![]() There have been recent advances in both identifying and reporting UViGs however, the identification of viruses from metagenomes and their distinction from prophages continues to be challenging (Nooij et al., 2018 Roux et al., 2019 Warwick-Dugdale et al., 2019). UViGs have led to the discovery of megaphages (with genomes >540 kb) from human and animal gut microbiomes (Devoto et al., 2019), provided first insights into their global distribution (Al-Shayeb et al., 2019), and confirmed that environmental cyanophages contribute to global marine photosynthesis rates (Fridman et al., 2017). Viruses are the most abundant biological entities in many ecosystems and can exert proportionately large effects on ecosystem functions (Fuhrman, 1999 Breitbart et al., 2002). MAGs not only represent bacteria and archaea but also include viruses, which are an integral part of most microbial communities (Dutilh et al., 2014 Brum et al., 2015 Paez-Espino et al., 2016 Roux et al., 2019). And indeed, such metagenome-assembled-genomes (MAGs) have provided information leading to the cultivation of organisms of interest (Gutleben et al., 2018 Cross et al., 2019 Imachi et al., 2020), along with the discoveries of new metabolic processes (Daims et al., 2015), novel insights into the ecology and evolution of globally abundant groups (Delmont et al., 2018), and uncovering a wide diversity of novel phylum-level lineages that have restructured the current understanding of the tree of life (Brown et al., 2015 Hug et al., 2016). In addition to this wealth of information, one of the most beneficial outcomes of shotgun metagenomic projects is the ability to assemble high quality, complete or nearly complete, genomes from organisms not yet amenable to cultivation (Tyson et al., 2004 Luo et al., 2012). These data enable the determination of the community composition (who is there) and total community function (what are they capable of doing). In practice, metagenomic data typically represent hundreds to thousands of microorganisms and viruses at different coverage levels depending on the community structure within the sample (richness, evenness, and genome size variation). Shotgun metagenomics is a powerful method that conceptually allows all the genomes from all the organisms and their associated viruses within a sample to be determined given sufficient sequencing depth (Tyson et al., 2004 Venter et al., 2004 Handelsman et al., 2007). This work provides quantitative data to inform a cost–benefit analysis of the decision to supplement shotgun metagenomic projects with long reads towards the goal of recovering genomes from environmentally abundant groups. Of the shared MAGs recovered from each method, the ONT-only approach generated the longest and least fragmented MAGs, while the hybrid approach yielded the most complete. While yielding fewer MAGs, the ONT-only approach generated MAGs with a high probability of containing rRNA genes, 3× higher than either of the other methods. ![]() A similar number of viral genomes were reconstructed using the hybrid and ONT methods, and both recovered nearly fourfold more viral genomes than the Illumina-only approach. ![]() The hybrid approach recovered 2× more mid to high-quality MAGs compared to the Illumina-only approach and 4× more than the ONT-only approach. Assembly and metagenome-assembled genome (MAG) metrics for both microbes and viruses were determined from an Illumina-only assembly, ONT-only assembly, and a hybrid assembly approach. To compare the recovery of genomes from microorganisms and their viruses from groundwater, we generated shotgun metagenomes with Illumina sequencing accompanied by long reads derived from the Oxford Nanopore Technologies (ONT) sequencing platform. Assembling microbial and viral genomes from metagenomes is a powerful and appealing method to understand structure–function relationships in complex environments. ![]()
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