RiboTag : Ribosomal tagging strategy to analyze cell type specific mRNA expression in vivo
Sanz Iglesias, Elisenda (Universitat Autònoma de Barcelona. Institut de Neurociències)
Bean, Jonathan C. (University of Washington. Department of Pharmacology)
Carey, Daniel P. (University of Washington. Department of Pharmacology)
Quintana Romero, Albert (Universitat Autònoma de Barcelona. Institut de Neurociències)
McKnight, G. Stanley (University of Washington. Department of Pharmacology)

Fecha:	2019
Resumen:	Ribosome tagging has become a very useful in vivo approach for analyzing gene expression and mRNA translation in specific cell types that are difficult and time consuming to isolate by conventional methods. The approach is based on selectively expressing an HA-tagged ribosomal protein in a target cell type and then using antibodies against HA to purify the polysomes and associated mRNAs from the target cell. The original approach makes use of a mouse line (RiboTag) harboring a modified allele of Rpl22 (Rpl22-HA) that is induced by the action of Cre recombinase. The Rpl22-HA gene can also be introduced into the animal by stereotaxic injections of an AAV-DIO-Rpl22-HA that is then activated in Cre-expressing cells. Both methods for tagging ribosomes facilitate the immunoprecipitation of ribosome bound mRNAs and their analysis by qRT-PCR or RNA-Seq. This protocol will discuss the technical procedures and describe important considerations relevant to the analysis of the data.
Ayudas:	European Commission 658352 European Commission 638106 Ministerio de Economía y Competitividad RyC-2012-11873 Ministerio de Economía y Competitividad SAF2014-57981P Ministerio de Economía y Competitividad SAF2017-88108-R Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-323
Derechos:	Tots els drets reservats.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió sotmesa a revisió
Materia:	Gene expression ; Ribosome tagging ; Neuronal transcripts ; Polyribosome ; Immunoprecipitation
Publicado en:	Current Protocols in Neuroscience, Vol. 88, issue 1 (June 2019) , e77, ISSN 1934-8576

DOI: 10.1002/cpns.77
PMID: 31216392

Preprint 58 p, 970.8 KB

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