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RISE: a database of RNA interactome from sequencing experiments
Jing Gong1,2, Di Shao1,2, Kui Xu1,2
1MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing 100084, China.
Nucleic Acids Research
|October 18, 2017
Summary
The RISE database compiles 328,811 RNA-RNA interactions (RRIs), focusing on mRNA and lncRNA, offering insights into RNA regulation. This resource aids researchers in exploring RNA networks and their functions.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- RNA-RNA interactions (RRIs) are crucial for gene regulation and cellular function.
- Existing databases primarily focus on microRNA targeting, leaving other RRIs underrepresented.
Purpose of the Study:
- To introduce RISE, a comprehensive database of RNA-RNA interactions from sequencing experiments.
- To provide a centralized resource for exploring diverse RRIs, including those involving mRNA and long non-coding RNAs.
Main Methods:
- Aggregated RRIs from high-throughput sequencing techniques (PARIS, SPLASH, LIGR-seq, MARIO, RIA-seq, RAP-RNA, CLASH).
- Included interactions from existing databases and publications.
- Analyzed network properties of human and mouse RRI networks.
Main Results:
- RISE contains 328,811 RRIs, predominantly in human, mouse, and yeast.
- Over half of the RRIs involve mRNA and long non-coding RNAs, expanding beyond miRNA interactions.
- Limited overlap between different experimental techniques suggests technique-specific biases and dynamic RRI nature.
- Human and mouse RRI networks exhibit scale-free, small-world, hierarchical, and modular characteristics.
Conclusions:
- RISE serves as a valuable resource for studying diverse RNA-RNA interactions.
- The findings highlight the dynamic and technique-dependent nature of RRIs.
- Network analyses identify key RNAs and interactions for further research and provide functional annotations for exploration.