Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Visualizing adenosine to inosine RNA editing in single mammalian cells

View ORCID ProfileIan A. Mellis, View ORCID ProfileRohit K. Gupte, View ORCID ProfileArjun Raj, View ORCID ProfileSara H. Rouhanifard
doi: https://doi.org/10.1101/088146
Ian A. Mellis
1Department of Bioengineering, University of Pennsylvania, Philadelphia PA
2Genomics and Computational Biology Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Ian A. Mellis
Rohit K. Gupte
1Department of Bioengineering, University of Pennsylvania, Philadelphia PA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Rohit K. Gupte
Arjun Raj
1Department of Bioengineering, University of Pennsylvania, Philadelphia PA
2Genomics and Computational Biology Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Arjun Raj
Sara H. Rouhanifard
1Department of Bioengineering, University of Pennsylvania, Philadelphia PA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Sara H. Rouhanifard
  • For correspondence: sara.rouhanifard@gmail.com
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Conversion of adenosine bases to inosine in RNA is a frequent type of RNA editing, but important details about its biology, including subcellular localization, remain unknown due to a lack of imaging tools. We developed an RNA FISH strategy we called inoFISH that enables us to directly visualize and quantify adenosine-to-inosine edited transcripts in situ. Applying this tool to three edited transcripts (GRIA2, EIF2AK2 and NUP43), we found that editing of these transcripts is not correlated with nuclear localization nor paraspeckle association, and that NUP43 exhibits constant editing rates between single cells while the rates for GRIA2 vary.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted November 16, 2016.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Visualizing adenosine to inosine RNA editing in single mammalian cells
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Visualizing adenosine to inosine RNA editing in single mammalian cells
Ian A. Mellis, Rohit K. Gupte, Arjun Raj, Sara H. Rouhanifard
bioRxiv 088146; doi: https://doi.org/10.1101/088146
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Visualizing adenosine to inosine RNA editing in single mammalian cells
Ian A. Mellis, Rohit K. Gupte, Arjun Raj, Sara H. Rouhanifard
bioRxiv 088146; doi: https://doi.org/10.1101/088146

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Molecular Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4229)
  • Biochemistry (9118)
  • Bioengineering (6753)
  • Bioinformatics (23947)
  • Biophysics (12103)
  • Cancer Biology (9498)
  • Cell Biology (13745)
  • Clinical Trials (138)
  • Developmental Biology (7617)
  • Ecology (11664)
  • Epidemiology (2066)
  • Evolutionary Biology (15479)
  • Genetics (10621)
  • Genomics (14297)
  • Immunology (9467)
  • Microbiology (22806)
  • Molecular Biology (9081)
  • Neuroscience (48895)
  • Paleontology (355)
  • Pathology (1479)
  • Pharmacology and Toxicology (2566)
  • Physiology (3826)
  • Plant Biology (8309)
  • Scientific Communication and Education (1467)
  • Synthetic Biology (2294)
  • Systems Biology (6172)
  • Zoology (1297)