Gene-wise Analysis of Viral Genomes: Trends and Variations in GC Content with a Novel Graphical Tool for Gene-specific Calculation

Author: Sumeet Kumar Parida, Samarth Godara, Shbana Begam, Shruti Godara and Shambhavi Yadav

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Abstract

Despite the known significance of GC content in shaping viral genome stability, evolution, and host adaptation, insightful analysis of GC content across viruses’ genes remains underexplored. In this direction, the existing studies primarily focus on isolated viral families or specific host-virus interactions, leaving a gap in understanding the broader patterns and implications of GC content variability across viral genes. To address this gap, the present study introduces GCVirolens, a GUI-based software designed to analyze GC content variations across the genes of virome. It is a standalone, Windows-based bioinformatics tool developed in Python. The study systematically compares gene-specific GC content across various viruses. Twenty viral genomes were selected for analysis, with ten from plant species and ten from animal species. By evaluating the gene-specific GC content of these viral genomes, the research provides novel insights into factors that may influence viral adaptation to different hosts and environmental conditions. The results showed that the genes of animal viruses exhibited a wider range of GC content. In contrast, the genes of plant viruses displayed more consistent GC content. The broader GC content range observed in animal viruses may reflect their need to adapt to more complex and varied host immune systems. In contrast, the narrower GC content range in plant viruses might be tied to plant cells' relatively uniform metabolic conditions. The results contribute to a deeper understanding of virus genome dynamics and provide a foundation for future research on viral adaptation mechanisms, which could inform the development of targeted antiviral strategies

Keywords

GC content, Gene-wise analysis, Host adaptation, Virus genome, Viral adaptation

Conclusion

Viral genome stability, gene expression, and host adaptability are influenced by GC content. Nonetheless, the existing tools need to be more precise for detailed gene-specific analysis across virus types. In this scenario, the proposed software, GCVirolens, offers user-friendly gene-specific GC content analysis for viral genomes. Its unique design focuses on systematic gene-wise analysis, a feature absents in current tools. Additionally, in the second phase of the study, the gene-wise GC content of 20 viral genomes, comprising 10 plant viruses and the other 10 representing animal viruses, was extracted and analyzed. Results from these experiments revealed significant variations in GC content across different viral species and between individual genes within the same genome. The proposed work's implications are substantial in virology. It enables researchers to understand gene-specific GC content, enhancing insights into viral evolution, genome stability, and host adaptation. In the future, authors intend to expand the study to analyze viral cross-species transmission and mutation trends. Comparing GC content across strains or species, and using machine learning to predict viral behaviour, would enhance its impact. In summary, GC Virolens offers a new, precise, and user-friendly method for analyzing viral genomes, filling a crucial gap in virology. It presents a foundation for advanced computational approaches in viral genome analysis, paving the way for future progress in virology research. FUTURE SCOPE GCVirolens can be extended to analyze GC content across a wider range of organisms, including bacteria, plants, and higher eukaryotes, enabling comparative studies across diverse taxa. Future versions could include a web-based or cloud-hosted interface, allowing for broader accessibility and integration with online genomic databases.

References

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How to cite this article

Sumeet Kumar Parida, Samarth Godara, Shbana Begam, Shruti Godara and Shambhavi Yadav (2024). Gene-wise Analysis of Viral Genomes: Trends and Variations in GC Content with a Novel Graphical Tool for Gene-specific Calculation