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Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions
Krishna Choudhary1, Fei Deng1, Sharon Aviran1
1Department of Biomedical Engineering and Genome Center, University of California at Davis, Davis, CA 95616, USA.
Quantitative Biology (Beijing, China)
|July 19, 2017
Summary
RNA structure profiling experiments generate vast, complex data. This review highlights comparative and integrative analysis methods to interpret this data and advance RNA biology research.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- Structure profiling experiments offer single-nucleotide resolution of RNA structure.
- High-throughput sequencing enables transcriptome-wide RNA structure profiling in living cells.
- These advancements present significant data interpretation and analysis challenges.
Purpose of the Study:
- To review current practices in analyzing RNA structure profiling data.
- To emphasize comparative and integrative analysis approaches.
- To identify emerging questions in the field.
Main Methods:
- Review of existing literature on RNA structure profiling data analysis.
- Emphasis on comparative analysis across transcriptomes.
- Integration of profiling data with structure prediction algorithms.
Main Results:
- Comparative analysis reveals conserved structural patterns in RNA.
- Profiling data integration improves RNA structure prediction accuracy.
- Emerging questions in data analysis are highlighted.
Conclusions:
- Advanced analysis methods are crucial to match experimental progress in RNA structure profiling.
- Methodological development will enhance the utility of profiling technologies.
- Refined analyses will unlock the full potential of RNA structure profiling for biological insights.
Keywords:
RNA secondary structure predictionRNA structure profilingSHAPE-Seqchemical structure probinghigh-throughput sequencingMore Related Videos
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