Reconstructing viral quasispecies from NGS amplicon reads

Area of Science:

• Virology
• Bioinformatics
• Genomics

Background:

• Viral quasispecies are complex mixtures of closely related viral genomes.
• Accurate reconstruction of viral populations is crucial for understanding viral evolution and disease dynamics.
• Next-generation sequencing (NGS) technologies provide high-throughput data for viral population analysis.

Purpose of the Study:

• To develop and evaluate novel algorithms for reconstructing viral quasispecies from amplicon sequencing reads.
• To compare the performance of parsimonious and likelihood models in viral quasispecies reconstruction.
• To assess the accuracy of viral quasispecies reconstruction using amplicon versus shotgun sequencing reads.

Main Methods:

• Development of several novel assembling algorithms for viral quasispecies reconstruction.
• Comparison of parsimonious and likelihood models.
• Validation using simulated error-free Hepatitis C virus (HCV) and real Hepatitis B virus (HBV) amplicon reads.
• Performance evaluation against existing methods, such as Prosperi et al.

Main Results:

• The proposed novel algorithms demonstrate superior performance compared to the method by Prosperi et al.
• Viral quasispecies reconstruction is generally more accurate using amplicon reads than shotgun reads.
• Successful reconstruction of viral quasispecies was achieved in most tested cases.

Conclusions:

• Novel algorithms offer improved accuracy for viral quasispecies reconstruction from amplicon NGS data.
• Amplicon sequencing is a viable and often more accurate strategy for viral quasispecies analysis.
• The implemented algorithms are publicly available for broader research application.