Cited by 55Evolution and Genetic DynamicsGenomics and Phylogenetic StudiesEvolution and Paleontology Studies

Detecting macroevolutionary genotype–phenotype associations using error-corrected rates of protein convergence

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Fukushima, Kenji, Pollock, David D.·2023·Nature Ecology & Evolution

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Abstract

On macroevolutionary timescales, extensive mutations and phylogenetic uncertainty mask the signals of genotype–phenotype associations underlying convergent evolution. To overcome this problem, we extended the widely used framework of non-synonymous to synonymous substitution rate ratios and developed the novel metric ω C , which measures the error-corrected convergence rate of protein evolution. While ω C distinguishes natural selection from genetic noise and phylogenetic errors in simulation and real examples, its accuracy allows an exploratory genome-wide search of adaptive molecular convergence without phenotypic hypothesis or candidate genes. Using gene expression data, we explored over 20 million branch combinations in vertebrate genes and identified the joint convergence of expression patterns and protein sequences with amino acid substitutions in functionally important sites, providing hypotheses on undiscovered phenotypes. We further extended our method with a heuristic algorithm to detect highly repetitive convergence among computationally non-trivial higher-order phylogenetic combinations. Our approach allows bidirectional searches for genotype–phenotype associations, even in lineages that diverged for hundreds of millions of years.

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Authors
Fukushima, K., & Pollock, D. D.
Affiliations
  • University of Würzburg (DE)
  • Pacific Northwest National Laboratory (US)
Corresponding author
Fukushima, Kenji
Venue
Nature Ecology & Evolution
Published
2023-01-05
Volume
7
Issue
1
Pages
155-170
ISSN
2397-334X (ISSN-L)
OpenAlex
W4313561177
Cited by
55
References
163
Citations by year
2026: 12 · 2025: 17 · 2024: 18 · 2023: 8
FWCI
9.12
Type
journal article
Language
en
Open access
Locations
  • Nature Ecology & Evolution (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by-nc-sa)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion, cc-by-nc-sa)
Funders
  • MEXT | Japan Society for the Promotion of Science (18J00178)
  • Alexander von Humboldt-Stiftung (Sofja Kovalevskaja programme 2018)
  • Human Frontier Science Program (RGY0082/2021)
  • U.S. Department of Health & Human Services | National Institutes of Health (GM083127)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
Keywords
genotype-phenotype correlation, convergent evolution, gene expression evolution, phylogenetic uncertainty
MeSH terms
Phenotype, Phylogeny, Genome, Evolution, Molecular, Genetic Association Studies

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