Effects of Life History and Genome Architecture on ssRNA Virus Evolution and Extinction Open Access

Bhardwaj, Anand (2013)

Permanent URL: https://etd.library.emory.edu/concern/etds/5712m695x?locale=en


Single-stranded RNA viruses have evolved to survive extremely high mutation rates.The ubiquity and effect of ssRNA viral diseases makes an understanding of the theoretical and mechanical underpinnings of rapid viral evolution vital to our ability to control them. In this body of work, we explore some of the ways in which ssRNA viruses can uncouple the rate at which variation is generated (mutation rate) from the rate at which variation is observed (measured rate of molecular evolution).

A combination of replication strategies and genome architecture allow ssRNA viruses to evolve rapidly while avoiding many of the consequences of their error-prone replication process. However, this also means that ssRNA viruses exist at the very periphery of viable parameter space. Our models of viral evolution suggest that this can be exploited as a means of viral control, an idea that is reflected in the relatively new and experimental process of lethal mutagenesis. We also highlight the general need for more molecular data and better estimates of viral replication parameters. Ironically, the latter are rare in the scientific literature because of a lack of awareness of their impact on the rates of ssRNA virus evolution, and not because of any particular difficulty in obtaining them.

Table of Contents

1 On Painting a Better Portrait

2 Demographic Extinction of ssRNA Viruses 2.1 Introduction 2.1.1 Lethal Mutagenesis 2.1.2 Limitations of a Formulation based on the Zero Class 2.2 Methods 2.2.1 Modeling Viral Intracellular Replication 2.2.2 Simulation 2.3 Results 2.3.1 Variation in P(E1) under extinction conditions 2.3.2 Variation in P(E1) with replication parameters 2.3.3 Extinction in a complex fitness landscape 2.4 Discussion 2.4.1 A case for P(E1) 2.4.2 The importance of the intracellular replication process 2.4.3 Implications for lethal mutagenesis in practice 2.5 Conclusions 2.6 Acknowledgments 3 Genome Architechture & Adaptive Evolution 3.1 Introduction 3.1.1 Adaptive evolution in non-recombining asexuals 3.2 Methods 3.2.1 Data 3.3 Results 3.3.1 Variation in k between species 3.3.2 Variation in k by gene 3.4 Discussion 3.4.1 The effect of deleterious mutations on adaptive substitution 3.4.2 Adaptive optima and mutation rates in nature 3.4.3 The effect of deleterious mutations on neutral substitution 3.5 Conclusions 3.6 Acknowledgments 4 The Fallacy of Neutral Optima 4.1 Neutral Optima: A scientically inconsistent theory 4.2 Rebuttal and Discussion 5 Intracellular Dynamics & Adaptive Evolution 5.1 Introduction 5.2 Limitations of Orr's framework 5.3 The Number of New Adaptive Mutations per Generation 5.4 The Probability of Fixation 5.4.1 The Linear case 5.4.2 The Non-linear Case 5.5 A New Formulation for Adaptive Evolution in ssRNA viruses 5.6 Results and Discussion 5.6.1 Probability of Fixation 5.6.2 Rate of Adaptive Evolution 5.7 Conclusions 5.8 Acknowledgements 6 Conclusions: Portrait of a Virus 7 Bibliography, Indices, and Supplements Raw Data List of Equations List of Figures Bibliography

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