System-wide analysis of RNA and protein subcellular localization dynamics.
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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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Acknowledgements: We thank C. De Matos Ferraz Franco of the MRC-Toxicology Proteomics Facility for collection of all MS data and D. Scadden for kindly providing the G3BP1–GFP expression plasmid, B. Fisher for kindly sharing equipment and M. Marti-Solano for assistance with the manuscript writing. We also thank the Advanced Light Imaging facility at the MRC Toxicology Unit and the Light Imaging Facility at the Human Technopole for their support in the acquisition of light microscopy data. E.V., T.S., R.M.L.Q., M.P. and M.E. are supported by Wellcome Trust, grant numbers 110170/Z/15/Z and 110071/Z/15/Z awarded to A.E.W. and K.S.L.; R.F.H, V.D. and M.M. are supported by the Medical Research Council, grant number 5TR00. L.M.B. is supported by EU Horizon 2020 programme INFRAIA project EPIC-XS (project 823839). O.M.C. was supported by a Wellcome Trust Mathematical Genomics and Medicine studentship funded by the Cambridge School of Clinical Medicine and by the Todd-Bird Junior Research Fellowship from New College, Oxford.
Funder: Mathematical Genomics and Medicine studentship funded by the Cambridge School of Clinical Medicine
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1548-7105
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Wellcome Trust (108467/Z/15/Z)
Wellcome Trust (110170/Z/15/Z)
Wellcome Trust (110071/Z/15/Z)
Biotechnology and Biological Sciences Research Council (BB/G024618/1)
Biotechnology and Biological Sciences Research Council (BB/H024247/1)
Biotechnology and Biological Sciences Research Council (BB/K00137X/1)
Biotechnology and Biological Sciences Research Council (BB/L018497/1)

