ArticleMolecular systems biology2009
Viral adaptation to host: a proteome-based analysis of codon usage and amino acid preferences.
Article in Molecular systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 163 papers.
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Who cites it
163 citing papers in PubMed, 268 citations in OpenAlex.
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- Genomic catalogue of giant viruses reveals expanded diversity and functional potential.Nature microbiology · 2026Article
- Multilayered nucleotide organization reveals purifying selection and host-driven adaptation in CPV and FPV.BMC veterinary research · 2026Article
- tRNA modifications in viral replication.The Journal of biological chemistry · 2026Review
- DNA viruses are constrained to ecological niches and share similar environmental adaptations with hosts.Nature communications · 2026Article
- Essentiality and dynamic expression of the human tRNA pool during viral infection.Molecular systems biology · 2026Article
- Coronaviruses reprogram the tRNA epitranscriptome to favor viral protein expression.Nature communications · 2026Article
- A Unified Framework to Prioritize RNA Virus Cross-Species Transmission Risk Across an Expansive Host Landscape.Viruses · 2026Article
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- Lifestyle shapes genome architecture and codon usage bias inFrontiers in microbiology · 2026Article
- Comparative analysis of codon usage bias revealed natural selection-driven evolution and host adaptation of infectious haematopoietic necrosis virus.Virus evolution · 2026Article
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- RNA editing signatures and codon adaptation reveal potential translational compatibility between Hendra virus and its natural host Pteropus Alecto.Archives of microbiology · 2025Article
- Uncovering position-specific patterns in codon and codon-pair usage in candidate genes associated with blood coagulation diseases.NAR genomics and bioinformatics · 2025Article
- Protein Language Models Expose Viral Immune Mimicry.Viruses · 2025Article
- Codon Usage Pattern of Papillomavirus E6, E7, and L1 Genes Across Hosts.Current microbiology · 2025Article
- Ciprofloxacin-driven purifying selection on viral genomes accelerates soil NProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Genomic sequencing and evolutionary analysis of bovine kobuvirus in Yunnan Province, China.BMC veterinary research · 2025Article
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- Strong evidence for the evolution of decreasing compositional heterogeneity in SARS-CoV-2 genomes during the pandemic.Scientific reports · 2025Article
103 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Viruses differ markedly in their specificity toward host organisms. Here, we test the level of general sequence adaptation that viruses display toward their hosts. We compiled a representative data set of viruses that infect hosts ranging from bacteria to humans. We consider their respective amino acid and codon usages and compare them among the viruses and their hosts. We show that bacteria-infecting viruses are strongly adapted to their specific hosts, but that they differ from other unrelated bacterial hosts. Viruses that infect humans, but not those that infect other mammals or aves, show a strong resemblance to most mammalian and avian hosts, in terms of both amino acid and codon preferences. In groups of viruses that infect humans or other mammals, the highest observed level of adaptation of viral proteins to host codon usages is for those proteins that appear abundantly in the virion. In contrast, proteins that are known to participate in host-specific recognition do not necessarily adapt to their respective hosts. The implication for the potential of viral infectivity is discussed.
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Registered trials
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.