a bayesian approach to analyse genetic variation within rna viral populations贝叶斯方法分析rna病毒种群内的遗传变异.pdf

A Bayesian Approach to Analyse Genetic Variation within RNA Viral Populations 1 1 2 3 1 Trevelyan J. McKinley *, Pablo R. Murcia , Julia R. Gog , Mariana Varela , James L. N. Wood 1 Cambridge Infectious Diseases Consortium, Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom, 2 Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom, 3 Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom Abstract The development of modern and affordable sequencing technologies has allowed the study of viral populations to an unprecedented depth. This is of particular interest for the study of within-host RNA viral populations, where variation due to error-prone polymerases can lead to immune escape, antiviral resistance and adaptation to new host species. Methods to sequence RNA virus genomes include reverse transcription (RT) and polymerase chain reaction (PCR). RT-PCR is a molecular biology technique widely used to amplify DNA from an RNA template. The method itself relies on the in vitro synthesis of copy DNA from RNA followed by multiple cycles of DNA amplification. However, this method introduces artefactual errors that can act as confounding factors when the sequence data are analysed. Although there are a growing number of published studies exploring the intra- and inter-host evolutionary dynamics of RNA viruses, the complexity of the methods used to generate sequences makes it difficult to produce probabilistic statements about the likely sources of observed sequence variants. This complexity is further compounded as both the depth of sequencing and the length of the genome