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TRIPBASE: a database for identifying the human genomic DNA and lncRNA triplexes.

Tzu-Chieh Lin1, Yen-Ling Liu1, Yu-Ting Liu1

  • 1Institute of Information Science, Academia Sinica, Taipei, 11529, Taiwan.

NAR Genomics and Bioinformatics
|May 24, 2023
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Summary

Long non-coding RNAs (lncRNAs) can bind DNA to form triplexes. This study introduces TRIPBASE, a database and filtering method to accurately predict these crucial lncRNA-DNA interactions, reducing false positives.

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Area of Science:

  • Genomics
  • RNA Biology
  • Bioinformatics

Background:

  • Long non-coding RNAs (lncRNAs) are key regulators in biological processes.
  • lncRNAs can form RNA-DNA:DNA triplexes with genomic DNA.
  • Existing computational methods for triplex prediction have high false-positive rates.

Purpose of the Study:

  • To improve the accuracy of computational prediction for lncRNA-DNA triplexes.
  • To develop a comprehensive database of human lncRNA-genome triplex interactions.
  • To provide a user-friendly tool for exploring these interactions.

Main Methods:

  • Collected experimental data on genomic RNA-DNA triplexes from ASO-mediated capture assays.
  • Analyzed data using Triplexator to identify true triplex binding potential.
  • Developed six computational attributes as filters to reduce false positives in predictions.

Main Results:

  • Identified key computational attributes for accurate triplex prediction.
  • Successfully reduced the false-positive rate of in-silico triplex predictions.
  • Created TRIPBASE, the first genome-wide database of human lncRNA-DNA triplex predictions.

Conclusions:

  • The proposed filters significantly enhance the accuracy of lncRNA-DNA triplex prediction.
  • TRIPBASE provides a valuable resource for researchers studying lncRNA functions.
  • TRIPBASE enables customized exploration of lncRNA-DNA interactions in human cis-regulatory regions.