Predicting evolution from the shape of genealogical trees

Abstract

Given a sample of genome sequences from an asexual population, can one predict its evolutionary future? Here we demonstrate that the branching patterns of reconstructed genealogical trees contains information about the relative fitness of the sampled sequences and that this information can be used to predict successful strains. Our approach is based on the assumption that evolution proceeds by accumulation of small effect mutations, does not require species specific input and can be applied to any asexual population under persistent selection pressure. We demonstrate its performance using historical data on seasonal influenza A/H3N2 virus. We predict the progenitor lineage of the upcoming influenza season with near optimal performance in 30% of cases and make informative predictions in 16 out of 19 years. Beyond providing a tool for prediction, our ability to make informative predictions implies persistent fitness variation among circulating influenza A/H3N2 viruses.

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• Neutral Evolution of Mutational Robustness
• Genealogies of rapidly adapting populations
• Genetic draft, selective interference, and population genetics of rapid adaptation
• The noisy edge of traveling waves
• Effect of selection on ancestry: an exactly soluble case and its phenomenological generalization
• Front Propagation up a Reaction Rate Gradient

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• Two fitness inference schemes compared using allele frequencies from 1,068,391 sequences sampled in the UK during the COVID-19 pandemic
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• Fierce selection and interference in B-cell repertoire response to chronic HIV-1