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Updated: Nov 3, 2025
12:35
Simultaneous Mapping and Quantitation of Ribonucleotides in Human Mitochondrial DNA
Published on: November 14, 2017
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Mapping ribonucleotides embedded in genomic DNA to single-nucleotide resolution using Ribose-Map.
Alli L Gombolay1, Francesca Storici2
1School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA. agombolay3@gatech.edu.
Nature Protocols
|June 5, 2021
Summary
Ribonucleotides are common in genomic DNA, but their distribution is poorly understood. Ribose-Map is a new bioinformatics toolkit that maps ribonucleotide locations and identifies incorporation signatures, standardizing analysis for researchers.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Ribonucleotides are the most common nonstandard nucleotides in genomic DNA.
- Replicative DNA polymerases frequently incorporate ribonucleotides into DNA.
- The distribution and biological signatures of incorporated ribonucleotides remain largely uncharacterized.
Purpose of the Study:
- To introduce Ribose-Map, a user-friendly bioinformatics toolkit for analyzing ribonucleotide sequencing data.
- To enable precise mapping of ribonucleotide locations in genomic DNA at single-nucleotide resolution.
- To identify biological signatures and hotspots of ribonucleotide incorporation.
Main Methods:
- Ribose-Map analyzes high-throughput ribonucleotide sequencing data.
- The toolkit maps ribonucleotide locations to genomic coordinates.
- It explores genome-wide distribution and sequence context of ribonucleotides.
Main Results:
- Ribose-Map standardizes the analysis of ribonucleotide sequencing experiments.
- It facilitates direct comparison of results across different sequencing techniques.
- The toolkit identifies hotspots and biological signatures of ribonucleotide incorporation.
Conclusions:
- Ribose-Map provides a comprehensive and standardized approach to analyzing ribonucleotide incorporation in DNA.
- The toolkit is accessible to researchers with basic command-line skills.
- It requires minimal computing and hands-on time, accelerating research in this area.
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