CREDO: Highly confident disease-relevant A-to-I RNA-editing discovery in breast cancer

Woochang Hwang1,2, Stefano Calza3,4, Marco Silvestri4,5

  • 1Data Science for Knowledge Creation Research Center, Seoul National University, Seoul, South Korea.

Scientific Reports
|March 27, 2019
PubMed

Insights

Adenosine-to-Inosine (A-to-I) RNA editing is common, but detecting it reliably is challenging. The CREDO pipeline effectively identifies clinically relevant A-to-I RNA editing events using matched DNA and RNA sequencing data, reducing false positives.

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Adenosine-to-Inosine (A-to-I) RNA editing is the most prevalent RNA modification.
  • Previous RNA editing detection methods using next-generation sequencing (NGS) data often yield high false positive rates.
  • Clinical relevance of detected RNA editing events, particularly in disease progression, has been largely overlooked.

Purpose of the Study:

  • To develop an effective RNA-editing discovery pipeline (CREDO) to identify reliable and clinically relevant A-to-I RNA editing events.
  • To reduce false positives in RNA editing detection by integrating DNA and RNA sequencing data.
  • To assess the clinical significance of RNA editing in cancer progression.

Main Methods:

  • Development of the CREDO pipeline incorporating novel statistical filtering modules.
  • Integration of DNA- and RNA-sequencing data from matched tumor-normal tissues.
  • Comparative analysis of CREDO against three existing RNA-editing discovery pipelines.
  • Application of CREDO to breast cancer data from The Cancer Genome Atlas (TCGA).

Main Results:

  • CREDO demonstrated significantly fewer false positives compared to other pipelines.
  • CREDO identified highly confident RNA editing events in breast cancer.
  • Discovered RNA editing events with significant clinical relevance to cancer progression, impacting patient survival.

Conclusions:

  • CREDO is an effective and reliable tool for discovering A-to-I RNA editing.
  • Integrating DNA- and RNA-seq data from matched tissues is crucial for accurate RNA editing detection.
  • Routine RNA editing detection should be considered with the increasing availability of multi-omics data.

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