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Rodriguez JM, Pozo F, di Domenico T, Vazquez J, Tress ML. An analysis of tissue-specific alternative splicing at the protein level. PLoS Comput Biol 2020; 16:e1008287. [PMID: 33017396 PMCID: PMC7561204 DOI: 10.1371/journal.pcbi.1008287] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 10/15/2020] [Accepted: 08/25/2020] [Indexed: 01/09/2023] Open
Abstract
The role of alternative splicing is one of the great unanswered questions in cellular biology. There is strong evidence for alternative splicing at the transcript level, and transcriptomics experiments show that many splice events are tissue specific. It has been suggested that alternative splicing evolved in order to remodel tissue-specific protein-protein networks. Here we investigated the evidence for tissue-specific splicing among splice isoforms detected in a large-scale proteomics analysis. Although the data supporting alternative splicing is limited at the protein level, clear patterns emerged among the small numbers of alternative splice events that we could detect in the proteomics data. More than a third of these splice events were tissue-specific and most were ancient: over 95% of splice events that were tissue-specific in both proteomics and RNAseq analyses evolved prior to the ancestors of lobe-finned fish, at least 400 million years ago. By way of contrast, three in four alternative exons in the human gene set arose in the primate lineage, so our results cannot be extrapolated to the whole genome. Tissue-specific alternative protein forms in the proteomics analysis were particularly abundant in nervous and muscle tissues and their genes had roles related to the cytoskeleton and either the structure of muscle fibres or cell-cell connections. Our results suggest that this conserved tissue-specific alternative splicing may have played a role in the development of the vertebrate brain and heart. We manually curated a set of 255 splice events detected in a large-scale tissue-based proteomics experiment and found that more than a third had evidence of significant tissue-specific differences. Events that were significantly tissue-specific at the protein level were highly conserved; almost 75% evolved over 400 million years ago. The tissues in which we found most evidence for tissue-specific splicing were nervous tissues and cardiac tissues. Genes with tissue-specific events in these two tissues had functions related to important cellular structures in brain and heart tissues. These splice events may have been essential for the development of vertebrate heart and muscle. However, our data set may not be representative of alternative exons as a whole. We found that most tissue specific splicing was strongly conserved, but just 5% of annotated alternative exons in the human gene set are ancient. More than three quarters of alternative exons are primate-derived. Although the analysis does not provide a definitive answer to the question of the functional role of alternative splicing, our results do indicate that alternative splice variants may have played a significant part in the evolution of brain and heart tissues in vertebrates.
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Affiliation(s)
- Jose Manuel Rodriguez
- Cardiovascular Proteomics Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Calle Melchor Fernandez, Madrid, Spain
| | - Fernando Pozo
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez, Madrid, Spain
| | - Tomas di Domenico
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez, Madrid, Spain
| | - Jesus Vazquez
- Cardiovascular Proteomics Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Calle Melchor Fernandez, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Michael L. Tress
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez, Madrid, Spain
- * E-mail:
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Abstract
Objective Alternative splicing can generate various structural and functional protein isoforms. Recently, accumulating evidence shows a relationship between alternative splicing and cancer. Cancer is a complex and chronic disease that involves malignant transformation. In this review, we consider alternative splicing events in relation to the hallmarks of cancer cells, and discuss current therapies to treat cancer-related to alternative splicing. Data sources Data cited in this article are from the PubMed and Embase database, primarily focusing on research published from 2000 to 2018. Study selection Articles were selected with the search terms “alternative splicing,” “cancer cell,” “tumor microenvironment,” and “therapy.” Results Alternative splicing plays an important role in tumorigenesis, development, and escape from cell death. Taking this trait of cancer cells into consideration will allow more definite diagnoses of cancer, and allow the development of more effective medicines to intervene in cancer that could focus on controlling alternative splicing or competitively binding to the final products. Conclusions Alternative splicing is common in cancer cells. Consideration of alternative splicing may allow different strategies for cancer therapy or the identification of novel biomarkers for cancer diagnosis.
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53
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Sciarrillo R, Wojtuszkiewicz A, Assaraf YG, Jansen G, Kaspers GJL, Giovannetti E, Cloos J. The role of alternative splicing in cancer: From oncogenesis to drug resistance. Drug Resist Updat 2020; 53:100728. [PMID: 33070093 DOI: 10.1016/j.drup.2020.100728] [Citation(s) in RCA: 127] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 09/17/2020] [Accepted: 09/21/2020] [Indexed: 12/15/2022]
Abstract
Alternative splicing is a tightly regulated process whereby non-coding sequences of pre-mRNA are removed and protein-coding segments are assembled in diverse combinations, ultimately giving rise to proteins with distinct or even opposing functions. In the past decade, whole genome/transcriptome sequencing studies revealed the high complexity of splicing regulation, which occurs co-transcriptionally and is influenced by chromatin status and mRNA modifications. Consequently, splicing profiles of both healthy and malignant cells display high diversity and alternative splicing was shown to be widely deregulated in multiple cancer types. In particular, mutations in pre-mRNA regulatory sequences, splicing regulators and chromatin modifiers, as well as differential expression of splicing factors are important contributors to cancer pathogenesis. It has become clear that these aberrations contribute to many facets of cancer, including oncogenic transformation, cancer progression, response to anticancer drug treatment as well as resistance to therapy. In this respect, alternative splicing was shown to perturb the expression a broad spectrum of relevant genes involved in drug uptake/metabolism (i.e. SLC29A1, dCK, FPGS, and TP), activation of nuclear receptor pathways (i.e. GR, AR), regulation of apoptosis (i.e. MCL1, BCL-X, and FAS) and modulation of response to immunotherapy (CD19). Furthermore, aberrant splicing constitutes an important source of novel cancer biomarkers and the spliceosome machinery represents an attractive target for a novel and rapidly expanding class of therapeutic agents. Small molecule inhibitors targeting SF3B1 or splice factor kinases were highly cytotoxic against a wide range of cancer models, including drug-resistant cells. Importantly, these effects are enhanced in specific cancer subsets, such as splicing factor-mutated and c-MYC-driven tumors. Furthermore, pre-clinical studies report synergistic effects of spliceosome modulators in combination with conventional antitumor agents. These strategies based on the use of low dose splicing modulators could shift the therapeutic window towards decreased toxicity in healthy tissues. Here we provide an extensive overview of the latest findings in the field of regulation of splicing in cancer, including molecular mechanisms by which cancer cells harness alternative splicing to drive oncogenesis and evade anticancer drug treatment as well as splicing-based vulnerabilities that can provide novel treatment opportunities. Furthermore, we discuss current challenges arising from genome-wide detection and prediction methods of aberrant splicing, as well as unravelling functional relevance of the plethora of cancer-related splicing alterations.
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Affiliation(s)
- Rocco Sciarrillo
- Department of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands; Department of Pediatric Oncology, Emma's Children's Hospital, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands; Department of Medical Oncology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands
| | - Anna Wojtuszkiewicz
- Department of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands
| | - Yehuda G Assaraf
- The Fred Wyszkowski Cancer Research Laboratory, Department of Biology, Technion-Israel Institute of Technology, Haifa 3200003, Israel
| | - Gerrit Jansen
- Amsterdam Immunology and Rheumatology Center, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands
| | - Gertjan J L Kaspers
- Department of Pediatric Oncology, Emma's Children's Hospital, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands; Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands
| | - Elisa Giovannetti
- Department of Medical Oncology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands; Fondazione Pisana per la Scienza, Pisa, Italy
| | - Jacqueline Cloos
- Department of Hematology, Amsterdam UMC, VU University Medical Center, Cancer Center Amsterdam, Amsterdam, Netherlands.
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54
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Lau E, Han Y, Williams DR, Thomas CT, Shrestha R, Wu JC, Lam MPY. Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome. Cell Rep 2020; 29:3751-3765.e5. [PMID: 31825849 PMCID: PMC6961840 DOI: 10.1016/j.celrep.2019.11.026] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 09/24/2019] [Accepted: 11/06/2019] [Indexed: 12/18/2022] Open
Abstract
The protein-level translational status and function of many alternative splicing events remain poorly understood. We use an RNA sequencing (RNA-seq)-guided proteomics method to identify protein alternative splicing isoforms in the human proteome by constructing tissue-specific protein databases that prioritize transcript splice junction pairs with high translational potential. Using the custom databases to reanalyze ~80 million mass spectra in public proteomics datasets, we identify more than 1,500 noncanonical protein isoforms across 12 human tissues, including ~400 sequences undocumented on TrEMBL and RefSeq databases. We apply the method to original quantitative mass spectrometry experiments and observe widespread isoform regulation during human induced pluripotent stem cell cardiomyocyte differentiation. On a proteome scale, alternative isoform regions overlap frequently with disordered sequences and post-translational modification sites, suggesting that alternative splicing may regulate protein function through modulating intrinsically disordered regions. The described approach may help elucidate functional consequences of alternative splicing and expand the scope of proteomics investigations in various systems. The translation and function of many alternative splicing events await confirmation at the protein level. Lau et al. use an integrated proteotranscriptomics approach to identify non-canonical and undocumented isoforms from 12 organs in the human proteome. Alternative isoforms interfere with functional sequence features and are differentially regulated during iPSC cardiomyocyte differentiation.
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Affiliation(s)
- Edward Lau
- Stanford Cardiovascular Institute, Department of Medicine, Stanford University, Palo Alto, CA, USA
| | - Yu Han
- Consortium for Fibrosis Research and Translation, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA; Departments of Medicine-Cardiology and Biochemistry and Molecular Genetics, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Damon R Williams
- Stanford Cardiovascular Institute, Department of Medicine, Stanford University, Palo Alto, CA, USA
| | - Cody T Thomas
- Departments of Medicine-Cardiology and Biochemistry and Molecular Genetics, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA
| | - Rajani Shrestha
- Stanford Cardiovascular Institute, Department of Medicine, Stanford University, Palo Alto, CA, USA
| | - Joseph C Wu
- Stanford Cardiovascular Institute, Department of Medicine, Stanford University, Palo Alto, CA, USA; Department of Radiology, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Maggie P Y Lam
- Consortium for Fibrosis Research and Translation, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA; Departments of Medicine-Cardiology and Biochemistry and Molecular Genetics, Anschutz Medical Campus, University of Colorado, Aurora, CO, USA.
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55
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A few good peptides: MHC class I-based cancer immunosurveillance and immunoevasion. Nat Rev Immunol 2020; 21:116-128. [PMID: 32820267 DOI: 10.1038/s41577-020-0390-6] [Citation(s) in RCA: 130] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/30/2020] [Indexed: 12/25/2022]
Abstract
The remarkable success of immune checkpoint inhibitors demonstrates the potential of tumour-specific CD8+ T cells to prevent and treat cancer. Although the number of lives saved by immunotherapy mounts, only a relatively small fraction of patients are cured. Here, we review two of the factors that limit the application of CD8+ T cell immunotherapies: difficulties in identifying tumour-specific peptides presented by MHC class I molecules and the ability of tumour cells to impair antigen presentation as they evolve under T cell selection. We describe recent advances in understanding how peptides are generated from non-canonical translation of defective ribosomal products, relate this to the dysregulated translation that is a feature of carcinogenesis and propose dysregulated translation as an important new source of tumour-specific peptides. We discuss how the synthesis and function of components of the antigen-processing and presentation pathway, including the recently described immunoribosome, are manipulated by tumours for immunoevasion and point to common druggable targets that may enhance immunotherapy.
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56
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Xu Z, Asakawa S. Physiological RNA dynamics in RNA-Seq analysis. Brief Bioinform 2020; 20:1725-1733. [PMID: 30010714 DOI: 10.1093/bib/bby045] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Revised: 04/24/2018] [Indexed: 02/06/2023] Open
Abstract
Physiological RNA dynamics cause problems in transcriptome analysis. Physiological RNA accumulation affects the analysis of RNA quantification, and physiological RNA degradation affects the analysis of the RNA sequence length, feature site and quantification. In the present article, we review the effects of physiological degradation and accumulation of RNA on analysing RNA sequencing data. Physiological RNA accumulation and degradation probably led to such phenomena as incorrect estimations of transcription quantification, differential expressions, co-expressions, RNA decay rates, alternative splicing, boundaries of transcription, novel genes, new single-nucleotide polymorphisms, small RNAs and gene fusion. Thus, the transcriptomic data obtained up to date warrant further scrutiny. New and improved techniques and bioinformatics software are needed to produce accurate data in transcriptome research.
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Affiliation(s)
- Zhongneng Xu
- Department of Ecology, Jinan University, Guangzhou 510632, China
| | - Shuichi Asakawa
- Department of Aquatic Bioscience, Graduate School of Agricultural and Life Science, The University of Tokyo, Tokyo 113-8657, Japan
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57
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Calviello L, Hirsekorn A, Ohler U. Quantification of translation uncovers the functions of the alternative transcriptome. Nat Struct Mol Biol 2020; 27:717-725. [DOI: 10.1038/s41594-020-0450-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 05/13/2020] [Indexed: 11/09/2022]
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58
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Kiniry SJ, Michel AM, Baranov PV. Computational methods for ribosome profiling data analysis. WILEY INTERDISCIPLINARY REVIEWS. RNA 2020; 11:e1577. [PMID: 31760685 DOI: 10.1002/wrna.1577] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 10/12/2019] [Accepted: 10/16/2019] [Indexed: 12/15/2022]
Abstract
Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis. This article is characterized under: Translation > Ribosome Structure/Function RNA Evolution and Genomics > Computational Analyses of RNA Translation > Translation Mechanisms Translation > Translation Regulation.
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Affiliation(s)
- Stephen J Kiniry
- School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland
| | - Audrey M Michel
- School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland
| | - Pavel V Baranov
- School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, RAS, Moscow, Russia
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59
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Reixachs-Solé M, Ruiz-Orera J, Albà MM, Eyras E. Ribosome profiling at isoform level reveals evolutionary conserved impacts of differential splicing on the proteome. Nat Commun 2020; 11:1768. [PMID: 32286305 PMCID: PMC7156646 DOI: 10.1038/s41467-020-15634-w] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Accepted: 03/11/2020] [Indexed: 12/14/2022] Open
Abstract
The differential production of transcript isoforms from gene loci is a key cellular mechanism. Yet, its impact in protein production remains an open question. Here, we describe ORQAS (ORF quantification pipeline for alternative splicing), a pipeline for the translation quantification of individual transcript isoforms using ribosome-protected mRNA fragments (ribosome profiling). We find evidence of translation for 40-50% of the expressed isoforms in human and mouse, with 53% of the expressed genes having more than one translated isoform in human, and 33% in mouse. Differential splicing analysis revealed that about 40% of the splicing changes at RNA level are concordant with changes in translation. Furthermore, orthologous cassette exons between human and mouse preserve the directionality of the change, and are enriched in microexons in a comparison between glia and glioma. ORQAS leverages ribosome profiling to uncover a widespread and evolutionarily conserved impact of differential splicing on translation, particularly of microexon-containing isoforms.
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Affiliation(s)
- Marina Reixachs-Solé
- The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia
| | - Jorge Ruiz-Orera
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, 13125, Germany
| | - M Mar Albà
- IMIM - Hospital del Mar Medical Research Institute, E08003, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies, E08010, Barcelona, Spain
- Pompeu Fabra University, E08003, Barcelona, Spain
| | - Eduardo Eyras
- The John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2601, Australia.
- EMBL Australia Partner Laboratory Network at the Australian National University, Canberra, ACT, 2601, Australia.
- IMIM - Hospital del Mar Medical Research Institute, E08003, Barcelona, Spain.
- Catalan Institution for Research and Advanced Studies, E08010, Barcelona, Spain.
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60
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Fujita KI, Ishizuka T, Mitsukawa M, Kurata M, Masuda S. Regulating Divergent Transcriptomes through mRNA Splicing and Its Modulation Using Various Small Compounds. Int J Mol Sci 2020; 21:ijms21062026. [PMID: 32188117 PMCID: PMC7139312 DOI: 10.3390/ijms21062026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 03/11/2020] [Accepted: 03/12/2020] [Indexed: 12/14/2022] Open
Abstract
Human transcriptomes are more divergent than genes and contribute to the sophistication of life. This divergence is derived from various isoforms arising from alternative splicing. In addition, alternative splicing regulated by spliceosomal factors and RNA structures, such as the RNA G-quadruplex, is important not only for isoform diversity but also for regulating gene expression. Therefore, abnormal splicing leads to serious diseases such as cancer and neurodegenerative disorders. In the first part of this review, we describe the regulation of divergent transcriptomes using alternative mRNA splicing. In the second part, we present the relationship between the disruption of splicing and diseases. Recently, various compounds with splicing inhibitor activity were established. These splicing inhibitors are recognized as a biological tool to investigate the molecular mechanism of splicing and as a potential therapeutic agent for cancer treatment. Food-derived compounds with similar functions were found and are expected to exhibit anticancer effects. In the final part, we describe the compounds that modulate the messenger RNA (mRNA) splicing process and their availability for basic research and future clinical potential.
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61
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Abstract
High-throughput sequencing-based methods and their applications in the study of transcriptomes have revolutionized our understanding of alternative splicing. Networks of functionally coordinated and biologically important alternative splicing events continue to be discovered in an ever-increasing diversity of cell types in the context of physiologically normal and disease states. These studies have been complemented by efforts directed at defining sequence codes governing splicing and their cognate trans-acting factors, which have illuminated important combinatorial principles of regulation. Additional studies have revealed critical roles of position-dependent, multivalent protein-RNA interactions that direct splicing outcomes. Investigations of evolutionary changes in RNA binding proteins, splice variants, and associated cis elements have further shed light on the emergence, mechanisms, and functions of splicing networks. Progress in these areas has emphasized the need for a coordinated, community-based effort to systematically address the functions of individual splice variants associated with normal and disease biology.
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62
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Ait-Hamlat A, Zea DJ, Labeeuw A, Polit L, Richard H, Laine E. Transcripts' Evolutionary History and Structural Dynamics Give Mechanistic Insights into the Functional Diversity of the JNK Family. J Mol Biol 2020; 432:2121-2140. [PMID: 32067951 DOI: 10.1016/j.jmb.2020.01.032] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 01/03/2020] [Accepted: 01/28/2020] [Indexed: 12/14/2022]
Abstract
Alternative splicing and alternative initiation/termination transcription sites have the potential to greatly expand the proteome in eukaryotes by producing several transcript isoforms from the same gene. Although these mechanisms are well described at the genomic level, little is known about their contribution to protein evolution and their impact at the protein structure level. Here, we address both issues by reconstructing the evolutionary history of transcripts and by modeling the tertiary structures of the corresponding protein isoforms. We reconstruct phylogenetic forests relating 60 protein-coding transcripts from the c-Jun N-terminal kinase (JNK) family observed in seven species. We identify two alternative splicing events of ancient origin and show that they induce subtle changes in the protein's structural dynamics. We highlight a previously uncharacterized transcript whose predicted structure seems stable in solution. We further demonstrate that orphan transcripts, for which no phylogeny could be reconstructed, display peculiar sequence and structural properties. Our approach is implemented in PhyloSofS (Phylogenies of Splicing Isoforms Structures), a fully automated computational tool freely available at https://github.com/PhyloSofS-Team/PhyloSofS.
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Affiliation(s)
- Adel Ait-Hamlat
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, 75005, France
| | - Diego Javier Zea
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, 75005, France
| | - Antoine Labeeuw
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, 75005, France
| | - Lélia Polit
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, 75005, France
| | - Hugues Richard
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, 75005, France.
| | - Elodie Laine
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, 75005, France.
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63
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Annalora AJ, Marcus CB, Iversen PL. Alternative Splicing in the Nuclear Receptor Superfamily Expands Gene Function to Refine Endo-Xenobiotic Metabolism. Drug Metab Dispos 2020; 48:272-287. [DOI: 10.1124/dmd.119.089102] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 12/31/2019] [Indexed: 12/20/2022] Open
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64
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Zhang P, Southey BR, Rodriguez-Zas SL. Co-expression networks uncover regulation of splicing and transcription markers of disease. PROCEEDINGS OF THE ... ANNUAL INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND COMPUTATIONAL BIOLOGY 2020; 70:119-128. [PMID: 35047432 DOI: 10.29007/rl4h] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Gene co-expression networks based on gene expression data are usually used to capture biologically significant patterns, enabling the discovery of biomarkers and interpretation of regulatory relationships. However, the coordination of numerous splicing changes within and across genes can exert a substantial impact on the function of these genes. This is particularly impactful in studies of the properties of the nervous system, which can be masked in the networks that only assess the correlation between gene expression levels. A bioinformatics approach was developed to uncover the role of alternative splicing and associated transcriptional networks using RNA-seq profiles. Data from 40 samples, including control and two treatments associated with sensitivity to stimuli across two central nervous system regions that can present differential splicing, were explored. The gene expression and relative isoform levels were integrated into a transcriptome-wide matrix, and then Graphical Lasso was applied to capture the interactions between genes and isoforms. Next, functional enrichment analysis enabled the discovery of pathways dysregulated at the isoform or gene levels and the interpretation of these interactions within a central nervous region. In addition, a Bayesian biclustering strategy was used to reconstruct treatment-specific networks from gene expression profile, allowing the identification of hub molecules and visualization of highly connected modules of isoforms and genes in specific conditions. Our bioinformatics approach can offer comparable insights into the discovery of biomarkers and therapeutic targets for a wide range of diseases and conditions.
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Affiliation(s)
- Pan Zhang
- Illinois Informatics Institute, University of Illinois at Urbana-Champaign, Urbana, IL, the U.S.,Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, the U.S
| | - Bruce R Southey
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, the U.S
| | - Sandra L Rodriguez-Zas
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, the U.S.,Department of Statistics, University of Illinois at Urbana-Champaign, Urbana, IL, the U.S.,Carle Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, the U.S
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65
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Agosto LM, Gazzara MR, Radens CM, Sidoli S, Baeza J, Garcia BA, Lynch KW. Deep profiling and custom databases improve detection of proteoforms generated by alternative splicing. Genome Res 2019; 29:2046-2055. [PMID: 31727681 PMCID: PMC6886501 DOI: 10.1101/gr.248435.119] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Accepted: 09/16/2019] [Indexed: 02/05/2023]
Abstract
Alternative pre-mRNA splicing has long been proposed to contribute greatly to proteome complexity. However, the extent to which mature mRNA isoforms are successfully translated into protein remains controversial. Here, we used high-throughput RNA sequencing and mass spectrometry (MS)–based proteomics to better evaluate the translation of alternatively spliced mRNAs. To increase proteome coverage and improve protein quantitation, we optimized cell fractionation and sample processing steps at both the protein and peptide level. Furthermore, we generated a custom peptide database trained on analysis of RNA-seq data with MAJIQ, an algorithm optimized to detect and quantify differential and unannotated splice junction usage. We matched tandem mass spectra acquired by data-dependent acquisition (DDA) against our custom RNA-seq based database, as well as SWISS-PROT and RefSeq databases to improve identification of splicing-derived proteoforms by 28% compared with use of the SWISS-PROT database alone. Altogether, we identified peptide evidence for 554 alternate proteoforms corresponding to 274 genes. Our increased depth and detection of proteins also allowed us to track changes in the transcriptome and proteome induced by T-cell stimulation, as well as fluctuations in protein subcellular localization. In sum, our data here confirm that use of generic databases in proteomic studies underestimates the number of spliced mRNA isoforms that are translated into protein and provides a workflow that improves isoform detection in large-scale proteomic experiments.
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Affiliation(s)
- Laura M Agosto
- Biochemistry and Molecular Biophysics Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.,Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.,Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Matthew R Gazzara
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.,Genomics and Computational Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Caleb M Radens
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.,Genetics and Epigenetics, Cell & Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Simone Sidoli
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.,Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Josue Baeza
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.,Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Benjamin A Garcia
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.,Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Kristen W Lynch
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
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66
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PRMT5 methylome profiling uncovers a direct link to splicing regulation in acute myeloid leukemia. Nat Struct Mol Biol 2019; 26:999-1012. [PMID: 31611688 PMCID: PMC6858565 DOI: 10.1038/s41594-019-0313-z] [Citation(s) in RCA: 95] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 09/03/2019] [Indexed: 12/28/2022]
Abstract
Protein arginine methyltransferase 5 (PRMT5) has emerged as a promising cancer drug target, and three PRMT5 inhibitors are currently in clinical trials for multiple malignancies. In this study, we investigated the role of PRMT5 in human acute myeloid leukemia (AML). Using an enzymatic dead version of PRMT5 and a PRMT5-specific inhibitor, we demonstrated the requirement of the catalytic activity of PRMT5 for the survival of AML cells. We then identified PRMT5 substrates using multiplexed quantitative proteomics and investigated their role in the survival of AML cells. We found that the function of the splicing regulator SRSF1 relies on its methylation by PRMT5 and that loss of PRMT5 leads to changes in alternative splicing of multiple essential genes. This explains the requirement of PRMT5 for leukemia cell survival. We show that PRMT5 regulates binding of SRSF1 to mRNAs and proteins and provide potential biomarkers for the treatment response to PRMT5 inhibitors.
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67
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Furlanis E, Traunmüller L, Fucile G, Scheiffele P. Landscape of ribosome-engaged transcript isoforms reveals extensive neuronal-cell-class-specific alternative splicing programs. Nat Neurosci 2019; 22:1709-1717. [PMID: 31451803 PMCID: PMC6763336 DOI: 10.1038/s41593-019-0465-5] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 07/09/2019] [Indexed: 01/21/2023]
Abstract
Nervous system function relies on complex assemblies of distinct neuronal cell types that have unique anatomical and functional properties instructed by molecular programs. Alternative splicing is a key mechanism for the expansion of molecular repertoires, and protein splice isoforms shape neuronal cell surface recognition and function. However, the logic of how alternative splicing programs are arrayed across neuronal cells types is poorly understood. We systematically mapped ribosome-associated transcript isoforms in genetically defined neuron types of the mouse forebrain. Our dataset provides an extensive resource of transcript diversity across major neuron classes. We find that neuronal transcript isoform profiles reliably distinguish even closely related classes of pyramidal cells and inhibitory interneurons in the mouse hippocampus and neocortex. These highly specific alternative splicing programs selectively control synaptic proteins and intrinsic neuronal properties. Thus, transcript diversification via alternative splicing is a central mechanism for the functional specification of neuronal cell types and circuits.
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Affiliation(s)
| | | | - Geoffrey Fucile
- Center for Scientific Computing (sciCORE), University of Basel, Basel, Switzerland
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68
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Frankiw L, Baltimore D, Li G. Alternative mRNA splicing in cancer immunotherapy. Nat Rev Immunol 2019; 19:675-687. [PMID: 31363190 DOI: 10.1038/s41577-019-0195-7] [Citation(s) in RCA: 150] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/02/2019] [Indexed: 12/12/2022]
Abstract
Immunotherapies are yielding effective treatments for several previously untreatable cancers. Still, the identification of suitable antigens specific to the tumour that can be targets for cancer vaccines and T cell therapies is a challenge. Alternative processing of mRNA, a phenomenon that has been shown to alter the proteomic diversity of many cancers, may offer the potential of a broadened target space. Here, we discuss the promise of analysing mRNA processing events in cancer cells, with an emphasis on mRNA splicing, for the identification of potential new targets for cancer immunotherapy. Further, we highlight the challenges that must be overcome for this new avenue to have clinical applicability.
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Affiliation(s)
- Luke Frankiw
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - David Baltimore
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
| | - Guideng Li
- Center of Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. .,Suzhou Institute of Systems Medicine, Suzhou, China.
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69
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Chaudhary S, Jabre I, Reddy ASN, Staiger D, Syed NH. Perspective on Alternative Splicing and Proteome Complexity in Plants. TRENDS IN PLANT SCIENCE 2019; 24:496-506. [PMID: 30852095 DOI: 10.1016/j.tplants.2019.02.006] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 01/28/2019] [Accepted: 02/08/2019] [Indexed: 05/02/2023]
Abstract
Alternative splicing (AS) generates multiple transcripts from the same gene, however, AS contribution to proteome complexity remains elusive in plants. AS is prevalent under stress conditions in plants, but it is counterintuitive why plants would invest in protein synthesis under declining energy supply. We propose that plants employ AS not only to potentially increasing proteomic complexity, but also to buffer against the stress-responsive transcriptome to reduce the metabolic cost of translating all AS transcripts. To maximise efficiency under stress, plants may make fewer proteins with disordered domains via AS to diversify substrate specificity and maintain sufficient regulatory capacity. Furthermore, we suggest that chromatin state-dependent AS engenders short/long-term stress memory to mediate reproducible transcriptional response in the future.
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Affiliation(s)
- Saurabh Chaudhary
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, CT1 1QU, UK; These authors contributed equally to this work
| | - Ibtissam Jabre
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, CT1 1QU, UK; These authors contributed equally to this work
| | - Anireddy S N Reddy
- Department of Biology and Program in Cell and Molecular Biology, Colorado State University, Fort Collins, CO 80523-1878, USA
| | - Dorothee Staiger
- RNA Biology and Molecular Physiology, Faculty of Biology, Bielefeld University, Bielefeld, Germany
| | - Naeem H Syed
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, CT1 1QU, UK.
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70
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View from an mRNP: The Roles of SR Proteins in Assembly, Maturation and Turnover. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1203:83-112. [PMID: 31811631 DOI: 10.1007/978-3-030-31434-7_3] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Serine- and arginine-rich proteins (SR proteins) are a family of multitasking RNA-binding proteins (RBPs) that are key determinants of messenger ribonucleoprotein (mRNP) formation, identity and fate. Apart from their essential functions in pre-mRNA splicing, SR proteins display additional pre- and post-splicing activities and connect nuclear and cytoplasmic gene expression machineries. Through changes in their post-translational modifications (PTMs) and their subcellular localization, they provide functional specificity and adjustability to mRNPs. Transcriptome-wide UV crosslinking and immunoprecipitation (CLIP-Seq) studies revealed that individual SR proteins are present in distinct mRNPs and act in specific pairs to regulate different gene expression programmes. Adopting an mRNP-centric viewpoint, we discuss the roles of SR proteins in the assembly, maturation, quality control and turnover of mRNPs and describe the mechanisms by which they integrate external signals, coordinate their multiple tasks and couple subsequent mRNA processing steps.
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71
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Networks of mRNA Processing and Alternative Splicing Regulation in Health and Disease. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1157:1-27. [PMID: 31342435 DOI: 10.1007/978-3-030-19966-1_1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
mRNA processing events introduce an intricate layer of complexity into gene expression processes, supporting a tremendous level of diversification of the genome's coding and regulatory potential, particularly in vertebrate species. The recent development of massive parallel sequencing methods and their adaptation to the identification and quantification of different RNA species and the dynamics of mRNA metabolism and processing has generated an unprecedented view over the regulatory networks that are established at this level, which contribute to sustain developmental, tissue specific or disease specific gene expression programs. In this chapter, we provide an overview of the recent evolution of transcriptome profiling methods and the surprising insights that have emerged in recent years regarding distinct mRNA processing events - from the 5' end to the 3' end of the molecule.
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72
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Chaudhary S, Khokhar W, Jabre I, Reddy ASN, Byrne LJ, Wilson CM, Syed NH. Alternative Splicing and Protein Diversity: Plants Versus Animals. FRONTIERS IN PLANT SCIENCE 2019; 10:708. [PMID: 31244866 PMCID: PMC6581706 DOI: 10.3389/fpls.2019.00708] [Citation(s) in RCA: 110] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Accepted: 05/13/2019] [Indexed: 05/11/2023]
Abstract
Plants, unlike animals, exhibit a very high degree of plasticity in their growth and development and employ diverse strategies to cope with the variations during diurnal cycles and stressful conditions. Plants and animals, despite their remarkable morphological and physiological differences, share many basic cellular processes and regulatory mechanisms. Alternative splicing (AS) is one such gene regulatory mechanism that modulates gene expression in multiple ways. It is now well established that AS is prevalent in all multicellular eukaryotes including plants and humans. Emerging evidence indicates that in plants, as in animals, transcription and splicing are coupled. Here, we reviewed recent evidence in support of co-transcriptional splicing in plants and highlighted similarities and differences between plants and humans. An unsettled question in the field of AS is the extent to which splice isoforms contribute to protein diversity. To take a critical look at this question, we presented a comprehensive summary of the current status of research in this area in both plants and humans, discussed limitations with the currently used approaches and suggested improvements to current methods and alternative approaches. We end with a discussion on the potential role of epigenetic modifications and chromatin state in splicing memory in plants primed with stresses.
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Affiliation(s)
- Saurabh Chaudhary
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, United Kingdom
| | - Waqas Khokhar
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, United Kingdom
| | - Ibtissam Jabre
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, United Kingdom
| | - Anireddy S. N. Reddy
- Department of Biology and Program in Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
| | - Lee J. Byrne
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, United Kingdom
| | - Cornelia M. Wilson
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, United Kingdom
| | - Naeem H. Syed
- School of Human and Life Sciences, Canterbury Christ Church University, Canterbury, United Kingdom
- *Correspondence: Naeem H. Syed,
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73
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SubCellBarCode: Proteome-wide Mapping of Protein Localization and Relocalization. Mol Cell 2019; 73:166-182.e7. [DOI: 10.1016/j.molcel.2018.11.035] [Citation(s) in RCA: 120] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2018] [Revised: 09/28/2018] [Accepted: 11/27/2018] [Indexed: 11/22/2022]
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74
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Translation of Small Open Reading Frames: Roles in Regulation and Evolutionary Innovation. Trends Genet 2018; 35:186-198. [PMID: 30606460 DOI: 10.1016/j.tig.2018.12.003] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Accepted: 12/07/2018] [Indexed: 01/01/2023]
Abstract
The translatome can be defined as the sum of the RNA sequences that are translated into proteins in the cell by the ribosomal machinery. Until recently, it was generally assumed that the translatome was essentially restricted to evolutionary conserved proteins encoded by the set of annotated protein-coding genes. However, it has become increasingly clear that it also includes small regulatory open reading frames (ORFs), functional micropeptides, de novo proteins, and the pervasive translation of likely nonfunctional proteins. Many of these ORFs have been discovered thanks to the development of ribosome profiling, a technique to sequence ribosome-protected RNA fragments. To fully capture the diversity of translated ORFs, we propose a comprehensive classification that includes the new types of translated ORFs in addition to standard proteins.
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75
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Seimetz J, Arif W, Bangru S, Hernaez M, Kalsotra A. Cell-type specific polysome profiling from mammalian tissues. Methods 2018; 155:131-139. [PMID: 30500367 DOI: 10.1016/j.ymeth.2018.11.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 10/29/2018] [Accepted: 11/26/2018] [Indexed: 12/21/2022] Open
Abstract
The regulation of gene expression occurs through complex relationships between transcription, processing, turnover, and translation, which are only beginning to be elucidated. We know that at least for certain messenger (m) RNAs, processing, modifications, and sequence elements can greatly influence their translational output through recognition by translation and turn-over machinery. Recently, we and others have combined high-throughput sequencing technologies with traditional biochemical methods of studying translation to extend our understanding of these relationships. Additionally, there is growing importance given to how these processes may be regulated across varied cell types as a means to achieve tissue-specific expression of proteins. Here, we provide an in-depth methodology for polysome profiling to dissect the composition of mRNAs and proteins that make up the translatome from both whole tissues and a specific cell type isolated from mammalian tissue. Also, we provide a detailed computational workflow for the analysis of the next-generation sequencing data generated from these experiments.
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Affiliation(s)
- Joseph Seimetz
- Department of Biochemistry, University of Illinois, Urbana-Champaign, IL, USA
| | - Waqar Arif
- Department of Biochemistry, University of Illinois, Urbana-Champaign, IL, USA
| | - Sushant Bangru
- Department of Biochemistry, University of Illinois, Urbana-Champaign, IL, USA
| | - Mikel Hernaez
- Carl R. Woese Institute for Genomic Biology, University of Illinois, Urbana-Champaign, IL, USA
| | - Auinash Kalsotra
- Department of Biochemistry, University of Illinois, Urbana-Champaign, IL, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois, Urbana-Champaign, IL, USA; Cancer Center@ Illinois, University of Illinois, Urbana-Champaign, IL, USA.
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76
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Sterne-Weiler T, Weatheritt RJ, Best AJ, Ha KC, Blencowe BJ. Efficient and Accurate Quantitative Profiling of Alternative Splicing Patterns of Any Complexity on a Laptop. Mol Cell 2018; 72:187-200.e6. [DOI: 10.1016/j.molcel.2018.08.018] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Revised: 06/24/2018] [Accepted: 08/09/2018] [Indexed: 01/08/2023]
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77
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El Marabti E, Younis I. The Cancer Spliceome: Reprograming of Alternative Splicing in Cancer. Front Mol Biosci 2018; 5:80. [PMID: 30246013 PMCID: PMC6137424 DOI: 10.3389/fmolb.2018.00080] [Citation(s) in RCA: 152] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Accepted: 08/09/2018] [Indexed: 12/15/2022] Open
Abstract
Alternative splicing allows for the expression of multiple RNA and protein isoforms from one gene, making it a major contributor to transcriptome and proteome diversification in eukaryotes. Advances in next generation sequencing technologies and genome-wide analyses have recently underscored the fact that the vast majority of multi-exon genes under normal physiology engage in alternative splicing in tissue-specific and developmental-specific manner. On the other hand, cancer cells exhibit remarkable transcriptome alterations partly by adopting cancer-specific splicing isoforms. These isoforms and their encoded proteins are not insignificant byproducts of the abnormal physiology of cancer cells, but either drivers of cancer progression or small but significant contributors to specific cancer hallmarks. Thus, it is paramount that the pathways that regulate alternative splicing in cancer, including the splicing factors that bind to pre-mRNAs and modulate spliceosome recruitment. In this review, we present a few distinct cases of alternative splicing in cancer, with an emphasis on their regulation as well as their contribution to cancer cell phenotype. Several categories of splicing aberrations are highlighted, including alterations in cancer-related genes that directly affect their pre-mRNA splicing, mutations in genes encoding splicing factors or core spliceosomal subunits, and the seemingly mutation-free disruptions in the balance of the expression of RNA-binding proteins, including components of both the major (U2-dependent) and minor (U12-dependent) spliceosomes. Given that the latter two classes cause global alterations in splicing that affect a wide range of genes, it remains a challenge to identify the ones that contribute to cancer progression. These challenges necessitate a systematic approach to decipher these aberrations and their impact on cancer. Ultimately, a sufficient understanding of splicing deregulation in cancer is predicted to pave the way for novel and innovative RNA-based therapies.
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Affiliation(s)
- Ettaib El Marabti
- Biological Sciences Program, Carnegie Mellon University in Qatar, Doha, Qatar
| | - Ihab Younis
- Biological Sciences Program, Carnegie Mellon University in Qatar, Doha, Qatar
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78
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Lin P, He RQ, Ma FC, Liang L, He Y, Yang H, Dang YW, Chen G. Systematic Analysis of Survival-Associated Alternative Splicing Signatures in Gastrointestinal Pan-Adenocarcinomas. EBioMedicine 2018; 34:46-60. [PMID: 30131306 PMCID: PMC6116578 DOI: 10.1016/j.ebiom.2018.07.040] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 07/29/2018] [Accepted: 07/31/2018] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Gastrointestinal pan-adenocarcinomas, which mainly include adenocarcinomas of the esophagus, stomach, colon, and rectum, place a heavy burden on society owing to their poor prognoses. Since aberrant alternative splicing (AS) are starting to be considered as efficacious signatures for tumor prognosis predicting and therapeutic targets, systematic analysis of AS events is urgent. METHODS Prognosis-related AS events were selected by using univariate COX regression analysis. Gene functional enrichment analysis revealed the pathways enriched by prognosis-related AS. Then, prognostic signatures based on AS events were developed for prognosis prediction. Potential mechanism to regulate splicing events by splicing factors was analyzed via Pearson correlation and regulatory networks were constructed. FINDINGS A total of 967, 918, 674, and 406 AS events were identified as prognosis-related AS events in esophagus, stomach, colon, and rectum adenocarcinomas, respectively. Survival-associated AS events were distinguishing in the four subtypes of adenocarcinoma. Furthermore, computational algorithm results indicated that perturbation of ribosome and ubiquitin-mediated proteolysis pathways were the potential molecular mechanisms corresponding to inferior prognoses. Most notably, several prognostic signatures based on AS events displayed moderate performance in prognosis predicting. The area under curve values of the time-dependent receiver operating characteristic were 0.961, 0.871, 0.870, and 0.890 in esophagus, stomach, colon, and rectum adenocarcinomas. Survival-associated splicing factors were submitted to construct the AS regulatory network, which could be an underlying mechanism of AS events. INTERPRETATION AS may could be ideal indiactors in the prognosis of gastrointestinal pan-adenocarcinomas. Exploring interesting splicing regulatory networks is conducive to solve the puzzles of AS.
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Affiliation(s)
- Peng Lin
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China
| | - Rong-Quan He
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China
| | - Fu-Chao Ma
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China
| | - Liang Liang
- Department of General Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China
| | - Yun He
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China
| | - Hong Yang
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China
| | - Yi-Wu Dang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China
| | - Gang Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, PR China.
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79
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Grantham ME, Brisson JA. Extensive Differential Splicing Underlies Phenotypically Plastic Aphid Morphs. Mol Biol Evol 2018; 35:1934-1946. [PMID: 29722880 PMCID: PMC6063273 DOI: 10.1093/molbev/msy095] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Phenotypic plasticity results in a diversity of phenotypes from a single genotype in response to environmental cues. To understand the molecular basis of phenotypic plasticity, studies have focused on differential gene expression levels between environmentally determined phenotypes. The extent of alternative splicing differences among environmentally determined phenotypes has largely been understudied. Here, we study alternative splicing differences among plastically produced morphs of the pea aphid using RNA-sequence data. Pea aphids express two separate polyphenisms (plasticity with discrete phenotypes): a wing polyphenism consisting of winged and wingless females and a reproduction polyphenism consisting of asexual and sexual females. We find that pea aphids alternatively splice 34% of their genes, a high percentage for invertebrates. We also find that there is extensive use of differential spliced events between genetically identical, polyphenic females. These differentially spliced events are enriched for exon skipping and mutually exclusive exon events that maintain the open reading frame, suggesting that polyphenic morphs use alternative splicing to produce phenotype-biased proteins. Many genes that are differentially spliced between polyphenic morphs have putative functions associated with their respective phenotypes. We find that the majority of differentially spliced genes is not differentially expressed genes. Our results provide a rich candidate gene list for future functional studies that would not have been previously considered based solely on gene expression studies, such as ensconsin in the reproductive polyphenism, and CAKI in the wing polyphenism. Overall, this study suggests an important role for alternative splicing in the expression of environmentally determined phenotypes.
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Affiliation(s)
- Mary E Grantham
- Department of Biology, University of Rochester, Rochester, NY
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80
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Chen Y, Zheng Y, Gao Y, Lin Z, Yang S, Wang T, Wang Q, Xie N, Hua R, Liu M, Sha J, Griswold MD, Li J, Tang F, Tong MH. Single-cell RNA-seq uncovers dynamic processes and critical regulators in mouse spermatogenesis. Cell Res 2018; 28:879-896. [PMID: 30061742 PMCID: PMC6123400 DOI: 10.1038/s41422-018-0074-y] [Citation(s) in RCA: 222] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 06/25/2018] [Accepted: 07/05/2018] [Indexed: 12/12/2022] Open
Abstract
A systematic interrogation of male germ cells is key to complete understanding of molecular mechanisms governing spermatogenesis and the development of new strategies for infertility therapies and male contraception. Here we develop an approach to purify all types of homogeneous spermatogenic cells by combining transgenic labeling and synchronization of the cycle of the seminiferous epithelium, and subsequent single-cell RNA-sequencing. We reveal extensive and previously uncharacterized dynamic processes and molecular signatures in gene expression, as well as specific patterns of alternative splicing, and novel regulators for specific stages of male germ cell development. Our transcriptomics analyses led us to discover discriminative markers for isolating round spermatids at specific stages, and different embryo developmental potentials between early and late stage spermatids, providing evidence that maturation of round spermatids impacts on embryo development. This work provides valuable insights into mammalian spermatogenesis, and a comprehensive resource for future studies towards the complete elucidation of gametogenesis.
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Affiliation(s)
- Yao Chen
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuxuan Zheng
- Beijing Advanced Innovation Center for Genomics, Biomedical Institute for Pioneering Investigation via Convergence, College of Life Sciences, Peking University, Beijing, 100871, China.,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, 100871, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Yun Gao
- Beijing Advanced Innovation Center for Genomics, Biomedical Institute for Pioneering Investigation via Convergence, College of Life Sciences, Peking University, Beijing, 100871, China.,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, 100871, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Zhen Lin
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Suming Yang
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Tongtong Wang
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Qiu Wang
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Nannan Xie
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Rong Hua
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Mingxi Liu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Jiahao Sha
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Michael D Griswold
- School of Molecular Biosciences and the Center for Reproductive Biology, Washington State University, Pullman, WA, USA
| | - Jinsong Li
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Fuchou Tang
- Beijing Advanced Innovation Center for Genomics, Biomedical Institute for Pioneering Investigation via Convergence, College of Life Sciences, Peking University, Beijing, 100871, China. .,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, 100871, China. .,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
| | - Ming-Han Tong
- State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
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81
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Furlanis E, Scheiffele P. Regulation of Neuronal Differentiation, Function, and Plasticity by Alternative Splicing. Annu Rev Cell Dev Biol 2018; 34:451-469. [PMID: 30028642 DOI: 10.1146/annurev-cellbio-100617-062826] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Posttranscriptional mechanisms provide powerful means to expand the coding power of genomes. In nervous systems, alternative splicing has emerged as a fundamental mechanism not only for the diversification of protein isoforms but also for the spatiotemporal control of transcripts. Thus, alternative splicing programs play instructive roles in the development of neuronal cell type-specific properties, neuronal growth, self-recognition, synapse specification, and neuronal network function. Here we discuss the most recent genome-wide efforts on mapping RNA codes and RNA-binding proteins for neuronal alternative splicing regulation. We illustrate how alternative splicing shapes key steps of neuronal development, neuronal maturation, and synaptic properties. Finally, we highlight efforts to dissect the spatiotemporal dynamics of alternative splicing and their potential contribution to neuronal plasticity and the mature nervous system.
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82
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Abstract
Single-cell analyses have revealed a tremendous variety among cells in the abundance and chemical composition of RNA. Much of this heterogeneity is due to alternative splicing by the spliceosome. Little is known about how many of the resulting isoforms are biologically functional or just provide noise with little to no impact. The dynamic nature of the spliceosome provides numerous opportunities for regulation but is also the source of stochastic fluctuations. We discuss possible origins of splicing stochasticity, the experimental approaches for studying heterogeneity in isoforms, and the potential biological significance of noisy splicing in development and disease.
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Affiliation(s)
- Yihan Wan
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Daniel R Larson
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892, USA.
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83
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Splicing dysfunction and disease: The case of granulopoiesis. Semin Cell Dev Biol 2018; 75:23-39. [DOI: 10.1016/j.semcdb.2017.08.048] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Revised: 08/28/2017] [Accepted: 08/28/2017] [Indexed: 12/20/2022]
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84
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Vanichkina DP, Schmitz U, Wong JJL, Rasko JE. Challenges in defining the role of intron retention in normal biology and disease. Semin Cell Dev Biol 2018; 75:40-49. [DOI: 10.1016/j.semcdb.2017.07.030] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 07/19/2017] [Accepted: 07/19/2017] [Indexed: 10/19/2022]
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85
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Tardaguila M, de la Fuente L, Marti C, Pereira C, Pardo-Palacios FJ, Del Risco H, Ferrell M, Mellado M, Macchietto M, Verheggen K, Edelmann M, Ezkurdia I, Vazquez J, Tress M, Mortazavi A, Martens L, Rodriguez-Navarro S, Moreno-Manzano V, Conesa A. SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification. Genome Res 2018; 28:396-411. [PMID: 29440222 PMCID: PMC5848618 DOI: 10.1101/gr.222976.117] [Citation(s) in RCA: 224] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 01/08/2018] [Indexed: 01/15/2023]
Abstract
High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, resulting more frequently in novel ORFs than novel UTRs, and are enriched in both general metabolic and neural-specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read-based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases, we find that alternative isoforms are elusive to proteogenomics detection. SQANTI allows the user to maximize the analytical outcome of long-read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes.
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Affiliation(s)
- Manuel Tardaguila
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, Genetics Institute, University of Florida, Gainesville, Florida 32611, USA
| | - Lorena de la Fuente
- Genomics of Gene Expression Laboratory, Centro de Investigaciones Principe Felipe (CIPF), 46012 Valencia, Spain
| | - Cristina Marti
- Genomics of Gene Expression Laboratory, Centro de Investigaciones Principe Felipe (CIPF), 46012 Valencia, Spain
| | - Cécile Pereira
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, Genetics Institute, University of Florida, Gainesville, Florida 32611, USA
| | | | - Hector Del Risco
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, Genetics Institute, University of Florida, Gainesville, Florida 32611, USA
| | - Marc Ferrell
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, Genetics Institute, University of Florida, Gainesville, Florida 32611, USA
| | | | - Marissa Macchietto
- Department of Developmental and Cell Biology, University of California, Irvine, California 92617, USA
| | - Kenneth Verheggen
- VIB-UGent Center for Medical Biotechnology, VIB, B-9000 Ghent, Belgium
- Department of Biochemistry, Ghent University, B-9000 Ghent, Belgium
| | - Mariola Edelmann
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, Genetics Institute, University of Florida, Gainesville, Florida 32611, USA
| | - Iakes Ezkurdia
- Centro Nacional de Investigaciones Cardiovasculares CNIC, 28029 Madrid, Spain
| | - Jesus Vazquez
- Centro Nacional de Investigaciones Cardiovasculares CNIC, 28029 Madrid, Spain
| | - Michael Tress
- Spanish National Cancer Research Centre (CNIO), 28029 Madrid, Spain
| | - Ali Mortazavi
- Department of Developmental and Cell Biology, University of California, Irvine, California 92617, USA
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, B-9000 Ghent, Belgium
- Department of Biochemistry, Ghent University, B-9000 Ghent, Belgium
| | - Susana Rodriguez-Navarro
- Gene Expression and mRNA Metabolism Laboratory, CSIC, IBV, 46010 Valencia, Spain
- Gene Expression and mRNA Metabolism Laboratory, CIPF, 46012 Valencia, Spain
| | | | - Ana Conesa
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, Genetics Institute, University of Florida, Gainesville, Florida 32611, USA
- Genomics of Gene Expression Laboratory, Centro de Investigaciones Principe Felipe (CIPF), 46012 Valencia, Spain
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86
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Reyes A, Huber W. Alternative start and termination sites of transcription drive most transcript isoform differences across human tissues. Nucleic Acids Res 2018; 46:582-592. [PMID: 29202200 PMCID: PMC5778607 DOI: 10.1093/nar/gkx1165] [Citation(s) in RCA: 153] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Revised: 10/28/2017] [Accepted: 11/07/2017] [Indexed: 11/23/2022] Open
Abstract
Most human genes generate multiple transcript isoforms. The differential expression of these isoforms can help specify cell types. Diverse transcript isoforms arise from the use of alternative transcription start sites, polyadenylation sites and splice sites; however, the relative contribution of these processes to isoform diversity in normal human physiology is unclear. To address this question, we investigated cell type-dependent differences in exon usage of over 18 000 protein-coding genes in 23 cell types from 798 samples of the Genotype-Tissue Expression Project. We found that about half of the expressed genes displayed tissue-dependent transcript isoforms. Alternative transcription start and termination sites, rather than alternative splicing, accounted for the majority of tissue-dependent exon usage. We confirmed the widespread tissue-dependent use of alternative transcription start sites in a second, independent dataset, Cap Analysis of Gene Expression data from the FANTOM consortium. Moreover, our results indicate that most tissue-dependent splicing involves untranslated exons and therefore may not increase proteome complexity. Thus, alternative transcription start and termination sites are the principal drivers of transcript isoform diversity across tissues, and may underlie the majority of cell type specific proteomes and functions.
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Affiliation(s)
- Alejandro Reyes
- European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA
| | - Wolfgang Huber
- European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
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87
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Signaling Pathways Driving Aberrant Splicing in Cancer Cells. Genes (Basel) 2017; 9:genes9010009. [PMID: 29286307 PMCID: PMC5793162 DOI: 10.3390/genes9010009] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 12/07/2017] [Accepted: 12/18/2017] [Indexed: 12/17/2022] Open
Abstract
Aberrant profiles of pre-mRNA splicing are frequently observed in cancer. At the molecular level, an altered profile results from a complex interplay between chromatin modifications, the transcriptional elongation rate of RNA polymerase, and effective binding of the spliceosome to the generated transcripts. Key players in this interplay are regulatory splicing factors (SFs) that bind to gene-specific splice-regulatory sequence elements. Although mutations in genes of some SFs were described, a major driver of aberrant splicing profiles is oncogenic signal transduction pathways. Signaling can affect either the transcriptional expression levels of SFs or the post-translational modification of SF proteins, and both modulate the ratio of nuclear versus cytoplasmic SFs in a given cell. Here, we will review currently known mechanisms by which cancer cell signaling, including the mitogen-activated protein kinases (MAPK), phosphatidylinositol 3 (PI3)-kinase pathway (PI3K) and wingless (Wnt) pathways but also signals from the tumor microenvironment, modulate the activity or subcellular localization of the Ser/Arg rich (SR) proteins and heterogeneous nuclear ribonucleoproteins (hnRNPs) families of SFs.
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88
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Hatje K, Rahman RU, Vidal RO, Simm D, Hammesfahr B, Bansal V, Rajput A, Mickael ME, Sun T, Bonn S, Kollmar M. The landscape of human mutually exclusive splicing. Mol Syst Biol 2017; 13:959. [PMID: 29242366 PMCID: PMC5740500 DOI: 10.15252/msb.20177728] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Mutually exclusive splicing of exons is a mechanism of functional gene and protein diversification with pivotal roles in organismal development and diseases such as Timothy syndrome, cardiomyopathy and cancer in humans. In order to obtain a first genomewide estimate of the extent and biological role of mutually exclusive splicing in humans, we predicted and subsequently validated mutually exclusive exons (MXEs) using 515 publically available RNA‐Seq datasets. Here, we provide evidence for the expression of over 855 MXEs, 42% of which represent novel exons, increasing the annotated human mutually exclusive exome more than fivefold. The data provide strong evidence for the existence of large and multi‐cluster MXEs in higher vertebrates and offer new insights into MXE evolution. More than 82% of the MXE clusters are conserved in mammals, and five clusters have homologous clusters in Drosophila. Finally, MXEs are significantly enriched in pathogenic mutations and their spatio‐temporal expression might predict human disease pathology.
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Affiliation(s)
- Klas Hatje
- Group Systems Biology of Motor Proteins Department of NMR-Based Structural Biology Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany.,Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany
| | - Raza-Ur Rahman
- Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany.,Center for Molecular Neurobiology, Institute of Medical Systems Biology University Clinic Hamburg-Eppendorf, Hamburg, Germany
| | - Ramon O Vidal
- Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany
| | - Dominic Simm
- Group Systems Biology of Motor Proteins Department of NMR-Based Structural Biology Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany.,Theoretical Computer Science and Algorithmic Methods, Institute of Computer Science Georg-August-University, Göttingen, Germany
| | - Björn Hammesfahr
- Group Systems Biology of Motor Proteins Department of NMR-Based Structural Biology Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany
| | - Vikas Bansal
- Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany.,Center for Molecular Neurobiology, Institute of Medical Systems Biology University Clinic Hamburg-Eppendorf, Hamburg, Germany
| | - Ashish Rajput
- Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany.,Center for Molecular Neurobiology, Institute of Medical Systems Biology University Clinic Hamburg-Eppendorf, Hamburg, Germany
| | - Michel Edwar Mickael
- Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany.,Center for Molecular Neurobiology, Institute of Medical Systems Biology University Clinic Hamburg-Eppendorf, Hamburg, Germany
| | - Ting Sun
- Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany.,Center for Molecular Neurobiology, Institute of Medical Systems Biology University Clinic Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan Bonn
- Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany .,Center for Molecular Neurobiology, Institute of Medical Systems Biology University Clinic Hamburg-Eppendorf, Hamburg, Germany.,German Center for Neurodegenerative Diseases, Tübingen, Germany
| | - Martin Kollmar
- Group Systems Biology of Motor Proteins Department of NMR-Based Structural Biology Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany
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89
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Wang X, Codreanu SG, Wen B, Li K, Chambers MC, Liebler DC, Zhang B. Detection of Proteome Diversity Resulted from Alternative Splicing is Limited by Trypsin Cleavage Specificity. Mol Cell Proteomics 2017; 17:422-430. [PMID: 29222161 PMCID: PMC5836368 DOI: 10.1074/mcp.ra117.000155] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Revised: 11/05/2017] [Indexed: 12/11/2022] Open
Abstract
Alternative splicing dramatically increases transcriptome complexity but its contribution to proteome diversity remains controversial. Exon-exon junction spanning peptides provide direct evidence for the translation of specific splice isoforms and are critical for delineating protein isoform complexity. Here we found that junction-spanning peptides are underrepresented in publicly available mass spectrometry-based shotgun proteomics data sets. Further analysis showed that evolutionarily conserved preferential nucleotide usage at exon boundaries increases the occurrence of lysine- and arginine-coding triplets at the end of exons. Because both lysine and arginine residues are cleavage sites of trypsin, the nearly exclusive use of trypsin as the protein digestion enzyme in shotgun proteomic analyses hinders the detection of junction-spanning peptides. To study the impact of enzyme selection on splice junction detectability, we performed in-silico digestion of the human proteome using six proteases. The six enzymes created a total of 161,125 detectable junctions, and only 1,029 were common across all enzyme digestions. Chymotrypsin digestion provided the largest number of detectable junctions. Our experimental results further showed that combination of a chymotrypsin-based human proteome analysis with a trypsin-based analysis increased detection of junction-spanning peptides by 37% over the trypsin-only analysis and identified over a thousand junctions that were undetectable in fully tryptic digests. Our study demonstrates that detection of proteome diversity resulted from alternative splicing is limited by trypsin cleavage specificity, and that complementary digestion schemes will be essential to comprehensively analyze the translation of alternative splicing isoforms.
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Affiliation(s)
- Xiaojing Wang
- From the ‡Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas 77030.,§Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030
| | - Simona G Codreanu
- ¶Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee 37232
| | - Bo Wen
- From the ‡Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas 77030.,§Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030
| | - Kai Li
- ‖BGI-Shenzhen, Shenzhen, Guangdong 518083, China
| | - Matthew C Chambers
- ¶Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee 37232
| | - Daniel C Liebler
- ¶Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee 37232.,**Jim Ayers Institute for Precancer Detection and Diagnosis, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee 37232
| | - Bing Zhang
- From the ‡Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas 77030; .,§Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030
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90
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Bush SJ, Chen L, Tovar-Corona JM, Urrutia AO. Alternative splicing and the evolution of phenotypic novelty. Philos Trans R Soc Lond B Biol Sci 2017; 372:rstb.2015.0474. [PMID: 27994117 DOI: 10.1098/rstb.2015.0474] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/01/2016] [Indexed: 12/21/2022] Open
Abstract
Alternative splicing, a mechanism of post-transcriptional RNA processing whereby a single gene can encode multiple distinct transcripts, has been proposed to underlie morphological innovations in multicellular organisms. Genes with developmental functions are enriched for alternative splicing events, suggestive of a contribution of alternative splicing to developmental programmes. The role of alternative splicing as a source of transcript diversification has previously been compared to that of gene duplication, with the relationship between the two extensively explored. Alternative splicing is reduced following gene duplication with the retention of duplicate copies higher for genes which were alternatively spliced prior to duplication. Furthermore, and unlike the case for overall gene number, the proportion of alternatively spliced genes has also increased in line with the evolutionary diversification of cell types, suggesting alternative splicing may contribute to the complexity of developmental programmes. Together these observations suggest a prominent role for alternative splicing as a source of functional innovation. However, it is unknown whether the proliferation of alternative splicing events indeed reflects a functional expansion of the transcriptome or instead results from weaker selection acting on larger species, which tend to have a higher number of cell types and lower population sizes.This article is part of the themed issue 'Evo-devo in the genomics era, and the origins of morphological diversity'.
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Affiliation(s)
- Stephen J Bush
- The Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Lu Chen
- West China Second University Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610041, People's Republic of China
| | | | - Araxi O Urrutia
- Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, UK .,Milner Centre for Evolution, University of Bath, Bath BA2 7AY, UK
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91
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Auboeuf D. Alternative mRNA processing sites decrease genetic variability while increasing functional diversity. Transcription 2017; 9:75-87. [PMID: 29099315 PMCID: PMC5834221 DOI: 10.1080/21541264.2017.1373891] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
Recent large-scale RNA sequencing efforts have revealed the extensive diversity of mRNA molecules produced from most eukaryotic coding genes, which arises from the usage of alternative, cryptic or non-canonical splicing and intronic polyadenylation sites. The prevailing view regarding the tremendous diversity of coding gene transcripts is that mRNA processing is a flexible and more-or-less noisy process leading to a diversity of proteins on which natural selection can act depending on protein-mediated cellular functions. However, this concept raises two main questions. First, do alternative mRNA processing pathways have a role other than generating mRNA and protein diversity? Second, is the cellular function of mRNA variants restricted to the biogenesis of functional protein isoforms? Here, I propose that the co-transcriptional use of alternative mRNA processing sites allows first, the resolution of co-transcriptional biophysical constraints that may otherwise result in DNA instability, and second, increases the diversity of cellular functions of mRNAs in a manner that is not restricted to protein synthesis.
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Affiliation(s)
- Didier Auboeuf
- a Univ Lyon, ENS de Lyon, Univ Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell , 46 Allée d'Italie Site Jacques Monod, Lyon , France
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92
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Babenko VN, Bragin AO, Chadaeva IV, Markel AL, Orlov YL. Differential alternative splicing in brain regions of rats selected for aggressive behavior. Mol Biol 2017. [DOI: 10.1134/s002689331705003x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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93
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Alternative Splicing in Genetic Diseases: Improved Diagnosis and Novel Treatment Options. INTERNATIONAL REVIEW OF CELL AND MOLECULAR BIOLOGY 2017; 335:85-141. [PMID: 29305015 DOI: 10.1016/bs.ircmb.2017.07.008] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Alternative splicing is an important mechanism to regulate gene expression and to expand the repertoire of gene products in order to accommodate an increase in complexity of multicellular organisms. It needs to be precisely regulated, which is achieved via RNA structure, splicing factors, transcriptional regulation, and chromatin. Changes in any of these factors can lead to disease. These may include the core spliceosome, splicing enhancer/repressor sequences and their interacting proteins, the speed of transcription by RNA polymerase II, and histone modifications. While the basic principle of splicing is well understood, it is still very difficult to predict splicing outcome, due to the multiple levels of regulation. Current molecular diagnostics mainly uses Sanger sequencing of exons, or next-generation sequencing of gene panels or the whole exome. Functional analysis of potential splicing variants is scarce, and intronic variants are often not considered. This likely results in underestimation of the percentage of splicing variants. Understanding how sequence variants may affect splicing is not only crucial for confirmation of diagnosis and for genetic counseling, but also for the development of novel treatment options. These include small molecules, transsplicing, antisense oligonucleotides, and gene therapy. Here we review the current state of molecular mechanisms of splicing regulation and how deregulation can lead to human disease, diagnostics to detect splicing variants, and novel treatment options based on splicing correction.
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94
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Beyond Read-Counts: Ribo-seq Data Analysis to Understand the Functions of the Transcriptome. Trends Genet 2017; 33:728-744. [PMID: 28887026 DOI: 10.1016/j.tig.2017.08.003] [Citation(s) in RCA: 79] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 08/03/2017] [Accepted: 08/04/2017] [Indexed: 01/16/2023]
Abstract
By mapping the positions of millions of translating ribosomes in the cell, ribosome profiling (Ribo-seq) has established its role as a powerful tool to study gene expression. Several laboratories have introduced modifications to the experimental protocol and expanded the repertoire of biochemical methods to study translation transcriptome-wide. However, the diversity of protocols highlights a need for standardization. At the same time, different computational analysis strategies have used Ribo-seq data to identify the set of translated sequences with high confidence. In this review we present an overview of such methodologies, outlining their assumptions, data requirements, and availability. At the interface between RNA and proteins, Ribo-seq can complement data from multiple omics approaches, zooming in on the central role of translation in the molecular cell.
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95
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Tapial J, Ha KCH, Sterne-Weiler T, Gohr A, Braunschweig U, Hermoso-Pulido A, Quesnel-Vallières M, Permanyer J, Sodaei R, Marquez Y, Cozzuto L, Wang X, Gómez-Velázquez M, Rayon T, Manzanares M, Ponomarenko J, Blencowe BJ, Irimia M. An atlas of alternative splicing profiles and functional associations reveals new regulatory programs and genes that simultaneously express multiple major isoforms. Genome Res 2017; 27:1759-1768. [PMID: 28855263 PMCID: PMC5630039 DOI: 10.1101/gr.220962.117] [Citation(s) in RCA: 245] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Accepted: 08/09/2017] [Indexed: 12/29/2022]
Abstract
Alternative splicing (AS) generates remarkable regulatory and proteomic complexity in metazoans. However, the functions of most AS events are not known, and programs of regulated splicing remain to be identified. To address these challenges, we describe the Vertebrate Alternative Splicing and Transcription Database (VastDB), the largest resource of genome-wide, quantitative profiles of AS events assembled to date. VastDB provides readily accessible quantitative information on the inclusion levels and functional associations of AS events detected in RNA-seq data from diverse vertebrate cell and tissue types, as well as developmental stages. The VastDB profiles reveal extensive new intergenic and intragenic regulatory relationships among different classes of AS and previously unknown and conserved landscapes of tissue-regulated exons. Contrary to recent reports concluding that nearly all human genes express a single major isoform, VastDB provides evidence that at least 48% of multiexonic protein-coding genes express multiple splice variants that are highly regulated in a cell/tissue-specific manner, and that >18% of genes simultaneously express multiple major isoforms across diverse cell and tissue types. Isoforms encoded by the latter set of genes are generally coexpressed in the same cells and are often engaged by translating ribosomes. Moreover, they are encoded by genes that are significantly enriched in functions associated with transcriptional control, implying they may have an important and wide-ranging role in controlling cellular activities. VastDB thus provides an unprecedented resource for investigations of AS function and regulation.
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Affiliation(s)
- Javier Tapial
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | - Kevin C H Ha
- Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | | | - André Gohr
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | | | - Antonio Hermoso-Pulido
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | - Mathieu Quesnel-Vallières
- Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | - Jon Permanyer
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | - Reza Sodaei
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | - Yamile Marquez
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | - Luca Cozzuto
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | - Xinchen Wang
- Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | - Melisa Gómez-Velázquez
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), 28029 Madrid, Spain
| | - Teresa Rayon
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), 28029 Madrid, Spain
| | - Miguel Manzanares
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), 28029 Madrid, Spain
| | - Julia Ponomarenko
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | | | - Manuel Irimia
- EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
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96
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Liu Y, Gonzàlez-Porta M, Santos S, Brazma A, Marioni JC, Aebersold R, Venkitaraman AR, Wickramasinghe VO. Impact of Alternative Splicing on the Human Proteome. Cell Rep 2017; 20:1229-1241. [PMID: 28768205 PMCID: PMC5554779 DOI: 10.1016/j.celrep.2017.07.025] [Citation(s) in RCA: 113] [Impact Index Per Article: 16.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Revised: 06/02/2017] [Accepted: 07/12/2017] [Indexed: 02/02/2023] Open
Abstract
Alternative splicing is a critical determinant of genome complexity and, by implication, is assumed to engender proteomic diversity. This notion has not been experimentally tested in a targeted, quantitative manner. Here, we have developed an integrative approach to ask whether perturbations in mRNA splicing patterns alter the composition of the proteome. We integrate RNA sequencing (RNA-seq) (to comprehensively report intron retention, differential transcript usage, and gene expression) with a data-independent acquisition (DIA) method, SWATH-MS (sequential window acquisition of all theoretical spectra-mass spectrometry), to capture an unbiased, quantitative snapshot of the impact of constitutive and alternative splicing events on the proteome. Whereas intron retention is accompanied by decreased protein abundance, alterations in differential transcript usage and gene expression alter protein abundance proportionate to transcript levels. Our findings illustrate how RNA splicing links isoform expression in the human transcriptome with proteomic diversity and provides a foundation for studying perturbations associated with human diseases.
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Affiliation(s)
- Yansheng Liu
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Mar Gonzàlez-Porta
- European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Sergio Santos
- European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Alvis Brazma
- European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - John C Marioni
- European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
| | - Ashok R Venkitaraman
- The Medical Research Council Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK.
| | - Vihandha O Wickramasinghe
- The Medical Research Council Cancer Unit, University of Cambridge, Cambridge CB2 0XZ, UK; RNA Biology and Cancer Laboratory, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
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97
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Fesenko I, Khazigaleeva R, Kirov I, Kniazev A, Glushenko O, Babalyan K, Arapidi G, Shashkova T, Butenko I, Zgoda V, Anufrieva K, Seredina A, Filippova A, Govorun V. Alternative splicing shapes transcriptome but not proteome diversity in Physcomitrella patens. Sci Rep 2017; 7:2698. [PMID: 28578384 PMCID: PMC5457400 DOI: 10.1038/s41598-017-02970-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Accepted: 04/20/2017] [Indexed: 12/13/2022] Open
Abstract
Alternative splicing (AS) can significantly impact the transcriptome and proteome of a eukaryotic cell. Here, using transcriptome and proteome profiling data, we analyzed AS in two life forms of the model moss Physcomitrella patens, namely protonemata and gametophores, as well as in protoplasts. We identified 12 043 genes subject to alternative splicing and analyzed the extent to which AS contributes to proteome diversity. We could distinguish a few examples that unambiguously indicated the presence of two or more splice isoforms from the same locus at the proteomic level. Our results indicate that alternative isoforms have a small effect on proteome diversity. We also revealed that mRNAs and pre-mRNAs have thousands of complementary binding sites for long non-coding RNAs (lncRNAs) that may lead to potential interactions in transcriptome. This finding points to an additional level of gene expression and AS regulation by non-coding transcripts in Physcomitrella patens. Among the differentially expressed and spliced genes we found serine/arginine-rich (SR) genes, which are known to regulate AS in cells. We found that treatment with abscisic (ABA) and methyl jasmonic acids (MeJA) led to an isoform-specific response and suggested that ABA in gametophores and MeJA in protoplasts regulate AS and the transcription of SR genes.
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Affiliation(s)
- Igor Fesenko
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.
| | - Regina Khazigaleeva
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Ilya Kirov
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Russian State Agrarian University - Moscow Timiryazev Agricultural Academy, Moscow, Russia
| | - Andrey Kniazev
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Oksana Glushenko
- Laboratory of the Proteomic Analysis, Research Institute for Physico-Chemical Medicine, Moscow, Russia
| | - Konstantin Babalyan
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Georgij Arapidi
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Tatyana Shashkova
- Laboratory of the Proteomic Analysis, Research Institute for Physico-Chemical Medicine, Moscow, Russia
| | - Ivan Butenko
- Laboratory of the Proteomic Analysis, Research Institute for Physico-Chemical Medicine, Moscow, Russia
| | - Victor Zgoda
- Institute of Biomedical Chemistry, Moscow, Russian Federation
| | - Ksenia Anufrieva
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Anna Seredina
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Anna Filippova
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Vadim Govorun
- Laboratory of Proteomics, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Laboratory of the Proteomic Analysis, Research Institute for Physico-Chemical Medicine, Moscow, Russia
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98
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Blencowe BJ. The Relationship between Alternative Splicing and Proteomic Complexity. Trends Biochem Sci 2017; 42:407-408. [DOI: 10.1016/j.tibs.2017.04.001] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 04/03/2017] [Indexed: 01/22/2023]
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99
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Tress ML, Abascal F, Valencia A. Most Alternative Isoforms Are Not Functionally Important. Trends Biochem Sci 2017; 42:408-410. [PMID: 28483377 DOI: 10.1016/j.tibs.2017.04.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 04/03/2017] [Indexed: 12/11/2022]
Affiliation(s)
- Michael L Tress
- Department of Structural and Computational Biology, Spanish National Cancer Research Centre (CNIO), 28029 Madrid, Spain.
| | | | - Alfonso Valencia
- Current address: Life Sciences Department, Barcelona Supercomputing Center (BSC-CNS), 08034 Barcelona, Spain
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100
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Jacob AG, Smith CWJ. Intron retention as a component of regulated gene expression programs. Hum Genet 2017; 136:1043-1057. [PMID: 28391524 PMCID: PMC5602073 DOI: 10.1007/s00439-017-1791-x] [Citation(s) in RCA: 185] [Impact Index Per Article: 26.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2017] [Accepted: 03/29/2017] [Indexed: 12/16/2022]
Abstract
Intron retention has long been an exemplar of regulated splicing with case studies of individual events serving as models that provided key mechanistic insights into the process of splicing control. In organisms such as plants and budding yeast, intron retention is well understood as a major mechanism of gene expression regulation. In contrast, in mammalian systems, the extent and functional significance of intron retention have, until recently, remained greatly underappreciated. Technical challenges to the global detection and quantitation of transcripts with retained introns have often led to intron retention being overlooked or dismissed as “noise”. Now, however, with the wealth of information available from high-throughput deep sequencing, combined with focused computational and statistical analyses, we are able to distinguish clear intron retention patterns in various physiological and pathological contexts. Several recent studies have demonstrated intron retention as a central component of gene expression programs during normal development as well as in response to stress and disease. Furthermore, these studies revealed various ways in which intron retention regulates protein isoform production, RNA stability and translation efficiency, and rapid induction of expression via post-transcriptional splicing of retained introns. In this review, we highlight critical findings from these transcriptomic studies and discuss commonalties in the patterns prevalent in intron retention networks at the functional and regulatory levels.
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Affiliation(s)
- Aishwarya G Jacob
- Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QW, UK
| | - Christopher W J Smith
- Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QW, UK.
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