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Villanueva E, Smith T, Pizzinga M, Elzek M, Queiroz RML, Harvey RF, Breckels LM, Crook OM, Monti M, Dezi V, Willis AE, Lilley KS. System-wide analysis of RNA and protein subcellular localization dynamics. Nat Methods 2024; 21:60-71. [PMID: 38036857 PMCID: PMC10776395 DOI: 10.1038/s41592-023-02101-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 10/24/2023] [Indexed: 12/02/2023]
Abstract
Although the subcellular dynamics of RNA and proteins are key determinants of cell homeostasis, their characterization is still challenging. Here we present an integrative framework to simultaneously interrogate the dynamics of the transcriptome and proteome at subcellular resolution by combining two methods: localization of RNA (LoRNA) and a streamlined density-based localization of proteins by isotope tagging (dLOPIT) to map RNA and protein to organelles (nucleus, endoplasmic reticulum and mitochondria) and membraneless compartments (cytosol, nucleolus and cytosolic granules). Interrogating all RNA subcellular locations at once enables system-wide quantification of the proportional distribution of RNA. We obtain a cell-wide overview of localization dynamics for 31,839 transcripts and 5,314 proteins during the unfolded protein response, revealing that endoplasmic reticulum-localized transcripts are more efficiently recruited to cytosolic granules than cytosolic RNAs, and that the translation initiation factor eIF3d is key to sustaining cytoskeletal function. Overall, we provide the most comprehensive overview so far of RNA and protein subcellular localization dynamics.
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Affiliation(s)
- Eneko Villanueva
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Tom Smith
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
- MRC Toxicology Unit, University of Cambridge, Cambridge, UK
| | - Mariavittoria Pizzinga
- MRC Toxicology Unit, University of Cambridge, Cambridge, UK
- Structural Biology Research Centre, Human Technopole, Milan, Italy
| | - Mohamed Elzek
- MRC Toxicology Unit, University of Cambridge, Cambridge, UK
| | - Rayner M L Queiroz
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
| | | | - Lisa M Breckels
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Oliver M Crook
- Department of Statistics, University of Oxford, Oxford, UK
| | - Mie Monti
- MRC Toxicology Unit, University of Cambridge, Cambridge, UK
| | - Veronica Dezi
- MRC Toxicology Unit, University of Cambridge, Cambridge, UK
| | - Anne E Willis
- MRC Toxicology Unit, University of Cambridge, Cambridge, UK.
| | - Kathryn S Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.
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Cheng LC, Zheng D, Zhang Q, Guvenek A, Cheng H, Tian B. Alternative 3' UTRs play a widespread role in translation-independent mRNA association with the endoplasmic reticulum. Cell Rep 2021; 36:109407. [PMID: 34289366 PMCID: PMC8501909 DOI: 10.1016/j.celrep.2021.109407] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 05/17/2021] [Accepted: 06/23/2021] [Indexed: 12/28/2022] Open
Abstract
Transcripts encoding membrane and secreted proteins are known to associate with the endoplasmic reticulum (ER) through translation. Here, using cell fractionation, polysome profiling, and 3' end sequencing, we show that transcripts differ substantially in translation-independent ER association (TiERA). Genes in certain functional groups, such as cell signaling, tend to have significantly higher TiERA potentials than others, suggesting the importance of ER association for their mRNA metabolism, such as localized translation. The TiERA potential of a transcript is determined largely by size, sequence content, and RNA structures. Alternative polyadenylation (APA) isoforms can have distinct TiERA potentials because of changes in transcript features. The widespread 3' UTR lengthening in cell differentiation leads to greater transcript association with the ER, especially for genes that are capable of expressing very long 3' UTRs. Our data also indicate that TiERA is in dynamic competition with translation-dependent ER association, suggesting limited space on the ER for mRNA association.
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Affiliation(s)
- Larry C Cheng
- Program in Gene Expression and Regulation and Center for Systems and Computational Biology, The Wistar Institute, Philadelphia, PA 19104, USA; Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Newark, NJ 07103, USA; Graduate Program in Quantitative Biomedicine, School of Graduate Studies, Rutgers University, Piscataway, NJ 08854, USA
| | - Dinghai Zheng
- Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Newark, NJ 07103, USA
| | - Qiang Zhang
- 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 the Chinese Academy of Sciences, Shanghai 200031, China
| | - Aysegul Guvenek
- Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Newark, NJ 07103, USA; Rutgers School of Graduate Studies, Newark, NJ 07103, USA
| | - Hong Cheng
- 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 the Chinese Academy of Sciences, Shanghai 200031, China
| | - Bin Tian
- Program in Gene Expression and Regulation and Center for Systems and Computational Biology, The Wistar Institute, Philadelphia, PA 19104, USA; Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Newark, NJ 07103, USA; Graduate Program in Quantitative Biomedicine, School of Graduate Studies, Rutgers University, Piscataway, NJ 08854, USA; Rutgers School of Graduate Studies, Newark, NJ 07103, USA.
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