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Editorial: Predicting virus evolution: from genome evolution to epidemiological trends

Year: 2023
Type: editorial
Abstract: Predicting virus evolution: from genome evolution to epidemiological trends 1 IntroductionEvolution is central to understanding viruses, given its importance in processes such as viral emergence (1), adaptation to host immunity (2), reversion of virulence in attenuated vaccine strains (3), loss of heterologous sequences in viral expression vectors (4), and development of resistance against antivirals (5).Viruses have proved invaluable for studying evolutionary processes and identifying the underlying mechanisms of evolution, due to their potential for rapid adaptation (6).As well as evolutionaryoriented comparative analyses of clinical and environmental samples, viruses of animals, plants, bacteria, and other organisms can be experimentally evolved in the laboratory under controlled conditions.Over the last decade, evolutionary biologists have devoted great efforts to predicting the outcomes of evolutionary processes and assessing the limits of such predictability (7, 8).However, despite the importance of viruses as model systems in evolutionary biology, there are only limited examples of evolutionary predictions tested on viruses (2, 8, 9).Such a lack of studies is remarkable, given that virus evolution is (i) rapid due to short generation times, large population sizes, and high mutation rates, (ii) repeatable in the clinic and laboratory, which is an important prerequisite for high predictability, and (iii) highly relevant due to its impact on health, livelihoods, and ecosystems (6, 8).Notable predictions of virus evolution, such as of future Influenza A virus (IAV) strains (2), illustrate these various aspects, from the basic feasibility of prediction to its relevance (8).Has evolutionary predictability been neglected in virus research, or are there insurmountable obstacles to making non-trivial predictions?Some problems, such as Frontiers in Virology frontiersin.
Language: English
Subfield: Genetics
Open Access status: gold
Estimated APC paid: $2,125
OpenAlex ID: W4377137372
Cites: 21
Cited by: 8
Related to: 10