Viral phylogenomics using an alignment-free method: A three-step approach to determine optimal length of k-mer

Zhang, Qian; Jun, Se -Ran; Leuze, Michael; Ussery, David; Nookaew, Intawat

doi:10.1038/srep40712

Title: Viral phylogenomics using an alignment-free method: A three-step approach to determine optimal length of k-mer

Journal Article · Thu Jan 19 00:00:00 EST 2017 · Scientific Reports

DOI:https://doi.org/10.1038/srep40712· OSTI ID:1351783

Zhang, Qian ^[1]; Jun, Se -Ran ^[2]; Leuze, Michael ^[1]; Ussery, David ^[2]; Nookaew, Intawat ^[2]

Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Arkansas for Medical Sciences, Little Rock, AR (United States)

The development of rapid, economical genome sequencing has shed new light on the classification of viruses. As of October 2016, the National Center for Biotechnology Information (NCBI) database contained >2 million viral genome sequences and a reference set of ~4000 viral genome sequences that cover a wide range of known viral families. Whole-genome sequences can be used to improve viral classification and provide insight into the viral tree of life . However, due to the lack of evolutionary conservation amongst diverse viruses, it is not feasible to build a viral tree of life using traditional phylogenetic methods based on conserved proteins. In this study, we used an alignment-free method that uses k-mers as genomic features for a large-scale comparison of complete viral genomes available in RefSeq. To determine the optimal feature length, k (an essential step in constructing a meaningful dendrogram), we designed a comprehensive strategy that combines three approaches: (1) cumulative relative entropy, (2) average number of common features among genomes, and (3) the Shannon diversity index. This strategy was used to determine k for all 3,905 complete viral genomes in RefSeq. Lastly, the resulting dendrogram shows consistency with the viral taxonomy of the ICTV and the Baltimore classification of viruses.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1351783

Journal Information:: Scientific Reports, Vol. 7; ISSN 2045-2322

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 25 works

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