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2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications
Published on: July 10, 2020
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A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry
Samuel Wein1,2, Byron Andrews3, Timo Sachsenberg4
1Epigenetics Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Nature Communications
|February 19, 2020
Summary
This study introduces NucleicAcidSearchEngine (NASE), a new open-source tool for analyzing RNA mass spectrometry (MS) data. NASE efficiently identifies modified RNA sequences and modifications, addressing limitations in current epitranscriptomics research.
Area of Science:
- Epitranscriptomics
- Molecular Biology
- Bioinformatics
Background:
- Post-transcriptional RNA modifications are crucial for biological processes.
- Identifying modified RNA residues in sequence context is challenging.
- Current software for RNA mass spectrometry (MS) data analysis is inadequate for high-throughput processing.
Purpose of the Study:
- To develop a high-performance, open-source software solution for analyzing RNA MS data.
- To improve the identification of modified RNA residues and their sequence contexts.
- To enable efficient, high-throughput analysis of complex epitranscriptomic datasets.
Main Methods:
- Development of a free and open-source database search engine named NucleicAcidSearchEngine (NASE).
- Application of NASE to analyze four diverse RNA MS datasets.
- Simultaneous characterization of multiple modification types within RNA sequences.
Main Results:
- NASE reliably identifies a wide range of modified RNA sequences across different datasets.
- Over 20 different modification types were characterized simultaneously in human tRNA.
- Evidence of incomplete RNA modifications was observed in human tRNA.
Conclusions:
- NASE overcomes performance and statistical limitations of existing RNA MS analysis tools.
- The developed engine facilitates comprehensive and efficient epitranscriptomic research.
- NASE enables the discovery of complex modification patterns, such as incomplete modifications in tRNA.
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