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Pan YJ, Liu BW, Pei DS. The Role of Alternative Splicing in Cancer: Regulatory Mechanism, Therapeutic Strategy, and Bioinformatics Application. DNA Cell Biol 2022; 41:790-809. [PMID: 35947859 DOI: 10.1089/dna.2022.0322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
[Formula: see text] Alternative splicing (AS) can generate distinct transcripts and subsequent isoforms that play differential functions from the same pre-mRNA. Recently, increasing numbers of studies have emerged, unmasking the association between AS and cancer. In this review, we arranged AS events that are closely related to cancer progression and presented promising treatments based on AS for cancer therapy. Obtaining proliferative capacity, acquiring invasive properties, gaining angiogenic features, shifting metabolic ability, and getting immune escape inclination are all splicing events involved in biological processes. Spliceosome-targeted and antisense oligonucleotide technologies are two novel strategies that are hopeful in tumor therapy. In addition, bioinformatics applications based on AS were summarized for better prediction and elucidation of regulatory routines mingled in. Together, we aimed to provide a better understanding of complicated AS events associated with cancer biology and reveal AS a promising target of cancer treatment in the future.
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Affiliation(s)
- Yao-Jie Pan
- Department of Pathology, Laboratory of Clinical and Experimental Pathology, Xuzhou Medical University, Xuzhou, China
| | - Bo-Wen Liu
- Department of General Surgery, Xuzhou Medical University, Xuzhou, China
| | - Dong-Sheng Pei
- Department of Pathology, Laboratory of Clinical and Experimental Pathology, Xuzhou Medical University, Xuzhou, China
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Busetto V, Barbosa I, Basquin J, Marquenet É, Hocq R, Hennion M, Paternina JA, Namane A, Conti E, Bensaude O, Le Hir H. Structural and functional insights into CWC27/CWC22 heterodimer linking the exon junction complex to spliceosomes. Nucleic Acids Res 2020; 48:5670-5683. [PMID: 32329775 PMCID: PMC7261170 DOI: 10.1093/nar/gkaa267] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 04/01/2020] [Accepted: 04/22/2020] [Indexed: 11/22/2022] Open
Abstract
Human CWC27 is an uncharacterized splicing factor and mutations in its gene are linked to retinal degeneration and other developmental defects. We identify the splicing factor CWC22 as the major CWC27 partner. Both CWC27 and CWC22 are present in published Bact spliceosome structures, but no interacting domains are visible. Here, the structure of a CWC27/CWC22 heterodimer bound to the exon junction complex (EJC) core component eIF4A3 is solved at 3Å-resolution. According to spliceosomal structures, the EJC is recruited in the C complex, once CWC27 has left. Our 3D structure of the eIF4A3/CWC22/CWC27 complex is compatible with the Bact spliceosome structure but not with that of the C complex, where a CWC27 loop would clash with the EJC core subunit Y14. A CWC27/CWC22 building block might thus form an intermediate landing platform for eIF4A3 onto the Bact complex prior to its conversion into C complex. Knock-down of either CWC27 or CWC22 in immortalized retinal pigment epithelial cells affects numerous common genes, indicating that these proteins cooperate, targeting the same pathways. As the most up-regulated genes encode factors involved in inflammation, our findings suggest a possible link to the retinal degeneration associated with CWC27 deficiencies.
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Affiliation(s)
- Virginia Busetto
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, 46 rue d'Ulm, 75005 Paris, France
| | - Isabelle Barbosa
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, 46 rue d'Ulm, 75005 Paris, France
| | - Jérôme Basquin
- Department of Structural Cell Biology, MPI of Biochemistry, Munich, Germany
| | - Émelie Marquenet
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, 46 rue d'Ulm, 75005 Paris, France
| | - Rémi Hocq
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, 46 rue d'Ulm, 75005 Paris, France
| | - Magali Hennion
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, 46 rue d'Ulm, 75005 Paris, France
| | - Janio Antonio Paternina
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, 46 rue d'Ulm, 75005 Paris, France
| | - Abdelkader Namane
- Génétique des Interactions Macromoléculaires, Genomes and Genetics Department, Institut Pasteur, 25-28 rue du docteur Roux 75015 Paris, France
| | - Elena Conti
- Department of Structural Cell Biology, MPI of Biochemistry, Munich, Germany
| | - Olivier Bensaude
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, 46 rue d'Ulm, 75005 Paris, France
| | - Hervé Le Hir
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, 46 rue d'Ulm, 75005 Paris, France
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Saraiva-Agostinho N, Barbosa-Morais NL. psichomics: graphical application for alternative splicing quantification and analysis. Nucleic Acids Res 2019; 47:e7. [PMID: 30277515 PMCID: PMC6344878 DOI: 10.1093/nar/gky888] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 09/24/2018] [Indexed: 12/26/2022] Open
Abstract
Alternative pre-mRNA splicing generates functionally distinct transcripts from the same gene and is involved in the control of multiple cellular processes, with its dysregulation being associated with a variety of pathologies. The advent of next-generation sequencing has enabled global studies of alternative splicing in different physiological and disease contexts. However, current bioinformatics tools for alternative splicing analysis from RNA-seq data are not user-friendly, disregard available exon-exon junction quantification or have limited downstream analysis features. To overcome such limitations, we have developed psichomics, an R package with an intuitive graphical interface for alternative splicing quantification and downstream dimensionality reduction, differential splicing and gene expression and survival analyses based on The Cancer Genome Atlas, the Genotype-Tissue Expression project, the Sequence Read Archive project and user-provided data. These integrative analyses can also incorporate clinical and molecular sample-associated features. We successfully used psichomics in a laptop to reveal alternative splicing signatures specific to stage I breast cancer and associated novel putative prognostic factors.
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Affiliation(s)
- Nuno Saraiva-Agostinho
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Av. Professor Egas Moniz, 1649-028 Lisboa, Portugal
| | - Nuno L Barbosa-Morais
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Av. Professor Egas Moniz, 1649-028 Lisboa, Portugal
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Mapleson D, Venturini L, Kaithakottil G, Swarbreck D. Efficient and accurate detection of splice junctions from RNA-seq with Portcullis. Gigascience 2018; 7:5173486. [PMID: 30418570 PMCID: PMC6302956 DOI: 10.1093/gigascience/giy131] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 10/25/2018] [Indexed: 12/14/2022] Open
Abstract
Next-generation sequencing technologies enable rapid and cheap genome-wide transcriptome analysis, providing vital information about gene structure, transcript expression, and alternative splicing. Key to this is the accurate identification of exon-exon junctions from RNA sequenced (RNA-seq) reads. A number of RNA-seq aligners capable of splitting reads across these splice junctions (SJs) have been developed; however, it has been shown that while they correctly identify most genuine SJs available in a given sample, they also often produce large numbers of incorrect SJs. Here, we describe the extent of this problem using popular RNA-seq mapping tools and present a new method, called Portcullis, to rapidly filter false SJs derived from spliced alignments. We show that Portcullis distinguishes between genuine and false-positive junctions to a high degree of accuracy across different species, samples, expression levels, error profiles, and read lengths. Portcullis is portable, efficient, and, to our knowledge, currently the only SJ prediction tool that reliably scales for use with large RNA-seq datasets and large, highly fragmented genomes, while delivering accurate SJs.
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Affiliation(s)
- Daniel Mapleson
- Earlham Institute, Norwich Research Park, NR47UZ, Norwich, United Kingdom
| | - Luca Venturini
- Earlham Institute, Norwich Research Park, NR47UZ, Norwich, United Kingdom
| | - Gemy Kaithakottil
- Earlham Institute, Norwich Research Park, NR47UZ, Norwich, United Kingdom
| | - David Swarbreck
- Earlham Institute, Norwich Research Park, NR47UZ, Norwich, United Kingdom
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Li Y, McGrail DJ, Xu J, Mills GB, Sahni N, Yi S. Gene Regulatory Network Perturbation by Genetic and Epigenetic Variation. Trends Biochem Sci 2018; 43:576-592. [PMID: 29941230 DOI: 10.1016/j.tibs.2018.05.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2018] [Revised: 04/25/2018] [Accepted: 05/27/2018] [Indexed: 01/28/2023]
Abstract
Gene regulatory networks underlie biological function and cellular physiology. Alternative splicing (AS) is a fundamental step in gene regulatory networks and plays a key role in development and disease. In addition to the identification of aberrant AS events, an increasing number of studies are focusing on molecular determinants of AS, including genetic and epigenetic regulators. We review here recent efforts to identify various deregulated AS events as well as their molecular determinants that alter biological functions, and discuss clinical features of AS and their druggable potential.
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Affiliation(s)
- Yongsheng Li
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Harbin 150081, China
| | - Daniel J McGrail
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Juan Xu
- College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Harbin 150081, China
| | - Gordon B Mills
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Nidhi Sahni
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Program in Quantitative and Computational Biosciences (QCB), Baylor College of Medicine, Houston, TX 77030, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA; Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, USA.
| | - Song Yi
- Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA; Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
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Hamilton MJ, Girke T, Martinez E. Global isoform-specific transcript alterations and deregulated networks in clear cell renal cell carcinoma. Oncotarget 2018; 9:23670-23680. [PMID: 29805765 PMCID: PMC5955119 DOI: 10.18632/oncotarget.25330] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 04/19/2018] [Indexed: 11/25/2022] Open
Abstract
Extensive genome-wide analyses of deregulated gene expression have now been performed for many types of cancer. However, most studies have focused on deregulation at the gene-level, which may overlook the alterations of specific transcripts for a given gene. Clear cell renal cell carcinoma (ccRCC) is one of the best-characterized and most pervasive renal cancers, and ccRCCs are well-documented to have aberrant RNA processing. In the present study, we examine the extent of aberrant isoform-specific RNA expression by reporting a comprehensive transcript-level analysis, using the new kallisto-sleuth-RATs pipeline, investigating coding and non-coding differential transcript expression in ccRCC. We analyzed 50 ccRCC tumors and their matched normal samples from The Cancer Genome Altas datasets. We identified 7,339 differentially expressed transcripts and 94 genes exhibiting differential transcript isoform usage in ccRCC. Additionally, transcript-level coexpression network analyses identified vasculature development and the tricarboxylic acid cycle as the most significantly deregulated networks correlating with ccRCC progression. These analyses uncovered several uncharacterized transcripts, including lncRNAs FGD5-AS1 and AL035661.1, as potential regulators of the tricarboxylic acid cycle associated with ccRCC progression. As ccRCC still presents treatment challenges, our results provide a new resource of potential therapeutics targets and highlight the importance of exploring alternative methodologies in transcriptome-wide studies.
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Affiliation(s)
- Michael J. Hamilton
- Department of Biochemistry, University of California at Riverside, Riverside, CA, USA
| | - Thomas Girke
- Department of Botany and Plant Sciences, University of California at Riverside, Riverside, CA, USA
| | - Ernest Martinez
- Department of Biochemistry, University of California at Riverside, Riverside, CA, USA
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Comparative Analysis and Classification of Cassette Exons and Constitutive Exons. BIOMED RESEARCH INTERNATIONAL 2017; 2017:7323508. [PMID: 29349080 PMCID: PMC5734011 DOI: 10.1155/2017/7323508] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Accepted: 11/13/2017] [Indexed: 12/11/2022]
Abstract
Alternative splicing (AS) is a major engine that drives proteome diversity in mammalian genomes and is a widespread cause of human hereditary diseases. More than 95% of genes in the human genome are alternatively spliced, and the most common type of AS is the cassette exon. Recent discoveries have demonstrated that the cassette exon plays an important role in genetic diseases. To discover the formation mechanism of cassette exon events, we statistically analyze cassette exons and find that cassette exon events are strongly influenced by individual exons that are smaller in size and that have a lower GC content, more codon terminations, and weaker splice sites. We propose an improved random-forest-based hybrid method of distinguishing cassette exons from constitutive exons. Our method achieves a high accuracy in classifying cassette exons and constitutive exons and is verified to outperform previous approaches. It is anticipated that this study will facilitate a better understanding of the underlying mechanisms in cassette exons.
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Peng S, Yang S, Bo X, Li F. paraGSEA: a scalable approach for large-scale gene expression profiling. Nucleic Acids Res 2017; 45:e155. [PMID: 28973463 PMCID: PMC5737394 DOI: 10.1093/nar/gkx679] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2017] [Accepted: 07/27/2017] [Indexed: 12/28/2022] Open
Abstract
More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA.
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Affiliation(s)
- Shaoliang Peng
- College of Computer Science and Electronic Engineering & National Supercomputer Centre in Changsha, Hunan University, Changsha 410082, China.,School of Computer Science, National University of Defense Technology, Changsha 410073, China
| | - Shunyun Yang
- School of Computer Science, National University of Defense Technology, Changsha 410073, China
| | - Xiaochen Bo
- Department of biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, China
| | - Fei Li
- Department of biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, China
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