Identification of mobile genetic elements with geNomad

Abstract

Identifying and characterizing mobile genetic elements in sequencing data is essential for understanding their diversity, ecology, biotechnological applications and impact on public health. Here we introduce geNomad, a classification and annotation framework that combines information from gene content and a deep neural network to identify sequences of plasmids and viruses. geNomad uses a dataset of more than 200,000 marker protein profiles to provide functional gene annotation and taxonomic assignment of viral genomes. Using a conditional random field model, geNomad also detects proviruses integrated into host genomes with high precision. In benchmarks, geNomad achieved high classification performance for diverse plasmids and viruses (Matthews correlation coefficient of 77.8% and 95.3%, respectively), substantially outperforming other tools. Leveraging geNomad’s speed and scalability, we processed over 2.7 trillion base pairs of sequencing data, leading to the discovery of millions of viruses and plasmids that are available through the IMG/VR and IMG/PR databases. geNomad is available at https://portal.nersc.gov/genomad.

Temporal Dynamics and Contribution of Phage Community to the Prevalence of Antibiotic Resistance Genes in a Full-Scale Sludge Anaerobic Digestion Plant

“…Following the latest database of International Committee on Taxonomy of Viruses, geNomad (v1.7.3) was used to determine the taxa of vOTUs . Two approaches, clustered regularly interspaced short palindromic repeats (CRISPR) and tRNA linkage, were used to identify the putative hosts of phages. ,, The CRISPR approach was based on the CRISPR-Cas system recording the genomic fragment of infecting phages, and the tRNA approach was based on the hypothesis that viral tRNA genes originate from their hosts .…”

“…Open reading frames (ORFs) on vOTUs were predicted with Prodigal (v2.6.3) and aligned against the SARG database (v2.0) using BLASTp for ARG detection with a threshold of e ≤ 1 × 10 –5 , query coverage ≥80, and identity ≥40%. ,, Considering the rare occurrence of ARGs on viral genomes, the ARG carrying phage contigs were further verified by geNomad, a highly sensitive classifying tool for virus and plasmid discrimination, to exclude the misjudgment of phage genomes . To detect the horizontal transfer of ARGs, ARGs in virome were aligned with prokaryotic contigs using BLASTn with a threshold of 100% identity and 90% query coverage …”

“…28,47,48 Considering the rare occurrence of ARGs on viral genomes, the ARG carrying phage contigs were further verified by geNomad, a highly sensitive classifying tool for virus and plasmid discrimination, to exclude the misjudgment of phage genomes. 44 To detect the horizontal transfer of ARGs, ARGs in virome were aligned with prokaryotic contigs using BLASTn with a threshold of 100% identity and 90% query coverage. 49 2.7.…”

Viral communities in millipede guts: Insights into the diversity and potential role in modulating the microbiome

“…Following recent advances in the discovery of viruses with small genome sizes (see Discussion), the minimum contig length was set to 1 kb. To reduce the impact of false positives, identified viral contigs were further confirmed and classified using geNomad v1.5.0 (Camargo et al, 2023). The identified viruses are assigned to taxonomic lineages according to the International Committee on Taxonomy of Viruses (ICTV) (Lefkowitz et al, 2018).…”

“…The lifestyles (virulent or lysogenic) of the identified viral genomes were predicted using the Phage TYPe prediction tool (PhaTYP) with default settings (Shang et al, 2023). Host prediction was done using the integrated Phage Host Prediction (iPHoP) tool with default settings, as described by Roux et al (2023). The host database was based on MAGs and the iPHoP database composed of the GTDB release 202 (47,894 genomes), Public IMG genomes not already in GTDB, as of 7 July 2021 (21,372 genomes), and from the GEM dataset (https://portal.nersc.gov/GEM/, 52,515 genomes).…”