ArticleMolecular biology and evolution2021
Limited Predictability of Amino Acid Substitutions in Seasonal Influenza Viruses.
Article in Molecular biology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Quantifying the predictability of evolution by analysis of coalescent rate variation.Molecular biology and evolution · 2026Article
- Predicting the antigenic evolution of seasonal influenza viruses using phylogenetic convergence.bioRxiv : the preprint server for biology · 2026Article
- SARS-CoV-2 wastewater genomic surveillance: approaches, challenges, and opportunities.Genome biology · 2026Review
- Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Reproducible and later vaccine strain selection can improve vaccine match to A/H3N2 seasonal influenza viruses.NPJ vaccines · 2025Article
- Exact and efficient phylodynamic simulation from arbitrarily large populations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Inferring effects of mutations on SARS-CoV-2 transmission from genomic surveillance data.Nature communications · 2025Article
- Forecasting framework for dominant SARS-CoV-2 strains before clade replacement using phylogeny-informed genetic distances.Frontiers in microbiology · 2025Article
- Article
- Characterization of Conserved Evolution in H7N9 Avian Influenza Virus Prior Mass Vaccination.Virulence · 2024Article
- Measures of Population Immunity Can Predict the Dominant Clade of Influenza A (H3N2) in the 2017-2018 Season and Reveal Age-Associated Differences in Susceptibility and Antibody-Binding Specificity.Influenza and other respiratory viruses · 2024Article
- Measures of population immunity can predict the dominant clade of influenza A (H3N2) in the 2017-2018 season and reveal age-associated differences in susceptibility and antibody-binding specificity.medRxiv : the preprint server for health sciences · 2024Article
- Transmission restriction and genomic evolution co-shape the genetic diversity patterns of influenza A virus.Virologica Sinica · 2024Article
- Seasonal antigenic prediction of influenza A H3N2 using machine learning.Nature communications · 2024Article
- Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks.Nature communications · 2024Article
- Predictive evolutionary modelling for influenza virus by site-based dynamics of mutations.Nature communications · 2024Article
- Predicting Potential PRRSV-2 Variant Emergence through Phylogenetic Inference.Transboundary and emerging diseases · 2024Article
- Article
- Phylogenetic identification of influenza virus candidates for seasonal vaccines.Science advances · 2023Article
- Genotype-phenotype landscapes for immune-pathogen coevolution.Trends in immunology · 2023Review
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4 authors.
Funding
Abstract
Seasonal influenza viruses repeatedly infect humans in part because they rapidly change their antigenic properties and evade host immune responses, necessitating frequent updates of the vaccine composition. Accurate predictions of strains circulating in the future could therefore improve the vaccine match. Here, we studied the predictability of frequency dynamics and fixation of amino acid substitutions. Current frequency was the strongest predictor of eventual fixation, as expected in neutral evolution. Other properties, such as occurrence in previously characterized epitopes or high Local Branching Index (LBI) had little predictive power. Parallel evolution was found to be moderately predictive of fixation. Although the LBI had little power to predict frequency dynamics, it was still successful at picking strains representative of future populations. The latter is due to a tendency of the LBI to be high for consensus-like sequences that are closer to the future than the average sequence. Simulations of models of adapting populations, in contrast, show clear signals of predictability. This indicates that the evolution of influenza HA and NA, while driven by strong selection pressure to change, is poorly described by common models of directional selection such as traveling fitness waves.
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