ViQUF: De Novo Viral Quasispecies Reconstruction Using Unitig-Based Flow Networks

Haplotype determination of the Bombyx mori nucleopolyhedrovirus by Nanopore sequencing and linkage of single nucleotide variants

Naturally occurring isolates of baculoviruses, such as the Bombyx mori nucleopolyhedrovirus (BmNPV), usually consist of numerous genetically different haplotypes. Deciphering the different haplotypes of such isolates is hampered by the large size of the dsDNA genome, as well as the short read length of next generation sequencing (NGS) techniques that are widely applied for baculovirus isolate characterization. In this study, we addressed this challenge by combining the accuracy of NGS to determine single nucleotide variants (SNVs) as genetic markers with the long read length of Nanopore sequencing technique. This hybrid approach allowed the comprehensive analysis of genetically homogeneous and heterogeneous isolates of BmNPV. Specifically, this allowed the identification of two putative major haplotypes in the heterogeneous isolate BmNPV-Ja by SNV position linkage. SNV positions, which were determined based on NGS data, were linked by the long Nanopore reads in a Position Weight Matrix. Using a modified Expectation-Maximization algorithm, the Nanopore reads were assigned according to the occurrence of variable SNV positions by machine learning. The cohorts of reads were de novo assembled, which led to the identification of BmNPV haplotypes. The method demonstrated the strength of the combined approach of short- and long-read sequencing techniques to decipher the genetic diversity of baculovirus isolates.

Phables: from fragmented assemblies to high-quality bacteriophage genomes

MOTIVATION

Microbial communities have a profound impact on both human health and various environments. Viruses infecting bacteria, known as bacteriophages or phages, play a key role in modulating bacterial communities within environments. High-quality phage genome sequences are essential for advancing our understanding of phage biology, enabling comparative genomics studies and developing phage-based diagnostic tools. Most available viral identification tools consider individual sequences to determine whether they are of viral origin. As a result of challenges in viral assembly, fragmentation of genomes can occur, and existing tools may recover incomplete genome fragments. Therefore, the identification and characterization of novel phage genomes remain a challenge, leading to the need of improved approaches for phage genome recovery.

RESULTS

We introduce Phables, a new computational method to resolve phage genomes from fragmented viral metagenome assemblies. Phables identifies phage-like components in the assembly graph, models each component as a flow network, and uses graph algorithms and flow decomposition techniques to identify genomic paths. Experimental results of viral metagenomic samples obtained from different environments show that Phables recovers on average over 49% more high-quality phage genomes compared to existing viral identification tools. Furthermore, Phables can resolve variant phage genomes with over 99% average nucleotide identity, a distinction that existing tools are unable to make.

AVAILABILITY AND IMPLEMENTATION

Phables is available on GitHub at https://github.com/Vini2/phables.

Phables: from fragmented assemblies to high-quality bacteriophage genomes

Microbial communities influence both human health and different environments. Viruses infecting bacteria, known as bacteriophages or phages, play a key role in modulating bacterial communities within environments. High-quality phage genome sequences are essential for advancing our understanding of phage biology, enabling comparative genomics studies, and developing phage-based diagnostic tools. Most available viral identification tools consider individual sequences to determine whether they are of viral origin. As a result of the challenges in viral assembly, fragmentation of genomes can occur, leading to the need for new approaches in viral identification. Therefore, the identification and characterisation of novel phages remain a challenge. We introduce Phables, a new computational method to resolve phage genomes from fragmented viral metagenome assemblies. Phables identifies phage-like components in the assembly graph, models each component as a flow network, and uses graph algorithms and flow decomposition techniques to identify genomic paths. Experimental results of viral metagenomic samples obtained from different environments show that Phables recovers on average over 49% more high-quality phage genomes compared to existing viral identification tools. Furthermore, Phables can resolve variant phage genomes with over 99% average nucleotide identity, a distinction that existing tools are unable to make. Phables is available on GitHub at https://github.com/Vini2/phables.