efam: an expanded, metaproteome-supported HMM profile database of viral protein families
| Autor: | Ann C. Gregory, Paul D. Piehowski, Matthew B. Sullivan, Ahmed A. Zayed, Dominik Lücking, Katherine R. Hargreaves, Ben Bolduc, Mohamed Mohssen, Joshua N. Adkins, Richard A. White, Eric L. Huang, Cristina Moraru, Dylan R. Cronin, Simon Roux |
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| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
0303 health sciences Database Viral protein Biology computer.software_genre medicine.disease_cause Biochemistry Computer Science Applications 03 medical and health sciences Computational Mathematics Annotation 0302 clinical medicine Viral sequence Computational Theory and Mathematics Metagenomics medicine Human virome Hidden Markov model Molecular Biology computer 030217 neurology & neurosurgery 030304 developmental biology |
| Zdroj: | BIOINFORMATICS |
| ISSN: | 1367-4811 |
| Popis: | Motivation Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Results Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from ‘conservative’ to ‘eXtremely Conservative’ resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ∼24% on average (up to ∼42%) and especially improved the recovery of often-missed shorter contigs ( Availability and implementation The resources are available on the iVirus platform at (doi.org/10.25739/9vze-4143). Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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