ERVcaller: identifying polymorphic endogenous retrovirus and other transposable element insertions using whole-genome...

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Endogenous retroviruses (ERVs) comprise approximately 8% of the human genome.
• ERVs are increasingly implicated in various human diseases.
• Accurate detection of polymorphic ERVs from whole-genome sequencing (WGS) data remains a significant challenge.

Purpose of the Study:

• To develop and evaluate ERVcaller, a novel computational tool for detecting and genotyping transposable element (TE) insertions, including ERVs, in the human genome.
• To assess the performance of ERVcaller against existing tools using simulated and real-world WGS datasets.

Main Methods:

• Development of the ERVcaller software for TE insertion detection and genotyping.
• Evaluation using simulated WGS data with known TE insertion sites.
• Benchmarking against existing tools using WGS data from the 1000 Genomes Project.

Main Results:

• ERVcaller demonstrated superior sensitivity and precision in detecting simulated ERV and TE insertions compared to existing methods.
• Analysis of 1000 Genomes Project data revealed that ERVcaller identified the highest number of TE insertions per sample.
• Experimental validation confirmed high detection sensitivity (94.0%) and genotyping accuracy (96.6%) for ERVcaller.

Conclusions:

• ERVcaller is a highly sensitive and precise tool for detecting and genotyping TE insertions from WGS data.
• The tool has broad applicability across species and can advance research into the role of ERVs in human health and disease.