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Molecular phylogeny, classification, evolution and detection of pestiviruses

Liu, Lihong (2009). Molecular phylogeny, classification, evolution and detection of pestiviruses. Diss. (sammanfattning/summary) Uppsala : Sveriges lantbruksuniv., Acta Universitatis Agriculturae Sueciae, 1652-6880
ISBN 978-91-86195-55-7
[Doctoral thesis]

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The genus Pestivirus comprises four recognised species: Bovine viral diarrhoea virus 1 (BVDV-1), Bovine viral diarrhoea virus 2 (BVDV-2), Border disease virus (BDV), and Classical swine fever virus (CSFV); and a tentative species, Pestivirus of giraffe. Recently, additional pestiviruses have been identified and presumed as novel subgroups/species based on single gene analyses that reveal different relationships among pestiviruses, depending on the genetic regions being analysed and the methods used. This thesis describes the application of a new strategy−analyzing a combined sequence dataset, and use of different methodologies in inferring pestivirus phylogeny, as a basis for both genetic classification and evolutionary studies. The Bayesian approach is demonstrated to be useful for inferring BVDV-1 phylogeny, where best result was obtained from the analysis of a combined sequence dataset. This strategy and method produce a reliable, well-supported phylogeny of BVDV-1. The whole-genome phylogeny of pestiviruses showed a closer phylogenetic relationship between the atypical pestiviruses and the recognised species BVDV-1 and BVDV-2. In order to obtain a unified classification scheme of pestiviruses, Maximum likelihood and Bayesian analyses of a molecular dataset of 56 pestiviruses and 2089 characters were performed, resulting in an identical, reliable tree topology. Dating of the most recent common ancestor was estimated for major pestivirus lineages and their evolutionary histories were revealed. Based on these results, a new proposal is suggested for the genetic classification of pestiviruses into nine species: BVDV-1, BVDV-2, BVDV-3, Pestivirus of giraffe, CSFV, BDV, Tunisian sheep virus, Antelope virus and Bungowannah virus. As powerful tools of molecular diagnostic virology, two real-time PCR assays have been developed for detection of atypical pestiviruses and CSFV by using TaqMan and primer-probe energy transfer (PriProET) technologies, respectively. Both assays are highly sensitive, specific, reproducible, and useful for the improved detection of two pestiviruses.

Authors/Creators:Liu, Lihong
Title:Molecular phylogeny, classification, evolution and detection of pestiviruses
Series Name/Journal:Acta Universitatis Agriculturae Sueciae
Year of publishing :2009
Number of Pages:41
ALLI Xia, H., Liu, L., Wahlberg, N., Baule, C., Belák, S. (2007). Molecular phylogenetic analysis of bovine viral diarrhoea virus: a Bayesian approach. Virus Research 130, 53-62. II Liu, L., Kampa, J., Belák, S., Baule, C. (2009). Virus recovery and full-length sequence analysis of atypical bovine pestivirus Th/04_KhonKaen. Veterinary Microbiology (accepted). III Liu, L., Xia, H., Wahlberg, N., Belák, S., Baule, C. (2009). Phylogeny, classification and evolutionary insights into pestiviruses. Virology 385, 351-357. IV Liu, L., Xia, H., Belák, S., Baule, C. (2008). A TaqMan real-time RT-PCR assay for selective detection of atypical bovine pestiviruses in clinical samples and biological products. Journal of Virological Methods 154, 82-85. V Liu, L., Xia, H., Belák, S., Widén, F. (2009). A novel real-time PCR assay based on primer-probe energy transfer for the improved detection of classical swine fever virus. Journal of Virological Methods (in revision).
Place of Publication:Uppsala
ISBN for printed version:978-91-86195-55-7
Publication Type:Doctoral thesis
Full Text Status:Public
Agrovoc terms:pestvirus, classification, phylogeny, evolution, pcr, statistical method
Keywords:Bayesian, classification, evolution, Maximum likelihood, pestivirus, real-time RT-PCR
Permanent URL:
ID Code:1945
Department:(VH) > Dept. of Biomedical Sciences and Veterinary Public Health
Deposited By: Lihong Liu
Deposited On:27 Feb 2009 00:00
Metadata Last Modified:02 Dec 2014 10:15

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