Biology subjects

Medvedeva, Y.

Publications and source records attributed to Medvedeva, Y..

2 recordsLinked to original sources

bioRxiv2024

HiMoRNA and RNA-Chrom integration: Chromatin-Associated LncRNAs in Genome-Wide Epigenetic Regulation

Long non-coding RNAs (lncRNAs) significantly contribute to genome structure and regulation. Many lncRNAs are known to interact with chromatin and in this way to affect gene expression patterns through epigenetic regulation. Still, experimental protocols for lncRNA-chromatin interactions do not provide any insight into the mechanisms of lncRNA-based genome-wide regulation. Here we present an integration of HiMoRNA - a resource containing correlated lncRNA-epigenetic changes in specific genomic locations genome-wide, - and RNA-Chrom, a resource featuring uniformly processed experimental data on RNA-chromatin interactions. Our integration approach allows generating interpretable and experimentally supported hypotheses on the mechanisms of lncRNA epigenetic regulation of gene expression. For this integration we have tailored the interface of HiMoRNA such that for many lncRNAs experimentally detected RNA-chromatin contacts are available from RNA-Chrom for browsing, analysis and downloading. HiMoRNA peaks supported by RNA-Chrom contacts can be explained by external experimental data. We believe that the integration of HiMoRNA and RNA-Chrom is a convenient and valuable approach that can provide experimental and mechanistic insights and greatly facilitate functional annotation of lncRNAs.

bioinformatics↗

bioRxiv2017

Transcriptome-Wide Prediction Of lncRNA-RNA Interactions By A Thermodynamics Algorithm

MotivationThe 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.\n\nResultsHere we 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.\n\nAvailabilityASSA is available at http://assa.sourceforge.net/.\n\nContactivan.antonov@gatech.edu

bioinformatics↗