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Accurate phylogenetic classification of variable-length DNA fragments

Abstract

Metagenome studies have retrieved vast amounts of sequence data from a variety of environments leading to new discoveries and insights into the uncultured microbial world. Except for very simple communities, the encountered diversity has made fragment assembly and the subsequent analysis a challenging problem. A taxonomic characterization of metagenomic fragments is required for a deeper understanding of shotgun-sequenced microbial communities, but success has mostly been limited to sequences containing phylogenetic marker genes. Here we present PhyloPythia, a composition-based classifier that combines higher-level generic clades from a set of 340 completed genomes with sample-derived population models. Extensive analyses on synthetic and real metagenome data sets showed that PhyloPythia allows the accurate classification of most sequence fragments across all considered taxonomic ranks, even for unknown organisms. The method requires no more than 100 kb of training sequence for the creation of accurate models of sample-specific populations and can assign fragments ≥1 kb with high specificity.

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Figure 1: Accuracy of phylogenetic assignments for differently sized genomic fragments with PhyloPythia.
Figure 2: Phylogenetic classification accuracy of PhyloPythia by clade for differently sized genomic fragments from unknown organisms.
Figure 3: Binning accuracy of Thiothrix sp. contigs using PhyloPythia.

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Acknowledgements

We thank N. Ivanova, V. Kunin and F. Warnecke for help with selection of CAP and Thiothrix-specific training sets and for validation analyses of the metagenomic data-set binning, L. Krause for providing the SEED data, T. Huynh for implementing the web interface, and S. Polonsky for comments and discussion. The work of H.G.M. and P.H. was performed under the auspices of the US Department of Energy's Office of Science, Biological and Environmental Research Program; the University of California, Lawrence Livermore National Laboratory, under contract W-7405-Eng-48; Lawrence Berkeley National Laboratory under contract DE-AC03-76SF00098; and Los Alamos National Laboratory under contract W-7405-ENG-36. PhyloPythia's results were incorporated in the US Department of Energy Joint Genome Institute Integrated Microbial Genomes & Metagenomes (IMG/M) experimental system (http://www.jgi.doe.gov).

Author information

Affiliations

Authors

Contributions

A.C.M. developed and evaluated the method, A.T. contributed codes for pattern discovery and discussion, P.H. and H.G.M. helped with discussions and the evaluation of the results for the EBPR sludges, A.C.M., I.R., H.G.M. and P.H. contributed to the writing of the manuscript, and A.C.M. and I.R. designed and planned the project.

Corresponding author

Correspondence to Isidore Rigoutsos.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

Assignment accuracy for differently sized genomic fragments and coding sequences from unknown organisms at the level of the class.

Supplementary Fig. 2

Wn parameter search for the sequence composition space with the highest classification accuracy for 15 kb fragments of unknown organisms at different phylogenetic levels.

Supplementary Fig. 3

Evaluation of the relation of genomic fragment length used for model creation and classification accuracy for genomic fragments of unknown organisms and different lengths.

Supplementary Fig. 4

Assignments at the domain level with PhyloPythia for 50 kb genomic fragments from unknown organisms.

Supplementary Fig. 5

Comparison of classification accuracy for 3 kb fragments and 3 kb fragments carrying ribosomal proteins with PhyloPythia.

Supplementary Fig. 6

Clades at different depths of the phylogenetic tree that are sufficiently represented by genomes of the 340 organisms for composition-based modeling.

Supplementary Table 1

Wn parameter search for the sequence composition space with the highest classification accuracy.

Supplementary Table 2

Classification accuracy of the SVM with a gaussian versus a linear kernel.

Supplementary Table 3

Classification accuracy of PhyloPythia for genomic fragments of unknown organisms at different taxonomic ranks.

Supplementary Table 4

Phylogenetic classification accuracy of PhyloPythia for genomic fragments of known organisms at different taxonomic ranks.

Supplementary Table 5

Search for the best parameter settings for the SOM and TETRA-method.

Supplementary Table 6

Comparison of PhyloPythia to the SOM-phylotype associations and tetranucleotide-based binning of the dominant sample populations for the contigs ≥1kb of the Sargasso Sea sample.

Supplementary Table 7

Evaluation of PhyloPythia's classification accuracy for genome fragments of different Prochlorococcus strains.

Supplementary Methods

Supplementary Note

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McHardy, A., Martín, H., Tsirigos, A. et al. Accurate phylogenetic classification of variable-length DNA fragments. Nat Methods 4, 63–72 (2007). https://doi.org/10.1038/nmeth976

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