ArticleBriefings in bioinformatics2022
A universal model of RNA.DNA:DNA triplex formation accurately predicts genome-wide RNA-DNA interactions.
Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Antisense Versus Antigene in the Computer-Aided Design of Triplex-Forming Oligonucleotides (TFO): Insights from a Dual-Method Review, Combining Bibliometric and Systematic Review.International journal of molecular sciences · 2025Pooled it
- RNA•DNA:DNA triplex formation byRNA (New York, N.Y.) · 2026Article
- Metamorphosis and lncRNAs: A Close Relationship.Genesis (New York, N.Y. : 2000) · 2026Review
- Non-B DNA structures and their contributions to genetic diversity, aging, and disease.Nucleic acids research · 2026Review
- Decoding RNA triple helices: identification from sequence and secondary structure.Briefings in bioinformatics · 2026Article
- Relevance of DNA tridimensional shape in RNA:DNA:DNA triple helix formation.Computational and structural biotechnology journal · 2026Article
- TripLexicon: prediction and analysis of gene regulatory RNA-DNA interactions.Bioinformatics (Oxford, England) · 2025Article
- 3plex Web: An interactive platform for RNA:DNA triplex prediction and analysis.Computational and structural biotechnology journal · 2025Article
- Computational Methods to Study DNA:DNA:RNA Triplex Formation by lncRNAs.Non-coding RNA · 2023Review
- LINC01137/miR-186-5p/WWOX: a novel axis identified from WWOX-related RNA interactome in bladder cancer.Frontiers in genetics · 2023Article
- 3plex enables deep computational investigation of triplex forming lncRNAs.Computational and structural biotechnology journal · 2023Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 2 countries.
Funding
Abstract
RNA.DNA:DNA triple helix (triplex) formation is a form of RNA-DNA interaction which regulates gene expression but is difficult to study experimentally in vivo. This makes accurate computational prediction of such interactions highly important in the field of RNA research. Current predictive methods use canonical Hoogsteen base pairing rules, which whilst biophysically valid, may not reflect the plastic nature of cell biology. Here, we present the first optimization approach to learn a probabilistic model describing RNA-DNA interactions directly from motifs derived from triplex sequencing data. We find that there are several stable interaction codes, including Hoogsteen base pairing and novel RNA-DNA base pairings, which agree with in vitro measurements. We implemented these findings in TriplexAligner, a program that uses the determined interaction codes to predict triplex binding. TriplexAligner predicts RNA-DNA interactions identified in all-to-all sequencing data more accurately than all previously published tools in human and mouse and also predicts previously studied triplex interactions with known regulatory functions. We further validated a novel triplex interaction using biophysical experiments. Our work is an important step towards better understanding of triplex formation and allows genome-wide analyses of RNA-DNA interactions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.