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TRAP-SEQ of Eukaryotic Translatomes Applied to the Detection of Polysome-Associated Long Noncoding RNAs

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RNA Tagging

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2166))

Abstract

Translating ribosome affinity purification (TRAP) technology allows the isolation of polysomal complexes and the RNAs associated with at least one 80S ribosome. TRAP consists of the stabilization and affinity purification of polysomes containing a tagged version of a ribosomal protein. Quantitative assessment of the TRAP RNA is achieved by direct sequencing (TRAP-SEQ), which provides accurate quantitation of ribosome-associated RNAs, including long noncoding RNAs (lncRNAs). Here we present an updated procedure for TRAP-SEQ, as well as a primary analysis guide for identification of ribosome-associated lncRNAs. This methodology enables the study of dynamic association of lncRNAs by assessing rapid changes in their transcript levels in polysomes at organ or cell-type level, during development, or in response to endogenous or exogenous stimuli.

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Acknowledgments

We thank Julia Bailey-Serres, Kaisa Kajala, and others that have contributed to improving the TRAP-SEQ technology. We also thank Claudio Rivero for discussion and advice on RNA-SEQ analysis. This work has been financially supported by grants from ANPCyT, Argentina, funded to M.E.Z. (PICT 2016-0582, PICT 2017-0581), F.A.B. (PICT 2016-0333), and M.A.R. (PICT 2017-2272). M.E.Z., F.A.B., and M.A.R. are members of CONICET. S.T. is a fellow of the same institution and has been awarded a Fulbright Scholarship.

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Correspondence to Mauricio A. Reynoso .

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Traubenik, S., Blanco, F., Zanetti, M.E., Reynoso, M.A. (2020). TRAP-SEQ of Eukaryotic Translatomes Applied to the Detection of Polysome-Associated Long Noncoding RNAs. In: Heinlein, M. (eds) RNA Tagging. Methods in Molecular Biology, vol 2166. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0712-1_26

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  • DOI: https://doi.org/10.1007/978-1-0716-0712-1_26

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  • Publisher Name: Humana, New York, NY

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  • Online ISBN: 978-1-0716-0712-1

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