect the accuracy of the quantification. To precisely assess circRNA expression level, droplet digital PCR (ddPCR) is rapidly taking over for the more popular qPCR. In this chapter, we describe the detailed procedure based on droplets partitioning to quantify both linear and circRNA abundancy and demonstrate the circularity of the transcript under study with high precision, in a single experiment.
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Affiliation(s)
- Linda Masante
- Department of Cellular, Computational and Integrative Biology - CIBIO, University of Trento, Trento, Italy
| | - Giorgia Susin
- Department of Cellular, Computational and Integrative Biology - CIBIO, University of Trento, Trento, Italy
| | - Marie-Laure Baudet
- Department of Cellular, Computational and Integrative Biology - CIBIO, University of Trento, Trento, Italy.
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3
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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: 32] [Impact Index Per Article: 10.7] [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.
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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:
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4
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Abstract
CircRNAs are a subclass of lncRNAs that have been found to be abundantly present in a wide range of species, including humans. CircRNAs are generally produced by a noncanonical splicing event called backsplicing that is dependent on the canonical splicing machinery, giving rise to circRNAs classified into three main categories: exonic circRNA, circular intronic RNA, and exon-intron circular RNA. Notably, circRNAs possess functional importance and display their functions through different mechanisms of action including sponging miRNAs, or even being translated into functional proteins. In addition, circRNAs also have great potential as biomarkers, particularly in cancer, thanks to their high stability, tissue type and developmental stage specificity, and their presence in biological fluids, which make them promising candidates as noninvasive biomarkers. In this chapter, we describe the most commonly used techniques for the study of circRNAs as cancer biomarkers, including high-throughput techniques such as RNA-Seq and microarrays, and other methods to analyze the presence of specific circRNAs in patient samples.
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Affiliation(s)
- Carla Solé
- Molecular Oncology Group, Biodonostia Research Institute, San Sebastián, Spain
| | - Gartze Mentxaka
- Molecular Oncology Group, Biodonostia Research Institute, San Sebastián, Spain
| | - Charles H Lawrie
- Molecular Oncology Group, Biodonostia Research Institute, San Sebastián, Spain. .,IKERBASQUE, Basque Foundation for Science, Bilbao, Spain. .,Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
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5
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Hong W, Zhang J, Dong H, Shi Y, Ma H, Zhou F, Xu B, Fu Y, Zhang S, Hou S, Li G, Wu Y, Chen S, Zhu X, You W, Shi F, Yang X, Gong Z, Huang J, Jin Y. Intron-targeted mutagenesis reveals roles for Dscam1 RNA pairing architecture-driven splicing bias in neuronal wiring. Cell Rep 2021; 36:109373. [PMID: 34260933 DOI: 10.1016/j.celrep.2021.109373] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 03/05/2021] [Accepted: 06/18/2021] [Indexed: 12/28/2022] Open
Abstract
Drosophila melanogaster Down syndrome cell adhesion molecule (Dscam1) can generate 38,016 different isoforms through largely stochastic, yet highly biased, alternative splicing. These isoforms are required for nervous functions. However, the functional significance of splicing bias remains unknown. Here, we provide evidence that Dscam1 splicing bias is required for mushroom body (MB) axonal wiring. We generate mutant flies with normal overall protein levels and an identical number but global changes in exon 4 and 9 isoform bias (DscamΔ4D-/- and DscamΔ9D-/-), respectively. In contrast to DscamΔ4D-/-, DscamΔ9D-/- exhibits remarkable MB defects, suggesting a variable domain-specific requirement for isoform bias. Importantly, changes in isoform bias cause axonal defects but do not influence the self-avoidance of axonal branches. We conclude that, in contrast to the isoform number that provides the molecular basis for neurite self-avoidance, isoform bias may play a role in MB axonal wiring by influencing non-repulsive signaling.
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Affiliation(s)
- Weiling Hong
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Jian Zhang
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Haiyang Dong
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Yang Shi
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Hongru Ma
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Fengyan Zhou
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Bingbing Xu
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Ying Fu
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Shixin Zhang
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Shouqing Hou
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Guo Li
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Yandan Wu
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Shuo Chen
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Xiaohua Zhu
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Wendong You
- Department of Neurosurgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Feng Shi
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Xiaofeng Yang
- Department of Neurosurgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Zhefeng Gong
- Department of Neuroscience, School of Medicine, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Jianhua Huang
- Institute of Insect Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China
| | - Yongfeng Jin
- MOE Laboratory of Biosystems Homeostasis & Protection and Innovation Center for Cell Signaling Network, College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China; Department of Neurosurgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang ZJ310058, China.
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6
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Joglekar A, Prjibelski A, Mahfouz A, Collier P, Lin S, Schlusche AK, Marrocco J, Williams SR, Haase B, Hayes A, Chew JG, Weisenfeld NI, Wong MY, Stein AN, Hardwick SA, Hunt T, Wang Q, Dieterich C, Bent Z, Fedrigo O, Sloan SA, Risso D, Jarvis ED, Flicek P, Luo W, Pitt GS, Frankish A, Smit AB, Ross ME, Tilgner HU. A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain. Nat Commun 2021; 12:463. [PMID: 33469025 PMCID: PMC7815907 DOI: 10.1038/s41467-020-20343-5] [Citation(s) in RCA: 119] [Impact Index Per Article: 29.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 11/27/2020] [Indexed: 01/19/2023] Open
Abstract
Splicing varies across brain regions, but the single-cell resolution of regional variation is unclear. We present a single-cell investigation of differential isoform expression (DIE) between brain regions using single-cell long-read sequencing in mouse hippocampus and prefrontal cortex in 45 cell types at postnatal day 7 ( www.isoformAtlas.com ). Isoform tests for DIE show better performance than exon tests. We detect hundreds of DIE events traceable to cell types, often corresponding to functionally distinct protein isoforms. Mostly, one cell type is responsible for brain-region specific DIE. However, for fewer genes, multiple cell types influence DIE. Thus, regional identity can, although rarely, override cell-type specificity. Cell types indigenous to one anatomic structure display distinctive DIE, e.g. the choroid plexus epithelium manifests distinct transcription-start-site usage. Spatial transcriptomics and long-read sequencing yield a spatially resolved splicing map. Our methods quantify isoform expression with cell-type and spatial resolution and it contributes to further our understanding of how the brain integrates molecular and cellular complexity.
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Affiliation(s)
- Anoushka Joglekar
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Andrey Prjibelski
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St Petersburg, Russia
| | - Ahmed Mahfouz
- Department of Human Genetics, Leiden University Medical Center, Leiden, 2333 ZC, The Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, 2333 ZC, The Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, 2628 XE, The Netherlands
| | - Paul Collier
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Susan Lin
- Graduate Program in Neuroscience, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10065, USA
- Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Anna Katharina Schlusche
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Jordan Marrocco
- Harold and Margaret Milliken Hatch Laboratory of Neuroendocrinology, The Rockefeller University, New York, NY, USA
| | | | - Bettina Haase
- The Vertebrate Genomes Lab, The Rockefeller University, New York, NY, USA
| | | | | | | | - Man Ying Wong
- Brain and Mind Research Institute and Appel Alzheimer's Research Institute, Weill Cornell Medicine, New York, NY, USA
| | | | - Simon A Hardwick
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Toby Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Qi Wang
- Section of Bioinformatics and Systems Cardiology, University Hospital, 96120, Heidelberg, Germany
| | - Christoph Dieterich
- Section of Bioinformatics and Systems Cardiology, University Hospital, 96120, Heidelberg, Germany
| | | | - Olivier Fedrigo
- The Vertebrate Genomes Lab, The Rockefeller University, New York, NY, USA
| | - Steven A Sloan
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Davide Risso
- Department of Statistical Sciences, University of Padova, Padova, Italy
| | - Erich D Jarvis
- The Vertebrate Genomes Lab, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Wenjie Luo
- Brain and Mind Research Institute and Appel Alzheimer's Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Geoffrey S Pitt
- Graduate Program in Neuroscience, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10065, USA
- Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - August B Smit
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - M Elizabeth Ross
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Hagen U Tilgner
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA.
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7
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Beltrán-García J, Osca-Verdegal R, Nacher-Sendra E, Pallardó FV, García-Giménez JL. Circular RNAs in Sepsis: Biogenesis, Function, and Clinical Significance. Cells 2020; 9:cells9061544. [PMID: 32630422 PMCID: PMC7349763 DOI: 10.3390/cells9061544] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 06/23/2020] [Accepted: 06/24/2020] [Indexed: 01/08/2023] Open
Abstract
Sepsis is a life-threatening condition that occurs when the body responds to an infection that damages it is own tissues. The major problem in sepsis is rapid, vital status deterioration in patients, which can progress to septic shock with multiple organ failure if not properly treated. As there are no specific treatments, early diagnosis is mandatory to reduce high mortality. Despite more than 170 different biomarkers being postulated, early sepsis diagnosis and prognosis remain a challenge for clinicians. Recent findings propose that circular RNAs (circRNAs) may play a prominent role in regulating the patients’ immune system against different pathogens, including bacteria and viruses. Mounting evidence also suggests that the misregulation of circRNAs is an early event in a wide range of diseases, including sepsis. Despite circRNA levels being altered in sepsis, the specific mechanisms controlling the dysregulation of these noncoding RNAs are not completely elucidated, although many factors are known to affect circRNA biogenesis. Therefore, there is a need to explore the molecular pathways that lead to this disorder. This review describes the role of this new class of regulatory RNAs in sepsis and the feasibility of using circRNAs as diagnostic biomarkers for sepsis, opening up new avenues for circRNA-based medicine.
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Affiliation(s)
- Jesús Beltrán-García
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, 28029 Madrid, Spain; (J.B.-G.); (F.V.P.)
- Instituto de Investigación Sanitaria INCLIVA, 46010 Valencia, Spain;
- Departamento de Fisiología, Facultad de Medicina y Odontología, Universitat de València, 46010 València, Spain;
| | - Rebeca Osca-Verdegal
- Instituto de Investigación Sanitaria INCLIVA, 46010 Valencia, Spain;
- Departamento de Fisiología, Facultad de Medicina y Odontología, Universitat de València, 46010 València, Spain;
| | - Elena Nacher-Sendra
- Departamento de Fisiología, Facultad de Medicina y Odontología, Universitat de València, 46010 València, Spain;
| | - Federico V. Pallardó
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, 28029 Madrid, Spain; (J.B.-G.); (F.V.P.)
- Instituto de Investigación Sanitaria INCLIVA, 46010 Valencia, Spain;
- Departamento de Fisiología, Facultad de Medicina y Odontología, Universitat de València, 46010 València, Spain;
| | - José Luis García-Giménez
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, 28029 Madrid, Spain; (J.B.-G.); (F.V.P.)
- Instituto de Investigación Sanitaria INCLIVA, 46010 Valencia, Spain;
- Departamento de Fisiología, Facultad de Medicina y Odontología, Universitat de València, 46010 València, Spain;
- Correspondence:
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8
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Xu B, Shi Y, Wu Y, Meng Y, Jin Y. Role of RNA secondary structures in regulating Dscam alternative splicing. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2019; 1862:194381. [DOI: 10.1016/j.bbagrm.2019.04.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 04/21/2019] [Accepted: 04/22/2019] [Indexed: 12/19/2022]
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9
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Haussmann IU, Ustaoglu P, Brauer U, Hemani Y, Dix TC, Soller M. Plasmid-based gap-repair recombineered transgenes reveal a central role for introns in mutually exclusive alternative splicing in Down Syndrome Cell Adhesion Molecule exon 4. Nucleic Acids Res 2019; 47:1389-1403. [PMID: 30541104 PMCID: PMC6379703 DOI: 10.1093/nar/gky1254] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 11/22/2018] [Accepted: 12/03/2018] [Indexed: 12/18/2022] Open
Abstract
Alternative splicing is a key feature of human genes, yet studying its regulation is often complicated by large introns. The Down Syndrome Cell Adhesion Molecule (Dscam) gene from Drosophila is one of the most complex genes generating vast molecular diversity by mutually exclusive alternative splicing. To resolve how alternative splicing in Dscam is regulated, we first developed plasmid-based UAS reporter genes for the Dscam variable exon 4 cluster and show that its alternative splicing is recapitulated by GAL4-mediated expression in neurons. We then developed gap-repair recombineering to very efficiently manipulate these large reporter plasmids in Escherichia coli using restriction enzymes or sgRNA/Cas9 DNA scission to capitalize on the many benefits of plasmids in phiC31 integrase-mediated transgenesis. Using these novel tools, we show that inclusion of Dscam exon 4 variables differs little in development and individual flies, and is robustly determined by sequences harbored in variable exons. We further show that introns drive selection of both proximal and distal variable exons. Since exon 4 cluster introns lack conserved sequences that could mediate robust long-range base-pairing to bring exons into proximity for splicing, our data argue for a central role of introns in mutually exclusive alternative splicing of Dscam exon 4 cluster.
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Affiliation(s)
- Irmgard U Haussmann
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.,School of Life Science, CSELS, Coventry University, Coventry CV1 5FB, UK
| | - Pinar Ustaoglu
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Ulrike Brauer
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Yash Hemani
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Thomas C Dix
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Matthias Soller
- School of Biosciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
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10
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Hardwick SA, Joglekar A, Flicek P, Frankish A, Tilgner HU. Getting the Entire Message: Progress in Isoform Sequencing. Front Genet 2019; 10:709. [PMID: 31475029 PMCID: PMC6706457 DOI: 10.3389/fgene.2019.00709] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 07/04/2019] [Indexed: 01/31/2023] Open
Abstract
The advent of second-generation sequencing and its application to RNA sequencing have revolutionized the field of genomics by allowing quantification of gene expression, as well as the definition of transcription start/end sites, exons, splice sites and RNA editing sites. However, due to the sequencing of fragments of cDNAs, these methods have not given a reliable picture of complete RNA isoforms. Third-generation sequencing has filled this gap and allows end-to-end sequencing of entire RNA/cDNA molecules. This approach to transcriptomics has been a "niche" technology for a couple of years but now is becoming mainstream with many different applications. Here, we review the background and progress made to date in this rapidly growing field. We start by reviewing the progressive realization that alternative splicing is omnipresent. We then focus on long-noncoding RNA isoforms and the distinct combination patterns of exons in noncoding and coding genes. We consider the implications of the recent technologies of direct RNA sequencing and single-cell isoform RNA sequencing. Finally, we discuss the parameters that define the success of long-read RNA sequencing experiments and strategies commonly used to make the most of such data.
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Affiliation(s)
- Simon A. Hardwick
- Brain and Mind Research Institute, Weill Cornell Medicine, NY, United States
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Anoushka Joglekar
- Brain and Mind Research Institute, Weill Cornell Medicine, NY, United States
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Hagen U. Tilgner
- Brain and Mind Research Institute, Weill Cornell Medicine, NY, United States
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11
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Arnaiz E, Sole C, Manterola L, Iparraguirre L, Otaegui D, Lawrie CH. CircRNAs and cancer: Biomarkers and master regulators. Semin Cancer Biol 2018; 58:90-99. [PMID: 30550956 DOI: 10.1016/j.semcancer.2018.12.002] [Citation(s) in RCA: 298] [Impact Index Per Article: 42.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 11/30/2018] [Accepted: 12/10/2018] [Indexed: 02/06/2023]
Abstract
Circular RNAs (circRNAs) are a novel class of regulatory RNAs that despite being relatively abundant have only recently begun to be explored. There are many thousands of genes that appear capable of producing circRNAs, however the function of all but a handful remain to be determined. What is emerging about these highly conserved molecules is that they play important roles in biology and cancer biology in particular. The most explored function of circRNAs is as master regulators of gene expression that act to sequester or ´sponge´ other gene expression regulators, in particular miRNAs. They have also been demonstrated to function via direct modulation of transcription, and by interfering with splicing mechanisms. Although generally expressed in low abundance when compared to their linear counterparts, they are often expressed in a tissue- and developmental stage- specific manner. Coupled with their remarkable resistance to RNAse activity due to a covalent closed cyclic structure, circRNAs show great promise as novel biomarkers of cancer and other diseases. In this review we consider the current state of knowledge regarding these molecules, their synthesis, function, and association with cancer. We will also review some of the challenges that remain to be resolved if this emerging class of RNAs are really to become useful in the clinic.
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Affiliation(s)
- Esther Arnaiz
- Molecular Oncology Group, Biodonostia Research Institute, Paseo Doctor Begiristain, s/n San Sebastián, 20014, Spain
| | - Carla Sole
- Molecular Oncology Group, Biodonostia Research Institute, Paseo Doctor Begiristain, s/n San Sebastián, 20014, Spain
| | - Lorea Manterola
- Molecular Oncology Group, Biodonostia Research Institute, Paseo Doctor Begiristain, s/n San Sebastián, 20014, Spain
| | - Leire Iparraguirre
- Multiple Sclerosis Group, Biodonostia Research Institute, Paseo Doctor Begiristain, s/n San Sebastián, 20014, Spain
| | - David Otaegui
- Multiple Sclerosis Group, Biodonostia Research Institute, Paseo Doctor Begiristain, s/n San Sebastián, 20014, Spain
| | - Charles H Lawrie
- Molecular Oncology Group, Biodonostia Research Institute, Paseo Doctor Begiristain, s/n San Sebastián, 20014, Spain; Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom; IKERBASQUE, Basque Foundation for Science, María Díaz Haroko Kalea, 3, 48013, Bilbao, Spain.
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12
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Gupta I, Collier PG, Haase B, Mahfouz A, Joglekar A, Floyd T, Koopmans F, Barres B, Smit AB, Sloan SA, Luo W, Fedrigo O, Ross ME, Tilgner HU. Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells. Nat Biotechnol 2018; 36:nbt.4259. [PMID: 30320766 DOI: 10.1038/nbt.4259] [Citation(s) in RCA: 219] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 08/20/2018] [Indexed: 01/10/2023]
Abstract
Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far. Although single splicing events have been described for ≤200 single cells with statistical confidence, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3' sequencing enables the identification of cellular subtypes, but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-type-specific combination patterns of distant splice sites. We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms.
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Affiliation(s)
- Ishaan Gupta
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, New York, USA
| | - Paul G Collier
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, New York, USA
| | | | - Ahmed Mahfouz
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, New York, USA
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, the Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands
| | - Anoushka Joglekar
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, New York, USA
| | - Taylor Floyd
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, New York, USA
| | - Frank Koopmans
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, the Netherlands
| | - Ben Barres
- Department of Neurobiology, Stanford University, Stanford, California, USA
| | - August B Smit
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, the Netherlands
| | - Steven A Sloan
- Department of Neurobiology, Stanford University, Stanford, California, USA
| | - Wenjie Luo
- Brain and Mind Research Institute and Appel Alzheimer's Research Institute, Weill Cornell Medicine, New York, New York, USA
| | | | - M Elizabeth Ross
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, New York, USA
| | - Hagen U Tilgner
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, New York, USA
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13
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Holdt LM, Kohlmaier A, Teupser D. Molecular functions and specific roles of circRNAs in the cardiovascular system. Noncoding RNA Res 2018; 3:75-98. [PMID: 30159442 PMCID: PMC6096412 DOI: 10.1016/j.ncrna.2018.05.002] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 05/11/2018] [Accepted: 05/11/2018] [Indexed: 12/25/2022] Open
Abstract
As part of the superfamily of long noncoding RNAs, circular RNAs (circRNAs) are emerging as a new type of regulatory molecules that partake in gene expression control. Here, we review the current knowledge about circRNAs in cardiovascular disease. CircRNAs are not only associated with different types of cardiovascular disease, but they have also been identified as intracellular effector molecules for pathophysiological changes in cardiovascular tissues, and as cardiovascular biomarkers. This evidence is put in the context of the current understanding of general circRNA biogenesis and of known interactions of circRNAs with DNA, RNA, and proteins.
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Affiliation(s)
- Lesca M. Holdt
- Institute of Laboratory Medicine, University Hospital, LMU Munich, Germany
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14
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Holdt LM, Kohlmaier A, Teupser D. Molecular roles and function of circular RNAs in eukaryotic cells. Cell Mol Life Sci 2018; 75:1071-1098. [PMID: 29116363 PMCID: PMC5814467 DOI: 10.1007/s00018-017-2688-5] [Citation(s) in RCA: 239] [Impact Index Per Article: 34.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 09/29/2017] [Accepted: 10/17/2017] [Indexed: 12/27/2022]
Abstract
Protein-coding and noncoding genes in eukaryotes are typically expressed as linear messenger RNAs, with exons arranged colinearly to their genomic order. Recent advances in sequencing and in mapping RNA reads to reference genomes have revealed that thousands of genes express also covalently closed circular RNAs. Many of these circRNAs are stable and contain exons, but are not translated into proteins. Here, we review the emerging understanding that both, circRNAs produced by co- and posttranscriptional head-to-tail "backsplicing" of a downstream splice donor to a more upstream splice acceptor, as well as circRNAs generated from intronic lariats during colinear splicing, may exhibit physiologically relevant regulatory functions in eukaryotes. We describe how circRNAs impact gene expression of their host gene locus by affecting transcriptional initiation and elongation or splicing, and how they partake in controlling the function of other molecules, for example by interacting with microRNAs and proteins. We conclude with an outlook how circRNA dysregulation affects disease, and how the stability of circRNAs might be exploited in biomedical applications.
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Affiliation(s)
- Lesca M Holdt
- Institute of Laboratory Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
| | - Alexander Kohlmaier
- Institute of Laboratory Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
- Faculty of Biology, Genetics, LMU Munich, Großhaderner Str. 2-4, 82152, Martinsried, Germany
| | - Daniel Teupser
- Institute of Laboratory Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
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15
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RNA sequencing and Prediction Tools for Circular RNAs Analysis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1087:17-33. [DOI: 10.1007/978-981-13-1426-1_2] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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16
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Tilgner H, Jahanbani F, Gupta I, Collier P, Wei E, Rasmussen M, Snyder M. Microfluidic isoform sequencing shows widespread splicing coordination in the human transcriptome. Genome Res 2017; 28:231-242. [PMID: 29196558 PMCID: PMC5793787 DOI: 10.1101/gr.230516.117] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Accepted: 11/30/2017] [Indexed: 12/21/2022]
Abstract
Understanding transcriptome complexity is crucial for understanding human biology and disease. Technologies such as Synthetic long-read RNA sequencing (SLR-RNA-seq) delivered 5 million isoforms and allowed assessing splicing coordination. Pacific Biosciences and Oxford Nanopore increase throughput also but require high input amounts or amplification. Our new droplet-based method, sparse isoform sequencing (spISO-seq), sequences 100k–200k partitions of 10–200 molecules at a time, enabling analysis of 10–100 million RNA molecules. SpISO-seq requires less than 1 ng of input cDNA, limiting or removing the need for prior amplification with its associated biases. Adjusting the number of reads devoted to each molecule reduces sequencing lanes and cost, with little loss in detection power. The increased number of molecules expands our understanding of isoform complexity. In addition to confirming our previously published cases of splicing coordination (e.g., BIN1), the greater depth reveals many new cases, such as MAPT. Coordination of internal exons is found to be extensive among protein coding genes: 23.5%–59.3% (95% confidence interval) of highly expressed genes with distant alternative exons exhibit coordination, showcasing the need for long-read transcriptomics. However, coordination is less frequent for noncoding sequences, suggesting a larger role of splicing coordination in shaping proteins. Groups of genes with coordination are involved in protein–protein interactions with each other, raising the possibility that coordination facilitates complex formation and/or function. We also find new splicing coordination types, involving initial and terminal exons. Our results provide a more comprehensive understanding of the human transcriptome and a general, cost-effective method to analyze it.
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Affiliation(s)
- Hagen Tilgner
- Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10021, USA
| | - Fereshteh Jahanbani
- Department of Genetics, Stanford University, Stanford, California 94304, USA
| | - Ishaan Gupta
- Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10021, USA
| | - Paul Collier
- Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York 10021, USA
| | - Eric Wei
- Department of Genetics, Stanford University, Stanford, California 94304, USA
| | | | - Michael Snyder
- Department of Genetics, Stanford University, Stanford, California 94304, USA
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17
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Abstract
Just a few years ago, it had been assumed that the dominant RNA isoforms produced from eukaryotic genes were variants of messenger RNA, functioning as intermediates in gene expression. In early 2012, however, a surprising discovery was made: circular RNA (circRNA) was shown to be a transcriptional product in thousands of human and mouse genes and in hundreds of cases constituted the dominant RNA isoform. Subsequent studies revealed that the expression of circRNAs is developmentally regulated, tissue and cell-type specific, and shared across the eukaryotic tree of life. These features suggest important functions for these molecules. Here, we describe major advances in the field of circRNA biology, focusing on the regulation of and functional roles played by these molecules.
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Affiliation(s)
- Steven P Barrett
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Julia Salzman
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
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18
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Ramanouskaya TV, Grinev VV. The determinants of alternative RNA splicing in human cells. Mol Genet Genomics 2017; 292:1175-1195. [PMID: 28707092 DOI: 10.1007/s00438-017-1350-0] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 07/06/2017] [Indexed: 12/29/2022]
Abstract
Alternative splicing represents an important level of the regulation of gene function in eukaryotic organisms. It plays a critical role in virtually every biological process within an organism, including regulation of cell division and cell death, differentiation of tissues in the embryo and the adult organism, as well as in cellular response to diverse environmental factors. In turn, studies of the last decade have shown that alternative splicing itself is controlled by different mechanisms. Unfortunately, there is no clear understanding of how these diverse mechanisms, or determinants, regulate and constrain the set of alternative RNA species produced from any particular gene in every cell of the human body. Here, we provide a consolidated overview of alternative splicing determinants including RNA-protein interactions, epigenetic regulation via chromatin remodeling, coupling of transcription-to-alternative splicing, effect of secondary structures in pre-RNA, and function of the RNA quality control systems. We also extensively and critically discuss some mechanistic insights on coordinated inclusion/exclusion of exons during the formation of mature RNA molecules. We conclude that the final structure of RNA is pre-determined by a complex interplay between cis- and trans-acting factors. Altogether, currently available empirical data significantly expand our understanding of the functioning of the alternative splicing machinery of cells in normal and pathological conditions. On the other hand, there are still many blind spots that require further deep investigations.
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19
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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.
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20
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Koo KM, Wee EJ, Trau M. High-speed biosensing strategy for non-invasive profiling of multiple cancer fusion genes in urine. Biosens Bioelectron 2017; 89:715-720. [DOI: 10.1016/j.bios.2016.11.024] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2016] [Revised: 11/03/2016] [Accepted: 11/08/2016] [Indexed: 11/29/2022]
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21
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Jin J, Vaud S, Zhelkovsky AM, Posfai J, McReynolds LA. Sensitive and specific miRNA detection method using SplintR Ligase. Nucleic Acids Res 2016; 44:e116. [PMID: 27154271 PMCID: PMC5291259 DOI: 10.1093/nar/gkw399] [Citation(s) in RCA: 78] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 04/25/2016] [Indexed: 12/11/2022] Open
Abstract
We describe a simple, specific and sensitive microRNA (miRNA) detection method that utilizes Chlorella virus DNA ligase (SplintR® Ligase). This two-step method involves ligation of adjacent DNA oligonucleotides hybridized to a miRNA followed by real-time quantitative PCR (qPCR). SplintR Ligase is 100X faster than either T4 DNA Ligase or T4 RNA Ligase 2 for RNA splinted DNA ligation. Only a 4–6 bp overlap between a DNA probe and miRNA was required for efficient ligation by SplintR Ligase. This property allows more flexibility in designing miRNA-specific ligation probes than methods that use reverse transcriptase for cDNA synthesis of miRNA. The qPCR SplintR ligation assay is sensitive; it can detect a few thousand molecules of miR-122. For miR-122 detection the SplintR qPCR assay, using a FAM labeled double quenched DNA probe, was at least 40× more sensitive than the TaqMan assay. The SplintR method, when coupled with NextGen sequencing, allowed multiplex detection of miRNAs from brain, kidney, testis and liver. The SplintR qPCR assay is specific; individual let-7 miRNAs that differ by one nucleotide are detected. The rapid kinetics and ability to ligate DNA probes hybridized to RNA with short complementary sequences makes SplintR Ligase a useful enzyme for miRNA detection.
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Affiliation(s)
- Jingmin Jin
- Division of RNA Biology, New England Biolabs, Ipswich, MA 01938-2773, USA
| | - Sophie Vaud
- Division of RNA Biology, New England Biolabs, Ipswich, MA 01938-2773, USA
| | | | - Janos Posfai
- Division of RNA Biology, New England Biolabs, Ipswich, MA 01938-2773, USA
| | - Larry A McReynolds
- Division of RNA Biology, New England Biolabs, Ipswich, MA 01938-2773, USA
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22
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Wee EJH, Trau M. Simple Isothermal Strategy for Multiplexed, Rapid, Sensitive, and Accurate miRNA Detection. ACS Sens 2016. [DOI: 10.1021/acssensors.6b00105] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Affiliation(s)
- Eugene J. H. Wee
- Center
for Personalized Nanomedicine, Australian Institute for Bioengineering
and Nanotechnology and ‡School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Matt Trau
- Center
for Personalized Nanomedicine, Australian Institute for Bioengineering
and Nanotechnology and ‡School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD 4072, Australia
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23
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Zhao L, Yang S, Zhang Y, Zhang Y, Hou C, Cheng Y, You X, Gu X, Zhao Z, Muhammad Tarique T. New Analytical Tool for the Detection of Ractopamine Abuse in Goat Skeletal Muscle by Potential Gene Expression Biomarkers. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2016; 64:1861-1867. [PMID: 26886866 DOI: 10.1021/acs.jafc.5b04956] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
In this study, quantification of mRNA gene expression was examined as biomarkers to detect ractopamaine abuse and ractopamaine residues in cashmere goats. It was focused on the identification of potential gene expression biomarkers and describing the coreletionship between gene expression and residue level by 58 animals for 49 days. The results showed that administration periods and residue levels significantly influenced mRNA expressions of the β2-adrenergic receptor (β2AR), the enzymes PRKACB, ADCY3, ATP1A3, ATP2A3, PTH, and MYLK, and the immune factors IL-1β and TNF-α. Statistical analysis like principal components analysis (PCA), hierarchical cluster analysis (HCA), and discriminant analysis (DA) showed that these genes can serve as potential biomarkers for ractopamine in skeletal muscle and that they are also suitable for describing different residue levels separately.
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Affiliation(s)
- Luyao Zhao
- Livestock-Product Quality and Safety Research Division, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences (CAAS) , Beijing 100081, PR China
| | - Shuming Yang
- Livestock-Product Quality and Safety Research Division, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences (CAAS) , Beijing 100081, PR China
| | - Yanhua Zhang
- Livestock-Product Quality and Safety Research Division, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences (CAAS) , Beijing 100081, PR China
| | - Ying Zhang
- Livestock-Product Quality and Safety Research Division, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences (CAAS) , Beijing 100081, PR China
| | - Can Hou
- Livestock-Product Quality and Safety Research Division, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences (CAAS) , Beijing 100081, PR China
| | - Yongyou Cheng
- Livestock-Product Quality and Safety Research Division, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences (CAAS) , Beijing 100081, PR China
| | - Xinyong You
- Livestock-Product Quality and Safety Research Division, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences (CAAS) , Beijing 100081, PR China
| | - Xu Gu
- Key Laboratory for Feed Biotechnology of the Ministry of Agriculture, Feed Research Institute, Chinese Academy of Agricultural Sciences , Beijing 10081, PR China
| | - Zhen Zhao
- Key Laboratory for Feed Biotechnology of the Ministry of Agriculture, Feed Research Institute, Chinese Academy of Agricultural Sciences , Beijing 10081, PR China
| | - Tunio Muhammad Tarique
- Livestock-Product Quality and Safety Research Division, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences (CAAS) , Beijing 100081, PR China
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24
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Bolisetty MT, Rajadinakaran G, Graveley BR. Determining exon connectivity in complex mRNAs by nanopore sequencing. Genome Biol 2015; 16:204. [PMID: 26420219 PMCID: PMC4588896 DOI: 10.1186/s13059-015-0777-z] [Citation(s) in RCA: 116] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2015] [Accepted: 09/11/2015] [Indexed: 11/29/2022] Open
Abstract
Short-read high-throughput RNA sequencing, though powerful, is limited in its ability to directly measure exon connectivity in mRNAs that contain multiple alternative exons located farther apart than the maximum read length. Here, we use the Oxford Nanopore MinION sequencer to identify 7,899 ‘full-length’ isoforms expressed from four Drosophila genes, Dscam1, MRP, Mhc, and Rdl. These results demonstrate that nanopore sequencing can be used to deconvolute individual isoforms and that it has the potential to be a powerful method for comprehensive transcriptome characterization.
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Affiliation(s)
- Mohan T Bolisetty
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, 06030, USA.,Present Address: The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06030, USA
| | - Gopinath Rajadinakaran
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, 06030, USA
| | - Brenton R Graveley
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, 06030, USA.
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25
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Nawy T. Splice and sequence. Nat Methods 2015. [DOI: 10.1038/nmeth.3427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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