RiboTag: Ribosomal Tagging Strategy to Analyze Cell‐Type‐Specific mRNA Expression In Vivo
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- Elisenda Sanz
- Department of Cell Biology, Physiology, and Immunology and Neuroscience Institute Autonomous University of Barcelona Barcelona Spain
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- Jonathan C. Bean
- Department of Pharmacology University of Washington Seattle Washington
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- Daniel P. Carey
- Department of Pharmacology University of Washington Seattle Washington
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- Albert Quintana
- Department of Cell Biology, Physiology, and Immunology and Neuroscience Institute Autonomous University of Barcelona Barcelona Spain
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- G. Stanley McKnight
- Department of Pharmacology University of Washington Seattle Washington
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<jats:title>Abstract</jats:title><jats:p>Ribosome tagging has become a very useful <jats:italic>in vivo</jats:italic> 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 a hemagglutinin A (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 <jats:italic>Rpl22</jats:italic> (<jats:italic>Rpl22‐HA</jats:italic>) that is induced by the action of Cre recombinase. The <jats:italic>Rpl22‐HA</jats:italic> gene can also be introduced into the animal by stereotaxic injection 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. © 2019 by John Wiley & Sons, Inc.</jats:p>
収録刊行物
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- Current Protocols in Neuroscience
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Current Protocols in Neuroscience 88 (1), e77-, 2019-06
Wiley
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詳細情報 詳細情報について
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- CRID
- 1360302867617582720
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- DOI
- 10.1002/cpns.77
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- ISSN
- 19348576
- 19348584
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- データソース種別
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- Crossref