ArticleMolecular biology and evolution2015
Nonadaptive Amino Acid Convergence Rates Decrease over Time.
Article in Molecular biology and evolution, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
- Adaptive molecular convergence is pervasive across deep time and largely decoupled from phenotypic convergence.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The genetic foundations of convergent traits.Nature reviews. Genetics · 2026Review
- Phenotypic complexity determines the predictability of molecular convergence.bioRxiv : the preprint server for biology · 2026Article
- Assessing the Potential of Ancient Protein Sequences in the Study of Hominid Evolution.Genome biology and evolution · 2026Article
- Insights into Convergent Evolution From Studying Amino Acid Patterns in Independent Lineages of Birds.Genome biology and evolution · 2025Article
- Detecting Convergence of Amino Acid Physicochemical Properties Underlying the Organismal Adaptive Convergent Evolution.Molecular ecology resources · 2025Article
- Estimating the proportion of beneficial mutations that are not adaptive in mammals.PLoS genetics · 2024Article
- Article
- Accurate Detection of Convergent Mutations in Large Protein Alignments With ConDor.Genome biology and evolution · 2024Article
- Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Molecular mechanisms of adaptive evolution in wild animals and plants.Science China. Life sciences · 2023Review
- Detecting macroevolutionary genotype-phenotype associations using error-corrected rates of protein convergence.Nature ecology & evolution · 2023Article
- RETRACTED: Constraints on the evolution of toxin-resistant Na,K-ATPases have limited dependence on sequence divergence.PLoS genetics · 2022Article
- Evolution of Amino Acid Propensities under Stability-Mediated Epistasis.Molecular biology and evolution · 2022Article
- Phylogenetic inference of changes in amino acid propensities with single-position resolution.PLoS computational biology · 2022Article
- Positive selection in noncoding genomic regions of vocal learning birds is associated with genes implicated in vocal learning and speech functions in humans.Genome research · 2021Article
- Shifts in amino acid preferences as proteins evolve: A synthesis of experimental and theoretical work.Protein science : a publication of the Protein Society · 2021Review
- Genomic basis of parallel adaptation varies with divergence inProceedings of the National Academy of Sciences of the United States of America · 2021Article
- Genomic Convergence in the Adaptation to Extreme Environments.Plant communications · 2020Review
- Senescence and entrenchment in evolution of amino acid sites.Nature communications · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Convergence is a central concept in evolutionary studies because it provides strong evidence for adaptation. It also provides information about the nature of the fitness landscape and the repeatability of evolution, and can mislead phylogenetic inference. To understand the role of adaptive convergence, we need to understand the patterns of nonadaptive convergence. Here, we consider the relationship between nonadaptive convergence and divergence in mitochondrial and model proteins. Surprisingly, nonadaptive convergence is much more common than expected in closely related organisms, falling off as organisms diverge. The extent of the convergent drop-off in mitochondrial proteins is well predicted by epistatic or coevolutionary effects in our "evolutionary Stokes shift" models and poorly predicted by conventional evolutionary models. Convergence probabilities decrease dramatically if the ancestral amino acids of branches being compared have diverged, but also drop slowly over evolutionary time even if the ancestral amino acids have not substituted. Convergence probabilities drop-off rapidly for quickly evolving sites, but much more slowly for slowly evolving sites. Furthermore, once sites have diverged their convergence probabilities are extremely low and indistinguishable from convergence levels at randomized sites. These results indicate that we cannot assume that excessive convergence early on is necessarily adaptive. This new understanding should help us to better discriminate adaptive from nonadaptive convergence and develop more relevant evolutionary models with improved validity for phylogenetic inference.
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