4.8 Article

Genome sequence-independent identification of RNA editing sites

Journal

NATURE METHODS
Volume 12, Issue 4, Pages 347-U106

Publisher

NATURE PORTFOLIO
DOI: 10.1038/NMETH.3314

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Funding

  1. US National Institutes of Health [R01HG006264, U01HG007013]
  2. US National Science Foundation [1262134]
  3. Direct For Biological Sciences [1262134] Funding Source: National Science Foundation
  4. Div Of Biological Infrastructure [1262134] Funding Source: National Science Foundation

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RNA editing generates post-transcriptional sequence changes that can be deduced from RNA-seq data, but detection typically requires matched genomic sequence or multiple related expression data sets. We developed the GIREMI tool (genome-independent identification of RNA editing by mutual information; https://www.ibp.ucla.edu/research/xiao/GIREMI.html) to predict adenosine-to-inosine editing accurately and sensitively from a single RNA-seq data set of modest sequencing depth. Using GIREMI on existing data, we observed tissue-specific and evolutionary patterns in editing sites in the human population.

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