universal TTSs
universal TTSs identifies DNA regions capable of forming triple helices with diverse RNAs to enable systematic discovery of "universal triplex target sites" relevant to lncRNA-mediated chromatin interactions.
Key Features:
- Identification of Universal TTSs: Identifies DNA sequences that form triple helices with a majority (>90%) of analyzed transcripts, defining "universal TTSs" and reporting their genome-wide rarity (~0.5%) alongside increased frequency in specific regions.
- Statistical Significance Estimation: Estimates significance of predicted RNA–DNA triplex interactions using a novel statistical method with an adjusted p-value threshold of <0.01.
- Enrichment Analysis: Detects enrichment of universal TTSs in purine-rich low complexity regions, indicating specific sequence characteristics associated with triplex formation.
- Genomic Context and Frequency Reporting: Reports differential frequencies of universal TTSs across genomic contexts, including >15% prevalence among MEG3 binding sites and ~40% prevalence in shared Capture-seq peaks.
Scientific Applications:
- Chromatin Structure Analysis: Supports investigation of the role of RNA–DNA triple helices in three-dimensional chromatin organization and long-distance chromosomal contacts.
- Enhancer–Promoter Interactions: Enables exploration of potential contributions of universal TTSs to distal enhancer–promoter interactions involved in gene regulation.
Methodology:
Integrates computational analyses with experimental RNA–DNA interaction data to predict triplex-forming DNA regions and applies a novel statistical significance estimation with an adjusted p-value threshold of <0.01.
Topics
Details
- License:
- GPL-3.0
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R, Python
- Added:
- 8/9/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Antonov I, Medvedeva YA. Purine-rich low complexity regions are potential RNA binding hubs in the human genome. F1000Research. 2019;7:76. doi:10.12688/f1000research.13522.2. PMID:31131080. PMCID:PMC6518440.