ArticleMolecular biology and evolution2011
The genomic rate of molecular adaptation of the human influenza A virus.
Article in Molecular biology and evolution, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 128 papers.
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Who cites it
128 citing papers in PubMed, 189 citations in OpenAlex.
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- K-FluDB: a novel K-mer-based database for enhanced genomic surveillance of Influenza A viruses.Bioinformatics advances · 2026Article
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- Structural analysis of antigenic variation and adaptive evolution of the H5N1 neuraminidase gene.PLoS computational biology · 2026Article
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- Association of poultry vaccination with interspecies transmission and molecular evolution of H5 subtype avian influenza virus.Science advances · 2025Article
- Concepts and Methods for Predicting Viral Evolution.Methods in molecular biology (Clifton, N.J.) · 2025Article
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- Hemagglutinin glycosylation pattern-specific effects: implications for the fitness of H9.4.2.5-branched H9N2 avian influenza viruses.Emerging microbes & infections · 2024Article
- Concepts and methods for predicting viral evolution.bioRxiv : the preprint server for biology · 2024Article
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- Defining the balance between optimal immunity and immunopathology in influenza virus infection.Nature reviews. Immunology · 2024Review
- Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.eLife · 2024Article
- Dimensionality reduction distills complex evolutionary relationships in seasonal influenza and SARS-CoV-2.bioRxiv : the preprint server for biology · 2024Article
- Epistasis mediates the evolution of the receptor binding mode in recent human H3N2 hemagglutinin.Nature communications · 2024Article
68 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Quantifying adaptive evolution at the genomic scale is an essential yet challenging aspect of evolutionary biology. Here, we develop a method that extends and generalizes previous approaches to estimate the rate of genomic adaptation in rapidly evolving populations and apply it to a large data set of complete human influenza A virus genome sequences. In accord with previous studies, we observe particularly high rates of adaptive evolution in domain 1 of the viral hemagglutinin (HA1). However, our novel approach also reveals previously unseen adaptation in other viral genes. Notably, we find that the rate of adaptation (per codon per year) is higher in surface residues of the viral neuraminidase than in HA1, indicating strong antibody-mediated selection on the former. We also observed high rates of adaptive evolution in several nonstructural proteins, which may relate to viral evasion of T-cell and innate immune responses. Furthermore, our analysis provides strong quantitative support for the hypothesis that human H1N1 influenza experiences weaker antigenic selection than H3N2. As well as shedding new light on the dynamics and determinants of positive Darwinian selection in influenza viruses, the approach introduced here is applicable to other pathogens for which densely sampled genome sequences are available, and hence is ideally suited to the interpretation of next-generation genome sequencing data.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.