detectEVE: Fast, Sensitive and Precise Detection of Endogenous Viral Elements in Genomic Data

Area of Science:

• Genomics
• Virology
• Bioinformatics

Background:

• Endogenous viral elements (EVEs) are viral sequences integrated into host genomes.
• Non-retroviral EVEs (nrEVEs) are challenging to detect due to their diversity.
• Existing tools lack sensitivity and specificity for comprehensive nrEVE identification.

Purpose of the Study:

• To develop and validate detectEVE, a novel tool for accurate nrEVE detection.
• To provide a user-friendly, open-source solution for identifying nrEVEs in genomic assemblies.
• To enhance the study of viral evolution and host-pathogen interactions.

Main Methods:

• Implementation of a confidence scoring system based on protein sequence similarity search results.
• Utilizing bit score distributions and viral characteristic hints for sensitive detection.
• Benchmarking detectEVE against existing methods for accuracy and speed.

Main Results:

• detectEVE demonstrates high accuracy and specificity in identifying nrEVEs.
• The tool is computationally efficient and significantly faster than current approaches.
• detectEVE successfully enhances genome annotations and aids in paleo-virological research.

Conclusions:

• detectEVE offers a significant advancement in the detection of non-retroviral endogenous viral elements.
• The tool's efficiency and accuracy facilitate large-scale studies and improve transcriptomic data interpretation.
• detectEVE addresses critical gaps in host-associated and virus-related research.