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Related Experiment Video

Updated: Jun 17, 2025

Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes

Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes

Published on: July 27, 2018

SegVir: Reconstruction of Complete Segmented RNA Viral Genomes from Metatranscriptomes.

Xubo Tang¹, Jiayu Shang², Guowei Chen¹

¹Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong (SAR), China.

Molecular Biology and Evolution

|August 13, 2024

Summary

This study introduces SegVir, a new tool for identifying and reconstructing segmented RNA viruses from metat જomice data. SegVir improves viral genome analysis by accurately detecting diverse viral segments and assessing genome completeness.

Keywords:

genome reconstruction metatranscriptomes segmented RNA viruses

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Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes

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Published on: July 27, 2018

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Published on: January 30, 2019

Area of Science:

Virology
Bioinformatics
Genomics

Background:

Segmented RNA viruses possess multisegment genomes, crucial for understanding viral diversity and evolution.
Metatranscriptomics accelerates the discovery of segmented viruses across ecosystems.
Current tools struggle with the high genetic diversity and reconstruction of complete segmented viral genomes.

Purpose of the Study:

To present SegVir, a novel computational tool for identifying and reconstructing complete segmented RNA virus genomes.
To address the limitations of existing tools in handling the complexity of segmented viral genomes.
To enhance the analysis of viral metagenomes by improving the detection and assembly of viral segments.

Main Methods:

SegVir utilizes both close and remote homology searches for accurate detection of conserved and divergent viral segments.
A novel method is introduced to evaluate genome completeness and conservation based on gene content.
The tool was evaluated using simulated and real metatranscriptomic datasets.

Main Results:

SegVir demonstrated superior sensitivity and precision compared to existing tools on simulated datasets.
Experiments with real data revealed previously unidentified virus segments not present in the NCBI database.
The findings highlight SegVir's capability to significantly enhance viral metagenome analysis.

Conclusions:

SegVir is an effective tool for the identification and reconstruction of segmented RNA viruses.
The tool has the potential to expand our knowledge of viral diversity and improve public health surveillance.
SegVir contributes to advancing the field of viral genomics and metagenomic analysis.