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Related Concept Videos

RNA Editing02:23

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RNA editing is a post-transcriptional modification where a precursor mRNA (pre-mRNA) nucleotide sequence is changed by base insertion, deletion, or modification. The extent of RNA editing varies from a few hundred bases, in mitochondrial DNA of trypanosomes, to a just single base, in nuclear genes of mammals. Even a single base change in the pre-mRNA can convert a codon for one amino acid into the codon for another amino acid or a stop codon. This type of re-coding can significantly affect the...
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Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
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A Nonsequencing Approach for the Rapid Detection of RNA Editing
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RED: A Java-MySQL Software for Identifying and Visualizing RNA Editing Sites Using Rule-Based and Statistical

Yongmei Sun1, Xing Li1, Di Wu1

  • 1School of Information and Communication Engineering, Beijing University of Posts & Telecommunications, Beijing, P. R. China.

Plos One
|March 2, 2016
PubMed
Summary
This summary is machine-generated.

RNA editing sites detector (RED) software identifies RNA editing sites using integrated filters and a GUI. It aids in distinguishing true sites from artifacts, offering visualization for RNA sequencing data analysis.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • RNA editing alters protein sequences and gene expression, posing challenges in identifying true editing sites.
  • Distinguishing genuine RNA editing from genomic variations and technical artifacts remains difficult.
  • A user-friendly software framework for RNA editing site identification and visualization is needed.

Purpose of the Study:

  • To develop and present RED (RNA Editing sites Detector), a novel software for identifying and visualizing RNA editing sites.
  • To integrate multiple rule-based and statistical filters for accurate RNA editing site detection.
  • To provide a user-friendly, platform-independent tool for analyzing RNA sequencing data.

Main Methods:

  • Developed RED, a Java-based software integrating rule-based and statistical filters.
  • Utilized MySQL database management system for efficient high-throughput data handling.
  • Compared RED's performance against REDItools using experimentally validated C→U RNA editing sites.

Main Results:

  • RED demonstrated sensitivity and specificity of 0.64 and 0.5, respectively, for C→U RNA editing sites.
  • REDItools showed higher sensitivity (0.75) but comparable specificity (0.5).
  • RED provides genome and site-level visualization via a graphical user interface.

Conclusions:

  • RED is a viable, easy-to-use tool for identifying and visualizing RNA editing sites from RNA-seq data.
  • The software can be applied with or without DNA sequencing data.
  • RED is freely available, promoting accessibility for researchers in RNA editing studies.