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MapToCleave: High-throughput profiling of microRNA biogenesis in living cells

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dc.contributor.author Kang, Wenjing
dc.contributor.author Fromm, Bastian
dc.contributor.author Houben, Anna J.
dc.contributor.author Høye, Eirik
dc.contributor.author Bezdan, Daniela
dc.contributor.author Arnan Ros, Carme
dc.contributor.author Thrane, Kim
dc.contributor.author Asp, Michaela
dc.contributor.author Johnson, Rory
dc.contributor.author Biryukova, Inna
dc.contributor.author Friedländer, Marc R.
dc.date.accessioned 2022-03-08T10:27:38Z
dc.date.available 2022-03-08T10:27:38Z
dc.date.issued 2021
dc.identifier.citation Kang W, Fromm B, Houben AJ, Høye E, Bezdan D, Arnan C et al. MapToCleave: High-throughput profiling of microRNA biogenesis in living cells. Cell Rep. 2021 Nov 16;37(7):110015. DOI: 10.1016/j.celrep.2021.110015
dc.identifier.issn 2211-1247
dc.identifier.uri http://hdl.handle.net/10230/52651
dc.description.abstract Previous large-scale studies have uncovered many features that determine the processing of microRNA (miRNA) precursors; however, they have been conducted in vitro. Here, we introduce MapToCleave, a method to simultaneously profile processing of thousands of distinct RNA structures in living cells. We find that miRNA precursors with a stable lower basal stem are more efficiently processed and also have higher expression in vivo in tissues from 20 animal species. We systematically compare the importance of known and novel sequence and structural features and test biogenesis of miRNA precursors from 10 animal and plant species in human cells. Lastly, we provide evidence that the GHG motif better predicts processing when defined as a structure rather than sequence motif, consistent with recent cryogenic electron microscopy (cryo-EM) studies. In summary, we apply a screening assay in living cells to reveal the importance of lower basal stem stability for miRNA processing and in vivo expression.
dc.description.sponsorship This work was supported by the following sources: ERC starting grant 758397, “miRCell”; Swedish Research Council (VR) grant 2015-04611, “MapToCleave”; and funding from the Strategic Research Area (SFO) program of the Swedish Research Council through Stockholm University. R.J. is supported by Science Foundation Ireland through Future Research Leaders award 18/FRL/6194. C.A. was supported by the Ministerio de Economía y Competitividad and FEDER funds under reference numbers BIO2011-26205 and BIO2015-70777-P and Secretaria d’Universitats i Investigació del Departament d’Economia i Coneixement de la Generalitat de Catalunya under award number 2014 SGR 1319. A.J.H. was funded as a Marie Curie Post-doctoral Fellow supported by the European Commission 7th Framework Program under grant agreement no. 330133. The computations were enabled by resources in a project (SNIC 2017/7-297) provided by the Swedish National Infrastructure for Computing (SNIC) at UPPMAX, partially funded by the Swedish Research Council through grant agreement no. 2018-05973
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.rights © 2021. Wenjing Kang et al. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject.other RNA
dc.subject.other Vida -- Origen
dc.subject.other Genètica
dc.title MapToCleave: High-throughput profiling of microRNA biogenesis in living cells
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1016/j.celrep.2021.110015
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/330133
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/758397
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/26205
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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