Abstract

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.

Keywords

pestivirus; classification; phylogeny; evolution; pcr; statistical methods

Published in

Acta Universitatis Agriculturae Sueciae
2009, number: 2009:8
ISBN: 9789186195557
Publisher: Dept. of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences

SLU Authors

• Liu, Lihong

  • Department of Animal Biosciences, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Pathobiology


Permanent link to this page (URI)

https://res.slu.se/id/publ/24992