Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model


Autoria(s): Yu, Zu-Guo; Chu, Ka-Hou; Li, Chi Pang; Anh, Vo; Zhou, Li-Qian; Wang, Roger
Data(s)

2010

Resumo

Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.

Identificador

http://eprints.qut.edu.au/42959/

Publicador

BioMed Central Ltd.

Relação

DOI:10.1186/1471-2148-10-192

Yu, Zu-Guo, Chu, Ka-Hou, Li, Chi Pang, Anh, Vo, Zhou, Li-Qian, & Wang, Roger (2010) Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model. BMC Evolutionary Biology, 10(192), pp. 1-11.

Fonte

Faculty of Science and Technology; Mathematical Sciences

Palavras-Chave #060102 Bioinformatics #060300 EVOLUTIONARY BIOLOGY #060400 GENETICS
Tipo

Journal Article