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EVAtool: an optimized reads assignment tool for small ncRNA quantification and its application in extracellular
Gui-Yan Xie1, Chun-Jie Liu1, An-Yuan Guo1,2
1Center for Artificial Intelligence Biology, Hubei Bioinformatics & Molecular Imaging Key Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology; Wuhan, 430074, China.
Accurately quantifying small non-coding RNAs (sncRNAs) in extracellular vesicles (EVs) is challenging. The new EVAtool uses an optimized reads assignment algorithm (ORAA) to improve sncRNA quantification in EV samples.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- Extracellular vesicles (EVs) mediate cell communication and are implicated in various diseases.
- Accurate quantification of diverse small non-coding RNA (sncRNA) biotypes within EVs is crucial but challenging due to short read lengths and multi-mapping issues.
Purpose of the Study:
- To develop and validate a computational tool for accurate sncRNA quantification in extracellular vesicles.
- To address the challenge of multi-mapping short reads in sncRNA sequencing data from EVs.
Main Methods:
- Development of an optimized reads assignment algorithm (ORAA) to dynamically map multi-mapping reads.
- Integration of ORAA into the EVAtool Python package for sncRNA quantification.
- Application of EVAtool to analyze sncRNA expression profiles in 200 samples from cognitive decline and multiple sclerosis cohorts.
Main Results:
- Over 20% of short reads were mapped to multiple sncRNA biotypes in multiple sclerosis samples.
- A significantly higher proportion of Y RNA was observed in cognitive decline samples compared to other sncRNA types.
- EVAtool demonstrated flexibility in quantifying default or user-specified sncRNA types.
Conclusions:
- EVAtool provides a flexible and extensible solution for accurate sncRNA quantification in extracellular vesicles.
- The tool aids in identifying potential biomarkers and functional molecules within EVs, particularly in disease contexts.
- Accurate sncRNA profiling using EVAtool can reveal disease-specific expression patterns, such as altered Y RNA proportions in cognitive decline.
