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Evaluation of a concatenated protein phylogeny for classification of tailed double-stranded DNA viruses belonging to the order Caudovirales

Abstract

Viruses of bacteria and archaea are important players in global carbon cycling as well as drivers of host evolution, yet the taxonomic classification of viruses remains a challenge due to their genetic diversity and absence of universally conserved genes. Traditional classification approaches employ a combination of phenotypic and genetic information which is no longer scalable in the era of bulk viral genome recovery through metagenomics. Here, we evaluate a phylogenetic approach for the classification of tailed double-stranded DNA viruses from the order Caudovirales by inferring a phylogeny from the concatenation of 77 single-copy protein markers using a maximum-likelihood method. Our approach is largely consistent with the International Committee on Taxonomy of Viruses, with 72 and 89% congruence at the subfamily and genus levels, respectively. Discrepancies could be attributed to misclassifications and a small number of highly mosaic genera confounding the phylogenetic signal. We also show that confidently resolved nodes in the concatenated protein tree are highly reproducible across different software and models, and conclude that the approach can serve as a framework for a rank-normalized taxonomy of most tailed double-stranded DNA viruses.

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Data availability

The genome accessions and Newick tree files of datasets used in this study are provided in the Supplementary Materials.

Code availability

The custom Bash, Python and R scripts used to process and analyse the data and generate the figures are available on request.

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Acknowledgements

We thank D. Waite from the University of Auckland for assistance with the tree inferences using IQ-TREE and ExaML. The project was supported by an Australian Research Council Laureate Fellowship (FL150100038) awarded to P.H.

Author information

S.J.L., M.D. and P.H. designed the study. S.J.L., P.-A.C. and D.H.P. performed the bioinformatic analyses. S.J.L. and P.H. wrote the manuscript. All authors edited drafts of the manuscript.

Competing interests

The authors declare no competing interests.

Correspondence to Philip Hugenholtz.

Supplementary information

Supplementary Information

Legends for Supplementary Datasets, Supplementary Tables 1 and 2, and Supplementary Figures 1–8.

Reporting Summary

Supplementary Dataset 1

This Excel file contains the lists of genome accessions in the datasets used for comparative analyses, along with marker composition and associated metadata.

Supplementary Dataset 2

This file contains the Newick tree of the reference CCP77 dataset.

Supplementary Dataset 3

This file contains the Newick tree of the CCP77-881 dataset (comparison with ICTV).

Supplementary Dataset 4

This file contains the Newick tree of the CCP77-408 dataset (comparison with VICTOR).

Supplementary Dataset 5

This file contains the Newick tree of the CCP77-1520 dataset (comparison withvConTACT).

Supplementary Dataset 6

This file contains the Newick tree of the CCP77-ViPTree dataset (comparison with ViPTree).

Supplementary Dataset 7

This file contains the Newick tree of the CCP77-GRAViTy dataset (comparison with GRAViTy).

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Fig. 1: Midpoint-rooted phylogeny of 1,803 RefSeq bacterial and archaeal viruses inferred from concatenation of 77 marker proteins using IQ-TREE.
Fig. 2: Genome datasets used in phylogenetic analyses, and dendrogram illustrating the similarity of trees inferred from the genome datasets.
Fig. 3: Congruence of CCP77 topologies with ICTV and VICTOR family, subfamily and genus classification.
Fig. 4: Congruence of CCP77-1520 topology with vConTACT genus-level classification.
Fig. 5: Comparison of the CCP77 phylogeny with GRAViTy and ViPTree via the ICTV taxonomy.