1
|
Cao X, Zhang Y, Ding Y, Wan Y. Identification of RNA structures and their roles in RNA functions. Nat Rev Mol Cell Biol 2024:10.1038/s41580-024-00748-6. [PMID: 38926530 DOI: 10.1038/s41580-024-00748-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/28/2024] [Indexed: 06/28/2024]
Abstract
The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.
Collapse
Affiliation(s)
- Xinang Cao
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Yueying Zhang
- Department of Cell and Developmental Biology, John Innes Centre, Norwich, UK
| | - Yiliang Ding
- Department of Cell and Developmental Biology, John Innes Centre, Norwich, UK.
| | - Yue Wan
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, Singapore.
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
| |
Collapse
|
2
|
Siemers M, Lippegaus A, Papenfort K. ChimericFragments: computation, analysis and visualization of global RNA networks. NAR Genom Bioinform 2024; 6:lqae035. [PMID: 38633425 PMCID: PMC11023125 DOI: 10.1093/nargab/lqae035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 03/08/2024] [Accepted: 03/28/2024] [Indexed: 04/19/2024] Open
Abstract
RNA-RNA interactions are a key feature of post-transcriptional gene regulation in all domains of life. While ever more experimental protocols are being developed to study RNA duplex formation on a genome-wide scale, computational methods for the analysis and interpretation of the underlying data are lagging behind. Here, we present ChimericFragments, an analysis framework for RNA-seq experiments that produce chimeric RNA molecules. ChimericFragments implements a novel statistical method based on the complementarity of the base-pairing RNAs around their ligation site and provides an interactive graph-based visualization for data exploration and interpretation. ChimericFragments detects true RNA-RNA interactions with high precision and is compatible with several widely used experimental procedures such as RIL-seq, LIGR-seq or CLASH. We further demonstrate that ChimericFragments enables the systematic detection of novel RNA regulators and RNA-target pairs with crucial roles in microbial physiology and virulence. ChimericFragments is written in Julia and available at: https://github.com/maltesie/ChimericFragments.
Collapse
Affiliation(s)
- Malte Siemers
- Friedrich Schiller University, Institute of Microbiology, 07745 Jena, Germany
- Microverse Cluster, Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Anne Lippegaus
- Friedrich Schiller University, Institute of Microbiology, 07745 Jena, Germany
| | - Kai Papenfort
- Friedrich Schiller University, Institute of Microbiology, 07745 Jena, Germany
- Microverse Cluster, Friedrich Schiller University Jena, 07743 Jena, Germany
| |
Collapse
|
3
|
Li T, Cheng C, Liu J. Chemical and Enzyme-Mediated Chemical Reactions for Studying Nucleic Acids and Their Modifications. Chembiochem 2024:e202400220. [PMID: 38742371 DOI: 10.1002/cbic.202400220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/10/2024] [Accepted: 05/14/2024] [Indexed: 05/16/2024]
Abstract
Nucleic acids are genetic information-carrying molecules inside cells. Apart from basic nucleotide building blocks, there exist various naturally occurring chemical modifications on nucleobase and ribose moieties, which greatly increase the encoding complexity of nuclei acids, contribute to the alteration of nucleic acid structures, and play versatile regulation roles in gene expression. To study the functions of certain nucleic acids in various biological contexts, robust tools to specifically label and identify these macromolecules and their modifications, and to illuminate their structures are highly necessary. In this review, we summarize recent technique advances of using chemical and enzyme-mediated chemical reactions to study nucleic acids and their modifications and structures. By highlighting the chemical principles of these techniques, we aim to present a perspective on the advancement of the field as well as to offer insights into developing specific chemical reactions and precise enzyme catalysis utilized for nucleic acids and their modifications.
Collapse
Affiliation(s)
- Tengwei Li
- MOE Key Laboratory of Macromolecular Synthesis and Functionalization, Department of Polymer Science and Engineering, Zhejiang University, Yuhangtang Road 866, Hangzhou, 310058, Zhejiang Province, China
| | - Chongguang Cheng
- MOE Key Laboratory of Macromolecular Synthesis and Functionalization, Department of Polymer Science and Engineering, Zhejiang University, Yuhangtang Road 866, Hangzhou, 310058, Zhejiang Province, China
| | - Jianzhao Liu
- MOE Key Laboratory of Macromolecular Synthesis and Functionalization, Department of Polymer Science and Engineering, Zhejiang University, Yuhangtang Road 866, Hangzhou, 310058, Zhejiang Province, China
- Life Sciences Institute, Zhejiang University, Yuhangtang Road 866, Hangzhou, 310058, Zhejiang Province, China
- State Key Laboratory of Transvascular Implantation Devices, Hangzhou, 310009, Zhejiang Province, China
| |
Collapse
|
4
|
Allan MF, Aruda J, Plung JS, Grote SL, Martin des Taillades YJ, de Lajarte AA, Bathe M, Rouskin S. Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591762. [PMID: 38746332 PMCID: PMC11092567 DOI: 10.1101/2024.04.29.591762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.
Collapse
|
5
|
Singh S, Shyamal S, Das A, Panda AC. Global identification of mRNA-interacting circular RNAs by CLiPPR-Seq. Nucleic Acids Res 2024; 52:e29. [PMID: 38324478 PMCID: PMC11014417 DOI: 10.1093/nar/gkae058] [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: 02/01/2023] [Revised: 01/04/2024] [Accepted: 01/18/2024] [Indexed: 02/09/2024] Open
Abstract
Although the functional role of circular RNA (circRNA) interaction with microRNAs and proteins has been studied extensively, circRNA interactions with the protein-coding mRNAs in intact cells remain largely unknown. Here, by employing AMT-mediated proximity ligation of RNA-RNA duplexes followed by circRNA enrichment and deep sequencing, we report a novel Cross-Linking Poly(A) Pulldown RNase R Sequencing (CLiPPR-seq) technology which identified hundreds of mRNA-interacting circRNAs in three different cell types, including βTC6, C2C12 and HeLa cells. Furthermore, CLiPP-seq without RNase R treatment was also performed to identify the mRNA expression in these cells. BLAST analysis of circRNAs in CLiPPR-seq sample with the mRNAs in CLiPP-seq samples determined their potential complementary sequences for circRNA-mRNA interaction. Pulldown of circRNAs and poly(A) RNAs confirmed the direct interaction of circRNAs with target mRNAs. Silencing of mRNA-interacting circRNAs led to the altered expression of target mRNAs in βTC6 cells, suggesting the role of direct interaction of circRNAs with mRNAs in gene expression regulation. CLiPPR-seq thus represents a novel method for illuminating the myriad of uncharacterized circRNA-mRNA hybrids that may regulate gene expression.
Collapse
Affiliation(s)
- Suman Singh
- Institute of Life Sciences, Nalco Square, Bhubaneswar, Odisha 751023, India
- Regional Center for Biotechnology, Faridabad, Haryana 121001, India
| | | | - Arundhati Das
- Institute of Life Sciences, Nalco Square, Bhubaneswar, Odisha 751023, India
| | - Amaresh C Panda
- Institute of Life Sciences, Nalco Square, Bhubaneswar, Odisha 751023, India
| |
Collapse
|
6
|
Price JL, Ziv O, Pinckert ML, Lim A, Miska EA. rnaCrosslinkOO: an object-oriented R package for the analysis of RNA structural data generated by RNA crosslinking experiments. Bioinformatics 2024; 40:btae193. [PMID: 38597883 PMCID: PMC11060868 DOI: 10.1093/bioinformatics/btae193] [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: 11/30/2023] [Revised: 03/06/2024] [Accepted: 04/08/2024] [Indexed: 04/11/2024] Open
Abstract
SUMMARY RNA (ribonucleic acid) molecules have secondary and tertiary structures in vivo which play a crucial role in cellular processes such as the regulation of gene expression, RNA processing and localization. The ability to investigate these structures will enhance our understanding of their function and contribute to the diagnosis and treatment of diseases caused by RNA dysregulation. However, there are no mature pipelines or packages for processing and analyzing complex in vivo RNA structural data. Here, we present rnaCrosslinkOO (RNA Crosslink Object-Oriented), a novel software package for the comprehensive analysis of data derived from the COMRADES (Crosslinking of Matched RNA and Deep Sequencing) method. rnaCrosslinkOO offers a comprehensive pipeline from raw sequencing reads to the identification and comparison of RNA structural features. It includes read processing and alignment, clustering of duplexes, data exploration, folding and comparisons of RNA structures. rnaCrosslinkOO also enables comparisons between conditions, the identification of inter-RNA interactions, and the incorporation of reactivity data to improve structure prediction. AVAILABILITY AND IMPLEMENTATION rnaCrosslinkOO is freely available to noncommercial users and implemented in R, with the source code and documentation accessible at https://CRAN.R-project.org/package=rnaCrosslinkOO. The software is supported on Linux, macOS, and Windows platforms.
Collapse
Affiliation(s)
- Jonathan L Price
- Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, United Kingdom
| | - Omer Ziv
- Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, United Kingdom
- Eleven Therapeutics, Cambridge, CB2 0RE, United Kingdom
| | - Malte L Pinckert
- Department of Pathology, University of Cambridge, Cambridge, CB2 1QP, United Kingdom
| | - Andrew Lim
- Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, United Kingdom
| | - Eric A Miska
- Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, United Kingdom
| |
Collapse
|
7
|
Huo M, Rai SK, Nakatsu K, Deng Y, Jijiwa M. Subverting the Canon: Novel Cancer-Promoting Functions and Mechanisms for snoRNAs. Int J Mol Sci 2024; 25:2923. [PMID: 38474168 PMCID: PMC10932220 DOI: 10.3390/ijms25052923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 02/27/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Small nucleolar RNAs (snoRNAs) constitute a class of intron-derived non-coding RNAs ranging from 60 to 300 nucleotides. Canonically localized in the nucleolus, snoRNAs play a pivotal role in RNA modifications and pre-ribosomal RNA processing. Based on the types of modifications they involve, such as methylation and pseudouridylation, they are classified into two main families-box C/D and H/ACA snoRNAs. Recent investigations have revealed the unconventional synthesis and biogenesis strategies of snoRNAs, indicating their more profound roles in pathogenesis than previously envisioned. This review consolidates recent discoveries surrounding snoRNAs and provides insights into their mechanistic roles in cancer. It explores the intricate interactions of snoRNAs within signaling pathways and speculates on potential therapeutic solutions emerging from snoRNA research. In addition, it presents recent findings on the long non-coding small nucleolar RNA host gene (lncSNHG), a subset of long non-coding RNAs (lncRNAs), which are the transcripts of parental SNHGs that generate snoRNA. The nucleolus, the functional epicenter of snoRNAs, is also discussed. Through a deconstruction of the pathways driving snoRNA-induced oncogenesis, this review aims to serve as a roadmap to guide future research in the nuanced field of snoRNA-cancer interactions and inspire potential snoRNA-related cancer therapies.
Collapse
Affiliation(s)
- Matthew Huo
- Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD 21218, USA;
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, USA; (S.K.R.); (K.N.)
| | - Sudhir Kumar Rai
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, USA; (S.K.R.); (K.N.)
| | - Ken Nakatsu
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, USA; (S.K.R.); (K.N.)
- Emory College of Arts and Sciences, Emory University, Atlanta, GA 30322, USA
| | - Youping Deng
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, USA; (S.K.R.); (K.N.)
| | - Mayumi Jijiwa
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, USA; (S.K.R.); (K.N.)
| |
Collapse
|
8
|
Fukute J, Maki K, Adachi T. The nucleolar shell provides anchoring sites for DNA untwisting. Commun Biol 2024; 7:83. [PMID: 38263258 PMCID: PMC10805735 DOI: 10.1038/s42003-023-05750-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 12/28/2023] [Indexed: 01/25/2024] Open
Abstract
DNA underwinding (untwisting) is a crucial step in transcriptional activation. DNA underwinding occurs between the site where torque is generated by RNA polymerase (RNAP) and the site where the axial rotation of DNA is constrained. However, what constrains DNA axial rotation in the nucleus is yet unknown. Here, we show that the anchorage to the nuclear protein condensates constrains DNA axial rotation for DNA underwinding in the nucleolus. In situ super-resolution imaging of underwound DNA reveal that underwound DNA accumulates in the nucleolus, a nuclear condensate with a core-shell structure. Specifically, underwound DNA is distributed in the nucleolar core owing to RNA polymerase I (RNAPI) activities. Furthermore, underwound DNA in the core decreases when nucleolar shell components are prevented from binding to their recognition structure, G-quadruplex (G4). Taken together, these results suggest that the nucleolar shell provides anchoring sites that constrain DNA axial rotation for RNAPI-driven DNA underwinding in the core. Our findings will contribute to understanding how nuclear protein condensates make up constraints for the site-specific regulation of DNA underwinding and transcription.
Collapse
Affiliation(s)
- Jumpei Fukute
- Laboratory of Cellular and Molecular Biomechanics, Department of Mammalian Regulatory Network, Graduate School of Biostudies, Kyoto University, Sakyo, Kyoto, Japan
- Laboratory of Biomechanics, Institute for Life and Medical Sciences, Kyoto University, Sakyo, Kyoto, Japan
| | - Koichiro Maki
- Laboratory of Cellular and Molecular Biomechanics, Department of Mammalian Regulatory Network, Graduate School of Biostudies, Kyoto University, Sakyo, Kyoto, Japan.
- Laboratory of Biomechanics, Institute for Life and Medical Sciences, Kyoto University, Sakyo, Kyoto, Japan.
- Department of Micro Engineering, Graduate School of Engineering, Kyoto University, Sakyo, Kyoto, Japan.
- Department of Medicine and Medical Science, Graduate School of Medicine, Kyoto University, Sakyo, Kyoto, Japan.
| | - Taiji Adachi
- Laboratory of Cellular and Molecular Biomechanics, Department of Mammalian Regulatory Network, Graduate School of Biostudies, Kyoto University, Sakyo, Kyoto, Japan
- Laboratory of Biomechanics, Institute for Life and Medical Sciences, Kyoto University, Sakyo, Kyoto, Japan
- Department of Micro Engineering, Graduate School of Engineering, Kyoto University, Sakyo, Kyoto, Japan
- Department of Medicine and Medical Science, Graduate School of Medicine, Kyoto University, Sakyo, Kyoto, Japan
| |
Collapse
|
9
|
Wu T, Cheng AY, Zhang Y, Xu J, Wu J, Wen L, Li X, Liu B, Dou X, Wang P, Zhang L, Fei J, Li J, Ouyang Z, He C. KARR-seq reveals cellular higher-order RNA structures and RNA-RNA interactions. Nat Biotechnol 2024:10.1038/s41587-023-02109-8. [PMID: 38238480 PMCID: PMC11255127 DOI: 10.1038/s41587-023-02109-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 12/15/2023] [Indexed: 02/12/2024]
Abstract
RNA fate and function are affected by their structures and interactomes. However, how RNA and RNA-binding proteins (RBPs) assemble into higher-order structures and how RNA molecules may interact with each other to facilitate functions remain largely unknown. Here we present KARR-seq, which uses N3-kethoxal labeling and multifunctional chemical crosslinkers to covalently trap and determine RNA-RNA interactions and higher-order RNA structures inside cells, independent of local protein binding to RNA. KARR-seq depicts higher-order RNA structure and detects widespread intermolecular RNA-RNA interactions with high sensitivity and accuracy. Using KARR-seq, we show that translation represses mRNA compaction under native and stress conditions. We determined the higher-order RNA structures of respiratory syncytial virus (RSV) and vesicular stomatitis virus (VSV) and identified RNA-RNA interactions between the viruses and the host RNAs that potentially regulate viral replication.
Collapse
Affiliation(s)
- Tong Wu
- Department of Chemistry, University of Chicago, Chicago, IL, USA
- Howard Hughes Medical Institute, Chicago, IL, USA
| | - Anthony Youzhi Cheng
- Department of Genetics and Genome Sciences and Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, USA
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Yuexiu Zhang
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH, USA
| | - Jiayu Xu
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH, USA
| | - Jinjun Wu
- Department of Biochemistry and Molecular Biology, Institute for Biophysical Dynamics, University of Chicago, Chicago, IL, USA
| | - Li Wen
- Department of Biochemistry and Molecular Biology, Institute for Biophysical Dynamics, University of Chicago, Chicago, IL, USA
| | - Xiao Li
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH, USA
| | - Bei Liu
- Department of Chemistry, University of Chicago, Chicago, IL, USA
- Howard Hughes Medical Institute, Chicago, IL, USA
| | - Xiaoyang Dou
- Department of Chemistry, University of Chicago, Chicago, IL, USA
- Howard Hughes Medical Institute, Chicago, IL, USA
| | - Pingluan Wang
- Department of Chemistry, University of Chicago, Chicago, IL, USA
- Howard Hughes Medical Institute, Chicago, IL, USA
| | - Linda Zhang
- Department of Chemistry, University of Chicago, Chicago, IL, USA
- Howard Hughes Medical Institute, Chicago, IL, USA
| | - Jingyi Fei
- Department of Biochemistry and Molecular Biology, Institute for Biophysical Dynamics, University of Chicago, Chicago, IL, USA
| | - Jianrong Li
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH, USA
| | - Zhengqing Ouyang
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, USA.
| | - Chuan He
- Department of Chemistry, University of Chicago, Chicago, IL, USA.
- Howard Hughes Medical Institute, Chicago, IL, USA.
- Department of Biochemistry and Molecular Biology, Institute for Biophysical Dynamics, University of Chicago, Chicago, IL, USA.
| |
Collapse
|
10
|
Bose R, Saleem I, Mustoe AM. Causes, functions, and therapeutic possibilities of RNA secondary structure ensembles and alternative states. Cell Chem Biol 2024; 31:17-35. [PMID: 38199037 PMCID: PMC10842484 DOI: 10.1016/j.chembiol.2023.12.010] [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: 09/11/2023] [Revised: 11/21/2023] [Accepted: 12/12/2023] [Indexed: 01/12/2024]
Abstract
RNA secondary structure plays essential roles in encoding RNA regulatory fate and function. Most RNAs populate ensembles of alternatively paired states and are continually unfolded and refolded by cellular processes. Measuring these structural ensembles and their contributions to cellular function has traditionally posed major challenges, but new methods and conceptual frameworks are beginning to fill this void. In this review, we provide a mechanism- and function-centric compendium of the roles of RNA secondary structural ensembles and minority states in regulating the RNA life cycle, from transcription to degradation. We further explore how dysregulation of RNA structural ensembles contributes to human disease and discuss the potential of drugging alternative RNA states to therapeutically modulate RNA activity. The emerging paradigm of RNA structural ensembles as central to RNA function provides a foundation for a deeper understanding of RNA biology and new therapeutic possibilities.
Collapse
Affiliation(s)
- Ritwika Bose
- Therapeutic Innovation Center (THINC), Department of Biochemistry and Molecular Pharmacology, Baylor College of Medicine, Houston, TX, USA
| | - Irfana Saleem
- Therapeutic Innovation Center (THINC), Department of Biochemistry and Molecular Pharmacology, Baylor College of Medicine, Houston, TX, USA
| | - Anthony M Mustoe
- Therapeutic Innovation Center (THINC), Department of Biochemistry and Molecular Pharmacology, Baylor College of Medicine, Houston, TX, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
| |
Collapse
|
11
|
Srivastava M, Dukeshire MR, Mir Q, Omoru OB, Manzourolajdad A, Janga SC. Experimental and computational methods for studying the dynamics of RNA-RNA interactions in SARS-COV2 genomes. Brief Funct Genomics 2024; 23:46-54. [PMID: 36752040 PMCID: PMC10799312 DOI: 10.1093/bfgp/elac050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/24/2022] [Accepted: 11/11/2022] [Indexed: 02/09/2023] Open
Abstract
Long-range ribonucleic acid (RNA)-RNA interactions (RRI) are prevalent in positive-strand RNA viruses, including Beta-coronaviruses, and these take part in regulatory roles, including the regulation of sub-genomic RNA production rates. Crosslinking of interacting RNAs and short read-based deep sequencing of resulting RNA-RNA hybrids have shown that these long-range structures exist in severe acute respiratory syndrome coronavirus (SARS-CoV)-2 on both genomic and sub-genomic levels and in dynamic topologies. Furthermore, co-evolution of coronaviruses with their hosts is navigated by genetic variations made possible by its large genome, high recombination frequency and a high mutation rate. SARS-CoV-2's mutations are known to occur spontaneously during replication, and thousands of aggregate mutations have been reported since the emergence of the virus. Although many long-range RRIs have been experimentally identified using high-throughput methods for the wild-type SARS-CoV-2 strain, evolutionary trajectory of these RRIs across variants, impact of mutations on RRIs and interaction of SARS-CoV-2 RNAs with the host have been largely open questions in the field. In this review, we summarize recent computational tools and experimental methods that have been enabling the mapping of RRIs in viral genomes, with a specific focus on SARS-CoV-2. We also present available informatics resources to navigate the RRI maps and shed light on the impact of mutations on the RRI space in viral genomes. Investigating the evolution of long-range RNA interactions and that of virus-host interactions can contribute to the understanding of new and emerging variants as well as aid in developing improved RNA therapeutics critical for combating future outbreaks.
Collapse
Affiliation(s)
- Mansi Srivastava
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University, 535 West Michigan Street, Indianapolis, Indiana 46202, USA
- Department of Biology, Indiana University, 1001 East 3 St, Bloomington, Indiana 47405, USA
| | - Matthew R Dukeshire
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University, 535 West Michigan Street, Indianapolis, Indiana 46202, USA
| | - Quoseena Mir
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University, 535 West Michigan Street, Indianapolis, Indiana 46202, USA
| | - Okiemute Beatrice Omoru
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University, 535 West Michigan Street, Indianapolis, Indiana 46202, USA
| | - Amirhossein Manzourolajdad
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University, 535 West Michigan Street, Indianapolis, Indiana 46202, USA
- Department of Computer Science, Colgate University, Hamilton, NY, USA
| | - Sarath Chandra Janga
- Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University, 535 West Michigan Street, Indianapolis, Indiana 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Medical Research and Library Building, 975 West Walnut Street, Indianapolis, Indiana 46202, USA
- Centre for Computational Biology and Bioinformatics, Indiana University School of Medicine, 5021 Health Information and Translational Sciences (HITS), 410 West 10th Street, Indianapolis, Indiana 46202, USA
| |
Collapse
|
12
|
Müller T, Mautner S, Videm P, Eggenhofer F, Raden M, Backofen R. CheRRI-Accurate classification of the biological relevance of putative RNA-RNA interaction sites. Gigascience 2024; 13:giae022. [PMID: 38837942 DOI: 10.1093/gigascience/giae022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 03/04/2024] [Accepted: 04/22/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND RNA-RNA interactions are key to a wide range of cellular functions. The detection of potential interactions helps to understand the underlying processes. However, potential interactions identified via in silico or experimental high-throughput methods can lack precision because of a high false-positive rate. RESULTS We present CheRRI, the first tool to evaluate the biological relevance of putative RNA-RNA interaction sites. CheRRI filters candidates via a machine learning-based model trained on experimental RNA-RNA interactome data. Its unique setup combines interactome data and an established thermodynamic prediction tool to integrate experimental data with state-of-the-art computational models. Applying these data to an automated machine learning approach provides the opportunity to not only filter data for potential false positives but also tailor the underlying interaction site model to specific needs. CONCLUSIONS CheRRI is a stand-alone postprocessing tool to filter either predicted or experimentally identified potential RNA-RNA interactions on a genomic level to enhance the quality of interaction candidates. It is easy to install (via conda, pip packages), use (via Galaxy), and integrate into existing RNA-RNA interaction pipelines.
Collapse
Affiliation(s)
- Teresa Müller
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany
| | - Stefan Mautner
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany
| | - Pavankumar Videm
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany
| | - Florian Eggenhofer
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany
| | - Martin Raden
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany
| | - Rolf Backofen
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Koehler-Allee 106, 79110 Freiburg, Germany
- Signalling Research Centre CIBSS, University of Freiburg, Schaenzlestr. 18, 79104 Freiburg, Germany
| |
Collapse
|
13
|
Fafard-Couture É, Labialle S, Scott MS. The regulatory roles of small nucleolar RNAs within their host locus. RNA Biol 2024; 21:1-11. [PMID: 38626213 PMCID: PMC11028025 DOI: 10.1080/15476286.2024.2342685] [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: 04/08/2024] [Indexed: 04/18/2024] Open
Abstract
Small nucleolar RNAs (snoRNAs) are a class of conserved noncoding RNAs forming complexes with proteins to catalyse site-specific modifications on ribosomal RNA. Besides this canonical role, several snoRNAs are now known to regulate diverse levels of gene expression. While these functions are carried out in trans by mature snoRNAs, evidence has also been emerging of regulatory roles of snoRNAs in cis, either within their genomic locus or as longer transcription intermediates during their maturation. Herein, we review recent findings that snoRNAs can interact in cis with their intron to regulate the expression of their host gene. We also explore the ever-growing diversity of longer host-derived snoRNA extensions and their functional impact across the transcriptome. Finally, we discuss the role of snoRNA duplications into forging these new layers of snoRNA-mediated regulation, as well as their involvement in the genomic imprinting of their host locus.
Collapse
Affiliation(s)
- Étienne Fafard-Couture
- Département de biochimie et de génomique fonctionnelle, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | | | - Michelle S Scott
- Département de biochimie et de génomique fonctionnelle, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, Québec, Canada
| |
Collapse
|
14
|
Liao KC, Xie X, Sundstrom AKB, Lim XN, Tan KK, Zhang Y, Zou J, Bifani AM, Poh HX, Chen JJ, Ng WC, Lim SY, Ooi EE, Sessions OM, Tay Y, Shi PY, Huber RG, Wan Y. Dengue and Zika RNA-RNA interactomes reveal pro- and anti-viral RNA in human cells. Genome Biol 2023; 24:279. [PMID: 38053173 PMCID: PMC10696742 DOI: 10.1186/s13059-023-03110-9] [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: 04/18/2023] [Accepted: 11/15/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND Identifying host factors is key to understanding RNA virus pathogenicity. Besides proteins, RNAs can interact with virus genomes to impact replication. RESULTS Here, we use proximity ligation sequencing to identify virus-host RNA interactions for four strains of Zika virus (ZIKV) and one strain of dengue virus (DENV-1) in human cells. We find hundreds of coding and non-coding RNAs that bind to DENV and ZIKV viruses. Host RNAs tend to bind to single-stranded regions along the virus genomes according to hybridization energetics. Compared to SARS-CoV-2 interactors, ZIKV-interacting host RNAs tend to be downregulated upon virus infection. Knockdown of several short non-coding RNAs, including miR19a-3p, and 7SK RNA results in a decrease in viral replication, suggesting that they act as virus-permissive factors. In addition, the 3'UTR of DYNLT1 mRNA acts as a virus-restrictive factor by binding to the conserved dumbbell region on DENV and ZIKV 3'UTR to decrease virus replication. We also identify a conserved set of host RNAs that interacts with DENV, ZIKV, and SARS-CoV-2, suggesting that these RNAs are broadly important for RNA virus infection. CONCLUSIONS This study demonstrates that host RNAs can impact virus replication in permissive and restrictive ways, expanding our understanding of host factors and RNA-based gene regulation during viral pathogenesis.
Collapse
Affiliation(s)
- Kuo-Chieh Liao
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, 138672, Singapore
| | - Xuping Xie
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX, 77555, USA
| | - Anna Karin Beatrice Sundstrom
- Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, 8 College Road, Singapore, 169857, Singapore
| | - Xin Ni Lim
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, 138672, Singapore
| | - Kiat Kee Tan
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, 138672, Singapore
| | - Yu Zhang
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, 138672, Singapore
| | - Jing Zou
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX, 77555, USA
| | - Amanda Makha Bifani
- Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, 8 College Road, Singapore, 169857, Singapore
| | - Hui Xian Poh
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, 138672, Singapore
| | - Jia Jia Chen
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, 117599, Singapore
| | - Wy Ching Ng
- Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, 8 College Road, Singapore, 169857, Singapore
| | - Su Ying Lim
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, 138672, Singapore
| | - Eng Eong Ooi
- Program in Emerging Infectious Diseases, Duke-NUS Graduate Medical School, 8 College Road, Singapore, 169857, Singapore
| | - October M Sessions
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore
- Department of Pharmacy, National University of Singapore, Singapore, 117559, Singapore
| | - Yvonne Tay
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, 117599, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore
| | - Pei-Yong Shi
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX, 77555, USA.
| | - Roland G Huber
- Biomolecular Function Discovery, Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Matrix #07-01, Singapore, 138671, Singapore.
| | - Yue Wan
- Stem Cell and Regenerative Biology, Genome Institute of Singapore, Singapore, 138672, Singapore.
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore.
| |
Collapse
|
15
|
Margasyuk S, Zavileyskiy L, Cao C, Pervouchine D. Long-range RNA structures in the human transcriptome beyond evolutionarily conserved regions. PeerJ 2023; 11:e16414. [PMID: 38047033 PMCID: PMC10691357 DOI: 10.7717/peerj.16414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 10/17/2023] [Indexed: 12/05/2023] Open
Abstract
RNA structure has been increasingly recognized as a critical player in the biogenesis and turnover of many transcripts classes. In eukaryotes, the prediction of RNA structure by thermodynamic modeling meets fundamental limitations due to the large sizes and complex, discontinuous organization of eukaryotic genes. Signatures of functional RNA structures can be found by detecting compensatory substitutions in homologous sequences, but a comparative approach is applicable only within conserved sequence blocks. Here, we developed a computational pipeline called PHRIC, which is not limited to conserved regions and relies on RNA contacts derived from RNA in situ conformation sequencing (RIC-seq) experiments. It extracts pairs of short RNA fragments surrounded by nested clusters of RNA contacts and predicts long, nearly perfect complementary base pairings formed between these fragments. In application to a panel of RIC-seq experiments in seven human cell lines, PHRIC predicted ~12,000 stable long-range RNA structures with equilibrium free energy below -15 kcal/mol, the vast majority of which fall outside of regions annotated as conserved among vertebrates. These structures, nevertheless, show some level of sequence conservation and remarkable compensatory substitution patterns in other clades. Furthermore, we found that introns have a higher propensity to form stable long-range RNA structures between each other, and moreover that RNA structures tend to concentrate within the same intron rather than connect adjacent introns. These results for the first time extend the application of proximity ligation assays to RNA structure prediction beyond conserved regions.
Collapse
Affiliation(s)
- Sergey Margasyuk
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Lev Zavileyskiy
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Changchang Cao
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Dmitri Pervouchine
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow, Russia
| |
Collapse
|
16
|
Tieng FYF, Abdullah-Zawawi MR, Md Shahri NAA, Mohamed-Hussein ZA, Lee LH, Mutalib NSA. A Hitchhiker's guide to RNA-RNA structure and interaction prediction tools. Brief Bioinform 2023; 25:bbad421. [PMID: 38040490 PMCID: PMC10753535 DOI: 10.1093/bib/bbad421] [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: 07/31/2023] [Revised: 10/16/2023] [Accepted: 10/26/2023] [Indexed: 12/03/2023] Open
Abstract
RNA biology has risen to prominence after a remarkable discovery of diverse functions of noncoding RNA (ncRNA). Most untranslated transcripts often exert their regulatory functions into RNA-RNA complexes via base pairing with complementary sequences in other RNAs. An interplay between RNAs is essential, as it possesses various functional roles in human cells, including genetic translation, RNA splicing, editing, ribosomal RNA maturation, RNA degradation and the regulation of metabolic pathways/riboswitches. Moreover, the pervasive transcription of the human genome allows for the discovery of novel genomic functions via RNA interactome investigation. The advancement of experimental procedures has resulted in an explosion of documented data, necessitating the development of efficient and precise computational tools and algorithms. This review provides an extensive update on RNA-RNA interaction (RRI) analysis via thermodynamic- and comparative-based RNA secondary structure prediction (RSP) and RNA-RNA interaction prediction (RIP) tools and their general functions. We also highlighted the current knowledge of RRIs and the limitations of RNA interactome mapping via experimental data. Then, the gap between RSP and RIP, the importance of RNA homologues, the relationship between pseudoknots, and RNA folding thermodynamics are discussed. It is hoped that these emerging prediction tools will deepen the understanding of RNA-associated interactions in human diseases and hasten treatment processes.
Collapse
Affiliation(s)
- Francis Yew Fu Tieng
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 56000, Malaysia
| | | | - Nur Alyaa Afifah Md Shahri
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 56000, Malaysia
| | - Zeti-Azura Mohamed-Hussein
- Institute of Systems Biology (INBIOSIS), UKM, Selangor 43600, Malaysia
- Department of Applied Physics, Faculty of Science and Technology, UKM, Selangor 43600, Malaysia
| | - Learn-Han Lee
- Sunway Microbiomics Centre, School of Medical and Life Sciences, Sunway University, Sunway City 47500, Malaysia
- Novel Bacteria and Drug Discovery Research Group, Microbiome and Bioresource Research Strength, Jeffrey Cheah School of Medicine and Health Sciences, Monash University of Malaysia, Selangor 47500, Malaysia
| | - Nurul-Syakima Ab Mutalib
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 56000, Malaysia
- Novel Bacteria and Drug Discovery Research Group, Microbiome and Bioresource Research Strength, Jeffrey Cheah School of Medicine and Health Sciences, Monash University of Malaysia, Selangor 47500, Malaysia
- Faculty of Health Sciences, UKM, Kuala Lumpur 50300, Malaysia
| |
Collapse
|
17
|
Kuhle B, Chen Q, Schimmel P. tRNA renovatio: Rebirth through fragmentation. Mol Cell 2023; 83:3953-3971. [PMID: 37802077 PMCID: PMC10841463 DOI: 10.1016/j.molcel.2023.09.016] [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: 05/23/2023] [Revised: 08/15/2023] [Accepted: 09/12/2023] [Indexed: 10/08/2023]
Abstract
tRNA function is based on unique structures that enable mRNA decoding using anticodon trinucleotides. These structures interact with specific aminoacyl-tRNA synthetases and ribosomes using 3D shape and sequence signatures. Beyond translation, tRNAs serve as versatile signaling molecules interacting with other RNAs and proteins. Through evolutionary processes, tRNA fragmentation emerges as not merely random degradation but an act of recreation, generating specific shorter molecules called tRNA-derived small RNAs (tsRNAs). These tsRNAs exploit their linear sequences and newly arranged 3D structures for unexpected biological functions, epitomizing the tRNA "renovatio" (from Latin, meaning renewal, renovation, and rebirth). Emerging methods to uncover full tRNA/tsRNA sequences and modifications, combined with techniques to study RNA structures and to integrate AI-powered predictions, will enable comprehensive investigations of tRNA fragmentation products and new interaction potentials in relation to their biological functions. We anticipate that these directions will herald a new era for understanding biological complexity and advancing pharmaceutical engineering.
Collapse
Affiliation(s)
- Bernhard Kuhle
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA; Department of Cellular Biochemistry, University Medical Center Göttingen, Göttingen, Germany
| | - Qi Chen
- Molecular Medicine Program, Department of Human Genetics, and Division of Urology, Department of Surgery, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Paul Schimmel
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA.
| |
Collapse
|
18
|
Tao S, Hou Y, Diao L, Hu Y, Xu W, Xie S, Xiao Z. Long noncoding RNA study: Genome-wide approaches. Genes Dis 2023; 10:2491-2510. [PMID: 37554208 PMCID: PMC10404890 DOI: 10.1016/j.gendis.2022.10.024] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 10/09/2022] [Accepted: 10/23/2022] [Indexed: 11/30/2022] Open
Abstract
Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in various biological processes across several species. Though many efforts have been devoted to the expansion of the lncRNAs landscape, much about lncRNAs is still unknown due to their great complexity. The development of high-throughput technologies and the constantly improved bioinformatic methods have resulted in a rapid expansion of lncRNA research and relevant databases. In this review, we introduced genome-wide research of lncRNAs in three parts: (i) novel lncRNA identification by high-throughput sequencing and computational pipelines; (ii) functional characterization of lncRNAs by expression atlas profiling, genome-scale screening, and the research of cancer-related lncRNAs; (iii) mechanism research by large-scale experimental technologies and computational analysis. Besides, primary experimental methods and bioinformatic pipelines related to these three parts are summarized. This review aimed to provide a comprehensive and systemic overview of lncRNA genome-wide research strategies and indicate a genome-wide lncRNA research system.
Collapse
Affiliation(s)
- Shuang Tao
- The Biotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China
| | - Yarui Hou
- The Biotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China
| | - Liting Diao
- The Biotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China
| | - Yanxia Hu
- The Biotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China
| | - Wanyi Xu
- The Biotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China
| | - Shujuan Xie
- The Biotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China
- Institute of Vaccine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China
| | - Zhendong Xiao
- The Biotherapy Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong 510630, China
| |
Collapse
|
19
|
Ripin N, Parker R. Formation, function, and pathology of RNP granules. Cell 2023; 186:4737-4756. [PMID: 37890457 PMCID: PMC10617657 DOI: 10.1016/j.cell.2023.09.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 07/28/2023] [Accepted: 09/07/2023] [Indexed: 10/29/2023]
Abstract
Ribonucleoprotein (RNP) granules are diverse membrane-less organelles that form through multivalent RNA-RNA, RNA-protein, and protein-protein interactions between RNPs. RNP granules are implicated in many aspects of RNA physiology, but in most cases their functions are poorly understood. RNP granules can be described through four key principles. First, RNP granules often arise because of the large size, high localized concentrations, and multivalent interactions of RNPs. Second, cells regulate RNP granule formation by multiple mechanisms including posttranslational modifications, protein chaperones, and RNA chaperones. Third, RNP granules impact cell physiology in multiple manners. Finally, dysregulation of RNP granules contributes to human diseases. Outstanding issues in the field remain, including determining the scale and molecular mechanisms of RNP granule function and how granule dysfunction contributes to human disease.
Collapse
Affiliation(s)
- Nina Ripin
- Department of Biochemistry and Howard Hughes Medical Institute, University of Colorado Boulder, Boulder, CO 80303, USA
| | - Roy Parker
- Department of Biochemistry and Howard Hughes Medical Institute, University of Colorado Boulder, Boulder, CO 80303, USA.
| |
Collapse
|
20
|
Hufsky F, Abecasis AB, Babaian A, Beck S, Brierley L, Dellicour S, Eggeling C, Elena SF, Gieraths U, Ha AD, Harvey W, Jones TC, Lamkiewicz K, Lovate GL, Lücking D, Machyna M, Nishimura L, Nocke MK, Renard BY, Sakaguchi S, Sakellaridi L, Spangenberg J, Tarradas-Alemany M, Triebel S, Vakulenko Y, Wijesekara RY, González-Candelas F, Krautwurst S, Pérez-Cataluña A, Randazzo W, Sánchez G, Marz M. The International Virus Bioinformatics Meeting 2023. Viruses 2023; 15:2031. [PMID: 37896809 PMCID: PMC10612056 DOI: 10.3390/v15102031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 09/08/2023] [Accepted: 09/14/2023] [Indexed: 10/29/2023] Open
Abstract
The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24-26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting.
Collapse
Affiliation(s)
- Franziska Hufsky
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Ana B. Abecasis
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Global Health and Tropical Medicine, GHTM, Associate Laboratory in Translation and Innovation towards Global Health, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, 1349-008 Lisboa, Portugal
| | - Artem Babaian
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada
- Donnelly Centre, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Sebastian Beck
- Leibniz Institute of Virology, Department Viral Zoonoses—One Health, 20251 Hamburg, Germany;
| | - Liam Brierley
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Department of Health Data Science, University of Liverpool, Liverpool L69 3GF, UK
| | - Simon Dellicour
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12, 50 av. FD Roosevelt, 1050 Bruxelles, Belgium
- Laboratory for Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, University of Leuven, 3000 Leuven, Belgium
| | - Christian Eggeling
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Institute of Applied Optics and Biophysics, Friedrich Schiller University Jena, Max-Wien-Platz 1, 07743 Jena, Germany
| | - Santiago F. Elena
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Institute for Integrative Systems Biology (I2SysBio), CSIC-Universitat de Valencia, Catedratico Agustin Escardino 9, 46980 Valencia, Spain
| | - Udo Gieraths
- Institute of Virology, Charité, Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Anh D. Ha
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, USA
| | - Will Harvey
- The Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Terry C. Jones
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Institute of Virology, Charité, Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
- Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Kevin Lamkiewicz
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Gabriel L. Lovate
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Dominik Lücking
- Max-Planck Institute for Marine Microbiology, Celsiusstraße 1, 28359 Bremen, Germany
| | - Martin Machyna
- Paul-Ehrlich-Institut, Host-Pathogen-Interactions, 63225 Langen, Germany
| | - Luca Nishimura
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Department of Genetics, School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Mishima 411-8540, Japan
- Human Genetics Laboratory, National Institute of Genetics, Mishima 411-8540, Japan
| | - Maximilian K. Nocke
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Department for Molecular & Medical Virology, Ruhr University Bochum, 44801 Bochum, Germany
| | - Bernard Y. Renard
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Digital Engineering Faculty, Hasso Plattner Institute, University of Potsdam, 14482 Potsdam, Germany
| | - Shoichi Sakaguchi
- Department of Microbiology and Infection Control, Faculty of Medicine, Osaka Medical and Pharmaceutical University, Osaka 569-8686, Japan;
| | - Lygeri Sakellaridi
- Institute for Virology and Immunobiology, University of Würzburg, Versbacher Str. 7, 97078 Würzburg, Germany
| | - Jannes Spangenberg
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Maria Tarradas-Alemany
- Computational Genomics Lab., Department of Genetics, Microbiology and Statistics, Institut de Biomedicina UB (IBUB), Universitat de Barcelona (UB), 08028 Barcelona, Spain
| | - Sandra Triebel
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Yulia Vakulenko
- Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | - Rajitha Yasas Wijesekara
- Institute for Bioinformatics, University of Medicine Greifswald, Felix-Hausdorff-Str. 8, 17475 Greifswald, Germany
| | - Fernando González-Candelas
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Institute for Integrative Systems Biology (I2SysBio), CSIC-Universitat de Valencia, Catedratico Agustin Escardino 9, 46980 Valencia, Spain
- Joint Research Unit “Infection and Public Health” FISABIO, University of Valencia, 46010 Valencia, Spain
| | - Sarah Krautwurst
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Alba Pérez-Cataluña
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, 46980 Valencia, Spain
| | - Walter Randazzo
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, 46980 Valencia, Spain
| | - Gloria Sánchez
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, 46980 Valencia, Spain
| | - Manja Marz
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
- German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
- Michael Stifel Center Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07745 Jena, Germany
- Leibniz Institute for Age Research—Fritz Lippman Institute, 07745 Jena, Germany
| |
Collapse
|
21
|
Margasyuk S, Kalinina M, Petrova M, Skvortsov D, Cao C, Pervouchine DD. RNA in situ conformation sequencing reveals novel long-range RNA structures with impact on splicing. RNA (NEW YORK, N.Y.) 2023; 29:1423-1436. [PMID: 37295923 PMCID: PMC10573301 DOI: 10.1261/rna.079508.122] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 05/22/2023] [Indexed: 06/12/2023]
Abstract
Over recent years, long-range RNA structure has emerged as a factor that is fundamental to alternative splicing regulation. An increasing number of human disorders are now being associated with splicing defects; hence it is essential to develop methods that assess long-range RNA structure experimentally. RNA in situ conformation sequencing (RIC-seq) is a method that recapitulates RNA structure within physiological RNA-protein complexes. In this work, we juxtapose pairs of conserved complementary regions (PCCRs) that were predicted in silico with the results of RIC-seq experiments conducted in seven human cell lines. We show statistically that RIC-seq support of PCCRs correlates with their properties, such as equilibrium free energy, presence of compensatory substitutions, and occurrence of A-to-I RNA editing sites and forked eCLIP peaks. Exons enclosed in PCCRs that are supported by RIC-seq tend to have weaker splice sites and lower inclusion rates, which is indicative of post-transcriptional splicing regulation mediated by RNA structure. Based on these findings, we prioritize PCCRs according to their RIC-seq support and show, using antisense nucleotides and minigene mutagenesis, that PCCRs in two disease-associated human genes, PHF20L1 and CASK, and also PCCRs in their murine orthologs, impact alternative splicing. In sum, we demonstrate how RIC-seq experiments can be used to discover functional long-range RNA structures, and particularly those that regulate alternative splicing.
Collapse
Affiliation(s)
- Sergey Margasyuk
- Skolkovo Institute of Science and Technology, Moscow 143026, Russia
| | - Marina Kalinina
- Skolkovo Institute of Science and Technology, Moscow 143026, Russia
| | - Marina Petrova
- Skolkovo Institute of Science and Technology, Moscow 143026, Russia
| | - Dmitry Skvortsov
- Skolkovo Institute of Science and Technology, Moscow 143026, Russia
- Moscow State University, Faculty of Chemistry, Moscow 119991, Russia
| | - Changchang Cao
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | | |
Collapse
|
22
|
Gabryelska MM, Conn SJ. The RNA interactome in the Hallmarks of Cancer. WILEY INTERDISCIPLINARY REVIEWS. RNA 2023; 14:e1786. [PMID: 37042179 PMCID: PMC10909452 DOI: 10.1002/wrna.1786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 03/12/2023] [Accepted: 03/20/2023] [Indexed: 04/13/2023]
Abstract
Ribonucleic acid (RNA) molecules are indispensable for cellular homeostasis in healthy and malignant cells. However, the functions of RNA extend well beyond that of a protein-coding template. Rather, both coding and non-coding RNA molecules function through critical interactions with a plethora of cellular molecules, including other RNAs, DNA, and proteins. Deconvoluting this RNA interactome, including the interacting partners, the nature of the interaction, and dynamic changes of these interactions in malignancies has yielded fundamental advances in knowledge and are emerging as a novel therapeutic strategy in cancer. Here, we present an RNA-centric review of recent advances in the field of RNA-RNA, RNA-protein, and RNA-DNA interactomic network analysis and their impact across the Hallmarks of Cancer. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.
Collapse
Affiliation(s)
- Marta M Gabryelska
- Flinders Health and Medical Research Institute (FHMRI), College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
| | - Simon J Conn
- Flinders Health and Medical Research Institute (FHMRI), College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
| |
Collapse
|
23
|
Deng J, Fang X, Huang L, Li S, Xu L, Ye K, Zhang J, Zhang K, Zhang QC. RNA structure determination: From 2D to 3D. FUNDAMENTAL RESEARCH 2023; 3:727-737. [PMID: 38933295 PMCID: PMC11197651 DOI: 10.1016/j.fmre.2023.06.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 06/04/2023] [Accepted: 06/05/2023] [Indexed: 06/28/2024] Open
Abstract
RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.
Collapse
Affiliation(s)
- Jie Deng
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Xianyang Fang
- Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Key Laboratory of RNA Biology, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Lin Huang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Shanshan Li
- MOE Key Laboratory for Cellular Dynamics and Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China
| | - Lilei Xu
- Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Keqiong Ye
- Key Laboratory of RNA Biology, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinsong Zhang
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
| | - Kaiming Zhang
- MOE Key Laboratory for Cellular Dynamics and Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230027, China
| | - Qiangfeng Cliff Zhang
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
| |
Collapse
|
24
|
Barbagallo C, Stella M, Ferrara C, Caponnetto A, Battaglia R, Barbagallo D, Di Pietro C, Ragusa M. RNA-RNA competitive interactions: a molecular civil war ruling cell physiology and diseases. EXPLORATION OF MEDICINE 2023:504-540. [DOI: 10.37349/emed.2023.00159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/02/2023] [Indexed: 09/02/2023] Open
Abstract
The idea that proteins are the main determining factors in the functioning of cells and organisms, and their dysfunctions are the first cause of pathologies, has been predominant in biology and biomedicine until recently. This protein-centered view was too simplistic and failed to explain the physiological and pathological complexity of the cell. About 80% of the human genome is dynamically and pervasively transcribed, mostly as non-protein-coding RNAs (ncRNAs), which competitively interact with each other and with coding RNAs generating a complex RNA network regulating RNA processing, stability, and translation and, accordingly, fine-tuning the gene expression of the cells. Qualitative and quantitative dysregulations of RNA-RNA interaction networks are strongly involved in the onset and progression of many pathologies, including cancers and degenerative diseases. This review will summarize the RNA species involved in the competitive endogenous RNA network, their mechanisms of action, and involvement in pathological phenotypes. Moreover, it will give an overview of the most advanced experimental and computational methods to dissect and rebuild RNA networks.
Collapse
Affiliation(s)
- Cristina Barbagallo
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy
| | - Michele Stella
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy
| | | | - Angela Caponnetto
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy
| | - Rosalia Battaglia
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy
| | - Davide Barbagallo
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy
| | - Cinzia Di Pietro
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy
| | - Marco Ragusa
- Section of Biology and Genetics, Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy
| |
Collapse
|
25
|
Shi B, An K, Wang Y, Fei Y, Guo C, Cliff Zhang Q, Yang YG, Tian X, Kan Q. RNA Structural Dynamics Modulate EGFR-TKI Resistance Through Controlling YRDC Translation in NSCLC Cells. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:850-865. [PMID: 36435452 PMCID: PMC10787121 DOI: 10.1016/j.gpb.2022.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 10/25/2022] [Accepted: 10/31/2022] [Indexed: 11/27/2022]
Abstract
Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) positively affect the initial control of non-small cell lung cancer (NSCLC). Rapidly acquired resistance to EGFR-TKIs is a major hurdle in successful treatment. However, the mechanisms that control the resistance of EGFR-TKIs remain largely unknown. RNA structures have widespread and crucial functions in many biological regulations; however, the functions of RNA structures in regulating cancer drug resistance remain unclear. Here, the psoralen analysis of RNA interactions and structures (PARIS) method is used to establish the higher-order RNA structure maps of EGFR-TKIs-resistant and -sensitive cells of NSCLC. Our results show that RNA structural regions are enriched in untranslated regions (UTRs) and correlate with translation efficiency (TE). Moreover, yrdC N6-threonylcarbamoyltransferase domain containing (YRDC) promotes resistance to EGFR-TKIs. RNA structure formation in YRDC 3' UTR suppresses embryonic lethal abnormal vision-like 1 (ELAVL1) binding, leading to EGFR-TKI sensitivity by impairing YRDC translation. A potential therapeutic strategy for cancer treatment is provided using antisense oligonucleotide (ASO) to perturb the interaction between RNA and protein. Our study reveals an unprecedented mechanism through which the RNA structure switch modulates EGFR-TKI resistance by controlling YRDC mRNA translation in an ELAVL1-dependent manner.
Collapse
Affiliation(s)
- Boyang Shi
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou 450052, China; Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Ke An
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou 450052, China; Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Yueqin Wang
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou 450052, China
| | - Yuhan Fei
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Caixia Guo
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Qiangfeng Cliff Zhang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yun-Gui Yang
- Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.
| | - Xin Tian
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou 450052, China.
| | - Quancheng Kan
- Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou 450052, China.
| |
Collapse
|
26
|
Wu KE, Zou JY, Chang H. Machine learning modeling of RNA structures: methods, challenges and future perspectives. Brief Bioinform 2023; 24:bbad210. [PMID: 37280185 DOI: 10.1093/bib/bbad210] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/12/2023] [Accepted: 05/17/2023] [Indexed: 06/08/2023] Open
Abstract
The three-dimensional structure of RNA molecules plays a critical role in a wide range of cellular processes encompassing functions from riboswitches to epigenetic regulation. These RNA structures are incredibly dynamic and can indeed be described aptly as an ensemble of structures that shifts in distribution depending on different cellular conditions. Thus, the computational prediction of RNA structure poses a unique challenge, even as computational protein folding has seen great advances. In this review, we focus on a variety of machine learning-based methods that have been developed to predict RNA molecules' secondary structure, as well as more complex tertiary structures. We survey commonly used modeling strategies, and how many are inspired by or incorporate thermodynamic principles. We discuss the shortcomings that various design decisions entail and propose future directions that could build off these methods to yield more robust, accurate RNA structure predictions.
Collapse
Affiliation(s)
- Kevin E Wu
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA 94305, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - James Y Zou
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Howard Chang
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA
| |
Collapse
|
27
|
Jakob C, Lovate GL, Desirò D, Gießler L, Smyth R, Marquet R, Lamkiewicz K, Marz M, Schwemmle M, Bolte H. Sequential disruption of SPLASH-identified vRNA-vRNA interactions challenges their role in influenza A virus genome packaging. Nucleic Acids Res 2023; 51:6479-6494. [PMID: 37224537 PMCID: PMC10325904 DOI: 10.1093/nar/gkad442] [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: 03/13/2023] [Revised: 05/02/2023] [Accepted: 05/10/2023] [Indexed: 05/26/2023] Open
Abstract
A fundamental step in the influenza A virus (IAV) replication cycle is the coordinated packaging of eight distinct genomic RNA segments (i.e. vRNAs) into a viral particle. Although this process is thought to be controlled by specific vRNA-vRNA interactions between the genome segments, few functional interactions have been validated. Recently, a large number of potentially functional vRNA-vRNA interactions have been detected in purified virions using the RNA interactome capture method SPLASH. However, their functional significance in coordinated genome packaging remains largely unclear. Here, we show by systematic mutational analysis that mutant A/SC35M (H7N7) viruses lacking several prominent SPLASH-identified vRNA-vRNA interactions involving the HA segment package the eight genome segments as efficiently as the wild-type virus. We therefore propose that the vRNA-vRNA interactions identified by SPLASH in IAV particles are not necessarily critical for the genome packaging process, leaving the underlying molecular mechanism elusive.
Collapse
Affiliation(s)
- Celia Jakob
- Institute of Virology, Medical Center – University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Gabriel L Lovate
- RNA Bioinformatics and High-Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Germany
| | - Daniel Desirò
- Department of Biochemistry, University of Cambridge, CambridgeCB2 1QW, UK
| | - Lara Gießler
- Institute of Virology, Medical Center – University of Freiburg, Freiburg, Germany
| | - Redmond P Smyth
- Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, Würzburg, Germany
- Julius-Maximilians-Universität Würzburg, Faculty of Medicine, Würzburg, Germany
| | - Roland Marquet
- Architecture et Réactivité de l’ARN, Université de Strasbourg, CNRS, IBMC, Strasbourg, France
| | - Kevin Lamkiewicz
- RNA Bioinformatics and High-Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Germany
- German Center for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany
- European Virus Bioinformatics Center (EVBC), Jena, Germany
| | - Manja Marz
- RNA Bioinformatics and High-Throughput Analysis, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Germany
- German Center for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany
- European Virus Bioinformatics Center (EVBC), Jena, Germany
- FLI Leibniz Institute for Age Research, Jena, Germany
| | - Martin Schwemmle
- Institute of Virology, Medical Center – University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Hardin Bolte
- Institute of Virology, Medical Center – University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| |
Collapse
|
28
|
Bergeron D, Faucher-Giguère L, Emmerichs AK, Choquet K, Song KS, Deschamps-Francoeur G, Fafard-Couture É, Rivera A, Couture S, Churchman LS, Heyd F, Abou Elela S, Scott MS. Intronic small nucleolar RNAs regulate host gene splicing through base pairing with their adjacent intronic sequences. Genome Biol 2023; 24:160. [PMID: 37415181 PMCID: PMC10324135 DOI: 10.1186/s13059-023-03002-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 06/29/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND Small nucleolar RNAs (snoRNAs) are abundant noncoding RNAs best known for their involvement in ribosomal RNA maturation. In mammals, most expressed snoRNAs are embedded in introns of longer genes and produced through transcription and splicing of their host. Intronic snoRNAs were long viewed as inert passengers with little effect on host expression. However, a recent study reported a snoRNA influencing the splicing and ultimate output of its host gene. Overall, the general contribution of intronic snoRNAs to host expression remains unclear. RESULTS Computational analysis of large-scale human RNA-RNA interaction datasets indicates that 30% of detected snoRNAs interact with their host transcripts. Many snoRNA-host duplexes are located near alternatively spliced exons and display high sequence conservation suggesting a possible role in splicing regulation. The study of the model SNORD2-EIF4A2 duplex indicates that the snoRNA interaction with the host intronic sequence conceals the branch point leading to decreased inclusion of the adjacent alternative exon. Extended SNORD2 sequence containing the interacting intronic region accumulates in sequencing datasets in a cell-type-specific manner. Antisense oligonucleotides and mutations that disrupt the formation of the snoRNA-intron structure promote the splicing of the alternative exon, shifting the EIF4A2 transcript ratio away from nonsense-mediated decay. CONCLUSIONS Many snoRNAs form RNA duplexes near alternative exons of their host transcripts, placing them in optimal positions to control host output as shown for the SNORD2-EIF4A2 model system. Overall, our study supports a more widespread role for intronic snoRNAs in the regulation of their host transcript maturation.
Collapse
Affiliation(s)
- Danny Bergeron
- Département de Biochimie Et Génomique Fonctionnelle, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada
| | - Laurence Faucher-Giguère
- Département de Microbiologie Et d'infectiologie, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada
| | - Ann-Kathrin Emmerichs
- Institute of Chemistry and Biochemistry, Freie Universität Berlin, Laboratory of RNA Biochemistry, Takustrasse 6, 14195, Berlin, Germany
| | - Karine Choquet
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - Kristina Sungeun Song
- Département de Biochimie Et Génomique Fonctionnelle, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada
| | - Gabrielle Deschamps-Francoeur
- Département de Biochimie Et Génomique Fonctionnelle, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada
| | - Étienne Fafard-Couture
- Département de Biochimie Et Génomique Fonctionnelle, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada
| | - Andrea Rivera
- Département de Microbiologie Et d'infectiologie, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada
| | - Sonia Couture
- Département de Microbiologie Et d'infectiologie, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada
| | - L Stirling Churchman
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - Florian Heyd
- Institute of Chemistry and Biochemistry, Freie Universität Berlin, Laboratory of RNA Biochemistry, Takustrasse 6, 14195, Berlin, Germany
| | - Sherif Abou Elela
- Département de Microbiologie Et d'infectiologie, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada
| | - Michelle S Scott
- Département de Biochimie Et Génomique Fonctionnelle, Faculté de Médecine Et Des Sciences de La Santé, Université de Sherbrooke, Sherbrooke, Québec, J1E 4K8, Canada.
| |
Collapse
|
29
|
Patel S, Sexton AN, Strine MS, Wilen CB, Simon MD, Pyle AM. Systematic detection of tertiary structural modules in large RNAs and RNP interfaces by Tb-seq. Nat Commun 2023; 14:3426. [PMID: 37296103 PMCID: PMC10255950 DOI: 10.1038/s41467-023-38623-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 05/09/2023] [Indexed: 06/12/2023] Open
Abstract
Compact RNA structural motifs control many aspects of gene expression, but we lack methods for finding these structures in the vast expanse of multi-kilobase RNAs. To adopt specific 3-D shapes, many RNA modules must compress their RNA backbones together, bringing negatively charged phosphates into close proximity. This is often accomplished by recruiting multivalent cations (usually Mg2+), which stabilize these sites and neutralize regions of local negative charge. Coordinated lanthanide ions, such as terbium (III) (Tb3+), can also be recruited to these sites, where they induce efficient RNA cleavage, thereby revealing compact RNA 3-D modules. Until now, Tb3+ cleavage sites were monitored via low-throughput biochemical methods only applicable to small RNAs. Here we present Tb-seq, a high-throughput sequencing method for detecting compact tertiary structures in large RNAs. Tb-seq detects sharp backbone turns found in RNA tertiary structures and RNP interfaces, providing a way to scan transcriptomes for stable structural modules and potential riboregulatory motifs.
Collapse
Affiliation(s)
- Shivali Patel
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Alec N Sexton
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Madison S Strine
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Craig B Wilen
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Matthew D Simon
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
- Chemical Biology Institute, Yale University, West Haven, CT, USA
| | - Anna Marie Pyle
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
- Department of Chemistry, Yale University, New Haven, CT, USA.
- Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT, USA.
| |
Collapse
|
30
|
Chakrabarti AM, Iosub IA, Lee FCY, Ule J, Luscombe NM. A computationally-enhanced hiCLIP atlas reveals Staufen1-RNA binding features and links 3' UTR structure to RNA metabolism. Nucleic Acids Res 2023; 51:3573-3589. [PMID: 37013995 PMCID: PMC10164587 DOI: 10.1093/nar/gkad221] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 02/08/2023] [Accepted: 03/31/2023] [Indexed: 04/05/2023] Open
Abstract
The structure of mRNA molecules plays an important role in its interactions with trans-acting factors, notably RNA binding proteins (RBPs), thus contributing to the functional consequences of this interplay. However, current transcriptome-wide experimental methods to chart these interactions are limited by their poor sensitivity. Here we extend the hiCLIP atlas of duplexes bound by Staufen1 (STAU1) ∼10-fold, through careful consideration of experimental assumptions, and the development of bespoke computational methods which we apply to existing data. We present Tosca, a Nextflow computational pipeline for the processing, analysis and visualisation of proximity ligation sequencing data generally. We use our extended duplex atlas to discover insights into the RNA selectivity of STAU1, revealing the importance of structural symmetry and duplex-span-dependent nucleotide composition. Furthermore, we identify heterogeneity in the relationship between transcripts with STAU1-bound 3' UTR duplexes and metabolism of the associated RNAs that we relate to RNA structure: transcripts with short-range proximal 3' UTR duplexes have high degradation rates, but those with long-range duplexes have low rates. Overall, our work enables the integrative analysis of proximity ligation data delivering insights into specific features and effects of RBP-RNA structure interactions.
Collapse
Affiliation(s)
| | - Ira A Iosub
- The Francis Crick Institute, London, NW1 4AT, UK
| | - Flora C Y Lee
- The Francis Crick Institute, London, NW1 4AT, UK
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Jernej Ule
- The Francis Crick Institute, London, NW1 4AT, UK
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 9RX, UK
| | - Nicholas M Luscombe
- The Francis Crick Institute, London, NW1 4AT, UK
- Okinawa Institute of Science and Technology Graduate University, Onna-son, Okinawa904-0495, Japan
| |
Collapse
|
31
|
Culbertson B, Garcia K, Markett D, Asgharian H, Chen L, Fish L, Navickas A, Yu J, Woo B, Nanda AS, Choi B, Zhou S, Rabinowitz J, Goodarzi H. A sense-antisense RNA interaction promotes breast cancer metastasis via regulation of NQO1 expression. NATURE CANCER 2023; 4:682-698. [PMID: 37169843 PMCID: PMC10212767 DOI: 10.1038/s43018-023-00554-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 04/05/2023] [Indexed: 05/13/2023]
Abstract
Antisense RNAs are ubiquitous in human cells, yet their role is largely unexplored. Here we profiled antisense RNAs in the MDA-MB-231 breast cancer cell line and its highly lung metastatic derivative. We identified one antisense RNA that drives cancer progression by upregulating the redox enzyme NADPH quinone dehydrogenase 1 (NQO1), and named it NQO1-AS. Knockdown of either NQO1 or NQO1-AS reduced lung colonization in a mouse model, and investigation into the role of NQO1 indicated that it is broadly protective against oxidative damage and ferroptosis. Breast cancer cells in the lung are dependent on this pathway, and this dependence can be exploited therapeutically by inducing ferroptosis while inhibiting NQO1. Together, our findings establish a role for NQO1-AS in the progression of breast cancer by regulating its sense mRNA post-transcriptionally. Because breast cancer predominantly affects females, the disease models used in this study are of female origin and the results are primarily applicable to females.
Collapse
Affiliation(s)
- Bruce Culbertson
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Kristle Garcia
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Daniel Markett
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Hosseinali Asgharian
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Li Chen
- Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism & Integrative Biology, Fudan University, Shanghai, China
| | - Lisa Fish
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Albertas Navickas
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Johnny Yu
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Brian Woo
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Arjun Scott Nanda
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Benedict Choi
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Shaopu Zhou
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Joshua Rabinowitz
- Department of Chemistry, Lewis Sigler Institute for Integrative Genomics, Princeton, NJ, USA
- Ludwig Institute for Cancer Research, Princeton, NJ, USA
| | - Hani Goodarzi
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA.
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
32
|
Allan MF, Brivanlou A, Rouskin S. RNA levers and switches controlling viral gene expression. Trends Biochem Sci 2023; 48:391-406. [PMID: 36710231 DOI: 10.1016/j.tibs.2022.12.002] [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] [Received: 09/12/2022] [Revised: 11/27/2022] [Accepted: 12/15/2022] [Indexed: 01/29/2023]
Abstract
RNA viruses are diverse and abundant pathogens that are responsible for numerous human diseases. RNA viruses possess relatively compact genomes and have therefore evolved multiple mechanisms to maximize their coding capacities, often by encoding overlapping reading frames. These reading frames are then decoded by mechanisms such as alternative splicing and ribosomal frameshifting to produce multiple distinct proteins. These solutions are enabled by the ability of the RNA genome to fold into 3D structures that can mimic cellular RNAs, hijack host proteins, and expose or occlude regulatory protein-binding motifs to ultimately control key process in the viral life cycle. We highlight recent findings focusing on less conventional mechanisms of gene expression and new discoveries on the role of RNA structures.
Collapse
Affiliation(s)
- Matthew F Allan
- Department of Microbiology, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Amir Brivanlou
- Department of Microbiology, Harvard Medical School, Boston, MA 02115, USA
| | - Silvi Rouskin
- Department of Microbiology, Harvard Medical School, Boston, MA 02115, USA.
| |
Collapse
|
33
|
How does precursor RNA structure influence RNA processing and gene expression? Biosci Rep 2023; 43:232489. [PMID: 36689327 PMCID: PMC9977717 DOI: 10.1042/bsr20220149] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 01/17/2023] [Accepted: 01/23/2023] [Indexed: 01/24/2023] Open
Abstract
RNA is a fundamental biomolecule that has many purposes within cells. Due to its single-stranded and flexible nature, RNA naturally folds into complex and dynamic structures. Recent technological and computational advances have produced an explosion of RNA structural data. Many RNA structures have regulatory and functional properties. Studying the structure of nascent RNAs is particularly challenging due to their low abundance and long length, but their structures are important because they can influence RNA processing. Precursor RNA processing is a nexus of pathways that determines mature isoform composition and that controls gene expression. In this review, we examine what is known about human nascent RNA structure and the influence of RNA structure on processing of precursor RNAs. These known structures provide examples of how other nascent RNAs may be structured and show how novel RNA structures may influence RNA processing including splicing and polyadenylation. RNA structures can be targeted therapeutically to treat disease.
Collapse
|
34
|
Lee WH, Li K, Lu Z. Chemical crosslinking and ligation methods for in vivo analysis of RNA structures and interactions. Methods Enzymol 2023; 691:253-281. [PMID: 37914449 PMCID: PMC10994722 DOI: 10.1016/bs.mie.2023.02.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2023]
Abstract
RNA structures and interactions in living cells drive a variety of biological processes and play critical roles in physiology and disease states. However, studies of RNA structures and interactions have been challenging due to limitations in available technologies. Direct determination of structures in vitro has been only possible to a small number of RNAs with limited sizes and conformations. We recently introduced two chemical crosslink-ligation techniques that enabled studies of transcriptome-wide secondary and tertiary structures and their dynamics. In a dramatically improved version of the psoralen analysis of RNA interactions and structures (PARIS2) method, we detailed the synthesis and use of amotosalen, a highly soluble psoralen analogue, and enhanced enzymology for higher efficiency duplex capture. We also introduced spatial 2'-hydroxyl acylation reversible crosslinking (SHARC) with exonuclease (exo) trimming, a method which utilizes a novel crosslinker class that targets the 2'-OH to capture three-dimensional (3D) structures. Both are powerful orthogonal approaches for solving in vivo RNA structure and interactions, integrating crosslinking, exo trimming, proximity ligation, and high throughput sequencing. In this chapter, we present a detailed protocol for the methods and highlight steps that outperform existing crosslink-ligation approaches.
Collapse
Affiliation(s)
- Wilson H Lee
- Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences
| | - Kongpan Li
- Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences
| | - Zhipeng Lu
- Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, United States.
| |
Collapse
|
35
|
Chiang TK, Kimchi O, Dhaliwal HK, Villarreal DA, Vasquez FF, Manoharan VN, Brenner MP, Garmann RF. Measuring intramolecular connectivity in long RNA molecules using two-dimensional DNA patch-probe arrays. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.12.532302. [PMID: 36993626 PMCID: PMC10055002 DOI: 10.1101/2023.03.12.532302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
We describe a simple method to infer intramolecular connections in a population of long RNA molecules in vitro. First we add DNA oligonucleotide "patches" that perturb the RNA connections, then we use a microarray containing a complete set of DNA oligonucleotide "probes" to record where perturbations occur. The pattern of perturbations reveals couplings between different regions of the RNA sequence, from which we infer connections as well as their prevalences in the population. We validate this patch-probe method using the 1,058-nucleotide RNA genome of satellite tobacco mosaic virus (STMV), which has previously been shown to have multiple long-range connections. Our results not only indicate long duplexes that agree with previous structures but also reveal the prevalence of competing connections. Together, these results suggest that globally-folded and locally-folded structures coexist in solution. We show that the prevalence of connections changes when pseudouridine, an important component of natural and synthetic RNA molecules, is substituted for uridine in STMV RNA.
Collapse
|
36
|
The emerging diagnostic and therapeutic roles of small nucleolar RNAs in lung diseases. Biomed Pharmacother 2023; 161:114519. [PMID: 36906975 DOI: 10.1016/j.biopha.2023.114519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Revised: 03/09/2023] [Accepted: 03/09/2023] [Indexed: 03/12/2023] Open
Abstract
Small nucleolar RNAs (snoRNAs) are non-coding RNA molecules that range from 60 to 300 nucleotides in length and are primarily located in the nucleoli of cells. They play a critical role in modifying ribosomal RNA and can also regulate alternative splicing and posttranscriptional modification of mRNA. Alterations in snoRNA expression can affect numerous cellular processes, including cell proliferation, apoptosis, angiogenesis, fibrosis, and inflammation, making them a promising target for diagnostics and treatment of various human pathologies. Recent evidence suggests that abnormal snoRNA expression is strongly associated with the development and progression of several lung diseases, such as lung cancer, asthma, chronic obstructive pulmonary disease, and pulmonary hypertension, as well as COVID-19. While few studies have shown a causal relationship between snoRNA expression and disease onset, this research field presents exciting opportunities for identifying new biomarkers and therapeutic targets in lung disease. This review discusses the emerging role and molecular mechanisms of snoRNAs in the pathogenesis of lung diseases, focusing on research opportunities, clinical studies, biomarkers, and therapeutic potential.
Collapse
|
37
|
Velema WA, Lu Z. Chemical RNA Cross-Linking: Mechanisms, Computational Analysis, and Biological Applications. JACS AU 2023; 3:316-332. [PMID: 36873678 PMCID: PMC9975857 DOI: 10.1021/jacsau.2c00625] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/23/2022] [Accepted: 12/23/2022] [Indexed: 06/18/2023]
Abstract
In recent years, RNA has emerged as a multifaceted biomolecule that is involved in virtually every function of the cell and is critical for human health. This has led to a substantial increase in research efforts to uncover the many chemical and biological aspects of RNA and target RNA for therapeutic purposes. In particular, analysis of RNA structures and interactions in cells has been critical for understanding their diverse functions and druggability. In the last 5 years, several chemical methods have been developed to achieve this goal, using chemical cross-linking combined with high-throughput sequencing and computational analysis. Applications of these methods resulted in important new insights into RNA functions in a variety of biological contexts. Given the rapid development of new chemical technologies, a thorough perspective on the past and future of this field is provided. In particular, the various RNA cross-linkers and their mechanisms, the computational analysis and challenges, and illustrative examples from recent literature are discussed.
Collapse
Affiliation(s)
- Willem A. Velema
- Institute
for Molecules and Materials, Radboud University, Nijmegen 6500 HC, The Netherlands
| | - Zhipeng Lu
- Department
of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, California 90033, United States
| |
Collapse
|
38
|
Ryczek N, Łyś A, Makałowska I. The Functional Meaning of 5'UTR in Protein-Coding Genes. Int J Mol Sci 2023; 24:ijms24032976. [PMID: 36769304 PMCID: PMC9917990 DOI: 10.3390/ijms24032976] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 01/20/2023] [Accepted: 01/26/2023] [Indexed: 02/05/2023] Open
Abstract
As it is well known, messenger RNA has many regulatory regions along its sequence length. One of them is the 5' untranslated region (5'UTR), which itself contains many regulatory elements such as upstream ORFs (uORFs), internal ribosome entry sites (IRESs), microRNA binding sites, and structural components involved in the regulation of mRNA stability, pre-mRNA splicing, and translation initiation. Activation of the alternative, more upstream transcription start site leads to an extension of 5'UTR. One of the consequences of 5'UTRs extension may be head-to-head gene overlap. This review describes elements in 5'UTR of protein-coding transcripts and the functional significance of protein-coding genes 5' overlap with implications for transcription, translation, and disease.
Collapse
|
39
|
Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets. Funct Integr Genomics 2023; 23:33. [PMID: 36625940 PMCID: PMC9838419 DOI: 10.1007/s10142-022-00947-4] [Citation(s) in RCA: 38] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/14/2022] [Accepted: 12/15/2022] [Indexed: 01/11/2023]
Abstract
Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.
Collapse
|
40
|
Margasyuk SD, Vlasenok MA, Li G, Cao C, Pervouchine DD. RNAcontacts: A Pipeline for Predicting Contacts from RNA Proximity Ligation Assays. Acta Naturae 2023; 15:51-57. [PMID: 37153509 PMCID: PMC10154773 DOI: 10.32607/actanaturae.11893] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/20/2023] [Indexed: 05/09/2023] Open
Abstract
High-throughput RNA proximity ligation assays are molecular methods that are used to simultaneously analyze the spatial proximity of many RNAs in living cells. Their principle is based on cross-linking, fragmentation, and subsequent religation of RNAs, followed by high-throughput sequencing. The generated fragments have two different types of splits, one resulting from pre-mRNA splicing and the other formed by the ligation of spatially close RNA strands. Here, we present RNAcontacts, a universal pipeline for detecting RNA-RNA contacts in high-throughput RNA proximity ligation assays. RNAcontacts circumvents the inherent problem of mapping sequences with two distinct types of splits using a two-pass alignment, in which splice junctions are inferred from a control RNA-seq experiment on the first pass and then provided to the aligner as bona fide introns on the second pass. Compared to previously developed methods, our approach allows for a more sensitive detection of RNA contacts and has a higher specificity with respect to splice junctions that are present in the biological sample. RNAcontacts automatically extracts contacts, clusters their ligation points, computes the read support, and generates tracks for visualizing through the UCSC Genome Browser. The pipeline is implemented in Snakemake, a reproducible and scalable workflow management system for rapid and uniform processing of multiple datasets. RNAcontacts is a generic pipeline for the detection of RNA contacts that can be used with any proximity ligation method as long as one of the interacting partners is RNA. RNAcontacts is available via the GitHub repository https://github.com/smargasyuk/ RNAcontacts/.
Collapse
Affiliation(s)
- S. D. Margasyuk
- Skolkovo Institute of Science and Technology, Moscow, 121205 Russian Federation
| | - M. A. Vlasenok
- Skolkovo Institute of Science and Technology, Moscow, 121205 Russian Federation
| | - G. Li
- College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, ZJ310058 China
| | - Ch. Cao
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101 China
| | - D. D. Pervouchine
- Skolkovo Institute of Science and Technology, Moscow, 121205 Russian Federation
| |
Collapse
|
41
|
Kumar D, Sahoo SS, Chauss D, Kazemian M, Afzali B. Non-coding RNAs in immunoregulation and autoimmunity: Technological advances and critical limitations. J Autoimmun 2023; 134:102982. [PMID: 36592512 PMCID: PMC9908861 DOI: 10.1016/j.jaut.2022.102982] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/11/2022] [Accepted: 12/15/2022] [Indexed: 01/02/2023]
Abstract
Immune cell function is critically dependent on precise control over transcriptional output from the genome. In this respect, integration of environmental signals that regulate gene expression, specifically by transcription factors, enhancer DNA elements, genome topography and non-coding RNAs (ncRNAs), are key components. The first three have been extensively investigated. Even though non-coding RNAs represent the vast majority of cellular RNA species, this class of RNA remains historically understudied. This is partly because of a lag in technological and bioinformatic innovations specifically capable of identifying and accurately measuring their expression. Nevertheless, recent progress in this domain has enabled a profusion of publications identifying novel sub-types of ncRNAs and studies directly addressing the function of ncRNAs in human health and disease. Many ncRNAs, including circular and enhancer RNAs, have now been demonstrated to play key functions in the regulation of immune cells and to show associations with immune-mediated diseases. Some ncRNAs may function as biomarkers of disease, aiding in diagnostics and in estimating response to treatment, while others may play a direct role in the pathogenesis of disease. Importantly, some are relatively stable and are amenable to therapeutic targeting, for example through gene therapy. Here, we provide an overview of ncRNAs and review technological advances that enable their study and hold substantial promise for the future. We provide context-specific examples by examining the associations of ncRNAs with four prototypical human autoimmune diseases, specifically rheumatoid arthritis, psoriasis, inflammatory bowel disease and multiple sclerosis. We anticipate that the utility and mechanistic roles of these ncRNAs in autoimmunity will be further elucidated in the near future.
Collapse
Affiliation(s)
- Dhaneshwar Kumar
- Immunoregulation Section, Kidney Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH, Bethesda, MD, USA
| | - Subhransu Sekhar Sahoo
- Departments of Biochemistry and Computer Science, Purdue University, West Lafayette, IN, USA
| | - Daniel Chauss
- Immunoregulation Section, Kidney Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH, Bethesda, MD, USA
| | - Majid Kazemian
- Departments of Biochemistry and Computer Science, Purdue University, West Lafayette, IN, USA
| | - Behdad Afzali
- Immunoregulation Section, Kidney Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH, Bethesda, MD, USA.
| |
Collapse
|
42
|
Krohmaly KI, Freishtat RJ, Hahn AL. Bioinformatic and experimental methods to identify and validate bacterial RNA-human RNA interactions. J Investig Med 2023; 71:23-31. [PMID: 36162901 DOI: 10.1136/jim-2022-002509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/31/2022] [Indexed: 01/21/2023]
Abstract
Ample evidence supports the importance of the microbiota on human health and disease. Recent studies suggest that extracellular vesicles are an important means of bacterial-host communication, in part via the transport of small RNAs (sRNAs). Bacterial sRNAs have been shown to co-precipitate with human and mouse RNA-induced silencing complex, hinting that some may regulate gene expression as eukaryotic microRNAs do. Bioinformatic tools, including those that can incorporate an sRNA's secondary structure, can be used to predict interactions between bacterial sRNAs and human messenger RNAs (mRNAs). Validation of these potential interactions using reproducible experimental methods is essential to move the field forward. This review will cover the evidence of interspecies communication via sRNAs, bioinformatic tools currently available to identify potential bacterial sRNA-host (specifically, human) mRNA interactions, and experimental methods to identify and validate those interactions.
Collapse
Affiliation(s)
- Kylie I Krohmaly
- Center for Genetic Medicine Research, Children's National Research Institute, Washington, District of Columbia, USA.,Institute for Biomedical Sciences, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA
| | - Robert J Freishtat
- Center for Genetic Medicine Research, Children's National Research Institute, Washington, District of Columbia, USA.,Division of Emergency Medicine, Children's National Hospital, Washington, District of Columbia, USA.,Department of Pediatrics, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA
| | - Andrea L Hahn
- Center for Genetic Medicine Research, Children's National Research Institute, Washington, District of Columbia, USA.,Department of Pediatrics, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA.,Division of Infectious Diseases, Children's National Hospital, Washington, District of Columbia, USA
| |
Collapse
|
43
|
Spitale RC, Incarnato D. Probing the dynamic RNA structurome and its functions. Nat Rev Genet 2023; 24:178-196. [PMID: 36348050 PMCID: PMC9644009 DOI: 10.1038/s41576-022-00546-w] [Citation(s) in RCA: 45] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/06/2022] [Indexed: 11/09/2022]
Abstract
RNA is a key regulator of almost every cellular process, and the structures adopted by RNA molecules are thought to be central to their functions. The recent fast-paced evolution of high-throughput sequencing-based RNA structure mapping methods has enabled the rapid in vivo structural interrogation of entire cellular transcriptomes. Collectively, these studies are shedding new light on the long underestimated complexity of the structural organization of the transcriptome - the RNA structurome. Moreover, recent analyses are challenging the view that the RNA structurome is a static entity by revealing how RNA molecules establish intricate networks of alternative intramolecular and intermolecular interactions and that these ensembles of RNA structures are dynamically regulated to finely tune RNA functions in living cells. This new understanding of how RNA can shape cell phenotypes has important implications for the development of RNA-targeted therapeutic strategies.
Collapse
Affiliation(s)
- Robert C. Spitale
- grid.266093.80000 0001 0668 7243Department of Pharmaceutical Sciences, University of California, Irvine, CA USA
| | - Danny Incarnato
- Department of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute (GBB), University of Groningen, Groningen, The Netherlands.
| |
Collapse
|
44
|
Ding T, Zhang H. Novel biological insights revealed from the investigation of multiscale genome architecture. Comput Struct Biotechnol J 2022; 21:312-325. [PMID: 36582436 PMCID: PMC9791078 DOI: 10.1016/j.csbj.2022.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 12/06/2022] [Accepted: 12/06/2022] [Indexed: 12/13/2022] Open
Abstract
Gene expression and cell fate determination require precise and coordinated epigenetic regulation. The complex three-dimensional (3D) genome organization plays a critical role in transcription in myriad biological processes. A wide range of architectural features of the 3D genome, including chromatin loops, topologically associated domains (TADs), chromatin compartments, and phase separation, together regulate the chromatin state and transcriptional activity at multiple levels. With the help of 3D genome informatics, recent biochemistry and imaging approaches based on different strategies have revealed functional interactions among biomacromolecules, even at the single-cell level. Here, we review the occurrence, mechanistic basis, and functional implications of dynamic genome organization, and outline recent experimental and computational approaches for profiling multiscale genome architecture to provide robust tools for studying the 3D genome.
Collapse
Affiliation(s)
| | - He Zhang
- Corresponding author at: School of Life Science and Technology, Tongji University, Shanghai 200092, PR China.
| |
Collapse
|
45
|
Yu B, Li P, Zhang QC, Hou L. Differential analysis of RNA structure probing experiments at nucleotide resolution: uncovering regulatory functions of RNA structure. Nat Commun 2022; 13:4227. [PMID: 35869080 PMCID: PMC9307511 DOI: 10.1038/s41467-022-31875-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 07/05/2022] [Indexed: 11/09/2022] Open
Abstract
RNAs perform their function by forming specific structures, which can change across cellular conditions. Structure probing experiments combined with next generation sequencing technology have enabled transcriptome-wide analysis of RNA secondary structure in various cellular conditions. Differential analysis of structure probing data in different conditions can reveal the RNA structurally variable regions (SVRs), which is important for understanding RNA functions. Here, we propose DiffScan, a computational framework for normalization and differential analysis of structure probing data in high resolution. DiffScan preprocesses structure probing datasets to remove systematic bias, and then scans the transcripts to identify SVRs and adaptively determines their lengths and locations. The proposed approach is compatible with most structure probing platforms (e.g., icSHAPE, DMS-seq). When evaluated with simulated and benchmark datasets, DiffScan identifies structurally variable regions at nucleotide resolution, with substantial improvement in accuracy compared with existing SVR detection methods. Moreover, the improvement is robust when tested in multiple structure probing platforms. Application of DiffScan in a dataset of multi-subcellular RNA structurome and a subsequent motif enrichment analysis suggest potential links of RNA structural variation and mRNA abundance, possibly mediated by RNA binding proteins such as the serine/arginine rich splicing factors. This work provides an effective tool for differential analysis of RNA secondary structure, reinforcing the power of structure probing experiments in deciphering the dynamic RNA structurome. The authors present DiffScan, an advanced tool for normalization and differential analysis of RNA structure probing experiments, combining their power in deciphering the dynamic RNA structurome and facilitating the discovery of RNA regulatory functions.
Collapse
|
46
|
Zheng Y, Luo H, Teng X, Hao X, Yan X, Tang Y, Zhang W, Wang Y, Zhang P, Li Y, Zhao Y, Chen R, He S. NPInter v5.0: ncRNA interaction database in a new era. Nucleic Acids Res 2022; 51:D232-D239. [PMID: 36373614 PMCID: PMC9825547 DOI: 10.1093/nar/gkac1002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 10/16/2022] [Accepted: 10/21/2022] [Indexed: 11/16/2022] Open
Abstract
Noncoding RNAs (ncRNAs) play key regulatory roles in biological processes by interacting with other biomolecules. With the development of high-throughput sequencing and experimental technologies, extensive ncRNA interactions have been accumulated. Therefore, we updated the NPInter database to a fifth version to document these interactions. ncRNA interaction entries were doubled from 1 100 618 to 2 596 695 by manual literature mining and high-throughput data processing. We integrated global RNA-DNA interactions from iMARGI, ChAR-seq and GRID-seq, greatly expanding the number of RNA-DNA interactions (from 888 915 to 8 329 382). In addition, we collected different types of RNA interaction between SARS-CoV-2 virus and its host from recently published studies. Long noncoding RNA (lncRNA) expression specificity in different cell types from tumor single cell RNA-seq (scRNA-seq) data were also integrated to provide a cell-type level view of interactions. A new module named RBP was built to display the interactions of RNA-binding proteins with annotations of localization, binding domains and functions. In conclusion, NPInter v5.0 (http://bigdata.ibp.ac.cn/npinter5/) provides informative and valuable ncRNA interactions for biological researchers.
Collapse
Affiliation(s)
| | | | | | - Xinpei Hao
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoyu Yan
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiheng Tang
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Wanyu Zhang
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yuanxin Wang
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Peng Zhang
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yanyan Li
- Key Laboratory of RNA Biology, Center for Big Data Research in Health, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Yi Zhao
- Bioinformatics Research Group, Key Laboratory of Intelligent Information Processing, Advanced Computing Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
| | - Runsheng Chen
- Correspondence may also be addressed to Runsheng Chen. Tel: +86 10 64888543; Fax: +86 10 64871293
| | - Shunmin He
- To whom correspondence should be addressed. Tel: +86 10 64887032; Fax: +86 10 64887032;
| |
Collapse
|
47
|
Zhang J, Fei Y, Sun L, Zhang QC. Advances and opportunities in RNA structure experimental determination and computational modeling. Nat Methods 2022; 19:1193-1207. [PMID: 36203019 DOI: 10.1038/s41592-022-01623-y] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 08/23/2022] [Indexed: 11/09/2022]
Abstract
Beyond transferring genetic information, RNAs are molecules with diverse functions that include catalyzing biochemical reactions and regulating gene expression. Most of these activities depend on RNAs' specific structures. Therefore, accurately determining RNA structure is integral to advancing our understanding of RNA functions. Here, we summarize the state-of-the-art experimental and computational technologies developed to evaluate RNA secondary and tertiary structures. We also highlight how the rapid increase of experimental data facilitates the integrative modeling approaches for better resolving RNA structures. Finally, we provide our thoughts on the latest advances and challenges in RNA structure determination methods, as well as on future directions for both experimental approaches and artificial intelligence-based computational tools to model RNA structure. Ultimately, we hope the technological advances will deepen our understanding of RNA biology and facilitate RNA structure-based biomedical research such as designing specific RNA structures for therapeutics and deploying RNA-targeting small-molecule drugs.
Collapse
Affiliation(s)
- Jinsong Zhang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China.,Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China.,Tsinghua-Peking Center for Life Sciences, Beijing, China
| | - Yuhan Fei
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China.,Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China.,Tsinghua-Peking Center for Life Sciences, Beijing, China
| | - Lei Sun
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China. .,Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China. .,Tsinghua-Peking Center for Life Sciences, Beijing, China.
| | - Qiangfeng Cliff Zhang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China. .,Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China. .,Tsinghua-Peking Center for Life Sciences, Beijing, China.
| |
Collapse
|
48
|
Gasińska K, Czop M, Kosior-Jarecka E, Wróbel-Dudzińska D, Kocki J, Żarnowski T. Small Nucleolar RNAs in Pseudoexfoliation Glaucoma. Cells 2022; 11:cells11172738. [PMID: 36078146 PMCID: PMC9454646 DOI: 10.3390/cells11172738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 08/24/2022] [Accepted: 08/31/2022] [Indexed: 11/16/2022] Open
Abstract
Small nucleolar RNAs (snoRNAs) are small non-coding regulatory RNAs that have been investigated extensively in recent years. However, the relationship between snoRNA and glaucoma is still unknown. This study aims to analyze the levels of snoRNA expression in the aqueous humor (AH) of patients with pseudoexfoliation glaucoma (PEXG) compared to a control group and identify hypothetical snoRNA-dependent mechanisms contributing to PEXG. The AH was obtained from eighteen Caucasian patients, comprising nine PEXG and nine age-matched control patients. RNA was isolated, and a microarray system was used to determine the snoRNA expression profiles. Functional and enrichment analyses were performed. We identified seven snoRNAs, SNORD73B, SNORD58A, SNORD56, SNORA77, SNORA72, SNORA64, and SNORA32, in the AH of the PEXG and control group patients. Five snoRNAs showed statistically significantly lower expression in the PEXG group, and two snoRNAs had statistically significantly higher expression in the PEXG group compared to the control group. In addition, we identified two factors-CACNB3 for SNORA64 and TMEM63C for SNORA32, similar to PEX-related genes (CACNA1A and TMEM136). The enrichment analysis for four genes targeted by snoRNAs revealed possible mechanisms associated with glaucoma and/or PEX, but the direct role of snoRNAs in these biological processes was not proven.
Collapse
Affiliation(s)
- Karolina Gasińska
- Department of Diagnostics and Microsurgery of Glaucoma, Medical University of Lublin, 20-079 Lublin, Poland
| | - Marcin Czop
- Department of Clinical Genetics, Medical University of Lublin, 20-080 Lublin, Poland
| | - Ewa Kosior-Jarecka
- Department of Diagnostics and Microsurgery of Glaucoma, Medical University of Lublin, 20-079 Lublin, Poland
- Correspondence:
| | - Dominika Wróbel-Dudzińska
- Department of Diagnostics and Microsurgery of Glaucoma, Medical University of Lublin, 20-079 Lublin, Poland
| | - Janusz Kocki
- Department of Clinical Genetics, Medical University of Lublin, 20-080 Lublin, Poland
| | - Tomasz Żarnowski
- Department of Diagnostics and Microsurgery of Glaucoma, Medical University of Lublin, 20-079 Lublin, Poland
| |
Collapse
|
49
|
Singh S, Shyamal S, Panda AC. Detecting RNA-RNA interactome. WILEY INTERDISCIPLINARY REVIEWS. RNA 2022; 13:e1715. [PMID: 35132791 DOI: 10.1002/wrna.1715] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/27/2021] [Accepted: 01/07/2022] [Indexed: 06/14/2023]
Abstract
The last decade has seen a robust increase in various types of novel RNA molecules and their complexity in gene regulation. RNA molecules play a critical role in cellular events by interacting with other biomolecules, including protein, DNA, and RNA. It has been established that RNA-RNA interactions play a critical role in several biological processes by regulating the biogenesis and function of RNA molecules. Interestingly, RNA-RNA interactions regulate the biogenesis of diverse RNA molecules, including mRNAs, microRNAs, tRNAs, and circRNAs, through splicing or backsplicing. Structured RNAs like rRNA, tRNA, and snRNAs achieve their functional conformation by intramolecular RNA-RNA interactions. In addition, functional consequences of many intermolecular RNA-RNA interactions have been extensively studied in the regulation of gene expression. Hence, it is essential to understand the mechanism and functions of RNA-RNA interactions in eukaryotes. Conventionally, RNA-RNA interactions have been identified through diverse biochemical methods for decades. The advent of high-throughput RNA-sequencing technologies has revolutionized the identification of global RNA-RNA interactome in cells and their importance in RNA structure and function in gene expression regulation. Although these technologies revealed tens of thousands of intramolecular and intermolecular RNA-RNA interactions, we further look forward to future unbiased and quantitative high-throughput technologies for detecting transcriptome-wide RNA-RNA interactions. With the ability to detect RNA-RNA interactome, we expect that future studies will reveal the higher-order structures of RNA molecules and multi-RNA hybrids impacting human health and diseases. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.
Collapse
Affiliation(s)
- Suman Singh
- Institute of Life Sciences, Nalco Square, Bhubaneswar, India
- Regional Center for Biotechnology, Faridabad, India
| | | | - Amaresh C Panda
- Institute of Life Sciences, Nalco Square, Bhubaneswar, India
| |
Collapse
|
50
|
Yang SL, Ponti RD, Wan Y, Huber RG. Computational and Experimental Approaches to Study the RNA Secondary Structures of RNA Viruses. Viruses 2022; 14:v14081795. [PMID: 36016417 PMCID: PMC9415818 DOI: 10.3390/v14081795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 08/12/2022] [Accepted: 08/13/2022] [Indexed: 11/16/2022] Open
Abstract
Most pandemics of recent decades can be traced to RNA viruses, including HIV, SARS, influenza, dengue, Zika, and SARS-CoV-2. These RNA viruses impose considerable social and economic burdens on our society, resulting in a high number of deaths and high treatment costs. As these RNA viruses utilize an RNA genome, which is important for different stages of the viral life cycle, including replication, translation, and packaging, studying how the genome folds is important to understand virus function. In this review, we summarize recent advances in computational and high-throughput RNA structure-mapping approaches and their use in understanding structures within RNA virus genomes. In particular, we focus on the genome structures of the dengue, Zika, and SARS-CoV-2 viruses due to recent significant outbreaks of these viruses around the world.
Collapse
Affiliation(s)
- Siwy Ling Yang
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore 138672, Singapore
| | - Riccardo Delli Ponti
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore 138671, Singapore
| | - Yue Wan
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), Singapore 138672, Singapore
- Correspondence: (Y.W.); (R.G.H.)
| | - Roland G. Huber
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore 138671, Singapore
- Correspondence: (Y.W.); (R.G.H.)
| |
Collapse
|