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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
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.
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.
