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Eg Phd, Mphil, Dclinpsychol This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following terms and conditions of use: This work is protected by copyright and other intellectual property rights, which are retained by the thesis author, unless otherwise stated. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This thesis cannot be reproduced or quoted extensively from without first obtaining permission in writing from the author. The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the author. When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given. Evolutionary analysis of rapidly evolving RNA viruses Melissa J. Ward Doctor of Philosophy Institute for Evolutionary Biology School of Biological Sciences The University of Edinburgh 2012 Abstract Recent advances in sequencing technology and computing power mean that we are in an unprecedented position to analyse large viral sequence datasets using state-of-the- art methods, with the aim of better understanding pathogen evolution and epidemiology. This thesis concerns the evolutionary analysis of rapidly evolving RNA viruses, with a focus on avian influenza and the use of Bayesian methodologies which account for uncertainty in the evolutionary process. As avian influenza viruses present an epidemiological and economic threat on a global scale, knowledge of how they are circulating and evolving is of substantial public health importance. In the first part of this thesis I consider avian influenza viruses of haemagglutinin (HA) subtype H7 which, along with H5, is the only subtype for which highly pathogenic influenza has been found. I conduct a comprehensive phylogenetic analysis of available H7 HA sequences to reveal global evolutionary relationships, which can help to target influenza surveillance in birds and facilitate the early detection of potential pandemic strains. I provide evidence for the continued distinction between American and Eurasian sequences, and suggest that the most likely route for the introduction of highly pathogenic H5N1 avian influenza to North America would be through the smuggling of caged birds. I proceed to apply novel methods to better understand the evolution of avian influenza. Firstly, I use an extension of stochastic mutational mapping methods to estimate the dN/dS ratio of H7 HA on different neuraminidase (NA) subtype backgrounds. I find dN/dS to be higher on the N2 NA background than on N1, N3 or N7 NA backgrounds, due to differences in selective pressure. Secondly, I investigate reassortment, which generates novel influenza strains and precedes human influenza pandemics. The rate at which reassortment occurs has been difficult to assess, and I take a novel approach to quantifying reassortment across phylogenies using discrete trait mapping methods. I also use discrete trait mapping to investigate inter-subtype recombination in early HIV-1 in Kinshasa, the epicentre of the HIV-1 group M epidemic. In the final section of the thesis, I describe a method whereby epidemiological parameters may be inferred from viral sequence data isolated from different infected individuals in a population. To conclude, I discuss the findings of this thesis in the context of other evolutionary and epidemiological studies, suggest future directions for avian influenza research and highlight scenarios in which the methods described in this thesis might find further application. 1 Acknowledgements This PhD was funded by the BBSRC. I am also grateful to ICHAIR for providing the opportunity for stimulating discussion with influenza researchers across Scotland. I should like to thank my supervisors, Andy Leigh Brown and Sam Lycett, for providing me with the opportunity to undertake a PhD and for their incredible academic and pastoral support over the past few years. They have both put a considerable amount of their time into meetings and discussions which were not only invaluable for the progress of my project, but also in helping me to become so much more confident and independent in my research. Their patience and understanding has really been quite astounding. I am hugely grateful to Jon Bollback for computational assistance at the start of my PhD, as well as for funding a very productive trip to visit his group in Vienna. I also thank Andrew Rambaut and Trevor Bedford for helpful technical discussions, and am indebted to Erik Volz for allowing me to become involved in his work. During my time in Edinburgh I have very much enjoyed discussions with past and present members of the Leigh Brown group: Fraser Lewis, Gareth Hughes, Lucy Weinert, Emma Hodcroft, Manon Ragonnet, Mojca Zelnikar and Lu Lu, as well as the Ashworth Virus Club. I thank Jayna Raghwani, Laura Emery and Sema Nickbakhsh for friendships which have made the PhD process so much more fun. My office mates in Room 102, especially Jess Hedge and Matty Hartfield, have also provided good humour which has eased me through writing up. I am extremely grateful to my friends away from Edinburgh, especially Maddy, Sally, Bex, Lucy, Claire, Lara, Kirsty, Martin and Michael, for the perspective they are always happy to provide. I thank my family for their love, encouragement and belief in me. I must also pay tribute to staff at the Royal Infirmary of Edinburgh, without whom I would not have been able to undertake a PhD, and to Iola Wilson for helping me to keep going once I had started it. Finally, I should like to thank Ed. He has put up with so much, and given so much, without ever tiring or complaining. With him, I feel that anything is possible. 2 Declaration I declare that this thesis is my own composition and that the work described herein is my own, except where explicitly stated below. This work has not been submitted for any degree or professional qualification except as specified. Melissa J. Ward 30 August, 2012 Chapter 4 The mutational mapping program used in this chapter was written by Dr. Jonathan Bollback as an adapted version of his SIMMAP software. Dr. Bollback devised the re-scalings for calculating dN/dS in consultation with me. Chapter 5 The idea of using discrete trait mapping methods for investigating reassortment was put forward by Dr. Samantha Lycett and Professor Andrew Rambaut. Chapter 6 Professor Andrew Rambaut provided advice on the HIV study presented in Chapter 6. Emma Hodcroft provided initial sequence alignments for Chapter 6. Chapter 7 The mathematical results presented in this chapter were first derived by Dr. Erik Volz. I then derived the results from an initial outline of the results and reasoning, added detail and recommended amendments where necessary, and wrote explanatory material to help produce a manuscript of publication quality. This work was subsequently published as Volz et al. (2009) and also formed the basis of Volz et al. (2012). Dr. Trevor Bedford, Dr. Erik Volz and Nuno Faria were involved in discussions about the application of the method to HIV-1 group M in West Central Africa. 3 Contents 1 Introduction to avian influenza ...................................................................... 11 1.1 Background to influenza ............................................................................. 12 1.2 Structure and function of influenza viruses ................................................. 13 1.3 Influenza virus nomenclature ...................................................................... 17 1.4 Birds as the natural hosts of the influenza A virus ...................................... 18 1.5 Influenza in poultry ..................................................................................... 20 1.6 Highly pathogenic avian influenza (HPAI) ................................................. 21 1.7 Influenza viruses in non-avian species ........................................................ 26 1.8 Virulence of HPAI in mammals .................................................................. 28 1.9 Transmission of influenza viruses between host species ............................ 31 1.10 Evolution of avian influenza viruses ........................................................... 32 1.11 Aims of study .............................................................................................. 35 2 Methods for analysing viral evolution ............................................................ 37 2.1. Statistical frameworks ................................................................................. 38 2.1.1 Maximum likelihood ............................................................................ 38 2.1.2 Bayesian inference ............................................................................... 39 2.1.3 The parsimony criterion ....................................................................... 40 2.2 Model selection ........................................................................................... 41 2.2.1 Likelihood ratio tests ............................................................................ 41 2.2.2 Bayes factor tests.................................................................................. 42 2.2.3 Akaike information criterion (AIC) ..................................................... 43 2.2.4 Bayesian information criterion (BIC) .................................................. 43
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