Literature DB >> 32130917

iTAG-RNA Isolates Cell-Specific Transcriptional Responses to Environmental Stimuli and Identifies an RNA-Based Endocrine Axis.

Jonatan Darr1, Archana Tomar1, Maximilian Lassi1, Raffaele Gerlini1, Lucia Berti2, Annette Hering3, Fabienne Scheid1, Martin Hrabě de Angelis4, Michael Witting5, Raffaele Teperino6.   

Abstract

Biofluids contain various circulating cell-free RNAs (ccfRNAs). The composition of these ccfRNAs varies among biofluids. They constitute tantalizing biomarker candidates for several pathologies and have been demonstrated to be mediators of cellular communication. Little is known about their function in physiological and developmental settings, and most works are limited to in vitro studies. Here, we develop iTAG-RNA, a method for the unbiased tagging of RNA transcripts in mice in vivo. We use iTAG-RNA to isolate hepatocytes and kidney proximal epithelial cell-specific transcriptional responses to a dietary challenge without interfering with the tissue architecture and to identify multiple hepatocyte-secreted ccfRNAs in plasma. We also identify specific transfer of liver-derived ccfRNAs to adipose tissue and skeletal muscle, where they likely constitute a buffering system to maintain lipid homeostasis under acute high-fat-diet feeding. Our findings directly demonstrate in vivo transfer of RNAs between tissues and highlight its implications for endocrine signaling and homeostasis.
Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  RNA tagging, mouse genetics, circulating RNA, 5EU prodrug, epigenetics, RNA biomarker

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Substances:

Year:  2020        PMID: 32130917     DOI: 10.1016/j.celrep.2020.02.020

Source DB:  PubMed          Journal:  Cell Rep            Impact factor:   9.423


  2 in total

Review 1.  Genetic control of non-genetic inheritance in mammals: state-of-the-art and perspectives.

Authors:  A Tomar; R Teperino
Journal:  Mamm Genome       Date:  2020-06-11       Impact factor: 2.957

2.  TRACE-seq: A transgenic system for unbiased and non-invasive transcriptome profiling of living cells.

Authors:  François Cherbonneau; Guoping Li; Priyanka Gokulnath; Parul Sahu; Aurore Prunevieille; Robert Kitchen; Gilles Benichou; Jérôme Larghero; Ibrahim Domian; Saumya Das
Journal:  iScience       Date:  2022-01-25
  2 in total

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