ASSA – Transcriptome-Wide Prediction Of lncRNA-RNA Interactions By Thermodynamics

The discovery of thousands of long noncoding RNAs (lncRNAs) in mammals raises a question about their functionality. It has been shown that some of them function post-transcriptionally via formation of inter-molecular duplexes. Sequence alignment tools are frequently used for transcriptome-wide prediction of RNA-RNA interactions. However, such approaches have poor prediction accuracy since they ignore RNA secondary structure and interaction energy. On the other hand, application of the thermodynamics- based algorithms to long transcripts is not computationally feasible on a large scale.

Here researchers at the Research Center of Biotechnology, RAS describe a new computational pipeline ASSA that combines sequence alignment and thermodynamics tools for efficient prediction of RNA-RNA interactions between long transcripts. ASSA outperforms four other tools in terms of the Area Under the Curve. ASSA predictions for the lncRNA HOTAIR confirm that it binds to the chromatin through hybridization with the nascent transcripts. Analysis of the 49 murine lncRNA knockdown experiments reveals one transcript that may regulate its targets via RNA-RNA interactions.

The ASSA pipeline


*The parameters can be adjusted by the ASSA options (the default values are shown on the gure).

Availability – ASSA is available at:

Antonov I, Marakhonov A, Zamkova M, Skoblov M, Medvedeva Y. (2017) Transcriptome-Wide Prediction Of lncRNA-RNA Interactions By A Thermodynamics Algorithm. bioRXiv [Epub ahead of print]. [abstract]

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